Major - Make path argument in wr.s3.to functions optional

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 `path` argument must be passed.")
         if path.endswith("/"):
             raise exceptions.InvalidArgumentValue(
                 "If <dataset=False>, the argument <path> should be a file path, not a directory."
@@ -79,6 +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."

awswrangler/s3/_write_parquet.py

@@ -198,7 +198,7 @@ def _to_parquet(
 @apply_configs
 def to_parquet(  # pylint: disable=too-many-arguments,too-many-locals
     df: pd.DataFrame,
-    path: str,
+    path: Optional[str] = None,
     index: bool = False,
     compression: Optional[str] = "snappy",
     max_rows_by_file: Optional[int] = None,
@@ -252,8 +252,9 @@ 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``).
+        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
@@ -511,6 +512,19 @@ 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
         )
+        catalog_path = catalog_table_input["StorageDescriptor"]["Location"] if catalog_table_input else None
+        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}"
+                )
     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
@@ -545,7 +559,7 @@ def to_parquet(  # pylint: disable=too-many-arguments,too-many-locals
             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,
@@ -565,7 +579,7 @@ 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,
                     partitions_types=partitions_types,
                     bucketing_info=bucketing_info,

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,
@@ -137,8 +137,9 @@ 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
-        Amazon S3 path (e.g. s3://bucket/filename.csv).
+    path : str, optional
+        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
@@ -414,13 +415,27 @@ 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 = catalog_table_input["StorageDescriptor"]["Location"] if catalog_table_input else None
+        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."
             )
 
     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 +449,7 @@ 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
@@ -461,7 +476,7 @@ def to_csv(  # pylint: disable=too-many-arguments,too-many-locals,too-many-state
             func=_to_text,
             concurrent_partitioning=concurrent_partitioning,
             df=df,
-            path_root=path,
+            path_root=path,  # type: ignore
             index=index,
             sep=sep,
             compression=compression,
@@ -486,7 +501,7 @@ def to_csv(  # pylint: disable=too-many-arguments,too-many-locals,too-many-state
                 catalog._create_csv_table(  # pylint: disable=protected-access
                     database=database,
                     table=table,
-                    path=path,
+                    path=path,  # type: ignore
                     columns_types=columns_types,
                     partitions_types=partitions_types,
                     bucketing_info=bucketing_info,

tests/test__routines.py

@@ -44,7 +44,6 @@ 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,
@@ -101,7 +100,6 @@ 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,
@@ -162,7 +160,6 @@ def test_routine_0(glue_database, glue_table, path, use_threads, concurrent_part
     df = pd.DataFrame({"c0": ["foo", None], "c1": [0, 1]})
     wr.s3.to_parquet(
         df=df,
-        path=path,
         dataset=True,
         mode="overwrite",
         database=glue_database,
@@ -223,7 +220,6 @@ def test_routine_0(glue_database, glue_table, path, use_threads, concurrent_part
     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,

tests/test_athena_csv.py

@@ -49,7 +49,6 @@ def test_to_csv_modes(glue_database, glue_table, path, use_threads, concurrent_p
     df = pd.DataFrame({"c1": [0, 1, 2]}, dtype="Int16")
     wr.s3.to_csv(
         df=df,
-        path=path,
         dataset=True,
         mode="overwrite",
         database=glue_database,
@@ -106,7 +105,6 @@ def test_to_csv_modes(glue_database, glue_table, path, use_threads, concurrent_p
     df = pd.DataFrame({"c0": ["foo", "boo"], "c1": [0, 1]})
     wr.s3.to_csv(
         df=df,
-        path=path,
         dataset=True,
         mode="overwrite",
         database=glue_database,

tests/test_s3.py

@@ -103,6 +103,23 @@ def mock_make_api_call(self, operation_name, kwarg):
             wr.s3.delete_objects(path=[path])
 
 
+def test_missing_or_wrong_path(path, glue_database, glue_table):
+    # Missing path
+    df = pd.DataFrame({"FooBoo": [1, 2, 3]})
+    with pytest.raises(wr.exceptions.InvalidArgumentValue):
+        wr.s3.to_parquet(df=df)
+    with pytest.raises(wr.exceptions.InvalidArgumentCombination):
+        wr.s3.to_parquet(df=df, dataset=True)
+    with pytest.raises(wr.exceptions.InvalidArgumentValue):
+        wr.s3.to_parquet(df=df, dataset=True, database=glue_database, table=glue_table)
+
+    # Wrong path
+    wr.s3.to_parquet(df=df, path=path, dataset=True, database=glue_database, table=glue_table)
+    wrong_path = "s3://bucket/prefix"
+    with pytest.raises(wr.exceptions.InvalidArgumentValue):
+        wr.s3.to_parquet(df=df, path=wrong_path, dataset=True, database=glue_database, table=glue_table)
+
+
 def test_s3_empty_dfs():
     df = pd.DataFrame()
     with pytest.raises(wr.exceptions.EmptyDataFrame):