code: def get_data_extractors():
      # Specify how to extract privacy_id, partition_key and value from an
      # element of restaurant_visits_rows.
      return pipeline_dp.DataExtractors(
          partition_extractor=lambda row: row.day,
          privacy_id_extractor=lambda row: row.user_id,
          value_extractor=lambda row: row.spent_money,
      )
  
file_path: pipelinedp/examples/restaurant_visits/run_without_frameworks_tuning.py
imports: from absl import app
  from absl import flags
  import pipeline_dp
  import pandas
  import analysis
  from analysis import parameter_tuning
  from pipeline_dp.dataset_histograms import computing_histograms
label_desc: Use image node_id 4 for calling a global function with example usage: get_data_extractors() and returns: pipeline_dp