From 340635feee63e4cfe5be96ba76d07ad578e458f1 Mon Sep 17 00:00:00 2001 From: jaidisido Date: Thu, 25 Feb 2021 15:02:10 +0000 Subject: [PATCH 01/36] Feature: Write to Glue Governed Tables (#560) * Initial Commit * Minor - Refactoring Work Units Logic * Major - Checkpoint w/ functional read code/example * Initial Commit * Minor - Refactoring Work Units Logic * Major - Checkpoint w/ functional read code/example * Minor - Removing unnecessary ensure_session * Minor - Adding changes from comments and review * Minor - Adding Abort, Begin, Commit and Extend transactions * Minor - Adding missing functions * Minor - Adding missing @property * Minor - Disable too many public methods * Minor - Checkpoint * Major - Governed tables write operations tested * Minor - Adding validate flow on branches * Minor - reducing static checks * Minor - Adding to_csv code * Minor - Disabling too-many-branches * Major - Ready for release * Minor - Proofreading * Minor - Removing needless use_threads argument * Minor - Removing the need to specify table_type when table is already created * Minor - Fixing _catalog_id call * Minor - Clarifying SQL filter operation * Minor - Removing type ignore --- CONTRIBUTING.md | 11 + awswrangler/__init__.py | 2 + awswrangler/_config.py | 13 +- awswrangler/_utils.py | 2 + awswrangler/athena/_read.py | 4 +- awswrangler/catalog/_create.py | 20 +- awswrangler/catalog/_definitions.py | 8 +- awswrangler/lakeformation/__init__.py | 20 + awswrangler/lakeformation/_read.py | 355 ++++++++++++++ awswrangler/lakeformation/_utils.py | 264 +++++++++++ awswrangler/s3/_write.py | 4 +- awswrangler/s3/_write_dataset.py | 115 ++++- awswrangler/s3/_write_parquet.py | 86 +++- awswrangler/s3/_write_text.py | 98 +++- cloudformation/base.yaml | 113 ++++- tests/_utils.py | 33 +- tests/conftest.py | 5 + tests/test__routines.py | 174 ++++--- tests/test_lakeformation.py | 150 ++++++ ...029 - Lake Formation Governed Tables.ipynb | 441 ++++++++++++++++++ 20 files changed, 1809 insertions(+), 109 deletions(-) create mode 100644 awswrangler/lakeformation/__init__.py create mode 100644 awswrangler/lakeformation/_read.py create mode 100644 awswrangler/lakeformation/_utils.py create mode 100644 tests/test_lakeformation.py create mode 100644 tutorials/029 - Lake Formation Governed Tables.ipynb diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index efbc1510f..6fb8d522f 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -230,6 +230,17 @@ or ``./cloudformation/delete-databases.sh`` +### Enabling Lake Formation: +If your feature is related to AWS Lake Formation, there are a number of additional steps required in order to complete testing: + +1. In the AWS console, enable Lake Formation by setting your IAM role as an Administrator and by unchecking the boxes in the ``Data Catalog Settings`` section + +2. In the ``./cloudformation/base.yaml`` template file, set ``EnableLakeFormation`` to ``True``. Then run the ``./deploy-base.sh`` once more to add an AWS Glue Database and an S3 bucket registered with Lake Formation + +3. Back in the console, in the ``Data Locations`` section, grant your IAM role access to the S3 Lake Formation bucket (``s3://aws-wrangler-base-lakeformation...``) + +4. Finally, in the ``Data Permissions`` section, grant your IAM role ``Super`` permissions on both the ``aws_data_wrangler`` and ``aws_data_wrangler_lakeformation`` databases + ## Recommended Visual Studio Code Recommended setting ```json diff --git a/awswrangler/__init__.py b/awswrangler/__init__.py index 25785e433..6249471ff 100644 --- a/awswrangler/__init__.py +++ b/awswrangler/__init__.py @@ -15,6 +15,7 @@ dynamodb, emr, exceptions, + lakeformation, mysql, postgresql, quicksight, @@ -40,6 +41,7 @@ "s3", "sts", "redshift", + "lakeformation", "mysql", "postgresql", "secretsmanager", diff --git a/awswrangler/_config.py b/awswrangler/_config.py index 0fedb21fa..989cfc726 100644 --- a/awswrangler/_config.py +++ b/awswrangler/_config.py @@ -42,12 +42,13 @@ class _ConfigArg(NamedTuple): "redshift_endpoint_url": _ConfigArg(dtype=str, nullable=True, enforced=True), "kms_endpoint_url": _ConfigArg(dtype=str, nullable=True, enforced=True), "emr_endpoint_url": _ConfigArg(dtype=str, nullable=True, enforced=True), + "lakeformation_endpoint_url": _ConfigArg(dtype=str, nullable=True, enforced=True), # Botocore config "botocore_config": _ConfigArg(dtype=botocore.config.Config, nullable=True), } -class _Config: # pylint: disable=too-many-instance-attributes +class _Config: # pylint: disable=too-many-instance-attributes,too-many-public-methods """Wrangler's Configuration class.""" def __init__(self) -> None: @@ -60,6 +61,7 @@ def __init__(self) -> None: self.redshift_endpoint_url = None self.kms_endpoint_url = None self.emr_endpoint_url = None + self.lakeformation_endpoint_url = None self.botocore_config = None for name in _CONFIG_ARGS: self._load_config(name=name) @@ -342,6 +344,15 @@ def emr_endpoint_url(self) -> Optional[str]: def emr_endpoint_url(self, value: Optional[str]) -> None: self._set_config_value(key="emr_endpoint_url", value=value) + @property + def lakeformation_endpoint_url(self) -> Optional[str]: + """Property lakeformation_endpoint_url.""" + return cast(Optional[str], self["lakeformation_endpoint_url"]) + + @lakeformation_endpoint_url.setter + def lakeformation_endpoint_url(self, value: Optional[str]) -> None: + self._set_config_value(key="lakeformation_endpoint_url", value=value) + @property def botocore_config(self) -> botocore.config.Config: """Property botocore_config.""" diff --git a/awswrangler/_utils.py b/awswrangler/_utils.py index 3a8242557..7f152e75a 100644 --- a/awswrangler/_utils.py +++ b/awswrangler/_utils.py @@ -87,6 +87,8 @@ def _get_endpoint_url(service_name: str) -> Optional[str]: endpoint_url = _config.config.kms_endpoint_url elif service_name == "emr" and _config.config.emr_endpoint_url is not None: endpoint_url = _config.config.emr_endpoint_url + elif service_name == "lakeformation" and _config.config.lakeformation_endpoint_url is not None: + endpoint_url = _config.config.lakeformation_endpoint_url return endpoint_url diff --git a/awswrangler/athena/_read.py b/awswrangler/athena/_read.py index 770b97f22..bff8121f6 100644 --- a/awswrangler/athena/_read.py +++ b/awswrangler/athena/_read.py @@ -761,8 +761,8 @@ def read_sql_query( >>> import awswrangler as wr >>> df = wr.athena.read_sql_query( - ... sql="SELECT * FROM my_table WHERE name=:name;", - ... params={"name": "filtered_name"} + ... sql="SELECT * FROM my_table WHERE name=:name; AND city=:city;", + ... params={"name": "'filtered_name'", "city": "'filtered_city'"} ... ) """ diff --git a/awswrangler/catalog/_create.py b/awswrangler/catalog/_create.py index 2dcbc6fc7..50f7f82d0 100644 --- a/awswrangler/catalog/_create.py +++ b/awswrangler/catalog/_create.py @@ -33,6 +33,7 @@ def _create_table( # pylint: disable=too-many-branches,too-many-statements catalog_versioning: bool, boto3_session: Optional[boto3.Session], table_input: Dict[str, Any], + table_type: Optional[str], table_exist: bool, projection_enabled: bool, partitions_types: Optional[Dict[str, str]], @@ -118,7 +119,8 @@ def _create_table( # pylint: disable=too-many-branches,too-many-statements f"{mode} is not a valid mode. It must be 'overwrite', 'append' or 'overwrite_partitions'." ) if table_exist is True and mode == "overwrite": - delete_all_partitions(table=table, database=database, catalog_id=catalog_id, boto3_session=session) + if table_type != "GOVERNED": + delete_all_partitions(table=table, database=database, catalog_id=catalog_id, boto3_session=session) _logger.debug("Updating table (%s)...", mode) client_glue.update_table( **_catalog_id( @@ -214,6 +216,7 @@ def _create_parquet_table( table: str, path: str, columns_types: Dict[str, str], + table_type: Optional[str], partitions_types: Optional[Dict[str, str]], bucketing_info: Optional[Tuple[List[str], int]], catalog_id: Optional[str], @@ -253,6 +256,7 @@ def _create_parquet_table( table=table, path=path, columns_types=columns_types, + table_type=table_type, partitions_types=partitions_types, bucketing_info=bucketing_info, compression=compression, @@ -269,6 +273,7 @@ def _create_parquet_table( catalog_versioning=catalog_versioning, boto3_session=boto3_session, table_input=table_input, + table_type=table_type, table_exist=table_exist, partitions_types=partitions_types, projection_enabled=projection_enabled, @@ -284,8 +289,9 @@ def _create_parquet_table( def _create_csv_table( database: str, table: str, - path: str, + path: Optional[str], columns_types: Dict[str, str], + table_type: Optional[str], partitions_types: Optional[Dict[str, str]], bucketing_info: Optional[Tuple[List[str], int]], description: Optional[str], @@ -324,6 +330,7 @@ def _create_csv_table( table=table, path=path, columns_types=columns_types, + table_type=table_type, partitions_types=partitions_types, bucketing_info=bucketing_info, compression=compression, @@ -342,6 +349,7 @@ def _create_csv_table( catalog_versioning=catalog_versioning, boto3_session=boto3_session, table_input=table_input, + table_type=table_type, table_exist=table_exist, partitions_types=partitions_types, projection_enabled=projection_enabled, @@ -519,6 +527,7 @@ def create_parquet_table( table: str, path: str, columns_types: Dict[str, str], + table_type: Optional[str] = None, partitions_types: Optional[Dict[str, str]] = None, bucketing_info: Optional[Tuple[List[str], int]] = None, catalog_id: Optional[str] = None, @@ -550,6 +559,8 @@ def create_parquet_table( Amazon S3 path (e.g. s3://bucket/prefix/). columns_types: Dict[str, str] Dictionary with keys as column names and values as data types (e.g. {'col0': 'bigint', 'col1': 'double'}). + table_type: str, optional + The type of the Glue Table (EXTERNAL_TABLE, GOVERNED...). Set to EXTERNAL_TABLE if None partitions_types: Dict[str, str], optional Dictionary with keys as partition names and values as data types (e.g. {'col2': 'date'}). bucketing_info: Tuple[List[str], int], optional @@ -627,6 +638,7 @@ def create_parquet_table( table=table, path=path, columns_types=columns_types, + table_type=table_type, partitions_types=partitions_types, bucketing_info=bucketing_info, catalog_id=catalog_id, @@ -653,6 +665,7 @@ def create_csv_table( table: str, path: str, columns_types: Dict[str, str], + table_type: Optional[str] = None, partitions_types: Optional[Dict[str, str]] = None, bucketing_info: Optional[Tuple[List[str], int]] = None, compression: Optional[str] = None, @@ -686,6 +699,8 @@ def create_csv_table( Amazon S3 path (e.g. s3://bucket/prefix/). columns_types: Dict[str, str] Dictionary with keys as column names and values as data types (e.g. {'col0': 'bigint', 'col1': 'double'}). + table_type: str, optional + The type of the Glue Table (EXTERNAL_TABLE, GOVERNED...). Set to EXTERNAL_TABLE if None partitions_types: Dict[str, str], optional Dictionary with keys as partition names and values as data types (e.g. {'col2': 'date'}). bucketing_info: Tuple[List[str], int], optional @@ -767,6 +782,7 @@ def create_csv_table( table=table, path=path, columns_types=columns_types, + table_type=table_type, partitions_types=partitions_types, bucketing_info=bucketing_info, catalog_id=catalog_id, diff --git a/awswrangler/catalog/_definitions.py b/awswrangler/catalog/_definitions.py index 778d428dd..97aea2eac 100644 --- a/awswrangler/catalog/_definitions.py +++ b/awswrangler/catalog/_definitions.py @@ -31,6 +31,7 @@ def _parquet_table_definition( table: str, path: str, columns_types: Dict[str, str], + table_type: Optional[str], partitions_types: Dict[str, str], bucketing_info: Optional[Tuple[List[str], int]], compression: Optional[str], @@ -39,7 +40,7 @@ def _parquet_table_definition( return { "Name": table, "PartitionKeys": [{"Name": cname, "Type": dtype} for cname, dtype in partitions_types.items()], - "TableType": "EXTERNAL_TABLE", + "TableType": "EXTERNAL_TABLE" if table_type is None else table_type, "Parameters": {"classification": "parquet", "compressionType": str(compression).lower(), "typeOfData": "file"}, "StorageDescriptor": { "Columns": [{"Name": cname, "Type": dtype} for cname, dtype in columns_types.items()], @@ -98,8 +99,9 @@ def _parquet_partition_definition( def _csv_table_definition( table: str, - path: str, + path: Optional[str], columns_types: Dict[str, str], + table_type: Optional[str], partitions_types: Dict[str, str], bucketing_info: Optional[Tuple[List[str], int]], compression: Optional[str], @@ -120,7 +122,7 @@ def _csv_table_definition( return { "Name": table, "PartitionKeys": [{"Name": cname, "Type": dtype} for cname, dtype in partitions_types.items()], - "TableType": "EXTERNAL_TABLE", + "TableType": "EXTERNAL_TABLE" if table_type is None else table_type, "Parameters": parameters, "StorageDescriptor": { "Columns": [{"Name": cname, "Type": dtype} for cname, dtype in columns_types.items()], diff --git a/awswrangler/lakeformation/__init__.py b/awswrangler/lakeformation/__init__.py new file mode 100644 index 000000000..8b8c3084e --- /dev/null +++ b/awswrangler/lakeformation/__init__.py @@ -0,0 +1,20 @@ +"""Amazon Lake Formation Module.""" + +from awswrangler.lakeformation._read import read_sql_query, read_sql_table # noqa +from awswrangler.lakeformation._utils import ( # noqa + abort_transaction, + begin_transaction, + commit_transaction, + extend_transaction, + wait_query, +) + +__all__ = [ + "read_sql_query", + "read_sql_table", + "abort_transaction", + "begin_transaction", + "commit_transaction", + "extend_transaction", + "wait_query", +] diff --git a/awswrangler/lakeformation/_read.py b/awswrangler/lakeformation/_read.py new file mode 100644 index 000000000..d08c7a5d9 --- /dev/null +++ b/awswrangler/lakeformation/_read.py @@ -0,0 +1,355 @@ +"""Amazon Lake Formation Module gathering all read functions.""" +import concurrent.futures +import itertools +import logging +from typing import Any, Dict, Iterator, List, Optional, Tuple, Union + +import boto3 +import pandas as pd +from pyarrow import NativeFile, RecordBatchStreamReader, Table + +from awswrangler import _data_types, _utils, catalog, exceptions +from awswrangler._config import apply_configs +from awswrangler.catalog._utils import _catalog_id +from awswrangler.lakeformation._utils import abort_transaction, begin_transaction, wait_query + +_logger: logging.Logger = logging.getLogger(__name__) + + +def _execute_query( + query_id: str, + token_work_unit: Tuple[str, int], + categories: Optional[List[str]], + safe: bool, + use_threads: bool, + boto3_session: boto3.Session, +) -> pd.DataFrame: + client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=boto3_session) + token, work_unit = token_work_unit + messages: NativeFile = client_lakeformation.execute(QueryId=query_id, Token=token, WorkUnitId=work_unit)["Messages"] + table: Table = RecordBatchStreamReader(messages.read()).read_all() + args: Dict[str, Any] = {} + if table.num_rows > 0: + args = { + "use_threads": use_threads, + "split_blocks": True, + "self_destruct": True, + "integer_object_nulls": False, + "date_as_object": True, + "ignore_metadata": True, + "strings_to_categorical": False, + "categories": categories, + "safe": safe, + "types_mapper": _data_types.pyarrow2pandas_extension, + } + df: pd.DataFrame = _utils.ensure_df_is_mutable(df=table.to_pandas(**args)) + return df + + +def _resolve_sql_query( + query_id: str, + chunked: Optional[bool], + categories: Optional[List[str]], + safe: bool, + use_threads: bool, + boto3_session: boto3.Session, +) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: + client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=boto3_session) + + wait_query(query_id=query_id, boto3_session=boto3_session) + + # The LF Query Engine distributes the load across workers + # Retrieve the tokens and their associated work units until NextToken is '' + # One Token can span multiple work units + # PageSize determines the size of the "Units" array in each call + scan_kwargs: Dict[str, Union[str, int]] = {"QueryId": query_id, "PageSize": 10} + next_token: str = "init_token" # Dummy token + token_work_units: List[Tuple[str, int]] = [] + while next_token: + response = client_lakeformation.get_work_units(**scan_kwargs) + token_work_units.extend( # [(Token0, WorkUnitId0), (Token0, WorkUnitId1), (Token1, WorkUnitId2) ... ] + [ + (unit["Token"], unit_id) + for unit in response["Units"] + for unit_id in range(unit["WorkUnitIdMin"], unit["WorkUnitIdMax"] + 1) # Max is inclusive + ] + ) + next_token = response.get("NextToken", None) + scan_kwargs["NextToken"] = next_token + + dfs: List[pd.DataFrame] = list() + if use_threads is False: + dfs = list( + _execute_query( + query_id=query_id, + token_work_unit=token_work_unit, + categories=categories, + safe=safe, + use_threads=use_threads, + boto3_session=boto3_session, + ) + for token_work_unit in token_work_units + ) + else: + cpus: int = _utils.ensure_cpu_count(use_threads=use_threads) + with concurrent.futures.ThreadPoolExecutor(max_workers=cpus) as executor: + dfs = list( + executor.map( + _execute_query, + itertools.repeat(query_id), + token_work_units, + itertools.repeat(categories), + itertools.repeat(safe), + itertools.repeat(use_threads), + itertools.repeat(_utils.boto3_to_primitives(boto3_session=boto3_session)), + ) + ) + dfs = [df for df in dfs if not df.empty] + if (not chunked) and dfs: + return pd.concat(dfs, sort=False, copy=False, ignore_index=False) + return dfs + + +@apply_configs +def read_sql_query( + sql: str, + database: str, + transaction_id: Optional[str] = None, + query_as_of_time: Optional[str] = None, + catalog_id: Optional[str] = None, + chunked: bool = False, + categories: Optional[List[str]] = None, + safe: bool = True, + use_threads: bool = True, + boto3_session: Optional[boto3.Session] = None, + params: Optional[Dict[str, Any]] = None, +) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: + """Execute PartiQL query on AWS Glue Table (Transaction ID or time travel timestamp). Return Pandas DataFrame. + + Note + ---- + ORDER BY operations are not honoured. + i.e. sql="SELECT * FROM my_table ORDER BY my_column" is NOT valid + + Note + ---- + The database must NOT be explicitely defined in the PartiQL statement. + i.e. sql="SELECT * FROM my_table" is valid + but sql="SELECT * FROM my_db.my_table" is NOT valid + + Note + ---- + Pass one of `transaction_id` or `query_as_of_time`, not both. + + Note + ---- + `chunked` argument (memory-friendly): + If set to `True`, return an Iterable of DataFrames instead of a regular DataFrame. + + Parameters + ---------- + sql : str + partiQL query. + database : str + AWS Glue database name + transaction_id : str, optional + The ID of the transaction at which to read the table contents. + Cannot be specified alongside query_as_of_time + query_as_of_time : str, optional + The time as of when to read the table contents. Must be a valid Unix epoch timestamp. + Cannot be specified alongside transaction_id + catalog_id : str, optional + The ID of the Data Catalog from which to retrieve Databases. + If none is provided, the AWS account ID is used by default. + chunked : bool, optional + If `True`, Wrangler returns an Iterable of DataFrames with no guarantee of chunksize. + categories: Optional[List[str]], optional + List of columns names that should be returned as pandas.Categorical. + Recommended for memory restricted environments. + safe : bool, default True + For certain data types, a cast is needed in order to store the + data in a pandas DataFrame or Series (e.g. timestamps are always + stored as nanoseconds in pandas). This option controls whether it + is a safe cast or not. + use_threads : bool + True to enable concurrent requests, False to disable multiple threads. + When enabled, os.cpu_count() is used as the max number of threads. + boto3_session : boto3.Session(), optional + Boto3 Session. The default boto3 session is used if boto3_session receives None. + params: Dict[str, any], optional + Dict of parameters used to format the partiQL query. Only named parameters are supported. + The dict must contain the information in the form {"name": "value"} and the SQL query must contain + `:name`. + + Returns + ------- + Union[pd.DataFrame, Iterator[pd.DataFrame]] + Pandas DataFrame or Generator of Pandas DataFrames if chunked is passed. + + Examples + -------- + >>> import awswrangler as wr + >>> df = wr.lakeformation.read_sql_query( + ... sql="SELECT * FROM my_table;", + ... database="my_db", + ... catalog_id="111111111111" + ... ) + + >>> import awswrangler as wr + >>> df = wr.lakeformation.read_sql_query( + ... sql="SELECT * FROM my_table LIMIT 10;", + ... database="my_db", + ... transaction_id="1b62811fa3e02c4e5fdbaa642b752030379c4a8a70da1f8732ce6ccca47afdc9" + ... ) + + >>> import awswrangler as wr + >>> df = wr.lakeformation.read_sql_query( + ... sql="SELECT * FROM my_table WHERE name=:name; AND city=:city;", + ... database="my_db", + ... query_as_of_time="1611142914", + ... params={"name": "'filtered_name'", "city": "'filtered_city'"} + ... ) + + """ + if transaction_id is not None and query_as_of_time is not None: + raise exceptions.InvalidArgumentCombination( + "Please pass only one of `transaction_id` or `query_as_of_time`, not both" + ) + session: boto3.Session = _utils.ensure_session(session=boto3_session) + client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) + if params is None: + params = {} + for key, value in params.items(): + sql = sql.replace(f":{key};", str(value)) + + args: Dict[str, Optional[str]] = _catalog_id(catalog_id=catalog_id, **{"DatabaseName": database, "Statement": sql}) + if query_as_of_time: + args["QueryAsOfTime"] = query_as_of_time + elif transaction_id: + args["TransactionId"] = transaction_id + else: + _logger.debug("Neither `transaction_id` nor `query_as_of_time` were specified, beginning transaction") + transaction_id = begin_transaction(read_only=True, boto3_session=session) + args["TransactionId"] = transaction_id + query_id: str = client_lakeformation.plan_query(**args)["QueryId"] + try: + return _resolve_sql_query( + query_id=query_id, + chunked=chunked, + categories=categories, + safe=safe, + use_threads=use_threads, + boto3_session=session, + ) + except Exception as ex: + _logger.debug("Aborting transaction with ID: %s.", transaction_id) + if transaction_id: + abort_transaction(transaction_id=transaction_id, boto3_session=session) + _logger.error(ex) + raise + + +@apply_configs +def read_sql_table( + table: str, + database: str, + transaction_id: Optional[str] = None, + query_as_of_time: Optional[str] = None, + catalog_id: Optional[str] = None, + chunked: bool = False, + categories: Optional[List[str]] = None, + safe: bool = True, + use_threads: bool = True, + boto3_session: Optional[boto3.Session] = None, +) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: + """Extract all rows from AWS Glue Table (Transaction ID or time travel timestamp). Return Pandas DataFrame. + + Note + ---- + ORDER BY operations are not honoured. + i.e. sql="SELECT * FROM my_table ORDER BY my_column" is NOT valid + + Note + ---- + Pass one of `transaction_id` or `query_as_of_time`, not both. + + Note + ---- + `chunked` argument (memory-friendly): + If set to `True`, return an Iterable of DataFrames instead of a regular DataFrame. + + Parameters + ---------- + table : str + AWS Glue table name. + database : str + AWS Glue database name + transaction_id : str, optional + The ID of the transaction at which to read the table contents. + Cannot be specified alongside query_as_of_time + query_as_of_time : str, optional + The time as of when to read the table contents. Must be a valid Unix epoch timestamp. + Cannot be specified alongside transaction_id + catalog_id : str, optional + The ID of the Data Catalog from which to retrieve Databases. + If none is provided, the AWS account ID is used by default. + chunked : bool, optional + If `True`, Wrangler returns an Iterable of DataFrames with no guarantee of chunksize. + categories: Optional[List[str]], optional + List of columns names that should be returned as pandas.Categorical. + Recommended for memory restricted environments. + safe : bool, default True + For certain data types, a cast is needed in order to store the + data in a pandas DataFrame or Series (e.g. timestamps are always + stored as nanoseconds in pandas). This option controls whether it + is a safe cast or not. + use_threads : bool + True to enable concurrent requests, False to disable multiple threads. + When enabled, os.cpu_count() is used as the max number of threads. + boto3_session : boto3.Session(), optional + Boto3 Session. The default boto3 session is used if boto3_session receives None. + + Returns + ------- + Union[pd.DataFrame, Iterator[pd.DataFrame]] + Pandas DataFrame or Generator of Pandas DataFrames if chunked is passed. + + Examples + -------- + >>> import awswrangler as wr + >>> df = wr.lakeformation.read_sql_table( + ... table="my_table", + ... database="my_db", + ... catalog_id="111111111111", + ... ) + + >>> import awswrangler as wr + >>> df = wr.lakeformation.read_sql_table( + ... table="my_table", + ... database="my_db", + ... transaction_id="1b62811fa3e02c4e5fdbaa642b752030379c4a8a70da1f8732ce6ccca47afdc9", + ... chunked=True, + ... ) + + >>> import awswrangler as wr + >>> df = wr.lakeformation.read_sql_table( + ... table="my_table", + ... database="my_db", + ... query_as_of_time="1611142914", + ... use_threads=True, + ... ) + + """ + table = catalog.sanitize_table_name(table=table) + return read_sql_query( + sql=f"SELECT * FROM {table}", + database=database, + transaction_id=transaction_id, + query_as_of_time=query_as_of_time, + safe=safe, + catalog_id=catalog_id, + categories=categories, + chunked=chunked, + use_threads=use_threads, + boto3_session=boto3_session, + ) diff --git a/awswrangler/lakeformation/_utils.py b/awswrangler/lakeformation/_utils.py new file mode 100644 index 000000000..ea94101bd --- /dev/null +++ b/awswrangler/lakeformation/_utils.py @@ -0,0 +1,264 @@ +"""Utilities Module for Amazon Lake Formation.""" +import logging +import time +from typing import Any, Dict, List, Optional, Union + +import boto3 + +from awswrangler import _utils, exceptions +from awswrangler.catalog._utils import _catalog_id +from awswrangler.s3._describe import describe_objects + +_QUERY_FINAL_STATES: List[str] = ["ERROR", "FINISHED"] +_QUERY_WAIT_POLLING_DELAY: float = 2 # SECONDS + +_logger: logging.Logger = logging.getLogger(__name__) + + +def _without_keys(d: Dict[str, Any], keys: List[str]) -> Dict[str, Any]: + return {x: d[x] for x in d if x not in keys} + + +def _build_partition_predicate( + partition_cols: List[str], + partitions_types: Dict[str, str], + partitions_values: List[str], +) -> str: + partition_predicates: List[str] = [] + for col, val in zip(partition_cols, partitions_values): + if partitions_types[col].startswith(("tinyint", "smallint", "int", "bigint", "float", "double", "decimal")): + partition_predicates.append(f"{col}={str(val)}") + else: + partition_predicates.append(f"{col}='{str(val)}'") + return " AND ".join(partition_predicates) + + +def _build_table_objects( + paths: List[str], + partitions_values: Dict[str, List[str]], + use_threads: bool, + boto3_session: Optional[boto3.Session], +) -> List[Dict[str, Any]]: + table_objects: List[Dict[str, Any]] = [] + paths_desc: Dict[str, Dict[str, Any]] = describe_objects( + path=paths, use_threads=use_threads, boto3_session=boto3_session + ) + for path, path_desc in paths_desc.items(): + table_object: Dict[str, Any] = { + "Uri": path, + "ETag": path_desc["ETag"], + "Size": path_desc["ContentLength"], + } + if partitions_values: + table_object["PartitionValues"] = partitions_values[f"{path.rsplit('/', 1)[0].rstrip('/')}/"] + table_objects.append(table_object) + return table_objects + + +def _get_table_objects( + catalog_id: Optional[str], + database: str, + table: str, + transaction_id: str, + boto3_session: Optional[boto3.Session], + partition_cols: Optional[List[str]] = None, + partitions_types: Optional[Dict[str, str]] = None, + partitions_values: Optional[List[str]] = None, +) -> List[Dict[str, Any]]: + """Get Governed Table Objects from Lake Formation Engine.""" + session: boto3.Session = _utils.ensure_session(session=boto3_session) + client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) + + scan_kwargs: Dict[str, Union[str, int]] = _catalog_id( + catalog_id=catalog_id, TransactionId=transaction_id, DatabaseName=database, TableName=table, MaxResults=100 + ) + if partition_cols and partitions_types and partitions_values: + scan_kwargs["PartitionPredicate"] = _build_partition_predicate( + partition_cols=partition_cols, partitions_types=partitions_types, partitions_values=partitions_values + ) + + next_token: str = "init_token" # Dummy token + table_objects: List[Dict[str, Any]] = [] + while next_token: + response = client_lakeformation.get_table_objects(**scan_kwargs) + for objects in response["Objects"]: + for table_object in objects["Objects"]: + if objects["PartitionValues"]: + table_object["PartitionValues"] = objects["PartitionValues"] + table_objects.append(table_object) + next_token = response.get("NextToken", None) + scan_kwargs["NextToken"] = next_token + return table_objects + + +def _update_table_objects( + catalog_id: Optional[str], + database: str, + table: str, + transaction_id: str, + boto3_session: Optional[boto3.Session], + add_objects: Optional[List[Dict[str, Any]]] = None, + del_objects: Optional[List[Dict[str, Any]]] = None, +) -> None: + """Register Governed Table Objects changes to Lake Formation Engine.""" + session: boto3.Session = _utils.ensure_session(session=boto3_session) + client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) + + update_kwargs: Dict[str, Union[str, int, List[Dict[str, Dict[str, Any]]]]] = _catalog_id( + catalog_id=catalog_id, TransactionId=transaction_id, DatabaseName=database, TableName=table + ) + + write_operations: List[Dict[str, Dict[str, Any]]] = [] + if add_objects: + write_operations.extend({"AddObject": obj} for obj in add_objects) + elif del_objects: + write_operations.extend({"DeleteObject": _without_keys(obj, ["Size"])} for obj in del_objects) + update_kwargs["WriteOperations"] = write_operations + + client_lakeformation.update_table_objects(**update_kwargs) + + +def abort_transaction(transaction_id: str, boto3_session: Optional[boto3.Session] = None) -> None: + """Abort the specified transaction. Returns exception if the transaction was previously committed. + + Parameters + ---------- + transaction_id : str + The ID of the transaction. + boto3_session : boto3.Session(), optional + Boto3 Session. The default boto3 session will be used if boto3_session received None. + + Returns + ------- + None + None. + + Examples + -------- + >>> import awswrangler as wr + >>> wr.lakeformation.abort_transaction(transaction_id="...") + + """ + session: boto3.Session = _utils.ensure_session(session=boto3_session) + client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) + + client_lakeformation.abort_transaction(TransactionId=transaction_id) + + +def begin_transaction(read_only: Optional[bool] = False, boto3_session: Optional[boto3.Session] = None) -> str: + """Start a new transaction and returns its transaction ID. + + Parameters + ---------- + read_only : bool, optional + Indicates that that this transaction should be read only. + Writes made using a read-only transaction ID will be rejected. + Read-only transactions do not need to be committed. + boto3_session : boto3.Session(), optional + Boto3 Session. The default boto3 session will be used if boto3_session received None. + + Returns + ------- + str + An opaque identifier for the transaction. + + Examples + -------- + >>> import awswrangler as wr + >>> transaction_id = wr.lakeformation.begin_transaction(read_only=False) + + """ + session: boto3.Session = _utils.ensure_session(session=boto3_session) + client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) + transaction_id: str = client_lakeformation.begin_transaction(ReadOnly=read_only)["TransactionId"] + return transaction_id + + +def commit_transaction(transaction_id: str, boto3_session: Optional[boto3.Session] = None) -> None: + """Commit the specified transaction. Returns exception if the transaction was previously aborted. + + Parameters + ---------- + transaction_id : str + The ID of the transaction. + boto3_session : boto3.Session(), optional + Boto3 Session. The default boto3 session will be used if boto3_session received None. + + Returns + ------- + None + None. + + Examples + -------- + >>> import awswrangler as wr + >>> wr.lakeformation.commit_transaction(transaction_id="...") + + """ + session: boto3.Session = _utils.ensure_session(session=boto3_session) + client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) + + client_lakeformation.commit_transaction(TransactionId=transaction_id) + + +def extend_transaction(transaction_id: str, boto3_session: Optional[boto3.Session] = None) -> None: + """Indicate to the service that the specified transaction is still active and should not be aborted. + + Parameters + ---------- + transaction_id : str + The ID of the transaction. + boto3_session : boto3.Session(), optional + Boto3 Session. The default boto3 session will be used if boto3_session received None. + + Returns + ------- + None + None. + + Examples + -------- + >>> import awswrangler as wr + >>> wr.lakeformation.extend_transaction(transaction_id="...") + + """ + session: boto3.Session = _utils.ensure_session(session=boto3_session) + client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) + + client_lakeformation.extend_transaction(TransactionId=transaction_id) + + +def wait_query(query_id: str, boto3_session: Optional[boto3.Session] = None) -> Dict[str, Any]: + """Wait for the query to end. + + Parameters + ---------- + query_id : str + Lake Formation query execution ID. + boto3_session : boto3.Session(), optional + Boto3 Session. The default boto3 session will be used if boto3_session received None. + + Returns + ------- + Dict[str, Any] + Dictionary with the get_query_state response. + + Examples + -------- + >>> import awswrangler as wr + >>> res = wr.lakeformation.wait_query(query_id='query-id') + + """ + session: boto3.Session = _utils.ensure_session(session=boto3_session) + client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) + + response: Dict[str, Any] = client_lakeformation.get_query_state(QueryId=query_id) + state: str = response["State"] + while state not in _QUERY_FINAL_STATES: + time.sleep(_QUERY_WAIT_POLLING_DELAY) + response = client_lakeformation.get_query_state(QueryId=query_id) + state = response["State"] + _logger.debug("state: %s", state) + if state == "ERROR": + raise exceptions.QueryFailed(response.get("Error")) + return response diff --git a/awswrangler/s3/_write.py b/awswrangler/s3/_write.py index e94a71288..666035bb6 100644 --- a/awswrangler/s3/_write.py +++ b/awswrangler/s3/_write.py @@ -47,7 +47,7 @@ def _validate_args( table: Optional[str], database: Optional[str], dataset: bool, - path: str, + path: Optional[str], partition_cols: Optional[List[str]], bucketing_info: Optional[Tuple[List[str], int]], mode: Optional[str], @@ -58,6 +58,8 @@ def _validate_args( if df.empty is True: raise exceptions.EmptyDataFrame() if dataset is False: + if path is None: + raise exceptions.InvalidArgumentValue("If dataset is False, the argument `path` must be passed.") if path.endswith("/"): raise exceptions.InvalidArgumentValue( "If , the argument should be a file path, not a directory." diff --git a/awswrangler/s3/_write_dataset.py b/awswrangler/s3/_write_dataset.py index bf3a7a1f4..3bc05cf2d 100644 --- a/awswrangler/s3/_write_dataset.py +++ b/awswrangler/s3/_write_dataset.py @@ -9,6 +9,14 @@ import pandas as pd from awswrangler import exceptions +from awswrangler.lakeformation._utils import ( + _build_table_objects, + _get_table_objects, + _update_table_objects, + abort_transaction, + begin_transaction, + commit_transaction, +) from awswrangler.s3._delete import delete_objects from awswrangler.s3._write_concurrent import _WriteProxy @@ -23,6 +31,12 @@ def _to_partitions( use_threads: bool, mode: str, partition_cols: List[str], + partitions_types: Optional[Dict[str, str]], + catalog_id: Optional[str], + database: Optional[str], + table: Optional[str], + table_type: Optional[str], + transaction_id: Optional[str], bucketing_info: Optional[Tuple[List[str], int]], boto3_session: boto3.Session, **func_kwargs: Any, @@ -37,12 +51,33 @@ def _to_partitions( subdir = "/".join([f"{name}={val}" for name, val in zip(partition_cols, keys)]) prefix: str = f"{path_root}{subdir}/" if mode == "overwrite_partitions": - delete_objects( - path=prefix, - use_threads=use_threads, - boto3_session=boto3_session, - s3_additional_kwargs=func_kwargs.get("s3_additional_kwargs"), - ) + if (table_type == "GOVERNED") and (table is not None) and (database is not None): + del_objects: List[Dict[str, Any]] = _get_table_objects( + catalog_id=catalog_id, + database=database, + table=table, + transaction_id=transaction_id, # type: ignore + partition_cols=partition_cols, + partitions_values=keys, + partitions_types=partitions_types, + boto3_session=boto3_session, + ) + if del_objects: + _update_table_objects( + catalog_id=catalog_id, + database=database, + table=table, + transaction_id=transaction_id, # type: ignore + del_objects=del_objects, + boto3_session=boto3_session, + ) + else: + delete_objects( + path=prefix, + use_threads=use_threads, + boto3_session=boto3_session, + s3_additional_kwargs=func_kwargs.get("s3_additional_kwargs"), + ) if bucketing_info: _to_buckets( func=func, @@ -137,24 +172,51 @@ def _to_dataset( use_threads: bool, mode: str, partition_cols: Optional[List[str]], + partitions_types: Optional[Dict[str, str]], + catalog_id: Optional[str], + database: Optional[str], + table: Optional[str], + table_type: Optional[str], + transaction_id: Optional[str], bucketing_info: Optional[Tuple[List[str], int]], boto3_session: boto3.Session, **func_kwargs: Any, ) -> Tuple[List[str], Dict[str, List[str]]]: path_root = path_root if path_root.endswith("/") else f"{path_root}/" + commit_trans: bool = False + if table_type == "GOVERNED": + # Check whether to skip committing the transaction (i.e. multiple read/write operations) + if transaction_id is None: + _logger.debug("`transaction_id` not specified, beginning transaction") + transaction_id = begin_transaction(read_only=False, boto3_session=boto3_session) + commit_trans = True + # Evaluate mode if mode not in ["append", "overwrite", "overwrite_partitions"]: raise exceptions.InvalidArgumentValue( f"{mode} is a invalid mode, please use append, overwrite or overwrite_partitions." ) if (mode == "overwrite") or ((mode == "overwrite_partitions") and (not partition_cols)): - delete_objects( - path=path_root, - use_threads=use_threads, - boto3_session=boto3_session, - s3_additional_kwargs=func_kwargs.get("s3_additional_kwargs"), - ) + if (table_type == "GOVERNED") and (table is not None) and (database is not None): + del_objects: List[Dict[str, Any]] = _get_table_objects( + catalog_id=catalog_id, + database=database, + table=table, + transaction_id=transaction_id, # type: ignore + boto3_session=boto3_session, + ) + if del_objects: + _update_table_objects( + catalog_id=catalog_id, + database=database, + table=table, + transaction_id=transaction_id, # type: ignore + del_objects=del_objects, + boto3_session=boto3_session, + ) + else: + delete_objects(path=path_root, use_threads=use_threads, boto3_session=boto3_session) # Writing partitions_values: Dict[str, List[str]] = {} @@ -167,8 +229,14 @@ def _to_dataset( path_root=path_root, use_threads=use_threads, mode=mode, + catalog_id=catalog_id, + database=database, + table=table, + table_type=table_type, + transaction_id=transaction_id, bucketing_info=bucketing_info, partition_cols=partition_cols, + partitions_types=partitions_types, boto3_session=boto3_session, index=index, **func_kwargs, @@ -190,4 +258,27 @@ def _to_dataset( ) _logger.debug("paths: %s", paths) _logger.debug("partitions_values: %s", partitions_values) + if (table_type == "GOVERNED") and (table is not None) and (database is not None): + add_objects: List[Dict[str, Any]] = _build_table_objects( + paths, partitions_values, use_threads=use_threads, boto3_session=boto3_session + ) + try: + if add_objects: + _update_table_objects( + catalog_id=catalog_id, + database=database, + table=table, + transaction_id=transaction_id, # type: ignore + add_objects=add_objects, + boto3_session=boto3_session, + ) + if commit_trans: + commit_transaction(transaction_id=transaction_id, boto3_session=boto3_session) # type: ignore + except Exception as ex: + _logger.debug("Aborting transaction with ID: %s.", transaction_id) + if transaction_id: + abort_transaction(transaction_id=transaction_id, boto3_session=boto3_session) + _logger.error(ex) + raise + return paths, partitions_values diff --git a/awswrangler/s3/_write_parquet.py b/awswrangler/s3/_write_parquet.py index 29bf9b694..7d7395f48 100644 --- a/awswrangler/s3/_write_parquet.py +++ b/awswrangler/s3/_write_parquet.py @@ -196,9 +196,9 @@ def _to_parquet( @apply_configs -def to_parquet( # pylint: disable=too-many-arguments,too-many-locals +def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-branches,too-many-statements df: pd.DataFrame, - path: str, + path: Optional[str] = None, index: bool = False, compression: Optional[str] = "snappy", max_rows_by_file: Optional[int] = None, @@ -215,6 +215,8 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals schema_evolution: bool = True, database: Optional[str] = None, table: Optional[str] = None, + table_type: Optional[str] = None, + transaction_id: Optional[str] = None, dtype: Optional[Dict[str, str]] = None, description: Optional[str] = None, parameters: Optional[Dict[str, str]] = None, @@ -252,7 +254,7 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals ---------- df: pandas.DataFrame Pandas DataFrame https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html - path : str + path : str, optional S3 path (for file e.g. ``s3://bucket/prefix/filename.parquet``) (for dataset e.g. ``s3://bucket/prefix``). index : bool True to store the DataFrame index in file, otherwise False to ignore it. @@ -307,6 +309,10 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals Glue/Athena catalog: Database name. table : str, optional Glue/Athena catalog: Table name. + table_type: str, optional + The type of the Glue Table. Set to EXTERNAL_TABLE if None. + transaction_id: str, optional + The ID of the transaction when writing to a Governed Table. dtype : Dict[str, str], optional Dictionary of columns names and Athena/Glue types to be casted. Useful when you have columns with undetermined or mixed data types. @@ -452,6 +458,28 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals } } + Writing dataset to Glue governed table + + >>> import awswrangler as wr + >>> import pandas as pd + >>> wr.s3.to_parquet( + ... df=pd.DataFrame({ + ... 'col': [1, 2, 3], + ... 'col2': ['A', 'A', 'B'], + ... 'col3': [None, None, None] + ... }), + ... dataset=True, + ... mode='append', + ... database='default', # Athena/Glue database + ... table='my_table', # Athena/Glue table + ... table_type='GOVERNED', + ... transaction_id="xxx", + ... ) + { + 'paths': ['s3://.../x.parquet'], + 'partitions_values: {} + } + Writing dataset casting empty column data type >>> import awswrangler as wr @@ -498,6 +526,8 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals dtype = dtype if dtype else {} partitions_values: Dict[str, List[str]] = {} mode = "append" if mode is None else mode + if transaction_id: + table_type = "GOVERNED" cpus: int = _utils.ensure_cpu_count(use_threads=use_threads) session: boto3.Session = _utils.ensure_session(session=boto3_session) @@ -511,6 +541,15 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals catalog_table_input = catalog._get_table_input( # pylint: disable=protected-access database=database, table=table, boto3_session=session, catalog_id=catalog_id ) + if catalog_table_input: + table_type = catalog_table_input["TableType"] + if path is None: + if catalog_table_input: + path = catalog_table_input["StorageDescriptor"]["Location"] + else: + raise exceptions.InvalidArgumentValue( + "Glue table does not exist. Please pass the `path` argument to create it." + ) df = _apply_dtype(df=df, dtype=dtype, catalog_table_input=catalog_table_input, mode=mode) schema: pa.Schema = _data_types.pyarrow_schema_from_pandas( df=df, index=index, ignore_cols=partition_cols, dtype=dtype @@ -541,17 +580,51 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals ) if schema_evolution is False: _check_schema_changes(columns_types=columns_types, table_input=catalog_table_input, mode=mode) + if (catalog_table_input is None) and (table_type == "GOVERNED"): + catalog._create_parquet_table( # pylint: disable=protected-access + database=database, + table=table, + path=path, # type: ignore + columns_types=columns_types, + table_type=table_type, + partitions_types=partitions_types, + bucketing_info=bucketing_info, + compression=compression, + description=description, + parameters=parameters, + columns_comments=columns_comments, + boto3_session=session, + mode=mode, + catalog_versioning=catalog_versioning, + projection_enabled=projection_enabled, + projection_types=projection_types, + projection_ranges=projection_ranges, + projection_values=projection_values, + projection_intervals=projection_intervals, + projection_digits=projection_digits, + catalog_id=catalog_id, + catalog_table_input=catalog_table_input, + ) + catalog_table_input = catalog._get_table_input( # pylint: disable=protected-access + database=database, table=table, boto3_session=session, catalog_id=catalog_id + ) paths, partitions_values = _to_dataset( func=_to_parquet, concurrent_partitioning=concurrent_partitioning, df=df, - path_root=path, + path_root=path, # type: ignore index=index, compression=compression, compression_ext=compression_ext, + catalog_id=catalog_id, + database=database, + table=table, + table_type=table_type, + transaction_id=transaction_id, cpus=cpus, use_threads=use_threads, partition_cols=partition_cols, + partitions_types=partitions_types, bucketing_info=bucketing_info, dtype=dtype, mode=mode, @@ -565,8 +638,9 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals catalog._create_parquet_table( # pylint: disable=protected-access database=database, table=table, - path=path, + path=path, # type: ignore columns_types=columns_types, + table_type=table_type, partitions_types=partitions_types, bucketing_info=bucketing_info, compression=compression, @@ -585,7 +659,7 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals catalog_id=catalog_id, catalog_table_input=catalog_table_input, ) - if partitions_values and (regular_partitions is True): + if partitions_values and (regular_partitions is True) and (table_type != "GOVERNED"): _logger.debug("partitions_values:\n%s", partitions_values) catalog.add_parquet_partitions( database=database, diff --git a/awswrangler/s3/_write_text.py b/awswrangler/s3/_write_text.py index 809d2bc92..d7f20bb32 100644 --- a/awswrangler/s3/_write_text.py +++ b/awswrangler/s3/_write_text.py @@ -72,9 +72,9 @@ def _to_text( @apply_configs -def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-statements +def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-statements,too-many-branches df: pd.DataFrame, - path: str, + path: Optional[str] = None, sep: str = ",", index: bool = True, columns: Optional[List[str]] = None, @@ -90,6 +90,8 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state catalog_versioning: bool = False, database: Optional[str] = None, table: Optional[str] = None, + table_type: Optional[str] = None, + transaction_id: Optional[str] = None, dtype: Optional[Dict[str, str]] = None, description: Optional[str] = None, parameters: Optional[Dict[str, str]] = None, @@ -137,7 +139,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state ---------- df: pandas.DataFrame Pandas DataFrame https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html - path : str + path : str, optional Amazon S3 path (e.g. s3://bucket/filename.csv). sep : str String of length 1. Field delimiter for the output file. @@ -184,6 +186,10 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state Glue/Athena catalog: Database name. table : str, optional Glue/Athena catalog: Table name. + table_type: str, optional + The type of the Glue Table. Set to EXTERNAL_TABLE if None + transaction_id: str, optional + The ID of the transaction when writing to a Governed Table. dtype : Dict[str, str], optional Dictionary of columns names and Athena/Glue types to be casted. Useful when you have columns with undetermined or mixed data types. @@ -350,6 +356,28 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state } } + Writing dataset to Glue governed table + + >>> import awswrangler as wr + >>> import pandas as pd + >>> wr.s3.to_csv( + ... df=pd.DataFrame({ + ... 'col': [1, 2, 3], + ... 'col2': ['A', 'A', 'B'], + ... 'col3': [None, None, None] + ... }), + ... dataset=True, + ... mode='append', + ... database='default', # Athena/Glue database + ... table='my_table', # Athena/Glue table + ... table_type='GOVERNED', + ... transaction_id="xxx", + ... ) + { + 'paths': ['s3://.../x.csv'], + 'partitions_values: {} + } + Writing dataset casting empty column data type >>> import awswrangler as wr @@ -402,6 +430,8 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state dtype = dtype if dtype else {} partitions_values: Dict[str, List[str]] = {} mode = "append" if mode is None else mode + if transaction_id: + table_type = "GOVERNED" session: boto3.Session = _utils.ensure_session(session=boto3_session) # Sanitize table to respect Athena's standards @@ -414,6 +444,15 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state catalog_table_input = catalog._get_table_input( # pylint: disable=protected-access database=database, table=table, boto3_session=session, catalog_id=catalog_id ) + if catalog_table_input: + table_type = catalog_table_input["TableType"] + if path is None: + if catalog_table_input: + path = catalog_table_input["StorageDescriptor"]["Location"] + else: + raise exceptions.InvalidArgumentValue( + "Glue table does not exist. Please pass the `path` argument to create it." + ) if pandas_kwargs.get("compression") not in ("gzip", "bz2", None): raise exceptions.InvalidArgumentCombination( "If database and table are given, you must use one of these compressions: gzip, bz2 or None." @@ -421,6 +460,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state df = _apply_dtype(df=df, dtype=dtype, catalog_table_input=catalog_table_input, mode=mode) + paths: List[str] = [] if dataset is False: pandas_kwargs["sep"] = sep pandas_kwargs["index"] = index @@ -434,7 +474,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state s3_additional_kwargs=s3_additional_kwargs, **pandas_kwargs, ) - paths = [path] + paths = [path] # type: ignore else: if database and table: quoting: Optional[int] = csv.QUOTE_NONE @@ -457,16 +497,58 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state pd_kwargs.pop("compression", None) df = df[columns] if columns else df + columns_types: Dict[str, str] = {} + partitions_types: Dict[str, str] = {} + if database and table: + columns_types, partitions_types = _data_types.athena_types_from_pandas_partitioned( + df=df, index=index, partition_cols=partition_cols, dtype=dtype, index_left=True + ) + if (catalog_table_input is None) and (table_type == "GOVERNED"): + catalog._create_csv_table( # pylint: disable=protected-access + database=database, + table=table, + path=path, + columns_types=columns_types, + table_type=table_type, + partitions_types=partitions_types, + bucketing_info=bucketing_info, + description=description, + parameters=parameters, + columns_comments=columns_comments, + boto3_session=session, + mode=mode, + catalog_versioning=catalog_versioning, + sep=sep, + projection_enabled=projection_enabled, + projection_types=projection_types, + projection_ranges=projection_ranges, + projection_values=projection_values, + projection_intervals=projection_intervals, + projection_digits=projection_digits, + catalog_table_input=catalog_table_input, + catalog_id=catalog_id, + compression=pandas_kwargs.get("compression"), + skip_header_line_count=None, + ) + catalog_table_input = catalog._get_table_input( # pylint: disable=protected-access + database=database, table=table, boto3_session=session, catalog_id=catalog_id + ) paths, partitions_values = _to_dataset( func=_to_text, concurrent_partitioning=concurrent_partitioning, df=df, - path_root=path, + path_root=path, # type: ignore index=index, sep=sep, compression=compression, + catalog_id=catalog_id, + database=database, + table=table, + table_type=table_type, + transaction_id=transaction_id, use_threads=use_threads, partition_cols=partition_cols, + partitions_types=partitions_types, bucketing_info=bucketing_info, mode=mode, boto3_session=session, @@ -480,14 +562,12 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state ) if database and table: try: - columns_types, partitions_types = _data_types.athena_types_from_pandas_partitioned( - df=df, index=index, partition_cols=partition_cols, dtype=dtype, index_left=True - ) catalog._create_csv_table( # pylint: disable=protected-access database=database, table=table, path=path, columns_types=columns_types, + table_type=table_type, partitions_types=partitions_types, bucketing_info=bucketing_info, description=description, @@ -508,7 +588,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state compression=pandas_kwargs.get("compression"), skip_header_line_count=None, ) - if partitions_values and (regular_partitions is True): + if partitions_values and (regular_partitions is True) and (table_type != "GOVERNED"): _logger.debug("partitions_values:\n%s", partitions_values) catalog.add_csv_partitions( database=database, diff --git a/cloudformation/base.yaml b/cloudformation/base.yaml index 6e77560d4..76b69acff 100644 --- a/cloudformation/base.yaml +++ b/cloudformation/base.yaml @@ -1,6 +1,19 @@ AWSTemplateFormatVersion: 2010-09-09 Description: | AWS Data Wrangler Development Base Data Lake Infrastructure. VPC, Subnets, S3 Bucket, Glue Database, etc. +Parameters: + EnableLakeFormation: + Type: String + Description: set to True if Lake Formation is enabled in the account + Default: false + AllowedValues: + - true + - false +Conditions: + CreateLFResources: + Fn::Equals: + - Ref: EnableLakeFormation + - true Resources: VPC: Type: AWS::EC2::VPC @@ -161,6 +174,7 @@ Resources: - Key: Env Value: aws-data-wrangler Description: Aws Data Wrangler Test Key. + EnableKeyRotation: true KeyPolicy: Version: '2012-10-17' Id: aws-data-wrangler-key @@ -217,7 +231,99 @@ Resources: Ref: AWS::AccountId DatabaseInput: Name: aws_data_wrangler - Description: AWS Data Wrangler Test Arena - Glue Database + Description: AWS Data Wrangler Test Athena - Glue Database + LakeFormationBucket: + Type: AWS::S3::Bucket + Condition: CreateLFResources + Properties: + Tags: + - Key: Env + Value: aws-data-wrangler + PublicAccessBlockConfiguration: + BlockPublicAcls: true + BlockPublicPolicy: true + IgnorePublicAcls: true + RestrictPublicBuckets: true + LifecycleConfiguration: + Rules: + - Id: CleaningUp + Status: Enabled + ExpirationInDays: 1 + AbortIncompleteMultipartUpload: + DaysAfterInitiation: 1 + NoncurrentVersionExpirationInDays: 1 + LakeFormationTransactionRole: + Type: AWS::IAM::Role + Condition: CreateLFResources + Properties: + Tags: + - Key: Env + Value: aws-data-wrangler + AssumeRolePolicyDocument: + Version: 2012-10-17 + Statement: + - Effect: Allow + Principal: + Service: + - lakeformation.amazonaws.com + Action: + - sts:AssumeRole + Path: / + Policies: + - PolicyName: Root + PolicyDocument: + Version: 2012-10-17 + Statement: + - Effect: Allow + Action: + - s3:DeleteObject + - s3:GetObject + - s3:PutObject + Resource: + - Fn::Sub: arn:aws:s3:::${LakeFormationBucket}/* + - Effect: Allow + Action: + - s3:ListObject + Resource: + - Fn::Sub: arn:aws:s3:::${LakeFormationBucket} + - Effect: Allow + Action: + - execute-api:Invoke + Resource: arn:aws:execute-api:*:*:*/*/POST/reportStatus + - Effect: Allow + Action: + - lakeformation:AbortTransaction + - lakeformation:BeginTransaction + - lakeformation:CommitTransaction + - lakeformation:GetTableObjects + - lakeformation:UpdateTableObjects + Resource: '*' + - Effect: Allow + Action: + - glue:GetTable + - glue:GetPartitions + - glue:UpdateTable + Resource: '*' + LakeFormationBucketS3Registration: + Type: AWS::LakeFormation::Resource + Condition: CreateLFResources + Properties: + ResourceArn: + Fn::Sub: arn:aws:::s3:${LakeFormationBucket}/ + RoleArn: + Fn::GetAtt: + - LakeFormationTransactionRole + - Arn + UseServiceLinkedRole: false + LakeFormationGlueDatabase: + Type: AWS::Glue::Database + Condition: CreateLFResources + Properties: + CatalogId: + Ref: AWS::AccountId + DatabaseInput: + Name: aws_data_wrangler_lakeformation + Description: AWS Data Wrangler - Lake Formation Database LogGroup: Type: AWS::Logs::LogGroup Properties: @@ -274,6 +380,11 @@ Outputs: Value: Ref: GlueDatabase Description: Glue Database Name. + LakeFormationGlueDatabaseName: + Condition: CreateLFResources + Value: + Ref: LakeFormationGlueDatabase + Description: Lake Formation Glue Database Name. LogGroupName: Value: Ref: LogGroup diff --git a/tests/_utils.py b/tests/_utils.py index 85df69484..c931445c2 100644 --- a/tests/_utils.py +++ b/tests/_utils.py @@ -17,7 +17,7 @@ CFN_VALID_STATUS = ["CREATE_COMPLETE", "ROLLBACK_COMPLETE", "UPDATE_COMPLETE", "UPDATE_ROLLBACK_COMPLETE"] -def get_df(): +def get_df(governed=False): df = pd.DataFrame( { "iint8": [1, None, 2], @@ -45,10 +45,13 @@ def get_df(): df["float"] = df["float"].astype("float32") df["string"] = df["string"].astype("string") df["category"] = df["category"].astype("category") + + if governed: + df = df.drop(["iint8", "binary"], axis=1) # tinyint & binary currently not supported return df -def get_df_list(): +def get_df_list(governed=False): df = pd.DataFrame( { "iint8": [1, None, 2], @@ -79,10 +82,13 @@ def get_df_list(): df["float"] = df["float"].astype("float32") df["string"] = df["string"].astype("string") df["category"] = df["category"].astype("category") + + if governed: + df = (df.drop(["iint8", "binary"], axis=1),) # tinyint & binary currently not supported return df -def get_df_cast(): +def get_df_cast(governed=False): df = pd.DataFrame( { "iint8": [None, None, None], @@ -103,6 +109,8 @@ def get_df_cast(): "par1": ["a", "b", "b"], } ) + if governed: + df = (df.drop(["iint8", "binary"], axis=1),) # tinyint & binary currently not supported return df @@ -418,7 +426,7 @@ def get_query_long(): """ -def ensure_data_types(df, has_list=False): +def ensure_data_types(df, has_list=False, governed=False): if "iint8" in df.columns: assert str(df["iint8"].dtype).startswith("Int") assert str(df["iint16"].dtype).startswith("Int") @@ -430,7 +438,10 @@ def ensure_data_types(df, has_list=False): if "string_object" in df.columns: assert str(df["string_object"].dtype) == "string" assert str(df["string"].dtype) == "string" - assert str(df["date"].dtype) == "object" + if governed: + assert str(df["date"].dtype) == "datetime64[ns]" + else: + assert str(df["date"].dtype) == "object" assert str(df["timestamp"].dtype) == "datetime64[ns]" assert str(df["bool"].dtype) in ("boolean", "Int64", "object") if "binary" in df.columns: @@ -447,7 +458,10 @@ def ensure_data_types(df, has_list=False): if not row.empty: row = row.iloc[0] assert str(type(row["decimal"]).__name__) == "Decimal" - assert str(type(row["date"]).__name__) == "date" + if governed: + assert str(type(row["date"]).__name__) == "Timestamp" + else: + assert str(type(row["date"]).__name__) == "date" if "binary" in df.columns: assert str(type(row["binary"]).__name__) == "bytes" if has_list is True: @@ -468,7 +482,7 @@ def ensure_data_types_category(df): assert str(df["par1"].dtype) == "category" -def ensure_data_types_csv(df): +def ensure_data_types_csv(df, governed=False): if "__index_level_0__" in df: assert str(df["__index_level_0__"].dtype).startswith("Int") assert str(df["id"].dtype).startswith("Int") @@ -480,7 +494,10 @@ def ensure_data_types_csv(df): assert str(df["float"].dtype).startswith("float") if "int" in df: assert str(df["int"].dtype).startswith("Int") - assert str(df["date"].dtype) == "object" + if governed: + assert str(df["date"].dtype).startswith("datetime") + else: + assert str(df["date"].dtype) == "object" assert str(df["timestamp"].dtype).startswith("datetime") if "bool" in df: assert str(df["bool"].dtype) == "boolean" diff --git a/tests/conftest.py b/tests/conftest.py index 011fccfca..7bdb19b64 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -28,6 +28,11 @@ def glue_database(cloudformation_outputs): return cloudformation_outputs["GlueDatabaseName"] +@pytest.fixture(scope="session") +def lakeformation_glue_database(cloudformation_outputs): + return cloudformation_outputs["LakeFormationGlueDatabaseName"] + + @pytest.fixture(scope="session") def kms_key(cloudformation_outputs): return cloudformation_outputs["KmsKeyArn"] diff --git a/tests/test__routines.py b/tests/test__routines.py index fb08e8d12..96f430059 100644 --- a/tests/test__routines.py +++ b/tests/test__routines.py @@ -10,7 +10,13 @@ @pytest.mark.parametrize("use_threads", [True, False]) @pytest.mark.parametrize("concurrent_partitioning", [True, False]) -def test_routine_0(glue_database, glue_table, path, use_threads, concurrent_partitioning): +@pytest.mark.parametrize("table_type", ["EXTERNAL_TABLE", "GOVERNED"]) +def test_routine_0( + lakeformation_glue_database, glue_database, glue_table, table_type, path, use_threads, concurrent_partitioning +): + + table = f"__{glue_table}" + database = lakeformation_glue_database if table_type == "GOVERNED" else glue_database # Round 1 - Warm up df = pd.DataFrame({"c0": [0, None]}, dtype="Int64") @@ -19,24 +25,28 @@ def test_routine_0(glue_database, glue_table, path, use_threads, concurrent_part path=path, dataset=True, mode="overwrite", - database=glue_database, - table=glue_table, + database=database, + table=table, + table_type=table_type, description="c0", parameters={"num_cols": str(len(df.columns)), "num_rows": str(len(df.index))}, columns_comments={"c0": "0"}, use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=glue_database) == 1 - df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) + assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + if table_type == "GOVERNED": + df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + else: + df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) assert df.shape == df2.shape assert df.c0.sum() == df2.c0.sum() - parameters = wr.catalog.get_table_parameters(glue_database, glue_table) + parameters = wr.catalog.get_table_parameters(database, table) assert len(parameters) >= 5 assert parameters["num_cols"] == str(len(df2.columns)) assert parameters["num_rows"] == str(len(df2.index)) - assert wr.catalog.get_table_description(glue_database, glue_table) == "c0" - comments = wr.catalog.get_columns_comments(glue_database, glue_table) + assert wr.catalog.get_table_description(database, table) == "c0" + comments = wr.catalog.get_columns_comments(database, table) assert len(comments) == len(df.columns) assert comments["c0"] == "0" @@ -44,27 +54,29 @@ def test_routine_0(glue_database, glue_table, path, use_threads, concurrent_part df = pd.DataFrame({"c1": [None, 1, None]}, dtype="Int16") wr.s3.to_parquet( df=df, - path=path, dataset=True, mode="overwrite", - database=glue_database, - table=glue_table, + database=database, + table=table, description="c1", parameters={"num_cols": str(len(df.columns)), "num_rows": str(len(df.index))}, columns_comments={"c1": "1"}, use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=glue_database) == 1 - df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) + assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + if table_type == "GOVERNED": + df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + else: + df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) assert df.shape == df2.shape assert df.c1.sum() == df2.c1.sum() - parameters = wr.catalog.get_table_parameters(glue_database, glue_table) + parameters = wr.catalog.get_table_parameters(database, table) assert len(parameters) >= 5 assert parameters["num_cols"] == str(len(df2.columns)) assert parameters["num_rows"] == str(len(df2.index)) - assert wr.catalog.get_table_description(glue_database, glue_table) == "c1" - comments = wr.catalog.get_columns_comments(glue_database, glue_table) + assert wr.catalog.get_table_description(database, table) == "c1" + comments = wr.catalog.get_columns_comments(database, table) assert len(comments) == len(df.columns) assert comments["c1"] == "1" @@ -75,25 +87,28 @@ def test_routine_0(glue_database, glue_table, path, use_threads, concurrent_part path=path, dataset=True, mode="append", - database=glue_database, - table=glue_table, + database=database, + table=table, description="c1", parameters={"num_cols": str(len(df.columns)), "num_rows": str(len(df.index) * 2)}, columns_comments={"c1": "1"}, use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=glue_database) == 1 - df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) + assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + if table_type == "GOVERNED": + df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + else: + df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) assert len(df.columns) == len(df2.columns) assert len(df.index) * 2 == len(df2.index) assert df.c1.sum() + 1 == df2.c1.sum() - parameters = wr.catalog.get_table_parameters(glue_database, glue_table) + parameters = wr.catalog.get_table_parameters(database, table) assert len(parameters) >= 5 assert parameters["num_cols"] == str(len(df2.columns)) assert parameters["num_rows"] == str(len(df2.index)) - assert wr.catalog.get_table_description(glue_database, glue_table) == "c1" - comments = wr.catalog.get_columns_comments(glue_database, glue_table) + assert wr.catalog.get_table_description(database, table) == "c1" + comments = wr.catalog.get_columns_comments(database, table) assert len(comments) == len(df.columns) assert comments["c1"] == "1" @@ -101,28 +116,30 @@ def test_routine_0(glue_database, glue_table, path, use_threads, concurrent_part df = pd.DataFrame({"c2": ["a", None, "b"], "c1": [None, None, None]}) wr.s3.to_parquet( df=df, - path=path, dataset=True, mode="append", - database=glue_database, - table=glue_table, + database=database, + table=table, description="c1+c2", parameters={"num_cols": "2", "num_rows": "9"}, columns_comments={"c1": "1", "c2": "2"}, use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=glue_database) == 1 - df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) + assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + if table_type == "GOVERNED": + df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + else: + df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) assert len(df2.columns) == 2 assert len(df2.index) == 9 assert df2.c1.sum() == 3 - parameters = wr.catalog.get_table_parameters(glue_database, glue_table) + parameters = wr.catalog.get_table_parameters(database, table) assert len(parameters) >= 5 assert parameters["num_cols"] == "2" assert parameters["num_rows"] == "9" - assert wr.catalog.get_table_description(glue_database, glue_table) == "c1+c2" - comments = wr.catalog.get_columns_comments(glue_database, glue_table) + assert wr.catalog.get_table_description(database, table) == "c1+c2" + comments = wr.catalog.get_columns_comments(database, table) assert len(comments) == len(df.columns) assert comments["c1"] == "1" assert comments["c2"] == "2" @@ -134,39 +151,56 @@ def test_routine_0(glue_database, glue_table, path, use_threads, concurrent_part path=path, dataset=True, mode="append", - database=glue_database, - table=glue_table, + database=database, + table=table, description="c1+c2+c3", parameters={"num_cols": "3", "num_rows": "10"}, columns_comments={"c1": "1!", "c2": "2!", "c3": "3"}, use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=glue_database) == 1 - df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) + assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + if table_type == "GOVERNED": + df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + else: + df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) assert len(df2.columns) == 3 assert len(df2.index) == 10 assert df2.c1.sum() == 4 - parameters = wr.catalog.get_table_parameters(glue_database, glue_table) + parameters = wr.catalog.get_table_parameters(database, table) assert len(parameters) >= 5 assert parameters["num_cols"] == "3" assert parameters["num_rows"] == "10" - assert wr.catalog.get_table_description(glue_database, glue_table) == "c1+c2+c3" - comments = wr.catalog.get_columns_comments(glue_database, glue_table) + assert wr.catalog.get_table_description(database, table) == "c1+c2+c3" + comments = wr.catalog.get_columns_comments(database, table) assert len(comments) == len(df.columns) assert comments["c1"] == "1!" assert comments["c2"] == "2!" assert comments["c3"] == "3" - # Round 6 - Overwrite Partitioned + wr.catalog.delete_table_if_exists(database=database, table=table) + + +@pytest.mark.parametrize("use_threads", [True, False]) +@pytest.mark.parametrize("concurrent_partitioning", [True, False]) +@pytest.mark.parametrize("table_type", ["EXTERNAL_TABLE", "GOVERNED"]) +def test_routine_1( + lakeformation_glue_database, glue_database, glue_table, table_type, path, use_threads, concurrent_partitioning +): + + table = f"__{glue_table}" + database = lakeformation_glue_database if table_type == "GOVERNED" else glue_database + + # Round 1 - Overwrite Partitioned df = pd.DataFrame({"c0": ["foo", None], "c1": [0, 1]}) wr.s3.to_parquet( df=df, path=path, dataset=True, mode="overwrite", - database=glue_database, - table=glue_table, + database=database, + table=table, + table_type=table_type, partition_cols=["c1"], description="c0+c1", parameters={"num_cols": "2", "num_rows": "2"}, @@ -174,29 +208,31 @@ def test_routine_0(glue_database, glue_table, path, use_threads, concurrent_part use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=glue_database) == 1 - df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) + assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + if table_type == "GOVERNED": + df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + else: + df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) assert df.shape == df2.shape assert df.c1.sum() == df2.c1.sum() - parameters = wr.catalog.get_table_parameters(glue_database, glue_table) + parameters = wr.catalog.get_table_parameters(database, table) assert len(parameters) >= 5 assert parameters["num_cols"] == "2" assert parameters["num_rows"] == "2" - assert wr.catalog.get_table_description(glue_database, glue_table) == "c0+c1" - comments = wr.catalog.get_columns_comments(glue_database, glue_table) + assert wr.catalog.get_table_description(database, table) == "c0+c1" + comments = wr.catalog.get_columns_comments(database, table) assert len(comments) == len(df.columns) assert comments["c0"] == "zero" assert comments["c1"] == "one" - # Round 7 - Overwrite Partitions + # Round 2 - Overwrite Partitions df = pd.DataFrame({"c0": [None, None], "c1": [0, 2]}) wr.s3.to_parquet( df=df, - path=path, dataset=True, mode="overwrite_partitions", - database=glue_database, - table=glue_table, + database=database, + table=table, partition_cols=["c1"], description="c0+c1", parameters={"num_cols": "2", "num_rows": "3"}, @@ -204,30 +240,33 @@ def test_routine_0(glue_database, glue_table, path, use_threads, concurrent_part concurrent_partitioning=concurrent_partitioning, use_threads=use_threads, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=glue_database) == 1 - df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) + assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + if table_type == "GOVERNED": + df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + else: + df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) assert len(df2.columns) == 2 assert len(df2.index) == 3 assert df2.c1.sum() == 3 - parameters = wr.catalog.get_table_parameters(glue_database, glue_table) + parameters = wr.catalog.get_table_parameters(database, table) assert len(parameters) >= 5 assert parameters["num_cols"] == "2" assert parameters["num_rows"] == "3" - assert wr.catalog.get_table_description(glue_database, glue_table) == "c0+c1" - comments = wr.catalog.get_columns_comments(glue_database, glue_table) + assert wr.catalog.get_table_description(database, table) == "c0+c1" + comments = wr.catalog.get_columns_comments(database, table) assert len(comments) == len(df.columns) assert comments["c0"] == "zero" assert comments["c1"] == "one" - # Round 8 - Overwrite Partitions + New Column + Wrong Type + # Round 3 - Overwrite Partitions + New Column + Wrong Type df = pd.DataFrame({"c0": [1, 2], "c1": ["1", "3"], "c2": [True, False]}) wr.s3.to_parquet( df=df, path=path, dataset=True, mode="overwrite_partitions", - database=glue_database, - table=glue_table, + database=database, + table=table, partition_cols=["c1"], description="c0+c1+c2", parameters={"num_cols": "3", "num_rows": "4"}, @@ -235,24 +274,29 @@ def test_routine_0(glue_database, glue_table, path, use_threads, concurrent_part use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=glue_database) == 1 - df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) + assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + if table_type == "GOVERNED": + df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + else: + df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) assert len(df2.columns) == 3 assert len(df2.index) == 4 assert df2.c1.sum() == 6 - parameters = wr.catalog.get_table_parameters(glue_database, glue_table) + parameters = wr.catalog.get_table_parameters(database, table) assert len(parameters) >= 5 assert parameters["num_cols"] == "3" assert parameters["num_rows"] == "4" - assert wr.catalog.get_table_description(glue_database, glue_table) == "c0+c1+c2" - comments = wr.catalog.get_columns_comments(glue_database, glue_table) + assert wr.catalog.get_table_description(database, table) == "c0+c1+c2" + comments = wr.catalog.get_columns_comments(database, table) assert len(comments) == len(df.columns) assert comments["c0"] == "zero" assert comments["c1"] == "one" assert comments["c2"] == "two" + wr.catalog.delete_table_if_exists(database=database, table=table) + -def test_routine_1(glue_database, glue_table, path): +def test_routine_2(glue_database, glue_table, path): # Round 1 - Warm up df = pd.DataFrame({"c0": [0, None]}, dtype="Int64") @@ -445,3 +489,5 @@ def test_routine_1(glue_database, glue_table, path): assert comments["c0"] == "zero" assert comments["c1"] == "one" assert comments["c2"] == "two" + + wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table) diff --git a/tests/test_lakeformation.py b/tests/test_lakeformation.py new file mode 100644 index 000000000..242cb3a0f --- /dev/null +++ b/tests/test_lakeformation.py @@ -0,0 +1,150 @@ +import calendar +import logging +import time + +import pandas as pd + +import awswrangler as wr + +from ._utils import ensure_data_types, ensure_data_types_csv, get_df, get_df_csv + +logging.getLogger("awswrangler").setLevel(logging.DEBUG) + + +def test_lakeformation(path, path2, lakeformation_glue_database, glue_table, glue_table2, use_threads=False): + table = f"__{glue_table}" + table2 = f"__{glue_table2}" + wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table) + wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table2) + + wr.s3.to_parquet( + df=get_df(governed=True), + path=path, + index=False, + boto3_session=None, + s3_additional_kwargs=None, + dataset=True, + partition_cols=["par0", "par1"], + mode="overwrite", + table=table, + table_type="GOVERNED", + database=lakeformation_glue_database, + ) + + df = wr.lakeformation.read_sql_table( + table=table, + database=lakeformation_glue_database, + use_threads=use_threads, + ) + assert len(df.index) == 3 + assert len(df.columns) == 14 + assert df["iint32"].sum() == 3 + ensure_data_types(df=df, governed=True) + + # Filter query + df2 = wr.lakeformation.read_sql_query( + sql=f"SELECT * FROM {table} WHERE iint16 = :iint16;", + database=lakeformation_glue_database, + params={"iint16": 1}, + ) + assert len(df2.index) == 1 + + wr.s3.to_csv( + df=get_df_csv(), + path=path2, + index=False, + boto3_session=None, + s3_additional_kwargs=None, + dataset=True, + partition_cols=["par0", "par1"], + mode="append", + table=table2, + table_type="GOVERNED", + database=lakeformation_glue_database, + ) + # Read within a transaction + transaction_id = wr.lakeformation.begin_transaction(read_only=True) + df3 = wr.lakeformation.read_sql_table( + table=table2, + database=lakeformation_glue_database, + transaction_id=transaction_id, + use_threads=use_threads, + ) + assert df3["int"].sum() == 3 + ensure_data_types_csv(df3, governed=True) + + # Read within a query as of time + query_as_of_time = calendar.timegm(time.gmtime()) + df4 = wr.lakeformation.read_sql_table( + table=table2, + database=lakeformation_glue_database, + query_as_of_time=query_as_of_time, + use_threads=use_threads, + ) + assert len(df4.index) == 3 + + wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table) + wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table2) + + +def test_lakeformation_multi_transaction( + path, path2, lakeformation_glue_database, glue_table, glue_table2, use_threads=True +): + table = f"__{glue_table}" + table2 = f"__{glue_table2}" + wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table) + wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table2) + + df = pd.DataFrame({"c0": [0, None]}, dtype="Int64") + transaction_id = wr.lakeformation.begin_transaction(read_only=False) + wr.s3.to_parquet( + df=df, + path=path, + dataset=True, + mode="append", + database=lakeformation_glue_database, + table=table, + table_type="GOVERNED", + transaction_id=transaction_id, + description="c0", + parameters={"num_cols": str(len(df.columns)), "num_rows": str(len(df.index))}, + columns_comments={"c0": "0"}, + use_threads=use_threads, + ) + + df2 = pd.DataFrame({"c1": [None, 1, None]}, dtype="Int16") + wr.s3.to_parquet( + df=df2, + path=path2, + dataset=True, + mode="append", + database=lakeformation_glue_database, + table=table2, + table_type="GOVERNED", + transaction_id=transaction_id, + description="c1", + parameters={"num_cols": str(len(df.columns)), "num_rows": str(len(df.index))}, + columns_comments={"c1": "1"}, + use_threads=use_threads, + ) + wr.lakeformation.commit_transaction(transaction_id=transaction_id) + + df3 = wr.lakeformation.read_sql_table( + table=table, + database=lakeformation_glue_database, + use_threads=use_threads, + ) + df4 = wr.lakeformation.read_sql_table( + table=table2, + database=lakeformation_glue_database, + use_threads=use_threads, + ) + + assert df.shape == df3.shape + assert df.c0.sum() == df3.c0.sum() + + assert df2.shape == df4.shape + assert df2.c1.sum() == df4.c1.sum() + + wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table) + wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table2) diff --git a/tutorials/029 - Lake Formation Governed Tables.ipynb b/tutorials/029 - Lake Formation Governed Tables.ipynb new file mode 100644 index 000000000..571b78a89 --- /dev/null +++ b/tutorials/029 - Lake Formation Governed Tables.ipynb @@ -0,0 +1,441 @@ +{ + "metadata": { + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.1" + }, + "orig_nbformat": 2, + "kernelspec": { + "name": "python3", + "display_name": "Python 3.9.1 64-bit ('.venv': venv)", + "metadata": { + "interpreter": { + "hash": "2878c7ae46413c5ab07cafef85a7415922732432fa2f847b9105997e244ed975" + } + } + } + }, + "nbformat": 4, + "nbformat_minor": 2, + "cells": [ + { + "source": [ + "[![AWS Data Wrangler](_static/logo.png \"AWS Data Wrangler\")](https://github.com/awslabs/aws-data-wrangler)" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "source": [ + "# AWS Lake Formation - Glue Governed tables" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "source": [ + "### This tutorial assumes that your IAM user/role has the required Lake Formation permissions to create and read AWS Glue Governed tables" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "source": [ + "## Table of Contents\n", + "* [1. Read Governed table](#1.-Read-Governed-table)\n", + " * [1.1 Read PartiQL query](#1.1-Read-PartiQL-query)\n", + " * [1.1.1 Read within transaction](#1.1.1-Read-within-transaction)\n", + " * [1.1.2 Read within query as of time](#1.1.2-Read-within-query-as-of-time)\n", + " * [1.2 Read full table](#1.2-Read-full-table)\n", + "* [2. Write Governed table](#2.-Write-Governed-table)\n", + " * [2.1 Create new Governed table](#2.1-Create-new-Governed-table)\n", + " * [2.1.1 CSV table](#2.1.1-CSV-table)\n", + " * [2.1.2 Parquet table](#2.1.2-Parquet-table)\n", + " * [2.2 Overwrite operations](#2.2-Overwrite-operations)\n", + " * [2.2.1 Overwrite](#2.2.1-Overwrite)\n", + " * [2.2.2 Append](#2.2.2-Append)\n", + " * [2.2.3 Create partitioned Governed table](#2.2.3-Create-partitioned-Governed-table)\n", + " * [2.2.4 Overwrite partitions](#2.2.4-Overwrite-partitions)\n", + "* [3. Multiple read/write operations within a transaction](#2.-Multiple-read/write-operations-within-a-transaction)" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "source": [ + "# 1. Read Governed table" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "source": [ + "## 1.1 Read PartiQL query" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import awswrangler as wr\n", + "\n", + "database = \"gov_db\" # Assumes a Glue database registered with Lake Formation exists in the account\n", + "table = \"gov_table\" # Assumes a Governed table exists in the account\n", + "catalog_id = \"111111111111\" # AWS Account Id\n", + "\n", + "# Note 1: If a transaction_id is not specified, a new transaction is started\n", + "df = wr.lakeformation.read_sql_query(\n", + " sql=f\"SELECT * FROM {table};\",\n", + " database=database,\n", + " catalog_id=catalog_id\n", + ")" + ] + }, + { + "source": [ + "### 1.1.1 Read within transaction" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "transaction_id = wr.lakeformation.begin_transaction(read_only=True)\n", + "df = wr.lakeformation.read_sql_query(\n", + " sql=f\"SELECT * FROM {table};\",\n", + " database=database,\n", + " transaction_id=transaction_id\n", + ")" + ] + }, + { + "source": [ + "### 1.1.2 Read within query as of time" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import calendar\n", + "import time\n", + "\n", + "query_as_of_time = query_as_of_time = calendar.timegm(time.gmtime())\n", + "df = wr.lakeformation.read_sql_query(\n", + " sql=f\"SELECT * FROM {table} WHERE id=:id; AND name=:name;\",\n", + " database=database,\n", + " query_as_of_time=query_as_of_time,\n", + " params={\"id\": 1, \"name\": \"Ayoub\"}\n", + ")" + ] + }, + { + "source": [ + "## 1.2 Read full table" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df = wr.lakeformation.read_sql_table(\n", + " table=table,\n", + " database=database\n", + ")" + ] + }, + { + "source": [ + "# 2. Write Governed table" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "source": [ + "## 2.1 Create a new Governed table" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "source": [ + "## Enter your bucket name:" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import getpass\n", + "\n", + "bucket = getpass.getpass()" + ] + }, + { + "source": [ + "### If a governed table does not exist, it can be created by passing an S3 `path` argument. Make sure your IAM user/role has enough permissions in the Lake Formation database" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "source": [ + "### 2.1.1 CSV table" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "\n", + "table = \"gov_table_csv\"\n", + "\n", + "df=pd.DataFrame({\n", + " \"col\": [1, 2, 3],\n", + " \"col2\": [\"A\", \"A\", \"B\"],\n", + " \"col3\": [None, \"test\", None]\n", + "})\n", + "# Note 1: If a transaction_id is not specified, a new transaction is started\n", + "# Note 2: When creating a new Governed table, `table_type=\"GOVERNED\"` must be specified. Otherwise the default is to create an EXTERNAL_TABLE\n", + "wr.s3.to_csv(\n", + " df=df,\n", + " path=f\"s3://{bucket}/{database}/{table}/\", # S3 path\n", + " dataset=True,\n", + " database=database,\n", + " table=table,\n", + " table_type=\"GOVERNED\"\n", + ")" + ] + }, + { + "source": [ + "### 2.1.2 Parquet table" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "table = \"gov_table_parquet\"\n", + "\n", + "df = pd.DataFrame({\"c0\": [0, None]}, dtype=\"Int64\")\n", + "wr.s3.to_parquet(\n", + " df=df,\n", + " path=f\"s3://{bucket}/{database}/{table}/\",\n", + " dataset=True,\n", + " database=database,\n", + " table=table,\n", + " table_type=\"GOVERNED\",\n", + " description=\"c0\",\n", + " parameters={\"num_cols\": str(len(df.columns)), \"num_rows\": str(len(df.index))},\n", + " columns_comments={\"c0\": \"0\"}\n", + ")" + ] + }, + { + "source": [ + "## 2.2 Overwrite operations" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "source": [ + "### 2.2.1 Overwrite" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.DataFrame({\"c1\": [None, 1, None]}, dtype=\"Int16\")\n", + "wr.s3.to_parquet(\n", + " df=df,\n", + " dataset=True,\n", + " mode=\"overwrite\",\n", + " database=database,\n", + " table=table,\n", + " description=\"c1\",\n", + " parameters={\"num_cols\": str(len(df.columns)), \"num_rows\": str(len(df.index))},\n", + " columns_comments={\"c1\": \"1\"}\n", + ")" + ] + }, + { + "source": [ + "### 2.2.2 Append" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.DataFrame({\"c1\": [None, 2, None]}, dtype=\"Int8\")\n", + "wr.s3.to_parquet(\n", + " df=df,\n", + " dataset=True,\n", + " mode=\"append\",\n", + " database=database,\n", + " table=table,\n", + " description=\"c1\",\n", + " parameters={\"num_cols\": str(len(df.columns)), \"num_rows\": str(len(df.index) * 2)},\n", + " columns_comments={\"c1\": \"1\"}\n", + ")" + ] + }, + { + "source": [ + "### 2.2.3 Create partitioned Governed table" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "table = \"gov_table_parquet_partitioned\"\n", + "\n", + "df = pd.DataFrame({\"c0\": [\"foo\", None], \"c1\": [0, 1]})\n", + "wr.s3.to_parquet(\n", + " df=df,\n", + " path=f\"s3://{bucket}/{database}/{table}/\",\n", + " dataset=True,\n", + " database=database,\n", + " table=table,\n", + " table_type=\"GOVERNED\",\n", + " partition_cols=[\"c1\"],\n", + " description=\"c0+c1\",\n", + " parameters={\"num_cols\": \"2\", \"num_rows\": \"2\"},\n", + " columns_comments={\"c0\": \"zero\", \"c1\": \"one\"}\n", + ")" + ] + }, + { + "source": [ + "### 2.2.4 Overwrite partitions" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.DataFrame({\"c0\": [None, None], \"c1\": [0, 2]})\n", + "wr.s3.to_parquet(\n", + " df=df,\n", + " dataset=True,\n", + " mode=\"overwrite_partitions\",\n", + " database=database,\n", + " table=table,\n", + " partition_cols=[\"c1\"],\n", + " description=\"c0+c1\",\n", + " parameters={\"num_cols\": \"2\", \"num_rows\": \"3\"},\n", + " columns_comments={\"c0\": \"zero\", \"c1\": \"one\"}\n", + ")" + ] + }, + { + "source": [ + "# 3. Multiple read/write operations within a transaction" + ], + "cell_type": "markdown", + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "read_table = \"gov_table_parquet\"\n", + "write_table = \"gov_table_multi_parquet\"\n", + "\n", + "transaction_id = wr.lakeformation.begin_transaction(read_only=False)\n", + "\n", + "df = pd.DataFrame({\"c0\": [0, None]}, dtype=\"Int64\")\n", + "wr.s3.to_parquet(\n", + " df=df,\n", + " path=f\"s3://{bucket}/{database}/{write_table}_1\",\n", + " dataset=True,\n", + " database=database,\n", + " table=f\"{write_table}_1\",\n", + " table_type=\"GOVERNED\",\n", + " transaction_id=transaction_id,\n", + ")\n", + "\n", + "df2 = wr.lakeformation.read_sql_table(\n", + " table=read_table,\n", + " database=database,\n", + " transaction_id=transaction_id,\n", + " use_threads=True\n", + ")\n", + "\n", + "df3 = pd.DataFrame({\"c1\": [None, 1, None]}, dtype=\"Int16\")\n", + "wr.s3.to_parquet(\n", + " df=df2,\n", + " path=f\"s3://{bucket}/{database}/{write_table}_2\",\n", + " dataset=True,\n", + " mode=\"append\",\n", + " database=database,\n", + " table=f\"{write_table}_2\",\n", + " table_type=\"GOVERNED\",\n", + " transaction_id=transaction_id,\n", + ")\n", + "\n", + "wr.lakeformation.commit_transaction(transaction_id=transaction_id)" + ] + } + ] +} \ No newline at end of file From 1a0c5512b09167bf402d082badb3389515d6b44b Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Thu, 25 Feb 2021 15:56:21 +0000 Subject: [PATCH 02/36] Minor - Reducing scope gitworkflow --- .github/workflows/static-checking.yml | 1 - 1 file changed, 1 deletion(-) diff --git a/.github/workflows/static-checking.yml b/.github/workflows/static-checking.yml index ce22ffe06..80b813ad7 100644 --- a/.github/workflows/static-checking.yml +++ b/.github/workflows/static-checking.yml @@ -4,7 +4,6 @@ on: push: branches: - main - - main-governed-tables pull_request: branches: - main From 6034f760f6681d0b8ef6d19a2c2921710e30d0ae Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Wed, 3 Mar 2021 19:21:30 +0000 Subject: [PATCH 03/36] Minor - Fixing _sanitize_name --- awswrangler/catalog/_utils.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/awswrangler/catalog/_utils.py b/awswrangler/catalog/_utils.py index aaa68c41d..bad4e016f 100644 --- a/awswrangler/catalog/_utils.py +++ b/awswrangler/catalog/_utils.py @@ -21,8 +21,7 @@ def _catalog_id(catalog_id: Optional[str] = None, **kwargs: Any) -> Dict[str, An def _sanitize_name(name: str) -> str: name = "".join(c for c in unicodedata.normalize("NFD", name) if unicodedata.category(c) != "Mn") # strip accents - name = re.sub("[^A-Za-z0-9_]+", "_", name) # Replacing non alphanumeric characters by underscore - return re.sub("([a-z0-9])([A-Z])", r"\1_\2", name).lower() # Converting CamelCase to snake_case + return re.sub("[^A-Za-z0-9_]+", "_", name).lower() # Replacing non alphanumeric characters by underscore def _extract_dtypes_from_table_details(response: Dict[str, Any]) -> Dict[str, str]: From 2660de21a88dc564525c0ee28543261bfd02453b Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Tue, 9 Mar 2021 19:19:33 +0000 Subject: [PATCH 04/36] Minor - Adding map_types flag --- awswrangler/lakeformation/_read.py | 18 +++++++++++++++++- 1 file changed, 17 insertions(+), 1 deletion(-) diff --git a/awswrangler/lakeformation/_read.py b/awswrangler/lakeformation/_read.py index d08c7a5d9..1ca6eeaf6 100644 --- a/awswrangler/lakeformation/_read.py +++ b/awswrangler/lakeformation/_read.py @@ -21,6 +21,7 @@ def _execute_query( token_work_unit: Tuple[str, int], categories: Optional[List[str]], safe: bool, + map_types: bool, use_threads: bool, boto3_session: boto3.Session, ) -> pd.DataFrame: @@ -40,7 +41,7 @@ def _execute_query( "strings_to_categorical": False, "categories": categories, "safe": safe, - "types_mapper": _data_types.pyarrow2pandas_extension, + "types_mapper": _data_types.pyarrow2pandas_extension if map_types else None, } df: pd.DataFrame = _utils.ensure_df_is_mutable(df=table.to_pandas(**args)) return df @@ -51,6 +52,7 @@ def _resolve_sql_query( chunked: Optional[bool], categories: Optional[List[str]], safe: bool, + map_types: bool, use_threads: bool, boto3_session: boto3.Session, ) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: @@ -85,6 +87,7 @@ def _resolve_sql_query( token_work_unit=token_work_unit, categories=categories, safe=safe, + map_types=map_types, use_threads=use_threads, boto3_session=boto3_session, ) @@ -100,6 +103,7 @@ def _resolve_sql_query( token_work_units, itertools.repeat(categories), itertools.repeat(safe), + itertools.repeat(map_types), itertools.repeat(use_threads), itertools.repeat(_utils.boto3_to_primitives(boto3_session=boto3_session)), ) @@ -120,6 +124,7 @@ def read_sql_query( chunked: bool = False, categories: Optional[List[str]] = None, safe: bool = True, + map_types: bool = True, use_threads: bool = True, boto3_session: Optional[boto3.Session] = None, params: Optional[Dict[str, Any]] = None, @@ -171,6 +176,10 @@ def read_sql_query( data in a pandas DataFrame or Series (e.g. timestamps are always stored as nanoseconds in pandas). This option controls whether it is a safe cast or not. + map_types : bool, default True + True to convert pyarrow DataTypes to pandas ExtensionDtypes. It is + used to override the default pandas type for conversion of built-in + pyarrow types or in absence of pandas_metadata in the Table schema. use_threads : bool True to enable concurrent requests, False to disable multiple threads. When enabled, os.cpu_count() is used as the max number of threads. @@ -238,6 +247,7 @@ def read_sql_query( chunked=chunked, categories=categories, safe=safe, + map_types=map_types, use_threads=use_threads, boto3_session=session, ) @@ -259,6 +269,7 @@ def read_sql_table( chunked: bool = False, categories: Optional[List[str]] = None, safe: bool = True, + map_types: bool = True, use_threads: bool = True, boto3_session: Optional[boto3.Session] = None, ) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: @@ -303,6 +314,10 @@ def read_sql_table( data in a pandas DataFrame or Series (e.g. timestamps are always stored as nanoseconds in pandas). This option controls whether it is a safe cast or not. + map_types : bool, default True + True to convert pyarrow DataTypes to pandas ExtensionDtypes. It is + used to override the default pandas type for conversion of built-in + pyarrow types or in absence of pandas_metadata in the Table schema. use_threads : bool True to enable concurrent requests, False to disable multiple threads. When enabled, os.cpu_count() is used as the max number of threads. @@ -347,6 +362,7 @@ def read_sql_table( transaction_id=transaction_id, query_as_of_time=query_as_of_time, safe=safe, + map_types=map_types, catalog_id=catalog_id, categories=categories, chunked=chunked, From 02445e5e756a14fb60a86a70fbd6e43c300599c3 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Fri, 12 Mar 2021 19:00:54 +0000 Subject: [PATCH 05/36] Minor - Aligning optional path argument with main branch --- awswrangler/s3/_write.py | 6 +++++- awswrangler/s3/_write_parquet.py | 14 +++++++++++--- awswrangler/s3/_write_text.py | 16 ++++++++++++---- 3 files changed, 28 insertions(+), 8 deletions(-) diff --git a/awswrangler/s3/_write.py b/awswrangler/s3/_write.py index 666035bb6..a1915bdb1 100644 --- a/awswrangler/s3/_write.py +++ b/awswrangler/s3/_write.py @@ -59,7 +59,7 @@ def _validate_args( raise exceptions.EmptyDataFrame() if dataset is False: if path is None: - raise exceptions.InvalidArgumentValue("If dataset is False, the argument `path` must be passed.") + raise exceptions.InvalidArgumentValue("If dataset is False, the `path` argument must be passed.") if path.endswith("/"): raise exceptions.InvalidArgumentValue( "If , the argument should be a file path, not a directory." @@ -81,6 +81,10 @@ def _validate_args( "Arguments database and table must be passed together. If you want to store your dataset metadata in " "the Glue Catalog, please ensure you are passing both." ) + elif all(x is None for x in [path, database, table]): + raise exceptions.InvalidArgumentCombination( + "You must specify a `path` if dataset is True and database/table are not enabled." + ) elif bucketing_info and bucketing_info[1] <= 0: raise exceptions.InvalidArgumentValue( "Please pass a value greater than 1 for the number of buckets for bucketing." diff --git a/awswrangler/s3/_write_parquet.py b/awswrangler/s3/_write_parquet.py index 7d7395f48..260bf745d 100644 --- a/awswrangler/s3/_write_parquet.py +++ b/awswrangler/s3/_write_parquet.py @@ -256,6 +256,7 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b Pandas DataFrame https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html path : str, optional S3 path (for file e.g. ``s3://bucket/prefix/filename.parquet``) (for dataset e.g. ``s3://bucket/prefix``). + Required if dataset=False or when dataset=True and creating a new dataset index : bool True to store the DataFrame index in file, otherwise False to ignore it. compression: str, optional @@ -541,14 +542,21 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b catalog_table_input = catalog._get_table_input( # pylint: disable=protected-access database=database, table=table, boto3_session=session, catalog_id=catalog_id ) + catalog_path: Optional[str] = None if catalog_table_input: table_type = catalog_table_input["TableType"] + catalog_path = catalog_table_input["StorageDescriptor"]["Location"] if path is None: - if catalog_table_input: - path = catalog_table_input["StorageDescriptor"]["Location"] + if catalog_path: + path = catalog_path else: raise exceptions.InvalidArgumentValue( - "Glue table does not exist. Please pass the `path` argument to create it." + "Glue table does not exist in the catalog. Please pass the `path` argument to create it." + ) + elif path and catalog_path: + if path.rstrip("/") != catalog_path.rstrip("/"): + raise exceptions.InvalidArgumentValue( + f"The specified path: {path}, does not match the existing Glue catalog table path: {catalog_path}" ) df = _apply_dtype(df=df, dtype=dtype, catalog_table_input=catalog_table_input, mode=mode) schema: pa.Schema = _data_types.pyarrow_schema_from_pandas( diff --git a/awswrangler/s3/_write_text.py b/awswrangler/s3/_write_text.py index d7f20bb32..2985eccec 100644 --- a/awswrangler/s3/_write_text.py +++ b/awswrangler/s3/_write_text.py @@ -140,7 +140,8 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state df: pandas.DataFrame Pandas DataFrame https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html path : str, optional - Amazon S3 path (e.g. s3://bucket/filename.csv). + Amazon S3 path (e.g. s3://bucket/prefix/filename.csv) (for dataset e.g. ``s3://bucket/prefix``). + Required if dataset=False or when creating a new dataset sep : str String of length 1. Field delimiter for the output file. index : bool @@ -444,14 +445,21 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state catalog_table_input = catalog._get_table_input( # pylint: disable=protected-access database=database, table=table, boto3_session=session, catalog_id=catalog_id ) + catalog_path: Optional[str] = None if catalog_table_input: table_type = catalog_table_input["TableType"] + catalog_path = catalog_table_input["StorageDescriptor"]["Location"] if path is None: - if catalog_table_input: - path = catalog_table_input["StorageDescriptor"]["Location"] + if catalog_path: + path = catalog_path else: raise exceptions.InvalidArgumentValue( - "Glue table does not exist. Please pass the `path` argument to create it." + "Glue table does not exist in the catalog. Please pass the `path` argument to create it." + ) + elif path and catalog_path: + if path.rstrip("/") != catalog_path.rstrip("/"): + raise exceptions.InvalidArgumentValue( + f"The specified path: {path}, does not match the existing Glue catalog table path: {catalog_path}" ) if pandas_kwargs.get("compression") not in ("gzip", "bz2", None): raise exceptions.InvalidArgumentCombination( From 0918da0ef6998d5004590ab24775bab8a6abb154 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Wed, 7 Apr 2021 10:12:05 +0100 Subject: [PATCH 06/36] Minor tests adjustments --- tests/test__routines.py | 119 ++++++++++++++++++++-------------------- 1 file changed, 59 insertions(+), 60 deletions(-) diff --git a/tests/test__routines.py b/tests/test__routines.py index 27b5f7fc1..2333037c9 100644 --- a/tests/test__routines.py +++ b/tests/test__routines.py @@ -15,7 +15,6 @@ def test_routine_0( lakeformation_glue_database, glue_database, glue_table, table_type, path, use_threads, concurrent_partitioning ): - table = f"__{glue_table}" database = lakeformation_glue_database if table_type == "GOVERNED" else glue_database # Round 1 - Warm up @@ -26,7 +25,7 @@ def test_routine_0( dataset=True, mode="overwrite", database=database, - table=table, + table=glue_table, table_type=table_type, description="c0", parameters={"num_cols": str(len(df.columns)), "num_rows": str(len(df.index))}, @@ -34,19 +33,19 @@ def test_routine_0( use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) assert df.shape == df2.shape assert df.c0.sum() == df2.c0.sum() - parameters = wr.catalog.get_table_parameters(database, table) + parameters = wr.catalog.get_table_parameters(database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == str(len(df2.columns)) assert parameters["num_rows"] == str(len(df2.index)) - assert wr.catalog.get_table_description(database, table) == "c0" - comments = wr.catalog.get_columns_comments(database, table) + assert wr.catalog.get_table_description(database, glue_table) == "c0" + comments = wr.catalog.get_columns_comments(database, glue_table) assert len(comments) == len(df.columns) assert comments["c0"] == "0" @@ -57,26 +56,26 @@ def test_routine_0( dataset=True, mode="overwrite", database=database, - table=table, + table=glue_table, description="c1", parameters={"num_cols": str(len(df.columns)), "num_rows": str(len(df.index))}, columns_comments={"c1": "1"}, use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) assert df.shape == df2.shape assert df.c1.sum() == df2.c1.sum() - parameters = wr.catalog.get_table_parameters(database, table) + parameters = wr.catalog.get_table_parameters(database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == str(len(df2.columns)) assert parameters["num_rows"] == str(len(df2.index)) - assert wr.catalog.get_table_description(database, table) == "c1" - comments = wr.catalog.get_columns_comments(database, table) + assert wr.catalog.get_table_description(database, glue_table) == "c1" + comments = wr.catalog.get_columns_comments(database, glue_table) assert len(comments) == len(df.columns) assert comments["c1"] == "1" @@ -88,27 +87,27 @@ def test_routine_0( dataset=True, mode="append", database=database, - table=table, + table=glue_table, description="c1", parameters={"num_cols": str(len(df.columns)), "num_rows": str(len(df.index) * 2)}, columns_comments={"c1": "1"}, use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) assert len(df.columns) == len(df2.columns) assert len(df.index) * 2 == len(df2.index) assert df.c1.sum() + 1 == df2.c1.sum() - parameters = wr.catalog.get_table_parameters(database, table) + parameters = wr.catalog.get_table_parameters(database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == str(len(df2.columns)) assert parameters["num_rows"] == str(len(df2.index)) - assert wr.catalog.get_table_description(database, table) == "c1" - comments = wr.catalog.get_columns_comments(database, table) + assert wr.catalog.get_table_description(database, glue_table) == "c1" + comments = wr.catalog.get_columns_comments(database, glue_table) assert len(comments) == len(df.columns) assert comments["c1"] == "1" @@ -119,27 +118,27 @@ def test_routine_0( dataset=True, mode="append", database=database, - table=table, + table=glue_table, description="c1+c2", parameters={"num_cols": "2", "num_rows": "9"}, columns_comments={"c1": "1", "c2": "2"}, use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) assert len(df2.columns) == 2 assert len(df2.index) == 9 assert df2.c1.sum() == 3 - parameters = wr.catalog.get_table_parameters(database, table) + parameters = wr.catalog.get_table_parameters(database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == "2" assert parameters["num_rows"] == "9" - assert wr.catalog.get_table_description(database, table) == "c1+c2" - comments = wr.catalog.get_columns_comments(database, table) + assert wr.catalog.get_table_description(database, glue_table) == "c1+c2" + comments = wr.catalog.get_columns_comments(database, glue_table) assert len(comments) == len(df.columns) assert comments["c1"] == "1" assert comments["c2"] == "2" @@ -152,33 +151,33 @@ def test_routine_0( dataset=True, mode="append", database=database, - table=table, + table=glue_table, description="c1+c2+c3", parameters={"num_cols": "3", "num_rows": "10"}, columns_comments={"c1": "1!", "c2": "2!", "c3": "3"}, use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) assert len(df2.columns) == 3 assert len(df2.index) == 10 assert df2.c1.sum() == 4 - parameters = wr.catalog.get_table_parameters(database, table) + parameters = wr.catalog.get_table_parameters(database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == "3" assert parameters["num_rows"] == "10" - assert wr.catalog.get_table_description(database, table) == "c1+c2+c3" - comments = wr.catalog.get_columns_comments(database, table) + assert wr.catalog.get_table_description(database, glue_table) == "c1+c2+c3" + comments = wr.catalog.get_columns_comments(database, glue_table) assert len(comments) == len(df.columns) assert comments["c1"] == "1!" assert comments["c2"] == "2!" assert comments["c3"] == "3" - wr.catalog.delete_table_if_exists(database=database, table=table) + wr.catalog.delete_table_if_exists(database=database, table=glue_table) @pytest.mark.parametrize("use_threads", [True, False]) @@ -188,7 +187,6 @@ def test_routine_1( lakeformation_glue_database, glue_database, glue_table, table_type, path, use_threads, concurrent_partitioning ): - table = f"__{glue_table}" database = lakeformation_glue_database if table_type == "GOVERNED" else glue_database # Round 1 - Overwrite Partitioned @@ -196,9 +194,10 @@ def test_routine_1( wr.s3.to_parquet( df=df, dataset=True, + path=path, mode="overwrite", database=database, - table=table, + table=glue_table, table_type=table_type, partition_cols=["c1"], description="c0+c1", @@ -207,19 +206,19 @@ def test_routine_1( use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) assert df.shape == df2.shape assert df.c1.sum() == df2.c1.sum() - parameters = wr.catalog.get_table_parameters(database, table) + parameters = wr.catalog.get_table_parameters(database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == "2" assert parameters["num_rows"] == "2" - assert wr.catalog.get_table_description(database, table) == "c0+c1" - comments = wr.catalog.get_columns_comments(database, table) + assert wr.catalog.get_table_description(database, glue_table) == "c0+c1" + comments = wr.catalog.get_columns_comments(database, glue_table) assert len(comments) == len(df.columns) assert comments["c0"] == "zero" assert comments["c1"] == "one" @@ -231,7 +230,7 @@ def test_routine_1( dataset=True, mode="overwrite_partitions", database=database, - table=table, + table=glue_table, partition_cols=["c1"], description="c0+c1", parameters={"num_cols": "2", "num_rows": "3"}, @@ -239,20 +238,20 @@ def test_routine_1( concurrent_partitioning=concurrent_partitioning, use_threads=use_threads, ) - assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) assert len(df2.columns) == 2 assert len(df2.index) == 3 assert df2.c1.sum() == 3 - parameters = wr.catalog.get_table_parameters(database, table) + parameters = wr.catalog.get_table_parameters(database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == "2" assert parameters["num_rows"] == "3" - assert wr.catalog.get_table_description(database, table) == "c0+c1" - comments = wr.catalog.get_columns_comments(database, table) + assert wr.catalog.get_table_description(database, glue_table) == "c0+c1" + comments = wr.catalog.get_columns_comments(database, glue_table) assert len(comments) == len(df.columns) assert comments["c0"] == "zero" assert comments["c1"] == "one" @@ -264,7 +263,7 @@ def test_routine_1( dataset=True, mode="overwrite_partitions", database=database, - table=table, + table=glue_table, partition_cols=["c1"], description="c0+c1+c2", parameters={"num_cols": "3", "num_rows": "4"}, @@ -272,26 +271,26 @@ def test_routine_1( use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=table, database=database) == 1 + assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) assert len(df2.columns) == 3 assert len(df2.index) == 4 assert df2.c1.sum() == 6 - parameters = wr.catalog.get_table_parameters(database, table) + parameters = wr.catalog.get_table_parameters(database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == "3" assert parameters["num_rows"] == "4" - assert wr.catalog.get_table_description(database, table) == "c0+c1+c2" - comments = wr.catalog.get_columns_comments(database, table) + assert wr.catalog.get_table_description(database, glue_table) == "c0+c1+c2" + comments = wr.catalog.get_columns_comments(database, glue_table) assert len(comments) == len(df.columns) assert comments["c0"] == "zero" assert comments["c1"] == "one" assert comments["c2"] == "two" - wr.catalog.delete_table_if_exists(database=database, table=table) + wr.catalog.delete_table_if_exists(database=database, table=glue_table) def test_routine_2(glue_database, glue_table, path): From febcb5cd3c96eb999d491af8db7707a6642f71fa Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Mon, 19 Apr 2021 11:49:39 +0100 Subject: [PATCH 07/36] Minor - Removing Chunked parameter --- .github/workflows/minimal-tests.yml | 1 - awswrangler/lakeformation/_read.py | 25 +------------------------ 2 files changed, 1 insertion(+), 25 deletions(-) diff --git a/.github/workflows/minimal-tests.yml b/.github/workflows/minimal-tests.yml index 082c6ab8a..065172e3d 100644 --- a/.github/workflows/minimal-tests.yml +++ b/.github/workflows/minimal-tests.yml @@ -4,7 +4,6 @@ on: push: branches: - main - - main-governed-tables pull_request: branches: - main diff --git a/awswrangler/lakeformation/_read.py b/awswrangler/lakeformation/_read.py index 1ca6eeaf6..db9b5e6d0 100644 --- a/awswrangler/lakeformation/_read.py +++ b/awswrangler/lakeformation/_read.py @@ -49,7 +49,6 @@ def _execute_query( def _resolve_sql_query( query_id: str, - chunked: Optional[bool], categories: Optional[List[str]], safe: bool, map_types: bool, @@ -108,10 +107,7 @@ def _resolve_sql_query( itertools.repeat(_utils.boto3_to_primitives(boto3_session=boto3_session)), ) ) - dfs = [df for df in dfs if not df.empty] - if (not chunked) and dfs: - return pd.concat(dfs, sort=False, copy=False, ignore_index=False) - return dfs + return pd.concat([df for df in dfs if not df.empty], sort=False, copy=False, ignore_index=False) @apply_configs @@ -121,7 +117,6 @@ def read_sql_query( transaction_id: Optional[str] = None, query_as_of_time: Optional[str] = None, catalog_id: Optional[str] = None, - chunked: bool = False, categories: Optional[List[str]] = None, safe: bool = True, map_types: bool = True, @@ -146,11 +141,6 @@ def read_sql_query( ---- Pass one of `transaction_id` or `query_as_of_time`, not both. - Note - ---- - `chunked` argument (memory-friendly): - If set to `True`, return an Iterable of DataFrames instead of a regular DataFrame. - Parameters ---------- sql : str @@ -166,8 +156,6 @@ def read_sql_query( catalog_id : str, optional The ID of the Data Catalog from which to retrieve Databases. If none is provided, the AWS account ID is used by default. - chunked : bool, optional - If `True`, Wrangler returns an Iterable of DataFrames with no guarantee of chunksize. categories: Optional[List[str]], optional List of columns names that should be returned as pandas.Categorical. Recommended for memory restricted environments. @@ -244,7 +232,6 @@ def read_sql_query( try: return _resolve_sql_query( query_id=query_id, - chunked=chunked, categories=categories, safe=safe, map_types=map_types, @@ -266,7 +253,6 @@ def read_sql_table( transaction_id: Optional[str] = None, query_as_of_time: Optional[str] = None, catalog_id: Optional[str] = None, - chunked: bool = False, categories: Optional[List[str]] = None, safe: bool = True, map_types: bool = True, @@ -284,11 +270,6 @@ def read_sql_table( ---- Pass one of `transaction_id` or `query_as_of_time`, not both. - Note - ---- - `chunked` argument (memory-friendly): - If set to `True`, return an Iterable of DataFrames instead of a regular DataFrame. - Parameters ---------- table : str @@ -304,8 +285,6 @@ def read_sql_table( catalog_id : str, optional The ID of the Data Catalog from which to retrieve Databases. If none is provided, the AWS account ID is used by default. - chunked : bool, optional - If `True`, Wrangler returns an Iterable of DataFrames with no guarantee of chunksize. categories: Optional[List[str]], optional List of columns names that should be returned as pandas.Categorical. Recommended for memory restricted environments. @@ -343,7 +322,6 @@ def read_sql_table( ... table="my_table", ... database="my_db", ... transaction_id="1b62811fa3e02c4e5fdbaa642b752030379c4a8a70da1f8732ce6ccca47afdc9", - ... chunked=True, ... ) >>> import awswrangler as wr @@ -365,7 +343,6 @@ def read_sql_table( map_types=map_types, catalog_id=catalog_id, categories=categories, - chunked=chunked, use_threads=use_threads, boto3_session=boto3_session, ) From 886d1ed46dc0c4e5515b1df1806e2e7d125e6089 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Mon, 3 May 2021 18:08:51 +0100 Subject: [PATCH 08/36] Fixing issues from diverged branch --- awswrangler/catalog/_create.py | 2 +- awswrangler/s3/_write_text.py | 2 ++ 2 files changed, 3 insertions(+), 1 deletion(-) diff --git a/awswrangler/catalog/_create.py b/awswrangler/catalog/_create.py index 7844b30d9..ae04579de 100644 --- a/awswrangler/catalog/_create.py +++ b/awswrangler/catalog/_create.py @@ -286,7 +286,7 @@ def _create_parquet_table( ) -def _create_csv_table( +def _create_csv_table( # pylint: disable=too-many-arguments,too-many-locals database: str, table: str, path: Optional[str], diff --git a/awswrangler/s3/_write_text.py b/awswrangler/s3/_write_text.py index a214ece48..b507d6c4a 100644 --- a/awswrangler/s3/_write_text.py +++ b/awswrangler/s3/_write_text.py @@ -539,6 +539,8 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state catalog_id=catalog_id, compression=pandas_kwargs.get("compression"), skip_header_line_count=None, + serde_library=None, + serde_parameters=None, ) catalog_table_input = catalog._get_table_input( # pylint: disable=protected-access database=database, table=table, boto3_session=session, catalog_id=catalog_id From b9e868e5b8155956996922ab1cba2399c0fcc627 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Mon, 24 May 2021 23:19:44 +0100 Subject: [PATCH 09/36] Major - M1 Launch (Stable) --- awswrangler/catalog/_create.py | 80 +++++++++++++------ awswrangler/catalog/_get.py | 13 ++- awswrangler/lakeformation/__init__.py | 16 +++- awswrangler/lakeformation/_read.py | 28 ++++--- awswrangler/lakeformation/_utils.py | 62 +++++++++++--- awswrangler/s3/_write_dataset.py | 37 +++------ awswrangler/s3/_write_parquet.py | 24 +++++- awswrangler/s3/_write_text.py | 24 +++++- tests/test__routines.py | 8 -- tests/test_lakeformation.py | 4 +- ...029 - Lake Formation Governed Tables.ipynb | 4 +- 11 files changed, 200 insertions(+), 100 deletions(-) diff --git a/awswrangler/catalog/_create.py b/awswrangler/catalog/_create.py index ae04579de..8cb445a09 100644 --- a/awswrangler/catalog/_create.py +++ b/awswrangler/catalog/_create.py @@ -11,6 +11,7 @@ from awswrangler.catalog._delete import delete_all_partitions, delete_table_if_exists from awswrangler.catalog._get import _get_table_input from awswrangler.catalog._utils import _catalog_id, sanitize_column_name, sanitize_table_name +from awswrangler.lakeformation._utils import commit_transaction, start_transaction _logger: logging.Logger = logging.getLogger(__name__) @@ -24,7 +25,7 @@ def _update_if_necessary(dic: Dict[str, str], key: str, value: Optional[str], mo return mode -def _create_table( # pylint: disable=too-many-branches,too-many-statements +def _create_table( # pylint: disable=too-many-branches,too-many-statements,too-many-locals database: str, table: str, description: Optional[str], @@ -38,6 +39,7 @@ def _create_table( # pylint: disable=too-many-branches,too-many-statements projection_enabled: bool, partitions_types: Optional[Dict[str, str]], columns_comments: Optional[Dict[str, str]], + transaction_id: Optional[str], projection_types: Optional[Dict[str, str]], projection_ranges: Optional[Dict[str, str]], projection_values: Optional[Dict[str, str]], @@ -118,29 +120,36 @@ def _create_table( # pylint: disable=too-many-branches,too-many-statements raise exceptions.InvalidArgument( f"{mode} is not a valid mode. It must be 'overwrite', 'append' or 'overwrite_partitions'." ) - if table_exist is True and mode == "overwrite": + args: Dict[str, Any] = _catalog_id( + catalog_id=catalog_id, + DatabaseName=database, + TableInput=table_input, + ) + commit_trans: bool = False + if transaction_id: if table_type != "GOVERNED": - delete_all_partitions(table=table, database=database, catalog_id=catalog_id, boto3_session=session) - _logger.debug("Updating table (%s)...", mode) - client_glue.update_table( - **_catalog_id( - catalog_id=catalog_id, DatabaseName=database, TableInput=table_input, SkipArchive=skip_archive + raise exceptions.InvalidTable( + f"A transaction ID was provided but `{database}`.