text: from zoltpy.covid19 import validate_quantile_csv_file
  import glob
  from pprint import pprint
  import sys
  import os
  import pandas as pd
  import numpy as np
  from datetime import datetime
  
  
  # Check for metadata file
  def check_for_metadata(my_path):
      for path in glob.iglob(my_path + "**/**/", recursive=False):
          team_model = os.path.basename(os.path.dirname(path))
          metadata_filename = "metadata-" + team_model + ".txt"
          txt_files = []
          for metadata_file in glob.iglob(path + "*.txt", recursive=False):
              txt_files += [os.path.basename(metadata_file)]
          if metadata_filename not in txt_files:
              print("MISSING ", metadata_filename)
  
  
  def filename_match_forecast_date(filename):
      df = pd.read_csv(filename)
      file_forecast_date = os.path.basename(os.path.basename(filename))[:10]
      forecast_date_column = set(list(df['forecast_date']))
      if len(forecast_date_column) > 1:
          return "ERROR: %s has multiple forecast dates: %s. Forecast date must be unique" % (
              filename, forecast_date_column)
      else:
          forecast_date_column = forecast_date_column.pop()
          if (file_forecast_date != forecast_date_column):
              return "ERROR %s forecast filename date %s does match forecast_date column %s" % (
                  filename, file_forecast_date, forecast_date_column)
          else:
              return None
  
  
  # Check forecast formatting
  
  
  def check_formatting(my_path):
      output_errors = {}
      df = pd.read_csv('code/validation/validated_files.csv')
      previous_checked = list(df['file_path'])
      files_in_repository = []
      # Iterate through processed csvs
      for path in glob.iglob(my_path + "**/**/", recursive=False):
          for filepath in glob.iglob(path + "*.csv", recursive=False):
              files_in_repository += [filepath]
  
              # check if file has been edited since last checked
              if filepath not in previous_checked:
                  # delete validated file if currrently present
                  df = df[df['file_path'] != filepath]
  
                  # validate file
                  file_error = validate_quantile_csv_file(filepath)
  
                  # Check forecast file date = forecast_date column
                  forecast_date_error = filename_match_forecast_date(filepath)
                  if forecast_date_error is not None:
                      if file_error == 'no errors':
                          file_error = [forecast_date_error]
                      else:
                          file_error += [forecast_date_error]
  
                  if file_error != 'no errors':
                      output_errors[filepath] = file_error
                  else:
                      # add to previously checked files
                      current_time = datetime.now()
                      df = df.append({'file_path': filepath,
                                      'validation_date': current_time}, ignore_index=True)
  
      # Remove files that have been deleted from repo
      # files that are in verify checks but NOT in repository
      deleted_files = np.setdiff1d(previous_checked, files_in_repository)
      df = df[~df['file_path'].isin(deleted_files)]
  
      # update previously checked files
      df.to_csv('code/validation/locally_validated_files.csv', index=False)
  
      # Output list of Errors
      if len(output_errors) > 0:
          for filename, errors in output_errors.items():
              print("\n* ERROR IN '", filename, "'")
              for error in errors:
                  print(error)
          sys.exit("\n ERRORS FOUND EXITING BUILD...")
      else:
          print("✓ no errors")
  
  
  def main():
      my_path = "./data-processed"
      check_for_metadata(my_path)
      check_formatting(my_path)
  
  
  if __name__ == "__main__":
      main()
  