content: #  Copyright (c) ZenML GmbH 2023. All Rights Reserved.
  #
  #  Licensed under the Apache License, Version 2.0 (the "License");
  #  you may not use this file except in compliance with the License.
  #  You may obtain a copy of the License at:
  #
  #       https://www.apache.org/licenses/LICENSE-2.0
  #
  #  Unless required by applicable law or agreed to in writing, software
  #  distributed under the License is distributed on an "AS IS" BASIS,
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  """Implementation of the Evidently Test Step."""
  
  from typing import Any, Dict, List, Optional, Sequence, Tuple, cast
  
  import pandas as pd
  from typing_extensions import Annotated
  
  from zenml import step
  from zenml.integrations.evidently.column_mapping import (
      EvidentlyColumnMapping,
  )
  from zenml.integrations.evidently.data_validators import EvidentlyDataValidator
  from zenml.integrations.evidently.tests import EvidentlyTestConfig
  from zenml.types import HTMLString
  
  
  @step
  def evidently_test_step(
      reference_dataset: pd.DataFrame,
      comparison_dataset: Optional[pd.DataFrame],
      column_mapping: Optional[EvidentlyColumnMapping] = None,
      ignored_cols: Optional[List[str]] = None,
      tests: Optional[List[EvidentlyTestConfig]] = None,
      test_options: Optional[Sequence[Tuple[str, Dict[str, Any]]]] = None,
      download_nltk_data: bool = False,
  ) -> Tuple[Annotated[str, "test_json"], Annotated[HTMLString, "test_html"]]:
      """Run an Evidently test suite on one or two pandas datasets.
  
      Args:
          reference_dataset: a Pandas DataFrame
          comparison_dataset: a Pandas DataFrame of new data you wish to
              compare against the reference data
          column_mapping: properties of the DataFrame columns used
          ignored_cols: columns to ignore during the Evidently profile step
          tests: a list of Evidently test configuration to use for the test suite.
          test_options: a list of tuples containing the name of the test
              and a dictionary of options for the test.
          download_nltk_data: whether to download the NLTK data for the report
              step. Defaults to False.
  
      Returns:
          A tuple containing the TestSuite in JSON and HTML formats.
  
      Raises:
          ValueError: If ignored_cols is an empty list
          ValueError: If column is not found in reference or comparison
              dataset
      """
      if not tests:
          tests = EvidentlyTestConfig.default_tests()
  
      data_validator = cast(
          EvidentlyDataValidator,
          EvidentlyDataValidator.get_active_data_validator(),
      )
  
      if ignored_cols:
          extra_cols = set(ignored_cols) - set(reference_dataset.columns)
          if extra_cols:
              raise ValueError(
                  f"Columns {extra_cols} configured in the ignored_cols "
                  "parameter are not found in the reference dataset."
              )
          reference_dataset = reference_dataset.drop(
              labels=list(ignored_cols), axis=1
          )
  
          if comparison_dataset is not None:
              extra_cols = set(ignored_cols) - set(comparison_dataset.columns)
              if extra_cols:
                  raise ValueError(
                      f"Columns {extra_cols} configured in the ignored_cols "
                      "parameter are not found in the comparison dataset."
                  )
  
              comparison_dataset = comparison_dataset.drop(
                  labels=list(ignored_cols), axis=1
              )
  
      if column_mapping:
          evidently_column_mapping = column_mapping.to_evidently_column_mapping()
      else:
          evidently_column_mapping = None
      test_suite = data_validator.data_validation(
          dataset=reference_dataset,
          comparison_dataset=comparison_dataset,
          check_list=tests,
          column_mapping=evidently_column_mapping,
          test_options=test_options or [],
          download_nltk_data=download_nltk_data,
      )
      return (
          test_suite.json(),
          HTMLString(test_suite.get_html()),
      )
  