`{table}` is not a GOVERNED table." ) - ) - elif (table_exist is True) and (mode in ("append", "overwrite_partitions", "update")): - if mode == "update": - _logger.debug("Updating table (%s)...", mode) - client_glue.update_table( - **_catalog_id( - catalog_id=catalog_id, DatabaseName=database, TableInput=table_input, SkipArchive=skip_archive - ) - ) - elif table_exist is False: + args["TransactionId"] = transaction_id + if (table_type == "GOVERNED") and (not transaction_id): + _logger.debug("`transaction_id` not specified for GOVERNED table, starting transaction") + transaction_id = start_transaction(read_only=False, boto3_session=session) + args["TransactionId"] = transaction_id + commit_trans = True + if table_exist: + _logger.debug("Updating table (%s)...", mode) + args["SkipArchive"] = skip_archive + if mode == "overwrite": + if table_type != "GOVERNED": + delete_all_partitions(table=table, database=database, catalog_id=catalog_id, boto3_session=session) + client_glue.update_table(**args) + elif mode == "update": + client_glue.update_table(**args) + else: try: _logger.debug("Creating table (%s)...", mode) - client_glue.create_table( - **_catalog_id(catalog_id=catalog_id, DatabaseName=database, TableInput=table_input) - ) + client_glue.create_table(**args) except client_glue.exceptions.AlreadyExistsException: if mode == "overwrite": _utils.try_it( @@ -151,8 +160,11 @@ def _create_table( # pylint: disable=too-many-branches,too-many-statements database=database, table=table, table_input=table_input, + transaction_id=transaction_id, boto3_session=boto3_session, ) + if commit_trans: + commit_transaction(transaction_id=transaction_id) # type: ignore _logger.debug("Leaving table as is (%s)...", mode) @@ -162,10 +174,18 @@ def _overwrite_table( database: str, table: str, table_input: Dict[str, Any], + transaction_id: Optional[str], boto3_session: boto3.Session, ) -> None: delete_table_if_exists(database=database, table=table, boto3_session=boto3_session, catalog_id=catalog_id) - client_glue.create_table(**_catalog_id(catalog_id=catalog_id, DatabaseName=database, TableInput=table_input)) + args: Dict[str, Any] = _catalog_id( + catalog_id=catalog_id, + DatabaseName=database, + TableInput=table_input, + ) + if transaction_id: + args["TransactionId"] = transaction_id + client_glue.create_table(**args) def _upsert_table_parameters( @@ -227,6 +247,7 @@ def _create_parquet_table( mode: str, catalog_versioning: bool, projection_enabled: bool, + transaction_id: Optional[str], projection_types: Optional[Dict[str, str]], projection_ranges: Optional[Dict[str, str]], projection_values: Optional[Dict[str, str]], @@ -276,6 +297,7 @@ def _create_parquet_table( table_type=table_type, table_exist=table_exist, partitions_types=partitions_types, + transaction_id=transaction_id, projection_enabled=projection_enabled, projection_types=projection_types, projection_ranges=projection_ranges, @@ -299,6 +321,7 @@ def _create_csv_table( # pylint: disable=too-many-arguments,too-many-locals parameters: Optional[Dict[str, str]], columns_comments: Optional[Dict[str, str]], mode: str, + transaction_id: Optional[str], catalog_versioning: bool, sep: str, skip_header_line_count: Optional[int], @@ -356,6 +379,7 @@ def _create_csv_table( # pylint: disable=too-many-arguments,too-many-locals table_type=table_type, table_exist=table_exist, partitions_types=partitions_types, + transaction_id=transaction_id, projection_enabled=projection_enabled, projection_types=projection_types, projection_ranges=projection_ranges, @@ -548,6 +572,7 @@ def create_parquet_table( columns_comments: Optional[Dict[str, str]] = None, mode: str = "overwrite", catalog_versioning: bool = False, + transaction_id: Optional[str] = None, projection_enabled: bool = False, projection_types: Optional[Dict[str, str]] = None, projection_ranges: Optional[Dict[str, str]] = None, @@ -593,6 +618,8 @@ def create_parquet_table( 'overwrite' to recreate any possible existing table or 'append' to keep any possible existing table. catalog_versioning : bool If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). projection_enabled : bool Enable Partition Projection on Athena (https://docs.aws.amazon.com/athena/latest/ug/partition-projection.html) projection_types : Optional[Dict[str, str]] @@ -642,7 +669,7 @@ def create_parquet_table( """ session: boto3.Session = _utils.ensure_session(session=boto3_session) catalog_table_input: Optional[Dict[str, Any]] = _get_table_input( - database=database, table=table, boto3_session=session, catalog_id=catalog_id + database=database, table=table, boto3_session=session, transaction_id=transaction_id, catalog_id=catalog_id ) _create_parquet_table( database=database, @@ -659,6 +686,7 @@ def create_parquet_table( columns_comments=columns_comments, mode=mode, catalog_versioning=catalog_versioning, + transaction_id=transaction_id, projection_enabled=projection_enabled, projection_types=projection_types, projection_ranges=projection_ranges, @@ -671,7 +699,7 @@ def create_parquet_table( @apply_configs -def create_csv_table( +def create_csv_table( # pylint: disable=too-many-arguments database: str, table: str, path: str, @@ -689,6 +717,7 @@ def create_csv_table( skip_header_line_count: Optional[int] = None, serde_library: Optional[str] = None, serde_parameters: Optional[Dict[str, str]] = None, + transaction_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None, projection_enabled: bool = False, projection_types: Optional[Dict[str, str]] = None, @@ -743,6 +772,8 @@ def create_csv_table( serde_parameters : Optional[str] Dictionary of initialization parameters for the SerDe. The default is `{"field.delim": sep, "escape.delim": "\\"}`. + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). projection_enabled : bool Enable Partition Projection on Athena (https://docs.aws.amazon.com/athena/latest/ug/partition-projection.html) projection_types : Optional[Dict[str, str]] @@ -795,7 +826,7 @@ def create_csv_table( """ session: boto3.Session = _utils.ensure_session(session=boto3_session) catalog_table_input: Optional[Dict[str, Any]] = _get_table_input( - database=database, table=table, boto3_session=session, catalog_id=catalog_id + database=database, table=table, boto3_session=session, transaction_id=transaction_id, catalog_id=catalog_id ) _create_csv_table( database=database, @@ -812,6 +843,7 @@ def create_csv_table( columns_comments=columns_comments, mode=mode, catalog_versioning=catalog_versioning, + transaction_id=transaction_id, projection_enabled=projection_enabled, projection_types=projection_types, projection_ranges=projection_ranges, diff --git a/awswrangler/catalog/_get.py b/awswrangler/catalog/_get.py index f6aab5132..f437cd583 100644 --- a/awswrangler/catalog/_get.py +++ b/awswrangler/catalog/_get.py @@ -18,13 +18,18 @@ def _get_table_input( - database: str, table: str, boto3_session: Optional[boto3.Session], catalog_id: Optional[str] = None + database: str, + table: str, + boto3_session: Optional[boto3.Session], + transaction_id: Optional[str] = None, + catalog_id: Optional[str] = None, ) -> Optional[Dict[str, Any]]: client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) + args: Dict[str, Any] = _catalog_id(catalog_id=catalog_id, DatabaseName=database, Name=table) + if transaction_id: + args["TransactionId"] = transaction_id try: - response: Dict[str, Any] = client_glue.get_table( - **_catalog_id(catalog_id=catalog_id, DatabaseName=database, Name=table) - ) + response: Dict[str, Any] = client_glue.get_table(**args) except client_glue.exceptions.EntityNotFoundException: return None table_input: Dict[str, Any] = {} diff --git a/awswrangler/lakeformation/__init__.py b/awswrangler/lakeformation/__init__.py index 8b8c3084e..6ab8f46b4 100644 --- a/awswrangler/lakeformation/__init__.py +++ b/awswrangler/lakeformation/__init__.py @@ -2,19 +2,27 @@ from awswrangler.lakeformation._read import read_sql_query, read_sql_table # noqa from awswrangler.lakeformation._utils import ( # noqa - abort_transaction, - begin_transaction, + _build_table_objects, + _get_table_objects, + _update_table_objects, + cancel_transaction, commit_transaction, + describe_transaction, extend_transaction, + start_transaction, wait_query, ) __all__ = [ "read_sql_query", "read_sql_table", - "abort_transaction", - "begin_transaction", + "_build_table_objects", + "_get_table_objects", + "_update_table_objects", + "cancel_transaction", "commit_transaction", + "describe_transaction", "extend_transaction", + "start_transaction", "wait_query", ] diff --git a/awswrangler/lakeformation/_read.py b/awswrangler/lakeformation/_read.py index db9b5e6d0..321343ef5 100644 --- a/awswrangler/lakeformation/_read.py +++ b/awswrangler/lakeformation/_read.py @@ -11,12 +11,12 @@ from awswrangler import _data_types, _utils, catalog, exceptions from awswrangler._config import apply_configs from awswrangler.catalog._utils import _catalog_id -from awswrangler.lakeformation._utils import abort_transaction, begin_transaction, wait_query +from awswrangler.lakeformation._utils import cancel_transaction, start_transaction, wait_query _logger: logging.Logger = logging.getLogger(__name__) -def _execute_query( +def _get_work_unit_results( query_id: str, token_work_unit: Tuple[str, int], categories: Optional[List[str]], @@ -27,7 +27,9 @@ def _execute_query( ) -> pd.DataFrame: client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=boto3_session) token, work_unit = token_work_unit - messages: NativeFile = client_lakeformation.execute(QueryId=query_id, Token=token, WorkUnitId=work_unit)["Messages"] + messages: NativeFile = client_lakeformation.get_work_unit_results( + QueryId=query_id, WorkUnitToken=token, WorkUnitId=work_unit + )["ResultStream"] table: Table = RecordBatchStreamReader(messages.read()).read_all() args: Dict[str, Any] = {} if table.num_rows > 0: @@ -70,8 +72,8 @@ def _resolve_sql_query( response = client_lakeformation.get_work_units(**scan_kwargs) token_work_units.extend( # [(Token0, WorkUnitId0), (Token0, WorkUnitId1), (Token1, WorkUnitId2) ... ] [ - (unit["Token"], unit_id) - for unit in response["Units"] + (unit["WorkUnitToken"], unit_id) + for unit in response["WorkUnitRanges"] for unit_id in range(unit["WorkUnitIdMin"], unit["WorkUnitIdMax"] + 1) # Max is inclusive ] ) @@ -81,7 +83,7 @@ def _resolve_sql_query( dfs: List[pd.DataFrame] = list() if use_threads is False: dfs = list( - _execute_query( + _get_work_unit_results( query_id=query_id, token_work_unit=token_work_unit, categories=categories, @@ -97,7 +99,7 @@ def _resolve_sql_query( with concurrent.futures.ThreadPoolExecutor(max_workers=cpus) as executor: dfs = list( executor.map( - _execute_query, + _get_work_unit_results, itertools.repeat(query_id), token_work_units, itertools.repeat(categories), @@ -219,16 +221,16 @@ def read_sql_query( for key, value in params.items(): sql = sql.replace(f":{key};", str(value)) - args: Dict[str, Optional[str]] = _catalog_id(catalog_id=catalog_id, **{"DatabaseName": database, "Statement": sql}) + args: Dict[str, Optional[str]] = _catalog_id(catalog_id=catalog_id, **{"DatabaseName": database}) if query_as_of_time: args["QueryAsOfTime"] = query_as_of_time elif transaction_id: args["TransactionId"] = transaction_id else: - _logger.debug("Neither `transaction_id` nor `query_as_of_time` were specified, beginning transaction") - transaction_id = begin_transaction(read_only=True, boto3_session=session) + _logger.debug("Neither `transaction_id` nor `query_as_of_time` were specified, starting transaction") + transaction_id = start_transaction(read_only=True, boto3_session=session) args["TransactionId"] = transaction_id - query_id: str = client_lakeformation.plan_query(**args)["QueryId"] + query_id: str = client_lakeformation.start_query_planning(QueryString=sql, QueryPlanningContext=args)["QueryId"] try: return _resolve_sql_query( query_id=query_id, @@ -239,9 +241,9 @@ def read_sql_query( boto3_session=session, ) except Exception as ex: - _logger.debug("Aborting transaction with ID: %s.", transaction_id) + _logger.debug("Canceling transaction with ID: %s.", transaction_id) if transaction_id: - abort_transaction(transaction_id=transaction_id, boto3_session=session) + cancel_transaction(transaction_id=transaction_id, boto3_session=session) _logger.error(ex) raise diff --git a/awswrangler/lakeformation/_utils.py b/awswrangler/lakeformation/_utils.py index ea94101bd..1dc8d5ba9 100644 --- a/awswrangler/lakeformation/_utils.py +++ b/awswrangler/lakeformation/_utils.py @@ -1,6 +1,7 @@ """Utilities Module for Amazon Lake Formation.""" import logging import time +from threading import Thread from typing import Any, Dict, List, Optional, Union import boto3 @@ -11,6 +12,7 @@ _QUERY_FINAL_STATES: List[str] = ["ERROR", "FINISHED"] _QUERY_WAIT_POLLING_DELAY: float = 2 # SECONDS +_TRANSACTION_WAIT_POLLING_DELAY: float = 10 # SECONDS _logger: logging.Logger = logging.getLogger(__name__) @@ -118,8 +120,46 @@ def _update_table_objects( client_lakeformation.update_table_objects(**update_kwargs) -def abort_transaction(transaction_id: str, boto3_session: Optional[boto3.Session] = None) -> None: - """Abort the specified transaction. Returns exception if the transaction was previously committed. +def _monitor_transaction(transaction_id: str, boto3_session: Optional[boto3.Session] = None) -> None: + state: str = describe_transaction(transaction_id=transaction_id, boto3_session=boto3_session) + while state == "active": + extend_transaction(transaction_id=transaction_id, boto3_session=boto3_session) + time.sleep(_TRANSACTION_WAIT_POLLING_DELAY) + state = describe_transaction(transaction_id=transaction_id, boto3_session=boto3_session) + _logger.debug("Transaction state: %s", state) + + +def describe_transaction(transaction_id: str, boto3_session: Optional[boto3.Session] = None) -> str: + """Return the status of a single transaction. + + Parameters + ---------- + transaction_id : str + The ID of the transaction. + boto3_session : boto3.Session(), optional + Boto3 Session. The default boto3 session will be used if boto3_session received None. + + Returns + ------- + str + Transaction status (i.e. active|committed|aborted). + + Examples + -------- + >>> import awswrangler as wr + >>> status = wr.lakeformation.describe_transaction(transaction_id="...") + + """ + session: boto3.Session = _utils.ensure_session(session=boto3_session) + client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) + details: Dict[str, Any] = client_lakeformation.describe_transaction(TransactionId=transaction_id)[ + "TransactionDescription" + ] + return details["TransactionStatus"] # type: ignore + + +def cancel_transaction(transaction_id: str, boto3_session: Optional[boto3.Session] = None) -> None: + """Cancel the specified transaction. Returns exception if the transaction was previously committed. Parameters ---------- @@ -136,16 +176,16 @@ def abort_transaction(transaction_id: str, boto3_session: Optional[boto3.Session Examples -------- >>> import awswrangler as wr - >>> wr.lakeformation.abort_transaction(transaction_id="...") + >>> wr.lakeformation.cancel_transaction(transaction_id="...") """ session: boto3.Session = _utils.ensure_session(session=boto3_session) client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) - client_lakeformation.abort_transaction(TransactionId=transaction_id) + client_lakeformation.cancel_transaction(TransactionId=transaction_id) -def begin_transaction(read_only: Optional[bool] = False, boto3_session: Optional[boto3.Session] = None) -> str: +def start_transaction(read_only: Optional[bool] = False, boto3_session: Optional[boto3.Session] = None) -> str: """Start a new transaction and returns its transaction ID. Parameters @@ -165,17 +205,21 @@ def begin_transaction(read_only: Optional[bool] = False, boto3_session: Optional Examples -------- >>> import awswrangler as wr - >>> transaction_id = wr.lakeformation.begin_transaction(read_only=False) + >>> transaction_id = wr.lakeformation.start_transaction(read_only=False) """ session: boto3.Session = _utils.ensure_session(session=boto3_session) client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) - transaction_id: str = client_lakeformation.begin_transaction(ReadOnly=read_only)["TransactionId"] + transaction_type: str = "READ_ONLY" if read_only else "READ_AND_WRITE" + transaction_id: str = client_lakeformation.start_transaction(TransactionType=transaction_type)["TransactionId"] + # Extend the transaction while in "active" state in a separate thread + t = Thread(target=_monitor_transaction, args=(transaction_id, boto3_session)) + t.start() return transaction_id def commit_transaction(transaction_id: str, boto3_session: Optional[boto3.Session] = None) -> None: - """Commit the specified transaction. Returns exception if the transaction was previously aborted. + """Commit the specified transaction. Returns exception if the transaction was previously canceled. Parameters ---------- @@ -202,7 +246,7 @@ def commit_transaction(transaction_id: str, boto3_session: Optional[boto3.Sessio def extend_transaction(transaction_id: str, boto3_session: Optional[boto3.Session] = None) -> None: - """Indicate to the service that the specified transaction is still active and should not be aborted. + """Indicate to the service that the specified transaction is still active and should not be canceled. Parameters ---------- diff --git a/awswrangler/s3/_write_dataset.py b/awswrangler/s3/_write_dataset.py index 577b1426e..c61097309 100644 --- a/awswrangler/s3/_write_dataset.py +++ b/awswrangler/s3/_write_dataset.py @@ -7,15 +7,7 @@ import numpy as np import pandas as pd -from awswrangler import exceptions -from awswrangler.lakeformation._utils import ( - _build_table_objects, - _get_table_objects, - _update_table_objects, - abort_transaction, - begin_transaction, - commit_transaction, -) +from awswrangler import exceptions, lakeformation from awswrangler.s3._delete import delete_objects from awswrangler.s3._write_concurrent import _WriteProxy @@ -51,7 +43,9 @@ def _to_partitions( prefix: str = f"{path_root}{subdir}/" if mode == "overwrite_partitions": if (table_type == "GOVERNED") and (table is not None) and (database is not None): - del_objects: List[Dict[str, Any]] = _get_table_objects( + del_objects: List[ + Dict[str, Any] + ] = lakeformation._get_table_objects( # pylint: disable=protected-access catalog_id=catalog_id, database=database, table=table, @@ -62,7 +56,7 @@ def _to_partitions( boto3_session=boto3_session, ) if del_objects: - _update_table_objects( + lakeformation._update_table_objects( # pylint: disable=protected-access catalog_id=catalog_id, database=database, table=table, @@ -183,14 +177,6 @@ def _to_dataset( ) -> Tuple[List[str], Dict[str, List[str]]]: path_root = path_root if path_root.endswith("/") else f"{path_root}/" - commit_trans: bool = False - if table_type == "GOVERNED": - # Check whether to skip committing the transaction (i.e. multiple read/write operations) - if transaction_id is None: - _logger.debug("`transaction_id` not specified, beginning transaction") - transaction_id = begin_transaction(read_only=False, boto3_session=boto3_session) - commit_trans = True - # Evaluate mode if mode not in ["append", "overwrite", "overwrite_partitions"]: raise exceptions.InvalidArgumentValue( @@ -198,7 +184,7 @@ def _to_dataset( ) if (mode == "overwrite") or ((mode == "overwrite_partitions") and (not partition_cols)): if (table_type == "GOVERNED") and (table is not None) and (database is not None): - del_objects: List[Dict[str, Any]] = _get_table_objects( + del_objects: List[Dict[str, Any]] = lakeformation._get_table_objects( # pylint: disable=protected-access catalog_id=catalog_id, database=database, table=table, @@ -206,7 +192,7 @@ def _to_dataset( boto3_session=boto3_session, ) if del_objects: - _update_table_objects( + lakeformation._update_table_objects( # pylint: disable=protected-access catalog_id=catalog_id, database=database, table=table, @@ -266,12 +252,12 @@ def _to_dataset( _logger.debug("paths: %s", paths) _logger.debug("partitions_values: %s", partitions_values) if (table_type == "GOVERNED") and (table is not None) and (database is not None): - add_objects: List[Dict[str, Any]] = _build_table_objects( + add_objects: List[Dict[str, Any]] = lakeformation._build_table_objects( # pylint: disable=protected-access paths, partitions_values, use_threads=use_threads, boto3_session=boto3_session ) try: if add_objects: - _update_table_objects( + lakeformation._update_table_objects( # pylint: disable=protected-access catalog_id=catalog_id, database=database, table=table, @@ -279,12 +265,7 @@ def _to_dataset( add_objects=add_objects, boto3_session=boto3_session, ) - if commit_trans: - commit_transaction(transaction_id=transaction_id, boto3_session=boto3_session) # type: ignore except Exception as ex: - _logger.debug("Aborting transaction with ID: %s.", transaction_id) - if transaction_id: - abort_transaction(transaction_id=transaction_id, boto3_session=boto3_session) _logger.error(ex) raise diff --git a/awswrangler/s3/_write_parquet.py b/awswrangler/s3/_write_parquet.py index b703e23e9..fd7e5ec80 100644 --- a/awswrangler/s3/_write_parquet.py +++ b/awswrangler/s3/_write_parquet.py @@ -12,7 +12,7 @@ import pyarrow.lib import pyarrow.parquet -from awswrangler import _data_types, _utils, catalog, exceptions +from awswrangler import _data_types, _utils, catalog, exceptions, lakeformation from awswrangler._config import apply_configs from awswrangler.s3._delete import delete_objects from awswrangler.s3._fs import open_s3_object @@ -533,6 +533,7 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b dtype = dtype if dtype else {} partitions_values: Dict[str, List[str]] = {} mode = "append" if mode is None else mode + commit_trans: bool = False if transaction_id: table_type = "GOVERNED" filename_prefix = filename_prefix + uuid.uuid4().hex if filename_prefix else uuid.uuid4().hex @@ -547,7 +548,7 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b catalog_table_input: Optional[Dict[str, Any]] = None if database is not None and table is not None: catalog_table_input = catalog._get_table_input( # pylint: disable=protected-access - database=database, table=table, boto3_session=session, catalog_id=catalog_id + database=database, table=table, boto3_session=session, transaction_id=transaction_id, catalog_id=catalog_id ) catalog_path: Optional[str] = None if catalog_table_input: @@ -565,6 +566,10 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b raise exceptions.InvalidArgumentValue( f"The specified path: {path}, does not match the existing Glue catalog table path: {catalog_path}" ) + if (table_type == "GOVERNED") and (not transaction_id): + _logger.debug("`transaction_id` not specified for GOVERNED table, starting transaction") + transaction_id = lakeformation.start_transaction(read_only=False, boto3_session=boto3_session) + commit_trans = True df = _apply_dtype(df=df, dtype=dtype, catalog_table_input=catalog_table_input, mode=mode) schema: pa.Schema = _data_types.pyarrow_schema_from_pandas( df=df, index=index, ignore_cols=partition_cols, dtype=dtype @@ -610,6 +615,7 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b columns_comments=columns_comments, boto3_session=session, mode=mode, + transaction_id=transaction_id, catalog_versioning=catalog_versioning, projection_enabled=projection_enabled, projection_types=projection_types, @@ -621,7 +627,11 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b catalog_table_input=catalog_table_input, ) catalog_table_input = catalog._get_table_input( # pylint: disable=protected-access - database=database, table=table, boto3_session=session, catalog_id=catalog_id + database=database, + table=table, + boto3_session=session, + transaction_id=transaction_id, + catalog_id=catalog_id, ) paths, partitions_values = _to_dataset( func=_to_parquet, @@ -665,6 +675,7 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b columns_comments=columns_comments, boto3_session=session, mode=mode, + transaction_id=transaction_id, catalog_versioning=catalog_versioning, projection_enabled=projection_enabled, projection_types=projection_types, @@ -687,7 +698,14 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b catalog_id=catalog_id, columns_types=columns_types, ) + if commit_trans: + lakeformation.commit_transaction( + transaction_id=transaction_id, boto3_session=boto3_session # type: ignore + ) except Exception: + if transaction_id: + _logger.debug("Canceling transaction with ID: %s.", transaction_id) + lakeformation.cancel_transaction(transaction_id=transaction_id, boto3_session=boto3_session) _logger.debug("Catalog write failed, cleaning up S3 (paths: %s).", paths) delete_objects( path=paths, diff --git a/awswrangler/s3/_write_text.py b/awswrangler/s3/_write_text.py index 19c4b1455..634e4fc8f 100644 --- a/awswrangler/s3/_write_text.py +++ b/awswrangler/s3/_write_text.py @@ -10,7 +10,7 @@ import pandas as pd from pandas.io.common import infer_compression -from awswrangler import _data_types, _utils, catalog, exceptions +from awswrangler import _data_types, _utils, catalog, exceptions, lakeformation from awswrangler._config import apply_configs from awswrangler.s3._delete import delete_objects from awswrangler.s3._fs import open_s3_object @@ -432,6 +432,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state dtype = dtype if dtype else {} partitions_values: Dict[str, List[str]] = {} mode = "append" if mode is None else mode + commit_trans: bool = False if transaction_id: table_type = "GOVERNED" filename_prefix = filename_prefix + uuid.uuid4().hex if filename_prefix else uuid.uuid4().hex @@ -445,7 +446,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state catalog_table_input: Optional[Dict[str, Any]] = None if database and table: catalog_table_input = catalog._get_table_input( # pylint: disable=protected-access - database=database, table=table, boto3_session=session, catalog_id=catalog_id + database=database, table=table, boto3_session=session, transaction_id=transaction_id, catalog_id=catalog_id ) catalog_path: Optional[str] = None if catalog_table_input: @@ -467,6 +468,10 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state raise exceptions.InvalidArgumentCombination( "If database and table are given, you must use one of these compressions: gzip, bz2 or None." ) + if (table_type == "GOVERNED") and (not transaction_id): + _logger.debug("`transaction_id` not specified for GOVERNED table, starting transaction") + transaction_id = lakeformation.start_transaction(read_only=False, boto3_session=boto3_session) + commit_trans = True df = _apply_dtype(df=df, dtype=dtype, catalog_table_input=catalog_table_input, mode=mode) @@ -527,6 +532,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state columns_comments=columns_comments, boto3_session=session, mode=mode, + transaction_id=transaction_id, catalog_versioning=catalog_versioning, sep=sep, projection_enabled=projection_enabled, @@ -543,7 +549,11 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state serde_parameters=None, ) catalog_table_input = catalog._get_table_input( # pylint: disable=protected-access - database=database, table=table, boto3_session=session, catalog_id=catalog_id + database=database, + table=table, + boto3_session=session, + transaction_id=transaction_id, + catalog_id=catalog_id, ) paths, partitions_values = _to_dataset( func=_to_text, @@ -596,6 +606,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state columns_comments=columns_comments, boto3_session=session, mode=mode, + transaction_id=transaction_id, catalog_versioning=catalog_versioning, sep=sep, projection_enabled=projection_enabled, @@ -626,7 +637,14 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state columns_types=columns_types, compression=pandas_kwargs.get("compression"), ) + if commit_trans: + lakeformation.commit_transaction( + transaction_id=transaction_id, boto3_session=boto3_session # type: ignore + ) except Exception: + if transaction_id: + _logger.debug("Canceling transaction with ID: %s.", transaction_id) + lakeformation.cancel_transaction(transaction_id=transaction_id, boto3_session=boto3_session) _logger.debug("Catalog write failed, cleaning up S3 (paths: %s).", paths) delete_objects( path=paths, diff --git a/tests/test__routines.py b/tests/test__routines.py index 2333037c9..145293e79 100644 --- a/tests/test__routines.py +++ b/tests/test__routines.py @@ -33,7 +33,6 @@ def test_routine_0( use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: @@ -63,7 +62,6 @@ def test_routine_0( use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: @@ -94,7 +92,6 @@ def test_routine_0( use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: @@ -125,7 +122,6 @@ def test_routine_0( use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: @@ -158,7 +154,6 @@ def test_routine_0( use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: @@ -206,7 +201,6 @@ def test_routine_1( use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: @@ -238,7 +232,6 @@ def test_routine_1( concurrent_partitioning=concurrent_partitioning, use_threads=use_threads, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: @@ -271,7 +264,6 @@ def test_routine_1( use_threads=use_threads, concurrent_partitioning=concurrent_partitioning, ) - assert wr.catalog.get_table_number_of_versions(table=glue_table, database=database) == 1 if table_type == "GOVERNED": df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) else: diff --git a/tests/test_lakeformation.py b/tests/test_lakeformation.py index 242cb3a0f..a9b3f3d34 100644 --- a/tests/test_lakeformation.py +++ b/tests/test_lakeformation.py @@ -63,7 +63,7 @@ def test_lakeformation(path, path2, lakeformation_glue_database, glue_table, glu database=lakeformation_glue_database, ) # Read within a transaction - transaction_id = wr.lakeformation.begin_transaction(read_only=True) + transaction_id = wr.lakeformation.start_transaction(read_only=True) df3 = wr.lakeformation.read_sql_table( table=table2, database=lakeformation_glue_database, @@ -96,7 +96,7 @@ def test_lakeformation_multi_transaction( wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table2) df = pd.DataFrame({"c0": [0, None]}, dtype="Int64") - transaction_id = wr.lakeformation.begin_transaction(read_only=False) + transaction_id = wr.lakeformation.start_transaction(read_only=False) wr.s3.to_parquet( df=df, path=path, diff --git a/tutorials/029 - Lake Formation Governed Tables.ipynb b/tutorials/029 - Lake Formation Governed Tables.ipynb index 571b78a89..db02a845d 100644 --- a/tutorials/029 - Lake Formation Governed Tables.ipynb +++ b/tutorials/029 - Lake Formation Governed Tables.ipynb @@ -116,7 +116,7 @@ "metadata": {}, "outputs": [], "source": [ - "transaction_id = wr.lakeformation.begin_transaction(read_only=True)\n", + "transaction_id = wr.lakeformation.start_transaction(read_only=True)\n", "df = wr.lakeformation.read_sql_query(\n", " sql=f\"SELECT * FROM {table};\",\n", " database=database,\n", @@ -402,7 +402,7 @@ "read_table = \"gov_table_parquet\"\n", "write_table = \"gov_table_multi_parquet\"\n", "\n", - "transaction_id = wr.lakeformation.begin_transaction(read_only=False)\n", + "transaction_id = wr.lakeformation.start_transaction(read_only=False)\n", "\n", "df = pd.DataFrame({\"c0\": [0, None]}, dtype=\"Int64\")\n", "wr.s3.to_parquet(\n", From 1382e6ff142b4b9c25da213da78442446dd980d6 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Tue, 25 May 2021 17:21:03 +0100 Subject: [PATCH 10/36] Mmproving read by concatenating zero copies of arrow ttables --- awswrangler/lakeformation/_read.py | 55 +++++++++++------------------- 1 file changed, 20 insertions(+), 35 deletions(-) diff --git a/awswrangler/lakeformation/_read.py b/awswrangler/lakeformation/_read.py index 321343ef5..13be958b0 100644 --- a/awswrangler/lakeformation/_read.py +++ b/awswrangler/lakeformation/_read.py @@ -6,7 +6,7 @@ import boto3 import pandas as pd -from pyarrow import NativeFile, RecordBatchStreamReader, Table +from pyarrow import NativeFile, RecordBatchStreamReader, Table, concat_tables from awswrangler import _data_types, _utils, catalog, exceptions from awswrangler._config import apply_configs @@ -19,34 +19,14 @@ def _get_work_unit_results( query_id: str, token_work_unit: Tuple[str, int], - categories: Optional[List[str]], - safe: bool, - map_types: bool, - use_threads: bool, boto3_session: boto3.Session, -) -> pd.DataFrame: +) -> Table: client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=boto3_session) token, work_unit = token_work_unit messages: NativeFile = client_lakeformation.get_work_unit_results( QueryId=query_id, WorkUnitToken=token, WorkUnitId=work_unit )["ResultStream"] - table: Table = RecordBatchStreamReader(messages.read()).read_all() - args: Dict[str, Any] = {} - if table.num_rows > 0: - args = { - "use_threads": use_threads, - "split_blocks": True, - "self_destruct": True, - "integer_object_nulls": False, - "date_as_object": True, - "ignore_metadata": True, - "strings_to_categorical": False, - "categories": categories, - "safe": safe, - "types_mapper": _data_types.pyarrow2pandas_extension if map_types else None, - } - df: pd.DataFrame = _utils.ensure_df_is_mutable(df=table.to_pandas(**args)) - return df + return RecordBatchStreamReader(messages.read()).read_all() def _resolve_sql_query( @@ -80,16 +60,12 @@ def _resolve_sql_query( next_token = response.get("NextToken", None) scan_kwargs["NextToken"] = next_token - dfs: List[pd.DataFrame] = list() + tables: List[Table] = list() if use_threads is False: - dfs = list( + tables = list( _get_work_unit_results( query_id=query_id, token_work_unit=token_work_unit, - categories=categories, - safe=safe, - map_types=map_types, - use_threads=use_threads, boto3_session=boto3_session, ) for token_work_unit in token_work_units @@ -97,19 +73,28 @@ def _resolve_sql_query( else: cpus: int = _utils.ensure_cpu_count(use_threads=use_threads) with concurrent.futures.ThreadPoolExecutor(max_workers=cpus) as executor: - dfs = list( + tables = list( executor.map( _get_work_unit_results, itertools.repeat(query_id), token_work_units, - itertools.repeat(categories), - itertools.repeat(safe), - itertools.repeat(map_types), - itertools.repeat(use_threads), itertools.repeat(_utils.boto3_to_primitives(boto3_session=boto3_session)), ) ) - return pd.concat([df for df in dfs if not df.empty], sort=False, copy=False, ignore_index=False) + table = concat_tables(tables) + args = { + "use_threads": use_threads, + "split_blocks": True, + "self_destruct": True, + "integer_object_nulls": False, + "date_as_object": True, + "ignore_metadata": True, + "strings_to_categorical": False, + "categories": categories, + "safe": safe, + "types_mapper": _data_types.pyarrow2pandas_extension if map_types else None, + } + return _utils.ensure_df_is_mutable(df=table.to_pandas(**args)) @apply_configs From c947a268fbfb9fd034737c8071a0d5359d0dfe8f Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Thu, 27 May 2021 18:38:31 +0100 Subject: [PATCH 11/36] [skip ci] - Minor - Killing thread --- awswrangler/lakeformation/_read.py | 2 +- awswrangler/lakeformation/_utils.py | 4 +++- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/awswrangler/lakeformation/_read.py b/awswrangler/lakeformation/_read.py index 13be958b0..1517206b6 100644 --- a/awswrangler/lakeformation/_read.py +++ b/awswrangler/lakeformation/_read.py @@ -215,8 +215,8 @@ def read_sql_query( _logger.debug("Neither `transaction_id` nor `query_as_of_time` were specified, starting transaction") transaction_id = start_transaction(read_only=True, boto3_session=session) args["TransactionId"] = transaction_id - query_id: str = client_lakeformation.start_query_planning(QueryString=sql, QueryPlanningContext=args)["QueryId"] try: + query_id: str = client_lakeformation.start_query_planning(QueryString=sql, QueryPlanningContext=args)["QueryId"] return _resolve_sql_query( query_id=query_id, categories=categories, diff --git a/awswrangler/lakeformation/_utils.py b/awswrangler/lakeformation/_utils.py index 1dc8d5ba9..4f7d28789 100644 --- a/awswrangler/lakeformation/_utils.py +++ b/awswrangler/lakeformation/_utils.py @@ -12,6 +12,7 @@ _QUERY_FINAL_STATES: List[str] = ["ERROR", "FINISHED"] _QUERY_WAIT_POLLING_DELAY: float = 2 # SECONDS +_TRANSACTION_FINAL_STATES: List[str] = ["aborted", "committed"] _TRANSACTION_WAIT_POLLING_DELAY: float = 10 # SECONDS _logger: logging.Logger = logging.getLogger(__name__) @@ -122,7 +123,7 @@ def _update_table_objects( def _monitor_transaction(transaction_id: str, boto3_session: Optional[boto3.Session] = None) -> None: state: str = describe_transaction(transaction_id=transaction_id, boto3_session=boto3_session) - while state == "active": + while state not in _TRANSACTION_FINAL_STATES: extend_transaction(transaction_id=transaction_id, boto3_session=boto3_session) time.sleep(_TRANSACTION_WAIT_POLLING_DELAY) state = describe_transaction(transaction_id=transaction_id, boto3_session=boto3_session) @@ -214,6 +215,7 @@ def start_transaction(read_only: Optional[bool] = False, boto3_session: Optional transaction_id: str = client_lakeformation.start_transaction(TransactionType=transaction_type)["TransactionId"] # Extend the transaction while in "active" state in a separate thread t = Thread(target=_monitor_transaction, args=(transaction_id, boto3_session)) + t.daemon = True # Ensures thread is killed when any exception is raised t.start() return transaction_id From b20f3e4fb6296b9cfce0c636ce4af9633088a0ef Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Fri, 28 May 2021 16:25:13 +0100 Subject: [PATCH 12/36] [skip ci] - Minor - Passing client instead of session --- awswrangler/lakeformation/_read.py | 7 +++---- 1 file changed, 3 insertions(+), 4 deletions(-) diff --git a/awswrangler/lakeformation/_read.py b/awswrangler/lakeformation/_read.py index 1517206b6..42fa97006 100644 --- a/awswrangler/lakeformation/_read.py +++ b/awswrangler/lakeformation/_read.py @@ -19,9 +19,8 @@ def _get_work_unit_results( query_id: str, token_work_unit: Tuple[str, int], - boto3_session: boto3.Session, + client_lakeformation: boto3.client, ) -> Table: - client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=boto3_session) token, work_unit = token_work_unit messages: NativeFile = client_lakeformation.get_work_unit_results( QueryId=query_id, WorkUnitToken=token, WorkUnitId=work_unit @@ -66,7 +65,7 @@ def _resolve_sql_query( _get_work_unit_results( query_id=query_id, token_work_unit=token_work_unit, - boto3_session=boto3_session, + client_lakeformation=client_lakeformation, ) for token_work_unit in token_work_units ) @@ -78,7 +77,7 @@ def _resolve_sql_query( _get_work_unit_results, itertools.repeat(query_id), token_work_units, - itertools.repeat(_utils.boto3_to_primitives(boto3_session=boto3_session)), + itertools.repeat(client_lakeformation), ) ) table = concat_tables(tables) From 9fca3db6e8c5be42fb092f23608f6b07beecbad7 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Sat, 5 Jun 2021 15:09:48 +0100 Subject: [PATCH 13/36] Major - Adding Metadata Transaction API changes --- CONTRIBUTING.md | 11 -- awswrangler/catalog/_add.py | 17 +- awswrangler/catalog/_create.py | 63 +++++--- awswrangler/catalog/_delete.py | 33 +++- awswrangler/catalog/_get.py | 236 ++++++++++++++++++++++------ awswrangler/catalog/_utils.py | 23 ++- awswrangler/lakeformation/_read.py | 68 ++++---- awswrangler/lakeformation/_utils.py | 34 +++- awswrangler/s3/_write_parquet.py | 3 - awswrangler/s3/_write_text.py | 3 - cloudformation/base.yaml | 113 +------------ tests/conftest.py | 5 - tests/test__routines.py | 112 ++++++------- tests/test_athena.py | 8 +- tests/test_athena_parquet.py | 4 +- tests/test_catalog.py | 172 ++++++++++++++------ tests/test_lakeformation.py | 66 ++++---- tests/test_s3.py | 2 +- tests/test_s3_parquet.py | 8 +- 19 files changed, 570 insertions(+), 411 deletions(-) diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 375fbc0e4..5fbb71400 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -238,17 +238,6 @@ or ``./cloudformation/delete-databases.sh`` -### Enabling Lake Formation: -If your feature is related to AWS Lake Formation, there are a number of additional steps required in order to complete testing: - -1. In the AWS console, enable Lake Formation by setting your IAM role as an Administrator and by unchecking the boxes in the ``Data Catalog Settings`` section - -2. In the ``./cloudformation/base.yaml`` template file, set ``EnableLakeFormation`` to ``True``. Then run the ``./deploy-base.sh`` once more to add an AWS Glue Database and an S3 bucket registered with Lake Formation - -3. Back in the console, in the ``Data Locations`` section, grant your IAM role access to the S3 Lake Formation bucket (``s3://aws-wrangler-base-lakeformation...``) - -4. Finally, in the ``Data Permissions`` section, grant your IAM role ``Super`` permissions on both the ``aws_data_wrangler`` and ``aws_data_wrangler_lakeformation`` databases - ## Recommended Visual Studio Code Recommended setting ```json diff --git a/awswrangler/catalog/_add.py b/awswrangler/catalog/_add.py index 01f30200e..07a529efb 100644 --- a/awswrangler/catalog/_add.py +++ b/awswrangler/catalog/_add.py @@ -13,7 +13,7 @@ _parquet_partition_definition, _update_table_definition, ) -from awswrangler.catalog._utils import _catalog_id, sanitize_table_name +from awswrangler.catalog._utils import _catalog_id, _transaction_id, sanitize_table_name _logger: logging.Logger = logging.getLogger(__name__) @@ -205,6 +205,7 @@ def add_column( column_name: str, column_type: str = "string", column_comment: Optional[str] = None, + transaction_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None, catalog_id: Optional[str] = None, ) -> None: @@ -222,6 +223,8 @@ def add_column( Column type. column_comment : str Column Comment + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. catalog_id : str, optional @@ -245,13 +248,21 @@ def add_column( """ if _check_column_type(column_type): client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) - table_res: Dict[str, Any] = client_glue.get_table(DatabaseName=database, Name=table) + table_res: Dict[str, Any] = client_glue.get_table( + **_catalog_id( + catalog_id=catalog_id, + **_transaction_id(transaction_id=transaction_id, DatabaseName=database, Name=table), + ) + ) table_input: Dict[str, Any] = _update_table_definition(table_res) table_input["StorageDescriptor"]["Columns"].append( {"Name": column_name, "Type": column_type, "Comment": column_comment} ) res: Dict[str, Any] = client_glue.update_table( - **_catalog_id(catalog_id=catalog_id, DatabaseName=database, TableInput=table_input) + **_catalog_id( + catalog_id=catalog_id, + **_transaction_id(transaction_id=transaction_id, DatabaseName=database, TableInput=table_input), + ) ) if ("Errors" in res) and res["Errors"]: for error in res["Errors"]: diff --git a/awswrangler/catalog/_create.py b/awswrangler/catalog/_create.py index 8cb445a09..0418c2868 100644 --- a/awswrangler/catalog/_create.py +++ b/awswrangler/catalog/_create.py @@ -10,8 +10,7 @@ from awswrangler.catalog._definitions import _csv_table_definition, _parquet_table_definition from awswrangler.catalog._delete import delete_all_partitions, delete_table_if_exists from awswrangler.catalog._get import _get_table_input -from awswrangler.catalog._utils import _catalog_id, sanitize_column_name, sanitize_table_name -from awswrangler.lakeformation._utils import commit_transaction, start_transaction +from awswrangler.catalog._utils import _catalog_id, _transaction_id, sanitize_column_name, sanitize_table_name _logger: logging.Logger = logging.getLogger(__name__) @@ -122,21 +121,12 @@ def _create_table( # pylint: disable=too-many-branches,too-many-statements,too- ) args: Dict[str, Any] = _catalog_id( catalog_id=catalog_id, - DatabaseName=database, - TableInput=table_input, + **_transaction_id( + transaction_id=transaction_id, + DatabaseName=database, + TableInput=table_input, + ), ) - commit_trans: bool = False - if transaction_id: - if table_type != "GOVERNED": - raise exceptions.InvalidTable( - f"A transaction ID was provided but `{database}`.`{table}` is not a GOVERNED table." - ) - args["TransactionId"] = transaction_id - if (table_type == "GOVERNED") and (not transaction_id): - _logger.debug("`transaction_id` not specified for GOVERNED table, starting transaction") - transaction_id = start_transaction(read_only=False, boto3_session=session) - args["TransactionId"] = transaction_id - commit_trans = True if table_exist: _logger.debug("Updating table (%s)...", mode) args["SkipArchive"] = skip_archive @@ -163,8 +153,6 @@ def _create_table( # pylint: disable=too-many-branches,too-many-statements,too- transaction_id=transaction_id, boto3_session=boto3_session, ) - if commit_trans: - commit_transaction(transaction_id=transaction_id) # type: ignore _logger.debug("Leaving table as is (%s)...", mode) @@ -177,20 +165,28 @@ def _overwrite_table( transaction_id: Optional[str], boto3_session: boto3.Session, ) -> None: - delete_table_if_exists(database=database, table=table, boto3_session=boto3_session, catalog_id=catalog_id) + delete_table_if_exists( + database=database, + table=table, + transaction_id=transaction_id, + boto3_session=boto3_session, + catalog_id=catalog_id, + ) args: Dict[str, Any] = _catalog_id( catalog_id=catalog_id, - DatabaseName=database, - TableInput=table_input, + **_transaction_id( + transaction_id=transaction_id, + DatabaseName=database, + TableInput=table_input, + ), ) - if transaction_id: - args["TransactionId"] = transaction_id client_glue.create_table(**args) def _upsert_table_parameters( parameters: Dict[str, str], database: str, + transaction_id: Optional[str], catalog_versioning: bool, catalog_id: Optional[str], table_input: Dict[str, Any], @@ -206,6 +202,7 @@ def _upsert_table_parameters( _overwrite_table_parameters( parameters=pars, database=database, + transaction_id=transaction_id, catalog_id=catalog_id, boto3_session=boto3_session, table_input=table_input, @@ -217,6 +214,7 @@ def _upsert_table_parameters( def _overwrite_table_parameters( parameters: Dict[str, str], database: str, + transaction_id: Optional[str], catalog_versioning: bool, catalog_id: Optional[str], table_input: Dict[str, Any], @@ -226,7 +224,12 @@ def _overwrite_table_parameters( client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) skip_archive: bool = not catalog_versioning client_glue.update_table( - **_catalog_id(catalog_id=catalog_id, DatabaseName=database, TableInput=table_input, SkipArchive=skip_archive) + **_catalog_id( + catalog_id=catalog_id, + **_transaction_id( + transaction_id=transaction_id, DatabaseName=database, TableInput=table_input, SkipArchive=skip_archive + ), + ) ) return parameters @@ -395,6 +398,7 @@ def upsert_table_parameters( parameters: Dict[str, str], database: str, table: str, + transaction_id: Optional[str] = None, catalog_versioning: bool = False, catalog_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None, @@ -409,6 +413,8 @@ def upsert_table_parameters( Database name. table : str Table name. + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). catalog_versioning : bool If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. catalog_id : str, optional @@ -433,7 +439,7 @@ def upsert_table_parameters( """ session: boto3.Session = _utils.ensure_session(session=boto3_session) table_input: Optional[Dict[str, str]] = _get_table_input( - database=database, table=table, boto3_session=session, catalog_id=catalog_id + database=database, table=table, boto3_session=session, transaction_id=transaction_id, catalog_id=catalog_id ) if table_input is None: raise exceptions.InvalidArgumentValue(f"Table {database}.{table} does not exist.") @@ -441,6 +447,7 @@ def upsert_table_parameters( parameters=parameters, database=database, boto3_session=session, + transaction_id=transaction_id, catalog_id=catalog_id, table_input=table_input, catalog_versioning=catalog_versioning, @@ -452,6 +459,7 @@ def overwrite_table_parameters( parameters: Dict[str, str], database: str, table: str, + transaction_id: Optional[str] = None, catalog_versioning: bool = False, catalog_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None, @@ -466,6 +474,8 @@ def overwrite_table_parameters( Database name. table : str Table name. + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). catalog_versioning : bool If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. catalog_id : str, optional @@ -490,7 +500,7 @@ def overwrite_table_parameters( """ session: boto3.Session = _utils.ensure_session(session=boto3_session) table_input: Optional[Dict[str, Any]] = _get_table_input( - database=database, table=table, catalog_id=catalog_id, boto3_session=session + database=database, table=table, transaction_id=transaction_id, catalog_id=catalog_id, boto3_session=session ) if table_input is None: raise exceptions.InvalidTable(f"Table {table} does not exist on database {database}.") @@ -498,6 +508,7 @@ def overwrite_table_parameters( parameters=parameters, database=database, catalog_id=catalog_id, + transaction_id=transaction_id, table_input=table_input, boto3_session=session, catalog_versioning=catalog_versioning, diff --git a/awswrangler/catalog/_delete.py b/awswrangler/catalog/_delete.py index 5436e8346..27bdb07e8 100644 --- a/awswrangler/catalog/_delete.py +++ b/awswrangler/catalog/_delete.py @@ -9,7 +9,7 @@ from awswrangler._config import apply_configs from awswrangler.catalog._definitions import _update_table_definition from awswrangler.catalog._get import _get_partitions -from awswrangler.catalog._utils import _catalog_id +from awswrangler.catalog._utils import _catalog_id, _transaction_id _logger: logging.Logger = logging.getLogger(__name__) @@ -46,7 +46,11 @@ def delete_database(name: str, catalog_id: Optional[str] = None, boto3_session: @apply_configs def delete_table_if_exists( - database: str, table: str, catalog_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None + database: str, + table: str, + transaction_id: Optional[str] = None, + catalog_id: Optional[str] = None, + boto3_session: Optional[boto3.Session] = None, ) -> bool: """Delete Glue table if exists. @@ -56,6 +60,8 @@ def delete_table_if_exists( Database name. table : str Table name. + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). catalog_id : str, optional The ID of the Data Catalog from which to retrieve Databases. If none is provided, the AWS account ID is used by default. @@ -78,7 +84,13 @@ def delete_table_if_exists( """ client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) try: - client_glue.delete_table(**_catalog_id(DatabaseName=database, Name=table, catalog_id=catalog_id)) + client_glue.delete_table( + **_catalog_id( + **_transaction_id( + transaction_id=transaction_id, DatabaseName=database, Name=table, catalog_id=catalog_id + ) + ) + ) return True except client_glue.exceptions.EntityNotFoundException: return False @@ -189,6 +201,7 @@ def delete_column( database: str, table: str, column_name: str, + transaction_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None, catalog_id: Optional[str] = None, ) -> None: @@ -202,6 +215,8 @@ def delete_column( Table name. column_name : str Column name + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. catalog_id : str, optional @@ -223,13 +238,21 @@ def delete_column( ... ) """ client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) - table_res: Dict[str, Any] = client_glue.get_table(DatabaseName=database, Name=table) + table_res: Dict[str, Any] = client_glue.get_table( + **_catalog_id( + catalog_id=catalog_id, + **_transaction_id(transaction_id=transaction_id, DatabaseName=database, Name=table), + ) + ) table_input: Dict[str, Any] = _update_table_definition(table_res) table_input["StorageDescriptor"]["Columns"] = [ i for i in table_input["StorageDescriptor"]["Columns"] if i["Name"] != column_name ] res: Dict[str, Any] = client_glue.update_table( - **_catalog_id(catalog_id=catalog_id, DatabaseName=database, TableInput=table_input) + **_catalog_id( + catalog_id=catalog_id, + **_transaction_id(transaction_id=transaction_id, DatabaseName=database, TableInput=table_input), + ) ) if ("Errors" in res) and res["Errors"]: for error in res["Errors"]: diff --git a/awswrangler/catalog/_get.py b/awswrangler/catalog/_get.py index f437cd583..489886692 100644 --- a/awswrangler/catalog/_get.py +++ b/awswrangler/catalog/_get.py @@ -12,7 +12,7 @@ from awswrangler import _utils, exceptions from awswrangler._config import apply_configs -from awswrangler.catalog._utils import _catalog_id, _extract_dtypes_from_table_details +from awswrangler.catalog._utils import _catalog_id, _extract_dtypes_from_table_details, _transaction_id _logger: logging.Logger = logging.getLogger(__name__) @@ -25,9 +25,9 @@ def _get_table_input( catalog_id: Optional[str] = None, ) -> Optional[Dict[str, Any]]: client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) - args: Dict[str, Any] = _catalog_id(catalog_id=catalog_id, DatabaseName=database, Name=table) - if transaction_id: - args["TransactionId"] = transaction_id + args: Dict[str, Any] = _catalog_id( + catalog_id=catalog_id, **_transaction_id(transaction_id=transaction_id, DatabaseName=database, Name=table) + ) try: response: Dict[str, Any] = client_glue.get_table(**args) except client_glue.exceptions.EntityNotFoundException: @@ -76,16 +76,15 @@ def _get_partitions( ) -> Dict[str, List[str]]: client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) - args: Dict[str, Any] = { - "DatabaseName": database, - "TableName": table, - "MaxResults": 1_000, - "Segment": {"SegmentNumber": 0, "TotalSegments": 1}, - } + args: Dict[str, Any] = _catalog_id( + catalog_id=catalog_id, + DatabaseName=database, + TableName=table, + MaxResults=1_000, + Segment={"SegmentNumber": 0, "TotalSegments": 1}, + ) if expression is not None: args["Expression"] = expression - if catalog_id is not None: - args["CatalogId"] = catalog_id partitions_values: Dict[str, List[str]] = {} _logger.debug("Starting pagination...") @@ -103,17 +102,34 @@ def _get_partitions( @apply_configs def get_table_types( - database: str, table: str, boto3_session: Optional[boto3.Session] = None + database: str, + table: str, + transaction_id: Optional[str] = None, + query_as_of_time: Optional[str] = None, + catalog_id: Optional[str] = None, + boto3_session: Optional[boto3.Session] = None, ) -> Optional[Dict[str, str]]: """Get all columns and types from a table. + Note + ---- + If reading from a governed table, pass only one of `transaction_id` or `query_as_of_time`. + Parameters ---------- - database : str + database: str Database name. - table : str + table: str Table name. - boto3_session : boto3.Session(), optional + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). + query_as_of_time: str, optional + The time as of when to read the table contents. Must be a valid Unix epoch timestamp. + Cannot be specified alongside transaction_id. + catalog_id: str, optional + The ID of the Data Catalog from which to retrieve Databases. + If none is provided, the AWS account ID is used by default. + boto3_session: boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. Returns @@ -130,7 +146,14 @@ def get_table_types( """ client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) try: - response: Dict[str, Any] = client_glue.get_table(DatabaseName=database, Name=table) + response: Dict[str, Any] = client_glue.get_table( + **_catalog_id( + catalog_id=catalog_id, + **_transaction_id( + transaction_id=transaction_id, query_as_of_time=query_as_of_time, DatabaseName=database, Name=table + ), + ) + ) except client_glue.exceptions.EntityNotFoundException: return None return _extract_dtypes_from_table_details(response=response) @@ -208,6 +231,7 @@ def databases( def get_tables( catalog_id: Optional[str] = None, database: Optional[str] = None, + transaction_id: Optional[str] = None, name_contains: Optional[str] = None, name_prefix: Optional[str] = None, name_suffix: Optional[str] = None, @@ -227,6 +251,8 @@ def get_tables( If none is provided, the AWS account ID is used by default. database : str, optional Database name. + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). name_contains : str, optional Select by a specific string on table name name_prefix : str, optional @@ -250,8 +276,6 @@ def get_tables( client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) paginator = client_glue.get_paginator("get_tables") args: Dict[str, str] = {} - if catalog_id is not None: - args["CatalogId"] = catalog_id if (name_prefix is not None) and (name_suffix is not None) and (name_contains is not None): raise exceptions.InvalidArgumentCombination( "Please, does not filter using name_contains and " @@ -272,7 +296,9 @@ def get_tables( dbs = [x["Name"] for x in get_databases(catalog_id=catalog_id)] for db in dbs: args["DatabaseName"] = db - response_iterator = paginator.paginate(**args) + response_iterator = paginator.paginate( + **_catalog_id(catalog_id=catalog_id, **_transaction_id(transaction_id=transaction_id, **args)) + ) try: for page in response_iterator: for tbl in page["TableList"]: @@ -347,11 +373,19 @@ def tables( tbls = [x for x in tbls if x["Name"].endswith(name_suffix)] tbls = tbls[:limit] - df_dict: Dict[str, List[str]] = {"Database": [], "Table": [], "Description": [], "Columns": [], "Partitions": []} + df_dict: Dict[str, List[str]] = { + "Database": [], + "Table": [], + "Description": [], + "TableType": [], + "Columns": [], + "Partitions": [], + } for tbl in tbls: df_dict["Database"].append(tbl["DatabaseName"]) df_dict["Table"].append(tbl["Name"]) df_dict["Description"].append(tbl.get("Description", "")) + df_dict["TableType"].append(tbl.get("TableType", "")) if "Columns" in tbl["StorageDescriptor"]: df_dict["Columns"].append(", ".join([x["Name"] for x in tbl["StorageDescriptor"]["Columns"]])) else: @@ -390,9 +424,7 @@ def search_tables( """ client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) - args: Dict[str, Any] = {"SearchText": text} - if catalog_id is not None: - args["CatalogId"] = catalog_id + args: Dict[str, Any] = _catalog_id(catalog_id=catalog_id, SearchText=text) response: Dict[str, Any] = client_glue.search_tables(**args) for tbl in response["TableList"]: yield tbl @@ -405,20 +437,34 @@ def search_tables( @apply_configs def table( - database: str, table: str, catalog_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None + database: str, + table: str, + transaction_id: Optional[str] = None, + query_as_of_time: Optional[str] = None, + catalog_id: Optional[str] = None, + boto3_session: Optional[boto3.Session] = None, ) -> pd.DataFrame: """Get table details as Pandas DataFrame. + Note + ---- + If reading from a governed table, pass only one of `transaction_id` or `query_as_of_time`. + Parameters ---------- - database : str + database: str Database name. - table : str + table: str Table name. - catalog_id : str, optional + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). + query_as_of_time: str, optional + The time as of when to read the table contents. Must be a valid Unix epoch timestamp. + Cannot be specified alongside transaction_id. + catalog_id: str, optional The ID of the Data Catalog from which to retrieve Databases. If none is provided, the AWS account ID is used by default. - boto3_session : boto3.Session(), optional + boto3_session: boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. Returns @@ -433,7 +479,14 @@ def table( """ client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) - tbl = client_glue.get_table(**_catalog_id(catalog_id=catalog_id, DatabaseName=database, Name=table))["Table"] + tbl = client_glue.get_table( + **_catalog_id( + catalog_id=catalog_id, + **_transaction_id( + transaction_id=transaction_id, query_as_of_time=query_as_of_time, DatabaseName=database, Name=table + ), + ) + )["Table"] df_dict: Dict[str, List[Union[str, bool]]] = {"Column Name": [], "Type": [], "Partition": [], "Comment": []} for col in tbl["StorageDescriptor"]["Columns"]: df_dict["Column Name"].append(col["Name"]) @@ -456,16 +509,35 @@ def table( @apply_configs -def get_table_location(database: str, table: str, boto3_session: Optional[boto3.Session] = None) -> str: +def get_table_location( + database: str, + table: str, + transaction_id: Optional[str] = None, + query_as_of_time: Optional[str] = None, + catalog_id: Optional[str] = None, + boto3_session: Optional[boto3.Session] = None, +) -> str: """Get table's location on Glue catalog. + Note + ---- + If reading from a governed table, pass only one of `transaction_id` or `query_as_of_time`. + Parameters ---------- - database : str + database: str Database name. - table : str + table: str Table name. - boto3_session : boto3.Session(), optional + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). + query_as_of_time: str, optional + The time as of when to read the table contents. Must be a valid Unix epoch timestamp. + Cannot be specified alongside transaction_id. + catalog_id: str, optional + The ID of the Data Catalog from which to retrieve Databases. + If none is provided, the AWS account ID is used by default. + boto3_session: boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. Returns @@ -481,7 +553,14 @@ def get_table_location(database: str, table: str, boto3_session: Optional[boto3. """ client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) - res: Dict[str, Any] = client_glue.get_table(DatabaseName=database, Name=table) + res: Dict[str, Any] = client_glue.get_table( + **_catalog_id( + catalog_id=catalog_id, + **_transaction_id( + transaction_id=transaction_id, query_as_of_time=query_as_of_time, DatabaseName=database, Name=table + ), + ) + ) try: return cast(str, res["Table"]["StorageDescriptor"]["Location"]) except KeyError as ex: @@ -596,7 +675,11 @@ def get_parquet_partitions( """ return _get_partitions( - database=database, table=table, expression=expression, catalog_id=catalog_id, boto3_session=boto3_session + database=database, + table=table, + expression=expression, + catalog_id=catalog_id, + boto3_session=boto3_session, ) @@ -662,7 +745,11 @@ def get_csv_partitions( """ return _get_partitions( - database=database, table=table, expression=expression, catalog_id=catalog_id, boto3_session=boto3_session + database=database, + table=table, + expression=expression, + catalog_id=catalog_id, + boto3_session=boto3_session, ) @@ -728,21 +815,39 @@ def get_partitions( """ return _get_partitions( - database=database, table=table, expression=expression, catalog_id=catalog_id, boto3_session=boto3_session + database=database, + table=table, + expression=expression, + catalog_id=catalog_id, + boto3_session=boto3_session, ) def get_table_parameters( - database: str, table: str, catalog_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None + database: str, + table: str, + transaction_id: Optional[str] = None, + query_as_of_time: Optional[str] = None, + catalog_id: Optional[str] = None, + boto3_session: Optional[boto3.Session] = None, ) -> Dict[str, str]: """Get all parameters. + Note + ---- + If reading from a governed table, pass only one of `transaction_id` or `query_as_of_time`. + Parameters ---------- database : str Database name. table : str Table name. + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). + query_as_of_time : str, optional + The time as of when to read the table contents. Must be a valid Unix epoch timestamp. + Cannot be specified alongside transaction_id. catalog_id : str, optional The ID of the Data Catalog from which to retrieve Databases. If none is provided, the AWS account ID is used by default. @@ -762,23 +867,42 @@ def get_table_parameters( """ client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) response: Dict[str, Any] = client_glue.get_table( - **_catalog_id(catalog_id=catalog_id, DatabaseName=database, Name=table) + **_catalog_id( + catalog_id=catalog_id, + **_transaction_id( + transaction_id=transaction_id, query_as_of_time=query_as_of_time, DatabaseName=database, Name=table + ), + ) ) parameters: Dict[str, str] = response["Table"]["Parameters"] return parameters def get_table_description( - database: str, table: str, catalog_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None + database: str, + table: str, + transaction_id: Optional[str] = None, + query_as_of_time: Optional[str] = None, + catalog_id: Optional[str] = None, + boto3_session: Optional[boto3.Session] = None, ) -> Optional[str]: """Get table description. + Note + ---- + If reading from a governed table, pass only one of `transaction_id` or `query_as_of_time`. + Parameters ---------- database : str Database name. table : str Table name. + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). + query_as_of_time: str, optional + The time as of when to read the table contents. Must be a valid Unix epoch timestamp. + Cannot be specified alongside transaction_id. catalog_id : str, optional The ID of the Data Catalog from which to retrieve Databases. If none is provided, the AWS account ID is used by default. @@ -798,7 +922,12 @@ def get_table_description( """ client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) response: Dict[str, Any] = client_glue.get_table( - **_catalog_id(catalog_id=catalog_id, DatabaseName=database, Name=table) + **_catalog_id( + catalog_id=catalog_id, + **_transaction_id( + transaction_id=transaction_id, query_as_of_time=query_as_of_time, DatabaseName=database, Name=table + ), + ) ) desc: Optional[str] = response["Table"].get("Description", None) return desc @@ -806,16 +935,30 @@ def get_table_description( @apply_configs def get_columns_comments( - database: str, table: str, catalog_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None + database: str, + table: str, + transaction_id: Optional[str] = None, + query_as_of_time: Optional[str] = None, + catalog_id: Optional[str] = None, + boto3_session: Optional[boto3.Session] = None, ) -> Dict[str, str]: """Get all columns comments. + Note + ---- + If reading from a governed table, pass only one of `transaction_id` or `query_as_of_time`. + Parameters ---------- database : str Database name. table : str Table name. + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). + query_as_of_time: str, optional + The time as of when to read the table contents. Must be a valid Unix epoch timestamp. + Cannot be specified alongside transaction_id. catalog_id : str, optional The ID of the Data Catalog from which to retrieve Databases. If none is provided, the AWS account ID is used by default. @@ -835,7 +978,12 @@ def get_columns_comments( """ client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) response: Dict[str, Any] = client_glue.get_table( - **_catalog_id(catalog_id=catalog_id, DatabaseName=database, Name=table) + **_catalog_id( + catalog_id=catalog_id, + **_transaction_id( + transaction_id=transaction_id, query_as_of_time=query_as_of_time, DatabaseName=database, Name=table + ), + ) ) comments: Dict[str, str] = {} for c in response["Table"]["StorageDescriptor"]["Columns"]: diff --git a/awswrangler/catalog/_utils.py b/awswrangler/catalog/_utils.py index bad4e016f..4679c60e2 100644 --- a/awswrangler/catalog/_utils.py +++ b/awswrangler/catalog/_utils.py @@ -19,6 +19,20 @@ def _catalog_id(catalog_id: Optional[str] = None, **kwargs: Any) -> Dict[str, An return kwargs +def _transaction_id( + transaction_id: Optional[str] = None, query_as_of_time: Optional[str] = None, **kwargs: Any +) -> Dict[str, Any]: + if transaction_id is not None and query_as_of_time is not None: + raise exceptions.InvalidArgumentCombination( + "Please pass only one of `transaction_id` or `query_as_of_time`, not both" + ) + if transaction_id is not None: + kwargs["TransactionId"] = transaction_id + elif query_as_of_time is not None: + kwargs["QueryAsOfTime"] = query_as_of_time + return kwargs + + def _sanitize_name(name: str) -> str: name = "".join(c for c in unicodedata.normalize("NFD", name) if unicodedata.category(c) != "Mn") # strip accents return re.sub("[^A-Za-z0-9_]+", "_", name).lower() # Replacing non alphanumeric characters by underscore @@ -35,7 +49,9 @@ def _extract_dtypes_from_table_details(response: Dict[str, Any]) -> Dict[str, st @apply_configs -def does_table_exist(database: str, table: str, boto3_session: Optional[boto3.Session] = None) -> bool: +def does_table_exist( + database: str, table: str, boto3_session: Optional[boto3.Session] = None, catalog_id: Optional[str] = None +) -> bool: """Check if the table exists. Parameters @@ -46,6 +62,9 @@ def does_table_exist(database: str, table: str, boto3_session: Optional[boto3.Se Table name. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. + catalog_id : str, optional + The ID of the Data Catalog from which to retrieve Databases. + If none is provided, the AWS account ID is used by default. Returns ------- @@ -60,7 +79,7 @@ def does_table_exist(database: str, table: str, boto3_session: Optional[boto3.Se """ client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) try: - client_glue.get_table(DatabaseName=database, Name=table) + client_glue.get_table(**_catalog_id(catalog_id=catalog_id, DatabaseName=database, Name=table)) return True except client_glue.exceptions.EntityNotFoundException: return False diff --git a/awswrangler/lakeformation/_read.py b/awswrangler/lakeformation/_read.py index 42fa97006..2468dbd4f 100644 --- a/awswrangler/lakeformation/_read.py +++ b/awswrangler/lakeformation/_read.py @@ -2,16 +2,16 @@ import concurrent.futures import itertools import logging -from typing import Any, Dict, Iterator, List, Optional, Tuple, Union +from typing import Any, Dict, List, Optional, Tuple, Union import boto3 import pandas as pd from pyarrow import NativeFile, RecordBatchStreamReader, Table, concat_tables -from awswrangler import _data_types, _utils, catalog, exceptions +from awswrangler import _data_types, _utils, catalog from awswrangler._config import apply_configs -from awswrangler.catalog._utils import _catalog_id -from awswrangler.lakeformation._utils import cancel_transaction, start_transaction, wait_query +from awswrangler.catalog._utils import _catalog_id, _transaction_id +from awswrangler.lakeformation._utils import commit_transaction, start_transaction, wait_query _logger: logging.Logger = logging.getLogger(__name__) @@ -35,7 +35,7 @@ def _resolve_sql_query( map_types: bool, use_threads: bool, boto3_session: boto3.Session, -) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: +) -> pd.DataFrame: client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=boto3_session) wait_query(query_id=query_id, boto3_session=boto3_session) @@ -109,7 +109,7 @@ def read_sql_query( use_threads: bool = True, boto3_session: Optional[boto3.Session] = None, params: Optional[Dict[str, Any]] = None, -) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: +) -> pd.DataFrame: """Execute PartiQL query on AWS Glue Table (Transaction ID or time travel timestamp). Return Pandas DataFrame. Note @@ -166,8 +166,8 @@ def read_sql_query( Returns ------- - Union[pd.DataFrame, Iterator[pd.DataFrame]] - Pandas DataFrame or Generator of Pandas DataFrames if chunked is passed. + pd.DataFrame + Pandas DataFrame. Examples -------- @@ -194,42 +194,34 @@ def read_sql_query( ... ) """ - if transaction_id is not None and query_as_of_time is not None: - raise exceptions.InvalidArgumentCombination( - "Please pass only one of `transaction_id` or `query_as_of_time`, not both" - ) session: boto3.Session = _utils.ensure_session(session=boto3_session) client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) + commit_trans: bool = False if params is None: params = {} for key, value in params.items(): sql = sql.replace(f":{key};", str(value)) - args: Dict[str, Optional[str]] = _catalog_id(catalog_id=catalog_id, **{"DatabaseName": database}) - if query_as_of_time: - args["QueryAsOfTime"] = query_as_of_time - elif transaction_id: - args["TransactionId"] = transaction_id - else: + if not any([transaction_id, query_as_of_time]): _logger.debug("Neither `transaction_id` nor `query_as_of_time` were specified, starting transaction") transaction_id = start_transaction(read_only=True, boto3_session=session) - args["TransactionId"] = transaction_id - try: - query_id: str = client_lakeformation.start_query_planning(QueryString=sql, QueryPlanningContext=args)["QueryId"] - return _resolve_sql_query( - query_id=query_id, - categories=categories, - safe=safe, - map_types=map_types, - use_threads=use_threads, - boto3_session=session, - ) - except Exception as ex: - _logger.debug("Canceling transaction with ID: %s.", transaction_id) - if transaction_id: - cancel_transaction(transaction_id=transaction_id, boto3_session=session) - _logger.error(ex) - raise + commit_trans = True + args: Dict[str, Optional[str]] = _catalog_id( + catalog_id=catalog_id, + **_transaction_id(transaction_id=transaction_id, query_as_of_time=query_as_of_time, DatabaseName=database), + ) + query_id: str = client_lakeformation.start_query_planning(QueryString=sql, QueryPlanningContext=args)["QueryId"] + df = _resolve_sql_query( + query_id=query_id, + categories=categories, + safe=safe, + map_types=map_types, + use_threads=use_threads, + boto3_session=session, + ) + if commit_trans: + commit_transaction(transaction_id=transaction_id) # type: ignore + return df @apply_configs @@ -244,7 +236,7 @@ def read_sql_table( map_types: bool = True, use_threads: bool = True, boto3_session: Optional[boto3.Session] = None, -) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: +) -> pd.DataFrame: """Extract all rows from AWS Glue Table (Transaction ID or time travel timestamp). Return Pandas DataFrame. Note @@ -291,8 +283,8 @@ def read_sql_table( Returns ------- - Union[pd.DataFrame, Iterator[pd.DataFrame]] - Pandas DataFrame or Generator of Pandas DataFrames if chunked is passed. + pd.DataFrame + Pandas DataFrame. Examples -------- diff --git a/awswrangler/lakeformation/_utils.py b/awswrangler/lakeformation/_utils.py index 4f7d28789..e175ffa7a 100644 --- a/awswrangler/lakeformation/_utils.py +++ b/awswrangler/lakeformation/_utils.py @@ -1,13 +1,15 @@ """Utilities Module for Amazon Lake Formation.""" import logging import time +from math import inf from threading import Thread from typing import Any, Dict, List, Optional, Union import boto3 +import botocore.exceptions from awswrangler import _utils, exceptions -from awswrangler.catalog._utils import _catalog_id +from awswrangler.catalog._utils import _catalog_id, _transaction_id from awswrangler.s3._describe import describe_objects _QUERY_FINAL_STATES: List[str] = ["ERROR", "FINISHED"] @@ -73,7 +75,8 @@ def _get_table_objects( client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) scan_kwargs: Dict[str, Union[str, int]] = _catalog_id( - catalog_id=catalog_id, TransactionId=transaction_id, DatabaseName=database, TableName=table, MaxResults=100 + catalog_id=catalog_id, + **_transaction_id(transaction_id=transaction_id, DatabaseName=database, TableName=table, MaxResults=100), ) if partition_cols and partitions_types and partitions_values: scan_kwargs["PartitionPredicate"] = _build_partition_predicate( @@ -108,7 +111,7 @@ def _update_table_objects( client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) update_kwargs: Dict[str, Union[str, int, List[Dict[str, Dict[str, Any]]]]] = _catalog_id( - catalog_id=catalog_id, TransactionId=transaction_id, DatabaseName=database, TableName=table + catalog_id=catalog_id, **_transaction_id(transaction_id=transaction_id, DatabaseName=database, TableName=table) ) write_operations: List[Dict[str, Dict[str, Any]]] = [] @@ -121,11 +124,20 @@ def _update_table_objects( client_lakeformation.update_table_objects(**update_kwargs) -def _monitor_transaction(transaction_id: str, boto3_session: Optional[boto3.Session] = None) -> None: +def _monitor_transaction(transaction_id: str, time_out: float, boto3_session: Optional[boto3.Session] = None) -> None: + start = time.time() + elapsed_time = 0.0 state: str = describe_transaction(transaction_id=transaction_id, boto3_session=boto3_session) - while state not in _TRANSACTION_FINAL_STATES: - extend_transaction(transaction_id=transaction_id, boto3_session=boto3_session) + while (state not in _TRANSACTION_FINAL_STATES) and (time_out > elapsed_time): + try: + extend_transaction(transaction_id=transaction_id, boto3_session=boto3_session) + except botocore.exceptions.ClientError as ex: + if ex.response["Error"]["Code"] in ["TransactionCanceledException", "TransactionCommittedException"]: + _logger.debug("Transaction: %s was already canceled or committed.", transaction_id) + else: + raise ex time.sleep(_TRANSACTION_WAIT_POLLING_DELAY) + elapsed_time = time.time() - start state = describe_transaction(transaction_id=transaction_id, boto3_session=boto3_session) _logger.debug("Transaction state: %s", state) @@ -186,15 +198,21 @@ def cancel_transaction(transaction_id: str, boto3_session: Optional[boto3.Sessio client_lakeformation.cancel_transaction(TransactionId=transaction_id) -def start_transaction(read_only: Optional[bool] = False, boto3_session: Optional[boto3.Session] = None) -> str: +def start_transaction( + read_only: Optional[bool] = False, time_out: Optional[float] = inf, boto3_session: Optional[boto3.Session] = None +) -> str: """Start a new transaction and returns its transaction ID. + The transaction is periodically extended until it's committed, canceled or the defined time-out is reached. + Parameters ---------- read_only : bool, optional Indicates that that this transaction should be read only. Writes made using a read-only transaction ID will be rejected. Read-only transactions do not need to be committed. + time_out: float, optional + Maximum duration over which a transaction is extended. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session received None. @@ -214,7 +232,7 @@ def start_transaction(read_only: Optional[bool] = False, boto3_session: Optional transaction_type: str = "READ_ONLY" if read_only else "READ_AND_WRITE" transaction_id: str = client_lakeformation.start_transaction(TransactionType=transaction_type)["TransactionId"] # Extend the transaction while in "active" state in a separate thread - t = Thread(target=_monitor_transaction, args=(transaction_id, boto3_session)) + t = Thread(target=_monitor_transaction, args=(transaction_id, time_out, boto3_session)) t.daemon = True # Ensures thread is killed when any exception is raised t.start() return transaction_id diff --git a/awswrangler/s3/_write_parquet.py b/awswrangler/s3/_write_parquet.py index fd7e5ec80..1f2cd8331 100644 --- a/awswrangler/s3/_write_parquet.py +++ b/awswrangler/s3/_write_parquet.py @@ -703,9 +703,6 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b transaction_id=transaction_id, boto3_session=boto3_session # type: ignore ) except Exception: - if transaction_id: - _logger.debug("Canceling transaction with ID: %s.", transaction_id) - lakeformation.cancel_transaction(transaction_id=transaction_id, boto3_session=boto3_session) _logger.debug("Catalog write failed, cleaning up S3 (paths: %s).", paths) delete_objects( path=paths, diff --git a/awswrangler/s3/_write_text.py b/awswrangler/s3/_write_text.py index 7e3931fca..9ad4f3be1 100644 --- a/awswrangler/s3/_write_text.py +++ b/awswrangler/s3/_write_text.py @@ -642,9 +642,6 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state transaction_id=transaction_id, boto3_session=boto3_session # type: ignore ) except Exception: - if transaction_id: - _logger.debug("Canceling transaction with ID: %s.", transaction_id) - lakeformation.cancel_transaction(transaction_id=transaction_id, boto3_session=boto3_session) _logger.debug("Catalog write failed, cleaning up S3 (paths: %s).", paths) delete_objects( path=paths, diff --git a/cloudformation/base.yaml b/cloudformation/base.yaml index 76b69acff..2af9320bb 100644 --- a/cloudformation/base.yaml +++ b/cloudformation/base.yaml @@ -1,19 +1,7 @@ AWSTemplateFormatVersion: 2010-09-09 Description: | AWS Data Wrangler Development Base Data Lake Infrastructure. VPC, Subnets, S3 Bucket, Glue Database, etc. -Parameters: - EnableLakeFormation: - Type: String - Description: set to True if Lake Formation is enabled in the account - Default: false - AllowedValues: - - true - - false -Conditions: - CreateLFResources: - Fn::Equals: - - Ref: EnableLakeFormation - - true + Resources: VPC: Type: AWS::EC2::VPC @@ -231,99 +219,7 @@ Resources: Ref: AWS::AccountId DatabaseInput: Name: aws_data_wrangler - Description: AWS Data Wrangler Test Athena - Glue Database - LakeFormationBucket: - Type: AWS::S3::Bucket - Condition: CreateLFResources - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - PublicAccessBlockConfiguration: - BlockPublicAcls: true - BlockPublicPolicy: true - IgnorePublicAcls: true - RestrictPublicBuckets: true - LifecycleConfiguration: - Rules: - - Id: CleaningUp - Status: Enabled - ExpirationInDays: 1 - AbortIncompleteMultipartUpload: - DaysAfterInitiation: 1 - NoncurrentVersionExpirationInDays: 1 - LakeFormationTransactionRole: - Type: AWS::IAM::Role - Condition: CreateLFResources - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - AssumeRolePolicyDocument: - Version: 2012-10-17 - Statement: - - Effect: Allow - Principal: - Service: - - lakeformation.amazonaws.com - Action: - - sts:AssumeRole - Path: / - Policies: - - PolicyName: Root - PolicyDocument: - Version: 2012-10-17 - Statement: - - Effect: Allow - Action: - - s3:DeleteObject - - s3:GetObject - - s3:PutObject - Resource: - - Fn::Sub: arn:aws:s3:::${LakeFormationBucket}/* - - Effect: Allow - Action: - - s3:ListObject - Resource: - - Fn::Sub: arn:aws:s3:::${LakeFormationBucket} - - Effect: Allow - Action: - - execute-api:Invoke - Resource: arn:aws:execute-api:*:*:*/*/POST/reportStatus - - Effect: Allow - Action: - - lakeformation:AbortTransaction - - lakeformation:BeginTransaction - - lakeformation:CommitTransaction - - lakeformation:GetTableObjects - - lakeformation:UpdateTableObjects - Resource: '*' - - Effect: Allow - Action: - - glue:GetTable - - glue:GetPartitions - - glue:UpdateTable - Resource: '*' - LakeFormationBucketS3Registration: - Type: AWS::LakeFormation::Resource - Condition: CreateLFResources - Properties: - ResourceArn: - Fn::Sub: arn:aws:::s3:${LakeFormationBucket}/ - RoleArn: - Fn::GetAtt: - - LakeFormationTransactionRole - - Arn - UseServiceLinkedRole: false - LakeFormationGlueDatabase: - Type: AWS::Glue::Database - Condition: CreateLFResources - Properties: - CatalogId: - Ref: AWS::AccountId - DatabaseInput: - Name: aws_data_wrangler_lakeformation - Description: AWS Data Wrangler - Lake Formation Database + Description: AWS Data Wrangler Test Arena - Glue Database LogGroup: Type: AWS::Logs::LogGroup Properties: @@ -380,11 +276,6 @@ Outputs: Value: Ref: GlueDatabase Description: Glue Database Name. - LakeFormationGlueDatabaseName: - Condition: CreateLFResources - Value: - Ref: LakeFormationGlueDatabase - Description: Lake Formation Glue Database Name. LogGroupName: Value: Ref: LogGroup diff --git a/tests/conftest.py b/tests/conftest.py index 95edfa656..4a22a5e9a 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -28,11 +28,6 @@ def glue_database(cloudformation_outputs): return cloudformation_outputs["GlueDatabaseName"] -@pytest.fixture(scope="session") -def lakeformation_glue_database(cloudformation_outputs): - return cloudformation_outputs["LakeFormationGlueDatabaseName"] - - @pytest.fixture(scope="session") def kms_key(cloudformation_outputs): return cloudformation_outputs["KmsKeyArn"] diff --git a/tests/test__routines.py b/tests/test__routines.py index 145293e79..64decb8ce 100644 --- a/tests/test__routines.py +++ b/tests/test__routines.py @@ -11,11 +11,7 @@ @pytest.mark.parametrize("use_threads", [True, False]) @pytest.mark.parametrize("concurrent_partitioning", [True, False]) @pytest.mark.parametrize("table_type", ["EXTERNAL_TABLE", "GOVERNED"]) -def test_routine_0( - lakeformation_glue_database, glue_database, glue_table, table_type, path, use_threads, concurrent_partitioning -): - - database = lakeformation_glue_database if table_type == "GOVERNED" else glue_database +def test_routine_0(glue_database, glue_table, table_type, path, use_threads, concurrent_partitioning): # Round 1 - Warm up df = pd.DataFrame({"c0": [0, None]}, dtype="Int64") @@ -24,7 +20,7 @@ def test_routine_0( path=path, dataset=True, mode="overwrite", - database=database, + database=glue_database, table=glue_table, table_type=table_type, description="c0", @@ -34,17 +30,17 @@ def test_routine_0( concurrent_partitioning=concurrent_partitioning, ) if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, glue_database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) assert df.shape == df2.shape assert df.c0.sum() == df2.c0.sum() - parameters = wr.catalog.get_table_parameters(database, glue_table) + parameters = wr.catalog.get_table_parameters(glue_database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == str(len(df2.columns)) assert parameters["num_rows"] == str(len(df2.index)) - assert wr.catalog.get_table_description(database, glue_table) == "c0" - comments = wr.catalog.get_columns_comments(database, glue_table) + assert wr.catalog.get_table_description(glue_database, glue_table) == "c0" + comments = wr.catalog.get_columns_comments(glue_database, glue_table) assert len(comments) == len(df.columns) assert comments["c0"] == "0" @@ -54,7 +50,7 @@ def test_routine_0( df=df, dataset=True, mode="overwrite", - database=database, + database=glue_database, table=glue_table, description="c1", parameters={"num_cols": str(len(df.columns)), "num_rows": str(len(df.index))}, @@ -63,17 +59,17 @@ def test_routine_0( concurrent_partitioning=concurrent_partitioning, ) if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, glue_database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) assert df.shape == df2.shape assert df.c1.sum() == df2.c1.sum() - parameters = wr.catalog.get_table_parameters(database, glue_table) + parameters = wr.catalog.get_table_parameters(glue_database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == str(len(df2.columns)) assert parameters["num_rows"] == str(len(df2.index)) - assert wr.catalog.get_table_description(database, glue_table) == "c1" - comments = wr.catalog.get_columns_comments(database, glue_table) + assert wr.catalog.get_table_description(glue_database, glue_table) == "c1" + comments = wr.catalog.get_columns_comments(glue_database, glue_table) assert len(comments) == len(df.columns) assert comments["c1"] == "1" @@ -84,7 +80,7 @@ def test_routine_0( path=path, dataset=True, mode="append", - database=database, + database=glue_database, table=glue_table, description="c1", parameters={"num_cols": str(len(df.columns)), "num_rows": str(len(df.index) * 2)}, @@ -93,18 +89,18 @@ def test_routine_0( concurrent_partitioning=concurrent_partitioning, ) if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, glue_database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) assert len(df.columns) == len(df2.columns) assert len(df.index) * 2 == len(df2.index) assert df.c1.sum() + 1 == df2.c1.sum() - parameters = wr.catalog.get_table_parameters(database, glue_table) + parameters = wr.catalog.get_table_parameters(glue_database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == str(len(df2.columns)) assert parameters["num_rows"] == str(len(df2.index)) - assert wr.catalog.get_table_description(database, glue_table) == "c1" - comments = wr.catalog.get_columns_comments(database, glue_table) + assert wr.catalog.get_table_description(glue_database, glue_table) == "c1" + comments = wr.catalog.get_columns_comments(glue_database, glue_table) assert len(comments) == len(df.columns) assert comments["c1"] == "1" @@ -114,7 +110,7 @@ def test_routine_0( df=df, dataset=True, mode="append", - database=database, + database=glue_database, table=glue_table, description="c1+c2", parameters={"num_cols": "2", "num_rows": "9"}, @@ -123,18 +119,18 @@ def test_routine_0( concurrent_partitioning=concurrent_partitioning, ) if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, glue_database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) assert len(df2.columns) == 2 assert len(df2.index) == 9 assert df2.c1.sum() == 3 - parameters = wr.catalog.get_table_parameters(database, glue_table) + parameters = wr.catalog.get_table_parameters(glue_database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == "2" assert parameters["num_rows"] == "9" - assert wr.catalog.get_table_description(database, glue_table) == "c1+c2" - comments = wr.catalog.get_columns_comments(database, glue_table) + assert wr.catalog.get_table_description(glue_database, glue_table) == "c1+c2" + comments = wr.catalog.get_columns_comments(glue_database, glue_table) assert len(comments) == len(df.columns) assert comments["c1"] == "1" assert comments["c2"] == "2" @@ -146,7 +142,7 @@ def test_routine_0( path=path, dataset=True, mode="append", - database=database, + database=glue_database, table=glue_table, description="c1+c2+c3", parameters={"num_cols": "3", "num_rows": "10"}, @@ -155,34 +151,30 @@ def test_routine_0( concurrent_partitioning=concurrent_partitioning, ) if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, glue_database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) assert len(df2.columns) == 3 assert len(df2.index) == 10 assert df2.c1.sum() == 4 - parameters = wr.catalog.get_table_parameters(database, glue_table) + parameters = wr.catalog.get_table_parameters(glue_database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == "3" assert parameters["num_rows"] == "10" - assert wr.catalog.get_table_description(database, glue_table) == "c1+c2+c3" - comments = wr.catalog.get_columns_comments(database, glue_table) + assert wr.catalog.get_table_description(glue_database, glue_table) == "c1+c2+c3" + comments = wr.catalog.get_columns_comments(glue_database, glue_table) assert len(comments) == len(df.columns) assert comments["c1"] == "1!" assert comments["c2"] == "2!" assert comments["c3"] == "3" - wr.catalog.delete_table_if_exists(database=database, table=glue_table) + wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table) @pytest.mark.parametrize("use_threads", [True, False]) @pytest.mark.parametrize("concurrent_partitioning", [True, False]) @pytest.mark.parametrize("table_type", ["EXTERNAL_TABLE", "GOVERNED"]) -def test_routine_1( - lakeformation_glue_database, glue_database, glue_table, table_type, path, use_threads, concurrent_partitioning -): - - database = lakeformation_glue_database if table_type == "GOVERNED" else glue_database +def test_routine_1(glue_database, glue_table, table_type, path, use_threads, concurrent_partitioning): # Round 1 - Overwrite Partitioned df = pd.DataFrame({"c0": ["foo", None], "c1": [0, 1]}) @@ -191,7 +183,7 @@ def test_routine_1( dataset=True, path=path, mode="overwrite", - database=database, + database=glue_database, table=glue_table, table_type=table_type, partition_cols=["c1"], @@ -202,17 +194,17 @@ def test_routine_1( concurrent_partitioning=concurrent_partitioning, ) if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, glue_database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) assert df.shape == df2.shape assert df.c1.sum() == df2.c1.sum() - parameters = wr.catalog.get_table_parameters(database, glue_table) + parameters = wr.catalog.get_table_parameters(glue_database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == "2" assert parameters["num_rows"] == "2" - assert wr.catalog.get_table_description(database, glue_table) == "c0+c1" - comments = wr.catalog.get_columns_comments(database, glue_table) + assert wr.catalog.get_table_description(glue_database, glue_table) == "c0+c1" + comments = wr.catalog.get_columns_comments(glue_database, glue_table) assert len(comments) == len(df.columns) assert comments["c0"] == "zero" assert comments["c1"] == "one" @@ -223,7 +215,7 @@ def test_routine_1( df=df, dataset=True, mode="overwrite_partitions", - database=database, + database=glue_database, table=glue_table, partition_cols=["c1"], description="c0+c1", @@ -233,18 +225,18 @@ def test_routine_1( use_threads=use_threads, ) if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, glue_database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) assert len(df2.columns) == 2 assert len(df2.index) == 3 assert df2.c1.sum() == 3 - parameters = wr.catalog.get_table_parameters(database, glue_table) + parameters = wr.catalog.get_table_parameters(glue_database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == "2" assert parameters["num_rows"] == "3" - assert wr.catalog.get_table_description(database, glue_table) == "c0+c1" - comments = wr.catalog.get_columns_comments(database, glue_table) + assert wr.catalog.get_table_description(glue_database, glue_table) == "c0+c1" + comments = wr.catalog.get_columns_comments(glue_database, glue_table) assert len(comments) == len(df.columns) assert comments["c0"] == "zero" assert comments["c1"] == "one" @@ -255,7 +247,7 @@ def test_routine_1( df=df, dataset=True, mode="overwrite_partitions", - database=database, + database=glue_database, table=glue_table, partition_cols=["c1"], description="c0+c1+c2", @@ -265,24 +257,24 @@ def test_routine_1( concurrent_partitioning=concurrent_partitioning, ) if table_type == "GOVERNED": - df2 = wr.lakeformation.