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  #
  #  Licensed under the Apache License, Version 2.0 (the "License");
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  #  You may obtain a copy of the License at:
  #
  #       https://www.apache.org/licenses/LICENSE-2.0
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  """Implementation of the Deepchecks data drift validation step."""
  
  from typing import Any, Dict, Optional, Sequence, cast
  
  import pandas as pd
  from deepchecks.core.suite import SuiteResult
  
  from zenml import step
  from zenml.integrations.deepchecks.data_validators.deepchecks_data_validator import (
      DeepchecksDataValidator,
  )
  from zenml.integrations.deepchecks.validation_checks import (
      DeepchecksDataDriftCheck,
  )
  
  
  @step
  def deepchecks_data_drift_check_step(
      reference_dataset: pd.DataFrame,
      target_dataset: pd.DataFrame,
      check_list: Optional[Sequence[DeepchecksDataDriftCheck]] = None,
      dataset_kwargs: Optional[Dict[str, Any]] = None,
      check_kwargs: Optional[Dict[str, Any]] = None,
      run_kwargs: Optional[Dict[str, Any]] = None,
  ) -> SuiteResult:
      """Run data drift checks on two pandas datasets using Deepchecks.
  
      Args:
          reference_dataset: Reference dataset for the data drift check.
          target_dataset: Target dataset to be used for the data drift check.
          check_list: Optional list of DeepchecksDataDriftCheck identifiers
              specifying the subset of Deepchecks data drift checks to be
              performed. If not supplied, the entire set of data drift checks will
              be performed.
          dataset_kwargs: Additional keyword arguments to be passed to the
              Deepchecks `tabular.Dataset` or `vision.VisionData` constructor.
          check_kwargs: Additional keyword arguments to be passed to the
              Deepchecks check object constructors. Arguments are grouped for
              each check and indexed using the full check class name or
              check enum value as dictionary keys.
          run_kwargs: Additional keyword arguments to be passed to the
              Deepchecks Suite `run` method.
  
      Returns:
          A Deepchecks suite result with the validation results.
      """
      data_validator = cast(
          DeepchecksDataValidator,
          DeepchecksDataValidator.get_active_data_validator(),
      )
  
      return data_validator.data_validation(
          dataset=reference_dataset,
          comparison_dataset=target_dataset,
          check_list=check_list,
          dataset_kwargs=dataset_kwargs or {},
          check_kwargs=check_kwargs or {},
          run_kwargs=run_kwargs or {},
      )
  