text: import click
  import csv
  import pandas as pd
  
  from datetime import datetime, timedelta
  
  
  @click.command()
  @click.option('--network', help='Network to download news from', default='FOXNEWS')
  @click.option('--start_date', help='Start date for getting closed captions in the format YYYYMMDD',
                default='20200101')
  @click.option('--end_date', help='End date for getting closed captions in the format YYYYMMDD',
                default='20200101')
  @click.option('--input_file', help='Path to search input file', default='../../data/raw/search.csv')
  @click.option('--output_file', help='Path to search output file', default='../../data/raw/search-filtered.csv')
  def filter_news_identifiers(network, start_date, end_date, input_file, output_file):
      programs = pd.read_csv(input_file)
      start_date_obj = datetime.strptime(start_date, '%Y%m%d')
      end_date_obj = datetime.strptime(end_date, '%Y%m%d')
  
      # construct list of dates encompassing the range between start date and end date
      date_strings = []
      temp_date = start_date_obj
      while temp_date <= end_date_obj:
          date_strings.append(temp_date.strftime('%Y%m%d'))
          temp_date = temp_date + timedelta(days=1)
  
      program_list = []
      for date_string in date_strings:
          program_list = program_list + list(programs[programs.identifier.str.contains('_{}'.format(date_string)) &
                                                      programs.identifier.str.contains(network)]['identifier'])
          print(date_string)
  
      filtered_programs_df = pd.DataFrame(program_list)
      filtered_programs_df.columns = ['identifier']
      filtered_programs_df.to_csv(output_file, index=False)
  
      print(program_list)
      print('Filtering completed')
  
  
  if __name__ == "__main__":
      filter_news_identifiers()
  