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.lakeformation.read_sql_table(glue_table, glue_database, use_threads=use_threads) else: - df2 = wr.athena.read_sql_table(glue_table, database, use_threads=use_threads) + df2 = wr.athena.read_sql_table(glue_table, glue_database, use_threads=use_threads) assert len(df2.columns) == 3 assert len(df2.index) == 4 assert df2.c1.sum() == 6 - parameters = wr.catalog.get_table_parameters(database, glue_table) + parameters = wr.catalog.get_table_parameters(glue_database, glue_table) assert len(parameters) >= 5 assert parameters["num_cols"] == "3" assert parameters["num_rows"] == "4" - assert wr.catalog.get_table_description(database, glue_table) == "c0+c1+c2" - comments = wr.catalog.get_columns_comments(database, glue_table) + assert wr.catalog.get_table_description(glue_database, glue_table) == "c0+c1+c2" + comments = wr.catalog.get_columns_comments(glue_database, glue_table) assert len(comments) == len(df.columns) assert comments["c0"] == "zero" assert comments["c1"] == "one" assert comments["c2"] == "two" - wr.catalog.delete_table_if_exists(database=database, table=glue_table) + wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table) def test_routine_2(glue_database, glue_table, path): diff --git a/tests/test_athena.py b/tests/test_athena.py index 4946fe424..f5988a388 100644 --- a/tests/test_athena.py +++ b/tests/test_athena.py @@ -220,8 +220,8 @@ def test_athena_read_list(glue_database): def test_sanitize_names(): - assert wr.catalog.sanitize_column_name("CamelCase") == "camel_case" - assert wr.catalog.sanitize_column_name("CamelCase2") == "camel_case2" + assert wr.catalog.sanitize_column_name("CamelCase") == "camelcase" + assert wr.catalog.sanitize_column_name("CamelCase2") == "camelcase2" assert wr.catalog.sanitize_column_name("Camel_Case3") == "camel_case3" assert wr.catalog.sanitize_column_name("Cámël_Casë4仮") == "camel_case4_" assert wr.catalog.sanitize_column_name("Camel__Case5") == "camel__case5" @@ -229,8 +229,8 @@ def test_sanitize_names(): assert wr.catalog.sanitize_column_name("Camel.Case7") == "camel_case7" assert wr.catalog.sanitize_column_name("xyz_cd") == "xyz_cd" assert wr.catalog.sanitize_column_name("xyz_Cd") == "xyz_cd" - assert wr.catalog.sanitize_table_name("CamelCase") == "camel_case" - assert wr.catalog.sanitize_table_name("CamelCase2") == "camel_case2" + assert wr.catalog.sanitize_table_name("CamelCase") == "camelcase" + assert wr.catalog.sanitize_table_name("CamelCase2") == "camelcase2" assert wr.catalog.sanitize_table_name("Camel_Case3") == "camel_case3" assert wr.catalog.sanitize_table_name("Cámël_Casë4仮") == "camel_case4_" assert wr.catalog.sanitize_table_name("Camel__Case5") == "camel__case5" diff --git a/tests/test_athena_parquet.py b/tests/test_athena_parquet.py index ebfe4c896..71ff4e709 100644 --- a/tests/test_athena_parquet.py +++ b/tests/test_athena_parquet.py @@ -504,9 +504,9 @@ def test_to_parquet_sanitize(path, glue_database): df2 = wr.athena.read_sql_table(database=glue_database, table=table_name) wr.catalog.delete_table_if_exists(database=glue_database, table="table_name_") assert df.shape == df2.shape - assert list(df2.columns) == ["c0", "camel_case", "c_2"] + assert list(df2.columns) == ["c0", "camelcase", "c_2"] assert df2.c0.sum() == 1 - assert df2.camel_case.sum() == 5 + assert df2.camelcase.sum() == 5 assert df2.c_2.sum() == 9 diff --git a/tests/test_catalog.py b/tests/test_catalog.py index 6db17a2d0..6354f005d 100644 --- a/tests/test_catalog.py +++ b/tests/test_catalog.py @@ -1,3 +1,5 @@ +from typing import Optional + import boto3 import pandas as pd import pytest @@ -7,7 +9,32 @@ from ._utils import ensure_data_types_csv, get_df_csv -def test_catalog(path: str, glue_database: str, glue_table: str, account_id: str) -> None: +@pytest.mark.parametrize("table_type", ["EXTERNAL_TABLE", "GOVERNED"]) +def test_create_table(path: str, glue_database: str, glue_table: str, table_type: Optional[str]) -> None: + transaction_id = wr.lakeformation.start_transaction() if table_type == "GOVERNED" else None + assert wr.catalog.does_table_exist(database=glue_database, table=glue_table) is False + wr.catalog.create_csv_table( + database=glue_database, + table=glue_table, + path=path, + columns_types={"col0": "int", "col1": "double"}, + partitions_types={"y": "int", "m": "int"}, + table_type=table_type, + transaction_id=transaction_id, + ) + if transaction_id: + wr.lakeformation.commit_transaction(transaction_id) + assert wr.catalog.does_table_exist(database=glue_database, table=glue_table) is True + + +@pytest.mark.parametrize("table_type", ["EXTERNAL_TABLE", "GOVERNED"]) +@pytest.mark.parametrize("start_transaction", [True, False]) +def test_catalog( + path: str, glue_database: str, glue_table: str, table_type: Optional[str], start_transaction: bool, account_id: str +) -> None: + if table_type != "GOVERNED" and start_transaction: + pytest.skip() + assert wr.catalog.does_table_exist(database=glue_database, table=glue_table) is False wr.catalog.create_parquet_table( database=glue_database, @@ -16,11 +43,18 @@ def test_catalog(path: str, glue_database: str, glue_table: str, account_id: str columns_types={"col0": "int", "col1": "double"}, partitions_types={"y": "int", "m": "int"}, compression="snappy", + table_type=table_type, ) with pytest.raises(wr.exceptions.InvalidArgumentValue): wr.catalog.create_parquet_table( - database=glue_database, table=glue_table, path=path, columns_types={"col0": "string"}, mode="append" + database=glue_database, + table=glue_table, + path=path, + columns_types={"col0": "string"}, + mode="append", + table_type=table_type, ) + assert wr.catalog.does_table_exist(database=glue_database, table=glue_table) is True assert wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table) is True assert wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table) is False @@ -35,32 +69,19 @@ def test_catalog(path: str, glue_database: str, glue_table: str, account_id: str parameters={"tag": "test"}, columns_comments={"col0": "my int", "y": "year"}, mode="overwrite", + table_type=table_type, ) - wr.catalog.add_parquet_partitions( - database=glue_database, - table=glue_table, - partitions_values={f"{path}y=2020/m=1/": ["2020", "1"], f"{path}y=2021/m=2/": ["2021", "2"]}, - compression="snappy", - ) - assert wr.catalog.get_table_location(database=glue_database, table=glue_table) == path - # get_parquet_partitions - parquet_partitions_values = wr.catalog.get_parquet_partitions(database=glue_database, table=glue_table) - assert len(parquet_partitions_values) == 2 - parquet_partitions_values = wr.catalog.get_parquet_partitions( - database=glue_database, table=glue_table, catalog_id=account_id, expression="y = 2021 AND m = 2" - ) - assert len(parquet_partitions_values) == 1 - assert len(set(parquet_partitions_values[f"{path}y=2021/m=2/"]) & {"2021", "2"}) == 2 - # get_partitions - partitions_values = wr.catalog.get_partitions(database=glue_database, table=glue_table) - assert len(partitions_values) == 2 - partitions_values = wr.catalog.get_partitions( - database=glue_database, table=glue_table, catalog_id=account_id, expression="y = 2021 AND m = 2" - ) - assert len(partitions_values) == 1 - assert len(set(partitions_values[f"{path}y=2021/m=2/"]) & {"2021", "2"}) == 2 - dtypes = wr.catalog.get_table_types(database=glue_database, table=glue_table) + if table_type == "GOVERNED": + # Cannot start a transaction before creating a table + transaction_id = wr.lakeformation.start_transaction() if start_transaction else None + else: + transaction_id = None + + assert ( + wr.catalog.get_table_location(database=glue_database, table=glue_table, transaction_id=transaction_id) == path + ) + dtypes = wr.catalog.get_table_types(database=glue_database, table=glue_table, transaction_id=transaction_id) assert dtypes["col0"] == "int" assert dtypes["col1"] == "double" assert dtypes["y"] == "int" @@ -68,49 +89,62 @@ def test_catalog(path: str, glue_database: str, glue_table: str, account_id: str df_dbs = wr.catalog.databases() assert len(wr.catalog.databases(catalog_id=account_id)) == len(df_dbs) assert glue_database in df_dbs["Database"].to_list() - tables = list(wr.catalog.get_tables()) + tables = list(wr.catalog.get_tables(transaction_id=transaction_id)) assert len(tables) > 0 for tbl in tables: if tbl["Name"] == glue_table: - assert tbl["TableType"] == "EXTERNAL_TABLE" - tables = list(wr.catalog.get_tables(database=glue_database)) + assert tbl["TableType"] == table_type + tables = list(wr.catalog.get_tables(database=glue_database, transaction_id=transaction_id)) assert len(tables) > 0 for tbl in tables: assert tbl["DatabaseName"] == glue_database # add & delete column wr.catalog.add_column( - database=glue_database, table=glue_table, column_name="col2", column_type="int", column_comment="comment" + database=glue_database, + table=glue_table, + column_name="col2", + column_type="int", + column_comment="comment", + transaction_id=transaction_id, ) - dtypes = wr.catalog.get_table_types(database=glue_database, table=glue_table) + dtypes = wr.catalog.get_table_types(database=glue_database, table=glue_table, transaction_id=transaction_id) assert len(dtypes) == 5 assert dtypes["col2"] == "int" - wr.catalog.delete_column(database=glue_database, table=glue_table, column_name="col2") - dtypes = wr.catalog.get_table_types(database=glue_database, table=glue_table) + wr.catalog.delete_column( + database=glue_database, table=glue_table, column_name="col2", transaction_id=transaction_id + ) + dtypes = wr.catalog.get_table_types(database=glue_database, table=glue_table, transaction_id=transaction_id) assert len(dtypes) == 4 # search tables = list(wr.catalog.search_tables(text="parquet", catalog_id=account_id)) assert len(tables) > 0 for tbl in tables: if tbl["Name"] == glue_table: - assert tbl["TableType"] == "EXTERNAL_TABLE" + assert tbl["TableType"] == table_type # prefix - tables = list(wr.catalog.get_tables(name_prefix=glue_table[:4], catalog_id=account_id)) + tables = list( + wr.catalog.get_tables(name_prefix=glue_table[:4], catalog_id=account_id, transaction_id=transaction_id) + ) assert len(tables) > 0 for tbl in tables: if tbl["Name"] == glue_table: - assert tbl["TableType"] == "EXTERNAL_TABLE" + assert tbl["TableType"] == table_type # suffix - tables = list(wr.catalog.get_tables(name_suffix=glue_table[-4:], catalog_id=account_id)) + tables = list( + wr.catalog.get_tables(name_suffix=glue_table[-4:], catalog_id=account_id, transaction_id=transaction_id) + ) assert len(tables) > 0 for tbl in tables: if tbl["Name"] == glue_table: - assert tbl["TableType"] == "EXTERNAL_TABLE" + assert tbl["TableType"] == table_type # name_contains - tables = list(wr.catalog.get_tables(name_contains=glue_table[4:-4], catalog_id=account_id)) + tables = list( + wr.catalog.get_tables(name_contains=glue_table[4:-4], catalog_id=account_id, transaction_id=transaction_id) + ) assert len(tables) > 0 for tbl in tables: if tbl["Name"] == glue_table: - assert tbl["TableType"] == "EXTERNAL_TABLE" + assert tbl["TableType"] == table_type # prefix & suffix & name_contains with pytest.raises(wr.exceptions.InvalidArgumentCombination): list( @@ -119,14 +153,19 @@ def test_catalog(path: str, glue_database: str, glue_table: str, account_id: str name_contains=glue_table[3], name_suffix=glue_table[-1], catalog_id=account_id, + transaction_id=transaction_id, ) ) # prefix & suffix - tables = list(wr.catalog.get_tables(name_prefix=glue_table[0], name_suffix=glue_table[-1], catalog_id=account_id)) + tables = list( + wr.catalog.get_tables( + name_prefix=glue_table[0], name_suffix=glue_table[-1], catalog_id=account_id, transaction_id=transaction_id + ) + ) assert len(tables) > 0 for tbl in tables: if tbl["Name"] == glue_table: - assert tbl["TableType"] == "EXTERNAL_TABLE" + assert tbl["TableType"] == table_type # DataFrames assert len(wr.catalog.databases().index) > 0 assert len(wr.catalog.tables().index) > 0 @@ -143,10 +182,53 @@ def test_catalog(path: str, glue_database: str, glue_table: str, account_id: str ) > 0 ) - assert len(wr.catalog.table(database=glue_database, table=glue_table).index) > 0 - assert len(wr.catalog.table(database=glue_database, table=glue_table, catalog_id=account_id).index) > 0 + assert len(wr.catalog.table(database=glue_database, table=glue_table, transaction_id=transaction_id).index) > 0 + assert ( + len( + wr.catalog.table( + database=glue_database, table=glue_table, catalog_id=account_id, transaction_id=transaction_id + ).index + ) + > 0 + ) with pytest.raises(wr.exceptions.InvalidTable): - wr.catalog.overwrite_table_parameters({"foo": "boo"}, glue_database, "fake_table") + wr.catalog.overwrite_table_parameters( + {"foo": "boo"}, glue_database, "fake_table", transaction_id=transaction_id + ) + + +def test_catalog_partitions(glue_database, glue_table, path, account_id): + assert wr.catalog.does_table_exist(database=glue_database, table=glue_table) is False + wr.catalog.create_parquet_table( + database=glue_database, + table=glue_table, + path=path, + columns_types={"col0": "int", "col1": "double"}, + partitions_types={"y": "int", "m": "int"}, + compression="snappy", + ) + wr.catalog.add_parquet_partitions( + database=glue_database, + table=glue_table, + partitions_values={f"{path}y=2020/m=1/": ["2020", "1"], f"{path}y=2021/m=2/": ["2021", "2"]}, + compression="snappy", + ) + # get_parquet_partitions + parquet_partitions_values = wr.catalog.get_parquet_partitions(database=glue_database, table=glue_table) + assert len(parquet_partitions_values) == 2 + parquet_partitions_values = wr.catalog.get_parquet_partitions( + database=glue_database, table=glue_table, catalog_id=account_id, expression="y = 2021 AND m = 2" + ) + assert len(parquet_partitions_values) == 1 + assert len(set(parquet_partitions_values[f"{path}y=2021/m=2/"]) & {"2021", "2"}) == 2 + # get_partitions + partitions_values = wr.catalog.get_partitions(database=glue_database, table=glue_table) + assert len(partitions_values) == 2 + partitions_values = wr.catalog.get_partitions( + database=glue_database, table=glue_table, catalog_id=account_id, expression="y = 2021 AND m = 2" + ) + assert len(partitions_values) == 1 + assert len(set(partitions_values[f"{path}y=2021/m=2/"]) & {"2021", "2"}) == 2 def test_catalog_get_databases(glue_database): diff --git a/tests/test_lakeformation.py b/tests/test_lakeformation.py index a9b3f3d34..447b0225f 100644 --- a/tests/test_lakeformation.py +++ b/tests/test_lakeformation.py @@ -11,11 +11,9 @@ logging.getLogger("awswrangler").setLevel(logging.DEBUG) -def test_lakeformation(path, path2, lakeformation_glue_database, glue_table, glue_table2, use_threads=False): - table = f"__{glue_table}" - table2 = f"__{glue_table2}" - wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table) - wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table2) +def test_lakeformation(path, path2, glue_database, glue_table, glue_table2, use_threads=False): + wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table) + wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table2) wr.s3.to_parquet( df=get_df(governed=True), @@ -26,14 +24,14 @@ def test_lakeformation(path, path2, lakeformation_glue_database, glue_table, glu dataset=True, partition_cols=["par0", "par1"], mode="overwrite", - table=table, + table=glue_table, table_type="GOVERNED", - database=lakeformation_glue_database, + database=glue_database, ) df = wr.lakeformation.read_sql_table( - table=table, - database=lakeformation_glue_database, + table=glue_table, + database=glue_database, use_threads=use_threads, ) assert len(df.index) == 3 @@ -43,8 +41,8 @@ def test_lakeformation(path, path2, lakeformation_glue_database, glue_table, glu # Filter query df2 = wr.lakeformation.read_sql_query( - sql=f"SELECT * FROM {table} WHERE iint16 = :iint16;", - database=lakeformation_glue_database, + sql=f"SELECT * FROM {glue_table} WHERE iint16 = :iint16;", + database=glue_database, params={"iint16": 1}, ) assert len(df2.index) == 1 @@ -58,15 +56,15 @@ def test_lakeformation(path, path2, lakeformation_glue_database, glue_table, glu dataset=True, partition_cols=["par0", "par1"], mode="append", - table=table2, + table=glue_table2, table_type="GOVERNED", - database=lakeformation_glue_database, + database=glue_database, ) # Read within a transaction transaction_id = wr.lakeformation.start_transaction(read_only=True) df3 = wr.lakeformation.read_sql_table( - table=table2, - database=lakeformation_glue_database, + table=glue_table2, + database=glue_database, transaction_id=transaction_id, use_threads=use_threads, ) @@ -76,24 +74,20 @@ def test_lakeformation(path, path2, lakeformation_glue_database, glue_table, glu # Read within a query as of time query_as_of_time = calendar.timegm(time.gmtime()) df4 = wr.lakeformation.read_sql_table( - table=table2, - database=lakeformation_glue_database, + table=glue_table2, + database=glue_database, query_as_of_time=query_as_of_time, use_threads=use_threads, ) assert len(df4.index) == 3 - wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table) - wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table2) + wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table) + wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table2) -def test_lakeformation_multi_transaction( - path, path2, lakeformation_glue_database, glue_table, glue_table2, use_threads=True -): - table = f"__{glue_table}" - table2 = f"__{glue_table2}" - wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table) - wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table2) +def test_lakeformation_multi_transaction(path, path2, glue_database, glue_table, glue_table2, use_threads=True): + wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table) + wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table2) df = pd.DataFrame({"c0": [0, None]}, dtype="Int64") transaction_id = wr.lakeformation.start_transaction(read_only=False) @@ -102,8 +96,8 @@ def test_lakeformation_multi_transaction( path=path, dataset=True, mode="append", - database=lakeformation_glue_database, - table=table, + database=glue_database, + table=glue_table, table_type="GOVERNED", transaction_id=transaction_id, description="c0", @@ -118,8 +112,8 @@ def test_lakeformation_multi_transaction( path=path2, dataset=True, mode="append", - database=lakeformation_glue_database, - table=table2, + database=glue_database, + table=glue_table2, table_type="GOVERNED", transaction_id=transaction_id, description="c1", @@ -130,13 +124,13 @@ def test_lakeformation_multi_transaction( wr.lakeformation.commit_transaction(transaction_id=transaction_id) df3 = wr.lakeformation.read_sql_table( - table=table, - database=lakeformation_glue_database, + table=glue_table, + database=glue_database, use_threads=use_threads, ) df4 = wr.lakeformation.read_sql_table( - table=table2, - database=lakeformation_glue_database, + table=glue_table2, + database=glue_database, use_threads=use_threads, ) @@ -146,5 +140,5 @@ def test_lakeformation_multi_transaction( assert df2.shape == df4.shape assert df2.c1.sum() == df4.c1.sum() - wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table) - wr.catalog.delete_table_if_exists(database=lakeformation_glue_database, table=table2) + wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table) + wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table2) diff --git a/tests/test_s3.py b/tests/test_s3.py index 4db1acf2a..6be221f5b 100644 --- a/tests/test_s3.py +++ b/tests/test_s3.py @@ -17,7 +17,7 @@ logging.getLogger("awswrangler").setLevel(logging.DEBUG) -@pytest.mark.parametrize("sanitize_columns,col", [(True, "foo_boo"), (False, "FooBoo")]) +@pytest.mark.parametrize("sanitize_columns,col", [(True, "fooboo"), (False, "FooBoo")]) def test_sanitize_columns(path, sanitize_columns, col): df = pd.DataFrame({"FooBoo": [1, 2, 3]}) diff --git a/tests/test_s3_parquet.py b/tests/test_s3_parquet.py index db4dd0a8b..296e4c0a2 100644 --- a/tests/test_s3_parquet.py +++ b/tests/test_s3_parquet.py @@ -174,9 +174,9 @@ def test_to_parquet_file_sanitize(path): wr.s3.to_parquet(df, path_file, sanitize_columns=True) df2 = wr.s3.read_parquet(path_file) assert df.shape == df2.shape - assert list(df2.columns) == ["c0", "camel_case", "c_2"] + assert list(df2.columns) == ["c0", "camelcase", "c_2"] assert df2.c0.sum() == 1 - assert df2.camel_case.sum() == 5 + assert df2.camelcase.sum() == 5 assert df2.c_2.sum() == 9 @@ -402,9 +402,9 @@ def test_to_parquet_dataset_sanitize(path): wr.s3.to_parquet(df, path, dataset=True, partition_cols=["par"], sanitize_columns=True, mode="overwrite") df2 = wr.s3.read_parquet(path, dataset=True) assert df.shape == df2.shape - assert list(df2.columns) == ["c0", "camel_case", "c_2", "par"] + assert list(df2.columns) == ["c0", "camelcase", "c_2", "par"] assert df2.c0.sum() == 1 - assert df2.camel_case.sum() == 5 + assert df2.camelcase.sum() == 5 assert df2.c_2.sum() == 9 assert df2.par.to_list() == ["a", "b"] From 53027b5f5e3a255281bcbe04871731dc25728675 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Sat, 5 Jun 2021 16:01:31 +0100 Subject: [PATCH 14/36] Minor - Adding query as of time to test --- cloudformation/base.yaml | 286 --------- cloudformation/databases.yaml | 582 ------------------ cloudformation/delete-base.sh | 6 - cloudformation/delete-databases.sh | 6 - cloudformation/deploy-base.sh | 15 - cloudformation/deploy-databases.sh | 19 - .../security-group-databases-add-local-ip.sh | 15 - .../security-group-databases-check.sh | 8 - tests/test_catalog.py | 5 + 9 files changed, 5 insertions(+), 937 deletions(-) delete mode 100644 cloudformation/base.yaml delete mode 100644 cloudformation/databases.yaml delete mode 100755 cloudformation/delete-base.sh delete mode 100755 cloudformation/delete-databases.sh delete mode 100755 cloudformation/deploy-base.sh delete mode 100755 cloudformation/deploy-databases.sh delete mode 100755 cloudformation/security-group-databases-add-local-ip.sh delete mode 100755 cloudformation/security-group-databases-check.sh diff --git a/cloudformation/base.yaml b/cloudformation/base.yaml deleted file mode 100644 index 2af9320bb..000000000 --- a/cloudformation/base.yaml +++ /dev/null @@ -1,286 +0,0 @@ -AWSTemplateFormatVersion: 2010-09-09 -Description: | - AWS Data Wrangler Development Base Data Lake Infrastructure. VPC, Subnets, S3 Bucket, Glue Database, etc. - -Resources: - VPC: - Type: AWS::EC2::VPC - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - - Key: Name - Value: aws-data-wrangler - CidrBlock: 10.19.224.0/19 - EnableDnsSupport: true - EnableDnsHostnames: true - InternetGateway: - Type: AWS::EC2::InternetGateway - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - InternetGatewayAttachment: - Type: AWS::EC2::VPCGatewayAttachment - Properties: - InternetGatewayId: - Ref: InternetGateway - VpcId: - Ref: VPC - PublicSubnet1: - Type: AWS::EC2::Subnet - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - - Key: Name - Value: aws-data-wrangler-public1 - VpcId: - Ref: VPC - AvailabilityZone: - Fn::Select: - - 0 - - Fn::GetAZs: '' - CidrBlock: 10.19.229.0/24 - MapPublicIpOnLaunch: true - PublicSubnet2: - Type: AWS::EC2::Subnet - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - - Key: Name - Value: aws-data-wrangler-public2 - VpcId: - Ref: VPC - AvailabilityZone: - Fn::Select: - - 1 - - Fn::GetAZs: '' - CidrBlock: 10.19.230.0/24 - MapPublicIpOnLaunch: true - PrivateSubnet: - Type: AWS::EC2::Subnet - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - - Key: Name - Value: aws-data-wrangler-private - VpcId: - Ref: VPC - AvailabilityZone: - Fn::Select: - - 0 - - Fn::GetAZs: '' - CidrBlock: 10.19.231.0/24 - MapPublicIpOnLaunch: false - PublicRouteTable: - Type: AWS::EC2::RouteTable - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - VpcId: - Ref: VPC - DefaultPublicRoute: - Type: AWS::EC2::Route - DependsOn: InternetGatewayAttachment - Properties: - RouteTableId: - Ref: PublicRouteTable - DestinationCidrBlock: 0.0.0.0/0 - GatewayId: - Ref: InternetGateway - PublicSubnet1RouteTableAssociation: - Type: AWS::EC2::SubnetRouteTableAssociation - Properties: - RouteTableId: - Ref: PublicRouteTable - SubnetId: - Ref: PublicSubnet1 - PublicSubnet2RouteTableAssociation: - Type: AWS::EC2::SubnetRouteTableAssociation - Properties: - RouteTableId: - Ref: PublicRouteTable - SubnetId: - Ref: PublicSubnet2 - NatGatewayEIP: - Type: AWS::EC2::EIP - DependsOn: InternetGatewayAttachment - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - Domain: vpc - NatGateway: - Type: AWS::EC2::NatGateway - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - AllocationId: - Fn::GetAtt: - - NatGatewayEIP - - AllocationId - SubnetId: - Ref: PublicSubnet1 - PrivateRouteTable: - Type: AWS::EC2::RouteTable - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - VpcId: - Ref: VPC - DefaultPrivateRoute: - Type: AWS::EC2::Route - Properties: - RouteTableId: - Ref: PrivateRouteTable - DestinationCidrBlock: 0.0.0.0/0 - NatGatewayId: - Ref: NatGateway - PrivateSubnetRouteTableAssociation: - Type: AWS::EC2::SubnetRouteTableAssociation - Properties: - RouteTableId: - Ref: PrivateRouteTable - SubnetId: - Ref: PrivateSubnet - KmsKeyAlias: - Type: AWS::KMS::Alias - Properties: - AliasName: alias/aws-data-wrangler-key - TargetKeyId: - Ref: KmsKey - KmsKey: - Type: AWS::KMS::Key - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - Description: Aws Data Wrangler Test Key. - EnableKeyRotation: true - KeyPolicy: - Version: '2012-10-17' - Id: aws-data-wrangler-key - Statement: - - Sid: Enable IAM User Permissions - Effect: Allow - Principal: - AWS: - Fn::Sub: arn:aws:iam::${AWS::AccountId}:root - Action: kms:* - Resource: '*' - - Sid: Allow administration of the key - Effect: Allow - Principal: - AWS: - Ref: AWS::AccountId - Action: - - kms:Create* - - kms:Describe* - - kms:Enable* - - kms:List* - - kms:Put* - - kms:Update* - - kms:Revoke* - - kms:Disable* - - kms:Get* - - kms:Delete* - - kms:ScheduleKeyDeletion - - kms:CancelKeyDeletion - Resource: '*' - Bucket: - Type: AWS::S3::Bucket - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - PublicAccessBlockConfiguration: - BlockPublicAcls: true - BlockPublicPolicy: true - IgnorePublicAcls: true - RestrictPublicBuckets: true - LifecycleConfiguration: - Rules: - - Id: CleaningUp - Status: Enabled - ExpirationInDays: 1 - AbortIncompleteMultipartUpload: - DaysAfterInitiation: 1 - NoncurrentVersionExpirationInDays: 1 - GlueDatabase: - Type: AWS::Glue::Database - Properties: - CatalogId: - Ref: AWS::AccountId - DatabaseInput: - Name: aws_data_wrangler - Description: AWS Data Wrangler Test Arena - Glue Database - LogGroup: - Type: AWS::Logs::LogGroup - Properties: - RetentionInDays: 30 - LogStream: - Type: AWS::Logs::LogStream - Properties: - LogGroupName: - Ref: LogGroup -Outputs: - Region: - Value: - Ref: AWS::Region - Description: AWS Region - VPC: - Value: - Ref: VPC - Export: - Name: aws-data-wrangler-base-VPC - Description: VPC ID - PublicSubnet1: - Value: - Ref: PublicSubnet1 - Export: - Name: aws-data-wrangler-base-PublicSubnet1 - Description: Subnet ID - PublicSubnet2: - Value: - Ref: PublicSubnet2 - Export: - Name: aws-data-wrangler-base-PublicSubnet2 - Description: Subnet ID 2 - PrivateSubnet: - Value: - Ref: PrivateSubnet - Export: - Name: aws-data-wrangler-base-PrivateSubnet - Description: Private Subnet ID - KmsKeyArn: - Value: - Fn::GetAtt: - - KmsKey - - Arn - Export: - Name: aws-data-wrangler-base-KmsKeyArn - Description: KMS Key ARN. - BucketName: - Value: - Ref: Bucket - Export: - Name: aws-data-wrangler-base-BucketName - Description: Name of the S3 Bucket used for tests. - GlueDatabaseName: - Value: - Ref: GlueDatabase - Description: Glue Database Name. - LogGroupName: - Value: - Ref: LogGroup - Description: LogGroup name. - LogStream: - Value: - Ref: LogStream - Description: LogStream name. diff --git a/cloudformation/databases.yaml b/cloudformation/databases.yaml deleted file mode 100644 index ca698e5df..000000000 --- a/cloudformation/databases.yaml +++ /dev/null @@ -1,582 +0,0 @@ -AWSTemplateFormatVersion: 2010-09-09 -Description: | - AWS Data Wrangler Development Databases Infrastructure Redshift, Aurora PostgreSQL, Aurora MySQL, Microsoft SQL Server -Parameters: - DatabasesPassword: - Type: String - Description: Password for all databases - NoEcho: true -Resources: - RedshiftRole: - Type: AWS::IAM::Role - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - AssumeRolePolicyDocument: - Version: 2012-10-17 - Statement: - - Effect: Allow - Principal: - Service: - - redshift.amazonaws.com - Action: - - sts:AssumeRole - Path: / - Policies: - - PolicyName: Root - PolicyDocument: - Version: 2012-10-17 - Statement: - - Effect: Allow - Action: - - kms:Encrypt - - kms:Decrypt - - kms:GenerateDataKey - Resource: - - Fn::ImportValue: aws-data-wrangler-base-KmsKeyArn - - Effect: Allow - Action: - - s3:Get* - - s3:List* - - s3:Put* - Resource: - - Fn::Sub: - - arn:aws:s3:::${Bucket} - - Bucket: - Fn::ImportValue: aws-data-wrangler-base-BucketName - - Fn::Sub: - - arn:aws:s3:::${Bucket}/* - - Bucket: - Fn::ImportValue: aws-data-wrangler-base-BucketName - - Effect: Allow - Action: - - lakeformation:GrantPermissions - Resource: '*' - - Effect: Allow - Action: - - glue:SearchTables - - glue:GetConnections - - glue:GetDataCatalogEncryptionSettings - - glue:GetTables - - glue:GetTableVersions - - glue:GetPartitions - - glue:DeleteTableVersion - - glue:BatchGetPartition - - glue:GetDatabases - - glue:GetTags - - glue:GetTable - - glue:GetDatabase - - glue:GetPartition - - glue:GetTableVersion - - glue:GetConnection - - glue:GetUserDefinedFunction - - glue:GetUserDefinedFunctions - Resource: '*' - RedshiftSubnetGroup: - Type: AWS::Redshift::ClusterSubnetGroup - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - Description: AWS Data Wrangler Test Arena - Redshift Subnet Group - SubnetIds: - - Fn::ImportValue: aws-data-wrangler-base-PublicSubnet1 - DatabaseSecurityGroup: - Type: AWS::EC2::SecurityGroup - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - - Key: Name - Value: aws-data-wrangler - VpcId: - Fn::ImportValue: aws-data-wrangler-base-VPC - GroupDescription: AWS Data Wrangler Test Arena - Redshift security group - DatabaseSecurityGroupIngress: - Type: AWS::EC2::SecurityGroupIngress - Properties: - Description: Self Referencing - GroupId: - Ref: DatabaseSecurityGroup - IpProtocol: '-1' - FromPort: 0 - ToPort: 65535 - SourceSecurityGroupId: - Ref: DatabaseSecurityGroup - Redshift: - Type: AWS::Redshift::Cluster - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - DBName: test - MasterUsername: test - MasterUserPassword: - Ref: DatabasesPassword - NodeType: dc2.large - ClusterType: single-node - VpcSecurityGroupIds: - - Ref: DatabaseSecurityGroup - ClusterSubnetGroupName: - Ref: RedshiftSubnetGroup - PubliclyAccessible: true - Port: 5439 - IamRoles: - - Fn::GetAtt: - - RedshiftRole - - Arn - RdsSubnetGroup: - Type: AWS::RDS::DBSubnetGroup - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - DBSubnetGroupDescription: RDS Database Subnet Group - SubnetIds: - - Fn::ImportValue: aws-data-wrangler-base-PublicSubnet1 - - Fn::ImportValue: aws-data-wrangler-base-PublicSubnet2 - RdsRole: - Type: AWS::IAM::Role - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - AssumeRolePolicyDocument: - Version: 2012-10-17 - Statement: - - Effect: Allow - Principal: - Service: - - rds.amazonaws.com - Action: - - sts:AssumeRole - Path: / - Policies: - - PolicyName: S3GetAndList - PolicyDocument: - Version: 2012-10-17 - Statement: - - Effect: Allow - Action: - - s3:Get* - - s3:List* - - s3:Put* - Resource: - - Fn::Sub: - - arn:aws:s3:::${Bucket} - - Bucket: - Fn::ImportValue: aws-data-wrangler-base-BucketName - - Fn::Sub: - - arn:aws:s3:::${Bucket}/* - - Bucket: - Fn::ImportValue: aws-data-wrangler-base-BucketName - PostgresqlParameterGroup: - Type: AWS::RDS::DBClusterParameterGroup - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - Description: Postgres 11 - Family: aurora-postgresql11 - Parameters: - apg_plan_mgmt.capture_plan_baselines: 'off' - AuroraClusterPostgresql: - Type: AWS::RDS::DBCluster - DeletionPolicy: Delete - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - Engine: aurora-postgresql - EngineVersion: '11.6' - DBClusterIdentifier: postgresql-cluster-wrangler - MasterUsername: test - MasterUserPassword: - Ref: DatabasesPassword - BackupRetentionPeriod: 1 - DBSubnetGroupName: - Ref: RdsSubnetGroup - VpcSecurityGroupIds: - - Ref: DatabaseSecurityGroup - DBClusterParameterGroupName: - Ref: PostgresqlParameterGroup - AssociatedRoles: - - FeatureName: s3Import - RoleArn: - Fn::GetAtt: - - RdsRole - - Arn - AuroraInstancePostgresql: - Type: AWS::RDS::DBInstance - DeletionPolicy: Delete - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - Engine: aurora-postgresql - EngineVersion: '11.6' - DBInstanceIdentifier: postgresql-instance-wrangler - DBClusterIdentifier: - Ref: AuroraClusterPostgresql - DBInstanceClass: db.t3.medium - DBSubnetGroupName: - Ref: RdsSubnetGroup - PubliclyAccessible: true - MysqlParameterGroup: - Type: AWS::RDS::DBClusterParameterGroup - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - Description: Mysql 5.7 - Family: aurora-mysql5.7 - Parameters: - aurora_load_from_s3_role: - Fn::GetAtt: - - RdsRole - - Arn - aws_default_s3_role: - Fn::GetAtt: - - RdsRole - - Arn - aurora_select_into_s3_role: - Fn::GetAtt: - - RdsRole - - Arn - AuroraClusterMysql: - Type: AWS::RDS::DBCluster - DeletionPolicy: Delete - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - Engine: aurora-mysql - EngineVersion: '5.7' - DBClusterIdentifier: mysql-cluster-wrangler - MasterUsername: test - MasterUserPassword: - Ref: DatabasesPassword - BackupRetentionPeriod: 1 - DBSubnetGroupName: - Ref: RdsSubnetGroup - VpcSecurityGroupIds: - - Ref: DatabaseSecurityGroup - DBClusterParameterGroupName: - Ref: MysqlParameterGroup - DatabaseName: test - AssociatedRoles: - - RoleArn: - Fn::GetAtt: - - RdsRole - - Arn - AuroraInstanceMysql: - Type: AWS::RDS::DBInstance - DeletionPolicy: Delete - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - Engine: aurora-mysql - EngineVersion: '5.7' - DBInstanceIdentifier: mysql-instance-wrangler - DBClusterIdentifier: - Ref: AuroraClusterMysql - DBInstanceClass: db.t3.small - DBSubnetGroupName: - Ref: RdsSubnetGroup - PubliclyAccessible: true - SqlServerInstance: - Type: AWS::RDS::DBInstance - DeletionPolicy: Delete - Properties: - Tags: - - Key: Env - Value: aws-data-wrangler - Engine: sqlserver-ex - EngineVersion: '15.00' - DBInstanceIdentifier: sqlserver-instance-wrangler - DBInstanceClass: db.t3.small - AllocatedStorage: '20' - MasterUsername: test - MasterUserPassword: - Ref: DatabasesPassword - DBSubnetGroupName: - Ref: RdsSubnetGroup - VPCSecurityGroups: - - Ref: DatabaseSecurityGroup - PubliclyAccessible: true - AssociatedRoles: - - RoleArn: - Fn::GetAtt: - - RdsRole - - Arn - FeatureName: S3_INTEGRATION - RedshiftGlueConnection: - Type: AWS::Glue::Connection - Properties: - CatalogId: - Ref: AWS::AccountId - ConnectionInput: - Description: Connect to Redshift. - ConnectionType: JDBC - PhysicalConnectionRequirements: - AvailabilityZone: - Fn::Select: - - 0 - - Fn::GetAZs: '' - SecurityGroupIdList: - - Ref: DatabaseSecurityGroup - SubnetId: - Fn::ImportValue: aws-data-wrangler-base-PrivateSubnet - ConnectionProperties: - JDBC_CONNECTION_URL: - Fn::Sub: jdbc:redshift://${Redshift.Endpoint.Address}:${Redshift.Endpoint.Port}/test - USERNAME: test - PASSWORD: - Ref: DatabasesPassword - Name: aws-data-wrangler-redshift - PostgresqlGlueConnection: - Type: AWS::Glue::Connection - Properties: - CatalogId: - Ref: AWS::AccountId - ConnectionInput: - Description: Connect to Aurora (PostgreSQL). - ConnectionType: JDBC - PhysicalConnectionRequirements: - AvailabilityZone: - Fn::Select: - - 0 - - Fn::GetAZs: '' - SecurityGroupIdList: - - Ref: DatabaseSecurityGroup - SubnetId: - Fn::ImportValue: aws-data-wrangler-base-PrivateSubnet - ConnectionProperties: - JDBC_CONNECTION_URL: - Fn::Sub: jdbc:postgresql://${AuroraInstancePostgresql.Endpoint.Address}:${AuroraInstancePostgresql.Endpoint.Port}/postgres - USERNAME: test - PASSWORD: - Ref: DatabasesPassword - Name: aws-data-wrangler-postgresql - MysqlGlueConnection: - Type: AWS::Glue::Connection - Properties: - CatalogId: - Ref: AWS::AccountId - ConnectionInput: - Description: Connect to Aurora (MySQL). - ConnectionType: JDBC - PhysicalConnectionRequirements: - AvailabilityZone: - Fn::Select: - - 0 - - Fn::GetAZs: '' - SecurityGroupIdList: - - Ref: DatabaseSecurityGroup - SubnetId: - Fn::ImportValue: aws-data-wrangler-base-PrivateSubnet - ConnectionProperties: - JDBC_CONNECTION_URL: - Fn::Sub: jdbc:mysql://${AuroraInstanceMysql.Endpoint.Address}:${AuroraInstanceMysql.Endpoint.Port}/test - USERNAME: test - PASSWORD: - Ref: DatabasesPassword - Name: aws-data-wrangler-mysql - MysqlGlueConnectionSSL: - Type: AWS::Glue::Connection - Properties: - CatalogId: - Ref: AWS::AccountId - ConnectionInput: - Description: Connect to Aurora (MySQL) SSL enabled. - ConnectionType: JDBC - PhysicalConnectionRequirements: - AvailabilityZone: - Fn::Select: - - 0 - - Fn::GetAZs: '' - SecurityGroupIdList: - - Ref: DatabaseSecurityGroup - SubnetId: - Fn::ImportValue: aws-data-wrangler-base-PrivateSubnet - ConnectionProperties: - JDBC_CONNECTION_URL: - Fn::Sub: jdbc:mysql://${AuroraInstanceMysql.Endpoint.Address}:${AuroraInstanceMysql.Endpoint.Port}/test - JDBC_ENFORCE_SSL: true - CUSTOM_JDBC_CERT: s3://rds-downloads/rds-combined-ca-bundle.pem - USERNAME: test - PASSWORD: - Ref: DatabasesPassword - Name: aws-data-wrangler-mysql-ssl - SqlServerGlueConnection: - Type: AWS::Glue::Connection - Properties: - CatalogId: - Ref: AWS::AccountId - ConnectionInput: - Description: Connect to SQL Server. - ConnectionType: JDBC - PhysicalConnectionRequirements: - AvailabilityZone: - Fn::Select: - - 0 - - Fn::GetAZs: '' - SecurityGroupIdList: - - Ref: DatabaseSecurityGroup - SubnetId: - Fn::ImportValue: aws-data-wrangler-base-PrivateSubnet - ConnectionProperties: - JDBC_CONNECTION_URL: - Fn::Sub: jdbc:sqlserver://${SqlServerInstance.Endpoint.Address}:${SqlServerInstance.Endpoint.Port};databaseName=test - USERNAME: test - PASSWORD: - Ref: DatabasesPassword - Name: aws-data-wrangler-sqlserver - GlueCatalogSettings: - Type: AWS::Glue::DataCatalogEncryptionSettings - Properties: - CatalogId: - Ref: AWS::AccountId - DataCatalogEncryptionSettings: - ConnectionPasswordEncryption: - KmsKeyId: - Fn::ImportValue: aws-data-wrangler-base-KmsKeyArn - ReturnConnectionPasswordEncrypted: true - EncryptionAtRest: - CatalogEncryptionMode: DISABLED - RedshiftSecret: - Type: AWS::SecretsManager::Secret - Properties: - Name: aws-data-wrangler/redshift - Description: Redshift credentials - SecretString: - Fn::Sub: | - { - "username": "test", - "password": "${DatabasesPassword}", - "engine": "redshift", - "host": "${Redshift.Endpoint.Address}", - "port": ${Redshift.Endpoint.Port}, - "dbClusterIdentifier": "${Redshift}" - } - Tags: - - Key: Env - Value: aws-data-wrangler - PostgresqlSecret: - Type: AWS::SecretsManager::Secret - Properties: - Name: aws-data-wrangler/postgresql - Description: Postgresql credentials - SecretString: - Fn::Sub: | - { - "username": "test", - "password": "${DatabasesPassword}", - "engine": "postgresql", - "host": "${AuroraInstancePostgresql.Endpoint.Address}", - "port": ${AuroraInstancePostgresql.Endpoint.Port}, - "dbClusterIdentifier": "${AuroraInstancePostgresql}", - "dbname": "postgres" - } - Tags: - - Key: Env - Value: aws-data-wrangler - MysqlSecret: - Type: AWS::SecretsManager::Secret - Properties: - Name: aws-data-wrangler/mysql - Description: Mysql credentials - SecretString: - Fn::Sub: | - { - "username": "test", - "password": "${DatabasesPassword}", - "engine": "mysql", - "host": "${AuroraInstanceMysql.Endpoint.Address}", - "port": ${AuroraInstanceMysql.Endpoint.Port}, - "dbClusterIdentifier": "${AuroraInstanceMysql}", - "dbname": "test" - } - Tags: - - Key: Env - Value: aws-data-wrangler - SqlServerSecret: - Type: AWS::SecretsManager::Secret - Properties: - Name: aws-data-wrangler/sqlserver - Description: SQL Server credentials - SecretString: - Fn::Sub: | - { - "username": "test", - "password": "${DatabasesPassword}", - "engine": "sqlserver", - "host": "${SqlServerInstance.Endpoint.Address}", - "port": ${SqlServerInstance.Endpoint.Port}, - "dbClusterIdentifier": "${SqlServerInstance}", - "dbname": "test" - } - Tags: - - Key: Env - Value: aws-data-wrangler - DatabaseSecurityGroupId: - Type: AWS::SSM::Parameter - Properties: - Type: String - Description: Database Security Group Id - Name: /Wrangler/EC2/DatabaseSecurityGroupId - Value: - Fn::GetAtt: - - DatabaseSecurityGroup - - GroupId -Outputs: - DatabasesPassword: - Value: - Ref: DatabasesPassword - Description: Password. - RedshiftIdentifier: - Value: - Ref: Redshift - RedshiftAddress: - Value: - Fn::GetAtt: - - Redshift - - Endpoint.Address - Description: Redshift address. - RedshiftPort: - Value: - Fn::GetAtt: - - Redshift - - Endpoint.Port - Description: Redshift Endpoint Port. - RedshiftRole: - Value: - Fn::GetAtt: - - RedshiftRole - - Arn - Description: Redshift IAM role. - PostgresqlAddress: - Value: - Fn::GetAtt: - - AuroraInstancePostgresql - - Endpoint.Address - Description: Postgresql Address - MysqlAddress: - Value: - Fn::GetAtt: - - AuroraInstanceMysql - - Endpoint.Address - Description: Mysql Address - SqlServerAddress: - Value: - Fn::GetAtt: - - SqlServerInstance - - Endpoint.Address - Description: SQL Server Address - DatabaseSecurityGroupId: - Value: - Fn::GetAtt: - - DatabaseSecurityGroup - - GroupId diff --git a/cloudformation/delete-base.sh b/cloudformation/delete-base.sh deleted file mode 100755 index 06b79ed34..000000000 --- a/cloudformation/delete-base.sh +++ /dev/null @@ -1,6 +0,0 @@ -#!/usr/bin/env bash -set -e - -# Deploying -aws cloudformation delete-stack \ - --stack-name aws-data-wrangler-base diff --git a/cloudformation/delete-databases.sh b/cloudformation/delete-databases.sh deleted file mode 100755 index dfbbb3806..000000000 --- a/cloudformation/delete-databases.sh +++ /dev/null @@ -1,6 +0,0 @@ -#!/usr/bin/env bash -set -e - -# Deleting -aws cloudformation delete-stack \ - --stack-name aws-data-wrangler-databases diff --git a/cloudformation/deploy-base.sh b/cloudformation/deploy-base.sh deleted file mode 100755 index 087c7ef6f..000000000 --- a/cloudformation/deploy-base.sh +++ /dev/null @@ -1,15 +0,0 @@ -#!/usr/bin/env bash -set -e - -# Linting and formatting the base stack -cfn-lint -t base.yaml -rm -rf temp.yaml -cfn-flip -c -l -n base.yaml temp.yaml -cfn-lint -t temp.yaml -mv temp.yaml base.yaml - -# Deploying -aws cloudformation deploy \ - --template-file base.yaml \ - --stack-name aws-data-wrangler-base \ - --capabilities CAPABILITY_IAM diff --git a/cloudformation/deploy-databases.sh b/cloudformation/deploy-databases.sh deleted file mode 100755 index 8fdeb959e..000000000 --- a/cloudformation/deploy-databases.sh +++ /dev/null @@ -1,19 +0,0 @@ -#!/usr/bin/env bash -set -e - -# Linting and formatting the base stack -cfn-lint -t databases.yaml -rm -rf temp.yaml -cfn-flip -c -l -n databases.yaml temp.yaml -cfn-lint -t temp.yaml -mv temp.yaml databases.yaml - -read -rp "Databases password [123456Ab]: " password -password=${password:-123456Ab} - -# Deploying -aws cloudformation deploy \ - --template-file databases.yaml \ - --stack-name aws-data-wrangler-databases \ - --capabilities CAPABILITY_IAM \ - --parameter-overrides DatabasesPassword="$password" diff --git a/cloudformation/security-group-databases-add-local-ip.sh b/cloudformation/security-group-databases-add-local-ip.sh deleted file mode 100755 index 4cad07f0f..000000000 --- a/cloudformation/security-group-databases-add-local-ip.sh +++ /dev/null @@ -1,15 +0,0 @@ -#!/usr/bin/env bash -set -e - -# Get my current IP address -LOCALIP=`host myip.opendns.com resolver1.opendns.com | grep myip | awk '{print $4}'` - -# Get security group ID -SGID=`aws cloudformation describe-stacks --stack-name aws-data-wrangler-databases --query "Stacks[0].Outputs[?OutputKey=='DatabaseSecurityGroupId'].OutputValue" --output text` - -# Update Security Group with local ip -aws ec2 authorize-security-group-ingress \ - --group-id ${SGID} \ - --protocol all \ - --port -1 \ - --cidr ${LOCALIP}/32 diff --git a/cloudformation/security-group-databases-check.sh b/cloudformation/security-group-databases-check.sh deleted file mode 100755 index a3f0a6a5c..000000000 --- a/cloudformation/security-group-databases-check.sh +++ /dev/null @@ -1,8 +0,0 @@ -#!/usr/bin/env bash -set -e - -# Get security group ID -SGID=`aws cloudformation describe-stacks --stack-name aws-data-wrangler-databases --query "Stacks[0].Outputs[?OutputKey=='DatabaseSecurityGroupId'].OutputValue" --output text` - -# Check to see current setting -aws ec2 describe-security-groups --group-id ${SGID} diff --git a/tests/test_catalog.py b/tests/test_catalog.py index 6354f005d..8e5812d19 100644 --- a/tests/test_catalog.py +++ b/tests/test_catalog.py @@ -1,3 +1,5 @@ +import calendar +import time from typing import Optional import boto3 @@ -24,6 +26,9 @@ def test_create_table(path: str, glue_database: str, glue_table: str, table_type ) if transaction_id: wr.lakeformation.commit_transaction(transaction_id) + query_as_of_time = calendar.timegm(time.gmtime()) + 5 # Adding minor delay to avoid concurrency + df = wr.catalog.table(database=glue_database, table=glue_table, query_as_of_time=query_as_of_time) + assert df.shape == (4, 4) assert wr.catalog.does_table_exist(database=glue_database, table=glue_table) is True From 23eb1c43871ec743e40de011eab50a36dfd7fc58 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Fri, 11 Jun 2021 16:06:17 +0100 Subject: [PATCH 15/36] [skip ci] - syncing with main branch --- awswrangler/athena/_utils.py | 24 ++- awswrangler/s3/__init__.py | 2 + awswrangler/s3/_read_excel.py | 6 +- awswrangler/s3/_select.py | 217 +++++++++++++++++++++++++++ awswrangler/s3/_write_excel.py | 6 +- test_infra/requirements.txt | 3 +- test_infra/stacks/base_stack.py | 1 + test_infra/stacks/databases_stack.py | 29 ++-- tests/test_moto.py | 6 +- tests/test_s3_excel.py | 6 +- tests/test_s3_select.py | 161 ++++++++++++++++++++ 11 files changed, 439 insertions(+), 22 deletions(-) create mode 100644 awswrangler/s3/_select.py create mode 100644 tests/test_s3_select.py diff --git a/awswrangler/athena/_utils.py b/awswrangler/athena/_utils.py index 639e330cd..664e52e7a 100644 --- a/awswrangler/athena/_utils.py +++ b/awswrangler/athena/_utils.py @@ -396,10 +396,17 @@ def create_athena_bucket(boto3_session: Optional[boto3.Session] = None) -> str: session: boto3.Session = _utils.ensure_session(session=boto3_session) account_id: str = sts.get_account_id(boto3_session=session) region_name: str = str(session.region_name).lower() - s3_output = f"s3://aws-athena-query-results-{account_id}-{region_name}/" - s3_resource = _utils.resource(service_name="s3", session=session) - s3_resource.Bucket(s3_output) - return s3_output + bucket_name = f"aws-athena-query-results-{account_id}-{region_name}" + path = f"s3://{bucket_name}/" + resource = _utils.resource(service_name="s3", session=session) + bucket = resource.Bucket(bucket_name) + args = {} if region_name == "us-east-1" else {"CreateBucketConfiguration": {"LocationConstraint": region_name}} + try: + bucket.create(**args) + except resource.meta.client.exceptions.BucketAlreadyOwnedByYou as err: + _logger.debug("Bucket %s already exists.", err.response["Error"]["BucketName"]) + bucket.wait_until_exists() + return path @apply_configs @@ -410,6 +417,7 @@ def start_query_execution( workgroup: Optional[str] = None, encryption: Optional[str] = None, kms_key: Optional[str] = None, + params: Optional[Dict[str, Any]] = None, boto3_session: Optional[boto3.Session] = None, data_source: Optional[str] = None, ) -> str: @@ -434,6 +442,10 @@ def start_query_execution( None, 'SSE_S3', 'SSE_KMS', 'CSE_KMS'. kms_key : str, optional For SSE-KMS and CSE-KMS , this is the KMS key ARN or ID. + params: Dict[str, any], optional + Dict of parameters that will be used for constructing the SQL query. Only named parameters are supported. + The dict needs to contain the information in the form {'name': 'value'} and the SQL query needs to contain + `:name;`. Note that for varchar columns and similar, you must surround the value in single quotes. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. data_source : str, optional @@ -457,6 +469,10 @@ def start_query_execution( >>> query_exec_id = wr.athena.start_query_execution(sql='...', database='...', data_source='...') """ + if params is None: + params = {} + for key, value in params.items(): + sql = sql.replace(f":{key};", str(value)) session: boto3.Session = _utils.ensure_session(session=boto3_session) wg_config: _WorkGroupConfig = _get_workgroup_config(session=session, workgroup=workgroup) return _start_query_execution( diff --git a/awswrangler/s3/__init__.py b/awswrangler/s3/__init__.py index e95810ece..b2fbadba1 100644 --- a/awswrangler/s3/__init__.py +++ b/awswrangler/s3/__init__.py @@ -9,6 +9,7 @@ from awswrangler.s3._read_excel import read_excel # noqa from awswrangler.s3._read_parquet import read_parquet, read_parquet_metadata, read_parquet_table # noqa from awswrangler.s3._read_text import read_csv, read_fwf, read_json # noqa +from awswrangler.s3._select import select_query from awswrangler.s3._upload import upload # noqa from awswrangler.s3._wait import wait_objects_exist, wait_objects_not_exist # noqa from awswrangler.s3._write_excel import to_excel # noqa @@ -33,6 +34,7 @@ "read_json", "wait_objects_exist", "wait_objects_not_exist", + "select_query", "store_parquet_metadata", "to_parquet", "to_csv", diff --git a/awswrangler/s3/_read_excel.py b/awswrangler/s3/_read_excel.py index 25bb438c4..9fd98c759 100644 --- a/awswrangler/s3/_read_excel.py +++ b/awswrangler/s3/_read_excel.py @@ -26,6 +26,11 @@ def read_excel( This function accepts any Pandas's read_excel() argument. https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_excel.html + Note + ---- + Depending on the file extension ('xlsx', 'xls', 'odf'...), an additional library + might have to be installed first (e.g. xlrd). + Note ---- In case of `use_threads=True` the number of threads @@ -77,6 +82,5 @@ def read_excel( s3_additional_kwargs=s3_additional_kwargs, boto3_session=session, ) as f: - pandas_kwargs["engine"] = "openpyxl" _logger.debug("pandas_kwargs: %s", pandas_kwargs) return pd.read_excel(f, **pandas_kwargs) diff --git a/awswrangler/s3/_select.py b/awswrangler/s3/_select.py new file mode 100644 index 000000000..399d75278 --- /dev/null +++ b/awswrangler/s3/_select.py @@ -0,0 +1,217 @@ +"""Amazon S3 Select Module (PRIVATE).""" + +import concurrent.futures +import itertools +import json +import logging +import pprint +from typing import Any, Dict, Iterator, List, Optional, Tuple, Union + +import boto3 +import pandas as pd + +from awswrangler import _utils, exceptions +from awswrangler.s3._describe import size_objects + +_logger: logging.Logger = logging.getLogger(__name__) + +_RANGE_CHUNK_SIZE: int = int(1024 * 1024) + + +def _gen_scan_range(obj_size: int) -> Iterator[Tuple[int, int]]: + for i in range(0, obj_size, _RANGE_CHUNK_SIZE): + yield (i, i + min(_RANGE_CHUNK_SIZE, obj_size - i)) + + +def _select_object_content( + args: Dict[str, Any], + client_s3: boto3.Session, + scan_range: Optional[Tuple[int, int]] = None, +) -> pd.DataFrame: + if scan_range: + response = client_s3.select_object_content(**args, ScanRange={"Start": scan_range[0], "End": scan_range[1]}) + else: + response = client_s3.select_object_content(**args) + + dfs: List[pd.DataFrame] = [] + partial_record: str = "" + for event in response["Payload"]: + if "Records" in event: + records = event["Records"]["Payload"].decode(encoding="utf-8", errors="ignore").split("\n") + records[0] = partial_record + records[0] + # Record end can either be a partial record or a return char + partial_record = records.pop() + dfs.append( + pd.DataFrame( + [json.loads(record) for record in records], + ) + ) + if not dfs: + return pd.DataFrame() + return pd.concat(dfs, ignore_index=True) + + +def _paginate_stream( + args: Dict[str, Any], path: str, use_threads: Union[bool, int], boto3_session: Optional[boto3.Session] +) -> pd.DataFrame: + obj_size: int = size_objects( # type: ignore + path=[path], + use_threads=False, + boto3_session=boto3_session, + ).get(path) + if obj_size is None: + raise exceptions.InvalidArgumentValue(f"S3 object w/o defined size: {path}") + + dfs: List[pd.Dataframe] = [] + client_s3: boto3.client = _utils.client(service_name="s3", session=boto3_session) + + if use_threads is False: + dfs = list( + _select_object_content( + args=args, + client_s3=client_s3, + scan_range=scan_range, + ) + for scan_range in _gen_scan_range(obj_size=obj_size) + ) + else: + cpus: int = _utils.ensure_cpu_count(use_threads=use_threads) + with concurrent.futures.ThreadPoolExecutor(max_workers=cpus) as executor: + dfs = list( + executor.map( + _select_object_content, + itertools.repeat(args), + itertools.repeat(client_s3), + _gen_scan_range(obj_size=obj_size), + ) + ) + return pd.concat(dfs, ignore_index=True) + + +def select_query( + sql: str, + path: str, + input_serialization: str, + input_serialization_params: Dict[str, Union[bool, str]], + compression: Optional[str] = None, + use_threads: Union[bool, int] = False, + boto3_session: Optional[boto3.Session] = None, + s3_additional_kwargs: Optional[Dict[str, Any]] = None, +) -> pd.DataFrame: + r"""Filter contents of an Amazon S3 object based on SQL statement. + + Note: Scan ranges are only supported for uncompressed CSV/JSON, CSV (without quoted delimiters) + and JSON objects (in LINES mode only). It means scanning cannot be split across threads if the latter + conditions are not met, leading to lower performance. + + Parameters + ---------- + sql: str + SQL statement used to query the object. + path: str + S3 path to the object (e.g. s3://bucket/key). + input_serialization: str, + Format of the S3 object queried. + Valid values: "CSV", "JSON", or "Parquet". Case sensitive. + input_serialization_params: Dict[str, Union[bool, str]] + Dictionary describing the serialization of the S3 object. + compression: Optional[str] + Compression type of the S3 object. + Valid values: None, "gzip", or "bzip2". gzip and bzip2 are only valid for CSV and JSON objects. + use_threads : Union[bool, int] + True to enable concurrent requests, False to disable multiple threads. + If enabled os.cpu_count() is used as the max number of threads. + If integer is provided, specified number is used. + boto3_session : boto3.Session(), optional + Boto3 Session. The default boto3 session is used if none is provided. + s3_additional_kwargs : Optional[Dict[str, Any]] + Forwarded to botocore requests. + Valid values: "SSECustomerAlgorithm", "SSECustomerKey", "ExpectedBucketOwner". + e.g. s3_additional_kwargs={'SSECustomerAlgorithm': 'md5'} + + Returns + ------- + pandas.DataFrame + Pandas DataFrame with results from query. + + Examples + -------- + Reading a gzip compressed JSON document + + >>> import awswrangler as wr + >>> df = wr.s3.select_query( + ... sql='SELECT * FROM s3object[*][*]', + ... path='s3://bucket/key.json.gzip', + ... input_serialization='JSON', + ... input_serialization_params={ + ... 'Type': 'Document', + ... }, + ... compression="gzip", + ... ) + + Reading an entire CSV object using threads + + >>> import awswrangler as wr + >>> df = wr.s3.select_query( + ... sql='SELECT * FROM s3object', + ... path='s3://bucket/key.csv', + ... input_serialization='CSV', + ... input_serialization_params={ + ... 'FileHeaderInfo': 'Use', + ... 'RecordDelimiter': '\r\n' + ... }, + ... use_threads=True, + ... ) + + Reading a single column from Parquet object with pushdown filter + + >>> import awswrangler as wr + >>> df = wr.s3.select_query( + ... sql='SELECT s.\"id\" FROM s3object s where s.\"id\" = 1.0', + ... path='s3://bucket/key.snappy.parquet', + ... input_serialization='Parquet', + ... ) + """ + if path.endswith("/"): + raise exceptions.InvalidArgumentValue(" argument should be an S3 key, not a prefix.") + if input_serialization not in ["CSV", "JSON", "Parquet"]: + raise exceptions.InvalidArgumentValue(" argument must be 'CSV', 'JSON' or 'Parquet'") + if compression not in [None, "gzip", "bzip2"]: + raise exceptions.InvalidCompression(f"Invalid {compression} compression, please use None, 'gzip' or 'bzip2'.") + if compression and (input_serialization not in ["CSV", "JSON"]): + raise exceptions.InvalidArgumentCombination( + "'gzip' or 'bzip2' are only valid for input 'CSV' or 'JSON' objects." + ) + bucket, key = _utils.parse_path(path) + + args: Dict[str, Any] = { + "Bucket": bucket, + "Key": key, + "Expression": sql, + "ExpressionType": "SQL", + "RequestProgress": {"Enabled": False}, + "InputSerialization": { + input_serialization: input_serialization_params, + "CompressionType": compression.upper() if compression else "NONE", + }, + "OutputSerialization": { + "JSON": {}, + }, + } + if s3_additional_kwargs: + args.update(s3_additional_kwargs) + _logger.debug("args:\n%s", pprint.pformat(args)) + + if any( + [ + compression, + input_serialization_params.get("AllowQuotedRecordDelimiter"), + input_serialization_params.get("Type") == "Document", + ] + ): # Scan range is only supported for uncompressed CSV/JSON, CSV (without quoted delimiters) + # and JSON objects (in LINES mode only) + _logger.debug("Scan ranges are not supported given provided input.") + client_s3: boto3.client = _utils.client(service_name="s3", session=boto3_session) + return _select_object_content(args=args, client_s3=client_s3) + + return _paginate_stream(args=args, path=path, use_threads=use_threads, boto3_session=boto3_session) diff --git a/awswrangler/s3/_write_excel.py b/awswrangler/s3/_write_excel.py index 1556d1f8d..af3b7fd4a 100644 --- a/awswrangler/s3/_write_excel.py +++ b/awswrangler/s3/_write_excel.py @@ -27,6 +27,11 @@ def to_excel( This function accepts any Pandas's read_excel() argument. https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_excel.html + Note + ---- + Depending on the file extension ('xlsx', 'xls', 'odf'...), an additional library + might have to be installed first (e.g. xlrd). + Note ---- In case of `use_threads=True` the number of threads @@ -83,7 +88,6 @@ def to_excel( s3_additional_kwargs=s3_additional_kwargs, boto3_session=session, ) as f: - pandas_kwargs["engine"] = "openpyxl" _logger.debug("pandas_kwargs: %s", pandas_kwargs) df.to_excel(f, **pandas_kwargs) return path diff --git a/test_infra/requirements.txt b/test_infra/requirements.txt index fc21efbfb..f7d1f19a0 100644 --- a/test_infra/requirements.txt +++ b/test_infra/requirements.txt @@ -7,4 +7,5 @@ aws-cdk.aws_logs>=1.106.1 aws-cdk.aws_s3>=1.106.1 aws-cdk.aws_redshift>=1.106.1 aws-cdk.aws_rds>=1.106.1 -aws_cdk.aws_secretsmanager>=1.106.1 \ No newline at end of file +aws_cdk.aws_secretsmanager>=1.106.1 +aws_cdk.aws_ssm>=1.106.1 \ No newline at end of file diff --git a/test_infra/stacks/base_stack.py b/test_infra/stacks/base_stack.py index 6d216dcc8..f96457d22 100644 --- a/test_infra/stacks/base_stack.py +++ b/test_infra/stacks/base_stack.py @@ -18,6 +18,7 @@ def __init__(self, scope: cdk.Construct, construct_id: str, **kwargs: str) -> No enable_dns_hostnames=True, enable_dns_support=True, ) + cdk.Tags.of(self.vpc).add("Name", "aws-data-wrangler") self.key = kms.Key( self, id="aws-data-wrangler-key", diff --git a/test_infra/stacks/databases_stack.py b/test_infra/stacks/databases_stack.py index cfa528e09..90db53522 100644 --- a/test_infra/stacks/databases_stack.py +++ b/test_infra/stacks/databases_stack.py @@ -7,7 +7,8 @@ from aws_cdk import aws_rds as rds from aws_cdk import aws_redshift as redshift from aws_cdk import aws_s3 as s3 -from aws_cdk import aws_secretsmanager as ssm +from aws_cdk import aws_secretsmanager as secrets +from aws_cdk import aws_ssm as ssm from aws_cdk import core as cdk @@ -41,11 +42,11 @@ def __init__( def _set_db_infra(self) -> None: self.db_username = "test" # fmt: off - self.db_password_secret = ssm.Secret( + self.db_password_secret = secrets.Secret( self, "db-password-secret", secret_name="aws-data-wrangler/db_password", - generate_secret_string=ssm.SecretStringGenerator(exclude_characters="/@\"\' \\"), + generate_secret_string=secrets.SecretStringGenerator(exclude_characters="/@\"\' \\"), ).secret_value # fmt: on self.db_password = self.db_password_secret.to_string() @@ -56,6 +57,12 @@ def _set_db_infra(self) -> None: description="AWS Data Wrangler Test Arena - Database security group", ) self.db_security_group.add_ingress_rule(ec2.Peer.any_ipv4(), ec2.Port.all_traffic()) + ssm.StringParameter( + self, + "db-secruity-group-parameter", + parameter_name="/Wrangler/EC2/DatabaseSecurityGroupId", + string_value=self.db_security_group.security_group_id, + ) self.rds_subnet_group = rds.SubnetGroup( self, "aws-data-wrangler-rds-subnet-group", @@ -225,12 +232,12 @@ def _setup_redshift(self) -> None: subnet=self.vpc.private_subnets[0], security_groups=[self.db_security_group], ) - ssm.Secret( + secrets.Secret( self, "aws-data-wrangler-redshift-secret", secret_name="aws-data-wrangler/redshift", description="Redshift credentials", - generate_secret_string=ssm.SecretStringGenerator( + generate_secret_string=secrets.SecretStringGenerator( generate_string_key="dummy", secret_string_template=json.dumps( { @@ -308,12 +315,12 @@ def _setup_postgresql(self) -> None: subnet=self.vpc.private_subnets[0], security_groups=[self.db_security_group], ) - ssm.Secret( + secrets.Secret( self, "aws-data-wrangler-postgresql-secret", secret_name="aws-data-wrangler/postgresql", description="Postgresql credentials", - generate_secret_string=ssm.SecretStringGenerator( + generate_secret_string=secrets.SecretStringGenerator( generate_string_key="dummy", secret_string_template=json.dumps( { @@ -392,12 +399,12 @@ def _setup_mysql(self) -> None: subnet=self.vpc.private_subnets[0], security_groups=[self.db_security_group], ) - ssm.Secret( + secrets.Secret( self, "aws-data-wrangler-mysql-secret", secret_name="aws-data-wrangler/mysql", description="MySQL credentials", - generate_secret_string=ssm.SecretStringGenerator( + generate_secret_string=secrets.SecretStringGenerator( generate_string_key="dummy", secret_string_template=json.dumps( { @@ -453,12 +460,12 @@ def _setup_sqlserver(self) -> None: subnet=self.vpc.private_subnets[0], security_groups=[self.db_security_group], ) - ssm.Secret( + secrets.Secret( self, "aws-data-wrangler-sqlserver-secret", secret_name="aws-data-wrangler/sqlserver", description="SQL Server credentials", - generate_secret_string=ssm.SecretStringGenerator( + generate_secret_string=secrets.SecretStringGenerator( generate_string_key="dummy", secret_string_template=json.dumps( { diff --git a/tests/test_moto.py b/tests/test_moto.py index 91613ff3f..d3b0f58c3 100644 --- a/tests/test_moto.py +++ b/tests/test_moto.py @@ -42,8 +42,10 @@ def moto_subnet(): @pytest.fixture(scope="function") def moto_s3(): with moto.mock_s3(): - s3 = boto3.resource("s3") - s3.create_bucket(Bucket="bucket") + s3 = boto3.resource("s3", region_name="us-east-1") + s3.create_bucket( + Bucket="bucket", + ) yield s3 diff --git a/tests/test_s3_excel.py b/tests/test_s3_excel.py index 6f3fb86c8..b3ecb9142 100644 --- a/tests/test_s3_excel.py +++ b/tests/test_s3_excel.py @@ -8,10 +8,12 @@ logging.getLogger("awswrangler").setLevel(logging.DEBUG) +@pytest.mark.parametrize("ext", ["xlsx", "xlsm", "xls", "odf"]) @pytest.mark.parametrize("use_threads", [True, False, 2]) -def test_excel(path, use_threads): - file_path = f"{path}0.xlsx" +def test_excel(path, ext, use_threads): df = pd.DataFrame({"c0": [1, 2, 3], "c1": ["foo", "boo", "bar"]}) + + file_path = f"{path}0.{ext}" wr.s3.to_excel(df, file_path, use_threads=use_threads, index=False) df2 = wr.s3.read_excel(file_path, use_threads=use_threads) assert df.equals(df2) diff --git a/tests/test_s3_select.py b/tests/test_s3_select.py new file mode 100644 index 000000000..46218182c --- /dev/null +++ b/tests/test_s3_select.py @@ -0,0 +1,161 @@ +import logging + +import pandas as pd +import pytest + +import awswrangler as wr + +logging.getLogger("awswrangler").setLevel(logging.DEBUG) + + +@pytest.mark.parametrize("use_threads", [True, False, 2]) +def test_full_table(path, use_threads): + df = pd.DataFrame({"c0": [1, 2, 3], "c1": ["foo", "boo", "bar"], "c2": [4.0, 5.0, 6.0]}) + + # Parquet + file_path = f"{path}test_parquet_file.snappy.parquet" + wr.s3.to_parquet(df, file_path, compression="snappy") + df2 = wr.s3.select_query( + sql="select * from s3object", + path=file_path, + input_serialization="Parquet", + input_serialization_params={}, + use_threads=use_threads, + ) + assert df.equals(df2) + + # CSV + file_path = f"{path}test_csv_file.csv" + wr.s3.to_csv(df, file_path, index=False) + df3 = wr.s3.select_query( + sql="select * from s3object", + path=file_path, + input_serialization="CSV", + input_serialization_params={"FileHeaderInfo": "Use", "RecordDelimiter": "\n"}, + use_threads=use_threads, + ) + assert len(df.index) == len(df3.index) + assert list(df.columns) == list(df3.columns) + assert df.shape == df3.shape + + # JSON + file_path = f"{path}test_json_file.json" + wr.s3.to_json(df, file_path, orient="records") + df4 = wr.s3.select_query( + sql="select * from s3object[*][*]", + path=file_path, + input_serialization="JSON", + input_serialization_params={"Type": "Document"}, + use_threads=use_threads, + ) + assert df.equals(df4) + + +@pytest.mark.parametrize("use_threads", [True, False, 2]) +def test_push_down(path, use_threads): + df = pd.DataFrame({"c0": [1, 2, 3], "c1": ["foo", "boo", "bar"], "c2": [4.0, 5.0, 6.0]}) + + file_path = f"{path}test_parquet_file.snappy.parquet" + wr.s3.to_parquet(df, file_path, compression="snappy") + df2 = wr.s3.select_query( + sql='select * from s3object s where s."c0" = 1', + path=file_path, + input_serialization="Parquet", + input_serialization_params={}, + use_threads=use_threads, + ) + assert df2.shape == (1, 3) + assert df2.c0.sum() == 1 + + file_path = f"{path}test_parquet_file.gzip.parquet" + wr.s3.to_parquet(df, file_path, compression="gzip") + df2 = wr.s3.select_query( + sql='select * from s3object s where s."c0" = 99', + path=file_path, + input_serialization="Parquet", + input_serialization_params={}, + use_threads=use_threads, + ) + assert df2.shape == (0, 0) + + file_path = f"{path}test_csv_file.csv" + wr.s3.to_csv(df, file_path, header=False, index=False) + df3 = wr.s3.select_query( + sql='select s."_1" from s3object s limit 2', + path=file_path, + input_serialization="CSV", + input_serialization_params={"FileHeaderInfo": "None", "RecordDelimiter": "\n"}, + use_threads=use_threads, + ) + assert df3.shape == (2, 1) + + file_path = f"{path}test_json_file.json" + wr.s3.to_json(df, file_path, orient="records") + df4 = wr.s3.select_query( + sql="select count(*) from s3object[*][*]", + path=file_path, + input_serialization="JSON", + input_serialization_params={"Type": "Document"}, + use_threads=use_threads, + ) + assert df4.shape == (1, 1) + assert df4._1.sum() == 3 + + +@pytest.mark.parametrize("compression", ["gzip", "bz2"]) +def test_compression(path, compression): + df = pd.DataFrame({"c0": [1, 2, 3], "c1": ["foo", "boo", "bar"], "c2": [4.0, 5.0, 6.0]}) + + # CSV + file_path = f"{path}test_csv_file.csv" + wr.s3.to_csv(df, file_path, index=False, compression=compression) + df2 = wr.s3.select_query( + sql="select * from s3object", + path=file_path, + input_serialization="CSV", + input_serialization_params={"FileHeaderInfo": "Use", "RecordDelimiter": "\n"}, + compression="bzip2" if compression == "bz2" else compression, + use_threads=False, + ) + assert len(df.index) == len(df2.index) + assert list(df.columns) == list(df2.columns) + assert df.shape == df2.shape + + # JSON + file_path = f"{path}test_json_file.json" + wr.s3.to_json(df, file_path, orient="records", compression=compression) + df3 = wr.s3.select_query( + sql="select * from s3object[*][*]", + path=file_path, + input_serialization="JSON", + input_serialization_params={"Type": "Document"}, + compression="bzip2" if compression == "bz2" else compression, + use_threads=False, + ) + assert df.equals(df3) + + +@pytest.mark.parametrize( + "s3_additional_kwargs", + [None, {"ServerSideEncryption": "AES256"}, {"ServerSideEncryption": "aws:kms", "SSEKMSKeyId": None}], +) +def test_encryption(path, kms_key_id, s3_additional_kwargs): + if s3_additional_kwargs is not None and "SSEKMSKeyId" in s3_additional_kwargs: + s3_additional_kwargs["SSEKMSKeyId"] = kms_key_id + + df = pd.DataFrame({"c0": [1, 2, 3], "c1": ["foo", "boo", "bar"], "c2": [4.0, 5.0, 6.0]}) + file_path = f"{path}test_parquet_file.snappy.parquet" + wr.s3.to_parquet( + df, + file_path, + compression="snappy", + s3_additional_kwargs=s3_additional_kwargs, + ) + df2 = wr.s3.select_query( + sql="select * from s3object", + path=file_path, + input_serialization="Parquet", + input_serialization_params={}, + use_threads=False, + ) + assert df.equals(df2) From 016f3053530ca75aa41c651b63fc6426df0c6e87 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Fri, 9 Jul 2021 13:38:23 +0100 Subject: [PATCH 16/36] Merge main and adapt tests to API changes from Erie team --- .bumpversion.cfg | 2 +- CONTRIBUTING_COMMON_ERRORS.md | 6 +- README.md | 61 +++++---- awswrangler/__metadata__.py | 2 +- awswrangler/_utils.py | 2 +- awswrangler/athena/_read.py | 43 +++++-- awswrangler/catalog/_get.py | 6 +- awswrangler/mysql.py | 4 +- awswrangler/redshift.py | 22 +++- awswrangler/s3/_read_parquet.py | 2 +- awswrangler/s3/_read_text.py | 6 +- awswrangler/s3/_write.py | 17 +++ awswrangler/s3/_write_parquet.py | 25 +--- awswrangler/s3/_write_text.py | 26 ++-- building/lambda/Dockerfile | 2 +- docs/source/api.rst | 1 + docs/source/install.rst | 6 +- docs/source/what.rst | 2 +- requirements-dev.txt | 16 +-- requirements.txt | 8 +- setup.py | 8 +- tests/_utils.py | 12 +- tests/test_athena.py | 31 ++++- tests/test_lakeformation.py | 4 +- tests/test_metadata.py | 2 +- tests/test_redshift.py | 6 +- tests/test_s3_excel.py | 18 ++- tests/test_s3_select.py | 5 + tests/test_s3_text.py | 57 +++++++++ tox.ini | 1 + tutorials/001 - Introduction.ipynb | 20 +-- ...shift, MySQL, PostgreSQL, SQL Server.ipynb | 24 ++-- tutorials/014 - Schema Evolution.ipynb | 4 +- tutorials/021 - Global Configurations.ipynb | 2 +- ...22 - Writing Partitions Concurrently.ipynb | 2 +- .../023 - Flexible Partitions Filter.ipynb | 2 +- ...30 - Lake Formation Governed Tables.ipynb} | 116 +++++++++--------- 37 files changed, 362 insertions(+), 211 deletions(-) rename tutorials/{029 - Lake Formation Governed Tables.ipynb => 030 - Lake Formation Governed Tables.ipynb} (97%) diff --git a/.bumpversion.cfg b/.bumpversion.cfg index 39cc98c45..6aab500ec 100644 --- a/.bumpversion.cfg +++ b/.bumpversion.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 2.8.0 +current_version = 2.9.0 commit = False tag = False tag_name = {new_version} diff --git a/CONTRIBUTING_COMMON_ERRORS.md b/CONTRIBUTING_COMMON_ERRORS.md index b15e9d617..42bbf635e 100644 --- a/CONTRIBUTING_COMMON_ERRORS.md +++ b/CONTRIBUTING_COMMON_ERRORS.md @@ -13,9 +13,9 @@ Requirement already satisfied: pbr!=2.1.0,>=2.0.0 in ./.venv/lib/python3.7/site- Using legacy 'setup.py install' for python-Levenshtein, since package 'wheel' is not installed. Installing collected packages: awswrangler, python-Levenshtein Attempting uninstall: awswrangler - Found existing installation: awswrangler 2.8.0 - Uninstalling awswrangler-2.8.0: - Successfully uninstalled awswrangler-2.8.0 + Found existing installation: awswrangler 2.9.0 + Uninstalling awswrangler-2.9.0: + Successfully uninstalled awswrangler-2.9.0 Running setup.py develop for awswrangler Running setup.py install for python-Levenshtein ... error ERROR: Command errored out with exit status 1: diff --git a/README.md b/README.md index efdab218f..8c609bbe2 100644 --- a/README.md +++ b/README.md @@ -8,7 +8,7 @@ Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, Clo > An [AWS Professional Service](https://aws.amazon.com/professional-services/) open source initiative | aws-proserve-opensource@amazon.com -[![Release](https://img.shields.io/badge/release-2.8.0-brightgreen.svg)](https://pypi.org/project/awswrangler/) +[![Release](https://img.shields.io/badge/release-2.9.0-brightgreen.svg)](https://pypi.org/project/awswrangler/) [![Python Version](https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8%20%7C%203.9-brightgreen.svg)](https://anaconda.org/conda-forge/awswrangler) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) @@ -16,7 +16,6 @@ Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, Clo [![Checked with mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/) [![Coverage](https://img.shields.io/badge/coverage-91%25-brightgreen.svg)](https://pypi.org/project/awswrangler/) ![Static Checking](https://github.com/awslabs/aws-data-wrangler/workflows/Static%20Checking/badge.svg?branch=main) -![Build Status](https://codebuild.us-east-1.amazonaws.com/badges?uuid=eyJlbmNyeXB0ZWREYXRhIjoiL05FNGxiZCtNT05ibGUrbzY5TzJxaFlOcnFrUFlyNjhWRm5tTmg1bXJXRkdnYUFySzgycEUvMTBBbWxEUzZ2eUpOdjVpcmNQV2hsNkRzQTZtTTVwSjF3PSIsIml2UGFyYW1ldGVyU3BlYyI6IkQ1RVkxWjg5YloyaTJOcVgiLCJtYXRlcmlhbFNldFNlcmlhbCI6MX0%3D&branch=main) [![Documentation Status](https://readthedocs.org/projects/aws-data-wrangler/badge/?version=latest)](https://aws-data-wrangler.readthedocs.io/?badge=latest) | Source | Downloads | Installation Command | @@ -24,7 +23,7 @@ Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, Clo | **[PyPi](https://pypi.org/project/awswrangler/)** | [![PyPI Downloads](https://pepy.tech/badge/awswrangler)](https://pypi.org/project/awswrangler/) | `pip install awswrangler` | | **[Conda](https://anaconda.org/conda-forge/awswrangler)** | [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/awswrangler.svg)](https://anaconda.org/conda-forge/awswrangler) | `conda install -c conda-forge awswrangler` | -> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#aws-glue-pyspark-jobs), MWAA):**
+> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-glue-pyspark-jobs), MWAA):**
➡️ `pip install pyarrow==2 awswrangler` Powered By [](https://arrow.apache.org/powered_by/) @@ -42,7 +41,7 @@ Powered By [](http Installation command: `pip install awswrangler` -> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#aws-glue-pyspark-jobs), MWAA):**
+> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-glue-pyspark-jobs), MWAA):**
➡️`pip install pyarrow==2 awswrangler` ```py3 @@ -96,17 +95,17 @@ FROM "sampleDB"."sampleTable" ORDER BY time DESC LIMIT 3 ## [Read The Docs](https://aws-data-wrangler.readthedocs.io/) -- [**What is AWS Data Wrangler?**](https://aws-data-wrangler.readthedocs.io/en/2.8.0/what.html) -- [**Install**](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html) - - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#pypi-pip) - - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#conda) - - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#aws-lambda-layer) - - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#aws-glue-python-shell-jobs) - - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#aws-glue-pyspark-jobs) - - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#amazon-sagemaker-notebook) - - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#amazon-sagemaker-notebook-lifecycle) - - [EMR](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#emr) - - [From source](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#from-source) +- [**What is AWS Data Wrangler?**](https://aws-data-wrangler.readthedocs.io/en/2.9.0/what.html) +- [**Install**](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html) + - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#pypi-pip) + - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#conda) + - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-lambda-layer) + - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-glue-python-shell-jobs) + - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-glue-pyspark-jobs) + - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#amazon-sagemaker-notebook) + - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#amazon-sagemaker-notebook-lifecycle) + - [EMR](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#emr) + - [From source](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#from-source) - [**Tutorials**](https://github.com/awslabs/aws-data-wrangler/tree/main/tutorials) - [001 - Introduction](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/001%20-%20Introduction.ipynb) - [002 - Sessions](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/002%20-%20Sessions.ipynb) @@ -136,22 +135,22 @@ FROM "sampleDB"."sampleTable" ORDER BY time DESC LIMIT 3 - [026 - Amazon Timestream](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/026%20-%20Amazon%20Timestream.ipynb) - [027 - Amazon Timestream 2](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/027%20-%20Amazon%20Timestream%202.ipynb) - [028 - Amazon DynamoDB](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/028%20-%20DynamoDB.ipynb) -- [**API Reference**](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html) - - [Amazon S3](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#amazon-s3) - - [AWS Glue Catalog](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#aws-glue-catalog) - - [Amazon Athena](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#amazon-athena) - - [Amazon Redshift](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#amazon-redshift) - - [PostgreSQL](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#postgresql) - - [MySQL](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#mysql) - - [SQL Server](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#sqlserver) - - [DynamoDB](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#dynamodb) - - [Amazon Timestream](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#amazon-timestream) - - [Amazon EMR](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#amazon-emr) - - [Amazon CloudWatch Logs](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#amazon-cloudwatch-logs) - - [Amazon Chime](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#amazon-chime) - - [Amazon QuickSight](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#amazon-quicksight) - - [AWS STS](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#aws-sts) - - [AWS Secrets Manager](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html#aws-secrets-manager) +- [**API Reference**](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html) + - [Amazon S3](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-s3) + - [AWS Glue Catalog](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#aws-glue-catalog) + - [Amazon Athena](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-athena) + - [Amazon Redshift](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-redshift) + - [PostgreSQL](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#postgresql) + - [MySQL](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#mysql) + - [SQL Server](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#sqlserver) + - [DynamoDB](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#dynamodb) + - [Amazon Timestream](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-timestream) + - [Amazon EMR](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-emr) + - [Amazon CloudWatch Logs](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-cloudwatch-logs) + - [Amazon Chime](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-chime) + - [Amazon QuickSight](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-quicksight) + - [AWS STS](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#aws-sts) + - [AWS Secrets Manager](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#aws-secrets-manager) - [**License**](https://github.com/awslabs/aws-data-wrangler/blob/main/LICENSE.txt) - [**Contributing**](https://github.com/awslabs/aws-data-wrangler/blob/main/CONTRIBUTING.md) - [**Legacy Docs** (pre-1.0.0)](https://aws-data-wrangler.readthedocs.io/en/0.3.3/) diff --git a/awswrangler/__metadata__.py b/awswrangler/__metadata__.py index f719472b0..a07e62c42 100644 --- a/awswrangler/__metadata__.py +++ b/awswrangler/__metadata__.py @@ -7,5 +7,5 @@ __title__: str = "awswrangler" __description__: str = "Pandas on AWS." -__version__: str = "2.8.0" +__version__: str = "2.9.0" __license__: str = "Apache License 2.0" diff --git a/awswrangler/_utils.py b/awswrangler/_utils.py index 47580903c..7af1f440d 100644 --- a/awswrangler/_utils.py +++ b/awswrangler/_utils.py @@ -229,7 +229,7 @@ def chunkify(lst: List[Any], num_chunks: int = 1, max_length: Optional[int] = No if not lst: return [] n: int = num_chunks if max_length is None else int(math.ceil((float(len(lst)) / float(max_length)))) - np_chunks = np.array_split(lst, n) + np_chunks = np.array_split(lst, n) # type: ignore return [arr.tolist() for arr in np_chunks if len(arr) > 0] diff --git a/awswrangler/athena/_read.py b/awswrangler/athena/_read.py index a22fdc931..795cb5a4b 100644 --- a/awswrangler/athena/_read.py +++ b/awswrangler/athena/_read.py @@ -6,7 +6,7 @@ import re import sys import uuid -from typing import Any, Dict, Iterator, List, Match, NamedTuple, Optional, Union +from typing import Any, Dict, Iterator, List, Match, NamedTuple, Optional, Tuple, Union import boto3 import botocore.exceptions @@ -385,6 +385,7 @@ def _resolve_query_without_cache_ctas( wg_config: _WorkGroupConfig, alt_database: Optional[str], name: Optional[str], + ctas_bucketing_info: Optional[Tuple[List[str], int]], use_threads: bool, s3_additional_kwargs: Optional[Dict[str, Any]], boto3_session: boto3.Session, @@ -392,11 +393,17 @@ def _resolve_query_without_cache_ctas( path: str = f"{s3_output}/{name}" ext_location: str = "\n" if wg_config.enforced is True else f",\n external_location = '{path}'\n" fully_qualified_name: str = f'"{alt_database}"."{name}"' if alt_database else f'"{database}"."{name}"' + bucketing_str = ( + (f",\n" f" bucketed_by = ARRAY{ctas_bucketing_info[0]},\n" f" bucket_count = {ctas_bucketing_info[1]}") + if ctas_bucketing_info + else "" + ) sql = ( f"CREATE TABLE {fully_qualified_name}\n" f"WITH(\n" f" format = 'Parquet',\n" f" parquet_compression = 'SNAPPY'" + f"{bucketing_str}" f"{ext_location}" f") AS\n" f"{sql}" @@ -521,6 +528,7 @@ def _resolve_query_without_cache( keep_files: bool, ctas_database_name: Optional[str], ctas_temp_table_name: Optional[str], + ctas_bucketing_info: Optional[Tuple[List[str], int]], use_threads: bool, s3_additional_kwargs: Optional[Dict[str, Any]], boto3_session: boto3.Session, @@ -553,12 +561,15 @@ def _resolve_query_without_cache( wg_config=wg_config, alt_database=ctas_database_name, name=name, + ctas_bucketing_info=ctas_bucketing_info, use_threads=use_threads, s3_additional_kwargs=s3_additional_kwargs, boto3_session=boto3_session, ) finally: - catalog.delete_table_if_exists(database=database, table=name, boto3_session=boto3_session) + catalog.delete_table_if_exists( + database=ctas_database_name or database, table=name, boto3_session=boto3_session + ) return _resolve_query_without_cache_regular( sql=sql, database=database, @@ -591,6 +602,7 @@ def read_sql_query( keep_files: bool = True, ctas_database_name: Optional[str] = None, ctas_temp_table_name: Optional[str] = None, + ctas_bucketing_info: Optional[Tuple[List[str], int]] = None, use_threads: bool = True, boto3_session: Optional[boto3.Session] = None, max_cache_seconds: int = 0, @@ -605,11 +617,11 @@ def read_sql_query( **Related tutorial:** - - `Amazon Athena `_ - - `Athena Cache `_ - - `Global Configurations `_ **There are two approaches to be defined through ctas_approach parameter:** @@ -657,7 +669,7 @@ def read_sql_query( /athena.html#Athena.Client.get_query_execution>`_ . For a practical example check out the - `related tutorial `_! @@ -731,6 +743,10 @@ def read_sql_query( The name of the temporary table and also the directory name on S3 where the CTAS result is stored. If None, it will use the follow random pattern: `f"temp_table_{uuid.uuid4().hex()}"`. On S3 this directory will be under under the pattern: `f"{s3_output}/{ctas_temp_table_name}/"`. + ctas_bucketing_info: Tuple[List[str], int], optional + Tuple consisting of the column names used for bucketing as the first element and the number of buckets as the + second element. + Only `str`, `int` and `bool` are supported as column data types for bucketing. use_threads : bool True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. @@ -839,6 +855,7 @@ def read_sql_query( keep_files=keep_files, ctas_database_name=ctas_database_name, ctas_temp_table_name=ctas_temp_table_name, + ctas_bucketing_info=ctas_bucketing_info, use_threads=use_threads, s3_additional_kwargs=s3_additional_kwargs, boto3_session=session, @@ -859,6 +876,7 @@ def read_sql_table( keep_files: bool = True, ctas_database_name: Optional[str] = None, ctas_temp_table_name: Optional[str] = None, + ctas_bucketing_info: Optional[Tuple[List[str], int]] = None, use_threads: bool = True, boto3_session: Optional[boto3.Session] = None, max_cache_seconds: int = 0, @@ -872,11 +890,11 @@ def read_sql_table( **Related tutorial:** - - `Amazon Athena `_ - - `Athena Cache `_ - - `Global Configurations `_ **There are two approaches to be defined through ctas_approach parameter:** @@ -921,7 +939,7 @@ def read_sql_table( /athena.html#Athena.Client.get_query_execution>`_ . For a practical example check out the - `related tutorial `_! @@ -993,6 +1011,10 @@ def read_sql_table( The name of the temporary table and also the directory name on S3 where the CTAS result is stored. If None, it will use the follow random pattern: `f"temp_table_{uuid.uuid4().hex}"`. On S3 this directory will be under under the pattern: `f"{s3_output}/{ctas_temp_table_name}/"`. + ctas_bucketing_info: Tuple[List[str], int], optional + Tuple consisting of the column names used for bucketing as the first element and the number of buckets as the + second element. + Only `str`, `int` and `bool` are supported as column data types for bucketing. use_threads : bool True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. @@ -1051,6 +1073,7 @@ def read_sql_table( keep_files=keep_files, ctas_database_name=ctas_database_name, ctas_temp_table_name=ctas_temp_table_name, + ctas_bucketing_info=ctas_bucketing_info, use_threads=use_threads, boto3_session=boto3_session, max_cache_seconds=max_cache_seconds, diff --git a/awswrangler/catalog/_get.py b/awswrangler/catalog/_get.py index 489886692..7e6007523 100644 --- a/awswrangler/catalog/_get.py +++ b/awswrangler/catalog/_get.py @@ -973,7 +973,7 @@ def get_columns_comments( Examples -------- >>> import awswrangler as wr - >>> pars = wr.catalog.get_table_parameters(database="...", table="...") + >>> pars = wr.catalog.get_columns_comments(database="...", table="...") """ client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) @@ -987,10 +987,10 @@ def get_columns_comments( ) comments: Dict[str, str] = {} for c in response["Table"]["StorageDescriptor"]["Columns"]: - comments[c["Name"]] = c["Comment"] + comments[c["Name"]] = c.get("Comment") if "PartitionKeys" in response["Table"]: for p in response["Table"]["PartitionKeys"]: - comments[p["Name"]] = p["Comment"] + comments[p["Name"]] = p.get("Comment") return comments diff --git a/awswrangler/mysql.py b/awswrangler/mysql.py index 941af8044..573fe95fa 100644 --- a/awswrangler/mysql.py +++ b/awswrangler/mysql.py @@ -37,7 +37,7 @@ def _drop_table(cursor: Cursor, schema: Optional[str], table: str) -> None: def _does_table_exist(cursor: Cursor, schema: Optional[str], table: str) -> bool: schema_str = f"TABLE_SCHEMA = '{schema}' AND" if schema else "" cursor.execute(f"SELECT * FROM INFORMATION_SCHEMA.TABLES WHERE " f"{schema_str} TABLE_NAME = '{table}'") - return len(cursor.fetchall()) > 0 # type: ignore + return len(cursor.fetchall()) > 0 def _create_table( @@ -141,7 +141,7 @@ def connect( password=attrs.password, port=attrs.port, host=attrs.host, - ssl=attrs.ssl_context, + ssl=attrs.ssl_context, # type: ignore read_timeout=read_timeout, write_timeout=write_timeout, connect_timeout=connect_timeout, diff --git a/awswrangler/redshift.py b/awswrangler/redshift.py index c7f009932..3ab21d19d 100644 --- a/awswrangler/redshift.py +++ b/awswrangler/redshift.py @@ -379,7 +379,16 @@ def connect( Note ---- - You MUST pass a `connection` OR `secret_id` + You MUST pass a `connection` OR `secret_id`. + Here is an example of the secret structure in Secrets Manager: + { + "host":"my-host.us-east-1.redshift.amazonaws.com", + "username":"test", + "password":"test", + "engine":"redshift", + "port":"5439", + "dbname": "mydb" + } https://github.com/aws/amazon-redshift-python-driver @@ -523,7 +532,7 @@ def connect_temp( Examples -------- >>> import awswrangler as wr - >>> con = wr.redshift.connect("MY_GLUE_CONNECTION") + >>> con = wr.redshift.connect_temp(cluster_identifier="my-cluster", user="test") >>> with con.cursor() as cursor: >>> cursor.execute("SELECT 1") >>> print(cursor.fetchall()) @@ -851,6 +860,7 @@ def unload_to_files( aws_secret_access_key: Optional[str] = None, aws_session_token: Optional[str] = None, region: Optional[str] = None, + unload_format: Optional[str] = None, max_file_size: Optional[float] = None, kms_key_id: Optional[str] = None, manifest: bool = False, @@ -890,6 +900,9 @@ def unload_to_files( same AWS Region as the Amazon Redshift cluster. By default, UNLOAD assumes that the target Amazon S3 bucket is located in the same AWS Region as the Amazon Redshift cluster. + unload_format: str, optional + Format of the unloaded S3 objects from the query. + Valid values: "CSV", "PARQUET". Case sensitive. Defaults to PARQUET. max_file_size : float, optional Specifies the maximum size (MB) of files that UNLOAD creates in Amazon S3. Specify a decimal value between 5.0 MB and 6200.0 MB. If None, the default @@ -925,9 +938,12 @@ def unload_to_files( """ + if unload_format not in [None, "CSV", "PARQUET"]: + raise exceptions.InvalidArgumentValue(" argument must be 'CSV' or 'PARQUET'") session: boto3.Session = _utils.ensure_session(session=boto3_session) s3.delete_objects(path=path, use_threads=use_threads, boto3_session=session) with con.cursor() as cursor: + format_str: str = unload_format or "PARQUET" partition_str: str = f"\nPARTITION BY ({','.join(partition_cols)})" if partition_cols else "" manifest_str: str = "\nmanifest" if manifest is True else "" region_str: str = f"\nREGION AS '{region}'" if region is not None else "" @@ -948,7 +964,7 @@ def unload_to_files( f"{auth_str}" "ALLOWOVERWRITE\n" "PARALLEL ON\n" - "FORMAT PARQUET\n" + f"FORMAT {format_str}\n" "ENCRYPTED" f"{kms_key_id_str}" f"{partition_str}" diff --git a/awswrangler/s3/_read_parquet.py b/awswrangler/s3/_read_parquet.py index f7fbfb24e..aaf803d0a 100644 --- a/awswrangler/s3/_read_parquet.py +++ b/awswrangler/s3/_read_parquet.py @@ -788,7 +788,7 @@ def read_parquet_table( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.8.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html columns : List[str], optional Names of columns to read from the file(s). validate_schema: diff --git a/awswrangler/s3/_read_text.py b/awswrangler/s3/_read_text.py index 9195a9265..7c2aec3e6 100644 --- a/awswrangler/s3/_read_text.py +++ b/awswrangler/s3/_read_text.py @@ -241,7 +241,7 @@ def read_csv( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.8.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html pandas_kwargs : KEYWORD arguments forwarded to pandas.read_csv(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. @@ -389,7 +389,7 @@ def read_fwf( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.8.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html pandas_kwargs: KEYWORD arguments forwarded to pandas.read_fwf(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. @@ -541,7 +541,7 @@ def read_json( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.8.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html pandas_kwargs: KEYWORD arguments forwarded to pandas.read_json(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. diff --git a/awswrangler/s3/_write.py b/awswrangler/s3/_write.py index 9af8d5956..9867c3312 100644 --- a/awswrangler/s3/_write.py +++ b/awswrangler/s3/_write.py @@ -99,3 +99,20 @@ def _sanitize( dtype = {catalog.sanitize_column_name(k): v.lower() for k, v in dtype.items()} _utils.check_duplicated_columns(df=df) return df, dtype, partition_cols + + +def _check_schema_changes(columns_types: Dict[str, str], table_input: Optional[Dict[str, Any]], mode: str) -> None: + if (table_input is not None) and (mode in ("append", "overwrite_partitions")): + catalog_cols: Dict[str, str] = {x["Name"]: x["Type"] for x in table_input["StorageDescriptor"]["Columns"]} + for c, t in columns_types.items(): + if c not in catalog_cols: + raise exceptions.InvalidArgumentValue( + f"Schema change detected: New column {c} with type {t}. " + "Please pass schema_evolution=True to allow new columns " + "behaviour." + ) + if t != catalog_cols[c]: # Data type change detected! + raise exceptions.InvalidArgumentValue( + f"Schema change detected: Data type change on column {c} " + f"(Old type: {catalog_cols[c]} / New type {t})." + ) diff --git a/awswrangler/s3/_write_parquet.py b/awswrangler/s3/_write_parquet.py index 1f2cd8331..962d30fae 100644 --- a/awswrangler/s3/_write_parquet.py +++ b/awswrangler/s3/_write_parquet.py @@ -17,30 +17,13 @@ from awswrangler.s3._delete import delete_objects from awswrangler.s3._fs import open_s3_object from awswrangler.s3._read_parquet import _read_parquet_metadata -from awswrangler.s3._write import _COMPRESSION_2_EXT, _apply_dtype, _sanitize, _validate_args +from awswrangler.s3._write import _COMPRESSION_2_EXT, _apply_dtype, _check_schema_changes, _sanitize, _validate_args from awswrangler.s3._write_concurrent import _WriteProxy from awswrangler.s3._write_dataset import _to_dataset _logger: logging.Logger = logging.getLogger(__name__) -def _check_schema_changes(columns_types: Dict[str, str], table_input: Optional[Dict[str, Any]], mode: str) -> None: - if (table_input is not None) and (mode in ("append", "overwrite_partitions")): - catalog_cols: Dict[str, str] = {x["Name"]: x["Type"] for x in table_input["StorageDescriptor"]["Columns"]} - for c, t in columns_types.items(): - if c not in catalog_cols: - raise exceptions.InvalidArgumentValue( - f"Schema change detected: New column {c} with type {t}. " - "Please pass schema_evolution=True to allow new columns " - "behaviour." - ) - if t != catalog_cols[c]: # Data type change detected! - raise exceptions.InvalidArgumentValue( - f"Schema change detected: Data type change on column {c} " - f"(Old type: {catalog_cols[c]} / New type {t})." - ) - - def _get_file_path(file_counter: int, file_path: str) -> str: slash_index: int = file_path.rfind("/") dot_index: int = file_path.find(".", slash_index) @@ -300,18 +283,18 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b concurrent_partitioning: bool If True will increase the parallelism level during the partitions writing. It will decrease the writing time and increase the memory usage. - https://aws-data-wrangler.readthedocs.io/en/2.8.0/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html + https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html mode: str, optional ``append`` (Default), ``overwrite``, ``overwrite_partitions``. Only takes effect if dataset=True. For details check the related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet + https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet catalog_versioning : bool If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. schema_evolution : bool If True allows schema evolution (new or missing columns), otherwise a exception will be raised. (Only considered if dataset=True and mode in ("append", "overwrite_partitions")) Related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.8.0/tutorials/014%20-%20Schema%20Evolution.html + https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/014%20-%20Schema%20Evolution.html database : str, optional Glue/Athena catalog: Database name. table : str, optional diff --git a/awswrangler/s3/_write_text.py b/awswrangler/s3/_write_text.py index 9ad4f3be1..1312c50d4 100644 --- a/awswrangler/s3/_write_text.py +++ b/awswrangler/s3/_write_text.py @@ -14,7 +14,7 @@ from awswrangler._config import apply_configs from awswrangler.s3._delete import delete_objects from awswrangler.s3._fs import open_s3_object -from awswrangler.s3._write import _COMPRESSION_2_EXT, _apply_dtype, _sanitize, _validate_args +from awswrangler.s3._write import _COMPRESSION_2_EXT, _apply_dtype, _check_schema_changes, _sanitize, _validate_args from awswrangler.s3._write_dataset import _to_dataset _logger: logging.Logger = logging.getLogger(__name__) @@ -87,6 +87,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state concurrent_partitioning: bool = False, mode: Optional[str] = None, catalog_versioning: bool = False, + schema_evolution: bool = False, database: Optional[str] = None, table: Optional[str] = None, table_type: Optional[str] = None, @@ -177,13 +178,18 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state concurrent_partitioning: bool If True will increase the parallelism level during the partitions writing. It will decrease the writing time and increase the memory usage. - https://aws-data-wrangler.readthedocs.io/en/2.8.0/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html + https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html mode : str, optional ``append`` (Default), ``overwrite``, ``overwrite_partitions``. Only takes effect if dataset=True. For details check the related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet + https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet catalog_versioning : bool If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. + schema_evolution : bool + If True allows schema evolution (new or missing columns), otherwise a exception will be raised. + (Only considered if dataset=True and mode in ("append", "overwrite_partitions")) + Related tutorial: + https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/014%20-%20Schema%20Evolution.html database : str, optional Glue/Athena catalog: Database name. table : str, optional @@ -448,10 +454,11 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state catalog_table_input = catalog._get_table_input( # pylint: disable=protected-access database=database, table=table, boto3_session=session, transaction_id=transaction_id, catalog_id=catalog_id ) + catalog_path: Optional[str] = None if catalog_table_input: table_type = catalog_table_input["TableType"] - catalog_path = catalog_table_input["StorageDescriptor"]["Location"] + catalog_path = catalog_table_input.get("StorageDescriptor", {}).get("Location") if path is None: if catalog_path: path = catalog_path @@ -494,7 +501,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state if database and table: quoting: Optional[int] = csv.QUOTE_NONE escapechar: Optional[str] = "\\" - header: Union[bool, List[str]] = False + header: Union[bool, List[str]] = pandas_kwargs.get("header", False) date_format: Optional[str] = "%Y-%m-%d %H:%M:%S.%f" pd_kwargs: Dict[str, Any] = {} compression: Optional[str] = pandas_kwargs.get("compression", None) @@ -512,12 +519,15 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state pd_kwargs.pop("compression", None) df = df[columns] if columns else df + columns_types: Dict[str, str] = {} partitions_types: Dict[str, str] = {} if database and table: columns_types, partitions_types = _data_types.athena_types_from_pandas_partitioned( df=df, index=index, partition_cols=partition_cols, dtype=dtype, index_left=True ) + if schema_evolution is False: + _check_schema_changes(columns_types=columns_types, table_input=catalog_table_input, mode=mode) if (catalog_table_input is None) and (table_type == "GOVERNED"): catalog._create_csv_table( # pylint: disable=protected-access database=database, @@ -555,6 +565,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state transaction_id=transaction_id, catalog_id=catalog_id, ) + paths, partitions_values = _to_dataset( func=_to_text, concurrent_partitioning=concurrent_partitioning, @@ -585,9 +596,6 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state ) if database and table: try: - columns_types, partitions_types = _data_types.athena_types_from_pandas_partitioned( - df=df, index=index, partition_cols=partition_cols, dtype=dtype, index_left=True - ) serde_info: Dict[str, Any] = {} if catalog_table_input: serde_info = catalog_table_input["StorageDescriptor"]["SerdeInfo"] @@ -618,7 +626,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state catalog_table_input=catalog_table_input, catalog_id=catalog_id, compression=pandas_kwargs.get("compression"), - skip_header_line_count=None, + skip_header_line_count=True if header else None, serde_library=serde_library, serde_parameters=serde_parameters, ) diff --git a/building/lambda/Dockerfile b/building/lambda/Dockerfile index 4ce0b4d47..83453eb0a 100644 --- a/building/lambda/Dockerfile +++ b/building/lambda/Dockerfile @@ -19,7 +19,7 @@ RUN pip3 install -r /root/requirements.txt ADD requirements-dev.txt /root/ # Removing "-e ." installation -RUN head -n -2 /root/requirements-dev.txt > /root/temp.txt +RUN head -n -3 /root/requirements-dev.txt > /root/temp.txt RUN mv /root/temp.txt /root/requirements-dev.txt RUN pip3 install -r /root/requirements-dev.txt diff --git a/docs/source/api.rst b/docs/source/api.rst index 75a118926..c9ce8b37b 100644 --- a/docs/source/api.rst +++ b/docs/source/api.rst @@ -42,6 +42,7 @@ Amazon S3 read_parquet read_parquet_metadata read_parquet_table + select_query size_objects store_parquet_metadata to_csv diff --git a/docs/source/install.rst b/docs/source/install.rst index 0d2b4338c..f5688df6d 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -62,7 +62,7 @@ Go to your Glue PySpark job and create a new *Job parameters* key/value: To install a specific version, set the value for above Job parameter as follows: -* Value: ``pyarrow==2,awswrangler==2.8.0`` +* Value: ``pyarrow==2,awswrangler==2.9.0`` .. note:: Pyarrow 3 is not currently supported in Glue PySpark Jobs, which is why a previous installation of pyarrow 2 is required. @@ -95,7 +95,7 @@ Here is an example of how to reference the Lambda layer in your CDK app: "wrangler-bucket", bucket_arn="arn:aws:s3:::aws-data-wrangler-public-artifacts", ), - key="releases/2.8.0/awswrangler-layer-2.8.0-py3.8.zip", + key="releases/2.9.0/awswrangler-layer-2.9.0-py3.8.zip", ), layer_version_name="aws-data-wrangler" ) @@ -190,7 +190,7 @@ complement Big Data pipelines. sudo pip install pyarrow==2 awswrangler .. note:: Make sure to freeze the Wrangler version in the bootstrap for productive - environments (e.g. awswrangler==2.8.0) + environments (e.g. awswrangler==2.9.0) .. note:: Pyarrow 3 is not currently supported in the default EMR image, which is why a previous installation of pyarrow 2 is required. diff --git a/docs/source/what.rst b/docs/source/what.rst index 05442207b..29aae1772 100644 --- a/docs/source/what.rst +++ b/docs/source/what.rst @@ -8,4 +8,4 @@ SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL Built on top of other open-source projects like `Pandas `_, `Apache Arrow `_ and `Boto3 `_, it offers abstracted functions to execute usual ETL tasks like load/unload data from **Data Lakes**, **Data Warehouses** and **Databases**. -Check our `tutorials `_ or the `list of functionalities `_. \ No newline at end of file +Check our `tutorials `_ or the `list of functionalities `_. \ No newline at end of file diff --git a/requirements-dev.txt b/requirements-dev.txt index 94703b42d..68a665704 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -1,7 +1,7 @@ wheel==0.36.2 isort==5.8.0 black==21.6b0 -pylint==2.8.3 +pylint==2.9.3 flake8==3.9.2 mypy==0.902 pydocstyle==6.1.1 @@ -9,20 +9,20 @@ doc8==0.8.1 tox==3.23.1 pytest==6.2.4 pytest-cov==2.12.1 -pytest-rerunfailures==10.0 -pytest-xdist==2.2.1 +pytest-rerunfailures==10.1 +pytest-xdist==2.3.0 pytest-timeout==1.4.2 pydot==1.4.2 -cfn-flip==1.2.3 twine==3.4.1 -sphinx==4.0.2 +sphinx==4.0.3 sphinx_bootstrap_theme==0.7.1 nbsphinx==0.8.6 nbsphinx-link==1.3.0 -IPython~=7.16 -moto==2.0.9 +IPython~=7.25 +moto==2.0.10 jupyterlab==3.0.16 -s3fs==0.4.2 # keep it at 0.4.2 +s3fs==2021.6.1 python-Levenshtein==0.12.2 bump2version==1.0.1 -e .[sqlserver] +-e .[excel-py3.6] \ No newline at end of file diff --git a/requirements.txt b/requirements.txt index ce5f5138f..be188ce39 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,9 +1,9 @@ boto3>=1.16.8,<2.0.0 botocore>=1.19.8,<2.0.0 -numpy>=1.18.0,<1.21.0 -pandas>=1.1.0,<1.3.0 +numpy>=1.18.0,<1.22.0 +pandas>=1.1.0,<1.4.0 pyarrow>=2.0.0,<4.1.0 -redshift-connector~=2.0.0 +redshift-connector~=2.0.882 pymysql>=0.9.0,<1.1.0 -pg8000>=1.16.0,<1.20.0 +pg8000>=1.16.0,<1.21.0 openpyxl~=3.0.0 diff --git a/setup.py b/setup.py index 50561e0e3..f3b24b569 100644 --- a/setup.py +++ b/setup.py @@ -32,5 +32,11 @@ "Programming Language :: Python :: 3.8", "Programming Language :: Python :: 3.9", ], - extras_require={"sqlserver": ["pyodbc~=4.0.30"]}, + extras_require={ + "sqlserver": ["pyodbc~=4.0.30"], + "excel-py3.6": [ + "xlrd>=2.0.1", + "xlwt>=1.3.0", + ], + }, ) diff --git a/tests/_utils.py b/tests/_utils.py index c931445c2..bc9dd3f75 100644 --- a/tests/_utils.py +++ b/tests/_utils.py @@ -426,7 +426,7 @@ def get_query_long(): """ -def ensure_data_types(df, has_list=False, governed=False): +def ensure_data_types(df, has_list=False): if "iint8" in df.columns: assert str(df["iint8"].dtype).startswith("Int") assert str(df["iint16"].dtype).startswith("Int") @@ -438,10 +438,7 @@ def ensure_data_types(df, has_list=False, governed=False): if "string_object" in df.columns: assert str(df["string_object"].dtype) == "string" assert str(df["string"].dtype) == "string" - if governed: - assert str(df["date"].dtype) == "datetime64[ns]" - else: - assert str(df["date"].dtype) == "object" + assert str(df["date"].dtype) == "object" assert str(df["timestamp"].dtype) == "datetime64[ns]" assert str(df["bool"].dtype) in ("boolean", "Int64", "object") if "binary" in df.columns: @@ -458,10 +455,7 @@ def ensure_data_types(df, has_list=False, governed=False): if not row.empty: row = row.iloc[0] assert str(type(row["decimal"]).__name__) == "Decimal" - if governed: - assert str(type(row["date"]).__name__) == "Timestamp" - else: - assert str(type(row["date"]).__name__) == "date" + assert str(type(row["date"]).__name__) == "date" if "binary" in df.columns: assert str(type(row["binary"]).__name__) == "bytes" if has_list is True: diff --git a/tests/test_athena.py b/tests/test_athena.py index f5988a388..7ddf8f913 100644 --- a/tests/test_athena.py +++ b/tests/test_athena.py @@ -112,7 +112,7 @@ def test_athena_ctas(path, path2, path3, glue_table, glue_table2, glue_database, ctas_temp_table_name=glue_table2, s3_output=path3, ) - assert wr.catalog.does_table_exist(database=glue_ctas_database, table=glue_table2) is True + assert wr.catalog.does_table_exist(database=glue_ctas_database, table=glue_table2) is False assert len(wr.s3.list_objects(path=path3)) > 2 assert len(wr.s3.list_objects(path=final_destination)) > 0 for df in dfs: @@ -121,6 +121,33 @@ def test_athena_ctas(path, path2, path3, glue_table, glue_table2, glue_database, assert len(wr.s3.list_objects(path=path3)) == 0 +def test_athena_read_sql_ctas_bucketing(path, path2, glue_table, glue_table2, glue_database, glue_ctas_database): + df = pd.DataFrame({"c0": [0, 1], "c1": ["foo", "bar"]}) + wr.s3.to_parquet( + df=df, + path=path, + dataset=True, + database=glue_database, + table=glue_table, + ) + df_ctas = wr.athena.read_sql_query( + sql=f"SELECT * FROM {glue_table}", + ctas_approach=True, + database=glue_database, + ctas_database_name=glue_ctas_database, + ctas_temp_table_name=glue_table2, + ctas_bucketing_info=(["c0"], 1), + s3_output=path2, + ) + df_no_ctas = wr.athena.read_sql_query( + sql=f"SELECT * FROM {glue_table}", + ctas_approach=False, + database=glue_database, + s3_output=path2, + ) + assert df_ctas.equals(df_no_ctas) + + def test_athena(path, glue_database, glue_table, kms_key, workgroup0, workgroup1): wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table) wr.s3.to_parquet( @@ -255,6 +282,7 @@ def test_athena_ctas_empty(glue_database): assert len(list(wr.athena.read_sql_query(sql=sql, database=glue_database, chunksize=1))) == 1 +@pytest.mark.xfail() def test_athena_struct(glue_database): sql = "SELECT CAST(ROW(1, 'foo') AS ROW(id BIGINT, value VARCHAR)) AS col0" with pytest.raises(wr.exceptions.UnsupportedType): @@ -469,6 +497,7 @@ def test_read_sql_query_wo_results(path, glue_database, glue_table): ensure_athena_query_metadata(df=df, ctas_approach=False, encrypted=False) +@pytest.mark.xfail() def test_read_sql_query_wo_results_ctas(path, glue_database, glue_table): wr.catalog.create_parquet_table(database=glue_database, table=glue_table, path=path, columns_types={"c0": "int"}) sql = f"ALTER TABLE {glue_database}.{glue_table} SET LOCATION '{path}dir/'" diff --git a/tests/test_lakeformation.py b/tests/test_lakeformation.py index 447b0225f..77483dfb0 100644 --- a/tests/test_lakeformation.py +++ b/tests/test_lakeformation.py @@ -37,7 +37,7 @@ def test_lakeformation(path, path2, glue_database, glue_table, glue_table2, use_ assert len(df.index) == 3 assert len(df.columns) == 14 assert df["iint32"].sum() == 3 - ensure_data_types(df=df, governed=True) + ensure_data_types(df=df) # Filter query df2 = wr.lakeformation.read_sql_query( @@ -69,7 +69,7 @@ def test_lakeformation(path, path2, glue_database, glue_table, glue_table2, use_ use_threads=use_threads, ) assert df3["int"].sum() == 3 - ensure_data_types_csv(df3, governed=True) + ensure_data_types_csv(df3) # Read within a query as of time query_as_of_time = calendar.timegm(time.gmtime()) diff --git a/tests/test_metadata.py b/tests/test_metadata.py index 332bf7ea0..a4fc97a92 100644 --- a/tests/test_metadata.py +++ b/tests/test_metadata.py @@ -2,7 +2,7 @@ def test_metadata(): - assert wr.__version__ == "2.8.0" + assert wr.__version__ == "2.9.0" assert wr.__title__ == "awswrangler" assert wr.__description__ == "Pandas on AWS." assert wr.__license__ == "Apache License 2.0" diff --git a/tests/test_redshift.py b/tests/test_redshift.py index 14221e0f4..ef45e53d6 100644 --- a/tests/test_redshift.py +++ b/tests/test_redshift.py @@ -352,7 +352,10 @@ def test_unload_extras(bucket, path, redshift_table, redshift_con, databases_par assert len(df.columns) == 2 -def test_unload_with_prefix(bucket, path, redshift_table, redshift_con, databases_parameters, kms_key_id): +@pytest.mark.parametrize("unload_format", [None, "CSV", "PARQUET"]) +def test_unload_with_prefix( + bucket, path, redshift_table, redshift_con, databases_parameters, kms_key_id, unload_format +): test_prefix = "my_prefix" table = redshift_table schema = databases_parameters["redshift"]["schema"] @@ -367,6 +370,7 @@ def test_unload_with_prefix(bucket, path, redshift_table, redshift_con, database "region": wr.s3.get_bucket_region(bucket), "max_file_size": 5.0, "kms_key_id": kms_key_id, + "unload_format": unload_format, } # Adding a prefix to S3 output files wr.redshift.unload_to_files(**args) diff --git a/tests/test_s3_excel.py b/tests/test_s3_excel.py index 71995f17e..0a5760e25 100644 --- a/tests/test_s3_excel.py +++ b/tests/test_s3_excel.py @@ -1,4 +1,5 @@ import logging +import sys import pandas as pd import pytest @@ -12,19 +13,26 @@ @pytest.mark.parametrize("use_threads", [True, False, 2]) def test_excel(path, ext, use_threads): df = pd.DataFrame({"c0": [1, 2, 3], "c1": ["foo", "boo", "bar"]}) - file_path = f"{path}0.{ext}" - wr.s3.to_excel(df, file_path, use_threads=use_threads, index=False) - df2 = wr.s3.read_excel(file_path, use_threads=use_threads) + pandas_kwargs = {} + if sys.version_info < (3, 7): + pandas_kwargs["engine"] = "xlwt" if ext == "xls" else "openpyxl" + wr.s3.to_excel(df, file_path, use_threads=use_threads, index=False, **pandas_kwargs) + if sys.version_info < (3, 7): + pandas_kwargs["engine"] = "xlrd" if ext == "xls" else "openpyxl" + df2 = wr.s3.read_excel(file_path, use_threads=use_threads, **pandas_kwargs) assert df.equals(df2) def test_read_xlsx_versioned(path) -> None: path_file = f"{path}0.xlsx" dfs = [pd.DataFrame({"c0": [0, 1, 2], "c1": [3, 4, 5]}), pd.DataFrame({"c0": [3, 4, 5], "c1": [6, 7, 8]})] + pandas_kwargs = {} + if sys.version_info < (3, 7): + pandas_kwargs["engine"] = "openpyxl" for df in dfs: - wr.s3.to_excel(df=df, path=path_file, index=False) + wr.s3.to_excel(df=df, path=path_file, index=False, **pandas_kwargs) version_id = wr.s3.describe_objects(path=path_file)[path_file]["VersionId"] - df_temp = wr.s3.read_excel(path_file, version_id=version_id) + df_temp = wr.s3.read_excel(path_file, version_id=version_id, **pandas_kwargs) assert df_temp.equals(df) assert version_id == wr.s3.describe_objects(path=path_file, version_id=version_id)[path_file]["VersionId"] diff --git a/tests/test_s3_select.py b/tests/test_s3_select.py index 46218182c..07aefba3f 100644 --- a/tests/test_s3_select.py +++ b/tests/test_s3_select.py @@ -1,4 +1,5 @@ import logging +import sys import pandas as pd import pytest @@ -102,6 +103,10 @@ def test_push_down(path, use_threads): assert df4._1.sum() == 3 +@pytest.mark.skipif( + sys.version_info < (3, 7), + reason="CSV compression on S3 is supported only starting from Pandas 1.2.0 that requires Python >=3.7.1", +) @pytest.mark.parametrize("compression", ["gzip", "bz2"]) def test_compression(path, compression): df = pd.DataFrame({"c0": [1, 2, 3], "c1": ["foo", "boo", "bar"], "c2": [4.0, 5.0, 6.0]}) diff --git a/tests/test_s3_text.py b/tests/test_s3_text.py index 185d48d0d..18dcc7ad2 100644 --- a/tests/test_s3_text.py +++ b/tests/test_s3_text.py @@ -119,6 +119,52 @@ def test_csv(path): wr.s3.read_csv(path=paths, iterator=True) +@pytest.mark.parametrize("header", [True, ["identifier"]]) +def test_csv_dataset_header(path, header, glue_database, glue_table): + path0 = f"{path}test_csv_dataset0.csv" + df0 = pd.DataFrame({"id": [1, 2, 3]}) + wr.s3.to_csv( + df=df0, + path=path0, + dataset=True, + database=glue_database, + table=glue_table, + index=False, + header=header, + ) + df1 = wr.s3.read_csv(path=path0) + if isinstance(header, list): + df0.columns = header + assert df0.equals(df1) + + +@pytest.mark.parametrize("mode", ["append", "overwrite"]) +def test_csv_dataset_header_modes(path, mode, glue_database, glue_table): + path0 = f"{path}test_csv_dataset0.csv" + dfs = [ + pd.DataFrame({"id": [1, 2, 3]}), + pd.DataFrame({"id": [4, 5, 6]}), + ] + for df in dfs: + wr.s3.to_csv( + df=df, + path=path0, + dataset=True, + database=glue_database, + table=glue_table, + mode=mode, + index=False, + header=True, + ) + dfs_conc = pd.concat(dfs) + df_res = wr.s3.read_csv(path=path0) + + if mode == "append": + assert len(df_res) == len(dfs_conc) + else: + assert df_res.equals(dfs[-1]) + + def test_json(path): df0 = pd.DataFrame({"id": [1, 2, 3]}) path0 = f"{path}test_json0.json" @@ -285,3 +331,14 @@ def test_read_csv_versioned(path) -> None: df_temp = wr.s3.read_csv(path_file, version_id=version_id) assert df_temp.equals(df) assert version_id == wr.s3.describe_objects(path=path_file, version_id=version_id)[path_file]["VersionId"] + + +def test_to_csv_schema_evolution(path, glue_database, glue_table) -> None: + path_file = f"{path}0.csv" + df = pd.DataFrame({"c0": [0, 1, 2], "c1": [3, 4, 5]}) + wr.s3.to_csv(df=df, path=path_file, dataset=True, database=glue_database, table=glue_table) + df["test"] = 1 + with pytest.raises(wr.exceptions.InvalidArgumentValue): + wr.s3.to_csv( + df=df, path=path_file, dataset=True, database=glue_database, table=glue_table, schema_evolution=True + ) diff --git a/tox.ini b/tox.ini index 11e72e732..649cd60e4 100644 --- a/tox.ini +++ b/tox.ini @@ -5,6 +5,7 @@ envlist = py{36,37,38,39} passenv = AWS_PROFILE AWS_DEFAULT_REGION AWS_ACCESS_KEY_ID AWS_SECRET_ACCESS_KEY AWS_SESSION_TOKEN deps = .[sqlserver] + .[excel-py3.6] pytest==6.2.2 pytest-rerunfailures==9.1.1 pytest-xdist==2.2.1 diff --git a/tutorials/001 - Introduction.ipynb b/tutorials/001 - Introduction.ipynb index 326be730e..8527b1e19 100644 --- a/tutorials/001 - Introduction.ipynb +++ b/tutorials/001 - Introduction.ipynb @@ -19,7 +19,7 @@ "\n", "Built on top of other open-source projects like [Pandas](https://github.com/pandas-dev/pandas), [Apache Arrow](https://github.com/apache/arrow) and [Boto3](https://github.com/boto/boto3), it offers abstracted functions to execute usual ETL tasks like load/unload data from **Data Lakes**, **Data Warehouses** and **Databases**.\n", "\n", - "Check our [list of functionalities](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html)." + "Check our [list of functionalities](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html)." ] }, { @@ -30,15 +30,15 @@ "\n", "The Wrangler runs almost anywhere over Python 3.6, 3.7, 3.8 and 3.9, so there are several different ways to install it in the desired enviroment.\n", "\n", - " - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#pypi-pip)\n", - " - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#conda)\n", - " - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#aws-lambda-layer)\n", - " - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#aws-glue-python-shell-jobs)\n", - " - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#aws-glue-pyspark-jobs)\n", - " - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#amazon-sagemaker-notebook)\n", - " - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#amazon-sagemaker-notebook-lifecycle)\n", - " - [EMR Cluster](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#emr-cluster)\n", - " - [From source](https://aws-data-wrangler.readthedocs.io/en/2.8.0/install.html#from-source)\n", + " - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#pypi-pip)\n", + " - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#conda)\n", + " - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-lambda-layer)\n", + " - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-glue-python-shell-jobs)\n", + " - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-glue-pyspark-jobs)\n", + " - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#amazon-sagemaker-notebook)\n", + " - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#amazon-sagemaker-notebook-lifecycle)\n", + " - [EMR Cluster](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#emr-cluster)\n", + " - [From source](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#from-source)\n", "\n", "Some good practices for most of the above methods are:\n", " - Use new and individual Virtual Environments for each project ([venv](https://docs.python.org/3/library/venv.html))\n", diff --git a/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb b/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb index f6d37f4d6..aebf6a9ae 100644 --- a/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb +++ b/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb @@ -10,14 +10,14 @@ "\n", "[Wrangler](https://github.com/awslabs/aws-data-wrangler)'s Redshift, MySQL and PostgreSQL have two basic function in common that tries to follow the Pandas conventions, but add more data type consistency.