class_docstr: Immutable data class containing the arguments for a FeatureProcessor.
  
  This class is used throughout sagemaker.feature_store.feature_processor module. Documentation
  for each field can be be found in the feature_processor decorator.
  
  Defaults are defined as literals in the feature_processor decorator's parameters for usability
  (i.e. literals in docs). Defaults, or any business logic, should not be added to this class.
  It only serves as an immutable data class.
docstr: Static initializer.
docstr_tok: ["Static","initializer","."]
code: def create(
      inputs: Sequence[
          Union[
              FeatureGroupDataSource,
              CSVDataSource,
              ParquetDataSource,
              BaseDataSource,
          ]
      ],
      output: str,
      mode: FeatureProcessorMode,
      target_stores: Optional[List[str]],
      parameters: Optional[Dict[str, Union[str, Dict]]],
      enable_ingestion: bool,
      spark_config: Dict[str, str],
  ) -> "FeatureProcessorConfig":
      """Static initializer."""
      return FeatureProcessorConfig(
          inputs=inputs,
          output=output,
          mode=mode,
          target_stores=target_stores,
          parameters=parameters,
          enable_ingestion=enable_ingestion,
          spark_config=spark_config,
      )
  
imports: from __future__ import absolute_import
  from typing import Dict, List, Optional, Sequence, Union
  import attr
  from sagemaker.feature_store.feature_processor._data_source import CSVDataSource, FeatureGroupDataSource, ParquetDataSource, BaseDataSource
  from sagemaker.feature_store.feature_processor._enums import FeatureProcessorMode
label_desc: Use image node_id 1 for calling the FeatureProcessorConfig obj's underlying member method code with example usage: obj.create(inputs, output, mode, target_stores, parameters, enable_ingestion, spark_config) and returns: FeatureProcessorConfig