/
legacy_config_transformer.py
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/
legacy_config_transformer.py
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#
# Copyright (c) 2023 Airbyte, Inc., all rights reserved.
#
import json
from datetime import datetime
from typing import Any, Dict, List, Mapping, Optional, Union
from source_s3.source import SourceS3Spec
from source_s3.source_files_abstract.formats.avro_spec import AvroFormat
from source_s3.source_files_abstract.formats.csv_spec import CsvFormat
from source_s3.source_files_abstract.formats.jsonl_spec import JsonlFormat
from source_s3.source_files_abstract.formats.parquet_spec import ParquetFormat
SECONDS_FORMAT = "%Y-%m-%dT%H:%M:%SZ"
MICROS_FORMAT = "%Y-%m-%dT%H:%M:%S.%fZ"
class LegacyConfigTransformer:
"""
Class that takes in S3 source configs in the legacy format and transforms them into
configs that can be used by the new S3 source built with the file-based CDK.
"""
@classmethod
def convert(cls, legacy_config: SourceS3Spec) -> Mapping[str, Any]:
transformed_config = {
"bucket": legacy_config.provider.bucket,
"streams": [
{
"name": legacy_config.dataset,
"globs": cls._create_globs(legacy_config.path_pattern),
"legacy_prefix": legacy_config.provider.path_prefix,
"validation_policy": "Emit Record",
}
],
}
if legacy_config.provider.start_date:
transformed_config["start_date"] = cls._transform_seconds_to_micros(legacy_config.provider.start_date)
if legacy_config.provider.aws_access_key_id:
transformed_config["aws_access_key_id"] = legacy_config.provider.aws_access_key_id
if legacy_config.provider.aws_secret_access_key:
transformed_config["aws_secret_access_key"] = legacy_config.provider.aws_secret_access_key
if legacy_config.provider.endpoint:
transformed_config["endpoint"] = legacy_config.provider.endpoint
if legacy_config.user_schema and legacy_config.user_schema != "{}":
transformed_config["streams"][0]["input_schema"] = legacy_config.user_schema
if legacy_config.format:
transformed_config["streams"][0]["format"] = cls._transform_file_format(legacy_config.format)
return transformed_config
@classmethod
def _create_globs(cls, path_pattern: str) -> List[str]:
if "|" in path_pattern:
return path_pattern.split("|")
else:
return [path_pattern]
@classmethod
def _transform_seconds_to_micros(cls, datetime_str: str) -> str:
try:
parsed_datetime = datetime.strptime(datetime_str, SECONDS_FORMAT)
return parsed_datetime.strftime(MICROS_FORMAT)
except ValueError as e:
raise ValueError("Timestamp could not be parsed when transforming legacy connector config") from e
@classmethod
def _transform_file_format(cls, format_options: Union[CsvFormat, ParquetFormat, AvroFormat, JsonlFormat]) -> Mapping[str, Any]:
if isinstance(format_options, AvroFormat):
return {"filetype": "avro"}
elif isinstance(format_options, CsvFormat):
additional_reader_options = cls.parse_config_options_str("additional_reader_options", format_options.additional_reader_options)
advanced_options = cls.parse_config_options_str("advanced_options", format_options.advanced_options)
csv_options = {
"filetype": "csv",
"delimiter": format_options.delimiter,
"quote_char": format_options.quote_char,
"double_quote": format_options.double_quote,
# values taken from https://github.com/apache/arrow/blob/43c05c56b37daa93e76b94bc3e6952d56d1ea3f2/cpp/src/arrow/csv/options.cc#L41-L45
"null_values": additional_reader_options.pop(
"null_values",
[
"",
"#N/A",
"#N/A N/A",
"#NA",
"-1.#IND",
"-1.#QNAN",
"-NaN",
"-nan",
"1.#IND",
"1.#QNAN",
"N/A",
"NA",
"NULL",
"NaN",
"n/a",
"nan",
"null",
],
),
"true_values": additional_reader_options.pop("true_values", ["1", "True", "TRUE", "true"]),
"false_values": additional_reader_options.pop("false_values", ["0", "False", "FALSE", "false"]),
"inference_type": "Primitive Types Only" if format_options.infer_datatypes else "None",
"strings_can_be_null": additional_reader_options.pop("strings_can_be_null", False),
}
if format_options.escape_char:
csv_options["escape_char"] = format_options.escape_char
if format_options.encoding:
csv_options["encoding"] = format_options.encoding
if skip_rows := advanced_options.pop("skip_rows", None):
csv_options["skip_rows_before_header"] = skip_rows
if skip_rows_after_names := advanced_options.pop("skip_rows_after_names", None):
csv_options["skip_rows_after_header"] = skip_rows_after_names
if column_names := advanced_options.pop("column_names", None):
csv_options["header_definition"] = {
"header_definition_type": "User Provided",
"column_names": column_names,
}
advanced_options.pop("autogenerate_column_names", None)
elif advanced_options.pop("autogenerate_column_names", None):
csv_options["header_definition"] = {"header_definition_type": "Autogenerated"}
else:
csv_options["header_definition"] = {"header_definition_type": "From CSV"}
cls._filter_legacy_noops(advanced_options)
if advanced_options or additional_reader_options:
raise ValueError(
"The config options you selected are no longer supported.\n" + f"advanced_options={advanced_options}"
if advanced_options
else "" + f"additional_reader_options={additional_reader_options}"
if additional_reader_options
else ""
)
return csv_options
elif isinstance(format_options, JsonlFormat):
return {"filetype": "jsonl"}
elif isinstance(format_options, ParquetFormat):
return {"filetype": "parquet", "decimal_as_float": True}
else:
# This should never happen because it would fail schema validation
raise ValueError(f"Format filetype {format_options} is not a supported file type")
@classmethod
def parse_config_options_str(cls, options_field: str, options_value: Optional[str]) -> Dict[str, Any]:
options_str = options_value or "{}"
try:
return json.loads(options_str)
except json.JSONDecodeError as error:
raise ValueError(f"Malformed {options_field} config json: {error}. Please ensure that it is a valid JSON.")
@staticmethod
def _filter_legacy_noops(advanced_options: Dict[str, Any]):
ignore_all = ("auto_dict_encode", "timestamp_parsers", "block_size")
ignore_by_value = (("check_utf8", False),)
for option in ignore_all:
advanced_options.pop(option, None)
for option, value_to_ignore in ignore_by_value:
if advanced_options.get(option) == value_to_ignore:
advanced_options.pop(option)