\n", "\n", - "- [wr.redshift.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.redshift.to_sql.html)\n", - "- [wr.redshift.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.redshift.read_sql_query.html)\n", - "- [wr.mysql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.mysql.to_sql.html)\n", - "- [wr.mysql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.mysql.read_sql_query.html)\n", - "- [wr.postgresql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.postgresql.to_sql.html)\n", - "- [wr.postgresql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.postgresql.read_sql_query.html)\n", - "- [wr.sqlserver.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.sqlserver.to_sql.html)\n", - "- [wr.sqlserver.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.sqlserver.read_sql_query.html)" + "- [wr.redshift.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.redshift.to_sql.html)\n", + "- [wr.redshift.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.redshift.read_sql_query.html)\n", + "- [wr.mysql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.mysql.to_sql.html)\n", + "- [wr.mysql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.mysql.read_sql_query.html)\n", + "- [wr.postgresql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.postgresql.to_sql.html)\n", + "- [wr.postgresql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.postgresql.read_sql_query.html)\n", + "- [wr.sqlserver.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.sqlserver.to_sql.html)\n", + "- [wr.sqlserver.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.sqlserver.read_sql_query.html)" ] }, { @@ -41,10 +41,10 @@ "source": [ "## Connect using the Glue Catalog Connections\n", "\n", - "- [wr.redshift.connect()](https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.redshift.connect.html)\n", - "- [wr.mysql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.mysql.connect.html)\n", - "- [wr.postgresql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.postgresql.connect.html)\n", - "- [wr.sqlserver.connect()](https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.sqlserver.connect.html)" + "- [wr.redshift.connect()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.redshift.connect.html)\n", + "- [wr.mysql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.mysql.connect.html)\n", + "- [wr.postgresql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.postgresql.connect.html)\n", + "- [wr.sqlserver.connect()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.sqlserver.connect.html)" ] }, { diff --git a/tutorials/014 - Schema Evolution.ipynb b/tutorials/014 - Schema Evolution.ipynb index d339338f5..9fb6b93a0 100644 --- a/tutorials/014 - Schema Evolution.ipynb +++ b/tutorials/014 - Schema Evolution.ipynb @@ -10,8 +10,8 @@ "\n", "Wrangler support new **columns** on Parquet Dataset through:\n", "\n", - "- [wr.s3.to_parquet()](https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet)\n", - "- [wr.s3.store_parquet_metadata()](https://aws-data-wrangler.readthedocs.io/en/2.8.0/stubs/awswrangler.s3.store_parquet_metadata.html#awswrangler.s3.store_parquet_metadata) i.e. \"Crawler\"" + "- [wr.s3.to_parquet()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet)\n", + "- [wr.s3.store_parquet_metadata()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.s3.store_parquet_metadata.html#awswrangler.s3.store_parquet_metadata) i.e. \"Crawler\"" ] }, { diff --git a/tutorials/021 - Global Configurations.ipynb b/tutorials/021 - Global Configurations.ipynb index d96b998f8..9b7b08314 100644 --- a/tutorials/021 - Global Configurations.ipynb +++ b/tutorials/021 - Global Configurations.ipynb @@ -13,7 +13,7 @@ "- **Environment variables**\n", "- **wr.config**\n", "\n", - "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html) to see if your function has some argument that can be configured through Global configurations.*\n", + "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html) to see if your function has some argument that can be configured through Global configurations.*\n", "\n", "*P.P.S. One exception to the above mentioned rules is the `botocore_config` property. It cannot be set through environment variables\n", "but only via `wr.config`. It will be used as the `botocore.config.Config` for all underlying `boto3` calls.\n", diff --git a/tutorials/022 - Writing Partitions Concurrently.ipynb b/tutorials/022 - Writing Partitions Concurrently.ipynb index 58ddf5fcf..620d734b6 100644 --- a/tutorials/022 - Writing Partitions Concurrently.ipynb +++ b/tutorials/022 - Writing Partitions Concurrently.ipynb @@ -13,7 +13,7 @@ " If True will increase the parallelism level during the partitions writing. It will decrease the\n", " writing time and increase the memory usage.\n", "\n", - "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html) to see it has some argument that can be configured through Global configurations.*" + "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html) to see it has some argument that can be configured through Global configurations.*" ] }, { diff --git a/tutorials/023 - Flexible Partitions Filter.ipynb b/tutorials/023 - Flexible Partitions Filter.ipynb index 4b190b787..22f5c4354 100644 --- a/tutorials/023 - Flexible Partitions Filter.ipynb +++ b/tutorials/023 - Flexible Partitions Filter.ipynb @@ -16,7 +16,7 @@ " - Ignored if `dataset=False`.\n", " \n", "\n", - "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.8.0/api.html) to see it has some argument that can be configured through Global configurations.*" + "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html) to see it has some argument that can be configured through Global configurations.*" ] }, { diff --git a/tutorials/029 - Lake Formation Governed Tables.ipynb b/tutorials/030 - Lake Formation Governed Tables.ipynb similarity index 97% rename from tutorials/029 - Lake Formation Governed Tables.ipynb rename to tutorials/030 - Lake Formation Governed Tables.ipynb index db02a845d..3cb56f80d 100644 --- a/tutorials/029 - Lake Formation Governed Tables.ipynb +++ b/tutorials/030 - Lake Formation Governed Tables.ipynb @@ -27,27 +27,28 @@ "nbformat_minor": 2, "cells": [ { + "cell_type": "markdown", "source": [ "[![AWS Data Wrangler](_static/logo.png \"AWS Data Wrangler\")](https://github.com/awslabs/aws-data-wrangler)" ], - "cell_type": "markdown", "metadata": {} }, { + "cell_type": "markdown", "source": [ - "# AWS Lake Formation - Glue Governed tables" + "# 30 - AWS Lake Formation - Glue Governed tables" ], - "cell_type": "markdown", "metadata": {} }, { + "cell_type": "markdown", "source": [ "### This tutorial assumes that your IAM user/role has the required Lake Formation permissions to create and read AWS Glue Governed tables" ], - "cell_type": "markdown", "metadata": {} }, { + "cell_type": "markdown", "source": [ "## Table of Contents\n", "* [1. Read Governed table](#1.-Read-Governed-table)\n", @@ -66,28 +67,25 @@ " * [2.2.4 Overwrite partitions](#2.2.4-Overwrite-partitions)\n", "* [3. Multiple read/write operations within a transaction](#2.-Multiple-read/write-operations-within-a-transaction)" ], - "cell_type": "markdown", "metadata": {} }, { + "cell_type": "markdown", "source": [ "# 1. Read Governed table" ], - "cell_type": "markdown", "metadata": {} }, { + "cell_type": "markdown", "source": [ "## 1.1 Read PartiQL query" ], - "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "import awswrangler as wr\n", "\n", @@ -101,20 +99,20 @@ " database=database,\n", " catalog_id=catalog_id\n", ")" - ] + ], + "outputs": [], + "metadata": {} }, { + "cell_type": "markdown", "source": [ "### 1.1.1 Read within transaction" ], - "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "transaction_id = wr.lakeformation.start_transaction(read_only=True)\n", "df = wr.lakeformation.read_sql_query(\n", @@ -122,20 +120,20 @@ " database=database,\n", " transaction_id=transaction_id\n", ")" - ] + ], + "outputs": [], + "metadata": {} }, { + "cell_type": "markdown", "source": [ "### 1.1.2 Read within query as of time" ], - "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "import calendar\n", "import time\n", @@ -147,78 +145,78 @@ " query_as_of_time=query_as_of_time,\n", " params={\"id\": 1, \"name\": \"Ayoub\"}\n", ")" - ] + ], + "outputs": [], + "metadata": {} }, { + "cell_type": "markdown", "source": [ "## 1.2 Read full table" ], - "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "df = wr.lakeformation.read_sql_table(\n", " table=table,\n", " database=database\n", ")" - ] + ], + "outputs": [], + "metadata": {} }, { + "cell_type": "markdown", "source": [ "# 2. Write Governed table" ], - "cell_type": "markdown", "metadata": {} }, { + "cell_type": "markdown", "source": [ "## 2.1 Create a new Governed table" ], - "cell_type": "markdown", "metadata": {} }, { + "cell_type": "markdown", "source": [ "## Enter your bucket name:" ], - "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "import getpass\n", "\n", "bucket = getpass.getpass()" - ] + ], + "outputs": [], + "metadata": {} }, { + "cell_type": "markdown", "source": [ "### If a governed table does not exist, it can be created by passing an S3 `path` argument. Make sure your IAM user/role has enough permissions in the Lake Formation database" ], - "cell_type": "markdown", "metadata": {} }, { + "cell_type": "markdown", "source": [ "### 2.1.1 CSV table" ], - "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "import pandas as pd\n", "\n", @@ -239,20 +237,20 @@ " table=table,\n", " table_type=\"GOVERNED\"\n", ")" - ] + ], + "outputs": [], + "metadata": {} }, { + "cell_type": "markdown", "source": [ "### 2.1.2 Parquet table" ], - "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "table = \"gov_table_parquet\"\n", "\n", @@ -268,27 +266,27 @@ " parameters={\"num_cols\": str(len(df.columns)), \"num_rows\": str(len(df.index))},\n", " columns_comments={\"c0\": \"0\"}\n", ")" - ] + ], + "outputs": [], + "metadata": {} }, { + "cell_type": "markdown", "source": [ "## 2.2 Overwrite operations" ], - "cell_type": "markdown", "metadata": {} }, { + "cell_type": "markdown", "source": [ "### 2.2.1 Overwrite" ], - "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "df = pd.DataFrame({\"c1\": [None, 1, None]}, dtype=\"Int16\")\n", "wr.s3.to_parquet(\n", @@ -301,20 +299,20 @@ " parameters={\"num_cols\": str(len(df.columns)), \"num_rows\": str(len(df.index))},\n", " columns_comments={\"c1\": \"1\"}\n", ")" - ] + ], + "outputs": [], + "metadata": {} }, { + "cell_type": "markdown", "source": [ "### 2.2.2 Append" ], - "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "df = pd.DataFrame({\"c1\": [None, 2, None]}, dtype=\"Int8\")\n", "wr.s3.to_parquet(\n", @@ -327,20 +325,20 @@ " parameters={\"num_cols\": str(len(df.columns)), \"num_rows\": str(len(df.index) * 2)},\n", " columns_comments={\"c1\": \"1\"}\n", ")" - ] + ], + "outputs": [], + "metadata": {} }, { + "cell_type": "markdown", "source": [ "### 2.2.3 Create partitioned Governed table" ], - "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "table = \"gov_table_parquet_partitioned\"\n", "\n", @@ -357,20 +355,20 @@ " parameters={\"num_cols\": \"2\", \"num_rows\": \"2\"},\n", " columns_comments={\"c0\": \"zero\", \"c1\": \"one\"}\n", ")" - ] + ], + "outputs": [], + "metadata": {} }, { + "cell_type": "markdown", "source": [ "### 2.2.4 Overwrite partitions" ], - "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "df = pd.DataFrame({\"c0\": [None, None], \"c1\": [0, 2]})\n", "wr.s3.to_parquet(\n", @@ -384,20 +382,20 @@ " parameters={\"num_cols\": \"2\", \"num_rows\": \"3\"},\n", " columns_comments={\"c0\": \"zero\", \"c1\": \"one\"}\n", ")" - ] + ], + "outputs": [], + "metadata": {} }, { + "cell_type": "markdown", "source": [ "# 3. Multiple read/write operations within a transaction" ], - "cell_type": "markdown", "metadata": {} }, { "cell_type": "code", "execution_count": null, - "metadata": {}, - "outputs": [], "source": [ "read_table = \"gov_table_parquet\"\n", "write_table = \"gov_table_multi_parquet\"\n", @@ -435,7 +433,9 @@ ")\n", "\n", "wr.lakeformation.commit_transaction(transaction_id=transaction_id)" - ] + ], + "outputs": [], + "metadata": {} } ] } \ No newline at end of file From df4eef2dbceeab9886d501e5c2f0d281fa5439de Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Thu, 5 Aug 2021 12:06:22 +0100 Subject: [PATCH 17/36] Merge main --- .bumpversion.cfg | 2 +- .github/dependabot.yml | 1 - .github/workflows/static-checking.yml | 2 +- .readthedocs.yml | 1 + CONTRIBUTING_COMMON_ERRORS.md | 6 +- README.md | 71 ++++--- awswrangler/__init__.py | 2 + awswrangler/__metadata__.py | 2 +- awswrangler/_databases.py | 6 + awswrangler/athena/_read.py | 22 +- awswrangler/athena/_utils.py | 7 +- awswrangler/data_api/__init__.py | 7 + awswrangler/data_api/connector.py | 71 +++++++ awswrangler/data_api/rds.py | 149 +++++++++++++ awswrangler/data_api/redshift.py | 199 ++++++++++++++++++ awswrangler/mysql.py | 21 +- awswrangler/postgresql.py | 23 +- awswrangler/redshift.py | 8 +- awswrangler/s3/_copy.py | 8 +- awswrangler/s3/_delete.py | 2 +- awswrangler/s3/_describe.py | 4 +- awswrangler/s3/_fs.py | 88 ++------ awswrangler/s3/_list.py | 8 +- awswrangler/s3/_read_parquet.py | 2 +- awswrangler/s3/_read_text.py | 6 +- awswrangler/s3/_write_excel.py | 4 +- awswrangler/s3/_write_parquet.py | 14 +- awswrangler/s3/_write_text.py | 14 +- awswrangler/timestream.py | 15 +- building/lambda/build-lambda-layer.sh | 2 +- docs/environment.yml | 2 +- docs/source/api.rst | 42 ++++ docs/source/install.rst | 6 +- docs/source/what.rst | 2 +- requirements-dev.txt | 22 +- requirements.txt | 10 +- test_infra/stacks/databases_stack.py | 60 +++++- tests/conftest.py | 7 +- tests/test_data_api.py | 129 ++++++++++++ tests/test_metadata.py | 2 +- tests/test_moto.py | 72 +++++++ tests/test_postgresql.py | 152 +++++++++++++ tests/test_timestream.py | 60 +++++- tutorials/001 - Introduction.ipynb | 20 +- ...shift, MySQL, PostgreSQL, SQL Server.ipynb | 24 +-- tutorials/014 - Schema Evolution.ipynb | 4 +- tutorials/021 - Global Configurations.ipynb | 2 +- ...22 - Writing Partitions Concurrently.ipynb | 2 +- .../023 - Flexible Partitions Filter.ipynb | 2 +- validate.sh | 2 +- 50 files changed, 1150 insertions(+), 239 deletions(-) create mode 100644 awswrangler/data_api/__init__.py create mode 100644 awswrangler/data_api/connector.py create mode 100644 awswrangler/data_api/rds.py create mode 100644 awswrangler/data_api/redshift.py create mode 100644 tests/test_data_api.py diff --git a/.bumpversion.cfg b/.bumpversion.cfg index 6aab500ec..438818fe7 100644 --- a/.bumpversion.cfg +++ b/.bumpversion.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 2.9.0 +current_version = 2.10.0 commit = False tag = False tag_name = {new_version} diff --git a/.github/dependabot.yml b/.github/dependabot.yml index 00b93acfa..2d6f43016 100644 --- a/.github/dependabot.yml +++ b/.github/dependabot.yml @@ -10,4 +10,3 @@ updates: prefix: "[skip ci] pip" prefix-development: "[skip ci] pip" include: "scope" - open-pull-requests-limit: 5 diff --git a/.github/workflows/static-checking.yml b/.github/workflows/static-checking.yml index 2e2c534f3..122726553 100644 --- a/.github/workflows/static-checking.yml +++ b/.github/workflows/static-checking.yml @@ -28,7 +28,7 @@ jobs: python -m pip install --upgrade pip pip install -U -r requirements-dev.txt - name: mypy check - run: yes y | mypy --install-types awswrangler + run: mypy --install-types --non-interactive awswrangler - name: Flake8 Lint run: flake8 . - name: Pylint Lint diff --git a/.readthedocs.yml b/.readthedocs.yml index 7030530af..91421b20f 100644 --- a/.readthedocs.yml +++ b/.readthedocs.yml @@ -1,4 +1,5 @@ version: 2 formats: all + conda: environment: docs/environment.yml diff --git a/CONTRIBUTING_COMMON_ERRORS.md b/CONTRIBUTING_COMMON_ERRORS.md index 42bbf635e..92f8aa94d 100644 --- a/CONTRIBUTING_COMMON_ERRORS.md +++ b/CONTRIBUTING_COMMON_ERRORS.md @@ -13,9 +13,9 @@ Requirement already satisfied: pbr!=2.1.0,>=2.0.0 in ./.venv/lib/python3.7/site- Using legacy 'setup.py install' for python-Levenshtein, since package 'wheel' is not installed. Installing collected packages: awswrangler, python-Levenshtein Attempting uninstall: awswrangler - Found existing installation: awswrangler 2.9.0 - Uninstalling awswrangler-2.9.0: - Successfully uninstalled awswrangler-2.9.0 + Found existing installation: awswrangler 2.10.0 + Uninstalling awswrangler-2.10.0: + Successfully uninstalled awswrangler-2.10.0 Running setup.py develop for awswrangler Running setup.py install for python-Levenshtein ... error ERROR: Command errored out with exit status 1: diff --git a/README.md b/README.md index 8c609bbe2..22f86e0a0 100644 --- a/README.md +++ b/README.md @@ -8,7 +8,7 @@ Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, Clo > An [AWS Professional Service](https://aws.amazon.com/professional-services/) open source initiative | aws-proserve-opensource@amazon.com -[![Release](https://img.shields.io/badge/release-2.9.0-brightgreen.svg)](https://pypi.org/project/awswrangler/) +[![Release](https://img.shields.io/badge/release-2.10.0-brightgreen.svg)](https://pypi.org/project/awswrangler/) [![Python Version](https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8%20%7C%203.9-brightgreen.svg)](https://anaconda.org/conda-forge/awswrangler) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) @@ -23,7 +23,7 @@ Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, Clo | **[PyPi](https://pypi.org/project/awswrangler/)** | [![PyPI Downloads](https://pepy.tech/badge/awswrangler)](https://pypi.org/project/awswrangler/) | `pip install awswrangler` | | **[Conda](https://anaconda.org/conda-forge/awswrangler)** | [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/awswrangler.svg)](https://anaconda.org/conda-forge/awswrangler) | `conda install -c conda-forge awswrangler` | -> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-glue-pyspark-jobs), MWAA):**
+> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-glue-pyspark-jobs), MWAA):**
➡️ `pip install pyarrow==2 awswrangler` Powered By [](https://arrow.apache.org/powered_by/) @@ -32,16 +32,17 @@ Powered By [](http - [Quick Start](#quick-start) - [Read The Docs](#read-the-docs) +- [Getting Help](#getting-help) - [Community Resources](#community-resources) - [Logging](#logging) - [Who uses AWS Data Wrangler?](#who-uses-aws-data-wrangler) -- [What is Amazon SageMaker Data Wrangler?](#what-is-amazon-sageMaker-data-wrangler) +- [What is Amazon Sagemaker Data Wrangler?](#what-is-amazon-sageMaker-data-wrangler) ## Quick Start Installation command: `pip install awswrangler` -> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-glue-pyspark-jobs), MWAA):**
+> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-glue-pyspark-jobs), MWAA):**
➡️`pip install pyarrow==2 awswrangler` ```py3 @@ -95,17 +96,17 @@ FROM "sampleDB"."sampleTable" ORDER BY time DESC LIMIT 3 ## [Read The Docs](https://aws-data-wrangler.readthedocs.io/) -- [**What is AWS Data Wrangler?**](https://aws-data-wrangler.readthedocs.io/en/2.9.0/what.html) -- [**Install**](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html) - - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#pypi-pip) - - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#conda) - - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-lambda-layer) - - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-glue-python-shell-jobs) - - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-glue-pyspark-jobs) - - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#amazon-sagemaker-notebook) - - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#amazon-sagemaker-notebook-lifecycle) - - [EMR](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#emr) - - [From source](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#from-source) +- [**What is AWS Data Wrangler?**](https://aws-data-wrangler.readthedocs.io/en/2.10.0/what.html) +- [**Install**](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html) + - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#pypi-pip) + - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#conda) + - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-lambda-layer) + - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-glue-python-shell-jobs) + - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-glue-pyspark-jobs) + - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#amazon-sagemaker-notebook) + - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#amazon-sagemaker-notebook-lifecycle) + - [EMR](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#emr) + - [From source](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#from-source) - [**Tutorials**](https://github.com/awslabs/aws-data-wrangler/tree/main/tutorials) - [001 - Introduction](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/001%20-%20Introduction.ipynb) - [002 - Sessions](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/002%20-%20Sessions.ipynb) @@ -135,26 +136,34 @@ FROM "sampleDB"."sampleTable" ORDER BY time DESC LIMIT 3 - [026 - Amazon Timestream](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/026%20-%20Amazon%20Timestream.ipynb) - [027 - Amazon Timestream 2](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/027%20-%20Amazon%20Timestream%202.ipynb) - [028 - Amazon DynamoDB](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/028%20-%20DynamoDB.ipynb) -- [**API Reference**](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html) - - [Amazon S3](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-s3) - - [AWS Glue Catalog](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#aws-glue-catalog) - - [Amazon Athena](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-athena) - - [Amazon Redshift](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-redshift) - - [PostgreSQL](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#postgresql) - - [MySQL](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#mysql) - - [SQL Server](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#sqlserver) - - [DynamoDB](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#dynamodb) - - [Amazon Timestream](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-timestream) - - [Amazon EMR](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-emr) - - [Amazon CloudWatch Logs](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-cloudwatch-logs) - - [Amazon Chime](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-chime) - - [Amazon QuickSight](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#amazon-quicksight) - - [AWS STS](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#aws-sts) - - [AWS Secrets Manager](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html#aws-secrets-manager) +- [**API Reference**](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html) + - [Amazon S3](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-s3) + - [AWS Glue Catalog](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#aws-glue-catalog) + - [Amazon Athena](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-athena) + - [Amazon Redshift](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-redshift) + - [PostgreSQL](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#postgresql) + - [MySQL](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#mysql) + - [SQL Server](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#sqlserver) + - [DynamoDB](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#dynamodb) + - [Amazon Timestream](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-timestream) + - [Amazon EMR](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-emr) + - [Amazon CloudWatch Logs](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-cloudwatch-logs) + - [Amazon Chime](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-chime) + - [Amazon QuickSight](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-quicksight) + - [AWS STS](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#aws-sts) + - [AWS Secrets Manager](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#aws-secrets-manager) - [**License**](https://github.com/awslabs/aws-data-wrangler/blob/main/LICENSE.txt) - [**Contributing**](https://github.com/awslabs/aws-data-wrangler/blob/main/CONTRIBUTING.md) - [**Legacy Docs** (pre-1.0.0)](https://aws-data-wrangler.readthedocs.io/en/0.3.3/) +## Getting Help + +The best way to interact with our team is through GitHub. You can open an [issue](https://github.com/awslabs/aws-data-wrangler/issues/new/choose) and choose from one of our templates for bug reports, feature requests... +You may also find help on these community resources: +* The #aws-data-wrangler Slack [channel](https://join.slack.com/t/aws-data-wrangler/shared_invite/zt-sxdx38sl-E0coRfAds8WdpxXD2Nzfrg) +* Ask a question on [Stack Overflow](https://stackoverflow.com/questions/tagged/awswrangler) + and tag it with `awswrangler` + ## Community Resources Please [send a Pull Request](https://github.com/awslabs/aws-data-wrangler/edit/main/README.md) with your resource reference and @githubhandle. diff --git a/awswrangler/__init__.py b/awswrangler/__init__.py index 6249471ff..55c0b702d 100644 --- a/awswrangler/__init__.py +++ b/awswrangler/__init__.py @@ -12,6 +12,7 @@ catalog, chime, cloudwatch, + data_api, dynamodb, emr, exceptions, @@ -35,6 +36,7 @@ "chime", "cloudwatch", "emr", + "data_api", "dynamodb", "exceptions", "quicksight", diff --git a/awswrangler/__metadata__.py b/awswrangler/__metadata__.py index a07e62c42..ec682bbe5 100644 --- a/awswrangler/__metadata__.py +++ b/awswrangler/__metadata__.py @@ -7,5 +7,5 @@ __title__: str = "awswrangler" __description__: str = "Pandas on AWS." -__version__: str = "2.9.0" +__version__: str = "2.10.0" __license__: str = "Apache License 2.0" diff --git a/awswrangler/_databases.py b/awswrangler/_databases.py index 8ae459744..fb7904c78 100644 --- a/awswrangler/_databases.py +++ b/awswrangler/_databases.py @@ -256,3 +256,9 @@ def convert_value_to_native_python_type(value: Any) -> Any: chunk_placeholders = ", ".join([f"({column_placeholders})" for _ in range(len(parameters_chunk))]) flattened_chunk = [convert_value_to_native_python_type(value) for row in parameters_chunk for value in row] yield chunk_placeholders, flattened_chunk + + +def validate_mode(mode: str, allowed_modes: List[str]) -> None: + """Check if mode is included in allowed_modes.""" + if mode not in allowed_modes: + raise exceptions.InvalidArgumentValue(f"mode must be one of {', '.join(allowed_modes)}") diff --git a/awswrangler/athena/_read.py b/awswrangler/athena/_read.py index 795cb5a4b..1229bba88 100644 --- a/awswrangler/athena/_read.py +++ b/awswrangler/athena/_read.py @@ -237,7 +237,7 @@ def _fetch_parquet_result( if not temp_table_fqn: raise exceptions.EmptyDataFrame("Query would return untyped, empty dataframe.") database, temp_table_name = map(lambda x: x.replace('"', ""), temp_table_fqn.split(".")) - dtype_dict = catalog.get_table_types(database=database, table=temp_table_name) + dtype_dict = catalog.get_table_types(database=database, table=temp_table_name, boto3_session=boto3_session) df = pd.DataFrame(columns=list(dtype_dict.keys())) df = cast_pandas_with_athena_types(df=df, dtype=dtype_dict) df = _apply_query_metadata(df=df, query_metadata=query_metadata) @@ -617,11 +617,11 @@ def read_sql_query( **Related tutorial:** - - `Amazon Athena `_ - - `Athena Cache `_ - - `Global Configurations `_ **There are two approaches to be defined through ctas_approach parameter:** @@ -669,7 +669,7 @@ def read_sql_query( /athena.html#Athena.Client.get_query_execution>`_ . For a practical example check out the - `related tutorial `_! @@ -779,7 +779,7 @@ def read_sql_query( The dict needs to contain the information in the form {'name': 'value'} and the SQL query needs to contain `:name;`. Note that for varchar columns and similar, you must surround the value in single quotes. s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'RequestPayer': 'requester'} Returns @@ -890,11 +890,11 @@ def read_sql_table( **Related tutorial:** - - `Amazon Athena `_ - - `Athena Cache `_ - - `Global Configurations `_ **There are two approaches to be defined through ctas_approach parameter:** @@ -939,7 +939,7 @@ def read_sql_table( /athena.html#Athena.Client.get_query_execution>`_ . For a practical example check out the - `related tutorial `_! @@ -1043,7 +1043,7 @@ def read_sql_table( data_source : str, optional Data Source / Catalog name. If None, 'AwsDataCatalog' will be used by default. s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'RequestPayer': 'requester'} Returns diff --git a/awswrangler/athena/_utils.py b/awswrangler/athena/_utils.py index 664e52e7a..a9a17acc9 100644 --- a/awswrangler/athena/_utils.py +++ b/awswrangler/athena/_utils.py @@ -405,6 +405,9 @@ def create_athena_bucket(boto3_session: Optional[boto3.Session] = None) -> str: bucket.create(**args) except resource.meta.client.exceptions.BucketAlreadyOwnedByYou as err: _logger.debug("Bucket %s already exists.", err.response["Error"]["BucketName"]) + except botocore.exceptions.ClientError as err: + if err.response["Error"]["Code"] == "OperationAborted": + _logger.debug("A conflicting conditional operation is currently in progress against this resource.") bucket.wait_until_exists() return path @@ -592,7 +595,7 @@ def describe_table( kms_key : str, optional For SSE-KMS and CSE-KMS , this is the KMS key ARN or ID. s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'RequestPayer': 'requester'} boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. @@ -663,7 +666,7 @@ def show_create_table( kms_key : str, optional For SSE-KMS and CSE-KMS , this is the KMS key ARN or ID. s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'RequestPayer': 'requester'} boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. diff --git a/awswrangler/data_api/__init__.py b/awswrangler/data_api/__init__.py new file mode 100644 index 000000000..5ebf997c9 --- /dev/null +++ b/awswrangler/data_api/__init__.py @@ -0,0 +1,7 @@ +"""Data API Service Module for RDS and Redshift.""" +from awswrangler.data_api import rds, redshift + +__all__ = [ + "redshift", + "rds", +] diff --git a/awswrangler/data_api/connector.py b/awswrangler/data_api/connector.py new file mode 100644 index 000000000..f565144e7 --- /dev/null +++ b/awswrangler/data_api/connector.py @@ -0,0 +1,71 @@ +"""Data API Connector base class.""" +import logging +from typing import Any, Dict, Optional + +import pandas as pd + + +class DataApiConnector: + """Base class for Data API (RDS, Redshift, etc.) connectors.""" + + def __init__(self, client: Any, logger: logging.Logger): + self.client = client + self.logger: logging.Logger = logger + + def execute(self, sql: str, database: Optional[str] = None) -> pd.DataFrame: + """Execute SQL statement against a Data API Service. + + Parameters + ---------- + sql: str + SQL statement to execute. + + Returns + ------- + A Pandas DataFrame containing the execution results. + """ + request_id: str = self._execute_statement(sql, database=database) + return self._get_statement_result(request_id) + + def _execute_statement(self, sql: str, database: Optional[str] = None) -> str: + raise NotImplementedError() + + def _get_statement_result(self, request_id: str) -> pd.DataFrame: + raise NotImplementedError() + + @staticmethod + def _get_column_value(column_value: Dict[str, Any]) -> Any: + """Return the first non-null key value for a given dictionary. + + The key names for a given record depend on the column type: stringValue, longValue, etc. + + Therefore, a record in the response does not have consistent key names. The ColumnMetadata + typeName information could be used to infer the key, but there is no direct mapping here + that could be easily parsed with creating a static dictionary: + varchar -> stringValue + int2 -> longValue + timestamp -> stringValue + + What has been observed is that each record appears to have a single key, so this function + iterates over the keys and returns the first non-null value. If none are found, None is + returned. + + Documentation: + https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/redshift-data.html#RedshiftDataAPIService.Client.get_statement_result + https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/rds-data.html#RDSDataService.Client.execute_statement + """ + for key in column_value: + if column_value[key] is not None: + if key == "arrayValue": + raise ValueError(f"arrayValue not supported yet - could not extract {column_value[key]}") + return column_value[key] + return None + + +class WaitConfig: + """Holds standard wait configuration values.""" + + def __init__(self, sleep: float, backoff: float, retries: int) -> None: + self.sleep = sleep + self.backoff = backoff + self.retries = retries diff --git a/awswrangler/data_api/rds.py b/awswrangler/data_api/rds.py new file mode 100644 index 000000000..71b34be51 --- /dev/null +++ b/awswrangler/data_api/rds.py @@ -0,0 +1,149 @@ +"""RDS Data API Connector.""" +import logging +import time +import uuid +from typing import Any, Dict, List, Optional + +import boto3 +import pandas as pd + +from awswrangler.data_api import connector + + +class RdsDataApi(connector.DataApiConnector): + """Provides access to the RDS Data API. + + Parameters + ---------- + resource_arn: str + ARN for the RDS resource. + database: str + Target database name. + secret_arn: str + The ARN for the secret to be used for authentication. + sleep: float + Number of seconds to sleep between connection attempts to paused clusters - defaults to 0.5. + backoff: float + Factor by which to increase the sleep between connection attempts to paused clusters - defaults to 1.0. + retries: int + Maximum number of connection attempts to paused clusters - defaults to 10. + """ + + def __init__( + self, + resource_arn: str, + database: str, + secret_arn: str = "", + sleep: float = 0.5, + backoff: float = 1.0, + retries: int = 30, + ) -> None: + self.resource_arn = resource_arn + self.database = database + self.secret_arn = secret_arn + self.wait_config = connector.WaitConfig(sleep, backoff, retries) + self.client = boto3.client("rds-data") + self.results: Dict[str, Dict[str, Any]] = {} + logger: logging.Logger = logging.getLogger(__name__) + super().__init__(self.client, logger) + + def _execute_statement(self, sql: str, database: Optional[str] = None) -> str: + if database is None: + database = self.database + + sleep: float = self.wait_config.sleep + total_tries: int = 0 + total_sleep: float = 0 + response: Optional[Dict[str, Any]] = None + last_exception: Optional[Exception] = None + while total_tries < self.wait_config.retries: + try: + response = self.client.execute_statement( + resourceArn=self.resource_arn, + database=database, + sql=sql, + secretArn=self.secret_arn, + includeResultMetadata=True, + ) + self.logger.debug( + "Response received after %s tries and sleeping for a total of %s seconds", total_tries, total_sleep + ) + break + except self.client.exceptions.BadRequestException as exception: + last_exception = exception + total_sleep += sleep + self.logger.debug("BadRequestException occurred: %s", exception) + self.logger.debug( + "Cluster may be paused - sleeping for %s seconds for a total of %s before retrying", + sleep, + total_sleep, + ) + time.sleep(sleep) + total_tries += 1 + sleep *= self.wait_config.backoff + + if response is None: + self.logger.exception("Maximum BadRequestException retries reached for query %s", sql) + raise self.client.exceptions.BadRequestException( + f"Query failed - BadRequestException received after {total_tries} tries and sleeping {total_sleep}s" + ) from last_exception + + request_id: str = uuid.uuid4().hex + self.results[request_id] = response + return request_id + + def _get_statement_result(self, request_id: str) -> pd.DataFrame: + try: + result = self.results.pop(request_id) + except KeyError as exception: + raise KeyError(f"Request {request_id} not found in results {self.results}") from exception + + if "records" not in result: + return pd.DataFrame() + + rows: List[List[Any]] = [] + for record in result["records"]: + row: List[Any] = [connector.DataApiConnector._get_column_value(column) for column in record] + rows.append(row) + + column_names: List[str] = [column["name"] for column in result["columnMetadata"]] + dataframe = pd.DataFrame(rows, columns=column_names) + return dataframe + + +def connect(resource_arn: str, database: str, secret_arn: str = "", **kwargs: Any) -> RdsDataApi: + """Create a RDS Data API connection. + + Parameters + ---------- + resource_arn: str + ARN for the RDS resource. + database: str + Target database name. + secret_arn: str + The ARN for the secret to be used for authentication. + **kwargs + Any additional kwargs are passed to the underlying RdsDataApi class. + + Returns + ------- + A RdsDataApi connection instance that can be used with `wr.rds.data_api.read_sql_query`. + """ + return RdsDataApi(resource_arn, database, secret_arn=secret_arn, **kwargs) + + +def read_sql_query(sql: str, con: RdsDataApi, database: Optional[str] = None) -> pd.DataFrame: + """Run an SQL query on an RdsDataApi connection and return the result as a dataframe. + + Parameters + ---------- + sql: str + SQL query to run. + database: str + Database to run query on - defaults to the database specified by `con`. + + Returns + ------- + A Pandas dataframe containing the query results. + """ + return con.execute(sql, database=database) diff --git a/awswrangler/data_api/redshift.py b/awswrangler/data_api/redshift.py new file mode 100644 index 000000000..d3947d91d --- /dev/null +++ b/awswrangler/data_api/redshift.py @@ -0,0 +1,199 @@ +"""Redshift Data API Connector.""" +import logging +import time +from typing import Any, Dict, List, Optional + +import boto3 +import pandas as pd + +from awswrangler.data_api import connector + + +class RedshiftDataApi(connector.DataApiConnector): + """Provides access to a Redshift cluster via the Data API. + + Parameters + ---------- + cluster_id: str + Id for the target Redshift cluster. + database: str + Target database name. + secret_arn: str + The ARN for the secret to be used for authentication - only required if `db_user` not provided. + db_user: str + The database user to generate temporary credentials for - only required if `secret_arn` not provided. + sleep: float + Number of seconds to sleep between result fetch attempts - defaults to 0.25. + backoff: float + Factor by which to increase the sleep between result fetch attempts - defaults to 1.5. + retries: int + Maximum number of result fetch attempts - defaults to 15. + """ + + def __init__( + self, + cluster_id: str, + database: str, + secret_arn: str = "", + db_user: str = "", + sleep: float = 0.25, + backoff: float = 1.5, + retries: int = 15, + ) -> None: + self.cluster_id = cluster_id + self.database = database + self.secret_arn = secret_arn + self.db_user = db_user + self.client = boto3.client("redshift-data") + self.waiter = RedshiftDataApiWaiter(self.client, sleep, backoff, retries) + logger: logging.Logger = logging.getLogger(__name__) + super().__init__(self.client, logger) + + def _validate_auth_method(self) -> None: + if self.secret_arn == "" and self.db_user == "": + raise ValueError("Either `secret_arn` or `db_user` must be set for authentication") + + def _execute_statement(self, sql: str, database: Optional[str] = None) -> str: + self._validate_auth_method() + credentials = {"SecretArn": self.secret_arn} + if self.db_user: + credentials = {"DbUser": self.db_user} + + if database is None: + database = self.database + + self.logger.debug("Executing %s", sql) + response: Dict[str, Any] = self.client.execute_statement( + ClusterIdentifier=self.cluster_id, + Database=database, + Sql=sql, + **credentials, + ) + return str(response["Id"]) + + def _get_statement_result(self, request_id: str) -> pd.DataFrame: + self.waiter.wait(request_id) + response: Dict[str, Any] + response = self.client.describe_statement(Id=request_id) + if not response["HasResultSet"]: + return pd.DataFrame() + + paginator = self.client.get_paginator("get_statement_result") + response_iterator = paginator.paginate(Id=request_id) + + rows: List[List[Any]] = [] + column_metadata: List[Dict[str, str]] + for response in response_iterator: + column_metadata = response["ColumnMetadata"] + for record in response["Records"]: + row: List[Any] = [connector.DataApiConnector._get_column_value(column) for column in record] + rows.append(row) + + column_names: List[str] = [column["name"] for column in column_metadata] + dataframe = pd.DataFrame(rows, columns=column_names) + return dataframe + + +class RedshiftDataApiWaiter: + """Waits for a DescribeStatement call to return a completed status. + + Parameters + ---------- + client: + A Boto client with a `describe_statement` function, such as 'redshift-data' + sleep: float + Number of seconds to sleep between tries. + backoff: float + Factor by which to increase the sleep between tries. + retries: int + Maximum number of tries. + """ + + def __init__(self, client: Any, sleep: float, backoff: float, retries: int) -> None: + self.client = client + self.wait_config = connector.WaitConfig(sleep, backoff, retries) + self.logger: logging.Logger = logging.getLogger(__name__) + + def wait(self, request_id: str) -> bool: + """Wait for the `describe_statement` function of self.client to return a completed status. + + Parameters + ---------- + request_id: + The execution id to check the status for. + + Returns + ------- + True if the execution finished without error. + Raises RedshiftDataApiExecutionFailedException if FAILED or ABORTED. + Raises RedshiftDataApiExecutionTimeoutException if retries exceeded before completion. + """ + sleep: float = self.wait_config.sleep + total_sleep: float = 0 + total_tries: int = 0 + while total_tries <= self.wait_config.retries: + response: Dict[str, Any] = self.client.describe_statement(Id=request_id) + status: str = response["Status"] + if status == "FINISHED": + return True + if status in ["ABORTED", "FAILED"]: + error = response["Error"] + raise RedshiftDataApiFailedException( + f"Request {request_id} failed with status {status} and error {error}" + ) + self.logger.debug("Statement execution status %s - sleeping for %s seconds", status, sleep) + time.sleep(sleep) + sleep = sleep * self.wait_config.backoff + total_tries += 1 + total_sleep += sleep + raise RedshiftDataApiTimeoutException( + f"Request {request_id} timed out after {total_tries} tries and {total_sleep}s total sleep" + ) + + +class RedshiftDataApiFailedException(Exception): + """Indicates a statement execution was aborted or failed.""" + + +class RedshiftDataApiTimeoutException(Exception): + """Indicates a statement execution did not complete in the expected wait time.""" + + +def connect(cluster_id: str, database: str, secret_arn: str = "", db_user: str = "", **kwargs: Any) -> RedshiftDataApi: + """Create a Redshift Data API connection. + + Parameters + ---------- + cluster_id: str + Id for the target Redshift cluster. + database: str + Target database name. + secret_arn: str + The ARN for the secret to be used for authentication - only required if `db_user` not provided. + db_user: str + The database user to generate temporary credentials for - only required if `secret_arn` not provided. + **kwargs + Any additional kwargs are passed to the underlying RedshiftDataApi class. + + Returns + ------- + A RedshiftDataApi connection instance that can be used with `wr.redshift.data_api.read_sql_query`. + """ + return RedshiftDataApi(cluster_id, database, secret_arn=secret_arn, db_user=db_user, **kwargs) + + +def read_sql_query(sql: str, con: RedshiftDataApi, database: Optional[str] = None) -> pd.DataFrame: + """Run an SQL query on a RedshiftDataApi connection and return the result as a dataframe. + + Parameters + ---------- + sql: str + SQL query to run. + database: str + Database to run query on - defaults to the database specified by `con`. + + Returns + ------- + A Pandas dataframe containing the query results. + """ + return con.execute(sql, database=database) diff --git a/awswrangler/mysql.py b/awswrangler/mysql.py index 573fe95fa..fefe2c801 100644 --- a/awswrangler/mysql.py +++ b/awswrangler/mysql.py @@ -18,7 +18,7 @@ _logger: logging.Logger = logging.getLogger(__name__) -def _validate_connection(con: pymysql.connections.Connection) -> None: +def _validate_connection(con: "pymysql.connections.Connection[Any]") -> None: if not isinstance(con, pymysql.connections.Connection): raise exceptions.InvalidConnection( "Invalid 'conn' argument, please pass a " @@ -77,7 +77,7 @@ def connect( read_timeout: Optional[int] = None, write_timeout: Optional[int] = None, connect_timeout: int = 10, -) -> pymysql.connections.Connection: +) -> "pymysql.connections.Connection[Any]": """Return a pymysql connection from a Glue Catalog Connection or Secrets Manager. https://pymysql.readthedocs.io @@ -150,7 +150,7 @@ def connect( def read_sql_query( sql: str, - con: pymysql.connections.Connection, + con: "pymysql.connections.Connection[Any]", index_col: Optional[Union[str, List[str]]] = None, params: Optional[Union[List[Any], Tuple[Any, ...], Dict[Any, Any]]] = None, chunksize: Optional[int] = None, @@ -206,7 +206,7 @@ def read_sql_query( def read_sql_table( table: str, - con: pymysql.connections.Connection, + con: "pymysql.connections.Connection[Any]", schema: Optional[str] = None, index_col: Optional[Union[str, List[str]]] = None, params: Optional[Union[List[Any], Tuple[Any, ...], Dict[Any, Any]]] = None, @@ -268,7 +268,7 @@ def read_sql_table( @apply_configs def to_sql( df: pd.DataFrame, - con: pymysql.connections.Connection, + con: "pymysql.connections.Connection[Any]", table: str, schema: str, mode: str = "append", @@ -292,8 +292,8 @@ def to_sql( Schema name mode : str Append, overwrite, upsert_duplicate_key, upsert_replace_into, upsert_distinct. - append: Inserts new records into table - overwrite: Drops table and recreates + append: Inserts new records into table. + overwrite: Drops table and recreates. upsert_duplicate_key: Performs an upsert using `ON DUPLICATE KEY` clause. Requires table schema to have defined keys, otherwise duplicate records will be inserted. upsert_replace_into: Performs upsert using `REPLACE INTO` clause. Less efficient and still requires the @@ -340,17 +340,16 @@ def to_sql( """ if df.empty is True: raise exceptions.EmptyDataFrame() + mode = mode.strip().lower() - modes = [ + allowed_modes = [ "append", "overwrite", "upsert_replace_into", "upsert_duplicate_key", "upsert_distinct", ] - if mode not in modes: - raise exceptions.InvalidArgumentValue(f"mode must be one of {', '.join(modes)}") - + _db_utils.validate_mode(mode=mode, allowed_modes=allowed_modes) _validate_connection(con=con) try: with con.cursor() as cursor: diff --git a/awswrangler/postgresql.py b/awswrangler/postgresql.py index 151eca61a..bc51ece20 100644 --- a/awswrangler/postgresql.py +++ b/awswrangler/postgresql.py @@ -277,6 +277,7 @@ def to_sql( varchar_lengths: Optional[Dict[str, int]] = None, use_column_names: bool = False, chunksize: int = 200, + upsert_conflict_columns: Optional[List[str]] = None, ) -> None: """Write records stored in a DataFrame into PostgreSQL. @@ -291,7 +292,11 @@ def to_sql( schema : str Schema name mode : str - Append or overwrite. + Append, overwrite or upsert. + append: Inserts new records into table. + overwrite: Drops table and recreates. + upsert: Perform an upsert which checks for conflicts on columns given by `upsert_conflict_columns` and + sets the new values on conflicts. Note that `upsert_conflict_columns` is required for this mode. index : bool True to store the DataFrame index as a column in the table, otherwise False to ignore it. @@ -307,6 +312,9 @@ def to_sql( inserted into the database columns `col1` and `col3`. chunksize: int Number of rows which are inserted with each SQL query. Defaults to inserting 200 rows per query. + upsert_conflict_columns: List[str], optional + This parameter is only supported if `mode` is set top `upsert`. In this case conflicts for the given columns are + checked for evaluating the upsert. Returns ------- @@ -330,6 +338,12 @@ def to_sql( """ if df.empty is True: raise exceptions.EmptyDataFrame() + + mode = mode.strip().lower() + allowed_modes = ["append", "overwrite", "upsert"] + _db_utils.validate_mode(mode=mode, allowed_modes=allowed_modes) + if mode == "upsert" and not upsert_conflict_columns: + raise exceptions.InvalidArgumentValue(" needs to be set when using upsert mode.") _validate_connection(con=con) try: with con.cursor() as cursor: @@ -347,13 +361,18 @@ def to_sql( df.reset_index(level=df.index.names, inplace=True) column_placeholders: str = ", ".join(["%s"] * len(df.columns)) insertion_columns = "" + upsert_str = "" if use_column_names: insertion_columns = f"({', '.join(df.columns)})" + if mode == "upsert": + upsert_columns = ", ".join(df.columns.map(lambda column: f"{column}=EXCLUDED.{column}")) + conflict_columns = ", ".join(upsert_conflict_columns) # type: ignore + upsert_str = f" ON CONFLICT ({conflict_columns}) DO UPDATE SET {upsert_columns}" placeholder_parameter_pair_generator = _db_utils.generate_placeholder_parameter_pairs( df=df, column_placeholders=column_placeholders, chunksize=chunksize ) for placeholders, parameters in placeholder_parameter_pair_generator: - sql: str = f'INSERT INTO "{schema}"."{table}" {insertion_columns} VALUES {placeholders}' + sql: str = f'INSERT INTO "{schema}"."{table}" {insertion_columns} VALUES {placeholders}{upsert_str}' _logger.debug("sql: %s", sql) cursor.executemany(sql, (parameters,)) con.commit() diff --git a/awswrangler/redshift.py b/awswrangler/redshift.py index 3ab21d19d..b4e55eadd 100644 --- a/awswrangler/redshift.py +++ b/awswrangler/redshift.py @@ -1253,9 +1253,7 @@ def copy_from_files( # pylint: disable=too-many-locals,too-many-arguments boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs: - Forward to botocore requests. Valid parameters: "ACL", "Metadata", "ServerSideEncryption", "StorageClass", - "SSECustomerAlgorithm", "SSECustomerKey", "SSEKMSKeyId", "SSEKMSEncryptionContext", "Tagging", - "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'ServerSideEncryption': 'aws:kms', 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN'} Returns @@ -1452,9 +1450,7 @@ def copy( # pylint: disable=too-many-arguments boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs: - Forward to botocore requests. Valid parameters: "ACL", "Metadata", "ServerSideEncryption", "StorageClass", - "SSECustomerAlgorithm", "SSECustomerKey", "SSEKMSKeyId", "SSEKMSEncryptionContext", "Tagging", - "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'ServerSideEncryption': 'aws:kms', 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN'} max_rows_by_file : int Max number of rows in each file. diff --git a/awswrangler/s3/_copy.py b/awswrangler/s3/_copy.py index c7307cef7..ef983f2e0 100644 --- a/awswrangler/s3/_copy.py +++ b/awswrangler/s3/_copy.py @@ -85,9 +85,7 @@ def merge_datasets( boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "ACL", "Metadata", "ServerSideEncryption", "StorageClass", - "SSECustomerAlgorithm", "SSECustomerKey", "SSEKMSKeyId", "SSEKMSEncryptionContext", "Tagging", - "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'ServerSideEncryption': 'aws:kms', 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN'} Returns @@ -189,9 +187,7 @@ def copy_objects( boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "ACL", "Metadata", "ServerSideEncryption", "StorageClass", - "SSECustomerAlgorithm", "SSECustomerKey", "SSEKMSKeyId", "SSEKMSEncryptionContext", "Tagging", - "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'ServerSideEncryption': 'aws:kms', 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN'} Returns diff --git a/awswrangler/s3/_delete.py b/awswrangler/s3/_delete.py index 4d84666a8..bf9ee3ca8 100644 --- a/awswrangler/s3/_delete.py +++ b/awswrangler/s3/_delete.py @@ -121,7 +121,7 @@ def delete_objects( Filter the s3 files by the Last modified date of the object. The filter is applied only after list all s3 files. s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'RequestPayer': 'requester'} boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. diff --git a/awswrangler/s3/_describe.py b/awswrangler/s3/_describe.py index 9a28d8f64..a4670bb4b 100644 --- a/awswrangler/s3/_describe.py +++ b/awswrangler/s3/_describe.py @@ -100,7 +100,7 @@ def describe_objects( Filter the s3 files by the Last modified date of the object. The filter is applied only after list all s3 files. s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'RequestPayer': 'requester'} boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. @@ -197,7 +197,7 @@ def size_objects( True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'RequestPayer': 'requester'} boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. diff --git a/awswrangler/s3/_fs.py b/awswrangler/s3/_fs.py index 32c759e93..183ff7f30 100644 --- a/awswrangler/s3/_fs.py +++ b/awswrangler/s3/_fs.py @@ -8,10 +8,12 @@ import socket from contextlib import contextmanager from errno import ESPIPE -from typing import Any, BinaryIO, Dict, Iterator, List, Optional, Set, Tuple, Union, cast +from typing import Any, BinaryIO, Dict, Iterator, List, Optional, Tuple, Union, cast import boto3 from botocore.exceptions import ReadTimeoutError +from botocore.loaders import Loader +from botocore.model import ServiceModel from awswrangler import _utils, exceptions from awswrangler._config import apply_configs @@ -24,84 +26,20 @@ _MIN_WRITE_BLOCK: int = 5_242_880 # 5 MB (5 * 2**20) _MIN_PARALLEL_READ_BLOCK: int = 5_242_880 # 5 MB (5 * 2**20) -BOTOCORE_ACCEPTED_KWARGS: Dict[str, Set[str]] = { - "get_object": { - "SSECustomerAlgorithm", - "SSECustomerKey", - "RequestPayer", - "ExpectedBucketOwner", - "VersionId", - }, - "copy_object": { - "ACL", - "Metadata", - "ServerSideEncryption", - "StorageClass", - "SSECustomerAlgorithm", - "SSECustomerKey", - "SSEKMSKeyId", - "SSEKMSEncryptionContext", - "Tagging", - "RequestPayer", - "ExpectedBucketOwner", - "CopySource", - }, - "create_multipart_upload": { - "ACL", - "Metadata", - "ServerSideEncryption", - "StorageClass", - "SSECustomerAlgorithm", - "SSECustomerKey", - "SSEKMSKeyId", - "SSEKMSEncryptionContext", - "Tagging", - "RequestPayer", - "ExpectedBucketOwner", - }, - "upload_part": { - "SSECustomerAlgorithm", - "SSECustomerKey", - "RequestPayer", - "ExpectedBucketOwner", - }, - "complete_multipart_upload": { - "RequestPayer", - "ExpectedBucketOwner", - }, - "put_object": { - "ACL", - "Metadata", - "ServerSideEncryption", - "StorageClass", - "SSECustomerAlgorithm", - "SSECustomerKey", - "SSEKMSKeyId", - "SSEKMSEncryptionContext", - "Tagging", - "RequestPayer", - "ExpectedBucketOwner", - }, - "list_objects_v2": { - "RequestPayer", - "ExpectedBucketOwner", - }, - "delete_objects": { - "RequestPayer", - "ExpectedBucketOwner", - "Objects", - }, - "head_object": { - "RequestPayer", - "ExpectedBucketOwner", - "VersionId", - }, -} +_BOTOCORE_LOADER = Loader() +_S3_JSON_MODEL = _BOTOCORE_LOADER.load_service_model(service_name="s3", type_name="service-2") +_S3_SERVICE_MODEL = ServiceModel(_S3_JSON_MODEL, service_name="s3") + + +def _snake_to_camel_case(s: str) -> str: + return "".join(c.title() for c in s.split("_")) def get_botocore_valid_kwargs(function_name: str, s3_additional_kwargs: Dict[str, Any]) -> Dict[str, Any]: """Filter and keep only the valid botocore key arguments.""" - return {k: v for k, v in s3_additional_kwargs.items() if k in BOTOCORE_ACCEPTED_KWARGS[function_name]} + s3_operation_model = _S3_SERVICE_MODEL.operation_model(_snake_to_camel_case(function_name)) + allowed_kwargs = s3_operation_model.input_shape.members.keys() # pylint: disable=E1101 + return {k: v for k, v in s3_additional_kwargs.items() if k in allowed_kwargs} def _fetch_range( diff --git a/awswrangler/s3/_list.py b/awswrangler/s3/_list.py index 43e09eab9..1232c67ef 100644 --- a/awswrangler/s3/_list.py +++ b/awswrangler/s3/_list.py @@ -149,10 +149,12 @@ def does_object_exist( path: str S3 path (e.g. s3://bucket/key). s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'RequestPayer': 'requester'} boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. + version_id: str, optional + Specific version of the object that should exist. Returns ------- @@ -216,7 +218,7 @@ def list_directories( path : str S3 path (e.g. s3://bucket/prefix). s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'RequestPayer': 'requester'} boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. @@ -286,7 +288,7 @@ def list_objects( ignore_empty: bool Ignore files with 0 bytes. s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'RequestPayer': 'requester'} boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. diff --git a/awswrangler/s3/_read_parquet.py b/awswrangler/s3/_read_parquet.py index aaf803d0a..660363a52 100644 --- a/awswrangler/s3/_read_parquet.py +++ b/awswrangler/s3/_read_parquet.py @@ -788,7 +788,7 @@ def read_parquet_table( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html columns : List[str], optional Names of columns to read from the file(s). validate_schema: diff --git a/awswrangler/s3/_read_text.py b/awswrangler/s3/_read_text.py index 7c2aec3e6..c6b4e9042 100644 --- a/awswrangler/s3/_read_text.py +++ b/awswrangler/s3/_read_text.py @@ -241,7 +241,7 @@ def read_csv( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html pandas_kwargs : KEYWORD arguments forwarded to pandas.read_csv(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. @@ -389,7 +389,7 @@ def read_fwf( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html pandas_kwargs: KEYWORD arguments forwarded to pandas.read_fwf(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. @@ -541,7 +541,7 @@ def read_json( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html pandas_kwargs: KEYWORD arguments forwarded to pandas.read_json(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. diff --git a/awswrangler/s3/_write_excel.py b/awswrangler/s3/_write_excel.py index af3b7fd4a..b6910a5c5 100644 --- a/awswrangler/s3/_write_excel.py +++ b/awswrangler/s3/_write_excel.py @@ -46,9 +46,7 @@ def to_excel( boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 Session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "ACL", "Metadata", "ServerSideEncryption", "StorageClass", - "SSECustomerAlgorithm", "SSECustomerKey", "SSEKMSKeyId", "SSEKMSEncryptionContext", "Tagging", - "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'ServerSideEncryption': 'aws:kms', 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN'} use_threads : bool True to enable concurrent requests, False to disable multiple threads. diff --git a/awswrangler/s3/_write_parquet.py b/awswrangler/s3/_write_parquet.py index 962d30fae..f1f327b11 100644 --- a/awswrangler/s3/_write_parquet.py +++ b/awswrangler/s3/_write_parquet.py @@ -258,9 +258,7 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "ACL", "Metadata", "ServerSideEncryption", "StorageClass", - "SSECustomerAlgorithm", "SSECustomerKey", "SSEKMSKeyId", "SSEKMSEncryptionContext", "Tagging", - "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'ServerSideEncryption': 'aws:kms', 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN'} sanitize_columns : bool True to sanitize columns names (using `wr.catalog.sanitize_table_name` and `wr.catalog.sanitize_column_name`) @@ -283,18 +281,18 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b concurrent_partitioning: bool If True will increase the parallelism level during the partitions writing. It will decrease the writing time and increase the memory usage. - https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html + https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html mode: str, optional ``append`` (Default), ``overwrite``, ``overwrite_partitions``. Only takes effect if dataset=True. For details check the related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet + https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet catalog_versioning : bool If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. schema_evolution : bool If True allows schema evolution (new or missing columns), otherwise a exception will be raised. (Only considered if dataset=True and mode in ("append", "overwrite_partitions")) Related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/014%20-%20Schema%20Evolution.html + https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/014%20-%20Schema%20Evolution.html database : str, optional Glue/Athena catalog: Database name. table : str, optional @@ -826,9 +824,7 @@ def store_parquet_metadata( # pylint: disable=too-many-arguments https://docs.aws.amazon.com/athena/latest/ug/partition-projection-supported-types.html (e.g. {'col_name': '1', 'col2_name': '2'}) s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "ACL", "Metadata", "ServerSideEncryption", "StorageClass", - "SSECustomerAlgorithm", "SSECustomerKey", "SSEKMSKeyId", "SSEKMSEncryptionContext", "Tagging", - "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'ServerSideEncryption': 'aws:kms', 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN'} boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. diff --git a/awswrangler/s3/_write_text.py b/awswrangler/s3/_write_text.py index df6cd8afe..fc1e15eaf 100644 --- a/awswrangler/s3/_write_text.py +++ b/awswrangler/s3/_write_text.py @@ -154,9 +154,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 Session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "ACL", "Metadata", "ServerSideEncryption", "StorageClass", - "SSECustomerAlgorithm", "SSECustomerKey", "SSEKMSKeyId", "SSEKMSEncryptionContext", "Tagging", - "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'ServerSideEncryption': 'aws:kms', 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN'} sanitize_columns : bool True to sanitize columns names or False to keep it as is. @@ -178,18 +176,18 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state concurrent_partitioning: bool If True will increase the parallelism level during the partitions writing. It will decrease the writing time and increase the memory usage. - https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html + https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html mode : str, optional ``append`` (Default), ``overwrite``, ``overwrite_partitions``. Only takes effect if dataset=True. For details check the related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet + https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet catalog_versioning : bool If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. schema_evolution : bool If True allows schema evolution (new or missing columns), otherwise a exception will be raised. (Only considered if dataset=True and mode in ("append", "overwrite_partitions")) Related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.9.0/tutorials/014%20-%20Schema%20Evolution.html + https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/014%20-%20Schema%20Evolution.html database : str, optional Glue/Athena catalog: Database name. table : str, optional @@ -691,9 +689,7 @@ def to_json( boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 Session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] - Forward to botocore requests. Valid parameters: "ACL", "Metadata", "ServerSideEncryption", "StorageClass", - "SSECustomerAlgorithm", "SSECustomerKey", "SSEKMSKeyId", "SSEKMSEncryptionContext", "Tagging", - "RequestPayer", "ExpectedBucketOwner". + Forwarded to botocore requests. e.g. s3_additional_kwargs={'ServerSideEncryption': 'aws:kms', 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN'} use_threads : bool True to enable concurrent requests, False to disable multiple threads. diff --git a/awswrangler/timestream.py b/awswrangler/timestream.py index 4bbc337c7..8c51bf2d1 100644 --- a/awswrangler/timestream.py +++ b/awswrangler/timestream.py @@ -32,6 +32,7 @@ def _write_batch( table: str, cols_names: List[str], measure_type: str, + version: int, batch: List[Any], boto3_primitives: _utils.Boto3PrimitivesType, ) -> List[Dict[str, str]]: @@ -59,6 +60,7 @@ def _write_batch( "MeasureValue": str(rec[1]), "Time": str(round(rec[0].timestamp() * 1_000)), "TimeUnit": "MILLISECONDS", + "Version": version, } for rec in batch ], @@ -117,6 +119,7 @@ def write( time_col: str, measure_col: str, dimensions_cols: List[str], + version: int = 1, num_threads: int = 32, boto3_session: Optional[boto3.Session] = None, ) -> List[Dict[str, str]]: @@ -136,6 +139,9 @@ def write( DataFrame column name to be used as measure. dimensions_cols : List[str] List of DataFrame column names to be used as dimensions. + version : int + Version number used for upserts. + Documentation https://docs.aws.amazon.com/timestream/latest/developerguide/API_WriteRecords.html. num_threads : str Number of thread to be used for concurrent writing. boto3_session : boto3.Session(), optional @@ -185,6 +191,7 @@ def write( itertools.repeat(table), itertools.repeat(cols_names), itertools.repeat(measure_type), + itertools.repeat(version), batches, itertools.repeat(_utils.boto3_to_primitives(boto3_session=boto3_session)), ) @@ -192,13 +199,17 @@ def write( return [item for sublist in res for item in sublist] -def query(sql: str, boto3_session: Optional[boto3.Session] = None) -> pd.DataFrame: +def query( + sql: str, pagination_config: Optional[Dict[str, Any]] = None, boto3_session: Optional[boto3.Session] = None +) -> pd.DataFrame: """Run a query and retrieve the result as a Pandas DataFrame. Parameters ---------- sql: str SQL query. + pagination_config: Dict[str, Any], optional + Pagination configuration dictionary of a form {'MaxItems': 10, 'PageSize': 10, 'StartingToken': '...'} boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 Session will be used if boto3_session receive None. @@ -223,7 +234,7 @@ def query(sql: str, boto3_session: Optional[boto3.Session] = None) -> pd.DataFra paginator = client.get_paginator("query") rows: List[List[Any]] = [] schema: List[Dict[str, str]] = [] - for page in paginator.paginate(QueryString=sql): + for page in paginator.paginate(QueryString=sql, PaginationConfig=pagination_config or {}): if not schema: schema = _process_schema(page=page) for row in page["Rows"]: diff --git a/building/lambda/build-lambda-layer.sh b/building/lambda/build-lambda-layer.sh index 8bf96afe7..5449c6cbb 100644 --- a/building/lambda/build-lambda-layer.sh +++ b/building/lambda/build-lambda-layer.sh @@ -14,7 +14,7 @@ export ARROW_HOME=$(pwd)/dist export LD_LIBRARY_PATH=$(pwd)/dist/lib:$LD_LIBRARY_PATH git clone \ - --branch apache-arrow-4.0.0 \ + --branch apache-arrow-5.0.0 \ --single-branch \ https://github.com/apache/arrow.git diff --git a/docs/environment.yml b/docs/environment.yml index 8dbc60fdb..d7ee84885 100644 --- a/docs/environment.yml +++ b/docs/environment.yml @@ -8,7 +8,7 @@ dependencies: - pip: - nbsphinx - nbsphinx-link - - sphinx + - sphinx==4.0.3 - sphinx_bootstrap_theme - IPython - -e .. diff --git a/docs/source/api.rst b/docs/source/api.rst index c9ce8b37b..b9b7b12aa 100644 --- a/docs/source/api.rst +++ b/docs/source/api.rst @@ -4,10 +4,13 @@ API Reference * `Amazon S3`_ * `AWS Glue Catalog`_ * `Amazon Athena`_ +* `AWS Lake Formation`_ * `Amazon Redshift`_ * `PostgreSQL`_ * `MySQL`_ * `Microsoft SQL Server`_ +* `Data API Redshift`_ +* `Data API RDS`_ * `DynamoDB`_ * `Amazon Timestream`_ * `Amazon EMR`_ @@ -116,6 +119,23 @@ Amazon Athena stop_query_execution wait_query +AWS Lake Formation +------------------ + +.. currentmodule:: awswrangler.lakeformation + +.. autosummary:: + :toctree: stubs + + read_sql_query + read_sql_table + cancel_transaction + commit_transaction + describe_transaction + extend_transaction + start_transaction + wait_query + Amazon Redshift --------------- @@ -173,6 +193,28 @@ ____________________ read_sql_table to_sql +Data API Redshift +----------------- + +.. currentmodule:: awswrangler.data_api.redshift + +.. autosummary:: + :toctree: stubs + + connect + read_sql_query + +Data API RDS +------------ + +.. currentmodule:: awswrangler.data_api.rds + +.. autosummary:: + :toctree: stubs + + connect + read_sql_query + DynamoDB -------- diff --git a/docs/source/install.rst b/docs/source/install.rst index f5688df6d..d846a6c9b 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -62,7 +62,7 @@ Go to your Glue PySpark job and create a new *Job parameters* key/value: To install a specific version, set the value for above Job parameter as follows: -* Value: ``pyarrow==2,awswrangler==2.9.0`` +* Value: ``pyarrow==2,awswrangler==2.10.0`` .. note:: Pyarrow 3 is not currently supported in Glue PySpark Jobs, which is why a previous installation of pyarrow 2 is required. @@ -95,7 +95,7 @@ Here is an example of how to reference the Lambda layer in your CDK app: "wrangler-bucket", bucket_arn="arn:aws:s3:::aws-data-wrangler-public-artifacts", ), - key="releases/2.9.0/awswrangler-layer-2.9.0-py3.8.zip", + key="releases/2.10.0/awswrangler-layer-2.10.0-py3.8.zip", ), layer_version_name="aws-data-wrangler" ) @@ -190,7 +190,7 @@ complement Big Data pipelines. sudo pip install pyarrow==2 awswrangler .. note:: Make sure to freeze the Wrangler version in the bootstrap for productive - environments (e.g. awswrangler==2.9.0) + environments (e.g. awswrangler==2.10.0) .. note:: Pyarrow 3 is not currently supported in the default EMR image, which is why a previous installation of pyarrow 2 is required. diff --git a/docs/source/what.rst b/docs/source/what.rst index 29aae1772..12e6995bd 100644 --- a/docs/source/what.rst +++ b/docs/source/what.rst @@ -8,4 +8,4 @@ SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL Built on top of other open-source projects like `Pandas `_, `Apache Arrow `_ and `Boto3 `_, it offers abstracted functions to execute usual ETL tasks like load/unload data from **Data Lakes**, **Data Warehouses** and **Databases**. -Check our `tutorials `_ or the `list of functionalities `_. \ No newline at end of file +Check our `tutorials `_ or the `list of functionalities `_. \ No newline at end of file diff --git a/requirements-dev.txt b/requirements-dev.txt index 68a665704..a5001518a 100644 --- a/requirements-dev.txt +++ b/requirements-dev.txt @@ -1,27 +1,27 @@ wheel==0.36.2 -isort==5.8.0 -black==21.6b0 -pylint==2.9.3 +isort==5.9.3 +black==21.7b0 +pylint==2.9.6 flake8==3.9.2 -mypy==0.902 +mypy==0.910 pydocstyle==6.1.1 -doc8==0.8.1 -tox==3.23.1 +doc8==0.9.0 +tox==3.24.1 pytest==6.2.4 pytest-cov==2.12.1 pytest-rerunfailures==10.1 pytest-xdist==2.3.0 pytest-timeout==1.4.2 pydot==1.4.2 -twine==3.4.1 +twine==3.4.2 sphinx==4.0.3 sphinx_bootstrap_theme==0.7.1 nbsphinx==0.8.6 nbsphinx-link==1.3.0 -IPython~=7.25 -moto==2.0.10 -jupyterlab==3.0.16 -s3fs==2021.6.1 +IPython==7.16.0 +moto==2.2.1 +jupyterlab==3.1.2 +s3fs==2021.7.0 python-Levenshtein==0.12.2 bump2version==1.0.1 -e .[sqlserver] diff --git a/requirements.txt b/requirements.txt index be188ce39..9107cccb2 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,9 +1,9 @@ boto3>=1.16.8,<2.0.0 botocore>=1.19.8,<2.0.0 -numpy>=1.18.0,<1.22.0 -pandas>=1.1.0,<1.4.0 -pyarrow>=2.0.0,<4.1.0 -redshift-connector~=2.0.882 +numpy>=1.18.0,<2.0.0 +pandas>=1.1.0,<2.0.0 +pyarrow>=2.0.0,<5.1.0 +redshift-connector~=2.0.884 pymysql>=0.9.0,<1.1.0 -pg8000>=1.16.0,<1.21.0 +pg8000>=1.16.0,<1.22.0 openpyxl~=3.0.0 diff --git a/test_infra/stacks/databases_stack.py b/test_infra/stacks/databases_stack.py index 90db53522..6d75a6c08 100644 --- a/test_infra/stacks/databases_stack.py +++ b/test_infra/stacks/databases_stack.py @@ -37,6 +37,7 @@ def __init__( self._setup_redshift() self._setup_postgresql() self._setup_mysql() + self._setup_mysql_serverless() self._setup_sqlserver() def _set_db_infra(self) -> None: @@ -232,7 +233,7 @@ def _setup_redshift(self) -> None: subnet=self.vpc.private_subnets[0], security_groups=[self.db_security_group], ) - secrets.Secret( + secret = secrets.Secret( self, "aws-data-wrangler-redshift-secret", secret_name="aws-data-wrangler/redshift", @@ -251,6 +252,7 @@ def _setup_redshift(self) -> None: ), ), ) + cdk.CfnOutput(self, "RedshiftSecretArn", value=secret.secret_arn) cdk.CfnOutput(self, "RedshiftIdentifier", value=redshift_cluster.cluster_name) cdk.CfnOutput( self, @@ -424,6 +426,62 @@ def _setup_mysql(self) -> None: cdk.CfnOutput(self, "MysqlDatabase", value=database) cdk.CfnOutput(self, "MysqlSchema", value=schema) + def _setup_mysql_serverless(self) -> None: + port = 3306 + database = "test" + schema = "test" + aurora_mysql = rds.ServerlessCluster( + self, + "aws-data-wrangler-aurora-cluster-mysql-serverless", + removal_policy=cdk.RemovalPolicy.DESTROY, + engine=rds.DatabaseClusterEngine.aurora_mysql( + version=rds.AuroraMysqlEngineVersion.VER_5_7_12, + ), + cluster_identifier="mysql-serverless-cluster-wrangler", + default_database_name=database, + credentials=rds.Credentials.from_password( + username=self.db_username, + password=self.db_password_secret, + ), + scaling=rds.ServerlessScalingOptions( + auto_pause=cdk.Duration.minutes(5), + min_capacity=rds.AuroraCapacityUnit.ACU_1, + max_capacity=rds.AuroraCapacityUnit.ACU_1, + ), + backup_retention=cdk.Duration.days(1), + vpc=self.vpc, + vpc_subnets=ec2.SubnetSelection(subnet_type=ec2.SubnetType.PRIVATE), + subnet_group=self.rds_subnet_group, + security_groups=[self.db_security_group], + enable_data_api=True, + ) + secret = secrets.Secret( + self, + "aws-data-wrangler-mysql-serverless-secret", + secret_name="aws-data-wrangler/mysql-serverless", + description="MySQL serverless credentials", + generate_secret_string=secrets.SecretStringGenerator( + generate_string_key="dummy", + secret_string_template=json.dumps( + { + "username": self.db_username, + "password": self.db_password, + "engine": "mysql", + "host": aurora_mysql.cluster_endpoint.hostname, + "port": port, + "dbClusterIdentifier": aurora_mysql.cluster_identifier, + "dbname": database, + } + ), + ), + ) + cdk.CfnOutput(self, "MysqlServerlessSecretArn", value=secret.secret_arn) + cdk.CfnOutput(self, "MysqlServerlessClusterArn", value=aurora_mysql.cluster_arn) + cdk.CfnOutput(self, "MysqlServerlessAddress", value=aurora_mysql.cluster_endpoint.hostname) + cdk.CfnOutput(self, "MysqlServerlessPort", value=str(port)) + cdk.CfnOutput(self, "MysqlServerlessDatabase", value=database) + cdk.CfnOutput(self, "MysqlServerlessSchema", value=schema) + def _setup_sqlserver(self) -> None: port = 1433 database = "test" diff --git a/tests/conftest.py b/tests/conftest.py index 32f7db353..7b6f7ec61 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -129,7 +129,7 @@ def workgroup3(bucket, kms_key): @pytest.fixture(scope="session") def databases_parameters(cloudformation_outputs, db_password): - parameters = dict(postgresql={}, mysql={}, redshift={}, sqlserver={}) + parameters = dict(postgresql={}, mysql={}, redshift={}, sqlserver={}, mysql_serverless={}) parameters["postgresql"]["host"] = cloudformation_outputs["PostgresqlAddress"] parameters["postgresql"]["port"] = 3306 parameters["postgresql"]["schema"] = "public" @@ -138,6 +138,7 @@ def databases_parameters(cloudformation_outputs, db_password): parameters["mysql"]["port"] = 3306 parameters["mysql"]["schema"] = "test" parameters["mysql"]["database"] = "test" + parameters["redshift"]["secret_arn"] = cloudformation_outputs["RedshiftSecretArn"] parameters["redshift"]["host"] = cloudformation_outputs["RedshiftAddress"] parameters["redshift"]["port"] = cloudformation_outputs["RedshiftPort"] parameters["redshift"]["identifier"] = cloudformation_outputs["RedshiftIdentifier"] @@ -150,6 +151,10 @@ def databases_parameters(cloudformation_outputs, db_password): parameters["sqlserver"]["port"] = 1433 parameters["sqlserver"]["schema"] = "dbo" parameters["sqlserver"]["database"] = "test" + parameters["mysql_serverless"]["secret_arn"] = cloudformation_outputs["MysqlServerlessSecretArn"] + parameters["mysql_serverless"]["schema"] = "test" + parameters["mysql_serverless"]["database"] = "test" + parameters["mysql_serverless"]["arn"] = cloudformation_outputs["MysqlServerlessClusterArn"] return parameters diff --git a/tests/test_data_api.py b/tests/test_data_api.py new file mode 100644 index 000000000..ca6547518 --- /dev/null +++ b/tests/test_data_api.py @@ -0,0 +1,129 @@ +import pandas as pd +import pytest + +import awswrangler as wr + +from ._utils import get_time_str_with_random_suffix + + +@pytest.fixture +def redshift_connector(databases_parameters): + cluster_id = databases_parameters["redshift"]["identifier"] + database = databases_parameters["redshift"]["database"] + secret_arn = databases_parameters["redshift"]["secret_arn"] + conn = wr.data_api.redshift.connect(cluster_id, database, secret_arn=secret_arn) + return conn + + +def create_rds_connector(rds_type, parameters): + cluster_id = parameters[rds_type]["arn"] + database = parameters[rds_type]["database"] + secret_arn = parameters[rds_type]["secret_arn"] + conn = wr.data_api.rds.connect(cluster_id, database, secret_arn=secret_arn) + return conn + + +@pytest.fixture +def mysql_serverless_connector(databases_parameters): + return create_rds_connector("mysql_serverless", databases_parameters) + + +@pytest.fixture(scope="function") +def mysql_serverless_table(mysql_serverless_connector): + name = f"tbl_{get_time_str_with_random_suffix()}" + print(f"Table name: {name}") + yield name + wr.data_api.rds.read_sql_query(f"DROP TABLE IF EXISTS test.{name}", con=mysql_serverless_connector) + + +def test_data_api_redshift_columnless_query(redshift_connector): + dataframe = wr.data_api.redshift.read_sql_query("SELECT 1", con=redshift_connector) + unknown_column_indicator = "?column?" + expected_dataframe = pd.DataFrame([[1]], columns=[unknown_column_indicator]) + pd.testing.assert_frame_equal(dataframe, expected_dataframe) + + +def test_data_api_redshift_basic_select(redshift_connector, redshift_table): + wr.data_api.redshift.read_sql_query( + f"CREATE TABLE public.{redshift_table} (id INT, name VARCHAR)", con=redshift_connector + ) + wr.data_api.redshift.read_sql_query( + f"INSERT INTO public.{redshift_table} VALUES (42, 'test')", con=redshift_connector + ) + dataframe = wr.data_api.redshift.read_sql_query(f"SELECT * FROM public.{redshift_table}", con=redshift_connector) + expected_dataframe = pd.DataFrame([[42, "test"]], columns=["id", "name"]) + pd.testing.assert_frame_equal(dataframe, expected_dataframe) + + +def test_data_api_redshift_empty_results_select(redshift_connector, redshift_table): + wr.data_api.redshift.read_sql_query( + f"CREATE TABLE public.{redshift_table} (id INT, name VARCHAR)", con=redshift_connector + ) + wr.data_api.redshift.read_sql_query( + f"INSERT INTO public.{redshift_table} VALUES (42, 'test')", con=redshift_connector + ) + dataframe = wr.data_api.redshift.read_sql_query( + f"SELECT * FROM public.{redshift_table} where id = 50", con=redshift_connector + ) + expected_dataframe = pd.DataFrame([], columns=["id", "name"]) + pd.testing.assert_frame_equal(dataframe, expected_dataframe) + + +def test_data_api_redshift_column_subset_select(redshift_connector, redshift_table): + wr.data_api.redshift.read_sql_query( + f"CREATE TABLE public.{redshift_table} (id INT, name VARCHAR)", con=redshift_connector + ) + wr.data_api.redshift.read_sql_query( + f"INSERT INTO public.{redshift_table} VALUES (42, 'test')", con=redshift_connector + ) + dataframe = wr.data_api.redshift.read_sql_query(f"SELECT name FROM public.{redshift_table}", con=redshift_connector) + expected_dataframe = pd.DataFrame([["test"]], columns=["name"]) + pd.testing.assert_frame_equal(dataframe, expected_dataframe) + + +def test_data_api_mysql_columnless_query(mysql_serverless_connector): + dataframe = wr.data_api.rds.read_sql_query("SELECT 1", con=mysql_serverless_connector) + expected_dataframe = pd.DataFrame([[1]], columns=["1"]) + pd.testing.assert_frame_equal(dataframe, expected_dataframe) + + +def test_data_api_mysql_basic_select(mysql_serverless_connector, mysql_serverless_table): + wr.data_api.rds.read_sql_query( + f"CREATE TABLE test.{mysql_serverless_table} (id INT, name VARCHAR(128))", con=mysql_serverless_connector + ) + wr.data_api.rds.read_sql_query( + f"INSERT INTO test.{mysql_serverless_table} VALUES (42, 'test')", con=mysql_serverless_connector + ) + dataframe = wr.data_api.rds.read_sql_query( + f"SELECT * FROM test.{mysql_serverless_table}", con=mysql_serverless_connector + ) + expected_dataframe = pd.DataFrame([[42, "test"]], columns=["id", "name"]) + pd.testing.assert_frame_equal(dataframe, expected_dataframe) + + +def test_data_api_mysql_empty_results_select(mysql_serverless_connector, mysql_serverless_table): + wr.data_api.rds.read_sql_query( + f"CREATE TABLE test.{mysql_serverless_table} (id INT, name VARCHAR(128))", con=mysql_serverless_connector + ) + wr.data_api.rds.read_sql_query( + f"INSERT INTO test.{mysql_serverless_table} VALUES (42, 'test')", con=mysql_serverless_connector + ) + dataframe = wr.data_api.rds.read_sql_query( + f"SELECT * FROM test.{mysql_serverless_table} where id = 50", con=mysql_serverless_connector + ) + expected_dataframe = pd.DataFrame([], columns=["id", "name"]) + pd.testing.assert_frame_equal(dataframe, expected_dataframe) + + +def test_data_api_mysql_column_subset_select(mysql_serverless_connector, mysql_serverless_table): + wr.data_api.rds.read_sql_query( + f"CREATE TABLE test.{mysql_serverless_table} (id INT, name VARCHAR(128))", con=mysql_serverless_connector + ) + wr.data_api.rds.read_sql_query( + f"INSERT INTO test.{mysql_serverless_table} VALUES (42, 'test')", con=mysql_serverless_connector + ) + dataframe = wr.data_api.rds.read_sql_query( + f"SELECT name FROM test.{mysql_serverless_table}", con=mysql_serverless_connector + ) + expected_dataframe = pd.DataFrame([["test"]], columns=["name"]) + pd.testing.assert_frame_equal(dataframe, expected_dataframe) diff --git a/tests/test_metadata.py b/tests/test_metadata.py index a4fc97a92..d63273380 100644 --- a/tests/test_metadata.py +++ b/tests/test_metadata.py @@ -2,7 +2,7 @@ def test_metadata(): - assert wr.__version__ == "2.9.0" + assert wr.__version__ == "2.10.0" assert wr.__title__ == "awswrangler" assert wr.__description__ == "Pandas on AWS." assert wr.__license__ == "Apache License 2.0" diff --git a/tests/test_moto.py b/tests/test_moto.py index d3b0f58c3..600d89f8a 100644 --- a/tests/test_moto.py +++ b/tests/test_moto.py @@ -522,3 +522,75 @@ def test_dynamodb_fail_on_invalid_items(moto_dynamodb): with pytest.raises(InvalidArgumentValue): wr.dynamodb.put_items(items=items, table_name=table_name) + + +def mock_data_api_connector(connector, has_result_set=True): + request_id = "1234" + statement_response = {"ColumnMetadata": [{"name": "col1"}], "Records": [[{"stringValue": "test"}]]} + column_names = [column["name"] for column in statement_response["ColumnMetadata"]] + data = [[col["stringValue"] for col in record] for record in statement_response["Records"]] + response_dataframe = pd.DataFrame(data, columns=column_names) + + if type(connector) == wr.data_api.redshift.RedshiftDataApi: + connector.client.execute_statement = mock.MagicMock(return_value={"Id": request_id}) + connector.client.describe_statement = mock.MagicMock( + return_value={"Status": "FINISHED", "HasResultSet": has_result_set} + ) + connector.client.get_statement_result = mock.MagicMock(return_value=statement_response) + elif type(connector) == wr.data_api.rds.RdsDataApi: + records = statement_response["Records"] + metadata = statement_response["ColumnMetadata"] + del statement_response["Records"] + del statement_response["ColumnMetadata"] + if has_result_set: + statement_response["columnMetadata"] = metadata + statement_response["records"] = records + connector.client.execute_statement = mock.MagicMock(return_value=statement_response) + else: + raise ValueError(f"Unsupported connector type {type(connector)}") + + return response_dataframe + + +def test_data_api_redshift_create_connection(): + cluster_id = "cluster123" + conn = wr.data_api.redshift.connect(cluster_id, "db1", db_user="admin") + assert conn.cluster_id == cluster_id + + +def test_data_api_redshift_read_sql_results(): + cluster_id = "cluster123" + con = wr.data_api.redshift.connect(cluster_id, "db1", db_user="admin") + expected_dataframe = mock_data_api_connector(con) + dataframe = wr.data_api.redshift.read_sql_query("SELECT * FROM test", con=con) + pd.testing.assert_frame_equal(dataframe, expected_dataframe) + + +def test_data_api_redshift_read_sql_no_results(): + cluster_id = "cluster123" + con = wr.data_api.redshift.connect(cluster_id, "db1", db_user="admin") + mock_data_api_connector(con, has_result_set=False) + dataframe = wr.data_api.redshift.read_sql_query("DROP TABLE test", con=con) + assert dataframe.empty is True + + +def test_data_api_rds_create_connection(): + resource_arn = "arn123" + conn = wr.data_api.rds.connect(resource_arn, "db1", secret_arn="arn123") + assert conn.resource_arn == resource_arn + + +def test_data_api_rds_read_sql_results(): + resource_arn = "arn123" + con = wr.data_api.rds.connect(resource_arn, "db1", secret_arn="arn123") + expected_dataframe = mock_data_api_connector(con) + dataframe = wr.data_api.rds.read_sql_query("SELECT * FROM test", con=con) + pd.testing.assert_frame_equal(dataframe, expected_dataframe) + + +def test_data_api_rds_read_sql_no_results(): + resource_arn = "arn123" + con = wr.data_api.rds.connect(resource_arn, "db1", secret_arn="arn123") + mock_data_api_connector(con, has_result_set=False) + dataframe = wr.data_api.rds.read_sql_query("DROP TABLE test", con=con) + assert dataframe.empty is True diff --git a/tests/test_postgresql.py b/tests/test_postgresql.py index 4ee0dcb89..6478cc09f 100644 --- a/tests/test_postgresql.py +++ b/tests/test_postgresql.py @@ -219,3 +219,155 @@ def test_dfs_are_equal_for_different_chunksizes(postgresql_table, postgresql_con df["c1"] = df["c1"].astype("string") assert df.equals(df2) + + +def test_upsert(postgresql_table, postgresql_con): + create_table_sql = ( + f"CREATE TABLE public.{postgresql_table} " + "(c0 varchar NULL PRIMARY KEY," + "c1 int NULL DEFAULT 42," + "c2 int NOT NULL);" + ) + with postgresql_con.cursor() as cursor: + cursor.execute(create_table_sql) + postgresql_con.commit() + + df = pd.DataFrame({"c0": ["foo", "bar"], "c2": [1, 2]}) + + with pytest.raises(wr.exceptions.InvalidArgumentValue): + wr.postgresql.to_sql( + df=df, + con=postgresql_con, + schema="public", + table=postgresql_table, + mode="upsert", + upsert_conflict_columns=None, + use_column_names=True, + ) + + wr.postgresql.to_sql( + df=df, + con=postgresql_con, + schema="public", + table=postgresql_table, + mode="upsert", + upsert_conflict_columns=["c0"], + use_column_names=True, + ) + wr.postgresql.to_sql( + df=df, + con=postgresql_con, + schema="public", + table=postgresql_table, + mode="upsert", + upsert_conflict_columns=["c0"], + use_column_names=True, + ) + df2 = wr.postgresql.read_sql_table(con=postgresql_con, schema="public", table=postgresql_table) + assert bool(len(df2) == 2) + + wr.postgresql.to_sql( + df=df, + con=postgresql_con, + schema="public", + table=postgresql_table, + mode="upsert", + upsert_conflict_columns=["c0"], + use_column_names=True, + ) + df3 = pd.DataFrame({"c0": ["baz", "bar"], "c2": [3, 2]}) + wr.postgresql.to_sql( + df=df3, + con=postgresql_con, + schema="public", + table=postgresql_table, + mode="upsert", + upsert_conflict_columns=["c0"], + use_column_names=True, + ) + df4 = wr.postgresql.read_sql_table(con=postgresql_con, schema="public", table=postgresql_table) + assert bool(len(df4) == 3) + + df5 = pd.DataFrame({"c0": ["foo", "bar"], "c2": [4, 5]}) + wr.postgresql.to_sql( + df=df5, + con=postgresql_con, + schema="public", + table=postgresql_table, + mode="upsert", + upsert_conflict_columns=["c0"], + use_column_names=True, + ) + + df6 = wr.postgresql.read_sql_table(con=postgresql_con, schema="public", table=postgresql_table) + assert bool(len(df6) == 3) + assert bool(len(df6.loc[(df6["c0"] == "foo") & (df6["c2"] == 4)]) == 1) + assert bool(len(df6.loc[(df6["c0"] == "bar") & (df6["c2"] == 5)]) == 1) + + +def test_upsert_multiple_conflict_columns(postgresql_table, postgresql_con): + create_table_sql = ( + f"CREATE TABLE public.{postgresql_table} " + "(c0 varchar NULL PRIMARY KEY," + "c1 int NOT NULL," + "c2 int NOT NULL," + "UNIQUE (c1, c2));" + ) + with postgresql_con.cursor() as cursor: + cursor.execute(create_table_sql) + postgresql_con.commit() + + df = pd.DataFrame({"c0": ["foo", "bar"], "c1": [1, 2], "c2": [3, 4]}) + upsert_conflict_columns = ["c1", "c2"] + + wr.postgresql.to_sql( + df=df, + con=postgresql_con, + schema="public", + table=postgresql_table, + mode="upsert", + upsert_conflict_columns=upsert_conflict_columns, + use_column_names=True, + ) + wr.postgresql.to_sql( + df=df, + con=postgresql_con, + schema="public", + table=postgresql_table, + mode="upsert", + upsert_conflict_columns=upsert_conflict_columns, + use_column_names=True, + ) + df2 = wr.postgresql.read_sql_table(con=postgresql_con, schema="public", table=postgresql_table) + assert bool(len(df2) == 2) + + df3 = pd.DataFrame({"c0": ["baz", "spam"], "c1": [1, 5], "c2": [3, 2]}) + wr.postgresql.to_sql( + df=df3, + con=postgresql_con, + schema="public", + table=postgresql_table, + mode="upsert", + upsert_conflict_columns=upsert_conflict_columns, + use_column_names=True, + ) + df4 = wr.postgresql.read_sql_table(con=postgresql_con, schema="public", table=postgresql_table) + assert bool(len(df4) == 3) + + df5 = pd.DataFrame({"c0": ["egg", "spam"], "c1": [2, 5], "c2": [4, 2]}) + wr.postgresql.to_sql( + df=df5, + con=postgresql_con, + schema="public", + table=postgresql_table, + mode="upsert", + upsert_conflict_columns=upsert_conflict_columns, + use_column_names=True, + ) + + df6 = wr.postgresql.read_sql_table(con=postgresql_con, schema="public", table=postgresql_table) + df7 = pd.DataFrame({"c0": ["baz", "egg", "spam"], "c1": [1, 2, 5], "c2": [3, 4, 2]}) + df7["c0"] = df7["c0"].astype("string") + df7["c1"] = df7["c1"].astype("Int64") + df7["c2"] = df7["c2"].astype("Int64") + assert df6.equals(df7) diff --git a/tests/test_timestream.py b/tests/test_timestream.py index 769c6fea2..0e4f26fd1 100644 --- a/tests/test_timestream.py +++ b/tests/test_timestream.py @@ -2,13 +2,15 @@ from datetime import datetime import pandas as pd +import pytest import awswrangler as wr logging.getLogger("awswrangler").setLevel(logging.DEBUG) -def test_basic_scenario(timestream_database_and_table): +@pytest.mark.parametrize("pagination", [None, {}, {"MaxItems": 3, "PageSize": 2}]) +def test_basic_scenario(timestream_database_and_table, pagination): name = timestream_database_and_table df = pd.DataFrame( { @@ -41,11 +43,65 @@ def test_basic_scenario(timestream_database_and_table): FROM "{name}"."{name}" ORDER BY time DESC LIMIT 10 - """ + """, + pagination_config=pagination, ) assert df.shape == (3, 8) +def test_versioned(timestream_database_and_table): + name = timestream_database_and_table + time = [datetime.now(), datetime.now(), datetime.now()] + dfs = [ + pd.DataFrame( + { + "time": time, + "dim0": ["foo", "boo", "bar"], + "dim1": [1, 2, 3], + "measure": [1.0, 1.1, 1.2], + } + ), + pd.DataFrame( + { + "time": time, + "dim0": ["foo", "boo", "bar"], + "dim1": [1, 2, 3], + "measure": [1.0, 1.1, 1.9], + } + ), + pd.DataFrame( + { + "time": time, + "dim0": ["foo", "boo", "bar"], + "dim1": [1, 2, 3], + "measure": [1.0, 1.1, 1.9], + } + ), + ] + versions = [1, 1, 2] + rejected_rec_nums = [0, 1, 0] + for df, version, rejected_rec_num in zip(dfs, versions, rejected_rec_nums): + rejected_records = wr.timestream.write( + df=df, + database=name, + table=name, + time_col="time", + measure_col="measure", + dimensions_cols=["dim0", "dim1"], + version=version, + ) + assert len(rejected_records) == rejected_rec_num + df_out = wr.timestream.query( + f""" + SELECT + * + FROM "{name}"."{name}" + DESC LIMIT 10 + """ + ) + assert df_out.shape == (3, 5) + + def test_real_csv_load_scenario(timestream_database_and_table): name = timestream_database_and_table df = pd.read_csv( diff --git a/tutorials/001 - Introduction.ipynb b/tutorials/001 - Introduction.ipynb index 8527b1e19..bf5a9be54 100644 --- a/tutorials/001 - Introduction.ipynb +++ b/tutorials/001 - Introduction.ipynb @@ -19,7 +19,7 @@ "\n", "Built on top of other open-source projects like [Pandas](https://github.com/pandas-dev/pandas), [Apache Arrow](https://github.com/apache/arrow) and [Boto3](https://github.com/boto/boto3), it offers abstracted functions to execute usual ETL tasks like load/unload data from **Data Lakes**, **Data Warehouses** and **Databases**.\n", "\n", - "Check our [list of functionalities](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html)." + "Check our [list of functionalities](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html)." ] }, { @@ -30,15 +30,15 @@ "\n", "The Wrangler runs almost anywhere over Python 3.6, 3.7, 3.8 and 3.9, so there are several different ways to install it in the desired enviroment.\n", "\n", - " - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#pypi-pip)\n", - " - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#conda)\n", - " - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-lambda-layer)\n", - " - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-glue-python-shell-jobs)\n", - " - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#aws-glue-pyspark-jobs)\n", - " - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#amazon-sagemaker-notebook)\n", - " - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#amazon-sagemaker-notebook-lifecycle)\n", - " - [EMR Cluster](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#emr-cluster)\n", - " - [From source](https://aws-data-wrangler.readthedocs.io/en/2.9.0/install.html#from-source)\n", + " - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#pypi-pip)\n", + " - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#conda)\n", + " - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-lambda-layer)\n", + " - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-glue-python-shell-jobs)\n", + " - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-glue-pyspark-jobs)\n", + " - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#amazon-sagemaker-notebook)\n", + " - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#amazon-sagemaker-notebook-lifecycle)\n", + " - [EMR Cluster](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#emr-cluster)\n", + " - [From source](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#from-source)\n", "\n", "Some good practices for most of the above methods are:\n", " - Use new and individual Virtual Environments for each project ([venv](https://docs.python.org/3/library/venv.html))\n", diff --git a/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb b/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb index aebf6a9ae..fdd15458a 100644 --- a/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb +++ b/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb @@ -10,14 +10,14 @@ "\n", "[Wrangler](https://github.com/awslabs/aws-data-wrangler)'s Redshift, MySQL and PostgreSQL have two basic function in common that tries to follow the Pandas conventions, but add more data type consistency.\n", "\n", - "- [wr.redshift.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.redshift.to_sql.html)\n", - "- [wr.redshift.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.redshift.read_sql_query.html)\n", - "- [wr.mysql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.mysql.to_sql.html)\n", - "- [wr.mysql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.mysql.read_sql_query.html)\n", - "- [wr.postgresql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.postgresql.to_sql.html)\n", - "- [wr.postgresql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.postgresql.read_sql_query.html)\n", - "- [wr.sqlserver.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.sqlserver.to_sql.html)\n", - "- [wr.sqlserver.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.sqlserver.read_sql_query.html)" + "- [wr.redshift.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.redshift.to_sql.html)\n", + "- [wr.redshift.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.redshift.read_sql_query.html)\n", + "- [wr.mysql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.mysql.to_sql.html)\n", + "- [wr.mysql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.mysql.read_sql_query.html)\n", + "- [wr.postgresql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.postgresql.to_sql.html)\n", + "- [wr.postgresql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.postgresql.read_sql_query.html)\n", + "- [wr.sqlserver.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.sqlserver.to_sql.html)\n", + "- [wr.sqlserver.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.sqlserver.read_sql_query.html)" ] }, { @@ -41,10 +41,10 @@ "source": [ "## Connect using the Glue Catalog Connections\n", "\n", - "- [wr.redshift.connect()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.redshift.connect.html)\n", - "- [wr.mysql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.mysql.connect.html)\n", - "- [wr.postgresql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.postgresql.connect.html)\n", - "- [wr.sqlserver.connect()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.sqlserver.connect.html)" + "- [wr.redshift.connect()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.redshift.connect.html)\n", + "- [wr.mysql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.mysql.connect.html)\n", + "- [wr.postgresql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.postgresql.connect.html)\n", + "- [wr.sqlserver.connect()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.sqlserver.connect.html)" ] }, { diff --git a/tutorials/014 - Schema Evolution.ipynb b/tutorials/014 - Schema Evolution.ipynb index 9fb6b93a0..d3dcff769 100644 --- a/tutorials/014 - Schema Evolution.ipynb +++ b/tutorials/014 - Schema Evolution.ipynb @@ -10,8 +10,8 @@ "\n", "Wrangler support new **columns** on Parquet Dataset through:\n", "\n", - "- [wr.s3.to_parquet()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet)\n", - "- [wr.s3.store_parquet_metadata()](https://aws-data-wrangler.readthedocs.io/en/2.9.0/stubs/awswrangler.s3.store_parquet_metadata.html#awswrangler.s3.store_parquet_metadata) i.e. \"Crawler\"" + "- [wr.s3.to_parquet()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet)\n", + "- [wr.s3.store_parquet_metadata()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.s3.store_parquet_metadata.html#awswrangler.s3.store_parquet_metadata) i.e. \"Crawler\"" ] }, { diff --git a/tutorials/021 - Global Configurations.ipynb b/tutorials/021 - Global Configurations.ipynb index 9b7b08314..b990873c7 100644 --- a/tutorials/021 - Global Configurations.ipynb +++ b/tutorials/021 - Global Configurations.ipynb @@ -13,7 +13,7 @@ "- **Environment variables**\n", "- **wr.config**\n", "\n", - "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html) to see if your function has some argument that can be configured through Global configurations.*\n", + "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html) to see if your function has some argument that can be configured through Global configurations.*\n", "\n", "*P.P.S. One exception to the above mentioned rules is the `botocore_config` property. It cannot be set through environment variables\n", "but only via `wr.config`. It will be used as the `botocore.config.Config` for all underlying `boto3` calls.\n", diff --git a/tutorials/022 - Writing Partitions Concurrently.ipynb b/tutorials/022 - Writing Partitions Concurrently.ipynb index 620d734b6..3f4f1d127 100644 --- a/tutorials/022 - Writing Partitions Concurrently.ipynb +++ b/tutorials/022 - Writing Partitions Concurrently.ipynb @@ -13,7 +13,7 @@ " If True will increase the parallelism level during the partitions writing. It will decrease the\n", " writing time and increase the memory usage.\n", "\n", - "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html) to see it has some argument that can be configured through Global configurations.*" + "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html) to see it has some argument that can be configured through Global configurations.*" ] }, { diff --git a/tutorials/023 - Flexible Partitions Filter.ipynb b/tutorials/023 - Flexible Partitions Filter.ipynb index 22f5c4354..d162c9656 100644 --- a/tutorials/023 - Flexible Partitions Filter.ipynb +++ b/tutorials/023 - Flexible Partitions Filter.ipynb @@ -16,7 +16,7 @@ " - Ignored if `dataset=False`.\n", " \n", "\n", - "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.9.0/api.html) to see it has some argument that can be configured through Global configurations.*" + "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html) to see it has some argument that can be configured through Global configurations.*" ] }, { diff --git a/validate.sh b/validate.sh index 4449c1428..66ac590d6 100755 --- a/validate.sh +++ b/validate.sh @@ -3,7 +3,7 @@ set -ex isort --check . black --check . -yes y | mypy --install-types awswrangler +mypy --install-types --non-interactive awswrangler flake8 . pylint -j 0 awswrangler pydocstyle awswrangler/ --convention=numpy From a4000b86a0fc84e6d3871e36978afe24fcd6d130 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Thu, 12 Aug 2021 09:30:54 +0100 Subject: [PATCH 18/36] Merging main - move to poetry --- .bumpversion.cfg | 4 + .flake8 | 4 + .github/workflows/minimal-tests.yml | 4 +- .github/workflows/static-checking.yml | 4 +- .gitignore | 4 + CONTRIBUTING.md | 18 +- MANIFEST.in | 15 - awswrangler/_utils.py | 2 +- awswrangler/timestream.py | 67 +- building/build-wheel.sh | 5 +- building/lambda/Dockerfile | 14 +- building/lambda/build-docker-images.sh | 6 +- building/publish.sh | 9 +- docs/environment.yml | 4 +- poetry.lock | 3419 ++++++++++++++++++++++++ pyproject.toml | 100 +- pytest.ini | 8 - requirements-dev.txt | 28 - requirements.txt | 9 - setup.cfg | 18 - setup.py | 42 - test_infra/poetry.lock | 773 ++++++ test_infra/pyproject.toml | 20 + test_infra/requirements.txt | 11 - tests/test_timestream.py | 35 + tox.ini | 2 +- 26 files changed, 4432 insertions(+), 193 deletions(-) create mode 100644 .flake8 delete mode 100644 MANIFEST.in create mode 100644 poetry.lock delete mode 100644 pytest.ini delete mode 100644 requirements-dev.txt delete mode 100644 requirements.txt delete mode 100644 setup.cfg delete mode 100644 setup.py create mode 100644 test_infra/poetry.lock create mode 100644 test_infra/pyproject.toml delete mode 100644 test_infra/requirements.txt diff --git a/.bumpversion.cfg b/.bumpversion.cfg index 438818fe7..5636ff7d4 100644 --- a/.bumpversion.cfg +++ b/.bumpversion.cfg @@ -4,6 +4,10 @@ commit = False tag = False tag_name = {new_version} +[bumpversion:file:pyproject.toml] + +[bumpversion:file:test_infra/pyproject.toml] + [bumpversion:file:README.md] [bumpversion:file:CONTRIBUTING_COMMON_ERRORS.md] diff --git a/.flake8 b/.flake8 new file mode 100644 index 000000000..a288046ad --- /dev/null +++ b/.flake8 @@ -0,0 +1,4 @@ +[flake8] +max-line-length = 120 +extend-ignore = E203, W503 +exclude = .git,__pycache__,docs/source/conf.py,old,build,dist,.venv,.venv2,.tox,dev,.env,.coverage diff --git a/.github/workflows/minimal-tests.yml b/.github/workflows/minimal-tests.yml index 065172e3d..60a31194b 100644 --- a/.github/workflows/minimal-tests.yml +++ b/.github/workflows/minimal-tests.yml @@ -28,7 +28,9 @@ jobs: - name: Install Requirements run: | python -m pip install --upgrade pip - pip install -U -r requirements-dev.txt + python -m pip install poetry + poetry config virtualenvs.create false --local + poetry install --extras "sqlserver" -vvv - name: Test Metadata run: pytest tests/test_metadata.py - name: Test Session diff --git a/.github/workflows/static-checking.yml b/.github/workflows/static-checking.yml index 122726553..b21320c4f 100644 --- a/.github/workflows/static-checking.yml +++ b/.github/workflows/static-checking.yml @@ -26,7 +26,9 @@ jobs: - name: Install Requirements run: | python -m pip install --upgrade pip - pip install -U -r requirements-dev.txt + python -m pip install poetry + poetry config virtualenvs.create false --local + poetry install --extras "sqlserver" -vvv - name: mypy check run: mypy --install-types --non-interactive awswrangler - name: Flake8 Lint diff --git a/.gitignore b/.gitignore index 668de0c16..6b0afd551 100644 --- a/.gitignore +++ b/.gitignore @@ -26,6 +26,10 @@ share/python-wheels/ *.egg MANIFEST +# poetry +poetry.toml +envs.toml + # PyInstaller # Usually these files are written by a python script from a template # before PyInstaller builds the exe, so as to inject date/other infos into it. diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index 37a5441a7..d3420ade6 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -92,7 +92,7 @@ You can choose from three different environments to test your fixes/changes, bas ### Mocked test environment * Pick up a Linux or MacOS. -* Install Python 3.7, 3.8 or 3.9 +* Install Python 3.7, 3.8 or 3.9 with [poetry](https://github.com/python-poetry/poetry) for package management * Fork the AWS Data Wrangler repository and clone that into your development environment * Go to the project's directory create a Python's virtual environment for the project @@ -104,7 +104,7 @@ or * Install dependencies: -``pip install -r requirements-dev.txt`` +``poetry install --extras "sqlserver"`` * Run the validation script: @@ -123,7 +123,7 @@ or **DISCLAIMER**: Make sure you know what you are doing. These steps will charge some services on your AWS account and require a minimum security skill to keep your environment safe. * Pick up a Linux or MacOS. -* Install Python 3.7, 3.8 or 3.9 +* Install Python 3.7, 3.8 or 3.9 with [poetry](https://github.com/python-poetry/poetry) for package management * Fork the AWS Data Wrangler repository and clone that into your development environment * Go to the project's directory create a Python's virtual environment for the project @@ -135,7 +135,7 @@ or * Install dependencies: -``pip install -r requirements-dev.txt`` +``poetry install --extras "sqlserver"`` * Go to the ``test_infra`` directory @@ -143,7 +143,7 @@ or * Install CDK dependencies: -``pip install -r requirements.txt`` +``poetry install`` * [OPTIONAL] Set AWS_DEFAULT_REGION to define the region the Data Lake Test environment will deploy into. You may want to choose a region which you don't currently use: @@ -184,7 +184,7 @@ or **DISCLAIMER**: This environment contains Aurora MySQL, Aurora PostgreSQL and Redshift (single-node) clusters which will incur cost while running. * Pick up a Linux or MacOS. -* Install Python 3.7, 3.8 or 3.9 +* Install Python 3.7, 3.8 or 3.9 with [poetry](https://github.com/python-poetry/poetry) for package management * Fork the AWS Data Wrangler repository and clone that into your development environment * Go to the project's directory create a Python's virtual environment for the project @@ -192,7 +192,7 @@ or * Then run the command bellow to install all dependencies: -``pip install -r requirements-dev.txt`` +``poetry install --extras "sqlserver"`` * Go to the ``test_infra`` directory @@ -200,9 +200,9 @@ or * Install CDK dependencies: -``pip install -r requirements.txt`` +``poetry install`` -* [OPTIONAL] Set AWS_DEFAULT_REGION to define the region the Full Test envrioment will deploy into. You may want to choose a region which you don't currently use: +* [OPTIONAL] Set AWS_DEFAULT_REGION to define the region the Full Test environment will deploy into. You may want to choose a region which you don't currently use: ``export AWS_DEFAULT_REGION=ap-northeast-1`` diff --git a/MANIFEST.in b/MANIFEST.in deleted file mode 100644 index fd6ffa392..000000000 --- a/MANIFEST.in +++ /dev/null @@ -1,15 +0,0 @@ -include README.md -include LICENSE.txt -include NOTICE.txt -include THIRD_PARTY.txt -include requirements.txt -include awswrangler/py.typed - -global-exclude *.so -global-exclude *.pyc -global-exclude *~ -global-exclude \#* -global-exclude .git* -global-exclude .coverage* -global-exclude .DS_Store -global-exclude __pycache__ diff --git a/awswrangler/_utils.py b/awswrangler/_utils.py index 7af1f440d..47580903c 100644 --- a/awswrangler/_utils.py +++ b/awswrangler/_utils.py @@ -229,7 +229,7 @@ def chunkify(lst: List[Any], num_chunks: int = 1, max_length: Optional[int] = No if not lst: return [] n: int = num_chunks if max_length is None else int(math.ceil((float(len(lst)) / float(max_length)))) - np_chunks = np.array_split(lst, n) # type: ignore + np_chunks = np.array_split(lst, n) return [arr.tolist() for arr in np_chunks if len(arr) > 0] diff --git a/awswrangler/timestream.py b/awswrangler/timestream.py index 8c51bf2d1..630332f52 100644 --- a/awswrangler/timestream.py +++ b/awswrangler/timestream.py @@ -4,7 +4,7 @@ import itertools import logging from datetime import datetime -from typing import Any, Dict, List, Optional, cast +from typing import Any, Dict, Iterator, List, Optional, Union, cast import boto3 import pandas as pd @@ -103,6 +103,14 @@ def _process_row(schema: List[Dict[str, str]], row: Dict[str, Any]) -> List[Any] return row_processed +def _rows_to_df(rows: List[List[Any]], schema: List[Dict[str, str]]) -> pd.DataFrame: + df = pd.DataFrame(data=rows, columns=[c["name"] for c in schema]) + for col in schema: + if col["type"] == "VARCHAR": + df[col["name"]] = df[col["name"]].astype("string") + return df + + def _process_schema(page: Dict[str, Any]) -> List[Dict[str, str]]: schema: List[Dict[str, str]] = [] for col in page["ColumnInfo"]: @@ -112,6 +120,29 @@ def _process_schema(page: Dict[str, Any]) -> List[Dict[str, str]]: return schema +def _paginate_query( + sql: str, pagination_config: Optional[Dict[str, Any]], boto3_session: Optional[boto3.Session] = None +) -> Iterator[pd.DataFrame]: + client: boto3.client = _utils.client( + service_name="timestream-query", + session=boto3_session, + botocore_config=Config(read_timeout=60, retries={"max_attempts": 10}), + ) + paginator = client.get_paginator("query") + rows: List[List[Any]] = [] + schema: List[Dict[str, str]] = [] + page_iterator = paginator.paginate(QueryString=sql, PaginationConfig=pagination_config or {}) + for page in page_iterator: + if not schema: + schema = _process_schema(page=page) + _logger.debug("schema: %s", schema) + for row in page["Rows"]: + rows.append(_process_row(schema=schema, row=row)) + if len(rows) > 0: + yield _rows_to_df(rows, schema) + rows = [] + + def write( df: pd.DataFrame, database: str, @@ -200,14 +231,19 @@ def write( def query( - sql: str, pagination_config: Optional[Dict[str, Any]] = None, boto3_session: Optional[boto3.Session] = None -) -> pd.DataFrame: + sql: str, + chunked: bool = False, + pagination_config: Optional[Dict[str, Any]] = None, + boto3_session: Optional[boto3.Session] = None, +) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: """Run a query and retrieve the result as a Pandas DataFrame. Parameters ---------- sql: str SQL query. + chunked: bool + If True returns dataframe iterator, and a single dataframe otherwise. False by default. pagination_config: Dict[str, Any], optional Pagination configuration dictionary of a form {'MaxItems': 10, 'PageSize': 10, 'StartingToken': '...'