text: # 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
  #
  #     http://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,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  import logging
  from typing import Optional
  
  from openlineage.airflow.extractors.base import BaseExtractor, StepMetadata
  
  log = logging.getLogger(__file__)
  
  
  # Great Expectations is optional dependency.
  try:
      from great_expectations_provider.operators.great_expectations import GreatExpectationsOperator
      _has_great_expectations = True
  except Exception:
      # Create placeholder for GreatExpectationsOperator
      GreatExpectationsOperator = None
      log.warning('Did not find great_expectations_provider library or failed to import it')
      _has_great_expectations = False
  
  
  class GreatExpectationsExtractorImpl(BaseExtractor):
      """
      Great Expectations extractor extracts validation data from CheckpointResult object and
      parses it via ExpectationsParsers. Results are used to prepare data quality facet.
      """
      operator_class = GreatExpectationsOperator
  
      def __init__(self, operator):
          super().__init__(operator)
          self.result = None
  
      def extract(self) -> Optional[StepMetadata]:
          return None
  
      def extract_on_complete(self, task_instance) -> Optional[StepMetadata]:
          return None
  
  
  if _has_great_expectations:
      GreatExpectationsExtractor = GreatExpectationsExtractorImpl
  else:
      class GreatExpectationsExtractor:
          def __init__(self):
              raise RuntimeError('Great Expectations provider not found')
  