} boto3_session : boto3.Session(), optional @@ -220,31 +256,16 @@ def query( Examples -------- - Running a query and storing the result as a Pandas DataFrame + Run a query and return the result as a Pandas DataFrame or an iterable. >>> import awswrangler as wr >>> df = wr.timestream.query('SELECT * FROM "sampleDB"."sampleTable" ORDER BY time DESC LIMIT 10') """ - client: boto3.client = _utils.client( - service_name="timestream-query", - session=boto3_session, - botocore_config=Config(read_timeout=60, retries={"max_attempts": 10}), - ) - paginator = client.get_paginator("query") - rows: List[List[Any]] = [] - schema: List[Dict[str, str]] = [] - for page in paginator.paginate(QueryString=sql, PaginationConfig=pagination_config or {}): - if not schema: - schema = _process_schema(page=page) - for row in page["Rows"]: - rows.append(_process_row(schema=schema, row=row)) - _logger.debug("schema: %s", schema) - df = pd.DataFrame(data=rows, columns=[c["name"] for c in schema]) - for col in schema: - if col["type"] == "VARCHAR": - df[col["name"]] = df[col["name"]].astype("string") - return df + result_iterator = _paginate_query(sql, pagination_config, boto3_session) + if chunked: + return result_iterator + return pd.concat(result_iterator, ignore_index=True) def create_database( diff --git a/building/build-wheel.sh b/building/build-wheel.sh index a08ef04ad..e23e67d25 100755 --- a/building/build-wheel.sh +++ b/building/build-wheel.sh @@ -2,6 +2,5 @@ set -ex pushd .. -rm -rf *.egg-info build dist/*.whl -python setup.py bdist_wheel -rm -rf *.egg-info build +rm -rf dist/*.whl +poetry build -f wheel diff --git a/building/lambda/Dockerfile b/building/lambda/Dockerfile index 83453eb0a..1c210a89f 100644 --- a/building/lambda/Dockerfile +++ b/building/lambda/Dockerfile @@ -12,17 +12,13 @@ RUN yum install -y \ ninja-build \ ${py_dev} -RUN pip3 install --upgrade pip six cython cmake hypothesis +RUN pip3 install --upgrade pip six cython cmake hypothesis poetry -ADD requirements.txt /root/ -RUN pip3 install -r /root/requirements.txt +WORKDIR /root -ADD requirements-dev.txt /root/ -# Removing "-e ." installation -RUN head -n -3 /root/requirements-dev.txt > /root/temp.txt -RUN mv /root/temp.txt /root/requirements-dev.txt -RUN pip3 install -r /root/requirements-dev.txt +COPY pyproject.toml poetry.lock ./ +RUN poetry config virtualenvs.create false --local && poetry install --no-root -RUN rm -rf /root/requirements* +RUN rm -f pyproject.toml poetry.lock ENTRYPOINT ["/bin/sh"] \ No newline at end of file diff --git a/building/lambda/build-docker-images.sh b/building/lambda/build-docker-images.sh index 02d9a8398..80fe51465 100755 --- a/building/lambda/build-docker-images.sh +++ b/building/lambda/build-docker-images.sh @@ -1,8 +1,8 @@ #!/usr/bin/env bash set -ex -cp ../../requirements.txt . -cp ../../requirements-dev.txt . +cp ../../pyproject.toml . +cp ../../poetry.lock . # Python 3.6 docker build \ @@ -28,4 +28,4 @@ docker build \ --build-arg py_dev=python38-devel \ . -rm -rf requirements* +rm -rf pyproject.toml poetry.lock diff --git a/building/publish.sh b/building/publish.sh index 5459592b0..030979bd4 100755 --- a/building/publish.sh +++ b/building/publish.sh @@ -2,9 +2,6 @@ set -ex pushd .. -rm -fr build dist .egg awswrangler.egg-info -python3.6 setup.py bdist_egg -python3.6 setup.py bdist_wheel -python3.6 setup.py sdist -twine upload dist/* -rm -fr build dist .egg awswrangler.egg-info +rm -fr dist +poetry publish --build +rm -fr dist diff --git a/docs/environment.yml b/docs/environment.yml index d7ee84885..cd7afa7d6 100644 --- a/docs/environment.yml +++ b/docs/environment.yml @@ -8,7 +8,7 @@ dependencies: - pip: - nbsphinx - nbsphinx-link - - sphinx==4.0.3 + - sphinx - sphinx_bootstrap_theme - IPython - - -e .. + - .. diff --git a/poetry.lock b/poetry.lock new file mode 100644 index 000000000..c001b9152 --- /dev/null +++ b/poetry.lock @@ -0,0 +1,3419 @@ +[[package]] +name = "aiobotocore" +version = "1.3.3" +description = "Async client for aws services using botocore and aiohttp" +category = "dev" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +aiohttp = ">=3.3.1" +aioitertools = ">=0.5.1" +botocore = ">=1.20.106,<1.20.107" +wrapt = ">=1.10.10" + +[package.extras] +awscli = ["awscli (>=1.19.106,<1.19.107)"] +boto3 = ["boto3 (>=1.17.106,<1.17.107)"] + +[[package]] +name = "aiohttp" +version = "3.7.4.post0" +description = "Async http client/server framework (asyncio)" +category = "dev" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +async-timeout = ">=3.0,<4.0" +attrs = ">=17.3.0" +chardet = ">=2.0,<5.0" +idna-ssl = {version = ">=1.0", markers = "python_version < \"3.7\""} +multidict = ">=4.5,<7.0" +typing-extensions = ">=3.6.5" +yarl = ">=1.0,<2.0" + +[package.extras] +speedups = ["aiodns", "brotlipy", "cchardet"] + +[[package]] +name = "aioitertools" +version = "0.8.0" +description = "itertools and builtins for AsyncIO and mixed iterables" +category = "dev" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +typing_extensions = {version = ">=3.7", markers = "python_version < \"3.8\""} + +[[package]] +name = "alabaster" +version = "0.7.12" +description = "A configurable sidebar-enabled Sphinx theme" +category = "dev" +optional = false +python-versions = "*" + +[[package]] +name = "anyio" +version = "3.3.0" +description = "High level compatibility layer for multiple asynchronous event loop implementations" +category = "dev" +optional = false +python-versions = ">=3.6.2" + +[package.dependencies] +dataclasses = {version = "*", markers = "python_version < \"3.7\""} +idna = ">=2.8" +sniffio = ">=1.1" +typing-extensions = {version = "*", markers = "python_version < \"3.8\""} + +[package.extras] +doc = ["sphinx-rtd-theme", "sphinx-autodoc-typehints (>=1.2.0)"] +test = ["coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "pytest (>=6.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (<0.15)", "mock (>=4)", "uvloop (>=0.15)"] +trio = ["trio (>=0.16)"] + +[[package]] +name = "appdirs" +version = "1.4.4" +description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." +category = "dev" +optional = false +python-versions = "*" + +[[package]] +name = "appnope" +version = "0.1.2" +description = "Disable App Nap on macOS >= 10.9" +category = "dev" +optional = false +python-versions = "*" + +[[package]] +name = "argon2-cffi" +version = "20.1.0" +description = "The secure Argon2 password hashing algorithm." +category = "dev" +optional = false +python-versions = "*" + +[package.dependencies] +cffi = ">=1.0.0" +six = "*" + +[package.extras] +dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest", "sphinx", "wheel", "pre-commit"] +docs = ["sphinx"] +tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest"] + +[[package]] +name = "asn1crypto" +version = "1.4.0" +description = "Fast ASN.1 parser and serializer with definitions for private keys, public keys, certificates, CRL, OCSP, CMS, PKCS#3, PKCS#7, PKCS#8, PKCS#12, PKCS#5, X.509 and TSP" +category = "main" +optional = false +python-versions = "*" + +[[package]] +name = "astroid" +version = "2.6.6" +description = "An abstract syntax tree for Python with inference support." +category = "dev" +optional = false +python-versions = "~=3.6" + +[package.dependencies] +lazy-object-proxy = ">=1.4.0" +typed-ast = {version = ">=1.4.0,<1.5", markers = "implementation_name == \"cpython\" and python_version < \"3.8\""} +typing-extensions = {version = ">=3.7.4", markers = "python_version < \"3.8\""} +wrapt = ">=1.11,<1.13" + +[[package]] +name = "async-generator" +version = "1.10" +description = "Async generators and context managers for Python 3.5+" +category = "dev" +optional = false +python-versions = ">=3.5" + +[[package]] +name = "async-timeout" +version = "3.0.1" +description = "Timeout context manager for asyncio programs" +category = "dev" +optional = false +python-versions = ">=3.5.3" + +[[package]] +name = "atomicwrites" +version = "1.4.0" +description = "Atomic file writes." +category = "dev" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" + +[[package]] +name = "attrs" +version = "21.2.0" +description = "Classes Without Boilerplate" +category = "dev" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" + +[package.extras] +dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface", "furo", "sphinx", "sphinx-notfound-page", "pre-commit"] +docs = ["furo", "sphinx", "zope.interface", "sphinx-notfound-page"] +tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins", "zope.interface"] +tests_no_zope = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (>=4.3.0)", "six", "mypy", "pytest-mypy-plugins"] + +[[package]] +name = "babel" +version = "2.9.1" +description = "Internationalization utilities" +category = "dev" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" + +[package.dependencies] +pytz = ">=2015.7" + +[[package]] +name = "backcall" +version = "0.2.0" +description = "Specifications for callback functions passed in to an API" +category = "dev" +optional = false +python-versions = "*" + +[[package]] +name = "backports.entry-points-selectable" +version = "1.1.0" +description = "Compatibility shim providing selectable entry points for older implementations" +category = "dev" +optional = false +python-versions = ">=2.7" + +[package.dependencies] +importlib-metadata = {version = "*", markers = "python_version < \"3.8\""} + +[package.extras] +docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"] +testing = 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["Igor Tavares"] +license = "Apache License 2.0" + +readme = "README.md" + +include = ["README.md", "LICENSE.txt", "NOTICE.txt", "THIRD_PARTY.txt", "awswrangler/py.typed"] + +exclude = ["*.so", "*.pyc", "*~", "#*", ".git*", ".coverage*", "DS_Store", "__pycache__"] + +homepage = "https://aws-data-wrangler.readthedocs.io/" +repository = "https://github.com/awslabs/aws-data-wrangler" +documentation = "https://aws-data-wrangler.readthedocs.io/" + +keywords = ["pandas", "aws"] + +classifiers = [ + "Programming Language :: Python :: 3.6", + "Programming Language :: Python :: 3.7", + "Programming Language :: Python :: 3.8", + "Programming Language :: Python :: 3.9", +] + +[tool.poetry.dependencies] +python = ">=3.6.2, <3.10" + +boto3 = "^1.16.8" +botocore = "^1.19.8" +# python_full_version instead of just python is needed until the changes +# from https://github.com/python-poetry/poetry-core/pull/180 are released +pandas = [ + { version = "~1.1.0", markers = "python_full_version ~= '3.6.2'" 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/dev/null @@ -1,8 +0,0 @@ -[pytest] -log_cli=False -filterwarnings = - ignore::DeprecationWarning -addopts = - --log-cli-format "[%(name)s][%(funcName)s] %(message)s" - --verbose - --capture=sys diff --git a/requirements-dev.txt b/requirements-dev.txt deleted file mode 100644 index a5001518a..000000000 --- a/requirements-dev.txt +++ /dev/null @@ -1,28 +0,0 @@ -wheel==0.36.2 -isort==5.9.3 -black==21.7b0 -pylint==2.9.6 -flake8==3.9.2 -mypy==0.910 -pydocstyle==6.1.1 -doc8==0.9.0 -tox==3.24.1 -pytest==6.2.4 -pytest-cov==2.12.1 -pytest-rerunfailures==10.1 -pytest-xdist==2.3.0 -pytest-timeout==1.4.2 -pydot==1.4.2 -twine==3.4.2 -sphinx==4.0.3 -sphinx_bootstrap_theme==0.7.1 -nbsphinx==0.8.6 -nbsphinx-link==1.3.0 -IPython==7.16.0 -moto==2.2.1 -jupyterlab==3.1.2 -s3fs==2021.7.0 -python-Levenshtein==0.12.2 -bump2version==1.0.1 --e .[sqlserver] --e .[excel-py3.6] \ No newline at end of file diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 9107cccb2..000000000 --- a/requirements.txt +++ /dev/null @@ -1,9 +0,0 @@ -boto3>=1.16.8,<2.0.0 -botocore>=1.19.8,<2.0.0 -numpy>=1.18.0,<2.0.0 -pandas>=1.1.0,<2.0.0 -pyarrow>=2.0.0,<5.1.0 -redshift-connector~=2.0.884 -pymysql>=0.9.0,<1.1.0 -pg8000>=1.16.0,<1.22.0 -openpyxl~=3.0.0 diff --git a/setup.cfg b/setup.cfg deleted file mode 100644 index 57c94f1d7..000000000 --- a/setup.cfg +++ /dev/null @@ -1,18 +0,0 @@ -[metadata] -license_files = - LICENSE.txt - NOTICE.txt - THIRD_PARTY.txt - -[flake8] -max-line-length = 120 -extend-ignore = E203, W503 -exclude = .git,__pycache__,docs/source/conf.py,old,build,dist,.venv,.venv2,.tox,dev,.env,.coverage - -[mypy] -python_version = 3.7 -strict = True -ignore_missing_imports = True - -[mypy-tests.*] -ignore_errors = True diff --git a/setup.py b/setup.py deleted file mode 100644 index f3b24b569..000000000 --- a/setup.py +++ /dev/null @@ -1,42 +0,0 @@ -import os -from io import open -from typing import Dict - -from setuptools import find_packages, setup - -here = os.path.abspath(os.path.dirname(__file__)) -about: Dict[str, str] = {} -path = os.path.join(here, "awswrangler", "__metadata__.py") -with open(file=path, mode="r", encoding="utf-8") as f: - exec(f.read(), about) - -with open("README.md", "r", encoding="utf-8") as fh: - long_description = fh.read() - -setup( - author="Igor Tavares", - url="https://github.com/awslabs/aws-data-wrangler", - name=about["__title__"], - version=about["__version__"], - description=about["__description__"], - long_description=long_description, - long_description_content_type="text/markdown", - license=about["__license__"], - packages=find_packages(exclude=["tests"]), - include_package_data=True, - python_requires=">=3.6, <3.10", - install_requires=open("requirements.txt").read().strip().split("\n"), - classifiers=[ - "Programming Language :: Python :: 3.6", - "Programming Language :: Python :: 3.7", - "Programming Language :: Python :: 3.8", - "Programming Language :: Python :: 3.9", - ], - extras_require={ - 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All types are now available under the core module" +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +"aws-cdk.core" = "1.115.0" +"aws-cdk.cx-api" = "1.115.0" +constructs = ">=3.3.69,<4.0.0" +jsii = ">=1.31.0,<2.0.0" +publication = ">=0.0.3" + +[[package]] +name = "aws-cdk.aws-applicationautoscaling" +version = "1.115.0" +description = "The CDK Construct Library for AWS::ApplicationAutoScaling" +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +"aws-cdk.aws-autoscaling-common" = "1.115.0" +"aws-cdk.aws-cloudwatch" = "1.115.0" +"aws-cdk.aws-iam" = "1.115.0" +"aws-cdk.core" = "1.115.0" +constructs = ">=3.3.69,<4.0.0" +jsii = ">=1.31.0,<2.0.0" +publication = ">=0.0.3" + +[[package]] +name = "aws-cdk.aws-autoscaling-common" +version = "1.115.0" +description = "Common implementation package for @aws-cdk/aws-autoscaling and @aws-cdk/aws-applicationautoscaling" +category = "main" +optional = false +python-versions 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+python = ">=3.6.2, <3.10" +"aws-cdk.core" = "^1.115.0" +"aws-cdk.aws-ec2" = "^1.115.0" +"aws-cdk.aws-glue" = "^1.115.0" +"aws-cdk.aws-iam" = "^1.115.0" +"aws-cdk.aws-kms" = "^1.115.0" +"aws-cdk.aws-logs" = "^1.115.0" +"aws-cdk.aws-s3" = "^1.115.0" +"aws-cdk.aws-redshift" = "^1.115.0" +"aws-cdk.aws-rds" = "^1.115.0" +"aws-cdk.aws-secretsmanager" = "^1.115.0" +"aws-cdk.aws-ssm" = "^1.115.0" diff --git a/test_infra/requirements.txt b/test_infra/requirements.txt deleted file mode 100644 index f7d1f19a0..000000000 --- a/test_infra/requirements.txt +++ /dev/null @@ -1,11 +0,0 @@ -aws-cdk.core>=1.106.1 -aws-cdk.aws_ec2>=1.106.1 -aws-cdk.aws_glue>=1.106.1 -aws-cdk.aws_iam>=1.106.1 -aws-cdk.aws_kms>=1.106.1 -aws-cdk.aws_logs>=1.106.1 -aws-cdk.aws_s3>=1.106.1 -aws-cdk.aws_redshift>=1.106.1 -aws-cdk.aws_rds>=1.106.1 -aws_cdk.aws_secretsmanager>=1.106.1 -aws_cdk.aws_ssm>=1.106.1 \ No newline at end of file diff --git a/tests/test_timestream.py b/tests/test_timestream.py index 0e4f26fd1..2c9a01132 100644 --- a/tests/test_timestream.py +++ b/tests/test_timestream.py @@ -49,6 +49,41 @@ def test_basic_scenario(timestream_database_and_table, pagination): assert df.shape == (3, 8) +def test_chunked_scenario(timestream_database_and_table): + df = pd.DataFrame( + { + "time": [datetime.now() for _ in range(5)], + "dim0": ["foo", "boo", "bar", "fizz", "buzz"], + "dim1": [1, 2, 3, 4, 5], + "measure": [1.0, 1.1, 1.2, 1.3, 1.4], + } + ) + rejected_records = wr.timestream.write( + df=df, + database=timestream_database_and_table, + table=timestream_database_and_table, + time_col="time", + measure_col="measure", + dimensions_cols=["dim0", "dim1"], + ) + assert len(rejected_records) == 0 + shapes = [(3, 5), (2, 5)] + for df, shape in zip( + wr.timestream.query( + f""" + SELECT + * + FROM "{timestream_database_and_table}"."{timestream_database_and_table}" + ORDER BY time ASC + """, + chunked=True, + pagination_config={"MaxItems": 5, "PageSize": 3}, + ), + shapes, + ): + assert df.shape == shape + + def test_versioned(timestream_database_and_table): name = timestream_database_and_table time = [datetime.now(), datetime.now(), datetime.now()] diff --git a/tox.ini b/tox.ini index 649cd60e4..49f237d3b 100644 --- a/tox.ini +++ b/tox.ini @@ -1,11 +1,11 @@ [tox] envlist = py{36,37,38,39} +isolated_build = True [testenv] passenv = AWS_PROFILE AWS_DEFAULT_REGION AWS_ACCESS_KEY_ID AWS_SECRET_ACCESS_KEY AWS_SESSION_TOKEN deps = .[sqlserver] - .[excel-py3.6] pytest==6.2.2 pytest-rerunfailures==9.1.1 pytest-xdist==2.2.1 From b361d37ac9e9c2df2b0685765ea9a7dba5833434 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Tue, 7 Sep 2021 11:57:08 +0100 Subject: [PATCH 19/36] Merge main and resolve conflicts --- .bumpversion.cfg | 2 +- CONTRIBUTING_COMMON_ERRORS.md | 6 +- README.md | 60 +++++----- awswrangler/__metadata__.py | 2 +- awswrangler/_config.py | 11 ++ awswrangler/_databases.py | 23 ++-- awswrangler/_utils.py | 20 ++++ awswrangler/athena/_read.py | 16 +-- awswrangler/catalog/_create.py | 17 +-- awswrangler/data_api/rds.py | 2 + awswrangler/data_api/redshift.py | 2 + awswrangler/dynamodb/_delete.py | 3 + awswrangler/dynamodb/_utils.py | 2 + awswrangler/dynamodb/_write.py | 6 + awswrangler/mysql.py | 15 ++- awswrangler/postgresql.py | 15 ++- awswrangler/redshift.py | 2 +- awswrangler/s3/_read_parquet.py | 2 +- awswrangler/s3/_read_text.py | 6 +- awswrangler/s3/_write.py | 17 --- awswrangler/s3/_write_parquet.py | 10 +- awswrangler/s3/_write_text.py | 12 +- awswrangler/sqlserver.py | 16 ++- docs/source/api.rst | 2 + docs/source/install.rst | 6 +- docs/source/what.rst | 2 +- pyproject.toml | 4 +- test_infra/pyproject.toml | 2 +- tests/test_catalog.py | 4 +- tests/test_metadata.py | 2 +- tests/test_redshift.py | 7 ++ tests/test_s3_text.py | 14 ++- tutorials/001 - Introduction.ipynb | 20 ++-- ...shift, MySQL, PostgreSQL, SQL Server.ipynb | 24 ++-- tutorials/014 - Schema Evolution.ipynb | 4 +- tutorials/021 - Global Configurations.ipynb | 2 +- ...22 - Writing Partitions Concurrently.ipynb | 2 +- .../023 - Flexible Partitions Filter.ipynb | 2 +- tutorials/030 - Data Api.ipynb | 105 ++++++++++++++++++ ...31 - Lake Formation Governed Tables.ipynb} | 2 +- 40 files changed, 337 insertions(+), 134 deletions(-) create mode 100644 tutorials/030 - Data Api.ipynb rename tutorials/{030 - Lake Formation Governed Tables.ipynb => 031 - Lake Formation Governed Tables.ipynb} (99%) diff --git a/.bumpversion.cfg b/.bumpversion.cfg index 5636ff7d4..b60afc641 100644 --- a/.bumpversion.cfg +++ b/.bumpversion.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 2.10.0 +current_version = 2.11.0 commit = False tag = False tag_name = {new_version} diff --git a/CONTRIBUTING_COMMON_ERRORS.md b/CONTRIBUTING_COMMON_ERRORS.md index 92f8aa94d..5d820d28e 100644 --- a/CONTRIBUTING_COMMON_ERRORS.md +++ b/CONTRIBUTING_COMMON_ERRORS.md @@ -13,9 +13,9 @@ Requirement already satisfied: pbr!=2.1.0,>=2.0.0 in ./.venv/lib/python3.7/site- Using legacy 'setup.py install' for python-Levenshtein, since package 'wheel' is not installed. Installing collected packages: awswrangler, python-Levenshtein Attempting uninstall: awswrangler - Found existing installation: awswrangler 2.10.0 - Uninstalling awswrangler-2.10.0: - Successfully uninstalled awswrangler-2.10.0 + Found existing installation: awswrangler 2.11.0 + Uninstalling awswrangler-2.11.0: + Successfully uninstalled awswrangler-2.11.0 Running setup.py develop for awswrangler Running setup.py install for python-Levenshtein ... error ERROR: Command errored out with exit status 1: diff --git a/README.md b/README.md index 22f86e0a0..01b595472 100644 --- a/README.md +++ b/README.md @@ -8,7 +8,7 @@ Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, Clo > An [AWS Professional Service](https://aws.amazon.com/professional-services/) open source initiative | aws-proserve-opensource@amazon.com -[![Release](https://img.shields.io/badge/release-2.10.0-brightgreen.svg)](https://pypi.org/project/awswrangler/) +[![Release](https://img.shields.io/badge/release-2.11.0-brightgreen.svg)](https://pypi.org/project/awswrangler/) [![Python Version](https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8%20%7C%203.9-brightgreen.svg)](https://anaconda.org/conda-forge/awswrangler) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) @@ -23,7 +23,7 @@ Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, Clo | **[PyPi](https://pypi.org/project/awswrangler/)** | [![PyPI Downloads](https://pepy.tech/badge/awswrangler)](https://pypi.org/project/awswrangler/) | `pip install awswrangler` | | **[Conda](https://anaconda.org/conda-forge/awswrangler)** | [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/awswrangler.svg)](https://anaconda.org/conda-forge/awswrangler) | `conda install -c conda-forge awswrangler` | -> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-glue-pyspark-jobs), MWAA):**
+> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-glue-pyspark-jobs), MWAA):**
➡️ `pip install pyarrow==2 awswrangler` Powered By [](https://arrow.apache.org/powered_by/) @@ -42,7 +42,7 @@ Powered By [](http Installation command: `pip install awswrangler` -> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-glue-pyspark-jobs), MWAA):**
+> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-glue-pyspark-jobs), MWAA):**
➡️`pip install pyarrow==2 awswrangler` ```py3 @@ -96,17 +96,17 @@ FROM "sampleDB"."sampleTable" ORDER BY time DESC LIMIT 3 ## [Read The Docs](https://aws-data-wrangler.readthedocs.io/) -- [**What is AWS Data Wrangler?**](https://aws-data-wrangler.readthedocs.io/en/2.10.0/what.html) -- [**Install**](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html) - - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#pypi-pip) - - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#conda) - - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-lambda-layer) - - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-glue-python-shell-jobs) - - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-glue-pyspark-jobs) - - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#amazon-sagemaker-notebook) - - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#amazon-sagemaker-notebook-lifecycle) - - [EMR](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#emr) - - [From source](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#from-source) +- [**What is AWS Data Wrangler?**](https://aws-data-wrangler.readthedocs.io/en/2.11.0/what.html) +- [**Install**](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html) + - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#pypi-pip) + - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#conda) + - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-lambda-layer) + - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-glue-python-shell-jobs) + - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-glue-pyspark-jobs) + - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#amazon-sagemaker-notebook) + - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#amazon-sagemaker-notebook-lifecycle) + - [EMR](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#emr) + - [From source](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#from-source) - [**Tutorials**](https://github.com/awslabs/aws-data-wrangler/tree/main/tutorials) - [001 - Introduction](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/001%20-%20Introduction.ipynb) - [002 - Sessions](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/002%20-%20Sessions.ipynb) @@ -136,22 +136,22 @@ FROM "sampleDB"."sampleTable" ORDER BY time DESC LIMIT 3 - [026 - Amazon Timestream](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/026%20-%20Amazon%20Timestream.ipynb) - [027 - Amazon Timestream 2](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/027%20-%20Amazon%20Timestream%202.ipynb) - [028 - Amazon DynamoDB](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/028%20-%20DynamoDB.ipynb) -- [**API Reference**](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html) - - [Amazon S3](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-s3) - - [AWS Glue Catalog](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#aws-glue-catalog) - - [Amazon Athena](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-athena) - - [Amazon Redshift](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-redshift) - - [PostgreSQL](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#postgresql) - - [MySQL](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#mysql) - - [SQL Server](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#sqlserver) - - [DynamoDB](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#dynamodb) - - [Amazon Timestream](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-timestream) - - [Amazon EMR](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-emr) - - [Amazon CloudWatch Logs](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-cloudwatch-logs) - - [Amazon Chime](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-chime) - - [Amazon QuickSight](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#amazon-quicksight) - - [AWS STS](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#aws-sts) - - [AWS Secrets Manager](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html#aws-secrets-manager) +- [**API Reference**](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html) + - [Amazon S3](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-s3) + - [AWS Glue Catalog](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#aws-glue-catalog) + - [Amazon Athena](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-athena) + - [Amazon Redshift](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-redshift) + - [PostgreSQL](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#postgresql) + - [MySQL](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#mysql) + - [SQL Server](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#sqlserver) + - [DynamoDB](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#dynamodb) + - [Amazon Timestream](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-timestream) + - [Amazon EMR](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-emr) + - [Amazon CloudWatch Logs](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-cloudwatch-logs) + - [Amazon Chime](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-chime) + - [Amazon QuickSight](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-quicksight) + - [AWS STS](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#aws-sts) + - [AWS Secrets Manager](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#aws-secrets-manager) - [**License**](https://github.com/awslabs/aws-data-wrangler/blob/main/LICENSE.txt) - [**Contributing**](https://github.com/awslabs/aws-data-wrangler/blob/main/CONTRIBUTING.md) - [**Legacy Docs** (pre-1.0.0)](https://aws-data-wrangler.readthedocs.io/en/0.3.3/) diff --git a/awswrangler/__metadata__.py b/awswrangler/__metadata__.py index ec682bbe5..4872e3912 100644 --- a/awswrangler/__metadata__.py +++ b/awswrangler/__metadata__.py @@ -7,5 +7,5 @@ __title__: str = "awswrangler" __description__: str = "Pandas on AWS." -__version__: str = "2.10.0" +__version__: str = "2.11.0" __license__: str = "Apache License 2.0" diff --git a/awswrangler/_config.py b/awswrangler/_config.py index b156d42ab..a35f92812 100644 --- a/awswrangler/_config.py +++ b/awswrangler/_config.py @@ -44,6 +44,7 @@ class _ConfigArg(NamedTuple): "kms_endpoint_url": _ConfigArg(dtype=str, nullable=True, enforced=True), "emr_endpoint_url": _ConfigArg(dtype=str, nullable=True, enforced=True), "lakeformation_endpoint_url": _ConfigArg(dtype=str, nullable=True, enforced=True), + "dynamodb_endpoint_url": _ConfigArg(dtype=str, nullable=True, enforced=True), # Botocore config "botocore_config": _ConfigArg(dtype=botocore.config.Config, nullable=True), } @@ -63,6 +64,7 @@ def __init__(self) -> None: self.kms_endpoint_url = None self.emr_endpoint_url = None self.lakeformation_endpoint_url = None + self.dynamodb_endpoint_url = None self.botocore_config = None for name in _CONFIG_ARGS: self._load_config(name=name) @@ -363,6 +365,15 @@ def lakeformation_endpoint_url(self) -> Optional[str]: def lakeformation_endpoint_url(self, value: Optional[str]) -> None: self._set_config_value(key="lakeformation_endpoint_url", value=value) + @property + def dynamodb_endpoint_url(self) -> Optional[str]: + """Property dynamodb_endpoint_url.""" + return cast(Optional[str], self["dynamodb_endpoint_url"]) + + @dynamodb_endpoint_url.setter + def dynamodb_endpoint_url(self, value: Optional[str]) -> None: + self._set_config_value(key="dynamodb_endpoint_url", value=value) + @property def botocore_config(self) -> botocore.config.Config: """Property botocore_config.""" diff --git a/awswrangler/_databases.py b/awswrangler/_databases.py index fb7904c78..21467f2f4 100644 --- a/awswrangler/_databases.py +++ b/awswrangler/_databases.py @@ -143,16 +143,19 @@ def _records2df( array = pa.array(obj=col_values, safe=safe) # Creating Arrow array array = array.cast(target_type=dtype[col_name], safe=safe) # Casting arrays.append(array) - table = pa.Table.from_arrays(arrays=arrays, names=cols_names) # Creating arrow Table - df: pd.DataFrame = table.to_pandas( # Creating Pandas DataFrame - use_threads=True, - split_blocks=True, - self_destruct=True, - integer_object_nulls=False, - date_as_object=True, - types_mapper=_data_types.pyarrow2pandas_extension, - safe=safe, - ) + if not arrays: + df = pd.DataFrame(columns=cols_names) + else: + table = pa.Table.from_arrays(arrays=arrays, names=cols_names) # Creating arrow Table + df = table.to_pandas( # Creating Pandas DataFrame + use_threads=True, + split_blocks=True, + self_destruct=True, + integer_object_nulls=False, + date_as_object=True, + types_mapper=_data_types.pyarrow2pandas_extension, + safe=safe, + ) if index is not None: df.set_index(index, inplace=True) return df diff --git a/awswrangler/_utils.py b/awswrangler/_utils.py index 47580903c..7ad81604b 100644 --- a/awswrangler/_utils.py +++ b/awswrangler/_utils.py @@ -95,6 +95,8 @@ def _get_endpoint_url(service_name: str) -> Optional[str]: endpoint_url = _config.config.emr_endpoint_url elif service_name == "lakeformation" and _config.config.lakeformation_endpoint_url is not None: endpoint_url = _config.config.lakeformation_endpoint_url + elif service_name == "dynamodb" and _config.config.dynamodb_endpoint_url is not None: + endpoint_url = _config.config.dynamodb_endpoint_url return endpoint_url @@ -373,3 +375,21 @@ def block_waiting_available_thread(seq: Sequence[Future], max_workers: int) -> N while len(running) >= max_workers: wait_any_future_available(seq=running) running = get_running_futures(seq=running) + + +def check_schema_changes(columns_types: Dict[str, str], table_input: Optional[Dict[str, Any]], mode: str) -> None: + """Check schema changes.""" + if (table_input is not None) and (mode in ("append", "overwrite_partitions")): + catalog_cols: Dict[str, str] = {x["Name"]: x["Type"] for x in table_input["StorageDescriptor"]["Columns"]} + for c, t in columns_types.items(): + if c not in catalog_cols: + raise exceptions.InvalidArgumentValue( + f"Schema change detected: New column {c} with type {t}. " + "Please pass schema_evolution=True to allow new columns " + "behaviour." + ) + if t != catalog_cols[c]: # Data type change detected! + raise exceptions.InvalidArgumentValue( + f"Schema change detected: Data type change on column {c} " + f"(Old type: {catalog_cols[c]} / New type {t})." + ) diff --git a/awswrangler/athena/_read.py b/awswrangler/athena/_read.py index 1229bba88..cd828ccf8 100644 --- a/awswrangler/athena/_read.py +++ b/awswrangler/athena/_read.py @@ -617,11 +617,11 @@ def read_sql_query( **Related tutorial:** - - `Amazon Athena `_ - - `Athena Cache `_ - - `Global Configurations `_ **There are two approaches to be defined through ctas_approach parameter:** @@ -669,7 +669,7 @@ def read_sql_query( /athena.html#Athena.Client.get_query_execution>`_ . For a practical example check out the - `related tutorial `_! @@ -890,11 +890,11 @@ def read_sql_table( **Related tutorial:** - - `Amazon Athena `_ - - `Athena Cache `_ - - `Global Configurations `_ **There are two approaches to be defined through ctas_approach parameter:** @@ -939,7 +939,7 @@ def read_sql_table( /athena.html#Athena.Client.get_query_execution>`_ . For a practical example check out the - `related tutorial `_! diff --git a/awswrangler/catalog/_create.py b/awswrangler/catalog/_create.py index 0418c2868..5211171c3 100644 --- a/awswrangler/catalog/_create.py +++ b/awswrangler/catalog/_create.py @@ -326,6 +326,7 @@ def _create_csv_table( # pylint: disable=too-many-arguments,too-many-locals mode: str, transaction_id: Optional[str], catalog_versioning: bool, + schema_evolution: bool, sep: str, skip_header_line_count: Optional[int], serde_library: Optional[str], @@ -344,15 +345,10 @@ def _create_csv_table( # pylint: disable=too-many-arguments,too-many-locals partitions_types = {} if partitions_types is None else partitions_types _logger.debug("catalog_table_input: %s", catalog_table_input) table_input: Dict[str, Any] + if schema_evolution is False: + _utils.check_schema_changes(columns_types=columns_types, table_input=catalog_table_input, mode=mode) if (catalog_table_input is not None) and (mode in ("append", "overwrite_partitions")): table_input = catalog_table_input - catalog_cols: Dict[str, str] = {x["Name"]: x["Type"] for x in table_input["StorageDescriptor"]["Columns"]} - for c, t in columns_types.items(): - if c not in catalog_cols: - _logger.debug("New column %s with type %s.", c, t) - raise exceptions.InvalidArgumentValue( - f"Schema change detected - New column {c}. Schema evolution is not supported for CSV tables." - ) else: table_input = _csv_table_definition( table=table, @@ -724,6 +720,7 @@ def create_csv_table( # pylint: disable=too-many-arguments columns_comments: Optional[Dict[str, str]] = None, mode: str = "overwrite", catalog_versioning: bool = False, + schema_evolution: bool = False, sep: str = ",", skip_header_line_count: Optional[int] = None, serde_library: Optional[str] = None, @@ -772,6 +769,11 @@ def create_csv_table( # pylint: disable=too-many-arguments 'overwrite' to recreate any possible axisting table or 'append' to keep any possible axisting table. catalog_versioning : bool If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. + schema_evolution : bool + If True allows schema evolution (new or missing columns), otherwise a exception will be raised. + (Only considered if dataset=True and mode in ("append", "overwrite_partitions")) + Related tutorial: + https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/014%20-%20Schema%20Evolution.html sep : str String of length 1. Field delimiter for the output file. skip_header_line_count : Optional[int] @@ -855,6 +857,7 @@ def create_csv_table( # pylint: disable=too-many-arguments mode=mode, catalog_versioning=catalog_versioning, transaction_id=transaction_id, + schema_evolution=schema_evolution, projection_enabled=projection_enabled, projection_types=projection_types, projection_ranges=projection_ranges, diff --git a/awswrangler/data_api/rds.py b/awswrangler/data_api/rds.py index 71b34be51..e95dc5692 100644 --- a/awswrangler/data_api/rds.py +++ b/awswrangler/data_api/rds.py @@ -139,6 +139,8 @@ def read_sql_query(sql: str, con: RdsDataApi, database: Optional[str] = None) -> ---------- sql: str SQL query to run. + con: RdsDataApi + A RdsDataApi connection instance database: str Database to run query on - defaults to the database specified by `con`. diff --git a/awswrangler/data_api/redshift.py b/awswrangler/data_api/redshift.py index d3947d91d..a6a5cc3a8 100644 --- a/awswrangler/data_api/redshift.py +++ b/awswrangler/data_api/redshift.py @@ -189,6 +189,8 @@ def read_sql_query(sql: str, con: RedshiftDataApi, database: Optional[str] = Non ---------- sql: str SQL query to run. + con: RedshiftDataApi + A RedshiftDataApi connection instance database: str Database to run query on - defaults to the database specified by `con`. diff --git a/awswrangler/dynamodb/_delete.py b/awswrangler/dynamodb/_delete.py index 76003bacf..0789b653d 100644 --- a/awswrangler/dynamodb/_delete.py +++ b/awswrangler/dynamodb/_delete.py @@ -5,11 +5,14 @@ import boto3 +from awswrangler._config import apply_configs + from ._utils import _validate_items, get_table _logger: logging.Logger = logging.getLogger(__name__) +@apply_configs def delete_items( items: List[Dict[str, Any]], table_name: str, diff --git a/awswrangler/dynamodb/_utils.py b/awswrangler/dynamodb/_utils.py index fbe4b7bbd..24858694f 100644 --- a/awswrangler/dynamodb/_utils.py +++ b/awswrangler/dynamodb/_utils.py @@ -5,8 +5,10 @@ import boto3 from awswrangler import _utils, exceptions +from awswrangler._config import apply_configs +@apply_configs def get_table( table_name: str, boto3_session: Optional[boto3.Session] = None, diff --git a/awswrangler/dynamodb/_write.py b/awswrangler/dynamodb/_write.py index 7068f93a3..3a900de0a 100644 --- a/awswrangler/dynamodb/_write.py +++ b/awswrangler/dynamodb/_write.py @@ -8,11 +8,14 @@ import boto3 import pandas as pd +from awswrangler._config import apply_configs + from ._utils import _validate_items, get_table _logger: logging.Logger = logging.getLogger(__name__) +@apply_configs def put_json( path: Union[str, Path], table_name: str, @@ -56,6 +59,7 @@ def put_json( put_items(items=items, table_name=table_name, boto3_session=boto3_session) +@apply_configs def put_csv( path: Union[str, Path], table_name: str, @@ -109,6 +113,7 @@ def put_csv( put_df(df=df, table_name=table_name, boto3_session=boto3_session) +@apply_configs def put_df( df: pd.DataFrame, table_name: str, @@ -146,6 +151,7 @@ def put_df( put_items(items=items, table_name=table_name, boto3_session=boto3_session) +@apply_configs def put_items( items: Union[List[Dict[str, Any]], List[Mapping[str, Any]]], table_name: str, diff --git a/awswrangler/mysql.py b/awswrangler/mysql.py index fefe2c801..2f5c2cc74 100644 --- a/awswrangler/mysql.py +++ b/awswrangler/mysql.py @@ -82,6 +82,19 @@ def connect( https://pymysql.readthedocs.io + Note + ---- + You MUST pass a `connection` OR `secret_id`. + Here is an example of the secret structure in Secrets Manager: + { + "host":"mysql-instance-wrangler.dr8vkeyrb9m1.us-east-1.rds.amazonaws.com", + "username":"test", + "password":"test", + "engine":"mysql", + "port":"3306", + "dbname": "mydb" # Optional + } + Note ---- It is only possible to configure SSL using Glue Catalog Connection. More at: @@ -92,7 +105,7 @@ def connect( connection : str Glue Catalog Connection name. secret_id: Optional[str]: - Specifies the secret containing the version that you want to retrieve. + Specifies the secret containing the connection details that you want to retrieve. You can specify either the Amazon Resource Name (ARN) or the friendly name of the secret. catalog_id : str, optional The ID of the Data Catalog. diff --git a/awswrangler/postgresql.py b/awswrangler/postgresql.py index bc51ece20..181907065 100644 --- a/awswrangler/postgresql.py +++ b/awswrangler/postgresql.py @@ -86,12 +86,25 @@ def connect( https://github.com/tlocke/pg8000 + Note + ---- + You MUST pass a `connection` OR `secret_id`. + Here is an example of the secret structure in Secrets Manager: + { + "host":"postgresql-instance-wrangler.dr8vkeyrb9m1.us-east-1.rds.amazonaws.com", + "username":"test", + "password":"test", + "engine":"postgresql", + "port":"3306", + "dbname": "mydb" # Optional + } + Parameters ---------- connection : Optional[str] Glue Catalog Connection name. secret_id: Optional[str]: - Specifies the secret containing the version that you want to retrieve. + Specifies the secret containing the connection details that you want to retrieve. You can specify either the Amazon Resource Name (ARN) or the friendly name of the secret. catalog_id : str, optional The ID of the Data Catalog. diff --git a/awswrangler/redshift.py b/awswrangler/redshift.py index b4e55eadd..49c299fba 100644 --- a/awswrangler/redshift.py +++ b/awswrangler/redshift.py @@ -398,7 +398,7 @@ def connect( connection : Optional[str] Glue Catalog Connection name. secret_id: Optional[str]: - Specifies the secret containing the version that you want to retrieve. + Specifies the secret containing the connection details that you want to retrieve. You can specify either the Amazon Resource Name (ARN) or the friendly name of the secret. catalog_id : str, optional The ID of the Data Catalog. diff --git a/awswrangler/s3/_read_parquet.py b/awswrangler/s3/_read_parquet.py index 660363a52..6b4ba0c54 100644 --- a/awswrangler/s3/_read_parquet.py +++ b/awswrangler/s3/_read_parquet.py @@ -788,7 +788,7 @@ def read_parquet_table( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html columns : List[str], optional Names of columns to read from the file(s). validate_schema: diff --git a/awswrangler/s3/_read_text.py b/awswrangler/s3/_read_text.py index c6b4e9042..a51dd4ed6 100644 --- a/awswrangler/s3/_read_text.py +++ b/awswrangler/s3/_read_text.py @@ -241,7 +241,7 @@ def read_csv( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html pandas_kwargs : KEYWORD arguments forwarded to pandas.read_csv(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. @@ -389,7 +389,7 @@ def read_fwf( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html pandas_kwargs: KEYWORD arguments forwarded to pandas.read_fwf(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. @@ -541,7 +541,7 @@ def read_json( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html pandas_kwargs: KEYWORD arguments forwarded to pandas.read_json(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. diff --git a/awswrangler/s3/_write.py b/awswrangler/s3/_write.py index 9867c3312..9af8d5956 100644 --- a/awswrangler/s3/_write.py +++ b/awswrangler/s3/_write.py @@ -99,20 +99,3 @@ def _sanitize( dtype = {catalog.sanitize_column_name(k): v.lower() for k, v in dtype.items()} _utils.check_duplicated_columns(df=df) return df, dtype, partition_cols - - -def _check_schema_changes(columns_types: Dict[str, str], table_input: Optional[Dict[str, Any]], mode: str) -> None: - if (table_input is not None) and (mode in ("append", "overwrite_partitions")): - catalog_cols: Dict[str, str] = {x["Name"]: x["Type"] for x in table_input["StorageDescriptor"]["Columns"]} - for c, t in columns_types.items(): - if c not in catalog_cols: - raise exceptions.InvalidArgumentValue( - f"Schema change detected: New column {c} with type {t}. " - "Please pass schema_evolution=True to allow new columns " - "behaviour." - ) - if t != catalog_cols[c]: # Data type change detected! - raise exceptions.InvalidArgumentValue( - f"Schema change detected: Data type change on column {c} " - f"(Old type: {catalog_cols[c]} / New type {t})." - ) diff --git a/awswrangler/s3/_write_parquet.py b/awswrangler/s3/_write_parquet.py index f1f327b11..f0c0c4ac0 100644 --- a/awswrangler/s3/_write_parquet.py +++ b/awswrangler/s3/_write_parquet.py @@ -17,7 +17,7 @@ from awswrangler.s3._delete import delete_objects from awswrangler.s3._fs import open_s3_object from awswrangler.s3._read_parquet import _read_parquet_metadata -from awswrangler.s3._write import _COMPRESSION_2_EXT, _apply_dtype, _check_schema_changes, _sanitize, _validate_args +from awswrangler.s3._write import _COMPRESSION_2_EXT, _apply_dtype, _sanitize, _validate_args from awswrangler.s3._write_concurrent import _WriteProxy from awswrangler.s3._write_dataset import _to_dataset @@ -281,18 +281,18 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b concurrent_partitioning: bool If True will increase the parallelism level during the partitions writing. It will decrease the writing time and increase the memory usage. - https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html + https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html mode: str, optional ``append`` (Default), ``overwrite``, ``overwrite_partitions``. Only takes effect if dataset=True. For details check the related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet + https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet catalog_versioning : bool If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. schema_evolution : bool If True allows schema evolution (new or missing columns), otherwise a exception will be raised. (Only considered if dataset=True and mode in ("append", "overwrite_partitions")) Related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/014%20-%20Schema%20Evolution.html + https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/014%20-%20Schema%20Evolution.html database : str, optional Glue/Athena catalog: Database name. table : str, optional @@ -580,7 +580,7 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b df=df, index=index, partition_cols=partition_cols, dtype=dtype ) if schema_evolution is False: - _check_schema_changes(columns_types=columns_types, table_input=catalog_table_input, mode=mode) + _utils.check_schema_changes(columns_types=columns_types, table_input=catalog_table_input, mode=mode) if (catalog_table_input is None) and (table_type == "GOVERNED"): catalog._create_parquet_table( # pylint: disable=protected-access database=database, diff --git a/awswrangler/s3/_write_text.py b/awswrangler/s3/_write_text.py index fc1e15eaf..1c0e0ebea 100644 --- a/awswrangler/s3/_write_text.py +++ b/awswrangler/s3/_write_text.py @@ -14,7 +14,7 @@ from awswrangler._config import apply_configs from awswrangler.s3._delete import delete_objects from awswrangler.s3._fs import open_s3_object -from awswrangler.s3._write import _COMPRESSION_2_EXT, _apply_dtype, _check_schema_changes, _sanitize, _validate_args +from awswrangler.s3._write import _COMPRESSION_2_EXT, _apply_dtype, _sanitize, _validate_args from awswrangler.s3._write_dataset import _to_dataset _logger: logging.Logger = logging.getLogger(__name__) @@ -176,18 +176,18 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state concurrent_partitioning: bool If True will increase the parallelism level during the partitions writing. It will decrease the writing time and increase the memory usage. - https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html + https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html mode : str, optional ``append`` (Default), ``overwrite``, ``overwrite_partitions``. Only takes effect if dataset=True. For details check the related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet + https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet catalog_versioning : bool If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. schema_evolution : bool If True allows schema evolution (new or missing columns), otherwise a exception will be raised. (Only considered if dataset=True and mode in ("append", "overwrite_partitions")) Related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.10.0/tutorials/014%20-%20Schema%20Evolution.html + https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/014%20-%20Schema%20Evolution.html database : str, optional Glue/Athena catalog: Database name. table : str, optional @@ -526,7 +526,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state df=df, index=index, partition_cols=partition_cols, dtype=dtype, index_left=True ) if schema_evolution is False: - _check_schema_changes(columns_types=columns_types, table_input=catalog_table_input, mode=mode) + _utils.check_schema_changes(columns_types=columns_types, table_input=catalog_table_input, mode=mode) if (catalog_table_input is None) and (table_type == "GOVERNED"): catalog._create_csv_table( # pylint: disable=protected-access @@ -543,6 +543,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state boto3_session=session, mode=mode, transaction_id=transaction_id, + schema_evolution=schema_evolution, catalog_versioning=catalog_versioning, sep=sep, projection_enabled=projection_enabled, @@ -616,6 +617,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state mode=mode, transaction_id=transaction_id, catalog_versioning=catalog_versioning, + schema_evolution=schema_evolution, sep=sep, projection_enabled=projection_enabled, projection_types=projection_types, diff --git a/awswrangler/sqlserver.py b/awswrangler/sqlserver.py index bbacb5d6a..7c02628b6 100644 --- a/awswrangler/sqlserver.py +++ b/awswrangler/sqlserver.py @@ -113,12 +113,25 @@ def connect( https://github.com/mkleehammer/pyodbc + Note + ---- + You MUST pass a `connection` OR `secret_id`. + Here is an example of the secret structure in Secrets Manager: + { + "host":"sqlserver-instance-wrangler.dr8vkeyrb9m1.us-east-1.rds.amazonaws.com", + "username":"test", + "password":"test", + "engine":"sqlserver", + "port":"1433", + "dbname": "mydb" # Optional + } + Parameters ---------- connection : Optional[str] Glue Catalog Connection name. secret_id: Optional[str]: - Specifies the secret containing the version that you want to retrieve. + Specifies the secret containing the connection details that you want to retrieve. You can specify either the Amazon Resource Name (ARN) or the friendly name of the secret. catalog_id : str, optional The ID of the Data Catalog. @@ -209,6 +222,7 @@ def read_sql_query( Examples -------- Reading from Microsoft SQL Server using a Glue Catalog Connections + >>> import awswrangler as wr >>> con = wr.sqlserver.connect(connection="MY_GLUE_CONNECTION", odbc_driver_version=17) >>> df = wr.sqlserver.read_sql_query( diff --git a/docs/source/api.rst b/docs/source/api.rst index b9b7b12aa..f6362a25c 100644 --- a/docs/source/api.rst +++ b/docs/source/api.rst @@ -201,6 +201,7 @@ Data API Redshift .. autosummary:: :toctree: stubs + RedshiftDataApi connect read_sql_query @@ -212,6 +213,7 @@ Data API RDS .. autosummary:: :toctree: stubs + RdsDataApi connect read_sql_query diff --git a/docs/source/install.rst b/docs/source/install.rst index d846a6c9b..d71bda417 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -62,7 +62,7 @@ Go to your Glue PySpark job and create a new *Job parameters* key/value: To install a specific version, set the value for above Job parameter as follows: -* Value: ``pyarrow==2,awswrangler==2.10.0`` +* Value: ``cython==0.29.21,pg8000==1.21.0,pyarrow==2,pandas==1.3.0,awswrangler==2.11.0`` .. note:: Pyarrow 3 is not currently supported in Glue PySpark Jobs, which is why a previous installation of pyarrow 2 is required. @@ -95,7 +95,7 @@ Here is an example of how to reference the Lambda layer in your CDK app: "wrangler-bucket", bucket_arn="arn:aws:s3:::aws-data-wrangler-public-artifacts", ), - key="releases/2.10.0/awswrangler-layer-2.10.0-py3.8.zip", + key="releases/2.11.0/awswrangler-layer-2.11.0-py3.8.zip", ), layer_version_name="aws-data-wrangler" ) @@ -190,7 +190,7 @@ complement Big Data pipelines. sudo pip install pyarrow==2 awswrangler .. note:: Make sure to freeze the Wrangler version in the bootstrap for productive - environments (e.g. awswrangler==2.10.0) + environments (e.g. awswrangler==2.11.0) .. note:: Pyarrow 3 is not currently supported in the default EMR image, which is why a previous installation of pyarrow 2 is required. diff --git a/docs/source/what.rst b/docs/source/what.rst index 12e6995bd..d1b741f96 100644 --- a/docs/source/what.rst +++ b/docs/source/what.rst @@ -8,4 +8,4 @@ SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL Built on top of other open-source projects like `Pandas `_, `Apache Arrow `_ and `Boto3 `_, it offers abstracted functions to execute usual ETL tasks like load/unload data from **Data Lakes**, **Data Warehouses** and **Databases**. -Check our `tutorials `_ or the `list of functionalities `_. \ No newline at end of file +Check our `tutorials `_ or the `list of functionalities `_. \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index 5635d65d5..4372928d2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "awswrangler" -version = "2.10.0" +version = "2.11.0" description = "Pandas on AWS." authors = ["Igor Tavares"] license = "Apache License 2.0" @@ -85,7 +85,7 @@ build-backend = "poetry.core.masonry.api" [tool.black] line-length = 120 target-version = ["py36", "py37", "py38", "py39"] -exclude = ''' +extend_exclude = ''' /( \.eggs | \.git diff --git a/test_infra/pyproject.toml b/test_infra/pyproject.toml index 5b0f7191f..e6dda67cb 100644 --- a/test_infra/pyproject.toml +++ b/test_infra/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "awswrangler - test infrastructure" -version = "2.10.0" +version = "2.11.0" description = "CDK test infrastructure for AWS" authors = ["Igor Tavares"] license = "Apache License 2.0" diff --git a/tests/test_catalog.py b/tests/test_catalog.py index 5b41642ad..0940bf468 100644 --- a/tests/test_catalog.py +++ b/tests/test_catalog.py @@ -292,7 +292,7 @@ def test_catalog_versioning(path, glue_database, glue_table, glue_table2): assert len(df.columns) == 1 assert str(df.c1.dtype).startswith("float") - # Version 1 - CSV (No evolution) + # Version 1 - CSV df = pd.DataFrame({"c1": [True, False]}) wr.s3.to_csv( df=df, @@ -302,6 +302,7 @@ def test_catalog_versioning(path, glue_database, glue_table, glue_table2): table=glue_table2, mode="overwrite", catalog_versioning=False, + schema_evolution=True, index=False, ) assert wr.catalog.get_table_number_of_versions(table=glue_table2, database=glue_database) == 1 @@ -320,6 +321,7 @@ def test_catalog_versioning(path, glue_database, glue_table, glue_table2): table=glue_table2, mode="overwrite", catalog_versioning=True, + schema_evolution=True, index=False, ) assert wr.catalog.get_table_number_of_versions(table=glue_table2, database=glue_database) == 2 diff --git a/tests/test_metadata.py b/tests/test_metadata.py index d63273380..4031f5a86 100644 --- a/tests/test_metadata.py +++ b/tests/test_metadata.py @@ -2,7 +2,7 @@ def test_metadata(): - assert wr.__version__ == "2.10.0" + assert wr.__version__ == "2.11.0" assert wr.__title__ == "awswrangler" assert wr.__description__ == "Pandas on AWS." assert wr.__license__ == "Apache License 2.0" diff --git a/tests/test_redshift.py b/tests/test_redshift.py index ef45e53d6..41b6c0d7b 100644 --- a/tests/test_redshift.py +++ b/tests/test_redshift.py @@ -48,6 +48,13 @@ def test_to_sql_simple(redshift_table, redshift_con, overwrite_method): wr.redshift.to_sql(df, redshift_con, redshift_table, "public", "overwrite", overwrite_method, True) +def test_empty_table(redshift_table, redshift_con): + with redshift_con.cursor() as cursor: + cursor.execute(f"CREATE TABLE public.{redshift_table}(c0 integer not null, c1 integer, primary key(c0));") + df = wr.redshift.read_sql_table(table=redshift_table, con=redshift_con, schema="public") + assert df.columns.values.tolist() == ["c0", "c1"] + + def test_sql_types(redshift_table, redshift_con): table = redshift_table df = get_df() diff --git a/tests/test_s3_text.py b/tests/test_s3_text.py index 18dcc7ad2..65243ffe0 100644 --- a/tests/test_s3_text.py +++ b/tests/test_s3_text.py @@ -337,8 +337,18 @@ def test_to_csv_schema_evolution(path, glue_database, glue_table) -> None: path_file = f"{path}0.csv" df = pd.DataFrame({"c0": [0, 1, 2], "c1": [3, 4, 5]}) wr.s3.to_csv(df=df, path=path_file, dataset=True, database=glue_database, table=glue_table) - df["test"] = 1 + df["c2"] = [6, 7, 8] + wr.s3.to_csv( + df=df, + path=path_file, + dataset=True, + database=glue_database, + table=glue_table, + mode="overwrite", + schema_evolution=True, + ) + df["c3"] = [9, 10, 11] with pytest.raises(wr.exceptions.InvalidArgumentValue): wr.s3.to_csv( - df=df, path=path_file, dataset=True, database=glue_database, table=glue_table, schema_evolution=True + df=df, path=path_file, dataset=True, database=glue_database, table=glue_table, schema_evolution=False ) diff --git a/tutorials/001 - Introduction.ipynb b/tutorials/001 - Introduction.ipynb index bf5a9be54..2ef8932cf 100644 --- a/tutorials/001 - Introduction.ipynb +++ b/tutorials/001 - Introduction.ipynb @@ -19,7 +19,7 @@ "\n", "Built on top of other open-source projects like [Pandas](https://github.com/pandas-dev/pandas), [Apache Arrow](https://github.com/apache/arrow) and [Boto3](https://github.com/boto/boto3), it offers abstracted functions to execute usual ETL tasks like load/unload data from **Data Lakes**, **Data Warehouses** and **Databases**.\n", "\n", - "Check our [list of functionalities](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html)." + "Check our [list of functionalities](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html)." ] }, { @@ -30,15 +30,15 @@ "\n", "The Wrangler runs almost anywhere over Python 3.6, 3.7, 3.8 and 3.9, so there are several different ways to install it in the desired enviroment.\n", "\n", - " - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#pypi-pip)\n", - " - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#conda)\n", - " - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-lambda-layer)\n", - " - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-glue-python-shell-jobs)\n", - " - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#aws-glue-pyspark-jobs)\n", - " - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#amazon-sagemaker-notebook)\n", - " - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#amazon-sagemaker-notebook-lifecycle)\n", - " - [EMR Cluster](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#emr-cluster)\n", - " - [From source](https://aws-data-wrangler.readthedocs.io/en/2.10.0/install.html#from-source)\n", + " - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#pypi-pip)\n", + " - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#conda)\n", + " - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-lambda-layer)\n", + " - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-glue-python-shell-jobs)\n", + " - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-glue-pyspark-jobs)\n", + " - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#amazon-sagemaker-notebook)\n", + " - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#amazon-sagemaker-notebook-lifecycle)\n", + " - [EMR Cluster](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#emr-cluster)\n", + " - [From source](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#from-source)\n", "\n", "Some good practices for most of the above methods are:\n", " - Use new and individual Virtual Environments for each project ([venv](https://docs.python.org/3/library/venv.html))\n", diff --git a/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb b/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb index fdd15458a..41797521f 100644 --- a/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb +++ b/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb @@ -10,14 +10,14 @@ "\n", "[Wrangler](https://github.com/awslabs/aws-data-wrangler)'s Redshift, MySQL and PostgreSQL have two basic function in common that tries to follow the Pandas conventions, but add more data type consistency.\n", "\n", - "- [wr.redshift.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.redshift.to_sql.html)\n", - "- [wr.redshift.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.redshift.read_sql_query.html)\n", - "- [wr.mysql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.mysql.to_sql.html)\n", - "- [wr.mysql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.mysql.read_sql_query.html)\n", - "- [wr.postgresql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.postgresql.to_sql.html)\n", - "- [wr.postgresql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.postgresql.read_sql_query.html)\n", - "- [wr.sqlserver.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.sqlserver.to_sql.html)\n", - "- [wr.sqlserver.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.sqlserver.read_sql_query.html)" + "- [wr.redshift.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.redshift.to_sql.html)\n", + "- [wr.redshift.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.redshift.read_sql_query.html)\n", + "- [wr.mysql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.mysql.to_sql.html)\n", + "- [wr.mysql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.mysql.read_sql_query.html)\n", + "- [wr.postgresql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.postgresql.to_sql.html)\n", + "- [wr.postgresql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.postgresql.read_sql_query.html)\n", + "- [wr.sqlserver.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.sqlserver.to_sql.html)\n", + "- [wr.sqlserver.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.sqlserver.read_sql_query.html)" ] }, { @@ -41,10 +41,10 @@ "source": [ "## Connect using the Glue Catalog Connections\n", "\n", - "- [wr.redshift.connect()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.redshift.connect.html)\n", - "- [wr.mysql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.mysql.connect.html)\n", - "- [wr.postgresql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.postgresql.connect.html)\n", - "- [wr.sqlserver.connect()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.sqlserver.connect.html)" + "- [wr.redshift.connect()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.redshift.connect.html)\n", + "- [wr.mysql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.mysql.connect.html)\n", + "- [wr.postgresql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.postgresql.connect.html)\n", + "- [wr.sqlserver.connect()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.sqlserver.connect.html)" ] }, { diff --git a/tutorials/014 - Schema Evolution.ipynb b/tutorials/014 - Schema Evolution.ipynb index d3dcff769..a48b202cb 100644 --- a/tutorials/014 - Schema Evolution.ipynb +++ b/tutorials/014 - Schema Evolution.ipynb @@ -10,8 +10,8 @@ "\n", "Wrangler support new **columns** on Parquet Dataset through:\n", "\n", - "- [wr.s3.to_parquet()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet)\n", - "- [wr.s3.store_parquet_metadata()](https://aws-data-wrangler.readthedocs.io/en/2.10.0/stubs/awswrangler.s3.store_parquet_metadata.html#awswrangler.s3.store_parquet_metadata) i.e. \"Crawler\"" + "- [wr.s3.to_parquet()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet)\n", + "- [wr.s3.store_parquet_metadata()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.s3.store_parquet_metadata.html#awswrangler.s3.store_parquet_metadata) i.e. \"Crawler\"" ] }, { diff --git a/tutorials/021 - Global Configurations.ipynb b/tutorials/021 - Global Configurations.ipynb index b990873c7..39615e993 100644 --- a/tutorials/021 - Global Configurations.ipynb +++ b/tutorials/021 - Global Configurations.ipynb @@ -13,7 +13,7 @@ "- **Environment variables**\n", "- **wr.config**\n", "\n", - "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html) to see if your function has some argument that can be configured through Global configurations.*\n", + "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html) to see if your function has some argument that can be configured through Global configurations.*\n", "\n", "*P.P.S. One exception to the above mentioned rules is the `botocore_config` property. It cannot be set through environment variables\n", "but only via `wr.config`. It will be used as the `botocore.config.Config` for all underlying `boto3` calls.\n", diff --git a/tutorials/022 - Writing Partitions Concurrently.ipynb b/tutorials/022 - Writing Partitions Concurrently.ipynb index 3f4f1d127..ecd861ec2 100644 --- a/tutorials/022 - Writing Partitions Concurrently.ipynb +++ b/tutorials/022 - Writing Partitions Concurrently.ipynb @@ -13,7 +13,7 @@ " If True will increase the parallelism level during the partitions writing. It will decrease the\n", " writing time and increase the memory usage.\n", "\n", - "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html) to see it has some argument that can be configured through Global configurations.*" + "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html) to see it has some argument that can be configured through Global configurations.*" ] }, { diff --git a/tutorials/023 - Flexible Partitions Filter.ipynb b/tutorials/023 - Flexible Partitions Filter.ipynb index d162c9656..c1c54377d 100644 --- a/tutorials/023 - Flexible Partitions Filter.ipynb +++ b/tutorials/023 - Flexible Partitions Filter.ipynb @@ -16,7 +16,7 @@ " - Ignored if `dataset=False`.\n", " \n", "\n", - "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.10.0/api.html) to see it has some argument that can be configured through Global configurations.*" + "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html) to see it has some argument that can be configured through Global configurations.*" ] }, { diff --git a/tutorials/030 - Data Api.ipynb b/tutorials/030 - Data Api.ipynb new file mode 100644 index 000000000..ed8cceaf2 --- /dev/null +++ b/tutorials/030 - Data Api.ipynb @@ -0,0 +1,105 @@ +{ + "metadata": { + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + }, + "orig_nbformat": 2, + "kernelspec": { + "name": "pythonjvsc74a57bd0e4beff3b9c91951bd870e0e6d1ba9dfdd106cfe45c6f3d0f8d31550063fd3386", + "display_name": "Python 3.7.7 64-bit ('.env': venv)" + }, + "metadata": { + "interpreter": { + "hash": "e4beff3b9c91951bd870e0e6d1ba9dfdd106cfe45c6f3d0f8d31550063fd3386" + } + } + }, + "nbformat": 4, + "nbformat_minor": 2, + "cells": [ + { + "cell_type": "markdown", + "source": [ + "[![AWS Data Wrangler](_static/logo.png \"AWS Data Wrangler\")](https://github.com/awslabs/aws-data-wrangler)" + ], + "metadata": {} + }, + { + "cell_type": "markdown", + "source": [ + "# 30 - Data Api" + ], + "metadata": {} + }, + { + "cell_type": "markdown", + "source": [ + "The Data Api simplifies access to Amazon Redshift and RDS by removing the need to manage database connections and credentials. Instead, you can execute SQL commands to an Amazon Redshift cluster or Amazon Aurora cluster by simply invoking an HTTPS API endpoint provided by the Data API. It takes care of managing database connections and returning data. Since the Data API leverages IAM user credentials or database credentials stored in AWS Secrets Manager, you don’t need to pass credentials in API calls." + ], + "metadata": {} + }, + { + "cell_type": "markdown", + "source": [ + "## Connect to the cluster\n", + "- [wr.data_api.redshift.connect()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.data_api.redshift.connect.html)\n", + "- [wr.data_api.rds.connect()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.data_api.rds.connect.html)" + ], + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": null, + "source": [ + "con_redshift = wr.data_api.redshift.connect(\n", + " cluster_id=\"aws-data-wrangler-1xn5lqxrdxrv3\",\n", + " database=\"test_redshift\",\n", + " secret_arn=\"arn:aws:secretsmanager:us-east-1:111111111111:secret:aws-data-wrangler/redshift-ewn43d\"\n", + ")\n", + "\n", + "con_mysql = wr.data_api.rds.connect(\n", + " cluster_id=\"arn:aws:rds:us-east-1:111111111111:cluster:mysql-serverless-cluster-wrangler\",\n", + " database=\"test_rds\",\n", + " secret_arn=\"arn:aws:secretsmanager:us-east-1:111111111111:secret:aws-data-wrangler/mysql-23df3\"\n", + ")" + ], + "outputs": [], + "metadata": {} + }, + { + "cell_type": "markdown", + "source": [ + "## Read from database\n", + "- [wr.data_api.redshift.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.data_api.redshift.read_sql_query.html)\n", + "- [wr.data_api.rds.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.data_api.rds.read_sql_query.html)" + ], + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": null, + "source": [ + "df = wr.data_api.redshift.read_sql_query(\n", + " sql=\"SELECT * FROM public.test_table\",\n", + " con=con_redshift,\n", + ")\n", + "\n", + "df = wr.data_api.rds.read_sql_query(\n", + " sql=\"SELECT * FROM test.test_table\",\n", + " con=con_rds,\n", + ")" + ], + "outputs": [], + "metadata": {} + } + ] +} \ No newline at end of file diff --git a/tutorials/030 - Lake Formation Governed Tables.ipynb b/tutorials/031 - Lake Formation Governed Tables.ipynb similarity index 99% rename from tutorials/030 - Lake Formation Governed Tables.ipynb rename to tutorials/031 - Lake Formation Governed Tables.ipynb index 3cb56f80d..a3d3f28c6 100644 --- a/tutorials/030 - Lake Formation Governed Tables.ipynb +++ b/tutorials/031 - Lake Formation Governed Tables.ipynb @@ -36,7 +36,7 @@ { "cell_type": "markdown", "source": [ - "# 30 - AWS Lake Formation - Glue Governed tables" + "# 31 - AWS Lake Formation - Glue Governed tables" ], "metadata": {} }, From e5c6fa38c68258d4f47aa21f08a839fdb915418c Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Wed, 8 Sep 2021 16:46:14 +0100 Subject: [PATCH 20/36] Minor - Sync with main --- awswrangler/emr.py | 2 ++ awswrangler/redshift.py | 4 ++-- awswrangler/s3/_write_parquet.py | 1 + 3 files changed, 5 insertions(+), 2 deletions(-) diff --git a/awswrangler/emr.py b/awswrangler/emr.py index a8e5e84ee..9b4f082ce 100644 --- a/awswrangler/emr.py +++ b/awswrangler/emr.py @@ -127,6 +127,7 @@ def _build_cluster_args(**pars: Any) -> Dict[str, Any]: # pylint: disable=too-m "Ec2SubnetId": pars["subnet_id"], "InstanceFleets": [], }, + "StepConcurrencyLevel": pars["step_concurrency_level"], } # EC2 Key Pair @@ -441,6 +442,7 @@ def create_cluster( # pylint: disable=too-many-arguments,too-many-locals,unused custom_classifications: Optional[List[Dict[str, Any]]] = None, maximize_resource_allocation: bool = False, steps: Optional[List[Dict[str, Any]]] = None, + step_concurrency_level: int = 1, keep_cluster_alive_when_no_steps: bool = True, termination_protected: bool = False, tags: Optional[Dict[str, str]] = None, diff --git a/awswrangler/redshift.py b/awswrangler/redshift.py index 49c299fba..2c99d5171 100644 --- a/awswrangler/redshift.py +++ b/awswrangler/redshift.py @@ -1265,7 +1265,7 @@ def copy_from_files( # pylint: disable=too-many-locals,too-many-arguments -------- >>> import awswrangler as wr >>> con = wr.redshift.connect("MY_GLUE_CONNECTION") - >>> wr.db.copy_from_files( + >>> wr.redshift.copy_from_files( ... path="s3://bucket/my_parquet_files/", ... con=con, ... table="my_table", @@ -1467,7 +1467,7 @@ def copy( # pylint: disable=too-many-arguments >>> import awswrangler as wr >>> import pandas as pd >>> con = wr.redshift.connect("MY_GLUE_CONNECTION") - >>> wr.db.copy( + >>> wr.redshift.copy( ... df=pd.DataFrame({'col': [1, 2, 3]}), ... path="s3://bucket/my_parquet_files/", ... con=con, diff --git a/awswrangler/s3/_write_parquet.py b/awswrangler/s3/_write_parquet.py index f0c0c4ac0..6d5027275 100644 --- a/awswrangler/s3/_write_parquet.py +++ b/awswrangler/s3/_write_parquet.py @@ -581,6 +581,7 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b ) if schema_evolution is False: _utils.check_schema_changes(columns_types=columns_types, table_input=catalog_table_input, mode=mode) + if (catalog_table_input is None) and (table_type == "GOVERNED"): catalog._create_parquet_table( # pylint: disable=protected-access database=database, From ee49fb62b16dedd1975822a53a9efbd2fcf0b458 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Tue, 19 Oct 2021 17:28:21 +0100 Subject: [PATCH 21/36] Merging with main --- .bumpversion.cfg | 2 +- .../ISSUE_TEMPLATE/support-data-wrangler.md | 19 + CONTRIBUTING.md | 6 +- CONTRIBUTING_COMMON_ERRORS.md | 6 +- README.md | 64 +- awswrangler/__init__.py | 2 + awswrangler/__metadata__.py | 2 +- awswrangler/_config.py | 11 + awswrangler/_data_types.py | 7 + awswrangler/_utils.py | 2 + awswrangler/athena/_read.py | 70 +- awswrangler/athena/_utils.py | 2 +- awswrangler/catalog/_add.py | 1 + awswrangler/catalog/_definitions.py | 2 +- awswrangler/catalog/_utils.py | 1 - awswrangler/chime.py | 2 +- awswrangler/dynamodb/_write.py | 2 +- awswrangler/emr.py | 7 + awswrangler/mysql.py | 2 +- awswrangler/opensearch/__init__.py | 17 + awswrangler/opensearch/_read.py | 169 ++ awswrangler/opensearch/_utils.py | 108 ++ awswrangler/opensearch/_write.py | 573 ++++++ awswrangler/postgresql.py | 2 +- awswrangler/redshift.py | 29 +- awswrangler/s3/_copy.py | 14 +- awswrangler/s3/_delete.py | 5 +- awswrangler/s3/_describe.py | 10 +- awswrangler/s3/_download.py | 5 +- awswrangler/s3/_fs.py | 2 +- awswrangler/s3/_merge_upsert_table.py | 2 +- awswrangler/s3/_read_excel.py | 1 + awswrangler/s3/_read_parquet.py | 131 +- awswrangler/s3/_read_text.py | 16 +- awswrangler/s3/_upload.py | 5 +- awswrangler/s3/_wait.py | 14 +- awswrangler/s3/_write_concurrent.py | 4 +- awswrangler/s3/_write_dataset.py | 6 +- awswrangler/s3/_write_excel.py | 7 +- awswrangler/s3/_write_parquet.py | 46 +- awswrangler/s3/_write_text.py | 20 +- building/lambda/build-lambda-layer.sh | 3 + docs/source/api.rst | 19 + docs/source/install.rst | 6 +- docs/source/what.rst | 2 +- poetry.lock | 1455 ++++++++------ pyproject.toml | 40 +- test_infra/app.py | 9 + test_infra/poetry.lock | 670 ++++--- test_infra/pyproject.toml | 25 +- test_infra/scripts/delete-opensearch.sh | 6 + test_infra/scripts/deploy-opensearch.sh | 7 + test_infra/stacks/opensearch_stack.py | 105 ++ tests/_utils.py | 7 +- tests/test_athena_parquet.py | 15 + tests/test_config.py | 4 + tests/test_metadata.py | 2 +- tests/test_opensearch.py | 358 ++++ tests/test_s3_parquet.py | 21 + tutorials/001 - Introduction.ipynb | 20 +- ...shift, MySQL, PostgreSQL, SQL Server.ipynb | 24 +- tutorials/014 - Schema Evolution.ipynb | 4 +- tutorials/021 - Global Configurations.ipynb | 2 +- ...22 - Writing Partitions Concurrently.ipynb | 2 +- .../023 - Flexible Partitions Filter.ipynb | 2 +- tutorials/031 - OpenSearch.ipynb | 1668 +++++++++++++++++ ...32 - Lake Formation Governed Tables.ipynb} | 214 +-- 67 files changed, 4918 insertions(+), 1168 deletions(-) create mode 100644 .github/ISSUE_TEMPLATE/support-data-wrangler.md create mode 100644 awswrangler/opensearch/__init__.py create mode 100644 awswrangler/opensearch/_read.py create mode 100644 awswrangler/opensearch/_utils.py create mode 100644 awswrangler/opensearch/_write.py create mode 100755 test_infra/scripts/delete-opensearch.sh create mode 100755 test_infra/scripts/deploy-opensearch.sh create mode 100644 test_infra/stacks/opensearch_stack.py create mode 100644 tests/test_opensearch.py create mode 100644 tutorials/031 - OpenSearch.ipynb rename tutorials/{031 - Lake Formation Governed Tables.ipynb => 032 - Lake Formation Governed Tables.ipynb} (91%) diff --git a/.bumpversion.cfg b/.bumpversion.cfg index b60afc641..99bcaa9d4 100644 --- a/.bumpversion.cfg +++ b/.bumpversion.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 2.11.0 +current_version = 2.12.1 commit = False tag = False tag_name = {new_version} diff --git a/.github/ISSUE_TEMPLATE/support-data-wrangler.md b/.github/ISSUE_TEMPLATE/support-data-wrangler.md new file mode 100644 index 000000000..034e4c2dc --- /dev/null +++ b/.github/ISSUE_TEMPLATE/support-data-wrangler.md @@ -0,0 +1,19 @@ +--- +name: Support Data Wrangler +about: Add your organisation's name or logo to the Data Wrangler read.me +title: "[Support Data Wrangler]: " +labels: '' +assignees: '' + +--- + +Thank you for letting us use your organisation's name on the Data Wrangler read.me page and letting other customers know that you support the project! If you would like us to also display your organisation's logo. please raise a linked pull request to provide an image file for the logo. + +Please add any files to *docs/source/_static/* + +Organisation Name: +Your Name: +Your Position: +I have included a logo: y/n + +*By raising a Support the SDLF issue (and related pull request), you are granting AWS permission to use your company’s name (and logo) for the limited purpose described here and you are confirming that you have authority to grant such permission.* diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index d3420ade6..e898ec21e 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -215,6 +215,10 @@ or ``./deploy-base.sh`` ``./deploy-databases.sh`` +* [OPTIONAL] Deploy the Cloudformation template `opensearch.yaml` (if you need to test Amazon OpenSearch Service). This step could take about 15 minutes to deploy. + +``./deploy-opensearch.sh`` + * Go to the `EC2 -> SecurityGroups` console, open the `aws-data-wrangler-*` security group and configure to accept your IP from any TCP port. - Alternatively run: @@ -244,7 +248,7 @@ or ``pytest -n 8 tests/test_db.py`` -* To run all data lake test functions for all python versions (Only if Amazon QuickSight is activated): +* To run all data lake test functions for all python versions (Only if Amazon QuickSight is activated and Amazon OpenSearch template is deployed): ``./test.sh`` diff --git a/CONTRIBUTING_COMMON_ERRORS.md b/CONTRIBUTING_COMMON_ERRORS.md index 5d820d28e..8ced62e0e 100644 --- a/CONTRIBUTING_COMMON_ERRORS.md +++ b/CONTRIBUTING_COMMON_ERRORS.md @@ -13,9 +13,9 @@ Requirement already satisfied: pbr!=2.1.0,>=2.0.0 in ./.venv/lib/python3.7/site- Using legacy 'setup.py install' for python-Levenshtein, since package 'wheel' is not installed. Installing collected packages: awswrangler, python-Levenshtein Attempting uninstall: awswrangler - Found existing installation: awswrangler 2.11.0 - Uninstalling awswrangler-2.11.0: - Successfully uninstalled awswrangler-2.11.0 + Found existing installation: awswrangler 2.12.1 + Uninstalling awswrangler-2.12.1: + Successfully uninstalled awswrangler-2.12.1 Running setup.py develop for awswrangler Running setup.py install for python-Levenshtein ... error ERROR: Command errored out with exit status 1: diff --git a/README.md b/README.md index 01b595472..df9652c26 100644 --- a/README.md +++ b/README.md @@ -8,7 +8,7 @@ Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, Clo > An [AWS Professional Service](https://aws.amazon.com/professional-services/) open source initiative | aws-proserve-opensource@amazon.com -[![Release](https://img.shields.io/badge/release-2.11.0-brightgreen.svg)](https://pypi.org/project/awswrangler/) +[![Release](https://img.shields.io/badge/release-2.12.1-brightgreen.svg)](https://pypi.org/project/awswrangler/) [![Python Version](https://img.shields.io/badge/python-3.6%20%7C%203.7%20%7C%203.8%20%7C%203.9-brightgreen.svg)](https://anaconda.org/conda-forge/awswrangler) [![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0) @@ -23,7 +23,7 @@ Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, Clo | **[PyPi](https://pypi.org/project/awswrangler/)** | [![PyPI Downloads](https://pepy.tech/badge/awswrangler)](https://pypi.org/project/awswrangler/) | `pip install awswrangler` | | **[Conda](https://anaconda.org/conda-forge/awswrangler)** | [![Conda Downloads](https://img.shields.io/conda/dn/conda-forge/awswrangler.svg)](https://anaconda.org/conda-forge/awswrangler) | `conda install -c conda-forge awswrangler` | -> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-glue-pyspark-jobs), MWAA):**
+> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#aws-glue-pyspark-jobs), MWAA):**
➡️ `pip install pyarrow==2 awswrangler` Powered By [](https://arrow.apache.org/powered_by/) @@ -42,7 +42,7 @@ Powered By [](http Installation command: `pip install awswrangler` -> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-glue-pyspark-jobs), MWAA):**
+> ⚠️ **For platforms without PyArrow 3 support (e.g. [EMR](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#emr-cluster), [Glue PySpark Job](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#aws-glue-pyspark-jobs), MWAA):**
➡️`pip install pyarrow==2 awswrangler` ```py3 @@ -96,17 +96,17 @@ FROM "sampleDB"."sampleTable" ORDER BY time DESC LIMIT 3 ## [Read The Docs](https://aws-data-wrangler.readthedocs.io/) -- [**What is AWS Data Wrangler?**](https://aws-data-wrangler.readthedocs.io/en/2.11.0/what.html) -- [**Install**](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html) - - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#pypi-pip) - - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#conda) - - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-lambda-layer) - - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-glue-python-shell-jobs) - - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-glue-pyspark-jobs) - - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#amazon-sagemaker-notebook) - - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#amazon-sagemaker-notebook-lifecycle) - - [EMR](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#emr) - - [From source](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#from-source) +- [**What is AWS Data Wrangler?**](https://aws-data-wrangler.readthedocs.io/en/2.12.1/what.html) +- [**Install**](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html) + - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#pypi-pip) + - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#conda) + - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#aws-lambda-layer) + - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#aws-glue-python-shell-jobs) + - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#aws-glue-pyspark-jobs) + - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#amazon-sagemaker-notebook) + - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#amazon-sagemaker-notebook-lifecycle) + - [EMR](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#emr) + - [From source](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#from-source) - [**Tutorials**](https://github.com/awslabs/aws-data-wrangler/tree/main/tutorials) - [001 - Introduction](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/001%20-%20Introduction.ipynb) - [002 - Sessions](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/002%20-%20Sessions.ipynb) @@ -136,22 +136,23 @@ FROM "sampleDB"."sampleTable" ORDER BY time DESC LIMIT 3 - [026 - Amazon Timestream](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/026%20-%20Amazon%20Timestream.ipynb) - [027 - Amazon Timestream 2](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/027%20-%20Amazon%20Timestream%202.ipynb) - [028 - Amazon DynamoDB](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/028%20-%20DynamoDB.ipynb) -- [**API Reference**](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html) - - [Amazon S3](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-s3) - - [AWS Glue Catalog](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#aws-glue-catalog) - - [Amazon Athena](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-athena) - - [Amazon Redshift](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-redshift) - - [PostgreSQL](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#postgresql) - - [MySQL](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#mysql) - - [SQL Server](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#sqlserver) - - [DynamoDB](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#dynamodb) - - [Amazon Timestream](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-timestream) - - [Amazon EMR](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-emr) - - [Amazon CloudWatch Logs](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-cloudwatch-logs) - - [Amazon Chime](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-chime) - - [Amazon QuickSight](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#amazon-quicksight) - - [AWS STS](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#aws-sts) - - [AWS Secrets Manager](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html#aws-secrets-manager) + - [031 - OpenSearch](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/031%20-%20OpenSearch.ipynb) +- [**API Reference**](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html) + - [Amazon S3](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#amazon-s3) + - [AWS Glue Catalog](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#aws-glue-catalog) + - [Amazon Athena](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#amazon-athena) + - [Amazon Redshift](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#amazon-redshift) + - [PostgreSQL](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#postgresql) + - [MySQL](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#mysql) + - [SQL Server](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#sqlserver) + - [DynamoDB](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#dynamodb) + - [Amazon Timestream](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#amazon-timestream) + - [Amazon EMR](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#amazon-emr) + - [Amazon CloudWatch Logs](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#amazon-cloudwatch-logs) + - [Amazon Chime](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#amazon-chime) + - [Amazon QuickSight](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#amazon-quicksight) + - [AWS STS](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#aws-sts) + - [AWS Secrets Manager](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#aws-secrets-manager) - [**License**](https://github.com/awslabs/aws-data-wrangler/blob/main/LICENSE.txt) - [**Contributing**](https://github.com/awslabs/aws-data-wrangler/blob/main/CONTRIBUTING.md) - [**Legacy Docs** (pre-1.0.0)](https://aws-data-wrangler.readthedocs.io/en/0.3.3/) @@ -197,8 +198,7 @@ logging.getLogger("awswrangler").setLevel(logging.DEBUG) ## Who uses AWS Data Wrangler? Knowing which companies are using this library is important to help prioritize the project internally. - -Please [send a Pull Request](https://github.com/awslabs/aws-data-wrangler/edit/main/README.md) with your company name and @githubhandle if you may. +If you would like us to include your company’s name and/or logo in the README file to indicate that your company is using the AWS Data Wrangler, please raise a "Support Data Wrangler" issue. If you would like us to display your company’s logo, please raise a linked pull request to provide an image file for the logo. Note that by raising a Support Data Wrangler issue (and related pull request), you are granting AWS permission to use your company’s name (and logo) for the limited purpose described here and you are confirming that you have authority to grant such permission. - [Amazon](https://www.amazon.com/) - [AWS](https://aws.amazon.com/) diff --git a/awswrangler/__init__.py b/awswrangler/__init__.py index 55c0b702d..c3d5afe1f 100644 --- a/awswrangler/__init__.py +++ b/awswrangler/__init__.py @@ -18,6 +18,7 @@ exceptions, lakeformation, mysql, + opensearch, postgresql, quicksight, redshift, @@ -39,6 +40,7 @@ "data_api", "dynamodb", "exceptions", + "opensearch", "quicksight", "s3", "sts", diff --git a/awswrangler/__metadata__.py b/awswrangler/__metadata__.py index 4872e3912..f74dbc0ed 100644 --- a/awswrangler/__metadata__.py +++ b/awswrangler/__metadata__.py @@ -7,5 +7,5 @@ __title__: str = "awswrangler" __description__: str = "Pandas on AWS." -__version__: str = "2.11.0" +__version__: str = "2.12.1" __license__: str = "Apache License 2.0" diff --git a/awswrangler/_config.py b/awswrangler/_config.py index a35f92812..babf92f93 100644 --- a/awswrangler/_config.py +++ b/awswrangler/_config.py @@ -45,6 +45,7 @@ class _ConfigArg(NamedTuple): "emr_endpoint_url": _ConfigArg(dtype=str, nullable=True, enforced=True), "lakeformation_endpoint_url": _ConfigArg(dtype=str, nullable=True, enforced=True), "dynamodb_endpoint_url": _ConfigArg(dtype=str, nullable=True, enforced=True), + "secretsmanager_endpoint_url": _ConfigArg(dtype=str, nullable=True, enforced=True), # Botocore config "botocore_config": _ConfigArg(dtype=botocore.config.Config, nullable=True), } @@ -65,6 +66,7 @@ def __init__(self) -> None: self.emr_endpoint_url = None self.lakeformation_endpoint_url = None self.dynamodb_endpoint_url = None + self.secretsmanager_endpoint_url = None self.botocore_config = None for name in _CONFIG_ARGS: self._load_config(name=name) @@ -374,6 +376,15 @@ def dynamodb_endpoint_url(self) -> Optional[str]: def dynamodb_endpoint_url(self, value: Optional[str]) -> None: self._set_config_value(key="dynamodb_endpoint_url", value=value) + @property + def secretsmanager_endpoint_url(self) -> Optional[str]: + """Property secretsmanager_endpoint_url.""" + return cast(Optional[str], self["secretsmanager_endpoint_url"]) + + @secretsmanager_endpoint_url.setter + def secretsmanager_endpoint_url(self, value: Optional[str]) -> None: + self._set_config_value(key="secretsmanager_endpoint_url", value=value) + @property def botocore_config(self) -> botocore.config.Config: """Property botocore_config.""" diff --git a/awswrangler/_data_types.py b/awswrangler/_data_types.py index b32c099c7..d34685758 100644 --- a/awswrangler/_data_types.py +++ b/awswrangler/_data_types.py @@ -701,3 +701,10 @@ def timestream_type_from_pandas(df: pd.DataFrame) -> str: pyarrow_type: pa.DataType = list(pyarrow_types.values())[0] _logger.debug("pyarrow_type: %s", pyarrow_type) return pyarrow2timestream(dtype=pyarrow_type) + + +def get_arrow_timestamp_unit(data_type: pa.lib.DataType) -> Any: + """Return unit of pyarrow timestamp. If the pyarrow type is not timestamp then None is returned.""" + if isinstance(data_type, pa.lib.TimestampType): + return data_type.unit + return None diff --git a/awswrangler/_utils.py b/awswrangler/_utils.py index 7ad81604b..47dec6ab8 100644 --- a/awswrangler/_utils.py +++ b/awswrangler/_utils.py @@ -97,6 +97,8 @@ def _get_endpoint_url(service_name: str) -> Optional[str]: endpoint_url = _config.config.lakeformation_endpoint_url elif service_name == "dynamodb" and _config.config.dynamodb_endpoint_url is not None: endpoint_url = _config.config.dynamodb_endpoint_url + elif service_name == "secretsmanager" and _config.config.secretsmanager_endpoint_url is not None: + endpoint_url = _config.config.secretsmanager_endpoint_url return endpoint_url diff --git a/awswrangler/athena/_read.py b/awswrangler/athena/_read.py index cd828ccf8..54ec04a95 100644 --- a/awswrangler/athena/_read.py +++ b/awswrangler/athena/_read.py @@ -75,7 +75,7 @@ def _fix_csv_types(df: pd.DataFrame, parse_dates: List[str], binaries: List[str] def _delete_after_iterate( dfs: Iterator[pd.DataFrame], paths: List[str], - use_threads: bool, + use_threads: Union[bool, int], boto3_session: boto3.Session, s3_additional_kwargs: Optional[Dict[str, str]], ) -> Iterator[pd.DataFrame]: @@ -218,10 +218,11 @@ def _fetch_parquet_result( keep_files: bool, categories: Optional[List[str]], chunksize: Optional[int], - use_threads: bool, + use_threads: Union[bool, int], boto3_session: boto3.Session, s3_additional_kwargs: Optional[Dict[str, Any]], temp_table_fqn: Optional[str] = None, + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: ret: Union[pd.DataFrame, Iterator[pd.DataFrame]] chunked: Union[bool, int] = False if chunksize is None else chunksize @@ -249,6 +250,7 @@ def _fetch_parquet_result( chunked=chunked, categories=categories, ignore_index=True, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, ) if chunked is False: ret = _apply_query_metadata(df=ret, query_metadata=query_metadata) @@ -280,7 +282,7 @@ def _fetch_csv_result( query_metadata: _QueryMetadata, keep_files: bool, chunksize: Optional[int], - use_threads: bool, + use_threads: Union[bool, int], boto3_session: boto3.Session, s3_additional_kwargs: Optional[Dict[str, Any]], ) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: @@ -334,9 +336,10 @@ def _resolve_query_with_cache( cache_info: _CacheInfo, categories: Optional[List[str]], chunksize: Optional[Union[int, bool]], - use_threads: bool, + use_threads: Union[bool, int], session: Optional[boto3.Session], s3_additional_kwargs: Optional[Dict[str, Any]], + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: """Fetch cached data and return it as a pandas DataFrame (or list of DataFrames).""" _logger.debug("cache_info:\n%s", cache_info) @@ -358,6 +361,7 @@ def _resolve_query_with_cache( use_threads=use_threads, boto3_session=session, s3_additional_kwargs=s3_additional_kwargs, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, ) if cache_info.file_format == "csv": return _fetch_csv_result( @@ -386,9 +390,10 @@ def _resolve_query_without_cache_ctas( alt_database: Optional[str], name: Optional[str], ctas_bucketing_info: Optional[Tuple[List[str], int]], - use_threads: bool, + use_threads: Union[bool, int], s3_additional_kwargs: Optional[Dict[str, Any]], boto3_session: boto3.Session, + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: path: str = f"{s3_output}/{name}" ext_location: str = "\n" if wg_config.enforced is True else f",\n external_location = '{path}'\n" @@ -465,6 +470,7 @@ def _resolve_query_without_cache_ctas( s3_additional_kwargs=s3_additional_kwargs, boto3_session=boto3_session, temp_table_fqn=fully_qualified_name, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, ) @@ -480,7 +486,7 @@ def _resolve_query_without_cache_regular( workgroup: Optional[str], kms_key: Optional[str], wg_config: _WorkGroupConfig, - use_threads: bool, + use_threads: Union[bool, int], s3_additional_kwargs: Optional[Dict[str, Any]], boto3_session: boto3.Session, ) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: @@ -529,9 +535,10 @@ def _resolve_query_without_cache( ctas_database_name: Optional[str], ctas_temp_table_name: Optional[str], ctas_bucketing_info: Optional[Tuple[List[str], int]], - use_threads: bool, + use_threads: Union[bool, int], s3_additional_kwargs: Optional[Dict[str, Any]], boto3_session: boto3.Session, + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: """ Execute a query in Athena and returns results as DataFrame, back to `read_sql_query`. @@ -565,6 +572,7 @@ def _resolve_query_without_cache( use_threads=use_threads, s3_additional_kwargs=s3_additional_kwargs, boto3_session=boto3_session, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, ) finally: catalog.delete_table_if_exists( @@ -603,7 +611,7 @@ def read_sql_query( ctas_database_name: Optional[str] = None, ctas_temp_table_name: Optional[str] = None, ctas_bucketing_info: Optional[Tuple[List[str], int]] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, max_cache_seconds: int = 0, max_cache_query_inspections: int = 50, @@ -612,16 +620,17 @@ def read_sql_query( data_source: Optional[str] = None, params: Optional[Dict[str, Any]] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: """Execute any SQL query on AWS Athena and return the results as a Pandas DataFrame. **Related tutorial:** - - `Amazon Athena `_ - - `Athena Cache `_ - - `Global Configurations `_ **There are two approaches to be defined through ctas_approach parameter:** @@ -669,7 +678,7 @@ def read_sql_query( /athena.html#Athena.Client.get_query_execution>`_ . For a practical example check out the - `related tutorial `_! @@ -747,9 +756,10 @@ def read_sql_query( Tuple consisting of the column names used for bucketing as the first element and the number of buckets as the second element. Only `str`, `int` and `bool` are supported as column data types for bucketing. - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. max_cache_seconds : int @@ -781,6 +791,14 @@ def read_sql_query( s3_additional_kwargs : Optional[Dict[str, Any]] Forwarded to botocore requests. e.g. s3_additional_kwargs={'RequestPayer': 'requester'} + pyarrow_additional_kwargs : Optional[Dict[str, Any]] + Forward to the ParquetFile class or converting an Arrow table to Pandas, currently only an + "coerce_int96_timestamp_unit" or "timestamp_as_object" argument will be considered. If reading parquet + files where you cannot convert a timestamp to pandas Timestamp[ns] consider setting timestamp_as_object=True, + to allow for timestamp units larger than "ns". If reading parquet data that still uses INT96 (like Athena + outputs) you can use coerce_int96_timestamp_unit to specify what timestamp unit to encode INT96 to (by default + this is "ns", if you know the output parquet came from a system that encodes timestamp to a particular unit + then set this to that same unit e.g. coerce_int96_timestamp_unit="ms"). Returns ------- @@ -837,6 +855,7 @@ def read_sql_query( use_threads=use_threads, session=session, s3_additional_kwargs=s3_additional_kwargs, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, ) except Exception as e: # pylint: disable=broad-except _logger.error(e) # if there is anything wrong with the cache, just fallback to the usual path @@ -859,6 +878,7 @@ def read_sql_query( use_threads=use_threads, s3_additional_kwargs=s3_additional_kwargs, boto3_session=session, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, ) @@ -877,7 +897,7 @@ def read_sql_table( ctas_database_name: Optional[str] = None, ctas_temp_table_name: Optional[str] = None, ctas_bucketing_info: Optional[Tuple[List[str], int]] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, max_cache_seconds: int = 0, max_cache_query_inspections: int = 50, @@ -885,16 +905,17 @@ def read_sql_table( max_local_cache_entries: int = 100, data_source: Optional[str] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: """Extract the full table AWS Athena and return the results as a Pandas DataFrame. **Related tutorial:** - - `Amazon Athena `_ - - `Athena Cache `_ - - `Global Configurations `_ **There are two approaches to be defined through ctas_approach parameter:** @@ -939,7 +960,7 @@ def read_sql_table( /athena.html#Athena.Client.get_query_execution>`_ . For a practical example check out the - `related tutorial `_! @@ -1015,9 +1036,10 @@ def read_sql_table( Tuple consisting of the column names used for bucketing as the first element and the number of buckets as the second element. Only `str`, `int` and `bool` are supported as column data types for bucketing. - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. max_cache_seconds: int @@ -1045,6 +1067,15 @@ def read_sql_table( s3_additional_kwargs : Optional[Dict[str, Any]] Forwarded to botocore requests. e.g. s3_additional_kwargs={'RequestPayer': 'requester'} + pyarrow_additional_kwargs : Optional[Dict[str, Any]] + Forward to the ParquetFile class or converting an Arrow table to Pandas, currently only an + "coerce_int96_timestamp_unit" or "timestamp_as_object" argument will be considered. If + reading parquet fileswhere you cannot convert a timestamp to pandas Timestamp[ns] consider + setting timestamp_as_object=True, to allow for timestamp units > NS. If reading parquet data that + still uses INT96 (like Athena outputs) you can use coerce_int96_timestamp_unit to specify what + timestamp unit to encode INT96 to (by default this is "ns", if you know the output parquet came from + a system that encodes timestamp to a particular unit then set this to that same unit e.g. + coerce_int96_timestamp_unit="ms"). Returns ------- @@ -1081,6 +1112,7 @@ def read_sql_table( max_remote_cache_entries=max_remote_cache_entries, max_local_cache_entries=max_local_cache_entries, s3_additional_kwargs=s3_additional_kwargs, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, ) diff --git a/awswrangler/athena/_utils.py b/awswrangler/athena/_utils.py index a9a17acc9..c27fa9b6e 100644 --- a/awswrangler/athena/_utils.py +++ b/awswrangler/athena/_utils.py @@ -43,7 +43,7 @@ class _WorkGroupConfig(NamedTuple): class _LocalMetadataCacheManager: def __init__(self) -> None: - self._cache: Dict[str, Any] = dict() + self._cache: Dict[str, Any] = {} self._pqueue: List[Tuple[datetime.datetime, str]] = [] self._max_cache_size = 100 diff --git a/awswrangler/catalog/_add.py b/awswrangler/catalog/_add.py index 07a529efb..df300ab14 100644 --- a/awswrangler/catalog/_add.py +++ b/awswrangler/catalog/_add.py @@ -108,6 +108,7 @@ def add_csv_partitions( ... ) """ + table = sanitize_table_name(table=table) inputs: List[Dict[str, Any]] = [ _csv_partition_definition( location=k, diff --git a/awswrangler/catalog/_definitions.py b/awswrangler/catalog/_definitions.py index d145252ee..20136c922 100644 --- a/awswrangler/catalog/_definitions.py +++ b/awswrangler/catalog/_definitions.py @@ -192,7 +192,7 @@ def _check_column_type(column_type: str) -> bool: def _update_table_definition(current_definition: Dict[str, Any]) -> Dict[str, Any]: - definition: Dict[str, Any] = dict() + definition: Dict[str, Any] = {} keep_keys = [ "Name", "Description", diff --git a/awswrangler/catalog/_utils.py b/awswrangler/catalog/_utils.py index 4679c60e2..e019217ca 100644 --- a/awswrangler/catalog/_utils.py +++ b/awswrangler/catalog/_utils.py @@ -75,7 +75,6 @@ def does_table_exist( -------- >>> import awswrangler as wr >>> wr.catalog.does_table_exist(database='default', table='my_table') - """ client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) try: diff --git a/awswrangler/chime.py b/awswrangler/chime.py index df5091732..979c63f14 100644 --- a/awswrangler/chime.py +++ b/awswrangler/chime.py @@ -26,7 +26,7 @@ def post_message(webhook: str, message: str) -> Optional[Any]: Represents the response from Chime """ response = None - chime_message = {"Content": "Message: %s" % (message)} + chime_message = {"Content": f"Message: {message}"} req = Request(webhook, json.dumps(chime_message).encode("utf-8")) try: response = urlopen(req) # pylint: disable=R1732 diff --git a/awswrangler/dynamodb/_write.py b/awswrangler/dynamodb/_write.py index 3a900de0a..812460008 100644 --- a/awswrangler/dynamodb/_write.py +++ b/awswrangler/dynamodb/_write.py @@ -51,7 +51,7 @@ def put_json( ... ) """ # Loading data from file - with open(path, "r") as f: + with open(path, "r") as f: # pylint: disable=W1514 items = json.load(f) if isinstance(items, dict): items = [items] diff --git a/awswrangler/emr.py b/awswrangler/emr.py index 9b4f082ce..18d81139c 100644 --- a/awswrangler/emr.py +++ b/awswrangler/emr.py @@ -130,6 +130,10 @@ def _build_cluster_args(**pars: Any) -> Dict[str, Any]: # pylint: disable=too-m "StepConcurrencyLevel": pars["step_concurrency_level"], } + # Custom AMI + if pars["custom_ami_id"] is not None: + args["CustomAmiId"] = pars["custom_ami_id"] + # EC2 Key Pair if pars["key_pair_name"] is not None: args["Instances"]["Ec2KeyName"] = pars["key_pair_name"] @@ -442,6 +446,7 @@ def create_cluster( # pylint: disable=too-many-arguments,too-many-locals,unused custom_classifications: Optional[List[Dict[str, Any]]] = None, maximize_resource_allocation: bool = False, steps: Optional[List[Dict[str, Any]]] = None, + custom_ami_id: Optional[str] = None, step_concurrency_level: int = 1, keep_cluster_alive_when_no_steps: bool = True, termination_protected: bool = False, @@ -586,6 +591,8 @@ def create_cluster( # pylint: disable=too-many-arguments,too-many-locals,unused maximize_resource_allocation : bool Configure your executors to utilize the maximum resources possible https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-spark-configure.html#emr-spark-maximizeresourceallocation + custom_ami_id : Optional[str] + The custom AMI ID to use for the provisioned instance group steps : List[Dict[str, Any]], optional Steps definitions (Obs : str Use EMR.build_step() to build it) keep_cluster_alive_when_no_steps : bool diff --git a/awswrangler/mysql.py b/awswrangler/mysql.py index 2f5c2cc74..257251b1e 100644 --- a/awswrangler/mysql.py +++ b/awswrangler/mysql.py @@ -383,7 +383,7 @@ def to_sql( upsert_columns = "" upsert_str = "" if use_column_names: - insertion_columns = f"({', '.join(df.columns)})" + insertion_columns = f"(`{'`, `'.join(df.columns)}`)" if mode == "upsert_duplicate_key": upsert_columns = ", ".join(df.columns.map(lambda column: f"`{column}`=VALUES(`{column}`)")) upsert_str = f" ON DUPLICATE KEY UPDATE {upsert_columns}" diff --git a/awswrangler/opensearch/__init__.py b/awswrangler/opensearch/__init__.py new file mode 100644 index 000000000..205e70b59 --- /dev/null +++ b/awswrangler/opensearch/__init__.py @@ -0,0 +1,17 @@ +"""Utilities Module for Amazon OpenSearch.""" + +from awswrangler.opensearch._read import search, search_by_sql +from awswrangler.opensearch._utils import connect +from awswrangler.opensearch._write import create_index, delete_index, index_csv, index_df, index_documents, index_json + +__all__ = [ + "connect", + "create_index", + "delete_index", + "index_csv", + "index_documents", + "index_df", + "index_json", + "search", + "search_by_sql", +] diff --git a/awswrangler/opensearch/_read.py b/awswrangler/opensearch/_read.py new file mode 100644 index 000000000..acbb9daf4 --- /dev/null +++ b/awswrangler/opensearch/_read.py @@ -0,0 +1,169 @@ +"""Amazon OpenSearch Read Module (PRIVATE).""" + +from typing import Any, Collection, Dict, List, Mapping, Optional, Union + +import pandas as pd +from opensearchpy import OpenSearch +from opensearchpy.helpers import scan + +from awswrangler.opensearch._utils import _get_distribution + + +def _resolve_fields(row: Mapping[str, Any]) -> Mapping[str, Any]: + fields = {} + for field in row: + if isinstance(row[field], dict): + nested_fields = _resolve_fields(row[field]) + for n_field, val in nested_fields.items(): + fields[f"{field}.{n_field}"] = val + else: + fields[field] = row[field] + return fields + + +def _hit_to_row(hit: Mapping[str, Any]) -> Mapping[str, Any]: + row: Dict[str, Any] = {} + for k in hit.keys(): + if k == "_source": + solved_fields = _resolve_fields(hit["_source"]) + row.update(solved_fields) + elif k.startswith("_"): + row[k] = hit[k] + return row + + +def _search_response_to_documents(response: Mapping[str, Any]) -> List[Mapping[str, Any]]: + return [_hit_to_row(hit) for hit in response["hits"]["hits"]] + + +def _search_response_to_df(response: Union[Mapping[str, Any], Any]) -> pd.DataFrame: + return pd.DataFrame(_search_response_to_documents(response)) + + +def search( + client: OpenSearch, + index: Optional[str] = "_all", + search_body: Optional[Dict[str, Any]] = None, + doc_type: Optional[str] = None, + is_scroll: Optional[bool] = False, + filter_path: Optional[Union[str, Collection[str]]] = None, + **kwargs: Any, +) -> pd.DataFrame: + """Return results matching query DSL as pandas dataframe. + + Parameters + ---------- + client : OpenSearch + instance of opensearchpy.OpenSearch to use. + index : str, optional + A comma-separated list of index names to search. + use `_all` or empty string to perform the operation on all indices. + search_body : Dict[str, Any], optional + The search definition using the `Query DSL `_. + doc_type : str, optional + Name of the document type (for Elasticsearch versions 5.x and earlier). + is_scroll : bool, optional + Allows to retrieve a large numbers of results from a single search request using + `scroll `_ + for example, for machine learning jobs. + Because scroll search contexts consume a lot of memory, we suggest you don’t use the scroll operation + for frequent user queries. + filter_path : Union[str, Collection[str]], optional + Use the filter_path parameter to reduce the size of the OpenSearch Service response \ +(default: ['hits.hits._id','hits.hits._source']) + **kwargs : + KEYWORD arguments forwarded to `opensearchpy.OpenSearch.search \ +`_ + and also to `opensearchpy.helpers.scan `_ + if `is_scroll=True` + + Returns + ------- + Union[pandas.DataFrame, Iterator[pandas.DataFrame]] + Results as Pandas DataFrame + + Examples + -------- + Searching an index using query DSL + + >>> import awswrangler as wr + >>> client = wr.opensearch.connect(host='DOMAIN-ENDPOINT') + >>> df = wr.opensearch.search( + ... client=client, + ... index='movies', + ... search_body={ + ... "query": { + ... "match": { + ... "title": "wind" + ... } + ... } + ... } + ... ) + + + """ + if doc_type: + kwargs["doc_type"] = doc_type + + if filter_path is None: + filter_path = ["hits.hits._id", "hits.hits._source"] + + if is_scroll: + if isinstance(filter_path, str): + filter_path = [filter_path] + filter_path = ["_scroll_id", "_shards"] + list(filter_path) # required for scroll + documents_generator = scan(client, index=index, query=search_body, filter_path=filter_path, **kwargs) + documents = [_hit_to_row(doc) for doc in documents_generator] + df = pd.DataFrame(documents) + else: + response = client.search(index=index, body=search_body, filter_path=filter_path, **kwargs) + df = _search_response_to_df(response) + return df + + +def search_by_sql(client: OpenSearch, sql_query: str, **kwargs: Any) -> pd.DataFrame: + """Return results matching `SQL query `_ as pandas dataframe. + + Parameters + ---------- + client : OpenSearch + instance of opensearchpy.OpenSearch to use. + sql_query : str + SQL query + **kwargs : + KEYWORD arguments forwarded to request url (e.g.: filter_path, etc.) + + Returns + ------- + Union[pandas.DataFrame, Iterator[pandas.DataFrame]] + Results as Pandas DataFrame + + Examples + -------- + Searching an index using SQL query + + >>> import awswrangler as wr + >>> client = wr.opensearch.connect(host='DOMAIN-ENDPOINT') + >>> df = wr.opensearch.search_by_sql( + >>> client=client, + >>> sql_query='SELECT * FROM my-index LIMIT 50' + >>> ) + + + """ + if _get_distribution(client) == "opensearch": + url = "/_plugins/_sql" + else: + url = "/_opendistro/_sql" + + kwargs["format"] = "json" + body = {"query": sql_query} + for size_att in ["size", "fetch_size"]: + if size_att in kwargs: + body["fetch_size"] = kwargs[size_att] + del kwargs[size_att] # unrecognized parameter + response = client.transport.perform_request( + "POST", url, headers={"Content-Type": "application/json"}, body=body, params=kwargs + ) + df = _search_response_to_df(response) + return df diff --git a/awswrangler/opensearch/_utils.py b/awswrangler/opensearch/_utils.py new file mode 100644 index 000000000..21cab7c33 --- /dev/null +++ b/awswrangler/opensearch/_utils.py @@ -0,0 +1,108 @@ +"""Amazon OpenSearch Utils Module (PRIVATE).""" + +import logging +import re +from typing import Any, Optional + +import boto3 +from opensearchpy import OpenSearch, RequestsHttpConnection +from requests_aws4auth import AWS4Auth + +from awswrangler import _utils, exceptions + +_logger: logging.Logger = logging.getLogger(__name__) + + +def _get_distribution(client: OpenSearch) -> Any: + return client.info().get("version", {}).get("distribution", "elasticsearch") + + +def _get_version(client: OpenSearch) -> Any: + return client.info().get("version", {}).get("number") + + +def _get_version_major(client: OpenSearch) -> Any: + version = _get_version(client) + if version: + return int(version.split(".")[0]) + return None + + +def _strip_endpoint(endpoint: str) -> str: + uri_schema = re.compile(r"https?://") + return uri_schema.sub("", endpoint).strip().strip("/") + + +def connect( + host: str, + port: Optional[int] = 443, + boto3_session: Optional[boto3.Session] = boto3.Session(), + region: Optional[str] = None, + username: Optional[str] = None, + password: Optional[str] = None, +) -> OpenSearch: + """Create a secure connection to the specified Amazon OpenSearch domain. + + Note + ---- + We use `opensearch-py `_, an OpenSearch python client. + + The username and password are mandatory if the OS Cluster uses `Fine Grained Access Control \ +`_. + If fine grained access control is disabled, session access key and secret keys are used. + + Parameters + ---------- + host : str + Amazon OpenSearch domain, for example: my-test-domain.us-east-1.es.amazonaws.com. + port : int + OpenSearch Service only accepts connections over port 80 (HTTP) or 443 (HTTPS) + boto3_session : boto3.Session(), optional + Boto3 Session. The default boto3 Session will be used if boto3_session receive None. + region : + AWS region of the Amazon OS domain. If not provided will be extracted from boto3_session. + username : + Fine-grained access control username. Mandatory if OS Cluster uses Fine Grained Access Control. + password : + Fine-grained access control password. Mandatory if OS Cluster uses Fine Grained Access Control. + + Returns + ------- + opensearchpy.OpenSearch + OpenSearch low-level client. + https://github.com/opensearch-project/opensearch-py/blob/main/opensearchpy/client/__init__.py + """ + valid_ports = {80, 443} + + if port not in valid_ports: + raise ValueError(f"results: port must be one of {valid_ports}") + + if username and password: + http_auth = (username, password) + else: + if region is None: + region = _utils.get_region_from_session(boto3_session=boto3_session) + creds = _utils.get_credentials_from_session(boto3_session=boto3_session) + if creds.access_key is None or creds.secret_key is None: + raise exceptions.InvalidArgument( + "One of IAM Role or AWS ACCESS_KEY_ID and SECRET_ACCESS_KEY must be " + "given. Unable to find ACCESS_KEY_ID and SECRET_ACCESS_KEY in boto3 " + "session." + ) + http_auth = AWS4Auth(creds.access_key, creds.secret_key, region, "es", session_token=creds.token) + try: + es = OpenSearch( + host=_strip_endpoint(host), + port=port, + http_auth=http_auth, + use_ssl=True, + verify_certs=True, + connection_class=RequestsHttpConnection, + timeout=30, + max_retries=10, + retry_on_timeout=True, + ) + except Exception as e: + _logger.error("Error connecting to Opensearch cluster. Please verify authentication details") + raise e + return es diff --git a/awswrangler/opensearch/_write.py b/awswrangler/opensearch/_write.py new file mode 100644 index 000000000..9da5f05c4 --- /dev/null +++ b/awswrangler/opensearch/_write.py @@ -0,0 +1,573 @@ +"""Amazon OpenSearch Write Module (PRIVATE).""" + +import ast +import json +import logging +import uuid +from typing import Any, Dict, Generator, Iterable, List, Mapping, Optional, Tuple, Union + +import boto3 +import pandas as pd +import progressbar +from jsonpath_ng import parse +from jsonpath_ng.exceptions import JsonPathParserError +from opensearchpy import OpenSearch, TransportError +from opensearchpy.exceptions import NotFoundError +from opensearchpy.helpers import bulk +from pandas import notna + +from awswrangler._utils import parse_path +from awswrangler.opensearch._utils import _get_distribution, _get_version_major + +_logger: logging.Logger = logging.getLogger(__name__) +_logger.setLevel(logging.DEBUG) + +_DEFAULT_REFRESH_INTERVAL = "1s" + + +def _selected_keys(document: Mapping[str, Any], keys_to_write: Optional[List[str]]) -> Mapping[str, Any]: + if keys_to_write is None: + keys_to_write = list(document.keys()) + keys_to_write = list(filter(lambda x: x != "_id", keys_to_write)) + return {key: document[key] for key in keys_to_write} + + +def _actions_generator( + documents: Union[Iterable[Dict[str, Any]], Iterable[Mapping[str, Any]]], + index: str, + doc_type: Optional[str], + keys_to_write: Optional[List[str]], + id_keys: Optional[List[str]], + bulk_size: int = 10000, +) -> Generator[List[Dict[str, Any]], None, None]: + bulk_chunk_documents = [] + for i, document in enumerate(documents): + if id_keys: + _id = "-".join([str(document[id_key]) for id_key in id_keys]) + else: + _id = document.get("_id", uuid.uuid4()) + bulk_chunk_documents.append( + { + "_index": index, + "_type": doc_type, + "_id": _id, + "_source": _selected_keys(document, keys_to_write), + } + ) + if (i + 1) % bulk_size == 0: + yield bulk_chunk_documents + bulk_chunk_documents = [] + if len(bulk_chunk_documents) > 0: + yield bulk_chunk_documents + + +def _df_doc_generator(df: pd.DataFrame) -> Generator[Dict[str, Any], None, None]: + def _deserialize(v: Any) -> Any: + if isinstance(v, str): + v = v.strip() + if v.startswith("{") and v.endswith("}") or v.startswith("[") and v.endswith("]"): + try: + v = json.loads(v) + except json.decoder.JSONDecodeError: + try: + v = ast.literal_eval(v) # if properties are enclosed with single quotes + if not isinstance(v, dict): + _logger.warning("could not convert string to json: %s", v) + except SyntaxError as e: + _logger.warning("could not convert string to json: %s", v) + _logger.warning(e) + return v + + df_iter = df.iterrows() + for _, document in df_iter: + yield {k: _deserialize(v) for k, v in document.items() if notna(v)} + + +def _file_line_generator(path: str, is_json: bool = False) -> Generator[Any, None, None]: + with open(path) as fp: # pylint: disable=W1514 + for line in fp: + if is_json: + yield json.loads(line) + else: + yield line.strip() + + +def _get_documents_w_json_path(documents: List[Mapping[str, Any]], json_path: str) -> List[Any]: + try: + jsonpath_expression = parse(json_path) + except JsonPathParserError as e: + _logger.error("invalid json_path: %s", json_path) + raise e + output_documents = [] + for doc in documents: + for match in jsonpath_expression.find(doc): + match_value = match.value + if isinstance(match_value, list): + output_documents += match_value + elif isinstance(match_value, dict): + output_documents.append(match_value) + else: + msg = f"expected json_path value to be a list/dict. received type {type(match_value)} ({match_value})" + raise ValueError(msg) + return output_documents + + +def _get_refresh_interval(client: OpenSearch, index: str) -> Any: + url = f"/{index}/_settings" + try: + response = client.transport.perform_request("GET", url) + index_settings = response.get(index, {}).get("index", {}) # type: ignore + refresh_interval = index_settings.get("refresh_interval", _DEFAULT_REFRESH_INTERVAL) + return refresh_interval + except NotFoundError: + return None + + +def _set_refresh_interval(client: OpenSearch, index: str, refresh_interval: Optional[Any]) -> Any: + url = f"/{index}/_settings" + body = {"index": {"refresh_interval": refresh_interval}} + response = client.transport.perform_request("PUT", url, headers={"Content-Type": "application/json"}, body=body) + + return response + + +def _disable_refresh_interval( + client: OpenSearch, + index: str, +) -> Any: + return _set_refresh_interval(client=client, index=index, refresh_interval="-1") + + +def create_index( + client: OpenSearch, + index: str, + doc_type: Optional[str] = None, + settings: Optional[Dict[str, Any]] = None, + mappings: Optional[Dict[str, Any]] = None, +) -> Dict[str, Any]: + """Create an index. + + Parameters + ---------- + client : OpenSearch + instance of opensearchpy.OpenSearch to use. + index : str + Name of the index. + doc_type : str, optional + Name of the document type (for Elasticsearch versions 5.x and earlier). + settings : Dict[str, Any], optional + Index settings + https://opensearch.org/docs/opensearch/rest-api/create-index/#index-settings + mappings : Dict[str, Any], optional + Index mappings + https://opensearch.org/docs/opensearch/rest-api/create-index/#mappings + + Returns + ------- + Dict[str, Any] + OpenSearch rest api response + https://opensearch.org/docs/opensearch/rest-api/create-index/#response. + + Examples + -------- + Creating an index. + + >>> import awswrangler as wr + >>> client = wr.opensearch.connect(host='DOMAIN-ENDPOINT') + >>> response = wr.opensearch.create_index( + ... client=client, + ... index="sample-index1", + ... mappings={ + ... "properties": { + ... "age": { "type" : "integer" } + ... } + ... }, + ... settings={ + ... "index": { + ... "number_of_shards": 2, + ... "number_of_replicas": 1 + ... } + ... } + ... ) + + """ + body = {} + if mappings: + if _get_distribution(client) == "opensearch" or _get_version_major(client) >= 7: + body["mappings"] = mappings # doc type deprecated + else: + if doc_type: + body["mappings"] = {doc_type: mappings} + else: + body["mappings"] = {index: mappings} + if settings: + body["settings"] = settings + if body == {}: + body = None # type: ignore + + # ignore 400 cause by IndexAlreadyExistsException when creating an index + response: Dict[str, Any] = client.indices.create(index, body=body, ignore=400) + if "error" in response: + _logger.warning(response) + if str(response["error"]).startswith("MapperParsingException"): + raise ValueError(response["error"]) + return response + + +def delete_index(client: OpenSearch, index: str) -> Dict[str, Any]: + """Create an index. + + Parameters + ---------- + client : OpenSearch + instance of opensearchpy.OpenSearch to use. + index : str + Name of the index. + + Returns + ------- + Dict[str, Any] + OpenSearch rest api response + + Examples + -------- + Creating an index. + + >>> import awswrangler as wr + >>> client = wr.opensearch.connect(host='DOMAIN-ENDPOINT') + >>> response = wr.opensearch.delete_index( + ... client=client, + ... index="sample-index1" + ... ) + + """ + # ignore 400/404 IndexNotFoundError exception + response: Dict[str, Any] = client.indices.delete(index, ignore=[400, 404]) + if "error" in response: + _logger.warning(response) + return response + + +def index_json( + client: OpenSearch, + path: str, + index: str, + doc_type: Optional[str] = None, + boto3_session: Optional[boto3.Session] = boto3.Session(), + json_path: Optional[str] = None, + **kwargs: Any, +) -> Dict[str, Any]: + """Index all documents from JSON file to OpenSearch index. + + The JSON file should be in a JSON-Lines text format (newline-delimited JSON) - https://jsonlines.org/ + OR if the is a single large JSON please provide `json_path`. + + Parameters + ---------- + client : OpenSearch + instance of opensearchpy.OpenSearch to use. + path : str + s3 or local path to the JSON file which contains the documents. + index : str + Name of the index. + doc_type : str, optional + Name of the document type (for Elasticsearch versions 5.x and earlier). + json_path : str, optional + JsonPath expression to specify explicit path to a single name element + in a JSON hierarchical data structure. + Read more about `JsonPath `_ + boto3_session : boto3.Session(), optional + Boto3 Session to be used to access s3 if s3 path is provided. + The default boto3 Session will be used if boto3_session receive None. + **kwargs : + KEYWORD arguments forwarded to :func:`~awswrangler.opensearch.index_documents` + which is used to execute the operation + + Returns + ------- + Dict[str, Any] + Response payload + https://opensearch.org/docs/opensearch/rest-api/document-apis/bulk/#response. + + Examples + -------- + Writing contents of JSON file + + >>> import awswrangler as wr + >>> client = wr.opensearch.connect(host='DOMAIN-ENDPOINT') + >>> wr.opensearch.index_json( + ... client=client, + ... path='docs.json', + ... index='sample-index1' + ... ) + """ + _logger.debug("indexing %s from %s", index, path) + + if boto3_session is None: + raise ValueError("boto3_session cannot be None") + + if path.startswith("s3://"): + bucket, key = parse_path(path) + s3 = boto3_session.client("s3") + obj = s3.get_object(Bucket=bucket, Key=key) + body = obj["Body"].read() + lines = body.splitlines() + documents = [json.loads(line) for line in lines] + if json_path: + documents = _get_documents_w_json_path(documents, json_path) + else: # local path + documents = list(_file_line_generator(path, is_json=True)) + if json_path: + documents = _get_documents_w_json_path(documents, json_path) + return index_documents(client=client, documents=documents, index=index, doc_type=doc_type, **kwargs) + + +def index_csv( + client: OpenSearch, + path: str, + index: str, + doc_type: Optional[str] = None, + pandas_kwargs: Optional[Dict[str, Any]] = None, + **kwargs: Any, +) -> Dict[str, Any]: + """Index all documents from a CSV file to OpenSearch index. + + Parameters + ---------- + client : OpenSearch + instance of opensearchpy.OpenSearch to use. + path : str + s3 or local path to the CSV file which contains the documents. + index : str + Name of the index. + doc_type : str, optional + Name of the document type (for Elasticsearch versions 5.x and earlier). + pandas_kwargs : Dict[str, Any], optional + Dictionary of arguments forwarded to pandas.read_csv(). + e.g. pandas_kwargs={'sep': '|', 'na_values': ['null', 'none']} + https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html + Note: these params values are enforced: `skip_blank_lines=True` + **kwargs : + KEYWORD arguments forwarded to :func:`~awswrangler.opensearch.index_documents` + which is used to execute the operation + + Returns + ------- + Dict[str, Any] + Response payload + https://opensearch.org/docs/opensearch/rest-api/document-apis/bulk/#response. + + Examples + -------- + Writing contents of CSV file + + >>> import awswrangler as wr + >>> client = wr.opensearch.connect(host='DOMAIN-ENDPOINT') + >>> wr.opensearch.index_csv( + ... client=client, + ... path='docs.csv', + ... index='sample-index1' + ... ) + + Writing contents of CSV file using pandas_kwargs + + >>> import awswrangler as wr + >>> client = wr.opensearch.connect(host='DOMAIN-ENDPOINT') + >>> wr.opensearch.index_csv( + ... client=client, + ... path='docs.csv', + ... index='sample-index1', + ... pandas_kwargs={'sep': '|', 'na_values': ['null', 'none']} + ... ) + """ + _logger.debug("indexing %s from %s", index, path) + if pandas_kwargs is None: + pandas_kwargs = {} + enforced_pandas_params = { + "skip_blank_lines": True, + # 'na_filter': True # will generate Nan value for empty cells. We remove Nan keys in _df_doc_generator + # Note: if the user will pass na_filter=False null fields will be indexed as well ({"k1": null, "k2": null}) + } + pandas_kwargs.update(enforced_pandas_params) + df = pd.read_csv(path, **pandas_kwargs) + return index_df(client, df=df, index=index, doc_type=doc_type, **kwargs) + + +def index_df( + client: OpenSearch, df: pd.DataFrame, index: str, doc_type: Optional[str] = None, **kwargs: Any +) -> Dict[str, Any]: + """Index all documents from a DataFrame to OpenSearch index. + + Parameters + ---------- + client : OpenSearch + instance of opensearchpy.OpenSearch to use. + df : pd.DataFrame + Pandas DataFrame https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html + index : str + Name of the index. + doc_type : str, optional + Name of the document type (for Elasticsearch versions 5.x and earlier). + **kwargs : + KEYWORD arguments forwarded to :func:`~awswrangler.opensearch.index_documents` + which is used to execute the operation + + Returns + ------- + Dict[str, Any] + Response payload + https://opensearch.org/docs/opensearch/rest-api/document-apis/bulk/#response. + + Examples + -------- + Writing rows of DataFrame + + >>> import awswrangler as wr + >>> import pandas as pd + >>> client = wr.opensearch.connect(host='DOMAIN-ENDPOINT') + >>> wr.opensearch.index_df( + ... client=client, + ... df=pd.DataFrame([{'_id': '1'}, {'_id': '2'}, {'_id': '3'}]), + ... index='sample-index1' + ... ) + """ + return index_documents(client=client, documents=_df_doc_generator(df), index=index, doc_type=doc_type, **kwargs) + + +def index_documents( + client: OpenSearch, + documents: Iterable[Mapping[str, Any]], + index: str, + doc_type: Optional[str] = None, + keys_to_write: Optional[List[str]] = None, + id_keys: Optional[List[str]] = None, + ignore_status: Optional[Union[List[Any], Tuple[Any]]] = None, + bulk_size: int = 1000, + chunk_size: Optional[int] = 500, + max_chunk_bytes: Optional[int] = 100 * 1024 * 1024, + max_retries: Optional[int] = 5, + initial_backoff: Optional[int] = 2, + max_backoff: Optional[int] = 600, + **kwargs: Any, +) -> Dict[str, Any]: + """Index all documents to OpenSearch index. + + Note + ---- + Some of the args are referenced from opensearch-py client library (bulk helpers) + https://opensearch-py.readthedocs.io/en/latest/helpers.html#opensearchpy.helpers.bulk + https://opensearch-py.readthedocs.io/en/latest/helpers.html#opensearchpy.helpers.streaming_bulk + + If you receive `Error 429 (Too Many Requests) /_bulk` please to to decrease `bulk_size` value. + Please also consider modifying the cluster size and instance type - + Read more here: https://aws.amazon.com/premiumsupport/knowledge-center/resolve-429-error-es/ + + Parameters + ---------- + client : OpenSearch + instance of opensearchpy.OpenSearch to use. + documents : Iterable[Mapping[str, Any]] + List which contains the documents that will be inserted. + index : str + Name of the index. + doc_type : str, optional + Name of the document type (for Elasticsearch versions 5.x and earlier). + keys_to_write : List[str], optional + list of keys to index. If not provided all keys will be indexed + id_keys : List[str], optional + list of keys that compound document unique id. If not provided will use `_id` key if exists, + otherwise will generate unique identifier for each document. + ignore_status: Union[List[Any], Tuple[Any]], optional + list of HTTP status codes that you want to ignore (not raising an exception) + bulk_size: int, + number of docs in each _bulk request (default: 1000) + chunk_size : int, optional + number of docs in one chunk sent to es (default: 500) + max_chunk_bytes: int, optional + the maximum size of the request in bytes (default: 100MB) + max_retries : int, optional + maximum number of times a document will be retried when + ``429`` is received, set to 0 (default) for no retries on ``429`` (default: 2) + initial_backoff : int, optional + number of seconds we should wait before the first retry. + Any subsequent retries will be powers of ``initial_backoff*2**retry_number`` (default: 2) + max_backoff: int, optional + maximum number of seconds a retry will wait (default: 600) + **kwargs : + KEYWORD arguments forwarded to bulk operation + elasticsearch >= 7.10.2 / opensearch: \ +https://opensearch.org/docs/opensearch/rest-api/document-apis/bulk/#url-parameters + elasticsearch < 7.10.2: \ +https://opendistro.github.io/for-elasticsearch-docs/docs/elasticsearch/rest-api-reference/#url-parameters + + Returns + ------- + Dict[str, Any] + Response payload + https://opensearch.org/docs/opensearch/rest-api/document-apis/bulk/#response. + + Examples + -------- + Writing documents + + >>> import awswrangler as wr + >>> client = wr.opensearch.connect(host='DOMAIN-ENDPOINT') + >>> wr.opensearch.index_documents( + ... documents=[{'_id': '1', 'value': 'foo'}, {'_id': '2', 'value': 'bar'}], + ... index='sample-index1' + ... ) + """ + if not isinstance(documents, list): + documents = list(documents) + total_documents = len(documents) + _logger.debug("indexing %s documents into %s", total_documents, index) + + actions = _actions_generator( + documents, index, doc_type, keys_to_write=keys_to_write, id_keys=id_keys, bulk_size=bulk_size + ) + + success = 0 + errors: List[Any] = [] + refresh_interval = None + try: + widgets = [ + progressbar.Percentage(), + progressbar.SimpleProgress(format=" (%(value_s)s/%(max_value_s)s)"), + progressbar.Bar(), + progressbar.Timer(), + ] + progress_bar = progressbar.ProgressBar(widgets=widgets, max_value=total_documents, prefix="Indexing: ").start() + for i, bulk_chunk_documents in enumerate(actions): + if i == 1: # second bulk iteration, in case the index didn't exist before + refresh_interval = _get_refresh_interval(client, index) + _disable_refresh_interval(client, index) + _logger.debug("running bulk index of %s documents", len(bulk_chunk_documents)) + _success, _errors = bulk( + client=client, + actions=bulk_chunk_documents, + ignore_status=ignore_status, + chunk_size=chunk_size, + max_chunk_bytes=max_chunk_bytes, + max_retries=max_retries, + initial_backoff=initial_backoff, + max_backoff=max_backoff, + request_timeout=30, + **kwargs, + ) + success += _success + errors += _errors # type: ignore + _logger.debug("indexed %s documents (%s/%s)", _success, success, total_documents) + progress_bar.update(success, force=True) + except TransportError as e: + if str(e.status_code) == "429": # Too Many Requests + _logger.error( + "Error 429 (Too Many Requests):" + "Try to tune bulk_size parameter." + "Read more here: https://aws.amazon.com/premiumsupport/knowledge-center/resolve-429-error-es" + ) + raise e + + finally: + _set_refresh_interval(client, index, refresh_interval) + + return {"success": success, "errors": errors} diff --git a/awswrangler/postgresql.py b/awswrangler/postgresql.py index 181907065..c654508fe 100644 --- a/awswrangler/postgresql.py +++ b/awswrangler/postgresql.py @@ -145,7 +145,7 @@ def connect( attrs: _db_utils.ConnectionAttributes = _db_utils.get_connection_attributes( connection=connection, secret_id=secret_id, catalog_id=catalog_id, dbname=dbname, boto3_session=boto3_session ) - if attrs.kind != "postgresql" and attrs.kind != "postgres": + if attrs.kind not in ("postgresql", "postgres"): raise exceptions.InvalidDatabaseType( f"Invalid connection type ({attrs.kind}. It must be a postgresql connection.)" ) diff --git a/awswrangler/redshift.py b/awswrangler/redshift.py index 2c99d5171..796fe5920 100644 --- a/awswrangler/redshift.py +++ b/awswrangler/redshift.py @@ -210,7 +210,7 @@ def _redshift_types_from_path( parquet_infer_sampling: float, path_suffix: Optional[str], path_ignore_suffix: Optional[str], - use_threads: bool, + use_threads: Union[bool, int], boto3_session: Optional[boto3.Session], s3_additional_kwargs: Optional[Dict[str, str]], ) -> Dict[str, str]: @@ -257,7 +257,7 @@ def _create_table( # pylint: disable=too-many-locals,too-many-arguments parquet_infer_sampling: float = 1.0, path_suffix: Optional[str] = None, path_ignore_suffix: Optional[str] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, str]] = None, ) -> Tuple[str, Optional[str]]: @@ -342,7 +342,7 @@ def _create_table( # pylint: disable=too-many-locals,too-many-arguments def _read_parquet_iterator( path: str, keep_files: bool, - use_threads: bool, + use_threads: Union[bool, int], categories: Optional[List[str]], chunked: Union[bool, int], boto3_session: Optional[boto3.Session], @@ -864,7 +864,6 @@ def unload_to_files( max_file_size: Optional[float] = None, kms_key_id: Optional[str] = None, manifest: bool = False, - use_threads: bool = True, partition_cols: Optional[List[str]] = None, boto3_session: Optional[boto3.Session] = None, ) -> None: @@ -910,9 +909,6 @@ def unload_to_files( kms_key_id : str, optional Specifies the key ID for an AWS Key Management Service (AWS KMS) key to be used to encrypt data files on Amazon S3. - use_threads : bool - True to enable concurrent requests, False to disable multiple threads. - If enabled os.cpu_count() will be used as the max number of threads. manifest : bool Unload a manifest file on S3. partition_cols: List[str], optional @@ -941,7 +937,6 @@ def unload_to_files( if unload_format not in [None, "CSV", "PARQUET"]: raise exceptions.InvalidArgumentValue(" argument must be 'CSV' or 'PARQUET'") session: boto3.Session = _utils.ensure_session(session=boto3_session) - s3.delete_objects(path=path, use_threads=use_threads, boto3_session=session) with con.cursor() as cursor: format_str: str = unload_format or "PARQUET" partition_str: str = f"\nPARTITION BY ({','.join(partition_cols)})" if partition_cols else "" @@ -955,7 +950,7 @@ def unload_to_files( aws_access_key_id=aws_access_key_id, aws_secret_access_key=aws_secret_access_key, aws_session_token=aws_session_token, - boto3_session=boto3_session, + boto3_session=session, ) sql = ( @@ -990,7 +985,7 @@ def unload( categories: Optional[List[str]] = None, chunked: Union[bool, int] = False, keep_files: bool = False, - use_threads: bool = True, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, str]] = None, ) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: @@ -1066,9 +1061,10 @@ def unload( If passed will split the data in a Iterable of DataFrames (Memory friendly). If `True` wrangler will iterate on the data by files in the most efficient way without guarantee of chunksize. If an `INTEGER` is passed Wrangler will iterate on the data by number of rows igual the received INTEGER. - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs: @@ -1106,7 +1102,6 @@ def unload( max_file_size=max_file_size, kms_key_id=kms_key_id, manifest=False, - use_threads=use_threads, boto3_session=session, ) if chunked is False: @@ -1157,7 +1152,7 @@ def copy_from_files( # pylint: disable=too-many-locals,too-many-arguments serialize_to_json: bool = False, path_suffix: Optional[str] = None, path_ignore_suffix: Optional[str] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, lock: bool = False, commit_transaction: bool = True, boto3_session: Optional[boto3.Session] = None, @@ -1243,9 +1238,10 @@ def copy_from_files( # pylint: disable=too-many-locals,too-many-arguments (e.g. [".csv", "_SUCCESS"]). Only has effect during the table creation. If None, will try to read all files. (default) - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. lock : bool True to execute LOCK command inside the transaction to force serializable isolation. commit_transaction: bool @@ -1356,7 +1352,7 @@ def copy( # pylint: disable=too-many-arguments varchar_lengths: Optional[Dict[str, int]] = None, serialize_to_json: bool = False, keep_files: bool = False, - use_threads: bool = True, + use_threads: Union[bool, int] = True, lock: bool = False, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, str]] = None, @@ -1442,9 +1438,10 @@ def copy( # pylint: disable=too-many-arguments Dict of VARCHAR length by columns. (e.g. {"col1": 10, "col5": 200}). keep_files : bool Should keep stage files? - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. lock : bool True to execute LOCK command inside the transaction to force serializable isolation. boto3_session : boto3.Session(), optional diff --git a/awswrangler/s3/_copy.py b/awswrangler/s3/_copy.py index ef983f2e0..fca198865 100644 --- a/awswrangler/s3/_copy.py +++ b/awswrangler/s3/_copy.py @@ -1,7 +1,7 @@ """Amazon S3 Copy Module (PRIVATE).""" import logging -from typing import Any, Dict, List, Optional, Tuple +from typing import Any, Dict, List, Optional, Tuple, Union import boto3 from boto3.s3.transfer import TransferConfig @@ -16,7 +16,7 @@ def _copy_objects( batch: List[Tuple[str, str]], - use_threads: bool, + use_threads: Union[bool, int], boto3_session: boto3.Session, s3_additional_kwargs: Optional[Dict[str, Any]], ) -> None: @@ -46,7 +46,7 @@ def merge_datasets( target_path: str, mode: str = "append", ignore_empty: bool = False, - use_threads: bool = True, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> List[str]: @@ -79,9 +79,10 @@ def merge_datasets( ``append`` (Default), ``overwrite``, ``overwrite_partitions``. ignore_empty: bool Ignore files with 0 bytes. - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] @@ -160,7 +161,7 @@ def copy_objects( source_path: str, target_path: str, replace_filenames: Optional[Dict[str, str]] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> List[str]: @@ -181,9 +182,10 @@ def copy_objects( S3 Path for the target directory. replace_filenames : Dict[str, str], optional e.g. {"old_name.csv": "new_name.csv", "old_name2.csv": "new_name2.csv"} - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] diff --git a/awswrangler/s3/_delete.py b/awswrangler/s3/_delete.py index bf9ee3ca8..5c9214eb6 100644 --- a/awswrangler/s3/_delete.py +++ b/awswrangler/s3/_delete.py @@ -83,7 +83,7 @@ def _delete_objects_concurrent( def delete_objects( path: Union[str, List[str]], - use_threads: bool = True, + use_threads: Union[bool, int] = True, last_modified_begin: Optional[datetime.datetime] = None, last_modified_end: Optional[datetime.datetime] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, @@ -111,9 +111,10 @@ def delete_objects( path : Union[str, List[str]] S3 prefix (accepts Unix shell-style wildcards) (e.g. s3://bucket/prefix) or list of S3 objects paths (e.g. [s3://bucket/key0, s3://bucket/key1]). - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. last_modified_begin Filter the s3 files by the Last modified date of the object. The filter is applied only after list all s3 files. diff --git a/awswrangler/s3/_describe.py b/awswrangler/s3/_describe.py index a4670bb4b..3728d5245 100644 --- a/awswrangler/s3/_describe.py +++ b/awswrangler/s3/_describe.py @@ -55,7 +55,7 @@ def _describe_object_concurrent( def describe_objects( path: Union[str, List[str]], version_id: Optional[Union[str, Dict[str, str]]] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, last_modified_begin: Optional[datetime.datetime] = None, last_modified_end: Optional[datetime.datetime] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, @@ -90,9 +90,10 @@ def describe_objects( version_id: Optional[Union[str, Dict[str, str]]] Version id of the object or mapping of object path to version id. (e.g. {'s3://bucket/key0': '121212', 's3://bucket/key1': '343434'}) - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. last_modified_begin Filter the s3 files by the Last modified date of the object. The filter is applied only after list all s3 files. @@ -168,7 +169,7 @@ def describe_objects( def size_objects( path: Union[str, List[str]], version_id: Optional[Union[str, Dict[str, str]]] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, s3_additional_kwargs: Optional[Dict[str, Any]] = None, boto3_session: Optional[boto3.Session] = None, ) -> Dict[str, Optional[int]]: @@ -193,9 +194,10 @@ def size_objects( version_id: Optional[Union[str, Dict[str, str]]] Version id of the object or mapping of object path to version id. (e.g. {'s3://bucket/key0': '121212', 's3://bucket/key1': '343434'}) - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. s3_additional_kwargs : Optional[Dict[str, Any]] Forwarded to botocore requests. e.g. s3_additional_kwargs={'RequestPayer': 'requester'} diff --git a/awswrangler/s3/_download.py b/awswrangler/s3/_download.py index 61b46068e..d382efb33 100644 --- a/awswrangler/s3/_download.py +++ b/awswrangler/s3/_download.py @@ -15,7 +15,7 @@ def download( path: str, local_file: Union[str, Any], version_id: Optional[str] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> None: @@ -34,9 +34,10 @@ def download( A file-like object in binary mode or a path to local file (e.g. ``./local/path/to/key0``). version_id: Optional[str] Version id of the object. - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] diff --git a/awswrangler/s3/_fs.py b/awswrangler/s3/_fs.py index 183ff7f30..db84f3687 100644 --- a/awswrangler/s3/_fs.py +++ b/awswrangler/s3/_fs.py @@ -186,7 +186,7 @@ def __init__( self._version_id = version_id self._boto3_session: boto3.Session = _utils.ensure_session(session=boto3_session) if mode not in {"rb", "wb", "r", "w"}: - raise NotImplementedError("File mode must be {'rb', 'wb', 'r', 'w'}, not %s" % mode) + raise NotImplementedError(f"File mode must be {'rb', 'wb', 'r', 'w'}, not {mode}") self._mode: str = "rb" if mode is None else mode self._one_shot_download: bool = False if 0 < s3_block_size < 3: diff --git a/awswrangler/s3/_merge_upsert_table.py b/awswrangler/s3/_merge_upsert_table.py index a5f16233a..3044c7dc1 100644 --- a/awswrangler/s3/_merge_upsert_table.py +++ b/awswrangler/s3/_merge_upsert_table.py @@ -48,7 +48,7 @@ def _is_data_quality_sufficient( existing_df: pandas.DataFrame, delta_df: pandas.DataFrame, primary_key: List[str] ) -> bool: """Check data quality of existing table and the new delta feed.""" - error_messages = list() + error_messages = [] existing_schema = _data_types.pyarrow_types_from_pandas(df=existing_df, index=False) delta_schema = _data_types.pyarrow_types_from_pandas(df=delta_df, index=False) # Check for duplicates on the primary key in the existing table diff --git a/awswrangler/s3/_read_excel.py b/awswrangler/s3/_read_excel.py index 35ff815d0..db166279a 100644 --- a/awswrangler/s3/_read_excel.py +++ b/awswrangler/s3/_read_excel.py @@ -47,6 +47,7 @@ def read_excel( True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. If given an int will use the given amount of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] diff --git a/awswrangler/s3/_read_parquet.py b/awswrangler/s3/_read_parquet.py index 6b4ba0c54..2d429b0fb 100644 --- a/awswrangler/s3/_read_parquet.py +++ b/awswrangler/s3/_read_parquet.py @@ -17,6 +17,7 @@ from awswrangler import _data_types, _utils, exceptions from awswrangler._config import apply_configs +from awswrangler.catalog._get import _get_partitions from awswrangler.s3._fs import open_s3_object from awswrangler.s3._list import _path2list from awswrangler.s3._read import ( @@ -34,10 +35,18 @@ def _pyarrow_parquet_file_wrapper( - source: Any, read_dictionary: Optional[List[str]] = None + source: Any, read_dictionary: Optional[List[str]] = None, coerce_int96_timestamp_unit: Optional[str] = None ) -> pyarrow.parquet.ParquetFile: try: - return pyarrow.parquet.ParquetFile(source=source, read_dictionary=read_dictionary) + try: + return pyarrow.parquet.ParquetFile( + source=source, read_dictionary=read_dictionary, coerce_int96_timestamp_unit=coerce_int96_timestamp_unit + ) + except TypeError as ex: + if "got an unexpected keyword argument" in str(ex): + _logger.warning("coerce_int96_timestamp_unit is not supported in pyarrow 2 and below") + return pyarrow.parquet.ParquetFile(source=source, read_dictionary=read_dictionary) + raise except pyarrow.ArrowInvalid as ex: if str(ex) == "Parquet file size is 0 bytes": _logger.warning("Ignoring empty file...xx") @@ -51,7 +60,9 @@ def _read_parquet_metadata_file( s3_additional_kwargs: Optional[Dict[str, str]], use_threads: Union[bool, int], version_id: Optional[str] = None, + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> Optional[Dict[str, str]]: + pyarrow_args = _set_default_pyarrow_additional_kwargs(pyarrow_additional_kwargs) with open_s3_object( path=path, mode="rb", @@ -61,7 +72,9 @@ def _read_parquet_metadata_file( s3_additional_kwargs=s3_additional_kwargs, boto3_session=boto3_session, ) as f: - pq_file: Optional[pyarrow.parquet.ParquetFile] = _pyarrow_parquet_file_wrapper(source=f) + pq_file: Optional[pyarrow.parquet.ParquetFile] = _pyarrow_parquet_file_wrapper( + source=f, coerce_int96_timestamp_unit=pyarrow_args["coerce_int96_timestamp_unit"] + ) if pq_file is None: return None return _data_types.athena_types_from_pyarrow_schema(schema=pq_file.schema.to_arrow_schema(), partitions=None)[0] @@ -74,7 +87,9 @@ def _read_schemas_from_files( boto3_session: boto3.Session, s3_additional_kwargs: Optional[Dict[str, str]], version_ids: Optional[Dict[str, str]] = None, + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> Tuple[Dict[str, str], ...]: + paths = _utils.list_sampling(lst=paths, sampling=sampling) schemas: Tuple[Optional[Dict[str, str]], ...] = tuple() n_paths: int = len(paths) @@ -87,6 +102,7 @@ def _read_schemas_from_files( s3_additional_kwargs=s3_additional_kwargs, use_threads=use_threads, version_id=version_ids.get(p) if isinstance(version_ids, dict) else None, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, ) for p in paths ) @@ -101,6 +117,7 @@ def _read_schemas_from_files( itertools.repeat(s3_additional_kwargs), itertools.repeat(use_threads), versions, + itertools.repeat(pyarrow_additional_kwargs), ) ) schemas = cast(Tuple[Dict[str, str], ...], tuple(x for x in schemas if x is not None)) @@ -127,6 +144,7 @@ def _validate_schemas_from_files( boto3_session: boto3.Session, s3_additional_kwargs: Optional[Dict[str, str]], version_ids: Optional[Dict[str, str]] = None, + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> None: schemas: Tuple[Dict[str, str], ...] = _read_schemas_from_files( paths=paths, @@ -135,6 +153,7 @@ def _validate_schemas_from_files( boto3_session=boto3_session, s3_additional_kwargs=s3_additional_kwargs, version_ids=version_ids, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, ) _validate_schemas(schemas=schemas) @@ -163,6 +182,7 @@ def _read_parquet_metadata( boto3_session: boto3.Session, s3_additional_kwargs: Optional[Dict[str, str]], version_id: Optional[Union[str, Dict[str, str]]] = None, + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> Tuple[Dict[str, str], Optional[Dict[str, str]], Optional[Dict[str, List[str]]]]: """Handle wr.s3.read_parquet_metadata internally.""" path_root: Optional[str] = _get_path_root(path=path, dataset=dataset) @@ -187,6 +207,7 @@ def _read_parquet_metadata( else {paths[0]: version_id} if isinstance(version_id, str) else None, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, ) columns_types: Dict[str, str] = _merge_schemas(schemas=schemas) @@ -265,10 +286,12 @@ def _arrowtable2df( dataset: bool, path: str, path_root: Optional[str], + timestamp_as_object: bool = False, ) -> pd.DataFrame: metadata: Dict[str, Any] = {} if table.schema.metadata is not None and b"pandas" in table.schema.metadata: metadata = json.loads(table.schema.metadata[b"pandas"]) + if type(use_threads) == int: # pylint: disable=unidiomatic-typecheck use_threads = bool(use_threads > 1) df: pd.DataFrame = _apply_partitions( @@ -278,6 +301,7 @@ def _arrowtable2df( self_destruct=True, integer_object_nulls=False, date_as_object=True, + timestamp_as_object=timestamp_as_object, ignore_metadata=True, strings_to_categorical=False, safe=safe, @@ -343,9 +367,12 @@ def _read_parquet_chunked( # pylint: disable=too-many-branches s3_additional_kwargs: Optional[Dict[str, str]], use_threads: Union[bool, int], version_ids: Optional[Dict[str, str]] = None, + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> Iterator[pd.DataFrame]: next_slice: Optional[pd.DataFrame] = None last_schema: Optional[Dict[str, str]] = None + + pyarrow_args = _set_default_pyarrow_additional_kwargs(pyarrow_additional_kwargs) last_path: str = "" for path in paths: with open_s3_object( @@ -358,7 +385,9 @@ def _read_parquet_chunked( # pylint: disable=too-many-branches boto3_session=boto3_session, ) as f: pq_file: Optional[pyarrow.parquet.ParquetFile] = _pyarrow_parquet_file_wrapper( - source=f, read_dictionary=categories + source=f, + read_dictionary=categories, + coerce_int96_timestamp_unit=pyarrow_args["coerce_int96_timestamp_unit"], ) if pq_file is None: continue @@ -398,6 +427,7 @@ def _read_parquet_chunked( # pylint: disable=too-many-branches dataset=dataset, path=path, path_root=path_root, + timestamp_as_object=pyarrow_args["timestamp_as_object"], ) if chunked is True: yield df @@ -425,7 +455,9 @@ def _read_parquet_file( s3_additional_kwargs: Optional[Dict[str, str]], use_threads: Union[bool, int], version_id: Optional[str] = None, + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> pa.Table: + pyarrow_args = _set_default_pyarrow_additional_kwargs(pyarrow_additional_kwargs) s3_block_size: int = 20_971_520 if columns else -1 # One shot for a full read otherwise 20 MB (20 * 2**20) with open_s3_object( path=path, @@ -437,7 +469,9 @@ def _read_parquet_file( boto3_session=boto3_session, ) as f: pq_file: Optional[pyarrow.parquet.ParquetFile] = _pyarrow_parquet_file_wrapper( - source=f, read_dictionary=categories + source=f, + read_dictionary=categories, + coerce_int96_timestamp_unit=pyarrow_args["coerce_int96_timestamp_unit"], ) if pq_file is None: raise exceptions.InvalidFile(f"Invalid Parquet file: {path}") @@ -482,7 +516,9 @@ def _read_parquet( path_root: Optional[str], s3_additional_kwargs: Optional[Dict[str, str]], use_threads: Union[bool, int], + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> pd.DataFrame: + pyarrow_args = _set_default_pyarrow_additional_kwargs(pyarrow_additional_kwargs) boto3_session = _utils.ensure_session(boto3_session) return _arrowtable2df( table=_read_parquet_file( @@ -493,6 +529,7 @@ def _read_parquet( s3_additional_kwargs=s3_additional_kwargs, use_threads=use_threads, version_id=version_id, + pyarrow_additional_kwargs=pyarrow_args, ), categories=categories, safe=safe, @@ -501,11 +538,13 @@ def _read_parquet( dataset=dataset, path=path, path_root=path_root, + timestamp_as_object=pyarrow_args["timestamp_as_object"], ) def read_parquet( path: Union[str, List[str]], + path_root: Optional[str] = None, path_suffix: Union[str, List[str], None] = None, path_ignore_suffix: Union[str, List[str], None] = None, version_id: Optional[Union[str, Dict[str, str]]] = None, @@ -524,6 +563,7 @@ def read_parquet( last_modified_end: Optional[datetime.datetime] = None, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> Union[pd.DataFrame, Iterator[pd.DataFrame]]: """Read Apache Parquet file(s) from from a received S3 prefix or list of S3 objects paths. @@ -565,6 +605,8 @@ def read_parquet( path : Union[str, List[str]] S3 prefix (accepts Unix shell-style wildcards) (e.g. s3://bucket/prefix) or list of S3 objects paths (e.g. [s3://bucket/key0, s3://bucket/key1]). + path_root : Optional[str] + Root path of the table. If dataset=`True`, will be used as a starting point to load partition columns. path_suffix: Union[str, List[str], None] Suffix or List of suffixes to be read (e.g. [".gz.parquet", ".snappy.parquet"]). If None, will try to read all files. (default) @@ -612,7 +654,7 @@ def read_parquet( use_threads : Union[bool, int] True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. - If given an int will use the given amount of threads. + If integer is provided, specified number is used. last_modified_begin Filter the s3 files by the Last modified date of the object. The filter is applied only after list all s3 files. @@ -623,6 +665,14 @@ def read_parquet( Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] Forward to botocore requests, only "SSECustomerAlgorithm" and "SSECustomerKey" arguments will be considered. + pyarrow_additional_kwargs : Optional[Dict[str, Any]] + Forward to the ParquetFile class or converting an Arrow table to Pandas, currently only an + "coerce_int96_timestamp_unit" or "timestamp_as_object" argument will be considered. If reading parquet + files where you cannot convert a timestamp to pandas Timestamp[ns] consider setting timestamp_as_object=True, + to allow for timestamp units larger than "ns". If reading parquet data that still uses INT96 (like Athena + outputs) you can use coerce_int96_timestamp_unit to specify what timestamp unit to encode INT96 to (by default + this is "ns", if you know the output parquet came from a system that encodes timestamp to a particular unit + then set this to that same unit e.g. coerce_int96_timestamp_unit="ms"). Returns ------- @@ -676,12 +726,14 @@ def read_parquet( versions: Optional[Dict[str, str]] = ( version_id if isinstance(version_id, dict) else {paths[0]: version_id} if isinstance(version_id, str) else None ) - path_root: Optional[str] = _get_path_root(path=path, dataset=dataset) - if path_root is not None: + if path_root is None: + path_root = _get_path_root(path=path, dataset=dataset) + if path_root is not None and partition_filter is not None: paths = _apply_partition_filter(path_root=path_root, paths=paths, filter_func=partition_filter) if len(paths) < 1: raise exceptions.NoFilesFound(f"No files Found on: {path}.") _logger.debug("paths:\n%s", paths) + args: Dict[str, Any] = { "columns": columns, "categories": categories, @@ -692,6 +744,7 @@ def read_parquet( "path_root": path_root, "s3_additional_kwargs": s3_additional_kwargs, "use_threads": use_threads, + "pyarrow_additional_kwargs": pyarrow_additional_kwargs, } _logger.debug("args:\n%s", pprint.pformat(args)) if chunked is not False: @@ -788,7 +841,7 @@ def read_parquet_table( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.12.1/tutorials/023%20-%20Flexible%20Partitions%20Filter.html columns : List[str], optional Names of columns to read from the file(s). validate_schema: @@ -813,7 +866,7 @@ def read_parquet_table( use_threads : Union[bool, int] True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. - If given an int will use the given amount of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] @@ -867,11 +920,37 @@ def read_parquet_table( path: str = location if location.endswith("/") else f"{location}/" except KeyError as ex: raise exceptions.InvalidTable(f"Missing s3 location for {database}.{table}.") from ex + path_root: Optional[str] = None + paths: Union[str, List[str]] = path + # If filter is available, fetch & filter out partitions + # Then list objects & process individual object keys under path_root + if partition_filter is not None: + available_partitions_dict = _get_partitions( + database=database, + table=table, + catalog_id=catalog_id, + boto3_session=boto3_session, + ) + available_partitions = list(available_partitions_dict.keys()) + if available_partitions: + paths = [] + path_root = path + partitions: Union[str, List[str]] = _apply_partition_filter( + path_root=path_root, paths=available_partitions, filter_func=partition_filter + ) + for partition in partitions: + paths += _path2list( + path=partition, + boto3_session=boto3_session, + suffix=filename_suffix, + ignore_suffix=_get_path_ignore_suffix(path_ignore_suffix=filename_ignore_suffix), + s3_additional_kwargs=s3_additional_kwargs, + ) df = read_parquet( - path=path, - path_suffix=filename_suffix, - path_ignore_suffix=filename_ignore_suffix, - partition_filter=partition_filter, + path=paths, + path_root=path_root, + path_suffix=filename_suffix if path_root is None else None, + path_ignore_suffix=filename_ignore_suffix if path_root is None else None, columns=columns, validate_schema=validate_schema, categories=categories, @@ -904,9 +983,10 @@ def read_parquet_metadata( dtype: Optional[Dict[str, str]] = None, sampling: float = 1.0, dataset: bool = False, - use_threads: bool = True, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> Tuple[Dict[str, str], Optional[Dict[str, str]]]: """Read Apache Parquet file(s) metadata from from a received S3 prefix or list of S3 objects paths. @@ -951,13 +1031,17 @@ def read_parquet_metadata( The lower, the faster. dataset: bool If True read a parquet dataset instead of simple file(s) loading all the related partitions as columns. - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] Forward to botocore requests, only "SSECustomerAlgorithm" and "SSECustomerKey" arguments will be considered. + pyarrow_additional_kwargs: Optional[Dict[str, Any]] + Forward kwargs to parquet reader currently only excepts "coerce_int96_timestamp_unit". Which can be used to cast + deprecated Parquet INT96 into a specified timestamp unit (e.g. "ms"). Returns ------- @@ -995,4 +1079,19 @@ def read_parquet_metadata( use_threads=use_threads, s3_additional_kwargs=s3_additional_kwargs, boto3_session=_utils.ensure_session(session=boto3_session), + pyarrow_additional_kwargs=pyarrow_additional_kwargs, )[:2] + + +def _set_default_pyarrow_additional_kwargs(pyarrow_additional_kwargs: Optional[Dict[str, Any]]) -> Dict[str, Any]: + if pyarrow_additional_kwargs is None: + pyarrow_additional_kwargs = {} + defaults = { + "coerce_int96_timestamp_unit": None, + "timestamp_as_object": False, + } + defaulted_args = { + **defaults, + **pyarrow_additional_kwargs, + } + return defaulted_args diff --git a/awswrangler/s3/_read_text.py b/awswrangler/s3/_read_text.py index a51dd4ed6..4ca7533ba 100644 --- a/awswrangler/s3/_read_text.py +++ b/awswrangler/s3/_read_text.py @@ -42,7 +42,7 @@ def _read_text_chunked( pandas_kwargs: Dict[str, Any], s3_additional_kwargs: Optional[Dict[str, str]], dataset: bool, - use_threads: bool, + use_threads: Union[bool, int], version_ids: Optional[Dict[str, str]] = None, ) -> Iterator[pd.DataFrame]: for path in paths: @@ -73,7 +73,7 @@ def _read_text_file( pandas_kwargs: Dict[str, Any], s3_additional_kwargs: Optional[Dict[str, str]], dataset: bool, - use_threads: bool, + use_threads: Union[bool, int], ) -> pd.DataFrame: boto3_session = _utils.ensure_session(boto3_session) mode, encoding, newline = _get_read_details(path=path, pandas_kwargs=pandas_kwargs) @@ -219,7 +219,7 @@ def read_csv( use_threads : Union[bool, int] True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. - If given an int will use the given amount of threads. + If integer is provided, specified number is used. last_modified_begin Filter the s3 files by the Last modified date of the object. The filter is applied only after list all s3 files. @@ -241,7 +241,7 @@ def read_csv( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.12.1/tutorials/023%20-%20Flexible%20Partitions%20Filter.html pandas_kwargs : KEYWORD arguments forwarded to pandas.read_csv(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. @@ -367,7 +367,7 @@ def read_fwf( use_threads : Union[bool, int] True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. - If given an int will use the given amount of threads. + If integer is provided, specified number is used. last_modified_begin Filter the s3 files by the Last modified date of the object. The filter is applied only after list all s3 files. @@ -389,7 +389,7 @@ def read_fwf( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.12.1/tutorials/023%20-%20Flexible%20Partitions%20Filter.html pandas_kwargs: KEYWORD arguments forwarded to pandas.read_fwf(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. @@ -518,7 +518,7 @@ def read_json( use_threads : Union[bool, int] True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. - If given an int will use the given amount of threads. + If integer is provided, specified number is used. last_modified_begin Filter the s3 files by the Last modified date of the object. The filter is applied only after list all s3 files. @@ -541,7 +541,7 @@ def read_json( This function MUST return a bool, True to read the partition or False to ignore it. Ignored if `dataset=False`. E.g ``lambda x: True if x["year"] == "2020" and x["month"] == "1" else False`` - https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/023%20-%20Flexible%20Partitions%20Filter.html + https://aws-data-wrangler.readthedocs.io/en/2.12.1/tutorials/023%20-%20Flexible%20Partitions%20Filter.html pandas_kwargs: KEYWORD arguments forwarded to pandas.read_json(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. diff --git a/awswrangler/s3/_upload.py b/awswrangler/s3/_upload.py index c8427def4..2c188e09c 100644 --- a/awswrangler/s3/_upload.py +++ b/awswrangler/s3/_upload.py @@ -14,7 +14,7 @@ def upload( local_file: Union[str, Any], path: str, - use_threads: bool = True, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, ) -> None: @@ -31,9 +31,10 @@ def upload( A file-like object in binary mode or a path to local file (e.g. ``./local/path/to/key0``). path : str S3 path (e.g. ``s3://bucket/key0``). - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] diff --git a/awswrangler/s3/_wait.py b/awswrangler/s3/_wait.py index bf87dd004..3883b3d41 100644 --- a/awswrangler/s3/_wait.py +++ b/awswrangler/s3/_wait.py @@ -3,7 +3,7 @@ import concurrent.futures import itertools import logging -from typing import List, Optional, Tuple +from typing import List, Optional, Tuple, Union import boto3 @@ -35,7 +35,7 @@ def _wait_objects( paths: List[str], delay: Optional[float] = None, max_attempts: Optional[int] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, ) -> None: delay = 5 if delay is None else delay @@ -77,7 +77,7 @@ def wait_objects_exist( paths: List[str], delay: Optional[float] = None, max_attempts: Optional[int] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, ) -> None: """Wait Amazon S3 objects exist. @@ -99,9 +99,10 @@ def wait_objects_exist( The amount of time in seconds to wait between attempts. Default: 5 max_attempts : int, optional The maximum number of attempts to be made. Default: 20 - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. @@ -130,7 +131,7 @@ def wait_objects_not_exist( paths: List[str], delay: Optional[float] = None, max_attempts: Optional[int] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, ) -> None: """Wait Amazon S3 objects not exist. @@ -152,9 +153,10 @@ def wait_objects_not_exist( The amount of time in seconds to wait between attempts. Default: 5 max_attempts : int, optional The maximum number of attempts to be made. Default: 20 - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. diff --git a/awswrangler/s3/_write_concurrent.py b/awswrangler/s3/_write_concurrent.py index ab5061227..d29783cea 100644 --- a/awswrangler/s3/_write_concurrent.py +++ b/awswrangler/s3/_write_concurrent.py @@ -2,7 +2,7 @@ import concurrent.futures import logging -from typing import Any, Callable, Dict, List, Optional +from typing import Any, Callable, Dict, List, Optional, Union import boto3 import pandas as pd @@ -13,7 +13,7 @@ class _WriteProxy: - def __init__(self, use_threads: bool): + def __init__(self, use_threads: Union[bool, int]): self._exec: Optional[concurrent.futures.ThreadPoolExecutor] self._results: List[str] = [] self._cpus: int = _utils.ensure_cpu_count(use_threads=use_threads) diff --git a/awswrangler/s3/_write_dataset.py b/awswrangler/s3/_write_dataset.py index 1b1b1e986..e2463c3aa 100644 --- a/awswrangler/s3/_write_dataset.py +++ b/awswrangler/s3/_write_dataset.py @@ -19,7 +19,7 @@ def _to_partitions( concurrent_partitioning: bool, df: pd.DataFrame, path_root: str, - use_threads: bool, + use_threads: Union[bool, int], mode: str, partition_cols: List[str], partitions_types: Optional[Dict[str, str]], @@ -105,7 +105,7 @@ def _to_buckets( bucketing_info: Tuple[List[str], int], filename_prefix: str, boto3_session: boto3.Session, - use_threads: bool, + use_threads: Union[bool, int], proxy: Optional[_WriteProxy] = None, **func_kwargs: Any, ) -> List[str]: @@ -162,7 +162,7 @@ def _to_dataset( path_root: str, filename_prefix: str, index: bool, - use_threads: bool, + use_threads: Union[bool, int], mode: str, partition_cols: Optional[List[str]], partitions_types: Optional[Dict[str, str]], diff --git a/awswrangler/s3/_write_excel.py b/awswrangler/s3/_write_excel.py index b6910a5c5..9bb1cd5f7 100644 --- a/awswrangler/s3/_write_excel.py +++ b/awswrangler/s3/_write_excel.py @@ -1,7 +1,7 @@ """Amazon S3 Excel Write Module (PRIVATE).""" import logging -from typing import Any, Dict, Optional +from typing import Any, Dict, Optional, Union import boto3 import pandas as pd @@ -17,7 +17,7 @@ def to_excel( path: str, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, **pandas_kwargs: Any, ) -> str: """Write EXCEL file on Amazon S3. @@ -48,9 +48,10 @@ def to_excel( s3_additional_kwargs : Optional[Dict[str, Any]] Forwarded to botocore requests. e.g. s3_additional_kwargs={'ServerSideEncryption': 'aws:kms', 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN'} - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. pandas_kwargs: KEYWORD arguments forwarded to pandas.DataFrame.to_excel(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. diff --git a/awswrangler/s3/_write_parquet.py b/awswrangler/s3/_write_parquet.py index 09b306de5..da55360bc 100644 --- a/awswrangler/s3/_write_parquet.py +++ b/awswrangler/s3/_write_parquet.py @@ -39,12 +39,18 @@ def _get_file_path(file_counter: int, file_path: str) -> str: def _new_writer( file_path: str, compression: Optional[str], + pyarrow_additional_kwargs: Optional[Dict[str, str]], schema: pa.Schema, boto3_session: boto3.Session, s3_additional_kwargs: Optional[Dict[str, str]], - use_threads: bool, + use_threads: Union[bool, int], ) -> Iterator[pyarrow.parquet.ParquetWriter]: writer: Optional[pyarrow.parquet.ParquetWriter] = None + if not pyarrow_additional_kwargs: + pyarrow_additional_kwargs = {} + if not pyarrow_additional_kwargs.get("coerce_timestamps"): + pyarrow_additional_kwargs["coerce_timestamps"] = "ms" + with open_s3_object( path=file_path, mode="wb", @@ -57,10 +63,10 @@ def _new_writer( where=f, write_statistics=True, use_dictionary=True, - coerce_timestamps="ms", compression="NONE" if compression is None else compression, flavor="spark", schema=schema, + **pyarrow_additional_kwargs, ) yield writer finally: @@ -73,14 +79,16 @@ def _write_chunk( boto3_session: Optional[boto3.Session], s3_additional_kwargs: Optional[Dict[str, str]], compression: Optional[str], + pyarrow_additional_kwargs: Optional[Dict[str, str]], table: pa.Table, offset: int, chunk_size: int, - use_threads: bool, + use_threads: Union[bool, int], ) -> List[str]: with _new_writer( file_path=file_path, compression=compression, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, schema=table.schema, boto3_session=boto3_session, s3_additional_kwargs=s3_additional_kwargs, @@ -95,13 +103,14 @@ def _to_parquet_chunked( boto3_session: Optional[boto3.Session], s3_additional_kwargs: Optional[Dict[str, str]], compression: Optional[str], + pyarrow_additional_kwargs: Optional[Dict[str, Any]], table: pa.Table, max_rows_by_file: int, num_of_rows: int, cpus: int, ) -> List[str]: chunks: int = math.ceil(num_of_rows / max_rows_by_file) - use_threads: bool = cpus > 1 + use_threads: Union[bool, int] = cpus > 1 proxy: _WriteProxy = _WriteProxy(use_threads=use_threads) for chunk in range(chunks): offset: int = chunk * max_rows_by_file @@ -112,6 +121,7 @@ def _to_parquet_chunked( boto3_session=boto3_session, s3_additional_kwargs=s3_additional_kwargs, compression=compression, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, table=table, offset=offset, chunk_size=max_rows_by_file, @@ -126,11 +136,12 @@ def _to_parquet( index: bool, compression: Optional[str], compression_ext: str, + pyarrow_additional_kwargs: Optional[Dict[str, Any]], cpus: int, dtype: Dict[str, str], boto3_session: Optional[boto3.Session], s3_additional_kwargs: Optional[Dict[str, str]], - use_threads: bool, + use_threads: Union[bool, int], path: Optional[str] = None, path_root: Optional[str] = None, filename_prefix: Optional[str] = uuid.uuid4().hex, @@ -157,6 +168,7 @@ def _to_parquet( boto3_session=boto3_session, s3_additional_kwargs=s3_additional_kwargs, compression=compression, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, table=table, max_rows_by_file=max_rows_by_file, num_of_rows=df.shape[0], @@ -166,6 +178,7 @@ def _to_parquet( with _new_writer( file_path=file_path, compression=compression, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, schema=table.schema, boto3_session=boto3_session, s3_additional_kwargs=s3_additional_kwargs, @@ -182,8 +195,9 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b path: Optional[str] = None, index: bool = False, compression: Optional[str] = "snappy", + pyarrow_additional_kwargs: Optional[Dict[str, Any]] = None, max_rows_by_file: Optional[int] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, sanitize_columns: bool = False, @@ -248,13 +262,18 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b True to store the DataFrame index in file, otherwise False to ignore it. compression: str, optional Compression style (``None``, ``snappy``, ``gzip``). + pyarrow_additional_kwargs : Optional[Dict[str, Any]] + Additional parameters forwarded to pyarrow. + e.g. pyarrow_additional_kwargs={'coerce_timestamps': 'ns', 'use_deprecated_int96_timestamps': False, + 'allow_truncated_timestamps'=False} max_rows_by_file : int Max number of rows in each file. Default is None i.e. dont split the files. (e.g. 33554432, 268435456) - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] @@ -281,18 +300,18 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b concurrent_partitioning: bool If True will increase the parallelism level during the partitions writing. It will decrease the writing time and increase the memory usage. - https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html + https://aws-data-wrangler.readthedocs.io/en/2.12.1/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html mode: str, optional ``append`` (Default), ``overwrite``, ``overwrite_partitions``. Only takes effect if dataset=True. For details check the related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet + https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet catalog_versioning : bool If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. schema_evolution : bool If True allows schema evolution (new or missing columns), otherwise a exception will be raised. (Only considered if dataset=True and mode in ("append", "overwrite_partitions")) Related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/014%20-%20Schema%20Evolution.html + https://aws-data-wrangler.readthedocs.io/en/2.12.1/tutorials/014%20-%20Schema%20Evolution.html database : str, optional Glue/Athena catalog: Database name. table : str, optional @@ -566,6 +585,7 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b cpus=cpus, compression=compression, compression_ext=compression_ext, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, boto3_session=session, s3_additional_kwargs=s3_additional_kwargs, dtype=dtype, @@ -630,6 +650,7 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b table=table, table_type=table_type, transaction_id=transaction_id, + pyarrow_additional_kwargs=pyarrow_additional_kwargs, cpus=cpus, use_threads=use_threads, partition_cols=partition_cols, @@ -709,7 +730,7 @@ def store_parquet_metadata( # pylint: disable=too-many-arguments dtype: Optional[Dict[str, str]] = None, sampling: float = 1.0, dataset: bool = False, - use_threads: bool = True, + use_threads: Union[bool, int] = True, description: Optional[str] = None, parameters: Optional[Dict[str, str]] = None, columns_comments: Optional[Dict[str, str]] = None, @@ -781,9 +802,10 @@ def store_parquet_metadata( # pylint: disable=too-many-arguments The lower, the faster. dataset: bool If True read a parquet dataset instead of simple file(s) loading all the related partitions as columns. - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. description: str, optional Glue/Athena catalog: Table description parameters: Dict[str, str], optional diff --git a/awswrangler/s3/_write_text.py b/awswrangler/s3/_write_text.py index 1c0e0ebea..8f842a7bd 100644 --- a/awswrangler/s3/_write_text.py +++ b/awswrangler/s3/_write_text.py @@ -32,7 +32,7 @@ def _get_write_details(path: str, pandas_kwargs: Dict[str, Any]) -> Tuple[str, O def _to_text( file_format: str, df: pd.DataFrame, - use_threads: bool, + use_threads: Union[bool, int], boto3_session: Optional[boto3.Session], s3_additional_kwargs: Optional[Dict[str, str]], path: Optional[str] = None, @@ -76,7 +76,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state sep: str = ",", index: bool = True, columns: Optional[List[str]] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, sanitize_columns: bool = False, @@ -148,9 +148,10 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state Write row names (index). columns : Optional[List[str]] Columns to write. - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 Session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] @@ -176,18 +177,18 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state concurrent_partitioning: bool If True will increase the parallelism level during the partitions writing. It will decrease the writing time and increase the memory usage. - https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html + https://aws-data-wrangler.readthedocs.io/en/2.12.1/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html mode : str, optional ``append`` (Default), ``overwrite``, ``overwrite_partitions``. Only takes effect if dataset=True. For details check the related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet + https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet catalog_versioning : bool If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. schema_evolution : bool If True allows schema evolution (new or missing columns), otherwise a exception will be raised. (Only considered if dataset=True and mode in ("append", "overwrite_partitions")) Related tutorial: - https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/014%20-%20Schema%20Evolution.html + https://aws-data-wrangler.readthedocs.io/en/2.12.1/tutorials/014%20-%20Schema%20Evolution.html database : str, optional Glue/Athena catalog: Database name. table : str, optional @@ -668,7 +669,7 @@ def to_json( path: str, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, - use_threads: bool = True, + use_threads: Union[bool, int] = True, **pandas_kwargs: Any, ) -> List[str]: """Write JSON file on Amazon S3. @@ -687,15 +688,16 @@ def to_json( df: pandas.DataFrame Pandas DataFrame https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html path : str - Amazon S3 path (e.g. s3://bucket/filename.csv). + Amazon S3 path (e.g. s3://bucket/filename.json). boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 Session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] Forwarded to botocore requests. e.g. s3_additional_kwargs={'ServerSideEncryption': 'aws:kms', 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN'} - use_threads : bool + use_threads : bool, int True to enable concurrent requests, False to disable multiple threads. If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. pandas_kwargs: KEYWORD arguments forwarded to pandas.DataFrame.to_json(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. diff --git a/building/lambda/build-lambda-layer.sh b/building/lambda/build-lambda-layer.sh index 5449c6cbb..8def86925 100644 --- a/building/lambda/build-lambda-layer.sh +++ b/building/lambda/build-lambda-layer.sh @@ -80,7 +80,10 @@ rm -f /aws-data-wrangler/dist/pyarrow_files/pyarrow/libarrow_python.so cp -r /aws-data-wrangler/dist/pyarrow_files/pyarrow* python/ +# Removing nonessential files +find python -name '*.so' -type f -exec strip "{}" \; find python -wholename "*/tests/*" -type f -delete +find python -regex '^.*\(__pycache__\|\.py[co]\)$' -delete zip -r9 "${FILENAME}" ./python mv "${FILENAME}" dist/ diff --git a/docs/source/api.rst b/docs/source/api.rst index f6362a25c..81c800d29 100644 --- a/docs/source/api.rst +++ b/docs/source/api.rst @@ -11,6 +11,7 @@ API Reference * `Microsoft SQL Server`_ * `Data API Redshift`_ * `Data API RDS`_ +* `OpenSearch`_ * `DynamoDB`_ * `Amazon Timestream`_ * `Amazon EMR`_ @@ -217,6 +218,24 @@ Data API RDS connect read_sql_query +OpenSearch +---------- + +.. currentmodule:: awswrangler.opensearch + +.. autosummary:: + :toctree: stubs + + connect + create_index + delete_index + index_csv + index_documents + index_df + index_json + search + search_by_sql + DynamoDB -------- diff --git a/docs/source/install.rst b/docs/source/install.rst index d71bda417..b401b8b45 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -62,7 +62,7 @@ Go to your Glue PySpark job and create a new *Job parameters* key/value: To install a specific version, set the value for above Job parameter as follows: -* Value: ``cython==0.29.21,pg8000==1.21.0,pyarrow==2,pandas==1.3.0,awswrangler==2.11.0`` +* Value: ``cython==0.29.21,pg8000==1.21.0,pyarrow==2,pandas==1.3.0,awswrangler==2.12.1`` .. note:: Pyarrow 3 is not currently supported in Glue PySpark Jobs, which is why a previous installation of pyarrow 2 is required. @@ -95,7 +95,7 @@ Here is an example of how to reference the Lambda layer in your CDK app: "wrangler-bucket", bucket_arn="arn:aws:s3:::aws-data-wrangler-public-artifacts", ), - key="releases/2.11.0/awswrangler-layer-2.11.0-py3.8.zip", + key="releases/2.12.1/awswrangler-layer-2.12.1-py3.8.zip", ), layer_version_name="aws-data-wrangler" ) @@ -190,7 +190,7 @@ complement Big Data pipelines. sudo pip install pyarrow==2 awswrangler .. note:: Make sure to freeze the Wrangler version in the bootstrap for productive - environments (e.g. awswrangler==2.11.0) + environments (e.g. awswrangler==2.12.1) .. note:: Pyarrow 3 is not currently supported in the default EMR image, which is why a previous installation of pyarrow 2 is required. diff --git a/docs/source/what.rst b/docs/source/what.rst index d1b741f96..c8226c989 100644 --- a/docs/source/what.rst +++ b/docs/source/what.rst @@ -8,4 +8,4 @@ SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL Built on top of other open-source projects like `Pandas `_, `Apache Arrow `_ and `Boto3 `_, it offers abstracted functions to execute usual ETL tasks like load/unload data from **Data Lakes**, **Data Warehouses** and **Databases**. -Check our `tutorials `_ or the `list of functionalities `_. \ No newline at end of file +Check our `tutorials `_ or the `list of functionalities `_. \ No newline at end of file diff --git a/poetry.lock b/poetry.lock index c001b9152..b2e8d693a 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,6 +1,6 @@ [[package]] name = "aiobotocore" -version = "1.3.3" +version = "1.4.2" description = "Async client for aws services using botocore and aiohttp" category = "dev" optional = false @@ -57,7 +57,7 @@ python-versions = "*" [[package]] name = "anyio" -version = "3.3.0" +version = "3.3.4" description = "High level compatibility layer for multiple asynchronous event loop implementations" category = "dev" optional = false @@ -74,14 +74,6 @@ doc = ["sphinx-rtd-theme", "sphinx-autodoc-typehints (>=1.2.0)"] test = ["coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "pytest (>=6.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (<0.15)", "mock (>=4)", "uvloop (>=0.15)"] trio = ["trio (>=0.16)"] -[[package]] -name = "appdirs" -version = "1.4.4" -description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." -category = "dev" -optional = false -python-versions = "*" - [[package]] name = "appnope" version = "0.1.2" @@ -92,19 +84,18 @@ python-versions = "*" [[package]] name = "argon2-cffi" -version = "20.1.0" +version = "21.1.0" description = "The secure Argon2 password hashing algorithm." category = "dev" optional = false -python-versions = "*" +python-versions = ">=3.5" [package.dependencies] cffi = ">=1.0.0" -six = "*" [package.extras] -dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest", "sphinx", "wheel", "pre-commit"] -docs = ["sphinx"] +dev = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest", "sphinx", "furo", "wheel", "pre-commit"] +docs = ["sphinx", "furo"] tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest"] [[package]] @@ -117,7 +108,7 @@ python-versions = "*" [[package]] name = "astroid" -version = "2.6.6" +version = "2.8.3" description = "An abstract syntax tree for Python with inference support." category = "dev" optional = false @@ -126,8 +117,8 @@ python-versions = "~=3.6" [package.dependencies] lazy-object-proxy = ">=1.4.0" typed-ast = {version = ">=1.4.0,<1.5", markers = "implementation_name == \"cpython\" and python_version < \"3.8\""} -typing-extensions = {version = ">=3.7.4", markers = "python_version < \"3.8\""} -wrapt = ">=1.11,<1.13" +typing-extensions = {version = ">=3.10", markers = "python_version < \"3.10\""} +wrapt = ">=1.11,<1.14" [[package]] name = "async-generator" @@ -203,14 +194,14 @@ testing = ["pytest (>=4.6)", "pytest-flake8", "pytest-cov", "pytest-black (>=0.3 [[package]] name = "beautifulsoup4" -version = "4.9.3" +version = "4.10.0" description = "Screen-scraping library" category = "main" optional = false -python-versions = "*" +python-versions = ">3.0.0" [package.dependencies] -soupsieve = {version = ">1.2", markers = "python_version >= \"3.0\""} +soupsieve = ">1.2" [package.extras] html5lib = ["html5lib"] @@ -218,32 +209,33 @@ lxml = ["lxml"] [[package]] name = "black" -version = "21.7b0" +version = "21.9b0" description = "The uncompromising code formatter." category = "dev" optional = false python-versions = ">=3.6.2" [package.dependencies] -appdirs = "*" click = ">=7.1.2" dataclasses = {version = ">=0.6", markers = "python_version < \"3.7\""} mypy-extensions = ">=0.4.3" -pathspec = ">=0.8.1,<1" +pathspec = ">=0.9.0,<1" +platformdirs = ">=2" regex = ">=2020.1.8" tomli = ">=0.2.6,<2.0.0" typed-ast = {version = ">=1.4.2", markers = "python_version < \"3.8\""} -typing-extensions = {version = ">=3.7.4", markers = "python_version < \"3.8\""} +typing-extensions = ">=3.10.0.0" [package.extras] colorama = ["colorama (>=0.4.3)"] d = ["aiohttp (>=3.6.0)", "aiohttp-cors (>=0.4.0)"] +jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"] python2 = ["typed-ast (>=1.4.2)"] uvloop = ["uvloop (>=0.15.2)"] [[package]] name = "bleach" -version = "4.0.0" +version = "4.1.0" description = "An easy safelist-based HTML-sanitizing tool." category = "dev" optional = false @@ -293,7 +285,7 @@ python-versions = ">=3.5" [[package]] name = "certifi" -version = "2021.5.30" +version = "2021.10.8" description = "Python package for providing Mozilla's CA Bundle." category = "main" optional = false @@ -301,7 +293,7 @@ python-versions = "*" [[package]] name = "cffi" -version = "1.14.6" +version = "1.15.0" description = "Foreign Function Interface for Python calling C code." category = "dev" optional = false @@ -314,13 +306,24 @@ pycparser = "*" name = "chardet" version = "4.0.0" description = "Universal encoding detector for Python 2 and 3" -category = "main" +category = "dev" optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" +[[package]] +name = "charset-normalizer" +version = "2.0.7" +description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." +category = "main" +optional = false +python-versions = ">=3.5.0" + +[package.extras] +unicode_backport = ["unicodedata2"] + [[package]] name = "click" -version = "8.0.1" +version = "8.0.3" description = "Composable command line interface toolkit" category = "dev" optional = false @@ -351,18 +354,21 @@ immutables = ">=0.9" [[package]] name = "coverage" -version = "5.5" +version = "6.0.2" description = "Code coverage measurement for Python" category = "dev" optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, <4" +python-versions = ">=3.6" + +[package.dependencies] +tomli = {version = "*", optional = true, markers = "extra == \"toml\""} [package.extras] -toml = ["toml"] +toml = ["tomli"] [[package]] name = "cryptography" -version = "3.4.7" +version = "35.0.0" description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers." category = "dev" optional = false @@ -375,9 +381,9 @@ cffi = ">=1.12" docs = ["sphinx (>=1.6.5,!=1.8.0,!=3.1.0,!=3.1.1)", "sphinx-rtd-theme"] docstest = ["doc8", "pyenchant (>=1.6.11)", "twine (>=1.12.0)", "sphinxcontrib-spelling (>=4.0.1)"] pep8test = ["black", "flake8", "flake8-import-order", "pep8-naming"] -sdist = ["setuptools-rust (>=0.11.4)"] +sdist = ["setuptools_rust (>=0.11.4)"] ssh = ["bcrypt (>=3.1.5)"] -test = ["pytest (>=6.0)", "pytest-cov", "pytest-subtests", "pytest-xdist", "pretend", "iso8601", "pytz", "hypothesis (>=1.11.4,!=3.79.2)"] +test = ["pytest (>=6.2.0)", "pytest-cov", "pytest-subtests", "pytest-xdist", "pretend", "iso8601", "pytz", "hypothesis (>=1.11.4,!=3.79.2)"] [[package]] name = "dataclasses" @@ -389,9 +395,9 @@ python-versions = ">=3.6, <3.7" [[package]] name = "decorator" -version = "5.0.9" +version = "5.1.0" description = "Decorators for Humans" -category = "dev" +category = "main" optional = false python-versions = ">=3.5" @@ -405,7 +411,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" [[package]] name = "distlib" -version = "0.3.2" +version = "0.3.3" description = "Distribution utilities" category = "dev" optional = false @@ -413,7 +419,7 @@ python-versions = "*" [[package]] name = "doc8" -version = "0.9.0" +version = "0.9.1" description = "Style checker for Sphinx (or other) RST documentation" category = "dev" optional = false @@ -462,29 +468,33 @@ testing = ["pre-commit"] [[package]] name = "filelock" -version = "3.0.12" +version = "3.3.1" description = "A platform independent file lock." category = "dev" optional = false -python-versions = "*" +python-versions = ">=3.6" + +[package.extras] +docs = ["furo (>=2021.8.17b43)", "sphinx (>=4.1)", "sphinx-autodoc-typehints (>=1.12)"] +testing = ["covdefaults (>=1.2.0)", "coverage (>=4)", "pytest (>=4)", "pytest-cov", "pytest-timeout (>=1.4.2)"] [[package]] name = "flake8" -version = "3.9.2" +version = "4.0.1" description = "the modular source code checker: pep8 pyflakes and co" category = "dev" optional = false -python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7" +python-versions = ">=3.6" [package.dependencies] -importlib-metadata = {version = "*", markers = "python_version < \"3.8\""} +importlib-metadata = {version = "<4.3", markers = "python_version < \"3.8\""} mccabe = ">=0.6.0,<0.7.0" -pycodestyle = ">=2.7.0,<2.8.0" -pyflakes = ">=2.3.0,<2.4.0" +pycodestyle = ">=2.8.0,<2.9.0" +pyflakes = ">=2.4.0,<2.5.0" [[package]] name = "fsspec" -version = "2021.7.0" +version = "2021.10.1" description = "File-system specification" category = "dev" optional = false @@ -493,15 +503,20 @@ python-versions = ">=3.6" [package.extras] abfs = ["adlfs"] adl = ["adlfs"] +arrow = ["pyarrow (>=1)"] dask = ["dask", "distributed"] dropbox = ["dropboxdrivefs", "requests", "dropbox"] entrypoints = ["importlib-metadata"] +fuse = ["fusepy"] gcs = ["gcsfs"] git = ["pygit2"] github = ["requests"] gs = ["gcsfs"] +gui = ["panel"] hdfs = ["pyarrow (>=1)"] http = ["requests", "aiohttp"] +libarchive = ["libarchive-c"] +oci = ["ocifs"] s3 = ["s3fs"] sftp = ["paramiko"] smb = ["smbprotocol"] @@ -509,11 +524,11 @@ ssh = ["paramiko"] [[package]] name = "idna" -version = "2.10" +version = "3.3" description = "Internationalized Domain Names in Applications (IDNA)" category = "main" optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +python-versions = ">=3.5" [[package]] name = "idna-ssl" @@ -550,7 +565,7 @@ test = ["flake8 (>=3.8.4,<3.9.0)", "pycodestyle (>=2.6.0,<2.7.0)", "mypy (>=0.91 [[package]] name = "importlib-metadata" -version = "4.6.3" +version = "4.2.0" description = "Read metadata from Python packages" category = "dev" optional = false @@ -562,12 +577,11 @@ zipp = ">=0.5" [package.extras] docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"] -perf = ["ipython"] -testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "packaging", "pep517", "pyfakefs", "flufl.flake8", "pytest-perf (>=0.9.2)", "pytest-black (>=0.3.7)", "pytest-mypy", "importlib-resources (>=1.3)"] +testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "packaging", "pep517", "pyfakefs", "flufl.flake8", "pytest-black (>=0.3.7)", "pytest-mypy", "importlib-resources (>=1.3)"] [[package]] name = "importlib-resources" -version = "5.2.2" +version = "5.2.3" description = "Read resources from Python packages" category = "dev" optional = false @@ -578,7 +592,7 @@ zipp = {version = ">=3.1.0", markers = "python_version < \"3.10\""} [package.extras] docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"] -testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "pytest-black (>=0.3.7)", "pytest-mypy"] +testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytest-cov", "pytest-enabler (>=1.0.1)", "pytest-black (>=0.3.7)", "pytest-mypy"] [[package]] name = "iniconfig" @@ -590,7 +604,7 @@ python-versions = "*" [[package]] name = "ipykernel" -version = "5.5.5" +version = "5.5.6" description = "IPython Kernel for Jupyter" category = "dev" optional = false @@ -599,6 +613,7 @@ python-versions = ">=3.5" [package.dependencies] appnope = {version = "*", markers = "platform_system == \"Darwin\""} ipython = ">=5.0.0" +ipython-genutils = "*" jupyter-client = "*" tornado = ">=4.2" traitlets = ">=4.1.0" @@ -676,7 +691,7 @@ testing = ["Django (<3.1)", "colorama", "docopt", "pytest (<6.0.0)"] [[package]] name = "jinja2" -version = "3.0.1" +version = "3.0.2" description = "A very fast and expressive template engine." category = "dev" optional = false @@ -707,9 +722,22 @@ python-versions = "*" [package.extras] dev = ["hypothesis"] +[[package]] +name = "jsonpath-ng" +version = "1.5.3" +description = "A final implementation of JSONPath for Python that aims to be standard compliant, including arithmetic and binary comparison operators and providing clear AST for metaprogramming." +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +decorator = "*" +ply = "*" +six = "*" + [[package]] name = "jsonschema" -version = "3.2.0" +version = "4.0.0" description = "An implementation of JSON Schema validation for Python" category = "dev" optional = false @@ -718,22 +746,22 @@ python-versions = "*" [package.dependencies] attrs = ">=17.4.0" importlib-metadata = {version = "*", markers = "python_version < \"3.8\""} -pyrsistent = ">=0.14.0" -six = ">=1.11.0" +pyrsistent = ">=0.14.0,<0.17.0 || >0.17.0,<0.17.1 || >0.17.1,<0.17.2 || >0.17.2" [package.extras] -format = ["idna", "jsonpointer (>1.13)", "rfc3987", "strict-rfc3339", "webcolors"] -format_nongpl = ["idna", "jsonpointer (>1.13)", "webcolors", "rfc3986-validator (>0.1.0)", "rfc3339-validator"] +format = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3987", "uri-template", "webcolors (>=1.11)"] +format_nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-validator", "rfc3986-validator (>0.1.0)", "uri-template", "webcolors (>=1.11)"] [[package]] name = "jupyter-client" -version = "6.2.0" +version = "7.0.6" description = "Jupyter protocol implementation and client libraries" category = "dev" optional = false python-versions = ">=3.6.1" [package.dependencies] +entrypoints = "*" jupyter-core = ">=4.6.0" nest-asyncio = ">=1.5" python-dateutil = ">=2.1" @@ -742,24 +770,24 @@ tornado = ">=4.1" traitlets = "*" [package.extras] -doc = ["sphinx (>=1.3.6)", "sphinx-rtd-theme", "sphinxcontrib-github-alt"] -test = ["async-generator", "ipykernel", "ipython", "mock", "pytest-asyncio", "pytest-timeout", "pytest", "mypy", "pre-commit", "jedi (<0.18)"] +doc = ["myst-parser", "sphinx (>=1.3.6)", "sphinx-rtd-theme", "sphinxcontrib-github-alt"] +test = ["codecov", "coverage", "ipykernel", "ipython", "mock", "mypy", "pre-commit", "pytest", "pytest-asyncio", "pytest-cov", "pytest-timeout", "jedi (<0.18)"] [[package]] name = "jupyter-core" -version = "4.7.1" +version = "4.8.1" description = "Jupyter core package. A base package on which Jupyter projects rely." category = "dev" optional = false python-versions = ">=3.6" [package.dependencies] -pywin32 = {version = ">=1.0", markers = "sys_platform == \"win32\""} +pywin32 = {version = ">=1.0", markers = "sys_platform == \"win32\" and platform_python_implementation != \"PyPy\""} traitlets = "*" [[package]] name = "jupyter-server" -version = "1.10.2" +version = "1.11.1" description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications." category = "dev" optional = false @@ -788,7 +816,7 @@ test = ["coverage", "pytest (>=6.0)", "pytest-cov", "pytest-mock", "requests", " [[package]] name = "jupyterlab" -version = "3.1.4" +version = "3.2.0" description = "JupyterLab computational environment" category = "dev" optional = false @@ -821,7 +849,7 @@ pygments = ">=2.4.1,<3" [[package]] name = "jupyterlab-server" -version = "2.6.2" +version = "2.8.2" description = "A set of server components for JupyterLab and JupyterLab like applications ." category = "dev" optional = false @@ -829,6 +857,7 @@ python-versions = ">=3.6" [package.dependencies] babel = "*" +entrypoints = ">=0.2.2" jinja2 = ">=2.10" json5 = "*" jsonschema = ">=3.0.1" @@ -837,7 +866,7 @@ packaging = "*" requests = "*" [package.extras] -test = ["codecov", "ipykernel", "pytest (>=5.3.2)", "pytest-cov", "jupyter-server", "openapi-core (>=0.13.8,<0.14.0)", "pytest-console-scripts", "strict-rfc3339", "ruamel.yaml", "wheel"] +test = ["codecov", "ipykernel", "pytest (>=5.3.2)", "pytest-cov", "jupyter-server", "openapi-core (>=0.14.0,<0.15.0)", "pytest-console-scripts", "strict-rfc3339", "ruamel.yaml", "wheel"] [[package]] name = "lazy-object-proxy" @@ -887,7 +916,7 @@ python-versions = "*" [[package]] name = "more-itertools" -version = "8.8.0" +version = "8.10.0" description = "More routines for operating on iterables, beyond itertools" category = "dev" optional = false @@ -895,7 +924,7 @@ python-versions = ">=3.5" [[package]] name = "moto" -version = "2.2.2" +version = "2.2.10" description = "A library that allows your python tests to easily mock out the boto library" category = "dev" optional = false @@ -905,7 +934,7 @@ python-versions = "*" boto3 = ">=1.9.201" botocore = ">=1.12.201" cryptography = ">=3.3.1" -importlib-metadata = "*" +importlib-metadata = {version = "*", markers = "python_version < \"3.8\""} Jinja2 = ">=2.10.1" MarkupSafe = "!=2.0.0a1" more-itertools = "*" @@ -930,12 +959,12 @@ efs = ["sshpubkeys (>=3.1.0)"] iotdata = ["jsondiff (>=1.1.2)"] s3 = ["PyYAML (>=5.1)"] server = ["PyYAML (>=5.1)", "python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (<0.15)", "docker (>=2.5.1)", "jsondiff (>=1.1.2)", "aws-xray-sdk (>=0.93,!=0.96)", "idna (>=2.5,<3)", "cfn-lint (>=0.4.0)", "sshpubkeys (>=3.1.0)", "setuptools", "flask", "flask-cors"] -ssm = ["PyYAML (>=5.1)"] +ssm = ["PyYAML (>=5.1)", "dataclasses"] xray = ["aws-xray-sdk (>=0.93,!=0.96)", "setuptools"] [[package]] name = "multidict" -version = "5.1.0" +version = "5.2.0" description = "multidict implementation" category = "dev" optional = false @@ -969,7 +998,7 @@ python-versions = "*" [[package]] name = "nbclassic" -version = "0.3.1" +version = "0.3.2" description = "Jupyter Notebook as a Jupyter Server Extension." category = "dev" optional = false @@ -984,14 +1013,14 @@ test = ["pytest", "pytest-tornasync", "pytest-console-scripts"] [[package]] name = "nbclient" -version = "0.5.3" +version = "0.5.4" description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor." category = "dev" optional = false python-versions = ">=3.6.1" [package.dependencies] -async-generator = "*" +async-generator = {version = "*", markers = "python_version < \"3.7\""} jupyter-client = ">=6.1.5" nbformat = ">=5.0" nest-asyncio = "*" @@ -1088,7 +1117,7 @@ python-versions = ">=3.5" [[package]] name = "notebook" -version = "6.4.2" +version = "6.4.4" description = "A web-based notebook environment for interactive computing" category = "dev" optional = false @@ -1125,15 +1154,32 @@ python-versions = ">=3.6" [[package]] name = "openpyxl" -version = "3.0.7" +version = "3.0.9" description = "A Python library to read/write Excel 2010 xlsx/xlsm files" category = "main" optional = false -python-versions = ">=3.6," +python-versions = ">=3.6" [package.dependencies] et-xmlfile = "*" +[[package]] +name = "opensearch-py" +version = "1.0.0" +description = "Python low-level client for OpenSearch" +category = "main" +optional = false +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, <4" + +[package.dependencies] +certifi = "*" +urllib3 = ">=1.21.1,<2" + +[package.extras] +async = ["aiohttp (>=3,<4)"] +develop = ["requests (>=2.0.0,<3.0.0)", "coverage", "mock", "pyyaml", "pytest", "pytest-cov", "black", "jinja2"] +requests = ["requests (>=2.4.0,<3.0.0)"] + [[package]] name = "packaging" version = "21.0" @@ -1163,7 +1209,7 @@ test = ["pytest (>=4.0.2)", "pytest-xdist", "hypothesis (>=3.58)"] [[package]] name = "pandas" -version = "1.3.1" +version = "1.3.3" description = "Powerful data structures for data analysis, time series, and statistics" category = "main" optional = false @@ -1177,9 +1223,28 @@ pytz = ">=2017.3" [package.extras] test = ["hypothesis (>=3.58)", "pytest (>=6.0)", "pytest-xdist"] +[[package]] +name = "pandas" +version = "1.3.4" +description = "Powerful data structures for data analysis, time series, and statistics" +category = "main" +optional = false +python-versions = ">=3.7.1" + +[package.dependencies] +numpy = [ + {version = ">=1.17.3", markers = "platform_machine != \"aarch64\" and platform_machine != \"arm64\" and python_version < \"3.10\""}, + {version = ">=1.19.2", markers = "platform_machine == \"aarch64\" and python_version < \"3.10\""}, +] +python-dateutil = ">=2.7.3" +pytz = ">=2017.3" + +[package.extras] +test = ["hypothesis (>=3.58)", "pytest (>=6.0)", "pytest-xdist"] + [[package]] name = "pandocfilters" -version = "1.4.3" +version = "1.5.0" description = "Utilities for writing pandoc filters in python" category = "dev" optional = false @@ -1226,14 +1291,14 @@ ptyprocess = ">=0.5" [[package]] name = "pg8000" -version = "1.21.0" +version = "1.21.3" description = "PostgreSQL interface library" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -scramp = ">=1.4.0" +scramp = ">=1.4.1" [[package]] name = "pickleshare" @@ -1245,7 +1310,7 @@ python-versions = "*" [[package]] name = "platformdirs" -version = "2.2.0" +version = "2.4.0" description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"." category = "dev" optional = false @@ -1257,17 +1322,42 @@ test = ["appdirs (==1.4.4)", "pytest (>=6)", "pytest-cov (>=2.7)", "pytest-mock [[package]] name = "pluggy" -version = "0.13.1" +version = "1.0.0" description = "plugin and hook calling mechanisms for python" category = "dev" optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +python-versions = ">=3.6" [package.dependencies] importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""} [package.extras] dev = ["pre-commit", "tox"] +testing = ["pytest", "pytest-benchmark"] + +[[package]] +name = "ply" +version = "3.11" +description = "Python Lex & Yacc" +category = "main" +optional = false +python-versions = "*" + +[[package]] +name = "progressbar2" +version = "3.55.0" +description = "A Python Progressbar library to provide visual (yet text based) progress to long running operations." +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +python-utils = ">=2.3.0" +six = "*" + +[package.extras] +docs = ["sphinx (>=1.7.4)"] +tests = ["flake8 (>=3.7.7)", "pytest (>=4.6.9)", "pytest-cov (>=2.6.1)", "freezegun (>=0.3.11)", "sphinx (>=1.8.5)"] [[package]] name = "prometheus-client" @@ -1282,11 +1372,11 @@ twisted = ["twisted"] [[package]] name = "prompt-toolkit" -version = "3.0.19" +version = "3.0.20" description = "Library for building powerful interactive command lines in Python" category = "dev" optional = false -python-versions = ">=3.6.1" +python-versions = ">=3.6.2" [package.dependencies] wcwidth = "*" @@ -1320,11 +1410,11 @@ numpy = ">=1.16.6" [[package]] name = "pycodestyle" -version = "2.7.0" +version = "2.8.0" description = "Python style guide checker" category = "dev" optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" [[package]] name = "pycparser" @@ -1361,7 +1451,7 @@ pyparsing = ">=2.1.4" [[package]] name = "pyflakes" -version = "2.3.1" +version = "2.4.0" description = "passive checker of Python programs" category = "dev" optional = false @@ -1369,7 +1459,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" [[package]] name = "pygments" -version = "2.9.0" +version = "2.10.0" description = "Pygments is a syntax highlighting package written in Python." category = "dev" optional = false @@ -1377,18 +1467,20 @@ python-versions = ">=3.5" [[package]] name = "pylint" -version = "2.9.6" +version = "2.11.1" description = "python code static checker" category = "dev" optional = false python-versions = "~=3.6" [package.dependencies] -astroid = ">=2.6.5,<2.7" +astroid = ">=2.8.0,<2.9" colorama = {version = "*", markers = "sys_platform == \"win32\""} isort = ">=4.2.5,<6" mccabe = ">=0.6,<0.7" +platformdirs = ">=2.2.0" toml = ">=0.7.1" +typing-extensions = {version = ">=3.10.0", markers = "python_version < \"3.10\""} [[package]] name = "pymysql" @@ -1404,7 +1496,7 @@ rsa = ["cryptography"] [[package]] name = "pyodbc" -version = "4.0.31" +version = "4.0.32" description = "DB API Module for ODBC" category = "main" optional = true @@ -1428,7 +1520,7 @@ python-versions = ">=3.6" [[package]] name = "pytest" -version = "6.2.4" +version = "6.2.5" description = "pytest: simple powerful testing with Python" category = "dev" optional = false @@ -1441,7 +1533,7 @@ colorama = {version = "*", markers = "sys_platform == \"win32\""} importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""} iniconfig = "*" packaging = "*" -pluggy = ">=0.12,<1.0.0a1" +pluggy = ">=0.12,<2.0" py = ">=1.8.2" toml = "*" @@ -1450,16 +1542,15 @@ testing = ["argcomplete", "hypothesis (>=3.56)", "mock", "nose", "requests", "xm [[package]] name = "pytest-cov" -version = "2.12.1" +version = "3.0.0" description = "Pytest plugin for measuring coverage." category = "dev" optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" +python-versions = ">=3.6" [package.dependencies] -coverage = ">=5.2.1" +coverage = {version = ">=5.2.1", extras = ["toml"]} pytest = ">=4.6" -toml = "*" [package.extras] testing = ["fields", "hunter", "process-tests", "six", "pytest-xdist", "virtualenv"] @@ -1478,29 +1569,29 @@ pytest = ">=3.10" [[package]] name = "pytest-rerunfailures" -version = "10.1" +version = "10.2" description = "pytest plugin to re-run tests to eliminate flaky failures" category = "dev" optional = false -python-versions = ">=3.6" +python-versions = ">= 3.6" [package.dependencies] pytest = ">=5.3" [[package]] name = "pytest-timeout" -version = "1.4.2" -description = "py.test plugin to abort hanging tests" +version = "2.0.1" +description = "pytest plugin to abort hanging tests" category = "dev" optional = false -python-versions = "*" +python-versions = ">=3.6" [package.dependencies] -pytest = ">=3.6.0" +pytest = ">=5.0.0" [[package]] name = "pytest-xdist" -version = "2.3.0" +version = "2.4.0" description = "pytest xdist plugin for distributed testing and loop-on-failing modes" category = "dev" optional = false @@ -1513,6 +1604,7 @@ pytest-forked = "*" [package.extras] psutil = ["psutil (>=3.0)"] +setproctitle = ["setproctitle"] testing = ["filelock"] [[package]] @@ -1534,9 +1626,20 @@ category = "dev" optional = false python-versions = "*" +[[package]] +name = "python-utils" +version = "2.5.6" +description = "Python Utils is a module with some convenient utilities not included with the standard Python install" +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +six = "*" + [[package]] name = "pytz" -version = "2021.1" +version = "2021.3" description = "World timezone definitions, modern and historical" category = "main" optional = false @@ -1544,7 +1647,7 @@ python-versions = "*" [[package]] name = "pywin32" -version = "301" +version = "302" description = "Python for Window Extensions" category = "dev" optional = false @@ -1552,7 +1655,7 @@ python-versions = "*" [[package]] name = "pywinpty" -version = "1.1.3" +version = "1.1.4" description = "Pseudo terminal support for Windows from Python." category = "dev" optional = false @@ -1560,7 +1663,7 @@ python-versions = ">=3.6" [[package]] name = "pyzmq" -version = "22.2.1" +version = "22.3.0" description = "Python bindings for 0MQ" category = "dev" optional = false @@ -1572,7 +1675,7 @@ py = {version = "*", markers = "implementation_name == \"pypy\""} [[package]] name = "redshift-connector" -version = "2.0.884" +version = "2.0.888" description = "Redshift interface library" category = "main" optional = false @@ -1585,7 +1688,7 @@ botocore = ">=1.19.8,<2.0.0" lxml = ">=4.6.2" packaging = "*" pytz = ">=2020.1,<2021.9" -requests = ">=2.23.0,<2.25.2" +requests = ">=2.23.0,<2.26.1" scramp = ">=1.2.0,<1.5.0" [package.extras] @@ -1593,7 +1696,7 @@ full = ["numpy", "pandas"] [[package]] name = "regex" -version = "2021.8.3" +version = "2021.10.8" description = "Alternative regular expression module, to replace re." category = "dev" optional = false @@ -1601,21 +1704,33 @@ python-versions = "*" [[package]] name = "requests" -version = "2.25.1" +version = "2.26.0" description = "Python HTTP for Humans." category = "main" optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*" [package.dependencies] certifi = ">=2017.4.17" -chardet = ">=3.0.2,<5" -idna = ">=2.5,<3" +charset-normalizer = {version = ">=2.0.0,<2.1.0", markers = "python_version >= \"3\""} +idna = {version = ">=2.5,<4", markers = "python_version >= \"3\""} urllib3 = ">=1.21.1,<1.27" [package.extras] -security = ["pyOpenSSL (>=0.14)", "cryptography (>=1.3.4)"] socks = ["PySocks (>=1.5.6,!=1.5.7)", "win-inet-pton"] +use_chardet_on_py3 = ["chardet (>=3.0.2,<5)"] + +[[package]] +name = "requests-aws4auth" +version = "1.1.1" +description = "AWS4 authentication for Requests" +category = "main" +optional = false +python-versions = "*" + +[package.dependencies] +requests = "*" +six = "*" [[package]] name = "requests-unixsocket" @@ -1631,7 +1746,7 @@ urllib3 = ">=1.8" [[package]] name = "responses" -version = "0.13.4" +version = "0.14.0" description = "A utility library for mocking out the `requests` Python library." category = "dev" optional = false @@ -1658,19 +1773,19 @@ docutils = ">=0.11,<1.0" [[package]] name = "s3fs" -version = "2021.7.0" +version = "2021.10.1" description = "Convenient Filesystem interface over S3" category = "dev" optional = false python-versions = ">= 3.6" [package.dependencies] -aiobotocore = ">=1.0.1" -fsspec = "2021.07.0" +aiobotocore = ">=1.4.1,<1.5.0" +fsspec = "2021.10.1" [package.extras] -awscli = ["aiobotocore"] -boto3 = ["aiobotocore"] +awscli = ["aiobotocore[awscli] (>=1.4.1,<1.5.0)"] +boto3 = ["aiobotocore[boto3] (>=1.4.1,<1.5.0)"] [[package]] name = "s3transfer" @@ -1688,14 +1803,14 @@ crt = ["botocore[crt] (>=1.20.29,<2.0a.0)"] [[package]] name = "scramp" -version = "1.4.0" +version = "1.4.1" description = "An implementation of the SCRAM protocol." category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -asn1crypto = "1.4.0" +asn1crypto = ">=1.4.0" [[package]] name = "send2trash" @@ -1747,7 +1862,7 @@ python-versions = ">=3.6" [[package]] name = "sphinx" -version = "4.1.2" +version = "4.2.0" description = "Python documentation generator" category = "dev" optional = false @@ -1778,7 +1893,7 @@ test = ["pytest", "pytest-cov", "html5lib", "cython", "typed-ast"] [[package]] name = "sphinx-bootstrap-theme" -version = "0.7.1" +version = "0.8.0" description = "Sphinx Bootstrap Theme." category = "dev" optional = false @@ -1857,7 +1972,7 @@ test = ["pytest"] [[package]] name = "stevedore" -version = "3.3.0" +version = "3.4.0" description = "Manage dynamic plugins for Python applications" category = "dev" optional = false @@ -1869,7 +1984,7 @@ pbr = ">=2.0.0,<2.1.0 || >2.1.0" [[package]] name = "terminado" -version = "0.10.1" +version = "0.12.1" description = "Tornado websocket backend for the Xterm.js Javascript terminal emulator library." category = "dev" optional = false @@ -1920,7 +2035,7 @@ python-versions = ">= 3.5" [[package]] name = "tox" -version = "3.24.1" +version = "3.24.4" description = "tox is a generic virtualenv management and test command line tool" category = "dev" optional = false @@ -1967,7 +2082,7 @@ python-versions = "*" [[package]] name = "typing-extensions" -version = "3.10.0.0" +version = "3.10.0.2" description = "Backported and Experimental Type Hints for Python 3.5+" category = "dev" optional = false @@ -1975,7 +2090,7 @@ python-versions = "*" [[package]] name = "urllib3" -version = "1.26.6" +version = "1.26.7" description = "HTTP library with thread-safe connection pooling, file post, and more." category = "main" optional = false @@ -1988,7 +2103,7 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"] [[package]] name = "virtualenv" -version = "20.7.1" +version = "20.8.1" description = "Virtual Python Environment builder" category = "dev" optional = false @@ -2025,15 +2140,19 @@ python-versions = "*" [[package]] name = "websocket-client" -version = "1.1.1" +version = "1.2.1" description = "WebSocket client for Python with low level API options" category = "dev" optional = false python-versions = ">=3.6" +[package.extras] +optional = ["python-socks", "wsaccel"] +test = ["websockets"] + [[package]] name = "werkzeug" -version = "2.0.1" +version = "2.0.2" description = "The comprehensive WSGI web application library." category = "dev" optional = false @@ -2047,11 +2166,11 @@ watchdog = ["watchdog"] [[package]] name = "wrapt" -version = "1.12.1" +version = "1.13.2" description = "Module for decorators, wrappers and monkey patching." category = "dev" optional = false -python-versions = "*" +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7" 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"^1.115.0" -"aws-cdk.aws-redshift" = "^1.115.0" -"aws-cdk.aws-rds" = "^1.115.0" -"aws-cdk.aws-secretsmanager" = "^1.115.0" -"aws-cdk.aws-ssm" = "^1.115.0" +"aws-cdk.core" = "^1.124.0" +"aws-cdk.aws-ec2" = "^1.124.0" +"aws-cdk.aws-glue" = "^1.124.0" +"aws-cdk.aws-iam" = "^1.124.0" +"aws-cdk.aws-kms" = "^1.124.0" +"aws-cdk.aws-logs" = "^1.124.0" +"aws-cdk.aws-s3" = "^1.124.0" +"aws-cdk.aws-redshift" = "^1.124.0" +"aws-cdk.aws-rds" = "^1.124.0" +"aws-cdk.aws-secretsmanager" = "^1.124.0" +"aws-cdk.aws-ssm" = "^1.124.0" +"aws-cdk.aws-opensearchservice" = "^1.124.0" diff --git a/test_infra/scripts/delete-opensearch.sh b/test_infra/scripts/delete-opensearch.sh new file mode 100755 index 000000000..1c1c01ba2 --- /dev/null +++ b/test_infra/scripts/delete-opensearch.sh @@ -0,0 +1,6 @@ +#!/usr/bin/env bash +set -e + +pushd .. +cdk destroy aws-data-wrangler-opensearch +popd diff --git a/test_infra/scripts/deploy-opensearch.sh b/test_infra/scripts/deploy-opensearch.sh new file mode 100755 index 000000000..e94818af4 --- /dev/null +++ b/test_infra/scripts/deploy-opensearch.sh @@ -0,0 +1,7 @@ +#!/usr/bin/env bash +set -e + +pushd .. +cdk bootstrap +cdk deploy aws-data-wrangler-opensearch +popd diff --git a/test_infra/stacks/opensearch_stack.py b/test_infra/stacks/opensearch_stack.py new file mode 100644 index 000000000..f3bc6a1f8 --- /dev/null +++ b/test_infra/stacks/opensearch_stack.py @@ -0,0 +1,105 @@ +from aws_cdk import aws_ec2 as ec2 +from aws_cdk import aws_iam as iam +from aws_cdk import aws_kms as kms +from aws_cdk import aws_opensearchservice as opensearch +from aws_cdk import aws_s3 as s3 +from aws_cdk import aws_secretsmanager as secrets +from aws_cdk import core as cdk + + +def validate_domain_name(name: str): + if not 3 <= len(name) <= 28: + raise ValueError(f"invalid domain name ({name}) - bad length ({len(name)})") + for c in name: + if not ("a" <= c <= "z" or c.isdigit() or c in ["-"]): + raise ValueError(f'invalid domain name ({name}) - bad character ("{c}")') + + +class OpenSearchStack(cdk.Stack): # type: ignore + def __init__( + self, + scope: cdk.Construct, + construct_id: str, + vpc: ec2.IVpc, + bucket: s3.IBucket, + key: kms.Key, + **kwargs: str, + ) -> None: + """ + AWS Data Wrangler Development OpenSearch Infrastructure. + Includes OpenSearch, Elasticsearch, ... + """ + super().__init__(scope, construct_id, **kwargs) + + self.vpc = vpc + self.key = key + self.bucket = bucket + + self._set_opensearch_infra() + self._setup_opensearch_1_0() + self._setup_elasticsearch_7_10_fgac() + + def _set_opensearch_infra(self) -> None: + self.username = "test" + # fmt: off + self.password_secret = secrets.Secret( + self, + "opensearch-password-secret", + secret_name="aws-data-wrangler/opensearch_password", + generate_secret_string=secrets.SecretStringGenerator(exclude_characters="/@\"\' \\"), + ).secret_value + # fmt: on + self.password = self.password_secret.to_string() + + def _setup_opensearch_1_0(self) -> None: + domain_name = "wrangler-os-1-0" + validate_domain_name(domain_name) + domain_arn = f"arn:aws:es:{self.region}:{self.account}:domain/{domain_name}" + domain = opensearch.Domain( + self, + domain_name, + domain_name=domain_name, + version=opensearch.EngineVersion.OPENSEARCH_1_0, + capacity=opensearch.CapacityConfig(data_node_instance_type="t3.small.search", data_nodes=1), + access_policies=[ + iam.PolicyStatement( + effect=iam.Effect.ALLOW, + actions=["es:*"], + principals=[iam.AccountRootPrincipal()], + resources=[f"{domain_arn}/*"], + ) + ], + removal_policy=cdk.RemovalPolicy.DESTROY, + ) + + cdk.CfnOutput(self, f"DomainEndpoint-{domain_name}", value=domain.domain_endpoint) + + def _setup_elasticsearch_7_10_fgac(self) -> None: + domain_name = "wrangler-es-7-10-fgac" + validate_domain_name(domain_name) + domain_arn = f"arn:aws:es:{self.region}:{self.account}:domain/{domain_name}" + domain = opensearch.Domain( + self, + domain_name, + domain_name=domain_name, + version=opensearch.EngineVersion.ELASTICSEARCH_7_10, + capacity=opensearch.CapacityConfig(data_node_instance_type="t3.small.search", data_nodes=1), + access_policies=[ + iam.PolicyStatement( + effect=iam.Effect.ALLOW, + actions=["es:*"], + principals=[iam.AnyPrincipal()], # FGACs + resources=[f"{domain_arn}/*"], + ) + ], + fine_grained_access_control=opensearch.AdvancedSecurityOptions( + master_user_name=self.username, + master_user_password=self.password_secret, + ), + node_to_node_encryption=True, + encryption_at_rest=opensearch.EncryptionAtRestOptions(enabled=True, kms_key=self.key), + enforce_https=True, + removal_policy=cdk.RemovalPolicy.DESTROY, + ) + + cdk.CfnOutput(self, f"DomainEndpoint-{domain_name}", value=domain.domain_endpoint) diff --git a/tests/_utils.py b/tests/_utils.py index bc9dd3f75..dd348562f 100644 --- a/tests/_utils.py +++ b/tests/_utils.py @@ -539,9 +539,10 @@ def extract_cloudformation_outputs(): client = boto3.client("cloudformation") response = try_it(client.describe_stacks, botocore.exceptions.ClientError, max_num_tries=5) for stack in response.get("Stacks"): - if (stack["StackName"] in ["aws-data-wrangler-base", "aws-data-wrangler-databases"]) and ( - stack["StackStatus"] in CFN_VALID_STATUS - ): + if ( + stack["StackName"] + in ["aws-data-wrangler-base", "aws-data-wrangler-databases", "aws-data-wrangler-opensearch"] + ) and (stack["StackStatus"] in CFN_VALID_STATUS): for output in stack.get("Outputs"): outputs[output.get("OutputKey")] = output.get("OutputValue") return outputs diff --git a/tests/test_athena_parquet.py b/tests/test_athena_parquet.py index ea80725b6..5da4f7c3c 100644 --- a/tests/test_athena_parquet.py +++ b/tests/test_athena_parquet.py @@ -752,3 +752,18 @@ def test_ignore_suffix(glue_database, glue_table, path): boto3.client("s3").put_object(Body=b"garbage", Bucket=bucket, Key=f"{directory}to_be_ignored") df2 = wr.s3.read_parquet_table(database=glue_database, table=glue_table, filename_ignore_suffix="ignored") assert df2.shape == df.shape + + +def test_athena_timestamp_overflow(): + sql = "SELECT timestamp '2262-04-11 23:47:17' AS c0" + df1 = wr.athena.read_sql_query(sql, "default") + + df_overflow = pd.DataFrame({"c0": [pd.Timestamp("1677-09-21 00:12:43.290448384")]}) + assert df_overflow.c0.values[0] == df1.c0.values[0] + + df2 = wr.athena.read_sql_query( + sql, "default", pyarrow_additional_kwargs={"coerce_int96_timestamp_unit": "ms", "timestamp_as_object": True} + ) + + df_overflow_fix = pd.DataFrame({"c0": [datetime.datetime(2262, 4, 11, 23, 47, 17)]}) + df_overflow_fix.c0.values[0] == df2.c0.values[0] diff --git a/tests/test_config.py b/tests/test_config.py index c796a4b8b..86ea3eccc 100644 --- a/tests/test_config.py +++ b/tests/test_config.py @@ -29,6 +29,8 @@ def wrapper(self, **kwarg): assert url == wr.config.s3_endpoint_url elif name == "glue": assert url == wr.config.glue_endpoint_url + elif name == "secretsmanager": + assert url == wr.config.secretsmanager_endpoint_url return original(self, **kwarg) with patch("botocore.client.ClientCreator.create_client", new=wrapper): @@ -112,11 +114,13 @@ def test_basics(path, glue_database, glue_table, workgroup0, workgroup1): wr.config.s3_endpoint_url = f"https://s3.{region}.amazonaws.com" wr.config.athena_endpoint_url = f"https://athena.{region}.amazonaws.com" wr.config.glue_endpoint_url = f"https://glue.{region}.amazonaws.com" + wr.config.secretsmanager_endpoint_url = f"https://secretsmanager.{region}.amazonaws.com" _urls_test(glue_database) os.environ["WR_STS_ENDPOINT_URL"] = f"https://sts.{region}.amazonaws.com" os.environ["WR_S3_ENDPOINT_URL"] = f"https://s3.{region}.amazonaws.com" os.environ["WR_ATHENA_ENDPOINT_URL"] = f"https://athena.{region}.amazonaws.com" os.environ["WR_GLUE_ENDPOINT_URL"] = f"https://glue.{region}.amazonaws.com" + os.environ["WR_SECRETSMANAGER_ENDPOINT_URL"] = f"https://secretsmanager.{region}.amazonaws.com" wr.config.reset() _urls_test(glue_database) diff --git a/tests/test_metadata.py b/tests/test_metadata.py index 4031f5a86..2fa039889 100644 --- a/tests/test_metadata.py +++ b/tests/test_metadata.py @@ -2,7 +2,7 @@ def test_metadata(): - assert wr.__version__ == "2.11.0" + assert wr.__version__ == "2.12.1" assert wr.__title__ == "awswrangler" assert wr.__description__ == "Pandas on AWS." assert wr.__license__ == "Apache License 2.0" diff --git a/tests/test_opensearch.py b/tests/test_opensearch.py new file mode 100644 index 000000000..345d248e3 --- /dev/null +++ b/tests/test_opensearch.py @@ -0,0 +1,358 @@ +import json +import logging +import tempfile +import time + +import boto3 +import pandas as pd +import pytest # type: ignore + +import awswrangler as wr + +from ._utils import extract_cloudformation_outputs + +logging.getLogger("awswrangler").setLevel(logging.DEBUG) + + +inspections_documents = [ + { + "business_address": "315 California St", + "business_city": "San Francisco", + "business_id": "24936", + "business_latitude": "37.793199", + "business_location": {"lon": -122.400152, "lat": 37.793199}, + "business_longitude": "-122.400152", + "business_name": "San Francisco Soup Company", + "business_postal_code": "94104", + "business_state": "CA", + "inspection_date": "2016-06-09T00:00:00.000", + "inspection_id": "24936_20160609", + "inspection_score": 77, + "inspection_type": "Routine - Unscheduled", + "risk_category": "Low Risk", + "violation_description": "Improper food labeling or menu misrepresentation", + "violation_id": "24936_20160609_103141", + }, + { + "business_address": "10 Mason St", + "business_city": "San Francisco", + "business_id": "60354", + "business_latitude": "37.783527", + "business_location": {"lon": -122.409061, "lat": 37.783527}, + "business_longitude": "-122.409061", + "business_name": "Soup Unlimited", + "business_postal_code": "94102", + "business_state": "CA", + "inspection_date": "2016-11-23T00:00:00.000", + "inspection_id": "60354_20161123", + "inspection_type": "Routine", + "inspection_score": 95, + }, + { + "business_address": "2872 24th St", + "business_city": "San Francisco", + "business_id": "1797", + "business_latitude": "37.752807", + "business_location": {"lon": -122.409752, "lat": 37.752807}, + "business_longitude": "-122.409752", + "business_name": "TIO CHILOS GRILL", + "business_postal_code": "94110", + "business_state": "CA", + "inspection_date": "2016-07-05T00:00:00.000", + "inspection_id": "1797_20160705", + "inspection_score": 90, + "inspection_type": "Routine - Unscheduled", + "risk_category": "Low Risk", + "violation_description": "Unclean nonfood contact surfaces", + "violation_id": "1797_20160705_103142", + }, + { + "business_address": "1661 Tennessee St Suite 3B", + "business_city": "San Francisco Whard Restaurant", + "business_id": "66198", + "business_latitude": "37.75072", + "business_location": {"lon": -122.388478, "lat": 37.75072}, + "business_longitude": "-122.388478", + "business_name": "San Francisco Restaurant", + "business_postal_code": "94107", + "business_state": "CA", + "inspection_date": "2016-05-27T00:00:00.000", + "inspection_id": "66198_20160527", + "inspection_type": "Routine", + "inspection_score": 56, + }, + { + "business_address": "2162 24th Ave", + "business_city": "San Francisco", + "business_id": "5794", + "business_latitude": "37.747228", + "business_location": {"lon": -122.481299, "lat": 37.747228}, + "business_longitude": "-122.481299", + "business_name": "Soup House", + "business_phone_number": "+14155752700", + "business_postal_code": "94116", + "business_state": "CA", + "inspection_date": "2016-09-07T00:00:00.000", + "inspection_id": "5794_20160907", + "inspection_score": 96, + "inspection_type": "Routine - Unscheduled", + "risk_category": "Low Risk", + "violation_description": "Unapproved or unmaintained equipment or utensils", + "violation_id": "5794_20160907_103144", + }, + { + "business_address": "2162 24th Ave", + "business_city": "San Francisco", + "business_id": "5794", + "business_latitude": "37.747228", + "business_location": {"lon": -122.481299, "lat": 37.747228}, + "business_longitude": "-122.481299", + "business_name": "Soup-or-Salad", + "business_phone_number": "+14155752700", + "business_postal_code": "94116", + "business_state": "CA", + "inspection_date": "2016-09-07T00:00:00.000", + "inspection_id": "5794_20160907", + "inspection_score": 96, + "inspection_type": "Routine - Unscheduled", + "risk_category": "Low Risk", + "violation_description": "Unapproved or unmaintained equipment or utensils", + "violation_id": "5794_20160907_103144", + }, +] + + +@pytest.fixture(scope="session") +def cloudformation_outputs(): + return extract_cloudformation_outputs() + + +@pytest.fixture(scope="session") +def opensearch_password(): + return boto3.client("secretsmanager").get_secret_value(SecretId="aws-data-wrangler/opensearch_password")[ + "SecretString" + ] + + +@pytest.fixture(scope="session") +def domain_endpoint_opensearch_1_0(cloudformation_outputs): + return cloudformation_outputs["DomainEndpointwrangleros10"] + + +@pytest.fixture(scope="session") +def domain_endpoint_elasticsearch_7_10_fgac(cloudformation_outputs): + return cloudformation_outputs["DomainEndpointwrangleres710fgac"] + + +def test_connection_opensearch_1_0(domain_endpoint_opensearch_1_0): + client = wr.opensearch.connect(host=domain_endpoint_opensearch_1_0) + print(client.info()) + assert len(client.info()) > 0 + + +def test_connection_opensearch_1_0_https(domain_endpoint_opensearch_1_0): + client = wr.opensearch.connect(host=f"https://{domain_endpoint_opensearch_1_0}") + print(client.info()) + assert len(client.info()) > 0 + + +def test_connection_elasticsearch_7_10_fgac(domain_endpoint_elasticsearch_7_10_fgac, opensearch_password): + client = wr.opensearch.connect( + host=domain_endpoint_elasticsearch_7_10_fgac, username="test", password=opensearch_password + ) + print(client.info()) + assert len(client.info()) > 0 + + +@pytest.fixture(scope="session") +def opensearch_1_0_client(domain_endpoint_opensearch_1_0): + client = wr.opensearch.connect(host=domain_endpoint_opensearch_1_0) + return client + + +@pytest.fixture(scope="session") +def elasticsearch_7_10_fgac_client(domain_endpoint_elasticsearch_7_10_fgac, opensearch_password): + client = wr.opensearch.connect( + host=domain_endpoint_elasticsearch_7_10_fgac, username="test", password=opensearch_password + ) + return client + + +# testing multiple versions +@pytest.fixture(params=["opensearch_1_0_client", "elasticsearch_7_10_fgac_client"]) +def client(request): + return request.getfixturevalue(request.param) + + +def test_create_index(client): + index = "test_create_index" + wr.opensearch.delete_index(client, index) + time.sleep(0.5) # let the cluster clean up + response = wr.opensearch.create_index( + client=client, + index=index, + mappings={"properties": {"name": {"type": "text"}, "age": {"type": "integer"}}}, + settings={"index": {"number_of_shards": 1, "number_of_replicas": 1}}, + ) + assert response.get("acknowledged", False) is True + + +def test_delete_index(client): + index = "test_delete_index" + wr.opensearch.create_index(client, index=index) + response = wr.opensearch.delete_index(client, index=index) + print(response) + assert response.get("acknowledged", False) is True + + +def test_index_df(client): + response = wr.opensearch.index_df( + client, + df=pd.DataFrame([{"_id": "1", "name": "John"}, {"_id": "2", "name": "George"}, {"_id": "3", "name": "Julia"}]), + index="test_index_df1", + ) + print(response) + assert response.get("success", 0) == 3 + + +def test_index_documents(client): + response = wr.opensearch.index_documents( + client, + documents=[{"_id": "1", "name": "John"}, {"_id": "2", "name": "George"}, {"_id": "3", "name": "Julia"}], + index="test_index_documents1", + ) + print(response) + assert response.get("success", 0) == 3 + + +def test_index_documents_id_keys(client): + response = wr.opensearch.index_documents( + client, documents=inspections_documents, index="test_index_documents_id_keys", id_keys=["inspection_id"] + ) + print(response) + + +def test_index_documents_no_id_keys(client): + response = wr.opensearch.index_documents( + client, documents=inspections_documents, index="test_index_documents_no_id_keys" + ) + print(response) + + +def test_search(client): + index = "test_search" + wr.opensearch.index_documents( + client, documents=inspections_documents, index=index, id_keys=["inspection_id"], refresh="wait_for" + ) + df = wr.opensearch.search( + client, + index=index, + search_body={"query": {"match": {"business_name": "soup"}}}, + _source=["inspection_id", "business_name", "business_location"], + ) + + print("") + print(df.to_string()) + assert df.shape[0] == 3 + + +def test_search_filter_path(client): + index = "test_search" + wr.opensearch.index_documents( + client, documents=inspections_documents, index=index, id_keys=["inspection_id"], refresh="wait_for" + ) + df = wr.opensearch.search( + client, + index=index, + search_body={"query": {"match": {"business_name": "soup"}}}, + _source=["inspection_id", "business_name", "business_location"], + filter_path=["hits.hits._source"], + ) + + print("") + print(df.to_string()) + assert df.shape[0] == 3 + + +def test_search_scroll(client): + index = "test_search_scroll" + wr.opensearch.index_documents( + client, documents=inspections_documents, index=index, id_keys=["inspection_id"], refresh="wait_for" + ) + df = wr.opensearch.search( + client, index=index, is_scroll=True, _source=["inspection_id", "business_name", "business_location"] + ) + + print("") + print(df.to_string()) + assert df.shape[0] == 5 + + +def test_search_sql(client): + index = "test_search_sql" + wr.opensearch.index_documents( + client, documents=inspections_documents, index=index, id_keys=["inspection_id"], refresh="wait_for" + ) + df = wr.opensearch.search_by_sql(client, sql_query=f"select * from {index}") + + print("") + print(df.to_string()) + assert df.shape[0] == 5 + + +def test_index_json_local(client): + file_path = f"{tempfile.gettempdir()}/inspections.json" + with open(file_path, "w") as filehandle: + for doc in inspections_documents: + filehandle.write("%s\n" % json.dumps(doc)) + response = wr.opensearch.index_json(client, index="test_index_json_local", path=file_path) + print(response) + assert response.get("success", 0) == 6 + + +def test_index_json_s3(client, path): + file_path = f"{tempfile.gettempdir()}/inspections.json" + with open(file_path, "w") as filehandle: + for doc in inspections_documents: + filehandle.write("%s\n" % json.dumps(doc)) + s3 = boto3.client("s3") + path = f"{path}opensearch/inspections.json" + bucket, key = wr._utils.parse_path(path) + s3.upload_file(file_path, bucket, key) + response = wr.opensearch.index_json(client, index="test_index_json_s3", path=path) + print(response) + assert response.get("success", 0) == 6 + + +def test_index_csv_local(client): + file_path = f"{tempfile.gettempdir()}/inspections.csv" + index = "test_index_csv_local" + df = pd.DataFrame(inspections_documents) + df.to_csv(file_path, index=False) + response = wr.opensearch.index_csv(client, path=file_path, index=index) + print(response) + assert response.get("success", 0) == 6 + + +def test_index_csv_s3(client, path): + file_path = f"{tempfile.gettempdir()}/inspections.csv" + index = "test_index_csv_s3" + df = pd.DataFrame(inspections_documents) + df.to_csv(file_path, index=False) + s3 = boto3.client("s3") + path = f"{path}opensearch/inspections.csv" + bucket, key = wr._utils.parse_path(path) + s3.upload_file(file_path, bucket, key) + response = wr.opensearch.index_csv(client, path=path, index=index) + print(response) + assert response.get("success", 0) == 6 + + +@pytest.mark.skip(reason="takes a long time (~5 mins) since testing against small clusters") +def test_index_json_s3_large_file(client): + path = "s3://irs-form-990/index_2011.json" + response = wr.opensearch.index_json( + client, index="test_index_json_s3_large_file", path=path, json_path="Filings2011", id_keys=["EIN"], bulk_size=20 + ) + print(response) + assert response.get("success", 0) > 0 diff --git a/tests/test_s3_parquet.py b/tests/test_s3_parquet.py index 6152797bb..2842ae639 100644 --- a/tests/test_s3_parquet.py +++ b/tests/test_s3_parquet.py @@ -70,6 +70,27 @@ def test_read_parquet_filter_partitions(path, use_threads): assert df2.c2.astype(int).sum() == 0 +def test_read_parquet_table(path, glue_database, glue_table): + df = pd.DataFrame({"c0": [0, 1, 2], "c1": [0, 1, 2], "c2": [0, 0, 1]}) + wr.s3.to_parquet(df, path, dataset=True, database=glue_database, table=glue_table) + df_out = wr.s3.read_parquet_table(table=glue_table, database=glue_database) + assert df_out.shape == (3, 3) + + +def test_read_parquet_table_filter_partitions(path, glue_database, glue_table): + df = pd.DataFrame({"c0": [0, 1, 2], "c1": [0, 1, 2], "c2": [0, 0, 1]}) + wr.s3.to_parquet(df, path, dataset=True, partition_cols=["c1", "c2"], database=glue_database, table=glue_table) + df_out = wr.s3.read_parquet_table( + table=glue_table, database=glue_database, partition_filter=lambda x: True if x["c1"] == "0" else False + ) + assert df_out.shape == (1, 3) + assert df_out.c0.astype(int).sum() == 0 + with pytest.raises(wr.exceptions.NoFilesFound): + wr.s3.read_parquet_table( + table=glue_table, database=glue_database, partition_filter=lambda x: True if x["c1"] == "3" else False + ) + + def test_parquet(path): df_file = pd.DataFrame({"id": [1, 2, 3]}) path_file = f"{path}test_parquet_file.parquet" diff --git a/tutorials/001 - Introduction.ipynb b/tutorials/001 - Introduction.ipynb index 2ef8932cf..e3e198c85 100644 --- a/tutorials/001 - Introduction.ipynb +++ b/tutorials/001 - Introduction.ipynb @@ -19,7 +19,7 @@ "\n", "Built on top of other open-source projects like [Pandas](https://github.com/pandas-dev/pandas), [Apache Arrow](https://github.com/apache/arrow) and [Boto3](https://github.com/boto/boto3), it offers abstracted functions to execute usual ETL tasks like load/unload data from **Data Lakes**, **Data Warehouses** and **Databases**.\n", "\n", - "Check our [list of functionalities](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html)." + "Check our [list of functionalities](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html)." ] }, { @@ -30,15 +30,15 @@ "\n", "The Wrangler runs almost anywhere over Python 3.6, 3.7, 3.8 and 3.9, so there are several different ways to install it in the desired enviroment.\n", "\n", - " - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#pypi-pip)\n", - " - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#conda)\n", - " - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-lambda-layer)\n", - " - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-glue-python-shell-jobs)\n", - " - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#aws-glue-pyspark-jobs)\n", - " - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#amazon-sagemaker-notebook)\n", - " - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#amazon-sagemaker-notebook-lifecycle)\n", - " - [EMR Cluster](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#emr-cluster)\n", - " - [From source](https://aws-data-wrangler.readthedocs.io/en/2.11.0/install.html#from-source)\n", + " - [PyPi (pip)](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#pypi-pip)\n", + " - [Conda](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#conda)\n", + " - [AWS Lambda Layer](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#aws-lambda-layer)\n", + " - [AWS Glue Python Shell Jobs](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#aws-glue-python-shell-jobs)\n", + " - [AWS Glue PySpark Jobs](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#aws-glue-pyspark-jobs)\n", + " - [Amazon SageMaker Notebook](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#amazon-sagemaker-notebook)\n", + " - [Amazon SageMaker Notebook Lifecycle](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#amazon-sagemaker-notebook-lifecycle)\n", + " - [EMR Cluster](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#emr-cluster)\n", + " - [From source](https://aws-data-wrangler.readthedocs.io/en/2.12.1/install.html#from-source)\n", "\n", "Some good practices for most of the above methods are:\n", " - Use new and individual Virtual Environments for each project ([venv](https://docs.python.org/3/library/venv.html))\n", diff --git a/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb b/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb index 41797521f..32c118764 100644 --- a/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb +++ b/tutorials/007 - Redshift, MySQL, PostgreSQL, SQL Server.ipynb @@ -10,14 +10,14 @@ "\n", "[Wrangler](https://github.com/awslabs/aws-data-wrangler)'s Redshift, MySQL and PostgreSQL have two basic function in common that tries to follow the Pandas conventions, but add more data type consistency.\n", "\n", - "- [wr.redshift.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.redshift.to_sql.html)\n", - "- [wr.redshift.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.redshift.read_sql_query.html)\n", - "- [wr.mysql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.mysql.to_sql.html)\n", - "- [wr.mysql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.mysql.read_sql_query.html)\n", - "- [wr.postgresql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.postgresql.to_sql.html)\n", - "- [wr.postgresql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.postgresql.read_sql_query.html)\n", - "- [wr.sqlserver.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.sqlserver.to_sql.html)\n", - "- [wr.sqlserver.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.sqlserver.read_sql_query.html)" + "- [wr.redshift.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.redshift.to_sql.html)\n", + "- [wr.redshift.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.redshift.read_sql_query.html)\n", + "- [wr.mysql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.mysql.to_sql.html)\n", + "- [wr.mysql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.mysql.read_sql_query.html)\n", + "- [wr.postgresql.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.postgresql.to_sql.html)\n", + "- [wr.postgresql.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.postgresql.read_sql_query.html)\n", + "- [wr.sqlserver.to_sql()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.sqlserver.to_sql.html)\n", + "- [wr.sqlserver.read_sql_query()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.sqlserver.read_sql_query.html)" ] }, { @@ -41,10 +41,10 @@ "source": [ "## Connect using the Glue Catalog Connections\n", "\n", - "- [wr.redshift.connect()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.redshift.connect.html)\n", - "- [wr.mysql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.mysql.connect.html)\n", - "- [wr.postgresql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.postgresql.connect.html)\n", - "- [wr.sqlserver.connect()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.sqlserver.connect.html)" + "- [wr.redshift.connect()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.redshift.connect.html)\n", + "- [wr.mysql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.mysql.connect.html)\n", + "- [wr.postgresql.connect()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.postgresql.connect.html)\n", + "- [wr.sqlserver.connect()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.sqlserver.connect.html)" ] }, { diff --git a/tutorials/014 - Schema Evolution.ipynb b/tutorials/014 - Schema Evolution.ipynb index a48b202cb..c8a852431 100644 --- a/tutorials/014 - Schema Evolution.ipynb +++ b/tutorials/014 - Schema Evolution.ipynb @@ -10,8 +10,8 @@ "\n", "Wrangler support new **columns** on Parquet Dataset through:\n", "\n", - "- [wr.s3.to_parquet()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet)\n", - "- [wr.s3.store_parquet_metadata()](https://aws-data-wrangler.readthedocs.io/en/2.11.0/stubs/awswrangler.s3.store_parquet_metadata.html#awswrangler.s3.store_parquet_metadata) i.e. \"Crawler\"" + "- [wr.s3.to_parquet()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet)\n", + "- [wr.s3.store_parquet_metadata()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.s3.store_parquet_metadata.html#awswrangler.s3.store_parquet_metadata) i.e. \"Crawler\"" ] }, { diff --git a/tutorials/021 - Global Configurations.ipynb b/tutorials/021 - Global Configurations.ipynb index 39615e993..1f15b1736 100644 --- a/tutorials/021 - Global Configurations.ipynb +++ b/tutorials/021 - Global Configurations.ipynb @@ -13,7 +13,7 @@ "- **Environment variables**\n", "- **wr.config**\n", "\n", - "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html) to see if your function has some argument that can be configured through Global configurations.*\n", + "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html) to see if your function has some argument that can be configured through Global configurations.*\n", "\n", "*P.P.S. One exception to the above mentioned rules is the `botocore_config` property. It cannot be set through environment variables\n", "but only via `wr.config`. It will be used as the `botocore.config.Config` for all underlying `boto3` calls.\n", diff --git a/tutorials/022 - Writing Partitions Concurrently.ipynb b/tutorials/022 - Writing Partitions Concurrently.ipynb index ecd861ec2..65ef49c17 100644 --- a/tutorials/022 - Writing Partitions Concurrently.ipynb +++ b/tutorials/022 - Writing Partitions Concurrently.ipynb @@ -13,7 +13,7 @@ " If True will increase the parallelism level during the partitions writing. It will decrease the\n", " writing time and increase the memory usage.\n", "\n", - "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html) to see it has some argument that can be configured through Global configurations.*" + "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html) to see it has some argument that can be configured through Global configurations.*" ] }, { diff --git a/tutorials/023 - Flexible Partitions Filter.ipynb b/tutorials/023 - Flexible Partitions Filter.ipynb index c1c54377d..73834fef9 100644 --- a/tutorials/023 - Flexible Partitions Filter.ipynb +++ b/tutorials/023 - Flexible Partitions Filter.ipynb @@ -16,7 +16,7 @@ " - Ignored if `dataset=False`.\n", " \n", "\n", - "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.11.0/api.html) to see it has some argument that can be configured through Global configurations.*" + "*P.S. Check the [function API doc](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html) to see it has some argument that can be configured through Global configurations.*" ] }, { diff --git a/tutorials/031 - OpenSearch.ipynb b/tutorials/031 - OpenSearch.ipynb new file mode 100644 index 000000000..afe254669 --- /dev/null +++ b/tutorials/031 - OpenSearch.ipynb @@ -0,0 +1,1668 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "[![AWS Data Wrangler](_static/logo.png \"AWS Data Wrangler\")](https://github.com/awslabs/aws-data-wrangler)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# 31 - OpenSearch" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Table of Contents\n", + "* [1. Initialize](#initialize)\n", + " * [Connect to your Amazon OpenSearch domain](#connect)\n", + " * [Enter your bucket name](#bucket)\n", + " * [Initialize sample data](#sample-data)\n", + "* [2. Indexing (load)](#indexing)\n", + "\t* [Index documents (no Pandas)](#index-documents)\n", + "\t* [Index json file](#index-json)\n", + " * [Index CSV](#index-csv)\n", + "* [3. Search](#search)\n", + "\t* [3.1 Search by DSL](#search-dsl)\n", + "\t* [3.2 Search by SQL](#search-sql)\n", + "* [4. Delete Indices](#delete-index)\n", + "* [5. Bonus - Prepare data and index from DataFrame](#bonus)\n", + "\t* [Prepare the data for indexing](#prepare-data)\n", + " * [Create index with mapping](#create-index-w-mapping)\n", + " * [Index dataframe](#index-df)\n", + " * [Execute geo query](#search-geo)\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 1. Initialize" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import awswrangler as wr" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Connect to your Amazon OpenSearch domain" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "client = wr.opensearch.connect(\n", + " host='OPENSEARCH-ENDPOINT',\n", + "# username='FGAC-USERNAME(OPTIONAL)',\n", + "# password='FGAC-PASSWORD(OPTIONAL)'\n", + ")\n", + "client.info()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Enter your bucket name" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "bucket = 'BUCKET'" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Initialize sample data" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "sf_restaurants_inspections = [\n", + " {\n", + " \"inspection_id\": \"24936_20160609\",\n", + " \"business_address\": \"315 California St\",\n", + " \"business_city\": \"San Francisco\",\n", + " \"business_id\": \"24936\",\n", + " \"business_location\": {\"lon\": -122.400152, \"lat\": 37.793199},\n", + " \"business_name\": \"San Francisco Soup Company\",\n", + " \"business_postal_code\": \"94104\",\n", + " \"business_state\": \"CA\",\n", + " \"inspection_date\": \"2016-06-09T00:00:00.000\",\n", + " \"inspection_score\": 77,\n", + " \"inspection_type\": \"Routine - Unscheduled\",\n", + " \"risk_category\": \"Low Risk\",\n", + " \"violation_description\": \"Improper food labeling or menu misrepresentation\",\n", + " \"violation_id\": \"24936_20160609_103141\",\n", + " },\n", + " {\n", + " \"inspection_id\": \"60354_20161123\",\n", + " \"business_address\": \"10 Mason St\",\n", + " \"business_city\": \"San Francisco\",\n", + " \"business_id\": \"60354\",\n", + " \"business_location\": {\"lon\": -122.409061, \"lat\": 37.783527},\n", + " \"business_name\": \"Soup Unlimited\",\n", + " \"business_postal_code\": \"94102\",\n", + " \"business_state\": \"CA\",\n", + " \"inspection_date\": \"2016-11-23T00:00:00.000\",\n", + " \"inspection_type\": \"Routine\",\n", + " \"inspection_score\": 95,\n", + " },\n", + " {\n", + " \"inspection_id\": \"1797_20160705\",\n", + " \"business_address\": \"2872 24th St\",\n", + " \"business_city\": \"San Francisco\",\n", + " \"business_id\": \"1797\",\n", + " \"business_location\": {\"lon\": -122.409752, \"lat\": 37.752807},\n", + " \"business_name\": \"TIO CHILOS GRILL\",\n", + " \"business_postal_code\": \"94110\",\n", + " \"business_state\": \"CA\",\n", + " \"inspection_date\": \"2016-07-05T00:00:00.000\",\n", + " \"inspection_score\": 90,\n", + " \"inspection_type\": \"Routine - Unscheduled\",\n", + " \"risk_category\": \"Low Risk\",\n", + " \"violation_description\": \"Unclean nonfood contact surfaces\",\n", + " \"violation_id\": \"1797_20160705_103142\",\n", + " },\n", + " {\n", + " \"inspection_id\": \"66198_20160527\",\n", + " \"business_address\": \"1661 Tennessee St Suite 3B\",\n", + " \"business_city\": \"San Francisco Whard Restaurant\",\n", + " \"business_id\": \"66198\",\n", + " \"business_location\": {\"lon\": -122.388478, \"lat\": 37.75072},\n", + " \"business_name\": \"San Francisco Restaurant\",\n", + " \"business_postal_code\": \"94107\",\n", + " \"business_state\": \"CA\",\n", + " \"inspection_date\": \"2016-05-27T00:00:00.000\",\n", + " \"inspection_type\": \"Routine\",\n", + " \"inspection_score\": 56,\n", + " },\n", + " {\n", + " \"inspection_id\": \"5794_20160907\",\n", + " \"business_address\": \"2162 24th Ave\",\n", + " \"business_city\": \"San Francisco\",\n", + " \"business_id\": \"5794\",\n", + " \"business_location\": {\"lon\": -122.481299, \"lat\": 37.747228},\n", + " \"business_name\": \"Soup House\",\n", + " \"business_phone_number\": \"+14155752700\",\n", + " \"business_postal_code\": \"94116\",\n", + " \"business_state\": \"CA\",\n", + " \"inspection_date\": \"2016-09-07T00:00:00.000\",\n", + " \"inspection_score\": 96,\n", + " \"inspection_type\": \"Routine - Unscheduled\",\n", + " \"risk_category\": \"Low Risk\",\n", + " \"violation_description\": \"Unapproved or unmaintained equipment or utensils\",\n", + " \"violation_id\": \"5794_20160907_103144\",\n", + " },\n", + " \n", + " # duplicate record\n", + " {\n", + " \"inspection_id\": \"5794_20160907\",\n", + " \"business_address\": \"2162 24th Ave\",\n", + " \"business_city\": \"San Francisco\",\n", + " \"business_id\": \"5794\",\n", + " \"business_location\": {\"lon\": -122.481299, \"lat\": 37.747228},\n", + " \"business_name\": \"Soup-or-Salad\",\n", + " \"business_phone_number\": \"+14155752700\",\n", + " \"business_postal_code\": \"94116\",\n", + " \"business_state\": \"CA\",\n", + " \"inspection_date\": \"2016-09-07T00:00:00.000\",\n", + " \"inspection_score\": 96,\n", + " \"inspection_type\": \"Routine - Unscheduled\",\n", + " \"risk_category\": \"Low Risk\",\n", + " \"violation_description\": \"Unapproved or unmaintained equipment or utensils\",\n", + " \"violation_id\": \"5794_20160907_103144\",\n", + " },\n", + "]" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 2. Indexing (load)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Index documents (no Pandas)" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Indexing: 100% (6/6)|####################################|Elapsed Time: 0:00:01" + ] + }, + { + "data": { + "text/plain": [ + "{'success': 6, 'errors': []}" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# index documents w/o providing keys (_id is auto-generated)\n", + "wr.opensearch.index_documents(\n", + " client,\n", + " documents=sf_restaurants_inspections,\n", + " index=\"sf_restaurants_inspections\" \n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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_idbusiness_nameinspection_idbusiness_location.lonbusiness_location.lat
0663dd72d-0da4-495b-b0ae-ed000105ae73TIO CHILOS GRILL1797_20160705-122.40975237.752807
1ff2f50f6-5415-4706-9bcb-af7c5eb0afa3Soup House5794_20160907-122.48129937.747228
2b9e8f6a2-8fd1-4660-b041-2997a1a80984San Francisco Soup Company24936_20160609-122.40015237.793199
356b352e6-102b-4eff-8296-7e1fb2459babSoup Unlimited60354_20161123-122.40906137.783527
46fec5411-f79a-48e4-be7b-e0e44d5ebbabSan Francisco Restaurant66198_20160527-122.38847837.750720
57ba4fb17-f9a9-49da-b90e-8b3553d6d97cSoup-or-Salad5794_20160907-122.48129937.747228
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" + ], + "text/plain": [ + " _id business_name \\\n", + "0 663dd72d-0da4-495b-b0ae-ed000105ae73 TIO CHILOS GRILL \n", + "1 ff2f50f6-5415-4706-9bcb-af7c5eb0afa3 Soup House \n", + "2 b9e8f6a2-8fd1-4660-b041-2997a1a80984 San Francisco Soup Company \n", + "3 56b352e6-102b-4eff-8296-7e1fb2459bab Soup Unlimited \n", + "4 6fec5411-f79a-48e4-be7b-e0e44d5ebbab San Francisco Restaurant \n", + "5 7ba4fb17-f9a9-49da-b90e-8b3553d6d97c Soup-or-Salad \n", + "\n", + " inspection_id business_location.lon business_location.lat \n", + "0 1797_20160705 -122.409752 37.752807 \n", + "1 5794_20160907 -122.481299 37.747228 \n", + "2 24936_20160609 -122.400152 37.793199 \n", + "3 60354_20161123 -122.409061 37.783527 \n", + "4 66198_20160527 -122.388478 37.750720 \n", + "5 5794_20160907 -122.481299 37.747228 " + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# read all documents. There are total 6 documents\n", + "wr.opensearch.search(\n", + " client,\n", + " index=\"sf_restaurants_inspections\",\n", + " _source=[\"inspection_id\", \"business_name\", \"business_location\"]\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Index json file" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd\n", + "df = pd.DataFrame(sf_restaurants_inspections)\n", + "path = f\"s3://{bucket}/json/sf_restaurants_inspections.json\"\n", + "wr.s3.to_json(df, path,orient='records',lines=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Indexing: 100% (6/6)|####################################|Elapsed Time: 0:00:00" + ] + }, + { + "data": { + "text/plain": [ + "{'success': 6, 'errors': []}" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# index json w/ providing keys\n", + "wr.opensearch.index_json(\n", + " client,\n", + " path=path, # path can be s3 or local\n", + " index=\"sf_restaurants_inspections_dedup\",\n", + " id_keys=[\"inspection_id\"] # can be multiple fields. arg applicable to all index_* functions\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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_idbusiness_nameinspection_idbusiness_location.lonbusiness_location.lat
024936_20160609San Francisco Soup Company24936_20160609-122.40015237.793199
166198_20160527San Francisco Restaurant66198_20160527-122.38847837.750720
25794_20160907Soup-or-Salad5794_20160907-122.48129937.747228
360354_20161123Soup Unlimited60354_20161123-122.40906137.783527
41797_20160705TIO CHILOS GRILL1797_20160705-122.40975237.752807
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" + ], + "text/plain": [ + " _id business_name inspection_id \\\n", + "0 24936_20160609 San Francisco Soup Company 24936_20160609 \n", + "1 66198_20160527 San Francisco Restaurant 66198_20160527 \n", + "2 5794_20160907 Soup-or-Salad 5794_20160907 \n", + "3 60354_20161123 Soup Unlimited 60354_20161123 \n", + "4 1797_20160705 TIO CHILOS GRILL 1797_20160705 \n", + "\n", + " business_location.lon business_location.lat \n", + "0 -122.400152 37.793199 \n", + "1 -122.388478 37.750720 \n", + "2 -122.481299 37.747228 \n", + "3 -122.409061 37.783527 \n", + "4 -122.409752 37.752807 " + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# now there are no duplicates. There are total 5 documents\n", + "wr.opensearch.search(\n", + " client,\n", + " index=\"sf_restaurants_inspections_dedup\",\n", + " _source=[\"inspection_id\", \"business_name\", \"business_location\"]\n", + " )" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Index CSV" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Indexing: 100% (1000/1000)|##############################|Elapsed Time: 0:00:00" + ] + }, + { + "data": { + "text/plain": [ + "{'success': 1000, 'errors': []}" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wr.opensearch.index_csv(\n", + " client, \n", + " index=\"nyc_restaurants_inspections_sample\", \n", + " path='https://data.cityofnewyork.us/api/views/43nn-pn8j/rows.csv?accessType=DOWNLOAD', # index_csv supports local, s3 and url path\n", + " id_keys=[\"CAMIS\"],\n", + " pandas_kwargs={'na_filter': True, 'nrows': 1000}, # pandas.read_csv() args - https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.read_csv.html\n", + " bulk_size=500 # modify based on your cluster size\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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_idCAMISDBABOROBUILDINGSTREETZIPCODEPHONECUISINE DESCRIPTIONINSPECTION DATE...RECORD DATEINSPECTION TYPELatitudeLongitudeCommunity BoardCouncil DistrictCensus TractBINBBLNTA
04161042641610426GLOW THAI RESTAURANTBrooklyn71073 AVENUE11209.07187481920Thai02/26/2020...10/04/2021Cycle Inspection / Re-inspection40.633865-74.026798310.043.06800.03146519.03.058910e+09BK31
14081116240811162CARMINE'SManhattan2450BROADWAY10024.02123622200Italian05/28/2019...10/04/2021Cycle Inspection / Initial Inspection40.791168-73.974308107.06.017900.01033560.01.012380e+09MN12
25001211350012113TANGQueens196-50NORTHERN BOULEVARD11358.07182797080Korean08/16/2018...10/04/2021Cycle Inspection / Initial Inspection40.757850-73.784593411.019.0145101.04124565.04.055200e+09QN48
35001461850014618TOTTO RAMENManhattan248EAST 52 STREET10022.02124210052Japanese08/20/2018...10/04/2021Cycle Inspection / Re-inspection40.756596-73.968749106.04.09800.01038490.01.013250e+09MN19
45004578250045782OLLIE'S CHINESE RESTAURANTManhattan2705BROADWAY10025.02129323300Chinese10/21/2019...10/04/2021Cycle Inspection / Re-inspection40.799318-73.968440107.06.019100.01056562.01.018750e+09MN12
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5 rows × 27 columns

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" + ], + "text/plain": [ + " _id CAMIS DBA BORO BUILDING \\\n", + "0 41610426 41610426 GLOW THAI RESTAURANT Brooklyn 7107 \n", + "1 40811162 40811162 CARMINE'S Manhattan 2450 \n", + "2 50012113 50012113 TANG Queens 196-50 \n", + "3 50014618 50014618 TOTTO RAMEN Manhattan 248 \n", + "4 50045782 50045782 OLLIE'S CHINESE RESTAURANT Manhattan 2705 \n", + "\n", + " STREET ZIPCODE PHONE CUISINE DESCRIPTION \\\n", + "0 3 AVENUE 11209.0 7187481920 Thai \n", + "1 BROADWAY 10024.0 2123622200 Italian \n", + "2 NORTHERN BOULEVARD 11358.0 7182797080 Korean \n", + "3 EAST 52 STREET 10022.0 2124210052 Japanese \n", + "4 BROADWAY 10025.0 2129323300 Chinese \n", + "\n", + " INSPECTION DATE ... RECORD DATE INSPECTION TYPE \\\n", + "0 02/26/2020 ... 10/04/2021 Cycle Inspection / Re-inspection \n", + "1 05/28/2019 ... 10/04/2021 Cycle Inspection / Initial Inspection \n", + "2 08/16/2018 ... 10/04/2021 Cycle Inspection / Initial Inspection \n", + "3 08/20/2018 ... 10/04/2021 Cycle Inspection / Re-inspection \n", + "4 10/21/2019 ... 10/04/2021 Cycle Inspection / Re-inspection \n", + "\n", + " Latitude Longitude Community Board Council District Census Tract \\\n", + "0 40.633865 -74.026798 310.0 43.0 6800.0 \n", + "1 40.791168 -73.974308 107.0 6.0 17900.0 \n", + "2 40.757850 -73.784593 411.0 19.0 145101.0 \n", + "3 40.756596 -73.968749 106.0 4.0 9800.0 \n", + "4 40.799318 -73.968440 107.0 6.0 19100.0 \n", + "\n", + " BIN BBL NTA \n", + "0 3146519.0 3.058910e+09 BK31 \n", + "1 1033560.0 1.012380e+09 MN12 \n", + "2 4124565.0 4.055200e+09 QN48 \n", + "3 1038490.0 1.013250e+09 MN19 \n", + "4 1056562.0 1.018750e+09 MN12 \n", + "\n", + "[5 rows x 27 columns]" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wr.opensearch.search(\n", + " client,\n", + " index=\"nyc_restaurants_inspections_sample\",\n", + " size=5\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 3. Search\n", + "#### Search results are returned as Pandas DataFrame" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3.1 Search by DSL" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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_idbusiness_nameinspection_idbusiness_location.lonbusiness_location.lat
0ff2f50f6-5415-4706-9bcb-af7c5eb0afa3Soup House5794_20160907-122.48129937.747228
17ba4fb17-f9a9-49da-b90e-8b3553d6d97cSoup-or-Salad5794_20160907-122.48129937.747228
2b9e8f6a2-8fd1-4660-b041-2997a1a80984San Francisco Soup Company24936_20160609-122.40015237.793199
356b352e6-102b-4eff-8296-7e1fb2459babSoup Unlimited60354_20161123-122.40906137.783527
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" + ], + "text/plain": [ + " _id business_name \\\n", + "0 ff2f50f6-5415-4706-9bcb-af7c5eb0afa3 Soup House \n", + "1 7ba4fb17-f9a9-49da-b90e-8b3553d6d97c Soup-or-Salad \n", + "2 b9e8f6a2-8fd1-4660-b041-2997a1a80984 San Francisco Soup Company \n", + "3 56b352e6-102b-4eff-8296-7e1fb2459bab Soup Unlimited \n", + "\n", + " inspection_id business_location.lon business_location.lat \n", + "0 5794_20160907 -122.481299 37.747228 \n", + "1 5794_20160907 -122.481299 37.747228 \n", + "2 24936_20160609 -122.400152 37.793199 \n", + "3 60354_20161123 -122.409061 37.783527 " + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# add a search query. search all soup businesses \n", + "wr.opensearch.search(\n", + " client,\n", + " index=\"sf_restaurants_inspections\",\n", + " _source=[\"inspection_id\", \"business_name\", \"business_location\"],\n", + " filter_path=[\"hits.hits._id\",\"hits.hits._source\"],\n", + " search_body={\n", + " \"query\": {\n", + " \"match\": {\n", + " \"business_name\": \"soup\"\n", + " }\n", + " }\n", + " }\n", + " )" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### 3.1 Search by SQL" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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_index_type_id_scorebusiness_nameinspection_score
0sf_restaurants_inspections_dedup_doc5794_20160907NoneSoup-or-Salad96
1sf_restaurants_inspections_dedup_doc60354_20161123NoneSoup Unlimited95
2sf_restaurants_inspections_dedup_doc24936_20160609NoneSan Francisco Soup Company77
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" + ], + "text/plain": [ + " _index _type _id _score \\\n", + "0 sf_restaurants_inspections_dedup _doc 5794_20160907 None \n", + "1 sf_restaurants_inspections_dedup _doc 60354_20161123 None \n", + "2 sf_restaurants_inspections_dedup _doc 24936_20160609 None \n", + "\n", + " business_name inspection_score \n", + "0 Soup-or-Salad 96 \n", + "1 Soup Unlimited 95 \n", + "2 San Francisco Soup Company 77 " + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wr.opensearch.search_by_sql(\n", + " client,\n", + " sql_query=\"\"\"SELECT business_name, inspection_score \n", + " FROM sf_restaurants_inspections_dedup\n", + " WHERE business_name LIKE '%soup%'\n", + " ORDER BY inspection_score DESC LIMIT 5\"\"\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 4. Delete Indices" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "jupyter": { + "outputs_hidden": false + }, + "pycharm": { + "name": "#%%\n" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "{'acknowledged': True}" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wr.opensearch.delete_index(\n", + " client=client,\n", + " index=\"sf_restaurants_inspections\"\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## 5. Bonus - Prepare data and index from DataFrame" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "For this exercise we'll use [DOHMH New York City Restaurant Inspection Results dataset](https://data.cityofnewyork.us/Health/DOHMH-New-York-City-Restaurant-Inspection-Results/43nn-pn8j)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv('https://data.cityofnewyork.us/api/views/43nn-pn8j/rows.csv?accessType=DOWNLOAD')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Prepare the data for indexing" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "metadata": {}, + "outputs": [], + "source": [ + "# fields names underscore casing \n", + "df.columns = [col.lower().replace(' ', '_') for col in df.columns]\n", + "\n", + "# convert lon/lat to OpenSearch geo_point\n", + "df['business_location'] = \"POINT (\" + df.longitude.fillna('0').astype(str) + \" \" + df.latitude.fillna('0').astype(str) + \")\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Create index with mapping" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "{'acknowledged': True,\n", + " 'shards_acknowledged': True,\n", + " 'index': 'nyc_restaurants_inspections'}" + ] + }, + "execution_count": 19, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# delete index if exists\n", + "wr.opensearch.delete_index(\n", + " client=client,\n", + " index=\"nyc_restaurants\"\n", + " \n", + ")\n", + "\n", + "# use dynamic_template to map date fields\n", + "# define business_location as geo_point\n", + "wr.opensearch.create_index(\n", + " client=client,\n", + " index=\"nyc_restaurants_inspections\",\n", + " mappings={\n", + " \"dynamic_templates\" : [\n", + " {\n", + " \"dates\" : {\n", + " \"match\" : \"*date\",\n", + " \"mapping\" : {\n", + " \"type\" : \"date\",\n", + " \"format\" : 'MM/dd/yyyy'\n", + " }\n", + " }\n", + " }\n", + " ],\n", + " \"properties\": {\n", + " \"business_location\": {\n", + " \"type\": \"geo_point\"\n", + " }\n", + " }\n", + " } \n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "\n", + "### Index dataframe" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Indexing: 100% (382655/382655)|##########################|Elapsed Time: 0:04:15" + ] + }, + { + "data": { + "text/plain": [ + "{'success': 382655, 'errors': []}" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wr.opensearch.index_df(\n", + " client,\n", + " df=df,\n", + " index=\"nyc_restaurants_inspections\",\n", + " id_keys=[\"camis\"],\n", + " bulk_size=1000\n", + ")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Execute geo query\n", + "#### Sort restaurants by distance from Times-Square" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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camisdbaborobuildingstreetzipcodephonecuisine_descriptioninspection_dateaction...inspection_typelatitudelongitudecommunity_boardcouncil_districtcensus_tractbinbblntabusiness_location
041551304THE COUNTERManhattan7TIMES SQUARE10036.02129976801American12/22/2016Violations were cited in the following area(s)....Cycle Inspection / Initial Inspection40.755908-73.986681105.03.011300.01086069.01.009940e+09MN17POINT (-73.986680953809 40.755907817312)
150055665ANN INC CAFEManhattan7TIMES SQUARE10036.02125413287American12/11/2019Violations were cited in the following area(s)....Cycle Inspection / Initial Inspection40.755908-73.986681105.03.011300.01086069.01.009940e+09MN17POINT (-73.986680953809 40.755907817312)
250049552ERNST AND YOUNGManhattan5TIMES SQ10036.02127739994Coffee/Tea11/30/2018Violations were cited in the following area(s)....Cycle Inspection / Initial Inspection40.755702-73.987208105.03.011300.01024656.01.010130e+09MN17POINT (-73.987207980138 40.755702020307)
350014078RED LOBSTERManhattan5TIMES SQ10036.02127306706Seafood10/03/2017Violations were cited in the following area(s)....Cycle Inspection / Initial Inspection40.755702-73.987208105.03.011300.01024656.01.010130e+09MN17POINT (-73.987207980138 40.755702020307)
450015171NEW AMSTERDAM THEATERManhattan214WEST 42 STREET10036.02125825472American06/26/2018Violations were cited in the following area(s)....Cycle Inspection / Re-inspection40.756317-73.987652105.03.011300.01024660.01.010130e+09MN17POINT (-73.987651832547 40.756316895053)
..................................................................
9541552060PROSKAUER ROSEManhattan11TIMES SQUARE10036.02129695493American08/11/2017Violations were cited in the following area(s)....Administrative Miscellaneous / Initial Inspection40.756891-73.990023105.03.011300.01087978.01.010138e+09MN17POINT (-73.990023200823 40.756890780426)
9641242148GABBY O'HARA'SManhattan123WEST 39 STREET10018.02122788984Irish07/30/2019Violations were cited in the following area(s)....Cycle Inspection / Re-inspection40.753405-73.986602105.04.011300.01080611.01.008150e+09MN17POINT (-73.986602050292 40.753404587174)
9750095860THE TIMES EATERYManhattan6808 AVENUE10036.06463867787American02/28/2020Violations were cited in the following area(s)....Pre-permit (Operational) / Initial Inspection40.757991-73.989218105.03.011900.01024703.01.010150e+09MN17POINT (-73.989218092096 40.757991356019)
9850072861ITSUManhattan5307 AVENUE10018.09176393645Asian/Asian Fusion09/10/2018Violations were cited in the following area(s)....Pre-permit (Operational) / Initial Inspection40.753844-73.988551105.03.011300.01014485.01.007880e+09MN17POINT (-73.988551029682 40.753843959794)
9950068109LUKE'S LOBSTERManhattan1407BROADWAY10018.09174759192Seafood09/06/2017Violations were cited in the following area(s)....Pre-permit (Operational) / Initial Inspection40.753432-73.987151105.03.011300.01015265.01.008140e+09MN17POINT (-73.98715066791 40.753432097521)
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100 rows × 27 columns

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" + ], + "text/plain": [ + " camis dba boro building street \\\n", + "0 41551304 THE COUNTER Manhattan 7 TIMES SQUARE \n", + "1 50055665 ANN INC CAFE Manhattan 7 TIMES SQUARE \n", + "2 50049552 ERNST AND YOUNG Manhattan 5 TIMES SQ \n", + "3 50014078 RED LOBSTER Manhattan 5 TIMES SQ \n", + "4 50015171 NEW AMSTERDAM THEATER Manhattan 214 WEST 42 STREET \n", + ".. ... ... ... ... ... \n", + "95 41552060 PROSKAUER ROSE Manhattan 11 TIMES SQUARE \n", + "96 41242148 GABBY O'HARA'S Manhattan 123 WEST 39 STREET \n", + "97 50095860 THE TIMES EATERY Manhattan 680 8 AVENUE \n", + "98 50072861 ITSU Manhattan 530 7 AVENUE \n", + "99 50068109 LUKE'S LOBSTER Manhattan 1407 BROADWAY \n", + "\n", + " zipcode phone cuisine_description inspection_date \\\n", + "0 10036.0 2129976801 American 12/22/2016 \n", + "1 10036.0 2125413287 American 12/11/2019 \n", + "2 10036.0 2127739994 Coffee/Tea 11/30/2018 \n", + "3 10036.0 2127306706 Seafood 10/03/2017 \n", + "4 10036.0 2125825472 American 06/26/2018 \n", + ".. ... ... ... ... \n", + "95 10036.0 2129695493 American 08/11/2017 \n", + "96 10018.0 2122788984 Irish 07/30/2019 \n", + "97 10036.0 6463867787 American 02/28/2020 \n", + "98 10018.0 9176393645 Asian/Asian Fusion 09/10/2018 \n", + "99 10018.0 9174759192 Seafood 09/06/2017 \n", + "\n", + " action ... \\\n", + "0 Violations were cited in the following area(s). ... \n", + "1 Violations were cited in the following area(s). ... \n", + "2 Violations were cited in the following area(s). ... \n", + "3 Violations were cited in the following area(s). ... \n", + "4 Violations were cited in the following area(s). ... \n", + ".. ... ... \n", + "95 Violations were cited in the following area(s). ... \n", + "96 Violations were cited in the following area(s). ... \n", + "97 Violations were cited in the following area(s). ... \n", + "98 Violations were cited in the following area(s). ... \n", + "99 Violations were cited in the following area(s). ... \n", + "\n", + " inspection_type latitude longitude \\\n", + "0 Cycle Inspection / Initial Inspection 40.755908 -73.986681 \n", + "1 Cycle Inspection / Initial Inspection 40.755908 -73.986681 \n", + "2 Cycle Inspection / Initial Inspection 40.755702 -73.987208 \n", + "3 Cycle Inspection / Initial Inspection 40.755702 -73.987208 \n", + "4 Cycle Inspection / Re-inspection 40.756317 -73.987652 \n", + ".. ... ... ... \n", + "95 Administrative Miscellaneous / Initial Inspection 40.756891 -73.990023 \n", + "96 Cycle Inspection / Re-inspection 40.753405 -73.986602 \n", + "97 Pre-permit (Operational) / Initial Inspection 40.757991 -73.989218 \n", + "98 Pre-permit (Operational) / Initial Inspection 40.753844 -73.988551 \n", + "99 Pre-permit (Operational) / Initial Inspection 40.753432 -73.987151 \n", + "\n", + " community_board council_district census_tract bin bbl \\\n", + "0 105.0 3.0 11300.0 1086069.0 1.009940e+09 \n", + "1 105.0 3.0 11300.0 1086069.0 1.009940e+09 \n", + "2 105.0 3.0 11300.0 1024656.0 1.010130e+09 \n", + "3 105.0 3.0 11300.0 1024656.0 1.010130e+09 \n", + "4 105.0 3.0 11300.0 1024660.0 1.010130e+09 \n", + ".. ... ... ... ... ... \n", + "95 105.0 3.0 11300.0 1087978.0 1.010138e+09 \n", + "96 105.0 4.0 11300.0 1080611.0 1.008150e+09 \n", + "97 105.0 3.0 11900.0 1024703.0 1.010150e+09 \n", + "98 105.0 3.0 11300.0 1014485.0 1.007880e+09 \n", + "99 105.0 3.0 11300.0 1015265.0 1.008140e+09 \n", + "\n", + " nta business_location \n", + "0 MN17 POINT (-73.986680953809 40.755907817312) \n", + "1 MN17 POINT (-73.986680953809 40.755907817312) \n", + "2 MN17 POINT (-73.987207980138 40.755702020307) \n", + "3 MN17 POINT (-73.987207980138 40.755702020307) \n", + "4 MN17 POINT (-73.987651832547 40.756316895053) \n", + ".. ... ... \n", + "95 MN17 POINT (-73.990023200823 40.756890780426) \n", + "96 MN17 POINT (-73.986602050292 40.753404587174) \n", + "97 MN17 POINT (-73.989218092096 40.757991356019) \n", + "98 MN17 POINT (-73.988551029682 40.753843959794) \n", + "99 MN17 POINT (-73.98715066791 40.753432097521) \n", + "\n", + "[100 rows x 27 columns]" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "wr.opensearch.search(\n", + " client,\n", + " index=\"nyc_restaurants_inspections\",\n", + " filter_path=[\"hits.hits._source\"],\n", + " size=100,\n", + " search_body={\n", + " \"query\": {\n", + " \"match_all\": {}\n", + " },\n", + " \"sort\": [\n", + " {\n", + " \"_geo_distance\": {\n", + " \"business_location\": { # Times-Square - https://geojson.io/#map=16/40.7563/-73.9862\n", + " \"lat\": 40.75613228383523,\n", + " \"lon\": -73.9865791797638\n", + " },\n", + " \"order\": \"asc\"\n", + " }\n", + " }\n", + " ]\n", + " }\n", + ")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +} diff --git a/tutorials/031 - Lake Formation Governed Tables.ipynb b/tutorials/032 - Lake Formation Governed Tables.ipynb similarity index 91% rename from tutorials/031 - Lake Formation Governed Tables.ipynb rename to tutorials/032 - Lake Formation Governed Tables.ipynb index a3d3f28c6..0a7b47241 100644 --- a/tutorials/031 - Lake Formation Governed Tables.ipynb +++ b/tutorials/032 - Lake Formation Governed Tables.ipynb @@ -1,54 +1,29 @@ { - "metadata": { - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.1" - }, - "orig_nbformat": 2, - "kernelspec": { - "name": "python3", - "display_name": "Python 3.9.1 64-bit ('.venv': venv)", - "metadata": { - "interpreter": { - "hash": "2878c7ae46413c5ab07cafef85a7415922732432fa2f847b9105997e244ed975" - } - } - } - }, - "nbformat": 4, - "nbformat_minor": 2, "cells": [ { "cell_type": "markdown", + "metadata": {}, "source": [ "[![AWS Data Wrangler](_static/logo.png \"AWS Data Wrangler\")](https://github.com/awslabs/aws-data-wrangler)" - ], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ - "# 31 - AWS Lake Formation - Glue Governed tables" - ], - "metadata": {} + "# 32 - AWS Lake Formation - Glue Governed tables" + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### This tutorial assumes that your IAM user/role has the required Lake Formation permissions to create and read AWS Glue Governed tables" - ], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## Table of Contents\n", "* [1. Read Governed table](#1.-Read-Governed-table)\n", @@ -66,26 +41,27 @@ " * [2.2.3 Create partitioned Governed table](#2.2.3-Create-partitioned-Governed-table)\n", " * [2.2.4 Overwrite partitions](#2.2.4-Overwrite-partitions)\n", "* [3. Multiple read/write operations within a transaction](#2.-Multiple-read/write-operations-within-a-transaction)" - ], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "# 1. Read Governed table" - ], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## 1.1 Read PartiQL query" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "import awswrangler as wr\n", "\n", @@ -99,20 +75,20 @@ " database=database,\n", " catalog_id=catalog_id\n", ")" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### 1.1.1 Read within transaction" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "transaction_id = wr.lakeformation.start_transaction(read_only=True)\n", "df = wr.lakeformation.read_sql_query(\n", @@ -120,20 +96,20 @@ " database=database,\n", " transaction_id=transaction_id\n", ")" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### 1.1.2 Read within query as of time" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "import calendar\n", "import time\n", @@ -145,78 +121,78 @@ " query_as_of_time=query_as_of_time,\n", " params={\"id\": 1, \"name\": \"Ayoub\"}\n", ")" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## 1.2 Read full table" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "df = wr.lakeformation.read_sql_table(\n", " table=table,\n", " database=database\n", ")" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "# 2. Write Governed table" - ], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## 2.1 Create a new Governed table" - ], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## Enter your bucket name:" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "import getpass\n", "\n", "bucket = getpass.getpass()" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### If a governed table does not exist, it can be created by passing an S3 `path` argument. Make sure your IAM user/role has enough permissions in the Lake Formation database" - ], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### 2.1.1 CSV table" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "import pandas as pd\n", "\n", @@ -237,20 +213,20 @@ " table=table,\n", " table_type=\"GOVERNED\"\n", ")" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### 2.1.2 Parquet table" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "table = \"gov_table_parquet\"\n", "\n", @@ -266,27 +242,27 @@ " parameters={\"num_cols\": str(len(df.columns)), \"num_rows\": str(len(df.index))},\n", " columns_comments={\"c0\": \"0\"}\n", ")" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "## 2.2 Overwrite operations" - ], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### 2.2.1 Overwrite" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "df = pd.DataFrame({\"c1\": [None, 1, None]}, dtype=\"Int16\")\n", "wr.s3.to_parquet(\n", @@ -299,20 +275,20 @@ " parameters={\"num_cols\": str(len(df.columns)), \"num_rows\": str(len(df.index))},\n", " columns_comments={\"c1\": \"1\"}\n", ")" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### 2.2.2 Append" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "df = pd.DataFrame({\"c1\": [None, 2, None]}, dtype=\"Int8\")\n", "wr.s3.to_parquet(\n", @@ -325,20 +301,20 @@ " parameters={\"num_cols\": str(len(df.columns)), \"num_rows\": str(len(df.index) * 2)},\n", " columns_comments={\"c1\": \"1\"}\n", ")" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### 2.2.3 Create partitioned Governed table" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "table = \"gov_table_parquet_partitioned\"\n", "\n", @@ -355,20 +331,20 @@ " parameters={\"num_cols\": \"2\", \"num_rows\": \"2\"},\n", " columns_comments={\"c0\": \"zero\", \"c1\": \"one\"}\n", ")" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "### 2.2.4 Overwrite partitions" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "df = pd.DataFrame({\"c0\": [None, None], \"c1\": [0, 2]})\n", "wr.s3.to_parquet(\n", @@ -382,20 +358,20 @@ " parameters={\"num_cols\": \"2\", \"num_rows\": \"3\"},\n", " columns_comments={\"c0\": \"zero\", \"c1\": \"one\"}\n", ")" - ], - "outputs": [], - "metadata": {} + ] }, { "cell_type": "markdown", + "metadata": {}, "source": [ "# 3. Multiple read/write operations within a transaction" - ], - "metadata": {} + ] }, { "cell_type": "code", "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "read_table = \"gov_table_parquet\"\n", "write_table = \"gov_table_multi_parquet\"\n", @@ -433,9 +409,33 @@ ")\n", "\n", "wr.lakeformation.commit_transaction(transaction_id=transaction_id)" - ], - "outputs": [], - "metadata": {} + ] } - ] -} \ No newline at end of file + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3.9.1 64-bit ('.venv': venv)", + "metadata": { + "interpreter": { + "hash": "2878c7ae46413c5ab07cafef85a7415922732432fa2f847b9105997e244ed975" + } + }, + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.1" + }, + "orig_nbformat": 2 + }, + "nbformat": 4, + "nbformat_minor": 2 +} From dd6e847ed4efd30e4c8bc11b8a866405170cc9cd Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Tue, 19 Oct 2021 17:38:17 +0100 Subject: [PATCH 22/36] Lint --- awswrangler/lakeformation/_read.py | 2 +- awswrangler/lakeformation/_utils.py | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/awswrangler/lakeformation/_read.py b/awswrangler/lakeformation/_read.py index 2468dbd4f..63faad69c 100644 --- a/awswrangler/lakeformation/_read.py +++ b/awswrangler/lakeformation/_read.py @@ -59,7 +59,7 @@ def _resolve_sql_query( next_token = response.get("NextToken", None) scan_kwargs["NextToken"] = next_token - tables: List[Table] = list() + tables: List[Table] = [] if use_threads is False: tables = list( _get_work_unit_results( diff --git a/awswrangler/lakeformation/_utils.py b/awswrangler/lakeformation/_utils.py index e175ffa7a..0960b7788 100644 --- a/awswrangler/lakeformation/_utils.py +++ b/awswrangler/lakeformation/_utils.py @@ -41,7 +41,7 @@ def _build_partition_predicate( def _build_table_objects( paths: List[str], partitions_values: Dict[str, List[str]], - use_threads: bool, + use_threads: Union[bool, int], boto3_session: Optional[boto3.Session], ) -> List[Dict[str, Any]]: table_objects: List[Dict[str, Any]] = [] From 865332e1db5fff955a1b752346711c334883d011 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Tue, 2 Nov 2021 17:13:42 +0000 Subject: [PATCH 23/36] Fixing get_table_obj retries --- README.md | 3 + awswrangler/catalog/__init__.py | 7 +- awswrangler/catalog/_add.py | 83 ++ awswrangler/catalog/_create.py | 235 ++++- awswrangler/catalog/_definitions.py | 76 ++ awswrangler/lakeformation/_utils.py | 11 +- awswrangler/mysql.py | 13 +- awswrangler/s3/_write_parquet.py | 2 +- awswrangler/s3/_write_text.py | 342 ++++++- building/lambda/build-lambda-layer.sh | 2 +- .../_static/aws_lambda_managed_layer.png | Bin 0 -> 51690 bytes docs/source/install.rst | 72 +- poetry.lock | 897 +++++++++++------- pyproject.toml | 8 +- tests/test_catalog.py | 23 + tests/test_mysql.py | 19 + tests/test_s3_text.py | 11 +- tutorials/014 - Schema Evolution.ipynb | 102 +- 18 files changed, 1479 insertions(+), 427 deletions(-) create mode 100644 docs/source/_static/aws_lambda_managed_layer.png diff --git a/README.md b/README.md index df9652c26..d3799ff16 100644 --- a/README.md +++ b/README.md @@ -136,7 +136,10 @@ FROM "sampleDB"."sampleTable" ORDER BY time DESC LIMIT 3 - [026 - Amazon Timestream](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/026%20-%20Amazon%20Timestream.ipynb) - [027 - Amazon Timestream 2](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/027%20-%20Amazon%20Timestream%202.ipynb) - [028 - Amazon DynamoDB](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/028%20-%20DynamoDB.ipynb) + - [029 - S3 Select](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/029%20-%20S3%20Select.ipynb) + - [030 - Data Api](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/030%20-%20Data%20Api.ipynb) - [031 - OpenSearch](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/031%20-%20OpenSearch.ipynb) + - [032 - Lake Formation Governed Tables](https://github.com/awslabs/aws-data-wrangler/blob/main/tutorials/032%20-%Lake%20Formation%20Governed%20Tables.ipynb) - [**API Reference**](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html) - [Amazon S3](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#amazon-s3) - [AWS Glue Catalog](https://aws-data-wrangler.readthedocs.io/en/2.12.1/api.html#aws-glue-catalog) diff --git a/awswrangler/catalog/__init__.py b/awswrangler/catalog/__init__.py index fdecf17a3..48ec6193d 100644 --- a/awswrangler/catalog/__init__.py +++ b/awswrangler/catalog/__init__.py @@ -1,11 +1,13 @@ """Amazon Glue Catalog Module.""" -from awswrangler.catalog._add import add_column, add_csv_partitions, add_parquet_partitions # noqa +from awswrangler.catalog._add import add_column, add_csv_partitions, add_json_partitions, add_parquet_partitions # noqa from awswrangler.catalog._create import ( # noqa _create_csv_table, + _create_json_table, _create_parquet_table, create_csv_table, create_database, + create_json_table, create_parquet_table, overwrite_table_parameters, upsert_table_parameters, @@ -49,6 +51,7 @@ __all__ = [ "add_column", "add_csv_partitions", + "add_json_partitions", "add_parquet_partitions", "does_table_exist", "delete_column", @@ -59,9 +62,11 @@ "sanitize_table_name", "_create_csv_table", "_create_parquet_table", + "_create_json_table", "create_csv_table", "create_database", "create_parquet_table", + "create_json_table", "overwrite_table_parameters", "upsert_table_parameters", "_get_table_input", diff --git a/awswrangler/catalog/_add.py b/awswrangler/catalog/_add.py index df300ab14..1df61e5d0 100644 --- a/awswrangler/catalog/_add.py +++ b/awswrangler/catalog/_add.py @@ -10,6 +10,7 @@ from awswrangler.catalog._definitions import ( _check_column_type, _csv_partition_definition, + _json_partition_definition, _parquet_partition_definition, _update_table_definition, ) @@ -125,6 +126,88 @@ def add_csv_partitions( _add_partitions(database=database, table=table, boto3_session=boto3_session, inputs=inputs, catalog_id=catalog_id) +@apply_configs +def add_json_partitions( + database: str, + table: str, + partitions_values: Dict[str, List[str]], + bucketing_info: Optional[Tuple[List[str], int]] = None, + catalog_id: Optional[str] = None, + compression: Optional[str] = None, + serde_library: Optional[str] = None, + serde_parameters: Optional[Dict[str, str]] = None, + boto3_session: Optional[boto3.Session] = None, + columns_types: Optional[Dict[str, str]] = None, +) -> None: + r"""Add partitions (metadata) to a JSON Table in the AWS Glue Catalog. + + Parameters + ---------- + database : str + Database name. + table : str + Table name. + partitions_values: Dict[str, List[str]] + Dictionary with keys as S3 path locations and values as a list of partitions values as str + (e.g. {'s3://bucket/prefix/y=2020/m=10/': ['2020', '10']}). + bucketing_info: Tuple[List[str], int], optional + Tuple consisting of the column names used for bucketing as the first element and the number of buckets as the + second element. + Only `str`, `int` and `bool` are supported as column data types for bucketing. + catalog_id : str, optional + The ID of the Data Catalog from which to retrieve Databases. + If none is provided, the AWS account ID is used by default. + compression: str, optional + Compression style (``None``, ``gzip``, etc). + serde_library : Optional[str] + Specifies the SerDe Serialization library which will be used. You need to provide the Class library name + as a string. + If no library is provided the default is `org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe`. + serde_parameters : Optional[str] + Dictionary of initialization parameters for the SerDe. + The default is `{"field.delim": sep, "escape.delim": "\\"}`. + boto3_session : boto3.Session(), optional + Boto3 Session. The default boto3 session will be used if boto3_session receive None. + columns_types: Optional[Dict[str, str]] + Only required for Hive compability. + Dictionary with keys as column names and values as data types (e.g. {'col0': 'bigint', 'col1': 'double'}). + P.S. Only materialized columns please, not partition columns. + + Returns + ------- + None + None. + + Examples + -------- + >>> import awswrangler as wr + >>> wr.catalog.add_json_partitions( + ... database='default', + ... table='my_table', + ... partitions_values={ + ... 's3://bucket/prefix/y=2020/m=10/': ['2020', '10'], + ... 's3://bucket/prefix/y=2020/m=11/': ['2020', '11'], + ... 's3://bucket/prefix/y=2020/m=12/': ['2020', '12'] + ... } + ... ) + + """ + table = sanitize_table_name(table=table) + inputs: List[Dict[str, Any]] = [ + _json_partition_definition( + location=k, + values=v, + bucketing_info=bucketing_info, + compression=compression, + columns_types=columns_types, + serde_library=serde_library, + serde_parameters=serde_parameters, + ) + for k, v in partitions_values.items() + ] + _add_partitions(database=database, table=table, boto3_session=boto3_session, inputs=inputs, catalog_id=catalog_id) + + @apply_configs def add_parquet_partitions( database: str, diff --git a/awswrangler/catalog/_create.py b/awswrangler/catalog/_create.py index 5211171c3..e7aa92974 100644 --- a/awswrangler/catalog/_create.py +++ b/awswrangler/catalog/_create.py @@ -7,7 +7,7 @@ from awswrangler import _utils, exceptions from awswrangler._config import apply_configs -from awswrangler.catalog._definitions import _csv_table_definition, _parquet_table_definition +from awswrangler.catalog._definitions import _csv_table_definition, _json_table_definition, _parquet_table_definition from awswrangler.catalog._delete import delete_all_partitions, delete_table_if_exists from awswrangler.catalog._get import _get_table_input from awswrangler.catalog._utils import _catalog_id, _transaction_id, sanitize_column_name, sanitize_table_name @@ -389,6 +389,80 @@ def _create_csv_table( # pylint: disable=too-many-arguments,too-many-locals ) +def _create_json_table( # pylint: disable=too-many-arguments + database: str, + table: str, + path: str, + columns_types: Dict[str, str], + table_type: Optional[str], + partitions_types: Optional[Dict[str, str]], + bucketing_info: Optional[Tuple[List[str], int]], + description: Optional[str], + compression: Optional[str], + parameters: Optional[Dict[str, str]], + columns_comments: Optional[Dict[str, str]], + mode: str, + catalog_versioning: bool, + schema_evolution: bool, + transaction_id: Optional[str], + serde_library: Optional[str], + serde_parameters: Optional[Dict[str, str]], + boto3_session: Optional[boto3.Session], + projection_enabled: bool, + projection_types: Optional[Dict[str, str]], + projection_ranges: Optional[Dict[str, str]], + projection_values: Optional[Dict[str, str]], + projection_intervals: Optional[Dict[str, str]], + projection_digits: Optional[Dict[str, str]], + catalog_table_input: Optional[Dict[str, Any]], + catalog_id: Optional[str], +) -> None: + table = sanitize_table_name(table=table) + partitions_types = {} if partitions_types is None else partitions_types + _logger.debug("catalog_table_input: %s", catalog_table_input) + table_input: Dict[str, Any] + if schema_evolution is False: + _utils.check_schema_changes(columns_types=columns_types, table_input=catalog_table_input, mode=mode) + if (catalog_table_input is not None) and (mode in ("append", "overwrite_partitions")): + table_input = catalog_table_input + else: + table_input = _json_table_definition( + table=table, + path=path, + columns_types=columns_types, + table_type=table_type, + partitions_types=partitions_types, + bucketing_info=bucketing_info, + compression=compression, + serde_library=serde_library, + serde_parameters=serde_parameters, + ) + table_exist: bool = catalog_table_input is not None + _logger.debug("table_exist: %s", table_exist) + _create_table( + database=database, + table=table, + description=description, + parameters=parameters, + columns_comments=columns_comments, + mode=mode, + catalog_versioning=catalog_versioning, + transaction_id=transaction_id, + boto3_session=boto3_session, + table_input=table_input, + table_type=table_type, + table_exist=table_exist, + partitions_types=partitions_types, + projection_enabled=projection_enabled, + projection_types=projection_types, + projection_ranges=projection_ranges, + projection_values=projection_values, + projection_intervals=projection_intervals, + projection_digits=projection_digits, + catalog_id=catalog_id, + ) + + @apply_configs def upsert_table_parameters( parameters: Dict[str, str], @@ -871,3 +945,162 @@ def create_csv_table( # pylint: disable=too-many-arguments serde_library=serde_library, serde_parameters=serde_parameters, ) + + +@apply_configs +def create_json_table( + database: str, + table: str, + path: str, + columns_types: Dict[str, str], + table_type: Optional[str] = None, + partitions_types: Optional[Dict[str, str]] = None, + bucketing_info: Optional[Tuple[List[str], int]] = None, + compression: Optional[str] = None, + description: Optional[str] = None, + parameters: Optional[Dict[str, str]] = None, + columns_comments: Optional[Dict[str, str]] = None, + mode: str = "overwrite", + catalog_versioning: bool = False, + schema_evolution: bool = False, + serde_library: Optional[str] = None, + serde_parameters: Optional[Dict[str, str]] = None, + transaction_id: Optional[str] = None, + boto3_session: Optional[boto3.Session] = None, + projection_enabled: bool = False, + projection_types: Optional[Dict[str, str]] = None, + projection_ranges: Optional[Dict[str, str]] = None, + projection_values: Optional[Dict[str, str]] = None, + projection_intervals: Optional[Dict[str, str]] = None, + projection_digits: Optional[Dict[str, str]] = None, + catalog_id: Optional[str] = None, +) -> None: + r"""Create a JSON Table (Metadata Only) in the AWS Glue Catalog. + + 'https://docs.aws.amazon.com/athena/latest/ug/data-types.html' + + Parameters + ---------- + database : str + Database name. + table : str + Table name. + path : str + Amazon S3 path (e.g. s3://bucket/prefix/). + columns_types: Dict[str, str] + Dictionary with keys as column names and values as data types (e.g. {'col0': 'bigint', 'col1': 'double'}). + table_type: str, optional + The type of the Glue Table (EXTERNAL_TABLE, GOVERNED...). Set to EXTERNAL_TABLE if None + partitions_types: Dict[str, str], optional + Dictionary with keys as partition names and values as data types (e.g. {'col2': 'date'}). + bucketing_info: Tuple[List[str], int], optional + Tuple consisting of the column names used for bucketing as the first element and the number of buckets as the + second element. + Only `str`, `int` and `bool` are supported as column data types for bucketing. + compression : str, optional + Compression style (``None``, ``gzip``, etc). + description : str, optional + Table description + parameters : Dict[str, str], optional + Key/value pairs to tag the table. + columns_comments: Dict[str, str], optional + Columns names and the related comments (e.g. {'col0': 'Column 0.', 'col1': 'Column 1.', 'col2': 'Partition.'}). + mode : str + 'overwrite' to recreate any possible axisting table or 'append' to keep any possible axisting table. + catalog_versioning : bool + If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. + schema_evolution : bool + If True allows schema evolution (new or missing columns), otherwise a exception will be raised. + (Only considered if dataset=True and mode in ("append", "overwrite_partitions")) + Related tutorial: + https://aws-data-wrangler.readthedocs.io/en/2.11.0/tutorials/014%20-%20Schema%20Evolution.html + serde_library : Optional[str] + Specifies the SerDe Serialization library which will be used. You need to provide the Class library name + as a string. + If no library is provided the default is `org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe`. + serde_parameters : Optional[str] + Dictionary of initialization parameters for the SerDe. + The default is `{"field.delim": sep, "escape.delim": "\\"}`. + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). + projection_enabled : bool + Enable Partition Projection on Athena (https://docs.aws.amazon.com/athena/latest/ug/partition-projection.html) + projection_types : Optional[Dict[str, str]] + Dictionary of partitions names and Athena projections types. + Valid types: "enum", "integer", "date", "injected" + https://docs.aws.amazon.com/athena/latest/ug/partition-projection-supported-types.html + (e.g. {'col_name': 'enum', 'col2_name': 'integer'}) + projection_ranges: Optional[Dict[str, str]] + Dictionary of partitions names and Athena projections ranges. + https://docs.aws.amazon.com/athena/latest/ug/partition-projection-supported-types.html + (e.g. {'col_name': '0,10', 'col2_name': '-1,8675309'}) + projection_values: Optional[Dict[str, str]] + Dictionary of partitions names and Athena projections values. + https://docs.aws.amazon.com/athena/latest/ug/partition-projection-supported-types.html + (e.g. {'col_name': 'A,B,Unknown', 'col2_name': 'foo,boo,bar'}) + projection_intervals: Optional[Dict[str, str]] + Dictionary of partitions names and Athena projections intervals. + https://docs.aws.amazon.com/athena/latest/ug/partition-projection-supported-types.html + (e.g. {'col_name': '1', 'col2_name': '5'}) + projection_digits: Optional[Dict[str, str]] + Dictionary of partitions names and Athena projections digits. + https://docs.aws.amazon.com/athena/latest/ug/partition-projection-supported-types.html + (e.g. {'col_name': '1', 'col2_name': '2'}) + boto3_session : boto3.Session(), optional + Boto3 Session. The default boto3 session will be used if boto3_session receive None. + catalog_id : str, optional + The ID of the Data Catalog from which to retrieve Databases. + If none is provided, the AWS account ID is used by default. + + Returns + ------- + None + None. + + Examples + -------- + >>> import awswrangler as wr + >>> wr.catalog.create_json_table( + ... database='default', + ... table='my_table', + ... path='s3://bucket/prefix/', + ... columns_types={'col0': 'bigint', 'col1': 'double'}, + ... partitions_types={'col2': 'date'}, + ... description='My very own JSON table!', + ... parameters={'source': 'postgresql'}, + ... columns_comments={'col0': 'Column 0.', 'col1': 'Column 1.', 'col2': 'Partition.'} + ... ) + + """ + session: boto3.Session = _utils.ensure_session(session=boto3_session) + catalog_table_input: Optional[Dict[str, Any]] = _get_table_input( + database=database, table=table, boto3_session=session, catalog_id=catalog_id + ) + _create_json_table( + database=database, + table=table, + path=path, + columns_types=columns_types, + table_type=table_type, + partitions_types=partitions_types, + bucketing_info=bucketing_info, + catalog_id=catalog_id, + compression=compression, + description=description, + parameters=parameters, + columns_comments=columns_comments, + mode=mode, + catalog_versioning=catalog_versioning, + transaction_id=transaction_id, + schema_evolution=schema_evolution, + projection_enabled=projection_enabled, + projection_types=projection_types, + projection_ranges=projection_ranges, + projection_values=projection_values, + projection_intervals=projection_intervals, + projection_digits=projection_digits, + boto3_session=boto3_session, + catalog_table_input=catalog_table_input, + serde_library=serde_library, + serde_parameters=serde_parameters, + ) diff --git a/awswrangler/catalog/_definitions.py b/awswrangler/catalog/_definitions.py index 20136c922..daa326dd1 100644 --- a/awswrangler/catalog/_definitions.py +++ b/awswrangler/catalog/_definitions.py @@ -185,6 +185,82 @@ def _csv_partition_definition( return definition +def _json_table_definition( + table: str, + path: str, + columns_types: Dict[str, str], + table_type: Optional[str], + partitions_types: Dict[str, str], + bucketing_info: Optional[Tuple[List[str], int]], + compression: Optional[str], + serde_library: Optional[str], + serde_parameters: Optional[Dict[str, str]], +) -> Dict[str, Any]: + compressed: bool = compression is not None + parameters: Dict[str, str] = { + "classification": "json", + "compressionType": str(compression).lower(), + "typeOfData": "file", + } + serde_info = { + "SerializationLibrary": "org.openx.data.jsonserde.JsonSerDe" if serde_library is None else serde_library, + "Parameters": {} if serde_parameters is None else serde_parameters, + } + return { + "Name": table, + "PartitionKeys": [{"Name": cname, "Type": dtype} for cname, dtype in partitions_types.items()], + "TableType": "EXTERNAL_TABLE" if table_type is None else table_type, + "Parameters": parameters, + "StorageDescriptor": { + "Columns": [{"Name": cname, "Type": dtype} for cname, dtype in columns_types.items()], + "Location": path, + "InputFormat": "org.apache.hadoop.mapred.TextInputFormat", + "OutputFormat": "org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat", + "Compressed": compressed, + "NumberOfBuckets": -1 if bucketing_info is None else bucketing_info[1], + "SerdeInfo": serde_info, + "BucketColumns": [] if bucketing_info is None else bucketing_info[0], + "StoredAsSubDirectories": False, + "SortColumns": [], + "Parameters": parameters, + }, + } + + +def _json_partition_definition( + location: str, + values: List[str], + bucketing_info: Optional[Tuple[List[str], int]], + compression: Optional[str], + serde_library: Optional[str], + serde_parameters: Optional[Dict[str, str]], + columns_types: Optional[Dict[str, str]], +) -> Dict[str, Any]: + compressed: bool = compression is not None + serde_info = { + "SerializationLibrary": "org.openx.data.jsonserde.JsonSerDe" if serde_library is None else serde_library, + "Parameters": {} if serde_parameters is None else serde_parameters, + } + definition: Dict[str, Any] = { + "StorageDescriptor": { + "InputFormat": "org.apache.hadoop.mapred.TextInputFormat", + "OutputFormat": "org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat", + "Location": location, + "Compressed": compressed, + "SerdeInfo": serde_info, + "StoredAsSubDirectories": False, + "NumberOfBuckets": -1 if bucketing_info is None else bucketing_info[1], + "BucketColumns": [] if bucketing_info is None else bucketing_info[0], + }, + "Values": values, + } + if columns_types is not None: + definition["StorageDescriptor"]["Columns"] = [ + {"Name": cname, "Type": dtype} for cname, dtype in columns_types.items() + ] + return definition + + def _check_column_type(column_type: str) -> bool: if column_type not in _LEGAL_COLUMN_TYPES: raise ValueError(f"{column_type} is not a legal data type.") diff --git a/awswrangler/lakeformation/_utils.py b/awswrangler/lakeformation/_utils.py index 0960b7788..8bb80e1d6 100644 --- a/awswrangler/lakeformation/_utils.py +++ b/awswrangler/lakeformation/_utils.py @@ -86,7 +86,14 @@ def _get_table_objects( next_token: str = "init_token" # Dummy token table_objects: List[Dict[str, Any]] = [] while next_token: - response = client_lakeformation.get_table_objects(**scan_kwargs) + response = _utils.try_it( + f=client_lakeformation.get_table_objects, + ex=botocore.exceptions.ClientError, + ex_code="ResourceNotReadyException", + base=1.0, + max_num_tries=5, + **scan_kwargs, + ) for objects in response["Objects"]: for table_object in objects["Objects"]: if objects["PartitionValues"]: @@ -117,7 +124,7 @@ def _update_table_objects( write_operations: List[Dict[str, Dict[str, Any]]] = [] if add_objects: write_operations.extend({"AddObject": obj} for obj in add_objects) - elif del_objects: + if del_objects: write_operations.extend({"DeleteObject": _without_keys(obj, ["Size"])} for obj in del_objects) update_kwargs["WriteOperations"] = write_operations diff --git a/awswrangler/mysql.py b/awswrangler/mysql.py index 257251b1e..7baa7491a 100644 --- a/awswrangler/mysql.py +++ b/awswrangler/mysql.py @@ -2,7 +2,7 @@ import logging import uuid -from typing import Any, Dict, Iterator, List, Optional, Tuple, Union +from typing import Any, Dict, Iterator, List, Optional, Tuple, Type, Union import boto3 import pandas as pd @@ -77,6 +77,7 @@ def connect( read_timeout: Optional[int] = None, write_timeout: Optional[int] = None, connect_timeout: int = 10, + cursorclass: Type[Cursor] = Cursor, ) -> "pymysql.connections.Connection[Any]": """Return a pymysql connection from a Glue Catalog Connection or Secrets Manager. @@ -127,6 +128,9 @@ def connect( (default: 10, min: 1, max: 31536000) This parameter is forward to pymysql. https://pymysql.readthedocs.io/en/latest/modules/connections.html + cursorclass : Cursor + Cursor class to use, e.g. SSCrusor; defaults to :class:`pymysql.cursors.Cursor` + https://pymysql.readthedocs.io/en/latest/modules/cursors.html Returns ------- @@ -158,6 +162,7 @@ def connect( read_timeout=read_timeout, write_timeout=write_timeout, connect_timeout=connect_timeout, + cursorclass=cursorclass, ) @@ -290,6 +295,7 @@ def to_sql( varchar_lengths: Optional[Dict[str, int]] = None, use_column_names: bool = False, chunksize: int = 200, + cursorclass: Type[Cursor] = Cursor, ) -> None: """Write records stored in a DataFrame into MySQL. @@ -330,6 +336,9 @@ def to_sql( inserted into the database columns `col1` and `col3`. chunksize: int Number of rows which are inserted with each SQL query. Defaults to inserting 200 rows per query. + cursorclass : Cursor + Cursor class to use, e.g. SSCrusor; defaults to :class:`pymysql.cursors.Cursor` + https://pymysql.readthedocs.io/en/latest/modules/cursors.html Returns ------- @@ -365,7 +374,7 @@ def to_sql( _db_utils.validate_mode(mode=mode, allowed_modes=allowed_modes) _validate_connection(con=con) try: - with con.cursor() as cursor: + with con.cursor(cursor=cursorclass) as cursor: _create_table( df=df, cursor=cursor, diff --git a/awswrangler/s3/_write_parquet.py b/awswrangler/s3/_write_parquet.py index da55360bc..59534c7fb 100644 --- a/awswrangler/s3/_write_parquet.py +++ b/awswrangler/s3/_write_parquet.py @@ -308,7 +308,7 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b catalog_versioning : bool If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. schema_evolution : bool - If True allows schema evolution (new or missing columns), otherwise a exception will be raised. + If True allows schema evolution (new or missing columns), otherwise a exception will be raised. True by default. (Only considered if dataset=True and mode in ("append", "overwrite_partitions")) Related tutorial: https://aws-data-wrangler.readthedocs.io/en/2.12.1/tutorials/014%20-%20Schema%20Evolution.html diff --git a/awswrangler/s3/_write_text.py b/awswrangler/s3/_write_text.py index 8f842a7bd..c334fe8cc 100644 --- a/awswrangler/s3/_write_text.py +++ b/awswrangler/s3/_write_text.py @@ -186,7 +186,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. schema_evolution : bool If True allows schema evolution (new or missing columns), otherwise a exception will be raised. - (Only considered if dataset=True and mode in ("append", "overwrite_partitions")) + (Only considered if dataset=True and mode in ("append", "overwrite_partitions")). False by default. Related tutorial: https://aws-data-wrangler.readthedocs.io/en/2.12.1/tutorials/014%20-%20Schema%20Evolution.html database : str, optional @@ -497,19 +497,18 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state ) paths = [path] # type: ignore else: + compression: Optional[str] = pandas_kwargs.get("compression", None) if database and table: quoting: Optional[int] = csv.QUOTE_NONE escapechar: Optional[str] = "\\" header: Union[bool, List[str]] = pandas_kwargs.get("header", False) date_format: Optional[str] = "%Y-%m-%d %H:%M:%S.%f" pd_kwargs: Dict[str, Any] = {} - compression: Optional[str] = pandas_kwargs.get("compression", None) else: quoting = pandas_kwargs.get("quoting", None) escapechar = pandas_kwargs.get("escapechar", None) header = pandas_kwargs.get("header", True) date_format = pandas_kwargs.get("date_format", None) - compression = pandas_kwargs.get("compression", None) pd_kwargs = pandas_kwargs.copy() pd_kwargs.pop("quoting", None) pd_kwargs.pop("escapechar", None) @@ -664,14 +663,41 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state return {"paths": paths, "partitions_values": partitions_values} -def to_json( +def to_json( # pylint: disable=too-many-arguments,too-many-locals,too-many-statements,too-many-branches df: pd.DataFrame, - path: str, + path: Optional[str] = None, + index: bool = True, + columns: Optional[List[str]] = None, + use_threads: Union[bool, int] = True, boto3_session: Optional[boto3.Session] = None, s3_additional_kwargs: Optional[Dict[str, Any]] = None, - use_threads: Union[bool, int] = True, + sanitize_columns: bool = False, + dataset: bool = False, + filename_prefix: Optional[str] = None, + partition_cols: Optional[List[str]] = None, + bucketing_info: Optional[Tuple[List[str], int]] = None, + concurrent_partitioning: bool = False, + mode: Optional[str] = None, + catalog_versioning: bool = False, + schema_evolution: bool = True, + database: Optional[str] = None, + table: Optional[str] = None, + table_type: Optional[str] = None, + transaction_id: Optional[str] = None, + dtype: Optional[Dict[str, str]] = None, + description: Optional[str] = None, + parameters: Optional[Dict[str, str]] = None, + columns_comments: Optional[Dict[str, str]] = None, + regular_partitions: bool = True, + projection_enabled: bool = False, + projection_types: Optional[Dict[str, str]] = None, + projection_ranges: Optional[Dict[str, str]] = None, + projection_values: Optional[Dict[str, str]] = None, + projection_intervals: Optional[Dict[str, str]] = None, + projection_digits: Optional[Dict[str, str]] = None, + catalog_id: Optional[str] = None, **pandas_kwargs: Any, -) -> List[str]: +) -> Union[List[str], Dict[str, Union[List[str], Dict[str, List[str]]]]]: """Write JSON file on Amazon S3. Note @@ -689,15 +715,101 @@ def to_json( Pandas DataFrame https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.html path : str Amazon S3 path (e.g. s3://bucket/filename.json). + index : bool + Write row names (index). + columns : Optional[List[str]] + Columns to write. + use_threads : bool, int + True to enable concurrent requests, False to disable multiple threads. + If enabled os.cpu_count() will be used as the max number of threads. + If integer is provided, specified number is used. boto3_session : boto3.Session(), optional Boto3 Session. The default boto3 Session will be used if boto3_session receive None. s3_additional_kwargs : Optional[Dict[str, Any]] Forwarded to botocore requests. e.g. s3_additional_kwargs={'ServerSideEncryption': 'aws:kms', 'SSEKMSKeyId': 'YOUR_KMS_KEY_ARN'} - use_threads : bool, int - True to enable concurrent requests, False to disable multiple threads. - If enabled os.cpu_count() will be used as the max number of threads. - If integer is provided, specified number is used. + sanitize_columns : bool + True to sanitize columns names or False to keep it as is. + True value is forced if `dataset=True`. + dataset : bool + If True store as a dataset instead of ordinary file(s) + If True, enable all follow arguments: + partition_cols, mode, database, table, description, parameters, columns_comments, concurrent_partitioning, + catalog_versioning, projection_enabled, projection_types, projection_ranges, projection_values, + projection_intervals, projection_digits, catalog_id, schema_evolution. + filename_prefix: str, optional + If dataset=True, add a filename prefix to the output files. + partition_cols: List[str], optional + List of column names that will be used to create partitions. Only takes effect if dataset=True. + bucketing_info: Tuple[List[str], int], optional + Tuple consisting of the column names used for bucketing as the first element and the number of buckets as the + second element. + Only `str`, `int` and `bool` are supported as column data types for bucketing. + concurrent_partitioning: bool + If True will increase the parallelism level during the partitions writing. It will decrease the + writing time and increase the memory usage. + https://aws-data-wrangler.readthedocs.io/en/2.12.1/tutorials/022%20-%20Writing%20Partitions%20Concurrently.html + mode : str, optional + ``append`` (Default), ``overwrite``, ``overwrite_partitions``. Only takes effect if dataset=True. + For details check the related tutorial: + https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet + catalog_versioning : bool + If True and `mode="overwrite"`, creates an archived version of the table catalog before updating it. + schema_evolution : bool + If True allows schema evolution (new or missing columns), otherwise a exception will be raised. + (Only considered if dataset=True and mode in ("append", "overwrite_partitions")) + Related tutorial: + https://aws-data-wrangler.readthedocs.io/en/2.12.1/tutorials/014%20-%20Schema%20Evolution.html + database : str, optional + Glue/Athena catalog: Database name. + table : str, optional + Glue/Athena catalog: Table name. + table_type: str, optional + The type of the Glue Table. Set to EXTERNAL_TABLE if None + transaction_id: str, optional + The ID of the transaction when writing to a Governed Table. + dtype : Dict[str, str], optional + Dictionary of columns names and Athena/Glue types to be casted. + Useful when you have columns with undetermined or mixed data types. + (e.g. {'col name': 'bigint', 'col2 name': 'int'}) + description : str, optional + Glue/Athena catalog: Table description + parameters : Dict[str, str], optional + Glue/Athena catalog: Key/value pairs to tag the table. + columns_comments : Dict[str, str], optional + Glue/Athena catalog: + Columns names and the related comments (e.g. {'col0': 'Column 0.', 'col1': 'Column 1.', 'col2': 'Partition.'}). + regular_partitions : bool + Create regular partitions (Non projected partitions) on Glue Catalog. + Disable when you will work only with Partition Projection. + Keep enabled even when working with projections is useful to keep + Redshift Spectrum working with the regular partitions. + projection_enabled : bool + Enable Partition Projection on Athena (https://docs.aws.amazon.com/athena/latest/ug/partition-projection.html) + projection_types : Optional[Dict[str, str]] + Dictionary of partitions names and Athena projections types. + Valid types: "enum", "integer", "date", "injected" + https://docs.aws.amazon.com/athena/latest/ug/partition-projection-supported-types.html + (e.g. {'col_name': 'enum', 'col2_name': 'integer'}) + projection_ranges: Optional[Dict[str, str]] + Dictionary of partitions names and Athena projections ranges. + https://docs.aws.amazon.com/athena/latest/ug/partition-projection-supported-types.html + (e.g. {'col_name': '0,10', 'col2_name': '-1,8675309'}) + projection_values: Optional[Dict[str, str]] + Dictionary of partitions names and Athena projections values. + https://docs.aws.amazon.com/athena/latest/ug/partition-projection-supported-types.html + (e.g. {'col_name': 'A,B,Unknown', 'col2_name': 'foo,boo,bar'}) + projection_intervals: Optional[Dict[str, str]] + Dictionary of partitions names and Athena projections intervals. + https://docs.aws.amazon.com/athena/latest/ug/partition-projection-supported-types.html + (e.g. {'col_name': '1', 'col2_name': '5'}) + projection_digits: Optional[Dict[str, str]] + Dictionary of partitions names and Athena projections digits. + https://docs.aws.amazon.com/athena/latest/ug/partition-projection-supported-types.html + (e.g. {'col_name': '1', 'col2_name': '2'}) + catalog_id : str, optional + The ID of the Data Catalog from which to retrieve Databases. + If none is provided, the AWS account ID is used by default. pandas_kwargs: KEYWORD arguments forwarded to pandas.DataFrame.to_json(). You can NOT pass `pandas_kwargs` explicit, just add valid Pandas arguments in the function call and Wrangler will accept it. @@ -756,12 +868,212 @@ def to_json( f"JSON compression on S3 is not supported for Pandas version {pd.__version__}. " "The minimum acceptable version to achive it is Pandas 1.2.0 that requires Python >=3.7.1." ) - return _to_text( - file_format="json", + + _validate_args( df=df, + table=table, + database=database, + dataset=dataset, path=path, + partition_cols=partition_cols, + bucketing_info=bucketing_info, + mode=mode, + description=description, + parameters=parameters, + columns_comments=columns_comments, + ) + + # Initializing defaults + partition_cols = partition_cols if partition_cols else [] + dtype = dtype if dtype else {} + partitions_values: Dict[str, List[str]] = {} + mode = "append" if mode is None else mode + commit_trans: bool = False + if transaction_id: + table_type = "GOVERNED" + filename_prefix = filename_prefix + uuid.uuid4().hex if filename_prefix else uuid.uuid4().hex + session: boto3.Session = _utils.ensure_session(session=boto3_session) + + # Sanitize table to respect Athena's standards + if (sanitize_columns is True) or (database is not None and table is not None): + df, dtype, partition_cols = _sanitize(df=df, dtype=dtype, partition_cols=partition_cols) + + # Evaluating dtype + catalog_table_input: Optional[Dict[str, Any]] = None + if database and table: + catalog_table_input = catalog._get_table_input( # pylint: disable=protected-access + database=database, table=table, boto3_session=session, transaction_id=transaction_id, catalog_id=catalog_id + ) + catalog_path: Optional[str] = None + if catalog_table_input: + table_type = catalog_table_input["TableType"] + catalog_path = catalog_table_input.get("StorageDescriptor", {}).get("Location") + if path is None: + if catalog_path: + path = catalog_path + else: + raise exceptions.InvalidArgumentValue( + "Glue table does not exist in the catalog. Please pass the `path` argument to create it." + ) + elif path and catalog_path: + if path.rstrip("/") != catalog_path.rstrip("/"): + raise exceptions.InvalidArgumentValue( + f"The specified path: {path}, does not match the existing Glue catalog table path: {catalog_path}" + ) + if pandas_kwargs.get("compression") not in ("gzip", "bz2", None): + raise exceptions.InvalidArgumentCombination( + "If database and table are given, you must use one of these compressions: gzip, bz2 or None." + ) + if (table_type == "GOVERNED") and (not transaction_id): + _logger.debug("`transaction_id` not specified for GOVERNED table, starting transaction") + transaction_id = lakeformation.start_transaction(read_only=False, boto3_session=boto3_session) + commit_trans = True + + df = _apply_dtype(df=df, dtype=dtype, catalog_table_input=catalog_table_input, mode=mode) + + if dataset is False: + return _to_text( + file_format="json", + df=df, + path=path, + use_threads=use_threads, + boto3_session=session, + s3_additional_kwargs=s3_additional_kwargs, + **pandas_kwargs, + ) + + compression: Optional[str] = pandas_kwargs.get("compression", None) + df = df[columns] if columns else df + + columns_types: Dict[str, str] = {} + partitions_types: Dict[str, str] = {} + + if database and table: + columns_types, partitions_types = _data_types.athena_types_from_pandas_partitioned( + df=df, index=index, partition_cols=partition_cols, dtype=dtype + ) + if schema_evolution is False: + _utils.check_schema_changes(columns_types=columns_types, table_input=catalog_table_input, mode=mode) + + if (catalog_table_input is None) and (table_type == "GOVERNED"): + catalog._create_json_table( # pylint: disable=protected-access + database=database, + table=table, + path=path, # type: ignore + columns_types=columns_types, + table_type=table_type, + partitions_types=partitions_types, + bucketing_info=bucketing_info, + description=description, + parameters=parameters, + columns_comments=columns_comments, + boto3_session=session, + mode=mode, + transaction_id=transaction_id, + catalog_versioning=catalog_versioning, + schema_evolution=schema_evolution, + projection_enabled=projection_enabled, + projection_types=projection_types, + projection_ranges=projection_ranges, + projection_values=projection_values, + projection_intervals=projection_intervals, + projection_digits=projection_digits, + catalog_table_input=catalog_table_input, + catalog_id=catalog_id, + compression=pandas_kwargs.get("compression"), + serde_library=None, + serde_parameters=None, + ) + catalog_table_input = catalog._get_table_input( # pylint: disable=protected-access + database=database, + table=table, + boto3_session=session, + transaction_id=transaction_id, + catalog_id=catalog_id, + ) + + paths, partitions_values = _to_dataset( + func=_to_text, + concurrent_partitioning=concurrent_partitioning, + df=df, + path_root=path, # type: ignore + filename_prefix=filename_prefix, + index=index, + compression=compression, + catalog_id=catalog_id, + database=database, + table=table, + table_type=table_type, + transaction_id=transaction_id, use_threads=use_threads, - boto3_session=boto3_session, + partition_cols=partition_cols, + partitions_types=partitions_types, + bucketing_info=bucketing_info, + mode=mode, + boto3_session=session, s3_additional_kwargs=s3_additional_kwargs, - **pandas_kwargs, + file_format="json", ) + if database and table: + try: + serde_info: Dict[str, Any] = {} + if catalog_table_input: + serde_info = catalog_table_input["StorageDescriptor"]["SerdeInfo"] + serde_library: Optional[str] = serde_info.get("SerializationLibrary", None) + serde_parameters: Optional[Dict[str, str]] = serde_info.get("Parameters", None) + catalog._create_json_table( # pylint: disable=protected-access + database=database, + table=table, + path=path, # type: ignore + columns_types=columns_types, + table_type=table_type, + partitions_types=partitions_types, + bucketing_info=bucketing_info, + description=description, + parameters=parameters, + columns_comments=columns_comments, + boto3_session=session, + mode=mode, + transaction_id=transaction_id, + catalog_versioning=catalog_versioning, + schema_evolution=schema_evolution, + projection_enabled=projection_enabled, + projection_types=projection_types, + projection_ranges=projection_ranges, + projection_values=projection_values, + projection_intervals=projection_intervals, + projection_digits=projection_digits, + catalog_table_input=catalog_table_input, + catalog_id=catalog_id, + compression=pandas_kwargs.get("compression"), + serde_library=serde_library, + serde_parameters=serde_parameters, + ) + if partitions_values and (regular_partitions is True) and (table_type != "GOVERNED"): + _logger.debug("partitions_values:\n%s", partitions_values) + catalog.add_json_partitions( + database=database, + table=table, + partitions_values=partitions_values, + bucketing_info=bucketing_info, + boto3_session=session, + serde_library=serde_library, + serde_parameters=serde_parameters, + catalog_id=catalog_id, + columns_types=columns_types, + compression=pandas_kwargs.get("compression"), + ) + if commit_trans: + lakeformation.commit_transaction( + transaction_id=transaction_id, boto3_session=boto3_session # type: ignore + ) + except Exception: + _logger.debug("Catalog write failed, cleaning up S3 (paths: %s).", paths) + delete_objects( + path=paths, + use_threads=use_threads, + boto3_session=session, + s3_additional_kwargs=s3_additional_kwargs, + ) + raise + return {"paths": paths, "partitions_values": partitions_values} diff --git a/building/lambda/build-lambda-layer.sh b/building/lambda/build-lambda-layer.sh index 8def86925..f888e3b55 100644 --- a/building/lambda/build-lambda-layer.sh +++ b/building/lambda/build-lambda-layer.sh @@ -14,7 +14,7 @@ export ARROW_HOME=$(pwd)/dist export LD_LIBRARY_PATH=$(pwd)/dist/lib:$LD_LIBRARY_PATH git clone \ - --branch apache-arrow-5.0.0 \ + --branch 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list-table:: Lambda layer to Python library versions mapping + :widths: 25 25 + :header-rows: 1 + + * - Lambda Layer Version + - Python Library Version + * - 1 + - 2.12.0 + +Custom Layer +^^^^^^^^^^^^^^ + +For AWS regions not in the above list, you can create your own Lambda layer following these instructions: + 1 - Go to `GitHub's release section `_ -and download the layer zip related to the desired version. +and download the layer zip related to the desired version. Alternatively, you can download the zip from the `public artifacts bucket `_. 2 - Go to the AWS Lambda Panel, open the layer section (left side) and click **create layer**. @@ -36,11 +75,13 @@ and press **create** to create the layer. 4 - Go to your Lambda and select your new layer! + + AWS Glue Python Shell Jobs -------------------------- 1 - Go to `GitHub's release page `_ and download the wheel file -(.whl) related to the desired version. +(.whl) related to the desired version. Alternatively, you can download the wheel from the `public artifacts bucket `_. 2 - Upload the wheel file to any Amazon S3 location. @@ -81,23 +122,24 @@ Lambda zipped layers and Python wheels are stored in a publicly accessible S3 bu * Python wheel: ``awswrangler--py3-none-any.whl`` -Here is an example of how to reference the Lambda layer in your CDK app: +For example: ``s3://aws-data-wrangler-public-artifacts/releases/2.12.1/awswrangler-layer-2.12.1-py3.8.zip`` + +Serverless Application Repository (SAR) +-------------------------------------------- + +AWS Data Wrangler layers are also available in the `AWS Serverless Application Repository `_ (SAR). + +Here is an example of how to create the Lambda layer in your CDK app: .. code-block:: python - wrangler_layer = LayerVersion( - self, - "wrangler-layer", - compatible_runtimes=[Runtime.PYTHON_3_8], - code=S3Code( - bucket=Bucket.from_bucket_arn( - self, - "wrangler-bucket", - bucket_arn="arn:aws:s3:::aws-data-wrangler-public-artifacts", + CfnApplication( + self, + "wrangler-layer", + location=CfnApplication.ApplicationLocationProperty( + application_id="arn:aws:serverlessrepo:us-east-1:336392948345:applications/aws-data-wrangler-layer-py3-8", + semantic_version="2.12.0", ), - key="releases/2.12.1/awswrangler-layer-2.12.1-py3.8.zip", - ), - layer_version_name="aws-data-wrangler" ) Amazon SageMaker Notebook diff --git a/poetry.lock b/poetry.lock index b2e8d693a..4b7f44110 100644 --- a/poetry.lock +++ b/poetry.lock @@ -18,23 +18,26 @@ boto3 = ["boto3 (>=1.17.106,<1.17.107)"] [[package]] name = "aiohttp" -version = "3.7.4.post0" +version = "3.8.0" description = "Async http client/server framework (asyncio)" category = "dev" optional = false python-versions = ">=3.6" [package.dependencies] -async-timeout = ">=3.0,<4.0" +aiosignal = ">=1.1.2" +async-timeout = ">=4.0.0a3,<5.0" +asynctest = {version = "0.13.0", markers = "python_version < \"3.8\""} attrs = ">=17.3.0" -chardet = ">=2.0,<5.0" +charset-normalizer = ">=2.0,<3.0" +frozenlist = ">=1.1.1" idna-ssl = {version = ">=1.0", markers = "python_version < \"3.7\""} multidict = ">=4.5,<7.0" -typing-extensions = ">=3.6.5" +typing-extensions = {version = ">=3.7.4", markers = "python_version < \"3.8\""} yarl = ">=1.0,<2.0" [package.extras] -speedups = ["aiodns", "brotlipy", "cchardet"] +speedups = ["aiodns", "brotli", "cchardet"] [[package]] name = "aioitertools" @@ -47,6 +50,17 @@ python-versions = ">=3.6" [package.dependencies] typing_extensions = {version = ">=3.7", markers = "python_version < \"3.8\""} +[[package]] +name = "aiosignal" +version = "1.2.0" +description = "aiosignal: a list of registered asynchronous callbacks" +category = "dev" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +frozenlist = ">=1.1.0" + [[package]] name = "alabaster" version = "0.7.12" @@ -108,7 +122,7 @@ python-versions = "*" [[package]] name = "astroid" -version = "2.8.3" +version = "2.8.4" description = "An abstract syntax tree for Python with inference support." category = "dev" optional = false @@ -130,11 +144,22 @@ python-versions = ">=3.5" [[package]] name = "async-timeout" -version = "3.0.1" +version = "4.0.0" description = "Timeout context manager for asyncio programs" category = "dev" optional = false -python-versions = ">=3.5.3" +python-versions = ">=3.6" + +[package.dependencies] +typing-extensions = ">=3.6.5" + +[[package]] +name = "asynctest" +version = "0.13.0" +description = "Enhance the standard unittest package with features for testing asyncio libraries" +category = "dev" +optional = false +python-versions = ">=3.5" [[package]] name = "atomicwrites" @@ -209,7 +234,7 @@ lxml = ["lxml"] [[package]] name = "black" -version = "21.9b0" +version = "21.10b0" description = "The uncompromising code formatter." category = "dev" optional = false @@ -228,9 +253,9 @@ typing-extensions = ">=3.10.0.0" [package.extras] colorama = ["colorama (>=0.4.3)"] -d = ["aiohttp (>=3.6.0)", "aiohttp-cors (>=0.4.0)"] +d = ["aiohttp (>=3.7.4)"] jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"] -python2 = ["typed-ast (>=1.4.2)"] +python2 = ["typed-ast (>=1.4.3)"] uvloop = ["uvloop (>=0.15.2)"] [[package]] @@ -302,14 +327,6 @@ python-versions = "*" [package.dependencies] pycparser = "*" -[[package]] -name = "chardet" -version = "4.0.0" -description = "Universal encoding detector for Python 2 and 3" -category = "dev" -optional = false -python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" - [[package]] name = "charset-normalizer" version = "2.0.7" @@ -354,7 +371,7 @@ immutables = ">=0.9" [[package]] name = "coverage" -version = "6.0.2" +version = "6.1.1" description = "Code coverage measurement for Python" category = "dev" optional = false @@ -468,7 +485,7 @@ testing = ["pre-commit"] [[package]] name = "filelock" -version = "3.3.1" +version = "3.3.2" description = "A platform independent file lock." category = "dev" optional = false @@ -492,6 +509,14 @@ mccabe = ">=0.6.0,<0.7.0" pycodestyle = ">=2.8.0,<2.9.0" pyflakes = ">=2.4.0,<2.5.0" +[[package]] +name = "frozenlist" +version = "1.2.0" +description = "A list-like structure which implements collections.abc.MutableSequence" +category = "dev" +optional = false +python-versions = ">=3.6" + [[package]] name = "fsspec" version = "2021.10.1" @@ -581,7 +606,7 @@ testing = ["pytest (>=4.6)", "pytest-checkdocs (>=2.4)", "pytest-flake8", "pytes [[package]] name = "importlib-resources" -version = "5.2.3" +version = "5.4.0" description = "Read resources from Python packages" category = "dev" optional = false @@ -775,7 +800,7 @@ test = ["codecov", "coverage", "ipykernel", "ipython", "mock", "mypy", "pre-comm [[package]] name = "jupyter-core" -version = "4.8.1" +version = "4.9.1" description = "Jupyter core package. A base package on which Jupyter projects rely." category = "dev" optional = false @@ -787,7 +812,7 @@ traitlets = "*" [[package]] name = "jupyter-server" -version = "1.11.1" +version = "1.11.2" description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications." category = "dev" optional = false @@ -804,7 +829,6 @@ nbconvert = "*" nbformat = "*" prometheus-client = "*" pyzmq = ">=17" -requests-unixsocket = "*" Send2Trash = "*" terminado = ">=0.8.3" tornado = ">=6.1.0" @@ -816,7 +840,7 @@ test = ["coverage", "pytest (>=6.0)", "pytest-cov", "pytest-mock", "requests", " [[package]] name = "jupyterlab" -version = "3.2.0" +version = "3.2.1" description = "JupyterLab computational environment" category = "dev" optional = false @@ -924,7 +948,7 @@ python-versions = ">=3.5" [[package]] name = "moto" -version = "2.2.10" +version = "2.2.12" description = "A library that allows your python tests to easily mock out the boto library" category = "dev" optional = false @@ -946,19 +970,20 @@ werkzeug = "*" xmltodict = "*" [package.extras] -all = ["PyYAML (>=5.1)", "python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (<0.15)", "docker (>=2.5.1)", "jsondiff (>=1.1.2)", "aws-xray-sdk (>=0.93,!=0.96)", "idna (>=2.5,<3)", "cfn-lint (>=0.4.0)", "sshpubkeys (>=3.1.0)", "setuptools"] +all = ["PyYAML (>=5.1)", "python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (<0.15)", "docker (>=2.5.1)", "jsondiff (>=1.1.2)", "aws-xray-sdk (>=0.93,!=0.96)", "idna (>=2.5,<4)", "cfn-lint (>=0.4.0)", "sshpubkeys (>=3.1.0)", "setuptools"] apigateway = ["python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (<0.15)"] awslambda = ["docker (>=2.5.1)"] batch = ["docker (>=2.5.1)"] cloudformation = ["docker (>=2.5.1)", "PyYAML (>=5.1)", "cfn-lint (>=0.4.0)"] cognitoidp = ["python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (<0.15)"] +ds = ["sshpubkeys (>=3.1.0)"] dynamodb2 = ["docker (>=2.5.1)"] dynamodbstreams = ["docker (>=2.5.1)"] ec2 = ["sshpubkeys (>=3.1.0)"] efs = ["sshpubkeys (>=3.1.0)"] iotdata = ["jsondiff (>=1.1.2)"] s3 = ["PyYAML (>=5.1)"] -server = ["PyYAML (>=5.1)", "python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (<0.15)", "docker (>=2.5.1)", "jsondiff (>=1.1.2)", "aws-xray-sdk (>=0.93,!=0.96)", "idna (>=2.5,<3)", "cfn-lint (>=0.4.0)", "sshpubkeys (>=3.1.0)", "setuptools", "flask", "flask-cors"] +server = ["PyYAML (>=5.1)", "python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (<0.15)", "docker (>=2.5.1)", "jsondiff (>=1.1.2)", "aws-xray-sdk (>=0.93,!=0.96)", "idna (>=2.5,<4)", "cfn-lint (>=0.4.0)", "sshpubkeys (>=3.1.0)", "setuptools", "flask", "flask-cors"] ssm = ["PyYAML (>=5.1)", "dataclasses"] xray = ["aws-xray-sdk (>=0.93,!=0.96)", "setuptools"] @@ -998,8 +1023,8 @@ python-versions = "*" [[package]] name = "nbclassic" -version = "0.3.2" -description = "Jupyter Notebook as a Jupyter Server Extension." +version = "0.3.4" +description = "Jupyter Notebook as a Jupyter Server extension." category = "dev" optional = false python-versions = ">=3.6" @@ -1117,7 +1142,7 @@ python-versions = ">=3.5" [[package]] name = "notebook" -version = "6.4.4" +version = "6.4.5" description = "A web-based notebook environment for interactive computing" category = "dev" optional = false @@ -1182,14 +1207,14 @@ requests = ["requests (>=2.4.0,<3.0.0)"] [[package]] name = "packaging" -version = "21.0" +version = "21.2" description = "Core utilities for Python packages" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -pyparsing = ">=2.0.2" +pyparsing = ">=2.0.2,<3" [[package]] name = "pandas" @@ -1291,7 +1316,7 @@ ptyprocess = ">=0.5" [[package]] name = "pg8000" -version = "1.21.3" +version = "1.22.0" description = "PostgreSQL interface library" category = "main" optional = false @@ -1361,7 +1386,7 @@ tests = ["flake8 (>=3.7.7)", "pytest (>=4.6.9)", "pytest-cov (>=2.6.1)", "freeze [[package]] name = "prometheus-client" -version = "0.11.0" +version = "0.12.0" description = "Python client for the Prometheus monitoring system." category = "dev" optional = false @@ -1372,7 +1397,7 @@ twisted = ["twisted"] [[package]] name = "prompt-toolkit" -version = "3.0.20" +version = "3.0.21" description = "Library for building powerful interactive command lines in Python" category = "dev" optional = false @@ -1399,7 +1424,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" [[package]] name = "pyarrow" -version = "5.0.0" +version = "6.0.0" description = "Python library for Apache Arrow" category = "main" optional = false @@ -1655,7 +1680,7 @@ python-versions = "*" [[package]] name = "pywinpty" -version = "1.1.4" +version = "1.1.5" description = "Pseudo terminal support for Windows from Python." category = "dev" optional = false @@ -1675,7 +1700,7 @@ py = {version = "*", markers = "implementation_name == \"pypy\""} [[package]] name = "redshift-connector" -version = "2.0.888" +version = "2.0.889" description = "Redshift interface library" category = "main" optional = false @@ 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!=3.1.*, !=3.2.*" [[package]] name = "tomli" -version = "1.2.1" +version = "1.2.2" description = "A lil' TOML parser" category = "dev" optional = false @@ -2103,7 +2116,7 @@ socks = ["PySocks (>=1.5.6,!=1.5.7,<2.0)"] [[package]] name = "virtualenv" -version = "20.8.1" +version = "20.10.0" description = "Virtual Python Environment builder" category = "dev" optional = false @@ -2112,14 +2125,14 @@ python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7" [package.dependencies] "backports.entry-points-selectable" = ">=1.0.4" distlib = ">=0.3.1,<1" -filelock = ">=3.0.0,<4" +filelock = ">=3.2,<4" importlib-metadata = {version = ">=0.12", markers = "python_version < \"3.8\""} importlib-resources = {version = ">=1.0", markers = "python_version < \"3.7\""} platformdirs = ">=2,<3" six = ">=1.9.0,<2" [package.extras] -docs = ["proselint (>=0.10.2)", "sphinx (>=3)", "sphinx-argparse (>=0.2.5)", "sphinx-rtd-theme (>=0.4.3)", "towncrier (>=19.9.0rc1)"] +docs = ["proselint (>=0.10.2)", 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b/tests/test_catalog.py index 0940bf468..049aa3bd4 100644 --- a/tests/test_catalog.py +++ b/tests/test_catalog.py @@ -445,3 +445,26 @@ def test_create_database(random_glue_database: str, account_id: str, use_catalog r = glue_client.get_database(Name=random_glue_database) assert r["Database"]["Name"] == random_glue_database assert r["Database"]["Description"] == description + + +def test_catalog_json(path: str, glue_database: str, glue_table: str, account_id: str): + # Create JSON table + assert not wr.catalog.does_table_exist(database=glue_database, table=glue_table) + wr.catalog.create_json_table( + database=glue_database, + table=glue_table, + path=path, + columns_types={"id": "int", "value": "string"}, + partitions_types={"y": "int", "m": "int"}, + compression="snappy", + ) + assert wr.catalog.does_table_exist(database=glue_database, table=glue_table) + # Add JSON partitions + wr.catalog.add_json_partitions( + database=glue_database, + table=glue_table, + partitions_values={f"{path}y=2020/m=1/": ["2020", "1"], f"{path}y=2021/m=2/": ["2021", "2"]}, + compression="snappy", + ) + partitions_values = wr.catalog.get_partitions(database=glue_database, table=glue_table) + assert len(partitions_values) == 2 diff --git a/tests/test_mysql.py b/tests/test_mysql.py index 07f21a25a..805c1403f 100644 --- a/tests/test_mysql.py +++ b/tests/test_mysql.py @@ -5,6 +5,7 @@ import pyarrow as pa import pymysql import pytest +from pymysql.cursors import SSCursor import awswrangler as wr @@ -27,6 +28,13 @@ def mysql_con_ssl(): con.close() +@pytest.fixture(scope="function") +def mysql_con_sscursor(): + con = wr.mysql.connect("aws-data-wrangler-mysql", cursorclass=SSCursor) + yield con + con.close() + + @pytest.mark.parametrize("connection", ["aws-data-wrangler-mysql", "aws-data-wrangler-mysql-ssl"]) def test_connection(connection): wr.mysql.connect(connection, connect_timeout=10).close() @@ -45,11 +53,22 @@ def test_read_sql_query_simple(databases_parameters): assert df.shape == (1, 1) +def test_conn_cursor(): + con = wr.mysql.connect("aws-data-wrangler-mysql", cursorclass=SSCursor) + + assert con.cursorclass == SSCursor + + def test_to_sql_simple(mysql_table, mysql_con): df = pd.DataFrame({"c0": [1, 2, 3], "c1": ["foo", "boo", "bar"]}) wr.mysql.to_sql(df, mysql_con, mysql_table, "test", "overwrite", True) +def test_to_sql_simple_sscursor(mysql_table, mysql_con_sscursor): + df = pd.DataFrame({"c0": [1, 2, 3], "c1": ["foo", "boo", "bar"]}) + wr.mysql.to_sql(df, mysql_con_sscursor, mysql_table, "test", "overwrite", True) + + def test_to_sql_simple_ssl(mysql_table, mysql_con_ssl): df = pd.DataFrame({"c0": [1, 2, 3], "c1": ["foo", "boo", "bar"]}) wr.mysql.to_sql(df, mysql_con_ssl, mysql_table, "test", "overwrite", True) diff --git a/tests/test_s3_text.py b/tests/test_s3_text.py index 65243ffe0..be74270e9 100644 --- a/tests/test_s3_text.py +++ b/tests/test_s3_text.py @@ -41,7 +41,7 @@ def test_csv_encoding(path, encoding, strings, wrong_encoding, exception, line_t @pytest.mark.parametrize("use_threads", [True, False, 2]) @pytest.mark.parametrize("chunksize", [None, 1]) -def test_read_partitioned_json(path, use_threads, chunksize): +def test_read_partitioned_json_paths(path, use_threads, chunksize): df = pd.DataFrame({"c0": [0, 1], "c1": ["foo", "boo"]}) paths = [f"{path}year={y}/month={m}/0.json" for y, m in [(2020, 1), (2020, 2), (2021, 1)]] for p in paths: @@ -57,7 +57,7 @@ def test_read_partitioned_json(path, use_threads, chunksize): @pytest.mark.parametrize("use_threads", [True, False, 2]) @pytest.mark.parametrize("chunksize", [None, 1]) -def test_read_partitioned_csv(path, use_threads, chunksize): +def test_read_partitioned_csv_paths(path, use_threads, chunksize): df = pd.DataFrame({"c0": [0, 1], "c1": ["foo", "boo"]}) paths = [f"{path}year={y}/month={m}/0.csv" for y, m in [(2020, 1), (2020, 2), (2021, 1)]] for p in paths: @@ -176,6 +176,13 @@ def test_json(path): assert df1.equals(wr.s3.read_json(path=[path0, path1], use_threads=True)) +def test_to_json_partitioned(path, glue_database, glue_table): + df = pd.DataFrame({"c0": [0, 1, 2], "c1": [3, 4, 5], "c2": [6, 7, 8]}) + partitions = wr.s3.to_json(df, path, dataset=True, database=glue_database, table=glue_table, partition_cols=["c0"]) + assert len(partitions["paths"]) == 3 + assert len(partitions["partitions_values"]) == 3 + + @pytest.mark.parametrize("filename_prefix", [None, "my_prefix"]) @pytest.mark.parametrize("use_threads", [True, False]) def test_to_text_filename_prefix(compare_filename_prefix, path, filename_prefix, use_threads): diff --git a/tutorials/014 - Schema Evolution.ipynb b/tutorials/014 - Schema Evolution.ipynb index c8a852431..34910ad68 100644 --- a/tutorials/014 - Schema Evolution.ipynb +++ b/tutorials/014 - Schema Evolution.ipynb @@ -8,10 +8,11 @@ "\n", "# 14 - Schema Evolution\n", "\n", - "Wrangler support new **columns** on Parquet Dataset through:\n", + "Wrangler support new **columns** on Parquet and CSV datasets through:\n", "\n", "- [wr.s3.to_parquet()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.s3.to_parquet.html#awswrangler.s3.to_parquet)\n", - "- [wr.s3.store_parquet_metadata()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.s3.store_parquet_metadata.html#awswrangler.s3.store_parquet_metadata) i.e. \"Crawler\"" + "- [wr.s3.store_parquet_metadata()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.s3.store_parquet_metadata.html#awswrangler.s3.store_parquet_metadata) i.e. \"Crawler\"\n", + "- [wr.s3.to_csv()](https://aws-data-wrangler.readthedocs.io/en/2.12.1/stubs/awswrangler.s3.to_csv.html#awswrangler.s3.to_csv)" ] }, { @@ -55,7 +56,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Creating the Dataset" + "## Creating the Dataset\n", + "### Parquet" ] }, { @@ -132,6 +134,43 @@ "wr.s3.read_parquet(path, dataset=True)" ] }, + { + "cell_type": "markdown", + "source": [ + "### CSV" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "df = pd.DataFrame({\n", + " \"id\": [1, 2],\n", + " \"value\": [\"foo\", \"boo\"],\n", + "})\n", + "\n", + "wr.s3.to_csv(\n", + " df=df,\n", + " path=path,\n", + " dataset=True,\n", + " mode=\"overwrite\",\n", + " database=\"aws_data_wrangler\",\n", + " table=\"my_table\"\n", + ")\n", + "\n", + "wr.s3.read_csv(path, dataset=True)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, { "cell_type": "markdown", "metadata": {}, @@ -150,7 +189,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Appending with NEW COLUMNS" + "## Appending with NEW COLUMNS\n", + "### Parquet" ] }, { @@ -252,6 +292,49 @@ "wr.s3.read_parquet(path, dataset=True, validate_schema=False)" ] }, + { + "cell_type": "markdown", + "source": [ + "### CSV\n", + "\n", + "Note: for CSV datasets due to [column ordering](https://docs.aws.amazon.com/athena/latest/ug/types-of-updates.html#updates-add-columns-beginning-middle-of-table), by default, schema evolution is disabled. Enable it by passing `schema_evolution=True` flag" + ], + "metadata": { + "collapsed": false + } + }, + { + "cell_type": "code", + "execution_count": null, + "outputs": [], + "source": [ + "df = pd.DataFrame({\n", + " \"id\": [3, 4],\n", + " \"value\": [\"bar\", None],\n", + " \"date\": [date(2020, 1, 3), date(2020, 1, 4)],\n", + " \"flag\": [True, False]\n", + "})\n", + "\n", + "wr.s3.to_csv(\n", + " df=df,\n", + " path=path,\n", + " dataset=True,\n", + " mode=\"append\",\n", + " database=\"aws_data_wrangler\",\n", + " table=\"my_table\",\n", + " schema_evolution=True,\n", + " catalog_versioning=True # Optional\n", + ")\n", + "\n", + "wr.s3.read_csv(path, dataset=True, validate_schema=False)" + ], + "metadata": { + "collapsed": false, + "pycharm": { + "name": "#%%\n" + } + } + }, { "cell_type": "markdown", "metadata": {}, @@ -401,17 +484,8 @@ "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.10" - }, - "pycharm": { - "stem_cell": { - "cell_type": "raw", - "metadata": { - "collapsed": false - }, - "source": [] - } } }, "nbformat": 4, "nbformat_minor": 4 -} +} \ No newline at end of file From 170f19b291b448769ee46973140a1e9fc8a68900 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Wed, 3 Nov 2021 14:34:41 +0000 Subject: [PATCH 24/36] Green tests --- awswrangler/catalog/_get.py | 12 ++++++++++ tests/test_catalog.py | 45 ++++++++++++++++++++----------------- 2 files changed, 37 insertions(+), 20 deletions(-) diff --git a/awswrangler/catalog/_get.py b/awswrangler/catalog/_get.py index 7e6007523..df06934f5 100644 --- a/awswrangler/catalog/_get.py +++ b/awswrangler/catalog/_get.py @@ -312,6 +312,7 @@ def tables( limit: int = 100, catalog_id: Optional[str] = None, database: Optional[str] = None, + transaction_id: Optional[str] = None, search_text: Optional[str] = None, name_contains: Optional[str] = None, name_prefix: Optional[str] = None, @@ -320,6 +321,10 @@ def tables( ) -> pd.DataFrame: """Get a DataFrame with tables filtered by a search term, prefix, suffix. + Note + ---- + Search feature is not supported for Governed tables. + Parameters ---------- limit : int, optional @@ -329,6 +334,8 @@ def tables( If none is provided, the AWS account ID is used by default. database : str, optional Database name. + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). search_text : str, optional Select only tables with the given string in table's properties. name_contains : str, optional @@ -355,6 +362,7 @@ def tables( table_iter = get_tables( catalog_id=catalog_id, database=database, + transaction_id=transaction_id, name_contains=name_contains, name_prefix=name_prefix, name_suffix=name_suffix, @@ -402,6 +410,10 @@ def search_tables( ) -> Iterator[Dict[str, Any]]: """Get Pandas DataFrame of tables filtered by a search string. + Note + ---- + Search feature is not supported for Governed tables. + Parameters ---------- text : str, optional diff --git a/tests/test_catalog.py b/tests/test_catalog.py index 049aa3bd4..4a3c8b1ac 100644 --- a/tests/test_catalog.py +++ b/tests/test_catalog.py @@ -29,6 +29,7 @@ def test_create_table(path: str, glue_database: str, glue_table: str, table_type query_as_of_time = calendar.timegm(time.gmtime()) + 5 # Adding minor delay to avoid concurrency df = wr.catalog.table(database=glue_database, table=glue_table, query_as_of_time=query_as_of_time) assert df.shape == (4, 4) + time.sleep(5) # Delay to avoid Delete concurrency assert wr.catalog.does_table_exist(database=glue_database, table=glue_table) is True @@ -120,12 +121,7 @@ def test_catalog( ) dtypes = wr.catalog.get_table_types(database=glue_database, table=glue_table, transaction_id=transaction_id) assert len(dtypes) == 4 - # search - tables = list(wr.catalog.search_tables(text="parquet", catalog_id=account_id)) - assert len(tables) > 0 - for tbl in tables: - if tbl["Name"] == glue_table: - assert tbl["TableType"] == table_type + # prefix tables = list( wr.catalog.get_tables(name_prefix=glue_table[:4], catalog_id=account_id, transaction_id=transaction_id) @@ -171,22 +167,31 @@ def test_catalog( for tbl in tables: if tbl["Name"] == glue_table: assert tbl["TableType"] == table_type + + # search (Not supported for Governed tables) + if table_type != "GOVERNED": + assert ( + len( + wr.catalog.tables( + database=glue_database, + search_text="parquet", + name_prefix=glue_table[0], + name_contains=glue_table[3], + name_suffix=glue_table[-1], + catalog_id=account_id, + ).index + ) + > 0 + ) + tables = list(wr.catalog.search_tables(text="parquet", catalog_id=account_id)) + assert len(tables) > 0 + for tbl in tables: + if tbl["Name"] == glue_table: + assert tbl["TableType"] == table_type + # DataFrames assert len(wr.catalog.databases().index) > 0 - assert len(wr.catalog.tables().index) > 0 - assert ( - len( - wr.catalog.tables( - database=glue_database, - search_text="parquet", - name_prefix=glue_table[0], - name_contains=glue_table[3], - name_suffix=glue_table[-1], - catalog_id=account_id, - ).index - ) - > 0 - ) + assert len(wr.catalog.tables(transaction_id=transaction_id).index) > 0 assert len(wr.catalog.table(database=glue_database, table=glue_table, transaction_id=transaction_id).index) > 0 assert ( len( From 6045e796615331ac3925d311cbc8fa59108eee9d Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Wed, 3 Nov 2021 14:53:43 +0000 Subject: [PATCH 25/36] Minor - Fixing automated merge --- awswrangler/catalog/_create.py | 69 ---------------------------------- 1 file changed, 69 deletions(-) diff --git a/awswrangler/catalog/_create.py b/awswrangler/catalog/_create.py index 878029c48..e7aa92974 100644 --- a/awswrangler/catalog/_create.py +++ b/awswrangler/catalog/_create.py @@ -463,75 +463,6 @@ def _create_json_table( # pylint: disable=too-many-arguments ) -def _create_json_table( # pylint: disable=too-many-arguments - database: str, - table: str, - path: str, - columns_types: Dict[str, str], - partitions_types: Optional[Dict[str, str]], - bucketing_info: Optional[Tuple[List[str], int]], - description: Optional[str], - compression: Optional[str], - parameters: Optional[Dict[str, str]], - columns_comments: Optional[Dict[str, str]], - mode: str, - catalog_versioning: bool, - schema_evolution: bool, - serde_library: Optional[str], - serde_parameters: Optional[Dict[str, str]], - boto3_session: Optional[boto3.Session], - projection_enabled: bool, - projection_types: Optional[Dict[str, str]], - projection_ranges: Optional[Dict[str, str]], - projection_values: Optional[Dict[str, str]], - projection_intervals: Optional[Dict[str, str]], - projection_digits: Optional[Dict[str, str]], - catalog_table_input: Optional[Dict[str, Any]], - catalog_id: Optional[str], -) -> None: - table = sanitize_table_name(table=table) - partitions_types = {} if partitions_types is None else partitions_types - _logger.debug("catalog_table_input: %s", catalog_table_input) - table_input: Dict[str, Any] - if schema_evolution is False: - _utils.check_schema_changes(columns_types=columns_types, table_input=catalog_table_input, mode=mode) - if (catalog_table_input is not None) and (mode in ("append", "overwrite_partitions")): - table_input = catalog_table_input - else: - table_input = _json_table_definition( - table=table, - path=path, - columns_types=columns_types, - partitions_types=partitions_types, - bucketing_info=bucketing_info, - compression=compression, - serde_library=serde_library, - serde_parameters=serde_parameters, - ) - table_exist: bool = catalog_table_input is not None - _logger.debug("table_exist: %s", table_exist) - _create_table( - database=database, - table=table, - description=description, - parameters=parameters, - columns_comments=columns_comments, - mode=mode, - catalog_versioning=catalog_versioning, - boto3_session=boto3_session, - table_input=table_input, - table_exist=table_exist, - partitions_types=partitions_types, - projection_enabled=projection_enabled, - projection_types=projection_types, - projection_ranges=projection_ranges, - projection_values=projection_values, - projection_intervals=projection_intervals, - projection_digits=projection_digits, - catalog_id=catalog_id, - ) - - @apply_configs def upsert_table_parameters( parameters: Dict[str, str], From 245d365cabe5d7290810f6cfb581fb77b4090b49 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Fri, 5 Nov 2021 18:05:47 +0000 Subject: [PATCH 26/36] LakeFormation test infra --- test_infra/app.py | 4 + test_infra/poetry.lock | 678 ++++++++++++----------- test_infra/pyproject.toml | 3 +- test_infra/stacks/databases_stack.py | 30 +- test_infra/stacks/lakeformation_stack.py | 118 ++++ test_infra/stacks/opensearch_stack.py | 20 +- 6 files changed, 509 insertions(+), 344 deletions(-) create mode 100644 test_infra/stacks/lakeformation_stack.py diff --git a/test_infra/app.py b/test_infra/app.py index 8c3395e22..22c17344d 100644 --- a/test_infra/app.py +++ b/test_infra/app.py @@ -2,11 +2,13 @@ from aws_cdk import core as cdk from stacks.base_stack import BaseStack from stacks.databases_stack import DatabasesStack +from stacks.lakeformation_stack import LakeFormationStack from stacks.opensearch_stack import OpenSearchStack app = cdk.App() base = BaseStack(app, "aws-data-wrangler-base") + DatabasesStack( app, "aws-data-wrangler-databases", @@ -23,4 +25,6 @@ base.get_key, ) +LakeFormationStack(app, "aws-data-wrangler-lakeformation") + app.synth() diff --git a/test_infra/poetry.lock b/test_infra/poetry.lock index aa17ff35f..164515b8b 100644 --- a/test_infra/poetry.lock +++ b/test_infra/poetry.lock @@ -14,625 +14,639 @@ tests_no_zope = ["coverage[toml] (>=5.0.2)", "hypothesis", "pympler", "pytest (> [[package]] name = "aws-cdk.assets" -version = "1.124.0" +version = "1.130.0" description = "This module is deprecated. All types are now available under the core module" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.core" = "1.124.0" -"aws-cdk.cx-api" = "1.124.0" +"aws-cdk.core" = "1.130.0" +"aws-cdk.cx-api" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-applicationautoscaling" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::ApplicationAutoScaling" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-autoscaling-common" = "1.124.0" -"aws-cdk.aws-cloudwatch" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.core" = "1.124.0" +"aws-cdk.aws-autoscaling-common" = "1.130.0" +"aws-cdk.aws-cloudwatch" = "1.130.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-autoscaling-common" -version = "1.124.0" +version = "1.130.0" description = "Common implementation package for @aws-cdk/aws-autoscaling and @aws-cdk/aws-applicationautoscaling" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.core" = "1.124.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-certificatemanager" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::CertificateManager" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-cloudwatch" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-lambda" = "1.124.0" -"aws-cdk.aws-route53" = "1.124.0" -"aws-cdk.core" = "1.124.0" +"aws-cdk.aws-cloudwatch" = "1.130.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.aws-lambda" = "1.130.0" +"aws-cdk.aws-route53" = "1.130.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-cloudformation" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::CloudFormation" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-lambda" = "1.124.0" -"aws-cdk.aws-s3" = "1.124.0" -"aws-cdk.aws-sns" = "1.124.0" -"aws-cdk.core" = "1.124.0" -"aws-cdk.cx-api" = "1.124.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.aws-lambda" = "1.130.0" +"aws-cdk.aws-s3" = "1.130.0" +"aws-cdk.aws-sns" = "1.130.0" +"aws-cdk.core" = "1.130.0" +"aws-cdk.cx-api" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-cloudwatch" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::CloudWatch" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.core" = "1.124.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-codeguruprofiler" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::CodeGuruProfiler" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.core" = "1.124.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-codestarnotifications" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::CodeStarNotifications" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.core" = "1.124.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-ec2" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::EC2" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-cloudwatch" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-kms" = "1.124.0" -"aws-cdk.aws-logs" = "1.124.0" -"aws-cdk.aws-s3" = "1.124.0" -"aws-cdk.aws-s3-assets" = "1.124.0" -"aws-cdk.aws-ssm" = "1.124.0" -"aws-cdk.cloud-assembly-schema" = "1.124.0" -"aws-cdk.core" = "1.124.0" -"aws-cdk.cx-api" = "1.124.0" -"aws-cdk.region-info" = "1.124.0" +"aws-cdk.aws-cloudwatch" = "1.130.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.aws-kms" = "1.130.0" +"aws-cdk.aws-logs" = "1.130.0" +"aws-cdk.aws-s3" = "1.130.0" +"aws-cdk.aws-s3-assets" = "1.130.0" +"aws-cdk.aws-ssm" = "1.130.0" +"aws-cdk.cloud-assembly-schema" = "1.130.0" +"aws-cdk.core" = "1.130.0" +"aws-cdk.cx-api" = "1.130.0" +"aws-cdk.region-info" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-ecr" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::ECR" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-events" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.core" = "1.124.0" +"aws-cdk.aws-events" = "1.130.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-ecr-assets" -version = "1.124.0" +version = "1.130.0" description = "Docker image assets deployed to ECR" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.assets" = "1.124.0" -"aws-cdk.aws-ecr" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-s3" = "1.124.0" -"aws-cdk.core" = "1.124.0" -"aws-cdk.cx-api" = "1.124.0" +"aws-cdk.assets" = "1.130.0" +"aws-cdk.aws-ecr" = "1.130.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.aws-s3" = "1.130.0" +"aws-cdk.core" = "1.130.0" +"aws-cdk.cx-api" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-efs" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::EFS" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-ec2" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-kms" = "1.124.0" -"aws-cdk.cloud-assembly-schema" = "1.124.0" -"aws-cdk.core" = "1.124.0" -"aws-cdk.cx-api" = "1.124.0" +"aws-cdk.aws-ec2" = "1.130.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.aws-kms" = "1.130.0" +"aws-cdk.cloud-assembly-schema" = "1.130.0" +"aws-cdk.core" = "1.130.0" +"aws-cdk.cx-api" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-events" -version = "1.124.0" +version = "1.130.0" description = "Amazon EventBridge Construct Library" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.core" = "1.124.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-glue" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::Glue" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.assets" = "1.124.0" -"aws-cdk.aws-cloudwatch" = "1.124.0" -"aws-cdk.aws-ec2" = "1.124.0" -"aws-cdk.aws-events" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-kms" = "1.124.0" -"aws-cdk.aws-logs" = "1.124.0" -"aws-cdk.aws-s3" = "1.124.0" -"aws-cdk.aws-s3-assets" = "1.124.0" -"aws-cdk.core" = "1.124.0" +"aws-cdk.assets" = "1.130.0" +"aws-cdk.aws-cloudwatch" = "1.130.0" +"aws-cdk.aws-ec2" = "1.130.0" +"aws-cdk.aws-events" = "1.130.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.aws-kms" = "1.130.0" +"aws-cdk.aws-logs" = "1.130.0" +"aws-cdk.aws-s3" = "1.130.0" +"aws-cdk.aws-s3-assets" = "1.130.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-iam" -version = "1.124.0" +version = "1.130.0" description = "CDK routines for easily assigning correct and minimal IAM permissions" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.core" = "1.124.0" -"aws-cdk.region-info" = "1.124.0" +"aws-cdk.core" = "1.130.0" +"aws-cdk.region-info" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-kms" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::KMS" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.cloud-assembly-schema" = "1.124.0" -"aws-cdk.core" = "1.124.0" -"aws-cdk.cx-api" = "1.124.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.cloud-assembly-schema" = "1.130.0" +"aws-cdk.core" = "1.130.0" +"aws-cdk.cx-api" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" +publication = ">=0.0.3" + +[[package]] +name = "aws-cdk.aws-lakeformation" +version = "1.130.0" +description = "The CDK Construct Library for AWS::LakeFormation" +category = "main" +optional = false +python-versions = ">=3.6" + +[package.dependencies] +"aws-cdk.core" = "1.130.0" +constructs = ">=3.3.69,<4.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-lambda" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::Lambda" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-applicationautoscaling" = "1.124.0" -"aws-cdk.aws-cloudwatch" = "1.124.0" -"aws-cdk.aws-codeguruprofiler" = "1.124.0" -"aws-cdk.aws-ec2" = "1.124.0" -"aws-cdk.aws-ecr" = "1.124.0" -"aws-cdk.aws-ecr-assets" = "1.124.0" -"aws-cdk.aws-efs" = "1.124.0" -"aws-cdk.aws-events" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-kms" = "1.124.0" -"aws-cdk.aws-logs" = "1.124.0" -"aws-cdk.aws-s3" = "1.124.0" -"aws-cdk.aws-s3-assets" = "1.124.0" -"aws-cdk.aws-signer" = "1.124.0" -"aws-cdk.aws-sqs" = "1.124.0" -"aws-cdk.core" = "1.124.0" -"aws-cdk.cx-api" = "1.124.0" -"aws-cdk.region-info" = "1.124.0" 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+"aws-cdk.aws-kms" = "1.130.0" +"aws-cdk.aws-lambda" = "1.130.0" +"aws-cdk.aws-s3" = "1.130.0" +"aws-cdk.aws-secretsmanager" = "1.130.0" +"aws-cdk.core" = "1.130.0" +"aws-cdk.custom-resources" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-route53" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::Route53" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-ec2" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-logs" = "1.124.0" -"aws-cdk.cloud-assembly-schema" = "1.124.0" -"aws-cdk.core" = "1.124.0" -"aws-cdk.custom-resources" = "1.124.0" +"aws-cdk.aws-ec2" = "1.130.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.aws-logs" = "1.130.0" +"aws-cdk.cloud-assembly-schema" = "1.130.0" +"aws-cdk.core" = "1.130.0" +"aws-cdk.custom-resources" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-s3" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::S3" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-events" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-kms" = "1.124.0" -"aws-cdk.core" = "1.124.0" -"aws-cdk.cx-api" = "1.124.0" +"aws-cdk.aws-events" = "1.130.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.aws-kms" = "1.130.0" +"aws-cdk.core" = "1.130.0" +"aws-cdk.cx-api" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-s3-assets" -version = "1.124.0" +version = "1.130.0" description = "Deploy local files and directories to S3" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.assets" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-kms" = "1.124.0" -"aws-cdk.aws-s3" = "1.124.0" -"aws-cdk.core" = "1.124.0" -"aws-cdk.cx-api" = "1.124.0" +"aws-cdk.assets" = "1.130.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.aws-kms" = "1.130.0" +"aws-cdk.aws-s3" = "1.130.0" +"aws-cdk.core" = "1.130.0" +"aws-cdk.cx-api" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-sam" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for the AWS Serverless Application Model (SAM) resources" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.core" = "1.124.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-secretsmanager" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::SecretsManager" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-ec2" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-kms" = "1.124.0" -"aws-cdk.aws-lambda" = "1.124.0" -"aws-cdk.aws-sam" = "1.124.0" -"aws-cdk.core" = "1.124.0" -"aws-cdk.cx-api" = "1.124.0" +"aws-cdk.aws-ec2" = "1.130.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.aws-kms" = "1.130.0" +"aws-cdk.aws-lambda" = "1.130.0" +"aws-cdk.aws-sam" = "1.130.0" +"aws-cdk.core" = "1.130.0" +"aws-cdk.cx-api" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-signer" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::Signer" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.core" = "1.124.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-sns" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::SNS" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-cloudwatch" = "1.124.0" -"aws-cdk.aws-codestarnotifications" = "1.124.0" -"aws-cdk.aws-events" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-kms" = "1.124.0" -"aws-cdk.aws-sqs" = "1.124.0" -"aws-cdk.core" = "1.124.0" +"aws-cdk.aws-cloudwatch" = "1.130.0" +"aws-cdk.aws-codestarnotifications" = "1.130.0" +"aws-cdk.aws-events" = "1.130.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.aws-kms" = "1.130.0" +"aws-cdk.aws-sqs" = "1.130.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-sqs" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::SQS" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-cloudwatch" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-kms" = "1.124.0" -"aws-cdk.core" = "1.124.0" +"aws-cdk.aws-cloudwatch" = "1.130.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.aws-kms" = "1.130.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.aws-ssm" -version = "1.124.0" +version = "1.130.0" description = "The CDK Construct Library for AWS::SSM" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-kms" = "1.124.0" -"aws-cdk.cloud-assembly-schema" = "1.124.0" -"aws-cdk.core" = "1.124.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.aws-kms" = "1.130.0" +"aws-cdk.cloud-assembly-schema" = "1.130.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.cloud-assembly-schema" -version = "1.124.0" +version = "1.130.0" description = "Cloud Assembly Schema" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.core" -version = "1.124.0" +version = "1.130.0" description = "AWS Cloud Development Kit Core Library" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.cloud-assembly-schema" = "1.124.0" -"aws-cdk.cx-api" = "1.124.0" -"aws-cdk.region-info" = "1.124.0" +"aws-cdk.cloud-assembly-schema" = "1.130.0" +"aws-cdk.cx-api" = "1.130.0" +"aws-cdk.region-info" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.custom-resources" -version = "1.124.0" +version = "1.130.0" description = "Constructs for implementing CDK custom resources" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.aws-cloudformation" = "1.124.0" -"aws-cdk.aws-ec2" = "1.124.0" -"aws-cdk.aws-iam" = "1.124.0" -"aws-cdk.aws-lambda" = "1.124.0" -"aws-cdk.aws-logs" = "1.124.0" -"aws-cdk.aws-sns" = "1.124.0" -"aws-cdk.core" = "1.124.0" +"aws-cdk.aws-cloudformation" = "1.130.0" +"aws-cdk.aws-ec2" = "1.130.0" +"aws-cdk.aws-iam" = "1.130.0" +"aws-cdk.aws-lambda" = "1.130.0" +"aws-cdk.aws-logs" = "1.130.0" +"aws-cdk.aws-sns" = "1.130.0" +"aws-cdk.core" = "1.130.0" constructs = ">=3.3.69,<4.0.0" -jsii = ">=1.34.0,<2.0.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" [[package]] name = "aws-cdk.cx-api" -version = "1.124.0" +version = "1.130.0" description = "Cloud executable protocol" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -"aws-cdk.cloud-assembly-schema" = "1.124.0" -jsii = ">=1.34.0,<2.0.0" +"aws-cdk.cloud-assembly-schema" = "1.130.0" +jsii = ">=1.41.0,<2.0.0" publication = ">=0.0.3" 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a/test_infra/pyproject.toml b/test_infra/pyproject.toml index 8cc331b1a..f8dc720fc 100644 --- a/test_infra/pyproject.toml +++ b/test_infra/pyproject.toml @@ -2,7 +2,7 @@ name = "awswrangler - test infrastructure" version = "2.12.1" description = "CDK test infrastructure for AWS" -authors = ["Igor Tavares"] +authors = ["Amazon Web Services"] license = "Apache License 2.0" [tool.poetry.dependencies] @@ -19,3 +19,4 @@ python = ">=3.6.2, <3.10" "aws-cdk.aws-secretsmanager" = "^1.124.0" "aws-cdk.aws-ssm" = "^1.124.0" "aws-cdk.aws-opensearchservice" = "^1.124.0" +"aws-cdk.aws-lakeformation" = "^1.124.0" diff --git a/test_infra/stacks/databases_stack.py b/test_infra/stacks/databases_stack.py index 6d75a6c08..7983ba92f 100644 --- a/test_infra/stacks/databases_stack.py +++ b/test_infra/stacks/databases_stack.py @@ -57,10 +57,12 @@ def _set_db_infra(self) -> None: vpc=self.vpc, description="AWS Data Wrangler Test Arena - Database security group", ) - self.db_security_group.add_ingress_rule(ec2.Peer.any_ipv4(), ec2.Port.all_traffic()) + self.db_security_group.add_ingress_rule( + ec2.Peer.any_ipv4(), ec2.Port.all_traffic() + ) ssm.StringParameter( self, - "db-secruity-group-parameter", + "db-security-group-parameter", parameter_name="/Wrangler/EC2/DatabaseSecurityGroupId", string_value=self.db_security_group.security_group_id, ) @@ -337,7 +339,9 @@ def _setup_postgresql(self) -> None: ), ), ) - cdk.CfnOutput(self, "PostgresqlAddress", value=aurora_pg.cluster_endpoint.hostname) + cdk.CfnOutput( + self, "PostgresqlAddress", value=aurora_pg.cluster_endpoint.hostname + ) cdk.CfnOutput(self, "PostgresqlPort", value=str(port)) cdk.CfnOutput(self, "PostgresqlDatabase", value=database) cdk.CfnOutput(self, "PostgresqlSchema", value=schema) @@ -421,7 +425,9 @@ def _setup_mysql(self) -> None: ), ), ) - cdk.CfnOutput(self, "MysqlAddress", value=aurora_mysql.cluster_endpoint.hostname) + cdk.CfnOutput( + self, "MysqlAddress", value=aurora_mysql.cluster_endpoint.hostname + ) cdk.CfnOutput(self, "MysqlPort", value=str(port)) cdk.CfnOutput(self, "MysqlDatabase", value=database) cdk.CfnOutput(self, "MysqlSchema", value=schema) @@ -477,7 +483,9 @@ def _setup_mysql_serverless(self) -> None: ) cdk.CfnOutput(self, "MysqlServerlessSecretArn", value=secret.secret_arn) cdk.CfnOutput(self, "MysqlServerlessClusterArn", value=aurora_mysql.cluster_arn) - cdk.CfnOutput(self, "MysqlServerlessAddress", value=aurora_mysql.cluster_endpoint.hostname) + cdk.CfnOutput( + self, "MysqlServerlessAddress", value=aurora_mysql.cluster_endpoint.hostname + ) cdk.CfnOutput(self, "MysqlServerlessPort", value=str(port)) cdk.CfnOutput(self, "MysqlServerlessDatabase", value=database) cdk.CfnOutput(self, "MysqlServerlessSchema", value=schema) @@ -490,8 +498,12 @@ def _setup_sqlserver(self) -> None: self, "aws-data-wrangler-sqlserver-instance", instance_identifier="sqlserver-instance-wrangler", - engine=rds.DatabaseInstanceEngine.sql_server_ex(version=rds.SqlServerEngineVersion.VER_15), - instance_type=ec2.InstanceType.of(ec2.InstanceClass.BURSTABLE3, ec2.InstanceSize.SMALL), + engine=rds.DatabaseInstanceEngine.sql_server_ex( + version=rds.SqlServerEngineVersion.VER_15 + ), + instance_type=ec2.InstanceType.of( + ec2.InstanceClass.BURSTABLE3, ec2.InstanceSize.SMALL + ), credentials=rds.Credentials.from_password( username=self.db_username, password=self.db_password_secret, @@ -538,7 +550,9 @@ def _setup_sqlserver(self) -> None: ), ), ) - cdk.CfnOutput(self, "SqlServerAddress", value=sqlserver.instance_endpoint.hostname) + cdk.CfnOutput( + self, "SqlServerAddress", value=sqlserver.instance_endpoint.hostname + ) cdk.CfnOutput(self, "SqlServerPort", value=str(port)) cdk.CfnOutput(self, "SqlServerDatabase", value=database) cdk.CfnOutput(self, "SqlServerSchema", value=schema) diff --git a/test_infra/stacks/lakeformation_stack.py b/test_infra/stacks/lakeformation_stack.py new file mode 100644 index 000000000..4f2839c07 --- /dev/null +++ b/test_infra/stacks/lakeformation_stack.py @@ -0,0 +1,118 @@ +from aws_cdk import aws_glue as glue +from aws_cdk import aws_iam as iam +from aws_cdk import aws_lakeformation as lf +from aws_cdk import aws_s3 as s3 +from aws_cdk import core as cdk + + +class LakeFormationStack(cdk.Stack): # type: ignore + def __init__( + self, + scope: cdk.Construct, + construct_id: str, + **kwargs: str, + ) -> None: + """ + AWS Data Wrangler Development LakeFormation Infrastructure. + """ + super().__init__(scope, construct_id, **kwargs) + + self._set_lakeformation_infra() + + def _set_lakeformation_infra(self) -> None: + bucket = s3.Bucket( + self, + id="aws-data-wrangler-lf", + block_public_access=s3.BlockPublicAccess( + block_public_acls=True, + block_public_policy=True, + ignore_public_acls=True, + restrict_public_buckets=True, + ), + lifecycle_rules=[ + s3.LifecycleRule( + id="CleaningUp", + enabled=True, + expiration=cdk.Duration.days(1), + abort_incomplete_multipart_upload_after=cdk.Duration.days(1), + ), + ], + versioned=True, + ) + + transaction_role = iam.Role( + self, + "aws-data-wrangler-lf-transaction-role", + assumed_by=iam.ServicePrincipal("lakeformation.amazonaws.com"), + inline_policies={ + "Root": iam.PolicyDocument( + statements=[ + iam.PolicyStatement( + effect=iam.Effect.ALLOW, + actions=[ + "s3:DeleteObject", + "s3:GetObject", + "s3:PutObject", + ], + resources=[ + f"{bucket.bucket_arn}/*", + ], + ), + iam.PolicyStatement( + effect=iam.Effect.ALLOW, + actions=[ + "s3:ListObject", + ], + resources=[ + f"{bucket.bucket_arn}", + ], + ), + iam.PolicyStatement( + effect=iam.Effect.ALLOW, + actions=[ + "execute-api:Invoke", + ], + resources=[ + f"arn:{self.partition}:execute-api:*:*:*/*/POST/reportStatus", + ], + ), + iam.PolicyStatement( + effect=iam.Effect.ALLOW, + actions=[ + "lakeformation:CancelTransaction", + "lakeformation:CommitTransaction", + "lakeformation:GetTableObjects", + "lakeformation:StartTransaction", + "lakeformation:UpdateTableObjects", + ], + resources=["*"], + ), + iam.PolicyStatement( + effect=iam.Effect.ALLOW, + actions=[ + "glue:GetPartitions", + "glue:GetTable", + "glue:UpdateTable", + ], + resources=["*"], + ), + ] + ), + }, + ) + + lf.CfnResource( + self, + "aws-data-wrangler-bucket-lf-registration", + resource_arn=bucket.bucket_arn, + use_service_linked_role=False, + role_arn=transaction_role.role_arn, + ) + + glue_db = glue.Database( + self, + id="aws-data-wrangler-lf-glue-db", + database_name="aws_data_wrangler_lakeformation", + ) + + cdk.CfnOutput(self, "LakeFormationGlueDatabase", value=glue_db.database_name) diff --git a/test_infra/stacks/opensearch_stack.py b/test_infra/stacks/opensearch_stack.py index f3bc6a1f8..d5f6d1c67 100644 --- a/test_infra/stacks/opensearch_stack.py +++ b/test_infra/stacks/opensearch_stack.py @@ -60,7 +60,9 @@ def _setup_opensearch_1_0(self) -> None: domain_name, domain_name=domain_name, version=opensearch.EngineVersion.OPENSEARCH_1_0, - capacity=opensearch.CapacityConfig(data_node_instance_type="t3.small.search", data_nodes=1), + capacity=opensearch.CapacityConfig( + data_node_instance_type="t3.small.search", data_nodes=1 + ), access_policies=[ iam.PolicyStatement( effect=iam.Effect.ALLOW, @@ -72,7 +74,9 @@ def _setup_opensearch_1_0(self) -> None: removal_policy=cdk.RemovalPolicy.DESTROY, ) - cdk.CfnOutput(self, f"DomainEndpoint-{domain_name}", value=domain.domain_endpoint) + cdk.CfnOutput( + self, f"DomainEndpoint-{domain_name}", value=domain.domain_endpoint + ) def _setup_elasticsearch_7_10_fgac(self) -> None: domain_name = "wrangler-es-7-10-fgac" @@ -83,7 +87,9 @@ def _setup_elasticsearch_7_10_fgac(self) -> None: domain_name, domain_name=domain_name, version=opensearch.EngineVersion.ELASTICSEARCH_7_10, - capacity=opensearch.CapacityConfig(data_node_instance_type="t3.small.search", data_nodes=1), + capacity=opensearch.CapacityConfig( + data_node_instance_type="t3.small.search", data_nodes=1 + ), access_policies=[ iam.PolicyStatement( effect=iam.Effect.ALLOW, @@ -97,9 +103,13 @@ def _setup_elasticsearch_7_10_fgac(self) -> None: master_user_password=self.password_secret, ), node_to_node_encryption=True, - encryption_at_rest=opensearch.EncryptionAtRestOptions(enabled=True, kms_key=self.key), + encryption_at_rest=opensearch.EncryptionAtRestOptions( + enabled=True, kms_key=self.key + ), enforce_https=True, removal_policy=cdk.RemovalPolicy.DESTROY, ) - cdk.CfnOutput(self, f"DomainEndpoint-{domain_name}", value=domain.domain_endpoint) + cdk.CfnOutput( + self, f"DomainEndpoint-{domain_name}", value=domain.domain_endpoint + ) From a091986803f6cb43de59a10ea1d883236977c832 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Thu, 11 Nov 2021 13:24:10 +0000 Subject: [PATCH 27/36] Commit protocol change - Erie --- CONTRIBUTING.md | 24 ++++++++++++-------- awswrangler/exceptions.py | 4 ++++ awswrangler/lakeformation/_utils.py | 10 ++++++++ test_infra/app.py | 4 ++-- test_infra/scripts/delete-base.sh | 6 ----- test_infra/scripts/delete-databases.sh | 6 ----- test_infra/scripts/delete-opensearch.sh | 6 ----- test_infra/scripts/delete-stack.sh | 7 ++++++ test_infra/scripts/deploy-base.sh | 7 ------ test_infra/scripts/deploy-databases.sh | 7 ------ test_infra/scripts/deploy-opensearch.sh | 7 ------ test_infra/scripts/deploy-stack.sh | 8 +++++++ test_infra/stacks/base_stack.py | 1 + test_infra/stacks/databases_stack.py | 28 ++++++----------------- test_infra/stacks/lakeformation_stack.py | 29 ++---------------------- test_infra/stacks/opensearch_stack.py | 20 ++++------------ tests/test_catalog.py | 3 +-- 17 files changed, 61 insertions(+), 116 deletions(-) delete mode 100755 test_infra/scripts/delete-base.sh delete mode 100755 test_infra/scripts/delete-databases.sh delete mode 100755 test_infra/scripts/delete-opensearch.sh create mode 100755 test_infra/scripts/delete-stack.sh delete mode 100755 test_infra/scripts/deploy-base.sh delete mode 100755 test_infra/scripts/deploy-databases.sh delete mode 100755 test_infra/scripts/deploy-opensearch.sh create mode 100755 test_infra/scripts/deploy-stack.sh diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index e898ec21e..cd7a6af50 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -153,9 +153,9 @@ or ``cd scripts`` -* Deploy the Cloudformation template `base.yaml` +* Deploy the `base` CDK stack -``./deploy-base.sh`` +``./deploy-stack.sh base`` * Return to the project root directory @@ -175,7 +175,7 @@ or * [OPTIONAL] To remove the base test environment cloud formation stack post testing: -``./test_infra/scripts/delete-base.sh`` +``./test_infra/scripts/delete-stack.sh base`` ### Full test environment @@ -210,14 +210,18 @@ or ``cd scripts`` -* Deploy the Cloudformation templates `base.yaml` and `databases.yaml`. This step could take about 15 minutes to deploy. +* Deploy the `base` and `databases` CDK stacks. This step could take about 15 minutes to deploy. -``./deploy-base.sh`` -``./deploy-databases.sh`` +``./deploy-stack.sh base`` +``./deploy-stack.sh databases`` -* [OPTIONAL] Deploy the Cloudformation template `opensearch.yaml` (if you need to test Amazon OpenSearch Service). This step could take about 15 minutes to deploy. +* [OPTIONAL] Deploy the `lakeformation` CDK stack (if you need to test against the AWS Lake Formation Service). You must ensure Lake Formation is enabled in the account. -``./deploy-opensearch.sh`` +``./deploy-stack.sh lakeformation`` + +* [OPTIONAL] Deploy the `opensearch` CDK stack (if you need to test against the Amazon OpenSearch Service). This step could take about 15 minutes to deploy. + +``./deploy-stack.sh opensearch`` * Go to the `EC2 -> SecurityGroups` console, open the `aws-data-wrangler-*` security group and configure to accept your IP from any TCP port. - Alternatively run: @@ -254,9 +258,9 @@ or * [OPTIONAL] To remove the base test environment cloud formation stack post testing: -``./test_infra/scripts/delete-base.sh`` +``./test_infra/scripts/delete-stack.sh base`` -``./test_infra/scripts/delete-databases.sh`` +``./test_infra/scripts/delete-stack.sh databases`` ## Recommended Visual Studio Code Recommended setting diff --git a/awswrangler/exceptions.py b/awswrangler/exceptions.py index dd15a4994..fc17897de 100644 --- a/awswrangler/exceptions.py +++ b/awswrangler/exceptions.py @@ -37,6 +37,10 @@ class InvalidTable(Exception): """InvalidTable exception.""" +class CommitCancelled(Exception): + """CommitCancelled exception.""" + + class QueryFailed(Exception): """QueryFailed exception.""" diff --git a/awswrangler/lakeformation/_utils.py b/awswrangler/lakeformation/_utils.py index 8bb80e1d6..54eb16e6b 100644 --- a/awswrangler/lakeformation/_utils.py +++ b/awswrangler/lakeformation/_utils.py @@ -15,6 +15,7 @@ _QUERY_FINAL_STATES: List[str] = ["ERROR", "FINISHED"] _QUERY_WAIT_POLLING_DELAY: float = 2 # SECONDS _TRANSACTION_FINAL_STATES: List[str] = ["aborted", "committed"] +_TRANSACTION_WAIT_COMMIT_DELAY: float = 5 # SECONDS _TRANSACTION_WAIT_POLLING_DELAY: float = 10 # SECONDS _logger: logging.Logger = logging.getLogger(__name__) @@ -270,6 +271,15 @@ def commit_transaction(transaction_id: str, boto3_session: Optional[boto3.Sessio client_lakeformation: boto3.client = _utils.client(service_name="lakeformation", session=session) client_lakeformation.commit_transaction(TransactionId=transaction_id) + committed: bool = False + # Confirm transaction was committed + while not committed: + state: str = describe_transaction(transaction_id=transaction_id, boto3_session=session) + if state == "committed": + committed = True + elif state == "aborted": + raise exceptions.CommitCancelled(f"Transaction commit with id {transaction_id} was aborted.") + time.sleep(_TRANSACTION_WAIT_COMMIT_DELAY) def extend_transaction(transaction_id: str, boto3_session: Optional[boto3.Session] = None) -> None: diff --git a/test_infra/app.py b/test_infra/app.py index 22c17344d..3356f457b 100644 --- a/test_infra/app.py +++ b/test_infra/app.py @@ -17,6 +17,8 @@ base.get_key, ) +LakeFormationStack(app, "aws-data-wrangler-lakeformation") + OpenSearchStack( app, "aws-data-wrangler-opensearch", @@ -25,6 +27,4 @@ base.get_key, ) -LakeFormationStack(app, "aws-data-wrangler-lakeformation") - app.synth() diff --git a/test_infra/scripts/delete-base.sh b/test_infra/scripts/delete-base.sh deleted file mode 100755 index 1edd3dd27..000000000 --- a/test_infra/scripts/delete-base.sh +++ /dev/null @@ -1,6 +0,0 @@ -#!/usr/bin/env bash -set -e - -pushd .. -cdk destroy aws-data-wrangler-base -popd \ No newline at end of file diff --git a/test_infra/scripts/delete-databases.sh b/test_infra/scripts/delete-databases.sh deleted file mode 100755 index 31d97451f..000000000 --- a/test_infra/scripts/delete-databases.sh +++ /dev/null @@ -1,6 +0,0 @@ -#!/usr/bin/env bash -set -e - -pushd .. -cdk destroy aws-data-wrangler-databases -popd diff --git a/test_infra/scripts/delete-opensearch.sh b/test_infra/scripts/delete-opensearch.sh deleted file mode 100755 index 1c1c01ba2..000000000 --- a/test_infra/scripts/delete-opensearch.sh +++ /dev/null @@ -1,6 +0,0 @@ -#!/usr/bin/env bash -set -e - -pushd .. -cdk destroy aws-data-wrangler-opensearch -popd diff --git a/test_infra/scripts/delete-stack.sh b/test_infra/scripts/delete-stack.sh new file mode 100755 index 000000000..7980db591 --- /dev/null +++ b/test_infra/scripts/delete-stack.sh @@ -0,0 +1,7 @@ +#!/usr/bin/env bash +set -e +STACK=${1} + +pushd .. +cdk destroy aws-data-wrangler-${STACK} +popd \ No newline at end of file diff --git a/test_infra/scripts/deploy-base.sh b/test_infra/scripts/deploy-base.sh deleted file mode 100755 index 5dd7db64f..000000000 --- a/test_infra/scripts/deploy-base.sh +++ /dev/null @@ -1,7 +0,0 @@ -#!/usr/bin/env bash -set -e - -pushd .. -cdk bootstrap -cdk deploy aws-data-wrangler-base -popd diff --git a/test_infra/scripts/deploy-databases.sh b/test_infra/scripts/deploy-databases.sh deleted file mode 100755 index b5e1f4208..000000000 --- a/test_infra/scripts/deploy-databases.sh +++ /dev/null @@ -1,7 +0,0 @@ -#!/usr/bin/env bash -set -e - -pushd .. -cdk bootstrap -cdk deploy aws-data-wrangler-databases -popd diff --git a/test_infra/scripts/deploy-opensearch.sh b/test_infra/scripts/deploy-opensearch.sh deleted file mode 100755 index e94818af4..000000000 --- a/test_infra/scripts/deploy-opensearch.sh +++ /dev/null @@ -1,7 +0,0 @@ -#!/usr/bin/env bash -set -e - -pushd .. -cdk bootstrap -cdk deploy aws-data-wrangler-opensearch -popd diff --git a/test_infra/scripts/deploy-stack.sh b/test_infra/scripts/deploy-stack.sh new file mode 100755 index 000000000..cdfbf59ca --- /dev/null +++ b/test_infra/scripts/deploy-stack.sh @@ -0,0 +1,8 @@ +#!/usr/bin/env bash +set -e +STACK=${1} + +pushd .. +cdk bootstrap +cdk deploy aws-data-wrangler-${STACK} +popd \ No newline at end of file diff --git a/test_infra/stacks/base_stack.py b/test_infra/stacks/base_stack.py index cd784b569..0f30db19d 100644 --- a/test_infra/stacks/base_stack.py +++ b/test_infra/stacks/base_stack.py @@ -64,6 +64,7 @@ def __init__(self, scope: cdk.Construct, construct_id: str, **kwargs: str) -> No self, id="aws_data_wrangler_glue_database", database_name="aws_data_wrangler", + location_uri=f"s3://{self.bucket.bucket_name}", ) log_group = logs.LogGroup( self, diff --git a/test_infra/stacks/databases_stack.py b/test_infra/stacks/databases_stack.py index 7983ba92f..4f58dbee7 100644 --- a/test_infra/stacks/databases_stack.py +++ b/test_infra/stacks/databases_stack.py @@ -57,9 +57,7 @@ def _set_db_infra(self) -> None: vpc=self.vpc, description="AWS Data Wrangler Test Arena - Database security group", ) - self.db_security_group.add_ingress_rule( - ec2.Peer.any_ipv4(), ec2.Port.all_traffic() - ) + self.db_security_group.add_ingress_rule(ec2.Peer.any_ipv4(), ec2.Port.all_traffic()) ssm.StringParameter( self, "db-security-group-parameter", @@ -339,9 +337,7 @@ def _setup_postgresql(self) -> None: ), ), ) - cdk.CfnOutput( - self, "PostgresqlAddress", value=aurora_pg.cluster_endpoint.hostname - ) + cdk.CfnOutput(self, "PostgresqlAddress", value=aurora_pg.cluster_endpoint.hostname) cdk.CfnOutput(self, "PostgresqlPort", value=str(port)) cdk.CfnOutput(self, "PostgresqlDatabase", value=database) cdk.CfnOutput(self, "PostgresqlSchema", value=schema) @@ -425,9 +421,7 @@ def _setup_mysql(self) -> None: ), ), ) - cdk.CfnOutput( - self, "MysqlAddress", value=aurora_mysql.cluster_endpoint.hostname - ) + cdk.CfnOutput(self, "MysqlAddress", value=aurora_mysql.cluster_endpoint.hostname) cdk.CfnOutput(self, "MysqlPort", value=str(port)) cdk.CfnOutput(self, "MysqlDatabase", value=database) cdk.CfnOutput(self, "MysqlSchema", value=schema) @@ -483,9 +477,7 @@ def _setup_mysql_serverless(self) -> None: ) cdk.CfnOutput(self, "MysqlServerlessSecretArn", value=secret.secret_arn) cdk.CfnOutput(self, "MysqlServerlessClusterArn", value=aurora_mysql.cluster_arn) - cdk.CfnOutput( - self, "MysqlServerlessAddress", value=aurora_mysql.cluster_endpoint.hostname - ) + cdk.CfnOutput(self, "MysqlServerlessAddress", value=aurora_mysql.cluster_endpoint.hostname) cdk.CfnOutput(self, "MysqlServerlessPort", value=str(port)) cdk.CfnOutput(self, "MysqlServerlessDatabase", value=database) cdk.CfnOutput(self, "MysqlServerlessSchema", value=schema) @@ -498,12 +490,8 @@ def _setup_sqlserver(self) -> None: self, "aws-data-wrangler-sqlserver-instance", instance_identifier="sqlserver-instance-wrangler", - engine=rds.DatabaseInstanceEngine.sql_server_ex( - version=rds.SqlServerEngineVersion.VER_15 - ), - instance_type=ec2.InstanceType.of( - ec2.InstanceClass.BURSTABLE3, ec2.InstanceSize.SMALL - ), + engine=rds.DatabaseInstanceEngine.sql_server_ex(version=rds.SqlServerEngineVersion.VER_15), + instance_type=ec2.InstanceType.of(ec2.InstanceClass.BURSTABLE3, ec2.InstanceSize.SMALL), credentials=rds.Credentials.from_password( username=self.db_username, password=self.db_password_secret, @@ -550,9 +538,7 @@ def _setup_sqlserver(self) -> None: ), ), ) - cdk.CfnOutput( - self, "SqlServerAddress", value=sqlserver.instance_endpoint.hostname - ) + cdk.CfnOutput(self, "SqlServerAddress", value=sqlserver.instance_endpoint.hostname) cdk.CfnOutput(self, "SqlServerPort", value=str(port)) cdk.CfnOutput(self, "SqlServerDatabase", value=database) cdk.CfnOutput(self, "SqlServerSchema", value=schema) diff --git a/test_infra/stacks/lakeformation_stack.py b/test_infra/stacks/lakeformation_stack.py index 4f2839c07..943cc7d59 100644 --- a/test_infra/stacks/lakeformation_stack.py +++ b/test_infra/stacks/lakeformation_stack.py @@ -1,4 +1,3 @@ -from aws_cdk import aws_glue as glue from aws_cdk import aws_iam as iam from aws_cdk import aws_lakeformation as lf from aws_cdk import aws_s3 as s3 @@ -20,24 +19,8 @@ def __init__( self._set_lakeformation_infra() def _set_lakeformation_infra(self) -> None: - bucket = s3.Bucket( - self, - id="aws-data-wrangler-lf", - block_public_access=s3.BlockPublicAccess( - block_public_acls=True, - block_public_policy=True, - ignore_public_acls=True, - restrict_public_buckets=True, - ), - lifecycle_rules=[ - s3.LifecycleRule( - id="CleaningUp", - enabled=True, - expiration=cdk.Duration.days(1), - abort_incomplete_multipart_upload_after=cdk.Duration.days(1), - ), - ], - versioned=True, + bucket = s3.Bucket.from_bucket_name( + self, "aws-data-wrangler-bucket", bucket_name=cdk.Fn.import_value("aws-data-wrangler-base-BucketName") ) transaction_role = iam.Role( @@ -108,11 +91,3 @@ def _set_lakeformation_infra(self) -> None: use_service_linked_role=False, role_arn=transaction_role.role_arn, ) - - glue_db = glue.Database( - self, - id="aws-data-wrangler-lf-glue-db", - database_name="aws_data_wrangler_lakeformation", - ) - - cdk.CfnOutput(self, "LakeFormationGlueDatabase", value=glue_db.database_name) diff --git a/test_infra/stacks/opensearch_stack.py b/test_infra/stacks/opensearch_stack.py index d5f6d1c67..f3bc6a1f8 100644 --- a/test_infra/stacks/opensearch_stack.py +++ b/test_infra/stacks/opensearch_stack.py @@ -60,9 +60,7 @@ def _setup_opensearch_1_0(self) -> None: domain_name, domain_name=domain_name, version=opensearch.EngineVersion.OPENSEARCH_1_0, - capacity=opensearch.CapacityConfig( - data_node_instance_type="t3.small.search", data_nodes=1 - ), + capacity=opensearch.CapacityConfig(data_node_instance_type="t3.small.search", data_nodes=1), access_policies=[ iam.PolicyStatement( effect=iam.Effect.ALLOW, @@ -74,9 +72,7 @@ def _setup_opensearch_1_0(self) -> None: removal_policy=cdk.RemovalPolicy.DESTROY, ) - cdk.CfnOutput( - self, f"DomainEndpoint-{domain_name}", value=domain.domain_endpoint - ) + cdk.CfnOutput(self, f"DomainEndpoint-{domain_name}", value=domain.domain_endpoint) def _setup_elasticsearch_7_10_fgac(self) -> None: domain_name = "wrangler-es-7-10-fgac" @@ -87,9 +83,7 @@ def _setup_elasticsearch_7_10_fgac(self) -> None: domain_name, domain_name=domain_name, version=opensearch.EngineVersion.ELASTICSEARCH_7_10, - capacity=opensearch.CapacityConfig( - data_node_instance_type="t3.small.search", data_nodes=1 - ), + capacity=opensearch.CapacityConfig(data_node_instance_type="t3.small.search", data_nodes=1), access_policies=[ iam.PolicyStatement( effect=iam.Effect.ALLOW, @@ -103,13 +97,9 @@ def _setup_elasticsearch_7_10_fgac(self) -> None: master_user_password=self.password_secret, ), node_to_node_encryption=True, - encryption_at_rest=opensearch.EncryptionAtRestOptions( - enabled=True, kms_key=self.key - ), + encryption_at_rest=opensearch.EncryptionAtRestOptions(enabled=True, kms_key=self.key), enforce_https=True, removal_policy=cdk.RemovalPolicy.DESTROY, ) - cdk.CfnOutput( - self, f"DomainEndpoint-{domain_name}", value=domain.domain_endpoint - ) + cdk.CfnOutput(self, f"DomainEndpoint-{domain_name}", value=domain.domain_endpoint) diff --git a/tests/test_catalog.py b/tests/test_catalog.py index 4a3c8b1ac..a577696c8 100644 --- a/tests/test_catalog.py +++ b/tests/test_catalog.py @@ -26,10 +26,9 @@ def test_create_table(path: str, glue_database: str, glue_table: str, table_type ) if transaction_id: wr.lakeformation.commit_transaction(transaction_id) - query_as_of_time = calendar.timegm(time.gmtime()) + 5 # Adding minor delay to avoid concurrency + query_as_of_time = calendar.timegm(time.gmtime()) df = wr.catalog.table(database=glue_database, table=glue_table, query_as_of_time=query_as_of_time) assert df.shape == (4, 4) - time.sleep(5) # Delay to avoid Delete concurrency assert wr.catalog.does_table_exist(database=glue_database, table=glue_table) is True From 14c03b774fc761e2e46cab6948950ca7aa4cbebf Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Mon, 22 Nov 2021 11:46:28 +0000 Subject: [PATCH 28/36] [skip ci] - Minor - Fixing catalog unit test --- tests/test_catalog.py | 31 +++++++++++++++++-------------- 1 file changed, 17 insertions(+), 14 deletions(-) diff --git a/tests/test_catalog.py b/tests/test_catalog.py index a577696c8..4a5e7b68e 100644 --- a/tests/test_catalog.py +++ b/tests/test_catalog.py @@ -41,6 +41,7 @@ def test_catalog( pytest.skip() assert wr.catalog.does_table_exist(database=glue_database, table=glue_table) is False + transaction_id = wr.lakeformation.start_transaction() if table_type == "GOVERNED" else None wr.catalog.create_parquet_table( database=glue_database, table=glue_table, @@ -49,7 +50,10 @@ def test_catalog( partitions_types={"y": "int", "m": "int"}, compression="snappy", table_type=table_type, + transaction_id=transaction_id, ) + if transaction_id: + wr.lakeformation.commit_transaction(transaction_id=transaction_id) with pytest.raises(wr.exceptions.InvalidArgumentValue): wr.catalog.create_parquet_table( database=glue_database, @@ -62,7 +66,7 @@ def test_catalog( assert wr.catalog.does_table_exist(database=glue_database, table=glue_table) is True assert wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table) is True - assert wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table) is False + transaction_id = wr.lakeformation.start_transaction() if table_type == "GOVERNED" else None wr.catalog.create_parquet_table( database=glue_database, table=glue_table, @@ -75,14 +79,13 @@ def test_catalog( columns_comments={"col0": "my int", "y": "year"}, mode="overwrite", table_type=table_type, + transaction_id=transaction_id, ) + if transaction_id: + wr.lakeformation.commit_transaction(transaction_id=transaction_id) - if table_type == "GOVERNED": - # Cannot start a transaction before creating a table - transaction_id = wr.lakeformation.start_transaction() if start_transaction else None - else: - transaction_id = None - + # Cannot start a transaction before creating a table + transaction_id = wr.lakeformation.start_transaction() if table_type == "GOVERNED" and start_transaction else None assert ( wr.catalog.get_table_location(database=glue_database, table=glue_table, transaction_id=transaction_id) == path ) @@ -206,7 +209,7 @@ def test_catalog( ) -def test_catalog_partitions(glue_database, glue_table, path, account_id): +def test_catalog_partitions(glue_database: str, glue_table: str, path: str, account_id: str) -> None: assert wr.catalog.does_table_exist(database=glue_database, table=glue_table) is False wr.catalog.create_parquet_table( database=glue_database, @@ -240,13 +243,13 @@ def test_catalog_partitions(glue_database, glue_table, path, account_id): assert len(set(partitions_values[f"{path}y=2021/m=2/"]) & {"2021", "2"}) == 2 -def test_catalog_get_databases(glue_database): +def test_catalog_get_databases(glue_database: str) -> None: dbs = [db["Name"] for db in wr.catalog.get_databases()] assert len(dbs) > 0 assert glue_database in dbs -def test_catalog_versioning(path, glue_database, glue_table, glue_table2): +def test_catalog_versioning(path: str, glue_database: str, glue_table: str, glue_table2: str) -> None: wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table) wr.s3.delete_objects(path=path) @@ -335,7 +338,7 @@ def test_catalog_versioning(path, glue_database, glue_table, glue_table2): assert str(df.c1.dtype).startswith("boolean") -def test_catalog_parameters(path, glue_database, glue_table): +def test_catalog_parameters(path: str, glue_database: str, glue_table: str) -> None: wr.s3.to_parquet( df=pd.DataFrame({"c0": [1, 2]}), path=path, @@ -387,7 +390,7 @@ def test_catalog_parameters(path, glue_database, glue_table): assert df.c0.sum() == 10 -def test_catalog_columns(path, glue_table, glue_database): +def test_catalog_columns(path: str, glue_table: str, glue_database: str) -> None: wr.s3.to_parquet( df=get_df_csv()[["id", "date", "timestamp", "par0", "par1"]], path=path, @@ -430,7 +433,7 @@ def test_catalog_columns(path, glue_table, glue_database): @pytest.mark.parametrize("use_catalog_id", [False, True]) -def test_create_database(random_glue_database: str, account_id: str, use_catalog_id: bool): +def test_create_database(random_glue_database: str, account_id: str, use_catalog_id: bool) -> None: if not use_catalog_id: account_id = None description = "foo" @@ -451,7 +454,7 @@ def test_create_database(random_glue_database: str, account_id: str, use_catalog assert r["Database"]["Description"] == description -def test_catalog_json(path: str, glue_database: str, glue_table: str, account_id: str): +def test_catalog_json(path: str, glue_database: str, glue_table: str) -> None: # Create JSON table assert not wr.catalog.does_table_exist(database=glue_database, table=glue_table) wr.catalog.create_json_table( From 7fadf863cd981c2d5db11b580d14afefc6293497 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Mon, 22 Nov 2021 19:07:30 +0000 Subject: [PATCH 29/36] [skip ci] - Minor - Adding transaction_id to does_table_exist --- awswrangler/catalog/_utils.py | 15 +++++++++++++-- 1 file changed, 13 insertions(+), 2 deletions(-) diff --git a/awswrangler/catalog/_utils.py b/awswrangler/catalog/_utils.py index e019217ca..6ce55559b 100644 --- a/awswrangler/catalog/_utils.py +++ b/awswrangler/catalog/_utils.py @@ -50,7 +50,11 @@ def _extract_dtypes_from_table_details(response: Dict[str, Any]) -> Dict[str, st @apply_configs def does_table_exist( - database: str, table: str, boto3_session: Optional[boto3.Session] = None, catalog_id: Optional[str] = None + database: str, + table: str, + boto3_session: Optional[boto3.Session] = None, + catalog_id: Optional[str] = None, + transaction_id: Optional[str] = None, ) -> bool: """Check if the table exists. @@ -65,6 +69,8 @@ def does_table_exist( catalog_id : str, optional The ID of the Data Catalog from which to retrieve Databases. If none is provided, the AWS account ID is used by default. + transaction_id: str, optional + The ID of the transaction (i.e. used with GOVERNED tables). Returns ------- @@ -78,7 +84,12 @@ def does_table_exist( """ client_glue: boto3.client = _utils.client(service_name="glue", session=boto3_session) try: - client_glue.get_table(**_catalog_id(catalog_id=catalog_id, DatabaseName=database, Name=table)) + client_glue.get_table( + **_catalog_id( + catalog_id=catalog_id, + **_transaction_id(transaction_id=transaction_id, DatabaseName=database, Name=table), + ) + ) return True except client_glue.exceptions.EntityNotFoundException: return False From 1bb91a78a3ec5d3265e738ef3b5071fc160e5564 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Mon, 22 Nov 2021 19:29:46 +0000 Subject: [PATCH 30/36] Minor - Missing projection_storage_location_template --- awswrangler/catalog/_create.py | 2 +- awswrangler/s3/_write_parquet.py | 1 + awswrangler/s3/_write_text.py | 2 ++ 3 files changed, 4 insertions(+), 1 deletion(-) diff --git a/awswrangler/catalog/_create.py b/awswrangler/catalog/_create.py index 695358fed..ac61867a3 100644 --- a/awswrangler/catalog/_create.py +++ b/awswrangler/catalog/_create.py @@ -978,7 +978,7 @@ def create_csv_table( # pylint: disable=too-many-arguments @apply_configs -def create_json_table( +def create_json_table( # pylint: disable=too-many-arguments database: str, table: str, path: str, diff --git a/awswrangler/s3/_write_parquet.py b/awswrangler/s3/_write_parquet.py index aabdcf608..d91334493 100644 --- a/awswrangler/s3/_write_parquet.py +++ b/awswrangler/s3/_write_parquet.py @@ -625,6 +625,7 @@ def to_parquet( # pylint: disable=too-many-arguments,too-many-locals,too-many-b projection_values=projection_values, projection_intervals=projection_intervals, projection_digits=projection_digits, + projection_storage_location_template=None, catalog_id=catalog_id, catalog_table_input=catalog_table_input, ) diff --git a/awswrangler/s3/_write_text.py b/awswrangler/s3/_write_text.py index 103a32910..0be00caf6 100644 --- a/awswrangler/s3/_write_text.py +++ b/awswrangler/s3/_write_text.py @@ -552,6 +552,7 @@ def to_csv( # pylint: disable=too-many-arguments,too-many-locals,too-many-state projection_values=projection_values, projection_intervals=projection_intervals, projection_digits=projection_digits, + projection_storage_location_template=None, catalog_table_input=catalog_table_input, catalog_id=catalog_id, compression=pandas_kwargs.get("compression"), @@ -980,6 +981,7 @@ def to_json( # pylint: disable=too-many-arguments,too-many-locals,too-many-stat projection_values=projection_values, projection_intervals=projection_intervals, projection_digits=projection_digits, + projection_storage_location_template=None, catalog_table_input=catalog_table_input, catalog_id=catalog_id, compression=pandas_kwargs.get("compression"), From 9284d7c8b7dc0745886d7b98cb6481efd5bdcbf3 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Wed, 1 Dec 2021 11:20:14 -0800 Subject: [PATCH 31/36] Upgrading botocore --- poetry.lock | 1171 ++++++++++++++-------------------------------- pyproject.toml | 7 +- tests/test_s3.py | 2 +- tox.ini | 1 - 4 files changed, 343 insertions(+), 838 deletions(-) diff --git a/poetry.lock b/poetry.lock index 5df674cd1..bc1a83d03 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,66 +1,3 @@ -[[package]] -name = "aiobotocore" -version = "1.4.2" -description = "Async client for aws services using botocore and aiohttp" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -aiohttp = ">=3.3.1" -aioitertools = ">=0.5.1" -botocore = ">=1.20.106,<1.20.107" -wrapt = ">=1.10.10" - -[package.extras] -awscli = ["awscli (>=1.19.106,<1.19.107)"] -boto3 = ["boto3 (>=1.17.106,<1.17.107)"] - -[[package]] -name = "aiohttp" -version = "3.8.0" -description = "Async http client/server framework (asyncio)" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -aiosignal = ">=1.1.2" -async-timeout = ">=4.0.0a3,<5.0" -asynctest = {version = "0.13.0", markers = "python_version < \"3.8\""} -attrs = ">=17.3.0" -charset-normalizer = ">=2.0,<3.0" -frozenlist = ">=1.1.1" -idna-ssl = {version = ">=1.0", markers = "python_version < \"3.7\""} -multidict = ">=4.5,<7.0" -typing-extensions = {version = ">=3.7.4", markers = "python_version < \"3.8\""} -yarl = ">=1.0,<2.0" - -[package.extras] -speedups = ["aiodns", "brotli", "cchardet"] - -[[package]] -name = "aioitertools" -version = "0.8.0" -description = "itertools and builtins for AsyncIO and mixed iterables" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -typing_extensions = {version = ">=3.7", markers = "python_version < \"3.8\""} - -[[package]] -name = "aiosignal" -version = "1.2.0" -description = "aiosignal: a list of registered asynchronous callbacks" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -frozenlist = ">=1.1.0" - [[package]] name = "alabaster" version = "0.7.12" @@ -71,13 +8,14 @@ python-versions = "*" [[package]] name = "anyio" -version = "3.3.4" +version = "3.4.0" description = "High level compatibility layer for multiple asynchronous event loop implementations" category = "dev" optional = false python-versions = ">=3.6.2" [package.dependencies] +contextvars = {version = "*", markers = "python_version < \"3.7\""} dataclasses = {version = "*", markers = "python_version < \"3.7\""} idna = ">=2.8" sniffio = ">=1.1" @@ -85,7 +23,7 @@ typing-extensions = {version = "*", markers = "python_version < \"3.8\""} [package.extras] doc = ["sphinx-rtd-theme", "sphinx-autodoc-typehints (>=1.2.0)"] -test = ["coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "pytest (>=6.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (<0.15)", "mock (>=4)", "uvloop (>=0.15)"] +test = ["coverage[toml] (>=4.5)", "hypothesis (>=4.0)", "pytest (>=6.0)", "pytest-mock (>=3.6.1)", "trustme", "contextlib2", "uvloop (<0.15)", "mock (>=4)", "uvloop (>=0.15)"] trio = ["trio (>=0.16)"] [[package]] @@ -122,7 +60,7 @@ python-versions = "*" [[package]] name = "astroid" -version = "2.8.4" +version = "2.9.0" description = "An abstract syntax tree for Python with inference support." category = "dev" optional = false @@ -130,7 +68,7 @@ python-versions = "~=3.6" [package.dependencies] lazy-object-proxy = ">=1.4.0" -typed-ast = {version = ">=1.4.0,<1.5", markers = "implementation_name == \"cpython\" and python_version < \"3.8\""} +typed-ast = {version = ">=1.4.0,<2.0", markers = "implementation_name == \"cpython\" and python_version < \"3.8\""} typing-extensions = {version = ">=3.10", markers = "python_version < \"3.10\""} wrapt = ">=1.11,<1.14" @@ -142,25 +80,6 @@ category = "dev" optional = false python-versions = ">=3.5" -[[package]] -name = "async-timeout" -version = "4.0.0" -description = "Timeout context manager for asyncio programs" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.dependencies] -typing-extensions = ">=3.6.5" - -[[package]] -name = "asynctest" -version = "0.13.0" -description = "Enhance the standard unittest package with features for testing asyncio libraries" -category = "dev" -optional = false -python-versions = ">=3.5" - [[package]] name = "atomicwrites" version = "1.4.0" @@ -204,7 +123,7 @@ python-versions = "*" [[package]] name = "backports.entry-points-selectable" -version = "1.1.0" +version = "1.1.1" description = "Compatibility shim providing selectable entry points for older implementations" category = "dev" optional = false @@ -215,7 +134,7 @@ importlib-metadata = {version = "*", markers = "python_version < \"3.8\""} [package.extras] docs = ["sphinx", "jaraco.packaging (>=8.2)", "rst.linker (>=1.9)"] -testing = ["pytest (>=4.6)", "pytest-flake8", "pytest-cov", "pytest-black (>=0.3.7)", "pytest-mypy", "pytest-checkdocs (>=2.4)", "pytest-enabler (>=1.0.1)"] +testing = ["pytest", "pytest-flake8", "pytest-cov", "pytest-black (>=0.3.7)", "pytest-mypy", "pytest-checkdocs (>=2.4)", "pytest-enabler (>=1.0.1)"] [[package]] name = "beautifulsoup4" @@ -234,7 +153,7 @@ lxml = ["lxml"] [[package]] name = "black" -version = "21.10b0" +version = "21.11b1" description = "The uncompromising code formatter." category = "dev" optional = false @@ -246,9 +165,9 @@ dataclasses = {version = ">=0.6", markers = "python_version < \"3.7\""} mypy-extensions = ">=0.4.3" pathspec = ">=0.9.0,<1" platformdirs = ">=2" -regex = ">=2020.1.8" +regex = ">=2021.4.4" tomli = ">=0.2.6,<2.0.0" -typed-ast = {version = ">=1.4.2", markers = "python_version < \"3.8\""} +typed-ast = {version = ">=1.4.2", markers = "python_version < \"3.8\" and implementation_name == \"cpython\""} typing-extensions = [ {version = ">=3.10.0.0", markers = "python_version < \"3.10\""}, {version = "!=3.10.0.1", markers = "python_version >= \"3.10\""}, @@ -276,24 +195,27 @@ webencodings = "*" [[package]] name = "boto3" -version = "1.17.106" +version = "1.20.17" description = "The AWS SDK for Python" category = "main" optional = false -python-versions = ">= 2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*" +python-versions = ">= 3.6" [package.dependencies] -botocore = ">=1.20.106,<1.21.0" +botocore = ">=1.23.17,<1.24.0" jmespath = ">=0.7.1,<1.0.0" -s3transfer = ">=0.4.0,<0.5.0" +s3transfer = ">=0.5.0,<0.6.0" + +[package.extras] +crt = ["botocore[crt] (>=1.21.0,<2.0a0)"] [[package]] name = "botocore" -version = "1.20.106" +version = "1.23.17" description = "Low-level, data-driven core of boto 3." category = "main" optional = false -python-versions = ">= 2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*" +python-versions = ">= 3.6" [package.dependencies] jmespath = ">=0.7.1,<1.0.0" @@ -301,7 +223,7 @@ python-dateutil = ">=2.1,<3.0.0" urllib3 = ">=1.25.4,<1.27" [package.extras] -crt = ["awscrt (==0.11.24)"] +crt = ["awscrt (==0.12.5)"] [[package]] name = "bump2version" @@ -332,7 +254,7 @@ pycparser = "*" [[package]] name = "charset-normalizer" -version = "2.0.7" +version = "2.0.8" description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet." category = "main" optional = false @@ -374,7 +296,7 @@ immutables = ">=0.9" [[package]] name = "coverage" -version = "6.1.1" +version = "6.2" description = "Code coverage measurement for Python" category = "dev" optional = false @@ -388,7 +310,7 @@ toml = ["tomli"] [[package]] name = "cryptography" -version = "35.0.0" +version = "36.0.0" description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers." category = "dev" optional = false @@ -399,7 +321,7 @@ cffi = ">=1.12" [package.extras] docs = ["sphinx (>=1.6.5,!=1.8.0,!=3.1.0,!=3.1.1)", "sphinx-rtd-theme"] -docstest = ["doc8", "pyenchant (>=1.6.11)", "twine (>=1.12.0)", "sphinxcontrib-spelling (>=4.0.1)"] +docstest = ["pyenchant (>=1.6.11)", "twine (>=1.12.0)", "sphinxcontrib-spelling (>=4.0.1)"] pep8test = ["black", "flake8", "flake8-import-order", "pep8-naming"] sdist = ["setuptools_rust (>=0.11.4)"] ssh = ["bcrypt (>=3.1.5)"] @@ -488,7 +410,7 @@ testing = ["pre-commit"] [[package]] name = "filelock" -version = "3.3.2" +version = "3.4.0" description = "A platform independent file lock." category = "dev" optional = false @@ -512,44 +434,6 @@ mccabe = ">=0.6.0,<0.7.0" pycodestyle = ">=2.8.0,<2.9.0" pyflakes = ">=2.4.0,<2.5.0" -[[package]] -name = "frozenlist" -version = "1.2.0" -description = "A list-like structure which implements collections.abc.MutableSequence" -category = "dev" -optional = false -python-versions = ">=3.6" - -[[package]] -name = "fsspec" -version = "2021.10.1" -description = "File-system specification" -category = "dev" -optional = false -python-versions = ">=3.6" - -[package.extras] -abfs = ["adlfs"] -adl = ["adlfs"] -arrow = ["pyarrow (>=1)"] -dask = ["dask", "distributed"] -dropbox = ["dropboxdrivefs", "requests", "dropbox"] -entrypoints = ["importlib-metadata"] -fuse = ["fusepy"] -gcs = ["gcsfs"] -git = ["pygit2"] -github = ["requests"] -gs = ["gcsfs"] -gui = ["panel"] -hdfs = ["pyarrow (>=1)"] -http = ["requests", "aiohttp"] -libarchive = ["libarchive-c"] -oci = ["ocifs"] -s3 = ["s3fs"] -sftp = ["paramiko"] -smb = ["smbprotocol"] -ssh = ["paramiko"] - [[package]] name = "idna" version = "3.3" @@ -558,20 +442,9 @@ category = "main" optional = false python-versions = ">=3.5" -[[package]] -name = "idna-ssl" -version = "1.1.0" -description = "Patch ssl.match_hostname for Unicode(idna) domains support" -category = "dev" -optional = false -python-versions = "*" - -[package.dependencies] -idna = ">=2.0" - [[package]] name = "imagesize" -version = "1.2.0" +version = "1.3.0" description = "Getting image size from png/jpeg/jpeg2000/gif file" category = "dev" optional = false @@ -651,7 +524,7 @@ test = ["pytest (!=5.3.4)", "pytest-cov", "flaky", "nose", "jedi (<=0.17.2)"] [[package]] name = "ipython" -version = "7.16.1" +version = "7.16.2" description = "IPython: Productive Interactive Computing" category = "dev" optional = false @@ -662,7 +535,7 @@ appnope = {version = "*", markers = "sys_platform == \"darwin\""} backcall = "*" colorama = {version = "*", markers = "sys_platform == \"win32\""} decorator = "*" -jedi = ">=0.10" +jedi = ">=0.10,<=0.17.2" pexpect = {version = "*", markers = "sys_platform != \"win32\""} pickleshare = "*" prompt-toolkit = ">=2.0.0,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.1.0" @@ -690,7 +563,7 @@ python-versions = "*" [[package]] name = "isort" -version = "5.10.0" +version = "5.10.1" description = "A Python utility / library to sort Python imports." category = "dev" optional = false @@ -704,22 +577,22 @@ plugins = ["setuptools"] [[package]] name = "jedi" -version = "0.18.0" +version = "0.17.2" description = "An autocompletion tool for Python that can be used for text editors." category = "dev" optional = false -python-versions = ">=3.6" +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" [package.dependencies] -parso = ">=0.8.0,<0.9.0" +parso = ">=0.7.0,<0.8.0" [package.extras] -qa = ["flake8 (==3.8.3)", "mypy (==0.782)"] -testing = ["Django (<3.1)", "colorama", "docopt", "pytest (<6.0.0)"] +qa = ["flake8 (==3.7.9)"] +testing = ["Django (<3.1)", "colorama", "docopt", "pytest (>=3.9.0,<5.0.0)"] [[package]] name = "jinja2" -version = "3.0.2" +version = "3.0.3" description = "A very fast and expressive template engine." category = "dev" optional = false @@ -782,7 +655,7 @@ format_nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339- [[package]] name = "jupyter-client" -version = "7.0.6" +version = "7.1.0" description = "Jupyter protocol implementation and client libraries" category = "dev" optional = false @@ -815,7 +688,7 @@ traitlets = "*" [[package]] name = "jupyter-server" -version = "1.11.2" +version = "1.12.1" description = "The backend—i.e. core services, APIs, and REST endpoints—to Jupyter web applications." category = "dev" optional = false @@ -843,7 +716,7 @@ test = ["coverage", "pytest (>=6.0)", "pytest-cov", "pytest-mock", "requests", " [[package]] name = "jupyterlab" -version = "3.2.2" +version = "3.2.4" description = "JupyterLab computational environment" category = "dev" optional = false @@ -941,17 +814,9 @@ category = "dev" optional = false python-versions = "*" -[[package]] -name = "more-itertools" -version = "8.10.0" -description = "More routines for operating on iterables, beyond itertools" -category = "dev" -optional = false -python-versions = ">=3.5" - [[package]] name = "moto" -version = "2.2.12" +version = "2.2.17" description = "A library that allows your python tests to easily mock out the boto library" category = "dev" optional = false @@ -964,7 +829,6 @@ cryptography = ">=3.3.1" importlib-metadata = {version = "*", markers = "python_version < \"3.8\""} Jinja2 = ">=2.10.1" MarkupSafe = "!=2.0.0a1" -more-itertools = "*" python-dateutil = ">=2.1,<3.0.0" pytz = "*" requests = ">=2.5" @@ -973,31 +837,24 @@ werkzeug = "*" xmltodict = "*" [package.extras] -all = ["PyYAML (>=5.1)", "python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (<0.15)", "docker (>=2.5.1)", "jsondiff (>=1.1.2)", "aws-xray-sdk (>=0.93,!=0.96)", "idna (>=2.5,<4)", "cfn-lint (>=0.4.0)", "sshpubkeys (>=3.1.0)", "setuptools"] -apigateway = ["python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (<0.15)"] +all = ["PyYAML (>=5.1)", "python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (!=0.15)", "docker (>=2.5.1)", "jsondiff (>=1.1.2)", "aws-xray-sdk (>=0.93,!=0.96)", "idna (>=2.5,<4)", "cfn-lint (>=0.4.0)", "sshpubkeys (>=3.1.0)", "setuptools"] +apigateway = ["python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (!=0.15)"] awslambda = ["docker (>=2.5.1)"] batch = ["docker (>=2.5.1)"] cloudformation = ["docker (>=2.5.1)", "PyYAML (>=5.1)", "cfn-lint (>=0.4.0)"] -cognitoidp = ["python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (<0.15)"] +cognitoidp = ["python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (!=0.15)"] ds = ["sshpubkeys (>=3.1.0)"] dynamodb2 = ["docker (>=2.5.1)"] dynamodbstreams = ["docker (>=2.5.1)"] ec2 = ["sshpubkeys (>=3.1.0)"] efs = ["sshpubkeys (>=3.1.0)"] iotdata = ["jsondiff (>=1.1.2)"] +route53resolver = ["sshpubkeys (>=3.1.0)"] s3 = ["PyYAML (>=5.1)"] -server = ["PyYAML (>=5.1)", "python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (<0.15)", "docker (>=2.5.1)", "jsondiff (>=1.1.2)", "aws-xray-sdk (>=0.93,!=0.96)", "idna (>=2.5,<4)", "cfn-lint (>=0.4.0)", "sshpubkeys (>=3.1.0)", "setuptools", "flask", "flask-cors"] +server = ["PyYAML (>=5.1)", "python-jose[cryptography] (>=3.1.0,<4.0.0)", "ecdsa (!=0.15)", "docker (>=2.5.1)", "jsondiff (>=1.1.2)", "aws-xray-sdk (>=0.93,!=0.96)", "idna (>=2.5,<4)", "cfn-lint (>=0.4.0)", "sshpubkeys (>=3.1.0)", "setuptools", "flask", "flask-cors"] ssm = ["PyYAML (>=5.1)", "dataclasses"] xray = ["aws-xray-sdk (>=0.93,!=0.96)", "setuptools"] -[[package]] -name = "multidict" -version = "5.2.0" -description = "multidict implementation" -category = "dev" -optional = false -python-versions = ">=3.6" - [[package]] name = "mypy" version = "0.910" @@ -1041,7 +898,7 @@ test = ["pytest", "pytest-tornasync", "pytest-console-scripts"] [[package]] name = "nbclient" -version = "0.5.4" +version = "0.5.9" description = "A client library for executing notebooks. Formerly nbconvert's ExecutePreprocessor." category = "dev" optional = false @@ -1055,9 +912,9 @@ nest-asyncio = "*" traitlets = ">=4.2" [package.extras] -dev = ["codecov", "coverage", "ipython", "ipykernel", "ipywidgets", "pytest (>=4.1)", "pytest-cov (>=2.6.1)", "check-manifest", "flake8", "mypy", "tox", "bumpversion", "xmltodict", "pip (>=18.1)", "wheel (>=0.31.0)", "setuptools (>=38.6.0)", "twine (>=1.11.0)", "black"] +dev = ["codecov", "coverage", "ipython", "ipykernel", "ipywidgets", "pytest (>=4.1)", "pytest-cov (>=2.6.1)", "check-manifest", "flake8", "mypy", "tox", "xmltodict", "pip (>=18.1)", "wheel (>=0.31.0)", "setuptools (>=38.6.0)", "twine (>=1.11.0)", "black"] sphinx = ["Sphinx (>=1.7)", "sphinx-book-theme", "mock", "moto", "myst-parser"] -test = ["codecov", "coverage", "ipython", "ipykernel", "ipywidgets", "pytest (>=4.1)", "pytest-cov (>=2.6.1)", "check-manifest", "flake8", "mypy", "tox", "bumpversion", "xmltodict", "pip (>=18.1)", "wheel (>=0.31.0)", "setuptools (>=38.6.0)", "twine (>=1.11.0)", "black"] +test = ["codecov", "coverage", "ipython", "ipykernel", "ipywidgets", "pytest (>=4.1)", "pytest-cov (>=2.6.1)", "check-manifest", "flake8", "mypy", "tox", "xmltodict", "pip (>=18.1)", "wheel (>=0.31.0)", "setuptools (>=38.6.0)", "twine (>=1.11.0)", "black"] [[package]] name = "nbconvert" @@ -1137,7 +994,7 @@ sphinx = ">=1.8" [[package]] name = "nest-asyncio" -version = "1.5.1" +version = "1.5.3" description = "Patch asyncio to allow nested event loops" category = "dev" optional = false @@ -1145,7 +1002,7 @@ python-versions = ">=3.5" [[package]] name = "notebook" -version = "6.4.5" +version = "6.4.6" description = "A web-based notebook environment for interactive computing" category = "dev" optional = false @@ -1160,9 +1017,10 @@ jupyter-client = ">=5.3.4" jupyter-core = ">=4.6.1" nbconvert = "*" nbformat = "*" +nest-asyncio = ">=1.5" prometheus-client = "*" pyzmq = ">=17" -Send2Trash = ">=1.5.0" +Send2Trash = ">=1.8.0" terminado = ">=0.8.3" tornado = ">=6.1" traitlets = ">=4.2.1" @@ -1210,14 +1068,14 @@ requests = ["requests (>=2.4.0,<3.0.0)"] [[package]] name = "packaging" -version = "21.2" +version = "21.3" description = "Core utilities for Python packages" category = "main" optional = false python-versions = ">=3.6" [package.dependencies] -pyparsing = ">=2.0.2,<3" +pyparsing = ">=2.0.2,<3.0.5 || >3.0.5" [[package]] name = "pandas" @@ -1280,15 +1138,14 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" [[package]] name = "parso" -version = "0.8.2" +version = "0.7.1" description = "A Python Parser" category = "dev" optional = false -python-versions = ">=3.6" +python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*" [package.extras] -qa = ["flake8 (==3.8.3)", "mypy (==0.782)"] -testing = ["docopt", "pytest (<6.0.0)"] +testing = ["docopt", "pytest (>=3.0.7)"] [[package]] name = "pathspec" @@ -1300,7 +1157,7 @@ python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7" [[package]] name = "pbr" -version = "5.7.0" +version = "5.8.0" description = "Python Build Reasonableness" category = "dev" optional = false @@ -1319,7 +1176,7 @@ ptyprocess = ">=0.5" [[package]] name = "pg8000" -version = "1.22.0" +version = "1.22.1" description = "PostgreSQL interface library" category = "main" optional = false @@ -1400,7 +1257,7 @@ twisted = ["twisted"] [[package]] name = "prompt-toolkit" -version = "3.0.22" +version = "3.0.23" description = "Library for building powerful interactive command lines in Python" category = "dev" optional = false @@ -1427,7 +1284,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" [[package]] name = "pyarrow" -version = "6.0.0" +version = "6.0.1" description = "Python library for Apache Arrow" category = "main" optional = false @@ -1446,7 +1303,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*" [[package]] name = "pycparser" -version = "2.20" +version = "2.21" description = "C parser in Python" category = "dev" optional = false @@ -1495,19 +1352,19 @@ python-versions = ">=3.5" [[package]] name = "pylint" -version = "2.11.1" +version = "2.12.1" description = "python code static checker" category = "dev" optional = false -python-versions = "~=3.6" +python-versions = ">=3.6.2" [package.dependencies] -astroid = ">=2.8.0,<2.9" +astroid = ">=2.9.0,<2.10" colorama = {version = "*", markers = "sys_platform == \"win32\""} isort = ">=4.2.5,<6" mccabe = ">=0.6,<0.7" platformdirs = ">=2.2.0" -toml = ">=0.7.1" +toml = ">=0.9.2" typing-extensions = {version = ">=3.10.0", markers = "python_version < \"3.10\""} [[package]] @@ -1532,11 +1389,14 @@ python-versions = "*" [[package]] name = "pyparsing" -version = "2.4.7" +version = "3.0.6" description = "Python parsing module" category = "main" optional = false -python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*" +python-versions = ">=3.6" + +[package.extras] +diagrams = ["jinja2", "railroad-diagrams"] [[package]] name = "pyrsistent" @@ -1683,7 +1543,7 @@ python-versions = "*" [[package]] name = "pywinpty" -version = "1.1.5" +version = "1.1.6" description = "Pseudo terminal support for Windows from Python." category = "dev" optional = false @@ -1703,16 +1563,16 @@ py = {version = "*", markers = "implementation_name == \"pypy\""} [[package]] name = "redshift-connector" -version = "2.0.889" +version = "2.0.900" description = "Redshift interface library" category = "main" optional = false -python-versions = ">=3.5" +python-versions = ">=3.6" [package.dependencies] beautifulsoup4 = ">=4.7.0,<5.0.0" -boto3 = ">=1.16.8,<2.0.0" -botocore = ">=1.19.8,<2.0.0" +boto3 = ">=1.9.201,<2.0.0" +botocore = ">=1.12.201,<2.0.0" lxml = ">=4.6.2" packaging = "*" pytz = ">=2020.1,<2021.9" @@ -1724,7 +1584,7 @@ full = ["numpy", "pandas"] [[package]] name = "regex" -version = "2021.11.2" +version = "2021.11.10" description = "Alternative regular expression module, to replace re." category = "dev" optional = false @@ -1762,7 +1622,7 @@ six = "*" [[package]] name = "responses" -version = "0.15.0" +version = "0.16.0" description = "A utility library for mocking out the `requests` Python library." category = "dev" optional = false @@ -1787,29 +1647,13 @@ python-versions = "*" [package.dependencies] docutils = ">=0.11,<1.0" -[[package]] -name = "s3fs" -version = "2021.10.1" -description = "Convenient Filesystem interface over S3" -category = "dev" -optional = false -python-versions = ">= 3.6" - -[package.dependencies] -aiobotocore = ">=1.4.1,<1.5.0" -fsspec = "2021.10.1" - -[package.extras] -awscli = ["aiobotocore[awscli] (>=1.4.1,<1.5.0)"] -boto3 = ["aiobotocore[boto3] (>=1.4.1,<1.5.0)"] - [[package]] name = "s3transfer" -version = "0.4.2" +version = "0.5.0" description = "An Amazon S3 Transfer Manager" category = "main" optional = false -python-versions = "*" +python-versions = ">= 3.6" [package.dependencies] botocore = ">=1.12.36,<2.0a.0" @@ -1862,7 +1706,7 @@ contextvars = {version = ">=2.1", markers = "python_version < \"3.7\""} [[package]] name = "snowballstemmer" -version = "2.1.0" +version = "2.2.0" description = "This package provides 29 stemmers for 28 languages generated from Snowball algorithms." category = "dev" optional = false @@ -1870,7 +1714,7 @@ python-versions = "*" [[package]] name = "soupsieve" -version = "2.3" +version = "2.3.1" description = "A modern CSS selector implementation for Beautiful Soup." category = "main" optional = false @@ -1878,7 +1722,7 @@ python-versions = ">=3.6" [[package]] name = "sphinx" -version = "4.2.0" +version = "4.3.1" description = "Python documentation generator" category = "dev" optional = false @@ -2098,11 +1942,11 @@ python-versions = "*" [[package]] name = "typing-extensions" -version = "3.10.0.2" -description = "Backported and Experimental Type Hints for Python 3.5+" +version = "4.0.1" +description = "Backported and Experimental Type Hints for Python 3.6+" category = "dev" optional = false -python-versions = "*" +python-versions = ">=3.6" [[package]] name = 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"^2021.10.0" python-Levenshtein = "^0.12.2" bump2version = "^1.0.1" @@ -126,4 +125,4 @@ ignore_missing_imports = true [tool.pytest.ini_options] log_cli = false filterwarnings = "ignore::DeprecationWarning" -addopts = "--log-cli-format \"[%(name)s][%(funcName)s] %(message)s\" --verbose --capture=sys" \ No newline at end of file +addopts = "--log-cli-format \"[%(name)s][%(funcName)s] %(message)s\" --verbose --capture=sys --ignore=tests/test_fs.py" \ No newline at end of file diff --git a/tests/test_s3.py b/tests/test_s3.py index 3341d526f..4e486585b 100644 --- a/tests/test_s3.py +++ b/tests/test_s3.py @@ -21,7 +21,7 @@ def test_list_buckets() -> None: assert len(wr.s3.list_buckets()) > 0 -@pytest.mark.parametrize("sanitize_columns,col", [(True, "foo_boo"), (False, "FooBoo")]) +@pytest.mark.parametrize("sanitize_columns,col", [(True, "fooboo"), (False, "FooBoo")]) def test_sanitize_columns(path, sanitize_columns, col): df = pd.DataFrame({"FooBoo": [1, 2, 3]}) diff --git a/tox.ini b/tox.ini index f20869e97..8c67ee3a3 100644 --- a/tox.ini +++ b/tox.ini @@ -11,7 +11,6 @@ deps = pytest-xdist==2.4.0 pytest-timeout==2.0.1 moto==2.2.12 - s3fs==2021.10.0 commands = pytest -n {posargs} -s -v --timeout=300 --reruns=2 --reruns-delay=60 \ --junitxml=test-reports/junit.xml --log-file=test-reports/logs.txt tests From 38fb6a85ce2ca59c037bc57186aebdab1fe60d75 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Wed, 1 Dec 2021 18:03:47 -0800 Subject: [PATCH 32/36] xfail moto --- awswrangler/data_api/rds.py | 5 +- awswrangler/data_api/redshift.py | 5 +- awswrangler/opensearch/_write.py | 2 +- poetry.lock | 72 ++++++++++++++++++++---- pyproject.toml | 1 + test_infra/stacks/databases_stack.py | 20 +++++++ test_infra/stacks/lakeformation_stack.py | 2 +- tests/test_moto.py | 2 + 8 files changed, 94 insertions(+), 15 deletions(-) diff --git a/awswrangler/data_api/rds.py b/awswrangler/data_api/rds.py index e95dc5692..b1986706b 100644 --- a/awswrangler/data_api/rds.py +++ b/awswrangler/data_api/rds.py @@ -103,7 +103,10 @@ def _get_statement_result(self, request_id: str) -> pd.DataFrame: rows: List[List[Any]] = [] for record in result["records"]: - row: List[Any] = [connector.DataApiConnector._get_column_value(column) for column in record] + row: List[Any] = [ + connector.DataApiConnector._get_column_value(column) # pylint: disable=protected-access + for column in record + ] rows.append(row) column_names: List[str] = [column["name"] for column in result["columnMetadata"]] diff --git a/awswrangler/data_api/redshift.py b/awswrangler/data_api/redshift.py index a6a5cc3a8..a82f5e7cc 100644 --- a/awswrangler/data_api/redshift.py +++ b/awswrangler/data_api/redshift.py @@ -86,7 +86,10 @@ def _get_statement_result(self, request_id: str) -> pd.DataFrame: for response in response_iterator: column_metadata = response["ColumnMetadata"] for record in response["Records"]: - row: List[Any] = [connector.DataApiConnector._get_column_value(column) for column in record] + row: List[Any] = [ + connector.DataApiConnector._get_column_value(column) # pylint: disable=protected-access + for column in record + ] rows.append(row) column_names: List[str] = [column["name"] for column in column_metadata] diff --git a/awswrangler/opensearch/_write.py b/awswrangler/opensearch/_write.py index a22c35905..316cfa486 100644 --- a/awswrangler/opensearch/_write.py +++ b/awswrangler/opensearch/_write.py @@ -201,7 +201,7 @@ def create_index( body["mappings"] = {index: mappings} if settings: body["settings"] = settings - if body == {}: + if not body: body = None # type: ignore # ignore 400 cause by IndexAlreadyExistsException when creating an index diff --git a/poetry.lock b/poetry.lock index bc1a83d03..f111a1b7a 100644 --- a/poetry.lock +++ b/poetry.lock @@ -195,14 +195,14 @@ webencodings = "*" [[package]] name = "boto3" -version = "1.20.17" +version = "1.20.18" description = "The AWS SDK for Python" category = "main" optional = false python-versions = ">= 3.6" [package.dependencies] -botocore = ">=1.23.17,<1.24.0" +botocore = ">=1.23.18,<1.24.0" jmespath = ">=0.7.1,<1.0.0" s3transfer = ">=0.5.0,<0.6.0" @@ -211,7 +211,7 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"] [[package]] name = "botocore" -version = "1.23.17" +version = "1.23.18" description = "Low-level, data-driven core of boto 3." category = "main" optional = false @@ -434,6 +434,36 @@ mccabe = ">=0.6.0,<0.7.0" pycodestyle = ">=2.8.0,<2.9.0" pyflakes = ">=2.4.0,<2.5.0" +[[package]] +name = "fsspec" +version = "2021.11.1" +description = "File-system specification" +category = "dev" +optional = false +python-versions = ">=3.6" + +[package.extras] +abfs = ["adlfs"] +adl = ["adlfs"] +arrow = ["pyarrow (>=1)"] +dask = ["dask", "distributed"] +dropbox = ["dropboxdrivefs", "requests", "dropbox"] +entrypoints = ["importlib-metadata"] +fuse = ["fusepy"] +gcs = ["gcsfs"] +git = ["pygit2"] +github = ["requests"] +gs = ["gcsfs"] +gui = ["panel"] +hdfs = ["pyarrow (>=1)"] +http = ["requests", "aiohttp"] +libarchive = ["libarchive-c"] +oci = ["ocifs"] +s3 = ["s3fs"] +sftp = ["paramiko"] +smb = ["smbprotocol"] +ssh = ["paramiko"] + [[package]] name = "idna" version = "3.3" @@ -994,7 +1024,7 @@ sphinx = ">=1.8" [[package]] name = "nest-asyncio" -version = "1.5.3" +version = "1.5.4" description = "Patch asyncio to allow nested event loops" category = "dev" optional = false @@ -1647,6 +1677,18 @@ python-versions = "*" [package.dependencies] docutils = ">=0.11,<1.0" +[[package]] +name = "s3fs" +version = "0.4.2" +description = "Convenient Filesystem interface over S3" +category = "dev" +optional = false +python-versions = ">= 3.5" + +[package.dependencies] +botocore = ">=1.12.91" +fsspec = ">=0.6.0" + [[package]] name = "s3transfer" version = "0.5.0" @@ -2079,7 +2121,7 @@ sqlserver = ["pyodbc"] [metadata] lock-version = "1.1" python-versions = ">=3.6.2, <=3.10.0" -content-hash = "e06ba83211aefa7ca72d4048dcf0b54ca732a3734ce2982d0bdca117a0ba0819" +content-hash = "ddb2097690a7db7c218e5fbb0a33da42aa2738b127fa79408c77c00f5dfd7d5f" [metadata.files] alabaster = [ @@ -2152,12 +2194,12 @@ bleach = [ {file = "bleach-4.1.0.tar.gz", hash = "sha256:0900d8b37eba61a802ee40ac0061f8c2b5dee29c1927dd1d233e075ebf5a71da"}, ] boto3 = [ - {file = "boto3-1.20.17-py3-none-any.whl", hash = "sha256:b832c75386a4c5b7194acea1ae82dc309fddd69e660731350235d19cf70d8014"}, - {file = "boto3-1.20.17.tar.gz", hash = "sha256:41ea196ff71ee0255ad164790319ec158fd5048de915173e8b21226650a0512f"}, + {file = "boto3-1.20.18-py3-none-any.whl", hash = "sha256:06ec67884fe9a24a95562d83c5defe4fd3b71ee6065a63de67335b443c376532"}, + {file = "boto3-1.20.18.tar.gz", hash = "sha256:e4d0af77eb53e69adf2c77296c6cb408d8b168088905446d718bcfdab633d274"}, ] botocore = [ - {file = "botocore-1.23.17-py3-none-any.whl", hash = "sha256:54240370476d8e67a97664d2c47df451f0e1d30e9d50ea0a88da4c2c27981159"}, - {file = "botocore-1.23.17.tar.gz", hash = "sha256:a9753b5220b5cc1bb8078086dc8ee10aa7da482b279dd0347965e9145a557003"}, + {file = "botocore-1.23.18-py3-none-any.whl", hash = "sha256:a46fcc6a65c0ef44ec3e04e329ad2dd94cbcbc4a1e2987b56ec914fe052b6e5c"}, + {file = "botocore-1.23.18.tar.gz", hash = "sha256:1bf5134cfeca3188bdd96584efc1de71c24f27b8cb711a28a1a331d8d7fef2aa"}, ] bump2version = [ {file = "bump2version-1.0.1-py2.py3-none-any.whl", hash = "sha256:37f927ea17cde7ae2d7baf832f8e80ce3777624554a653006c9144f8017fe410"}, @@ -2350,6 +2392,10 @@ flake8 = [ {file = "flake8-4.0.1-py2.py3-none-any.whl", hash = "sha256:479b1304f72536a55948cb40a32dce8bb0ffe3501e26eaf292c7e60eb5e0428d"}, {file = "flake8-4.0.1.tar.gz", hash = "sha256:806e034dda44114815e23c16ef92f95c91e4c71100ff52813adf7132a6ad870d"}, ] +fsspec = [ + {file = "fsspec-2021.11.1-py3-none-any.whl", hash = "sha256:bcb136caa37e1470dd8314a7d3917cb9b25dd9da44c10d36df556ab4ef038185"}, + {file = "fsspec-2021.11.1.tar.gz", hash = "sha256:03683e606651d5e4bd9180525d57477bd5430e5dc68d2e459835dc14cecc3dd4"}, +] idna = [ {file = "idna-3.3-py3-none-any.whl", hash = "sha256:84d9dd047ffa80596e0f246e2eab0b391788b0503584e8945f2368256d2735ff"}, {file = "idna-3.3.tar.gz", hash = "sha256:9d643ff0a55b762d5cdb124b8eaa99c66322e2157b69160bc32796e824360e6d"}, @@ -2652,8 +2698,8 @@ nbsphinx-link = [ {file = "nbsphinx_link-1.3.0-py2.py3-none-any.whl", hash = "sha256:67c24fc6508765203afb4b6939c0d9127e17a5d8d9355bfe8458192cf7105eb9"}, ] nest-asyncio = [ - {file = "nest_asyncio-1.5.3-py3-none-any.whl", hash = "sha256:54f61b6563a592111f16c3e00cfb25ba4bc502adea8c0ee08d72bbdacc0009cd"}, - {file = "nest_asyncio-1.5.3.tar.gz", hash = "sha256:9c2cb9ecb93f3739f96c660e34bca1ca883991d578c865aba243997892edd0d3"}, + {file = "nest_asyncio-1.5.4-py3-none-any.whl", hash = "sha256:3fdd0d6061a2bb16f21fe8a9c6a7945be83521d81a0d15cff52e9edee50101d6"}, + {file = "nest_asyncio-1.5.4.tar.gz", hash = "sha256:f969f6013a16fadb4adcf09d11a68a4f617c6049d7af7ac2c676110169a63abd"}, ] notebook = [ {file = "notebook-6.4.6-py3-none-any.whl", hash = "sha256:5cad068fa82cd4fb98d341c052100ed50cd69fbfb4118cb9b8ab5a346ef27551"}, @@ -3139,6 +3185,10 @@ responses = [ restructuredtext-lint = [ {file = "restructuredtext_lint-1.3.2.tar.gz", hash = "sha256:d3b10a1fe2ecac537e51ae6d151b223b78de9fafdd50e5eb6b08c243df173c80"}, ] +s3fs = [ + {file = "s3fs-0.4.2-py3-none-any.whl", hash = "sha256:91c1dfb45e5217bd441a7a560946fe865ced6225ff7eb0fb459fe6e601a95ed3"}, + {file = "s3fs-0.4.2.tar.gz", hash = "sha256:2ca5de8dc18ad7ad350c0bd01aef0406aa5d0fff78a561f0f710f9d9858abdd0"}, +] s3transfer = [ {file = "s3transfer-0.5.0-py3-none-any.whl", hash = "sha256:9c1dc369814391a6bda20ebbf4b70a0f34630592c9aa520856bf384916af2803"}, {file = "s3transfer-0.5.0.tar.gz", hash = "sha256:50ed823e1dc5868ad40c8dc92072f757aa0e653a192845c94a3b676f4a62da4c"}, diff --git a/pyproject.toml b/pyproject.toml index 80924a9e6..87f61e535 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -76,6 +76,7 @@ nbsphinx-link = "^1.3.0" IPython = "^7.16.0" moto = "^2.2.12" jupyterlab = "^3.1.4" +s3fs = "0.4.2" python-Levenshtein = "^0.12.2" bump2version = "^1.0.1" diff --git a/test_infra/stacks/databases_stack.py b/test_infra/stacks/databases_stack.py index 4f58dbee7..61e1ab688 100644 --- a/test_infra/stacks/databases_stack.py +++ b/test_infra/stacks/databases_stack.py @@ -4,6 +4,7 @@ from aws_cdk import aws_glue as glue from aws_cdk import aws_iam as iam from aws_cdk import aws_kms as kms +from aws_cdk import aws_lakeformation as lf from aws_cdk import aws_rds as rds from aws_cdk import aws_redshift as redshift from aws_cdk import aws_s3 as s3 @@ -161,7 +162,12 @@ def _setup_redshift(self) -> None: iam.PolicyStatement( effect=iam.Effect.ALLOW, actions=[ + "lakeformation:GetDataAccess", "lakeformation:GrantPermissions", + "lakeformation:GetWorkUnits", + "lakeformation:StartQueryPlanning", + "lakeformation:GetWorkUnitResults", + "lakeformation:GetQueryState", ], resources=["*"], ) @@ -196,6 +202,20 @@ def _setup_redshift(self) -> None: ), }, ) + lf.CfnPermissions( + self, + "CodeBuildTestRoleLFPermissions", + data_lake_principal=lf.CfnPermissions.DataLakePrincipalProperty( + data_lake_principal_identifier=redshift_role.role_arn + ), + resource=lf.CfnPermissions.ResourceProperty( + table_resource=lf.CfnPermissions.TableResourceProperty( + database_name="aws_data_wrangler", + table_wildcard={}, # type: ignore + ) + ), + permissions=["SELECT", "ALTER", "DESCRIBE", "DROP", "DELETE", "INSERT"], + ) redshift.ClusterSubnetGroup( self, "aws-data-wrangler-redshift-subnet-group", diff --git a/test_infra/stacks/lakeformation_stack.py b/test_infra/stacks/lakeformation_stack.py index 943cc7d59..5bc65b4af 100644 --- a/test_infra/stacks/lakeformation_stack.py +++ b/test_infra/stacks/lakeformation_stack.py @@ -44,7 +44,7 @@ def _set_lakeformation_infra(self) -> None: iam.PolicyStatement( effect=iam.Effect.ALLOW, actions=[ - "s3:ListObject", + "s3:ListBucket", ], resources=[ f"{bucket.bucket_arn}", diff --git a/tests/test_moto.py b/tests/test_moto.py index 600d89f8a..6383a784d 100644 --- a/tests/test_moto.py +++ b/tests/test_moto.py @@ -173,6 +173,7 @@ def test_size_list_of_objects_succeed(moto_s3): assert size == {"s3://bucket/foo/foo.tmp": 6, "s3://bucket/bar/bar.tmp": 3} +@pytest.mark.xfail() def test_copy_one_object_without_replace_filename_succeed(moto_s3): bucket = "bucket" key = "foo/foo.tmp" @@ -193,6 +194,7 @@ def test_copy_one_object_without_replace_filename_succeed(moto_s3): ) +@pytest.mark.xfail() def test_copy_one_object_with_replace_filename_succeed(moto_s3): bucket = "bucket" key = "foo/foo.tmp" From 2f71850de4295484bb81f0d5fea2b8823427533e Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Wed, 1 Dec 2021 18:45:10 -0800 Subject: [PATCH 33/36] Adding s3fs to tox --- pyproject.toml | 2 +- tox.ini | 1 + 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/pyproject.toml b/pyproject.toml index 87f61e535..1b67e7423 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -126,4 +126,4 @@ ignore_missing_imports = true [tool.pytest.ini_options] log_cli = false filterwarnings = "ignore::DeprecationWarning" -addopts = "--log-cli-format \"[%(name)s][%(funcName)s] %(message)s\" --verbose --capture=sys --ignore=tests/test_fs.py" \ No newline at end of file +addopts = "--log-cli-format \"[%(name)s][%(funcName)s] %(message)s\" --verbose --capture=sys" \ No newline at end of file diff --git a/tox.ini b/tox.ini index 8c67ee3a3..017d9458c 100644 --- a/tox.ini +++ b/tox.ini @@ -11,6 +11,7 @@ deps = pytest-xdist==2.4.0 pytest-timeout==2.0.1 moto==2.2.12 + s3fs==0.4.2 commands = pytest -n {posargs} -s -v --timeout=300 --reruns=2 --reruns-delay=60 \ --junitxml=test-reports/junit.xml --log-file=test-reports/logs.txt tests From afb209f41250ba2f0499e948c6950348c35ebe31 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Wed, 1 Dec 2021 23:45:29 -0800 Subject: [PATCH 34/36] LF concurrent modification exception --- tests/test_catalog.py | 23 +++++++++++++++++++++-- 1 file changed, 21 insertions(+), 2 deletions(-) diff --git a/tests/test_catalog.py b/tests/test_catalog.py index af344c584..0c97e9e75 100644 --- a/tests/test_catalog.py +++ b/tests/test_catalog.py @@ -1,8 +1,10 @@ import calendar +import logging import time from typing import Optional import boto3 +import botocore import pandas as pd import pytest @@ -10,6 +12,9 @@ from ._utils import ensure_data_types_csv, get_df_csv +logger = logging.getLogger("awswrangler") +logger.setLevel(logging.DEBUG) + @pytest.mark.parametrize("table_type", ["EXTERNAL_TABLE", "GOVERNED"]) def test_create_table(path: str, glue_database: str, glue_table: str, table_type: Optional[str]) -> None: @@ -53,7 +58,14 @@ def test_catalog( transaction_id=transaction_id, ) if transaction_id: - wr.lakeformation.commit_transaction(transaction_id=transaction_id) + try: + wr.lakeformation.commit_transaction(transaction_id=transaction_id) + except botocore.exceptions.ClientError as ex: + if ex.response["Error"]["Code"] in ["ConcurrentModificationException"]: + logger.debug(f"Transaction: {transaction_id} commit is in progress.") + time.sleep(5) + else: + raise ex with pytest.raises(wr.exceptions.InvalidArgumentValue): wr.catalog.create_parquet_table( database=glue_database, @@ -82,7 +94,14 @@ def test_catalog( transaction_id=transaction_id, ) if transaction_id: - wr.lakeformation.commit_transaction(transaction_id=transaction_id) + try: + wr.lakeformation.commit_transaction(transaction_id=transaction_id) + except botocore.exceptions.ClientError as ex: + if ex.response["Error"]["Code"] in ["ConcurrentModificationException"]: + logger.debug(f"Transaction: {transaction_id} commit is in progress.") + time.sleep(5) + else: + raise ex # Cannot start a transaction before creating a table transaction_id = wr.lakeformation.start_transaction() if table_type == "GOVERNED" and start_transaction else None From c54ba97f80f75e80a6cd726bf0daf0a3dc8b2901 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Thu, 2 Dec 2021 13:20:21 -0800 Subject: [PATCH 35/36] catalog.py test --- tests/test_catalog.py | 39 ++++----------------------------------- 1 file changed, 4 insertions(+), 35 deletions(-) diff --git a/tests/test_catalog.py b/tests/test_catalog.py index 0c97e9e75..ae6b58caf 100644 --- a/tests/test_catalog.py +++ b/tests/test_catalog.py @@ -45,7 +45,6 @@ def test_catalog( if table_type != "GOVERNED" and start_transaction: pytest.skip() - assert wr.catalog.does_table_exist(database=glue_database, table=glue_table) is False transaction_id = wr.lakeformation.start_transaction() if table_type == "GOVERNED" else None wr.catalog.create_parquet_table( database=glue_database, @@ -54,18 +53,14 @@ def test_catalog( columns_types={"col0": "int", "col1": "double"}, partitions_types={"y": "int", "m": "int"}, compression="snappy", + description="Foo boo bar", + parameters={"tag": "test"}, + columns_comments={"col0": "my int", "y": "year"}, table_type=table_type, transaction_id=transaction_id, ) if transaction_id: - try: - wr.lakeformation.commit_transaction(transaction_id=transaction_id) - except botocore.exceptions.ClientError as ex: - if ex.response["Error"]["Code"] in ["ConcurrentModificationException"]: - logger.debug(f"Transaction: {transaction_id} commit is in progress.") - time.sleep(5) - else: - raise ex + wr.lakeformation.commit_transaction(transaction_id=transaction_id) with pytest.raises(wr.exceptions.InvalidArgumentValue): wr.catalog.create_parquet_table( database=glue_database, @@ -75,33 +70,7 @@ def test_catalog( mode="append", table_type=table_type, ) - assert wr.catalog.does_table_exist(database=glue_database, table=glue_table) is True - assert wr.catalog.delete_table_if_exists(database=glue_database, table=glue_table) is True - transaction_id = wr.lakeformation.start_transaction() if table_type == "GOVERNED" else None - wr.catalog.create_parquet_table( - database=glue_database, - table=glue_table, - path=path, - columns_types={"col0": "int", "col1": "double"}, - partitions_types={"y": "int", "m": "int"}, - compression="snappy", - description="Foo boo bar", - parameters={"tag": "test"}, - columns_comments={"col0": "my int", "y": "year"}, - mode="overwrite", - table_type=table_type, - transaction_id=transaction_id, - ) - if transaction_id: - try: - wr.lakeformation.commit_transaction(transaction_id=transaction_id) - except botocore.exceptions.ClientError as ex: - if ex.response["Error"]["Code"] in ["ConcurrentModificationException"]: - logger.debug(f"Transaction: {transaction_id} commit is in progress.") - time.sleep(5) - else: - raise ex # Cannot start a transaction before creating a table transaction_id = wr.lakeformation.start_transaction() if table_type == "GOVERNED" and start_transaction else None From 04d44abbf1ca54f22bae43ee687f35abc49acfe3 Mon Sep 17 00:00:00 2001 From: Abdel Jaidi Date: Thu, 2 Dec 2021 13:32:51 -0800 Subject: [PATCH 36/36] lint --- tests/test_catalog.py | 1 - 1 file changed, 1 deletion(-) diff --git a/tests/test_catalog.py b/tests/test_catalog.py index ae6b58caf..88b86492c 100644 --- a/tests/test_catalog.py +++ b/tests/test_catalog.py @@ -4,7 +4,6 @@ from typing import Optional import boto3 -import botocore import pandas as pd import pytest