old_contents: import time
  
  import pandas as pd
  
  from OHA.WHO import WHO
  from OHA.param_builders.who_param_builder import WhoParamsBuilder as WPB
  
  
  def calculate_hearts_risk(row):
      # column names: country,age,gender,bp,total_chol,smoker,diabetes,cvd_risk
      is_smoker = False
      has_diabetes = False
      if row['smoker'] == '1':
          is_smoker = True
  
      if row['diabetes'] == '1':
          has_diabetes = True
  
      params = WPB() \
          .gender(row['gender']) \
          .age(row['age']) \
          .sbp1(row['bp']) \
          .sbp2(row['bp']) \
          .chol(row['total_chol'], 'mmol/l') \
          .region(row['country']) \
          .smoker(is_smoker) \
          .diabetic(has_diabetes) \
          .build()
      result = WHO().calculate(params)
      # print('--> WHO:', params, ' => ', result, '---\n')
      return result['risk_range']
  
  
  print('---> running tests ---')
  
  filename = 'OHA/tests/who_tests.csv'
  tests_df = pd.read_csv(filename)
  
  tests_df['calculated'] = tests_df.apply(calculate_hearts_risk, axis=1)
  tests_df['result'] = tests_df.apply(lambda x: True if x['cvd_risk'] == x['calculated'] else False, axis=1)
  print(tests_df)
  
  df_filtered = tests_df.query('result == True')
  
  total_tests = tests_df['result'].count()
  successful_tests = df_filtered['result'].count()
  success_percentage = round(((int(successful_tests) / int(total_tests)) * 100), 2)
  
  # add the date-time to the filname
  timestr = time.strftime("%Y%m%d-%H%M%S")
  filename = 'tmp/test_results/who_tests_processed_' + timestr + '.csv'
  print('---> completed tests ---, %s' % success_percentage, '% correct --- outputting to file', filename)
  tests_df.to_csv(filename)
  
new_contents: import time
  
  import pandas as pd
  
  from OHA.WHO import WHO
  from OHA.param_builders.who_param_builder import WhoParamsBuilder as WPB
  
  
  def calculate_hearts_risk(row):
      # column names: country,age,gender,bp,total_chol,smoker,diabetes,cvd_risk
      is_smoker = False
      has_diabetes = False
      if row['smoker'] == '1':
          is_smoker = True
  
      if row['diabetes'] == '1':
          has_diabetes = True
  
      params = WPB() \
          .gender(row['gender']) \
          .age(row['age']) \
          .sbp1(row['bp']) \
          .sbp2(row['bp']) \
          .chol(row['total_chol'], 'mmol/l') \
          .region(row['country']) \
          .smoker(is_smoker) \
          .diabetic(has_diabetes) \
          .build()
      result = WHO().calculate(params)
      # print('--> WHO:', params, ' => ', result, '---\n')
      return result['risk_range']
  
  
  print('---> running tests ---')
  
  filename = 'tests/data/who_tests.csv'
  tests_df = pd.read_csv(filename)
  
  tests_df['calculated'] = tests_df.apply(calculate_hearts_risk, axis=1)
  tests_df['result'] = tests_df.apply(lambda x: True if x['cvd_risk'] == x['calculated'] else False, axis=1)
  print(tests_df)
  
  df_filtered = tests_df.query('result == True')
  
  total_tests = tests_df['result'].count()
  successful_tests = df_filtered['result'].count()
  success_percentage = round(((int(successful_tests) / int(total_tests)) * 100), 2)
  
  # add the date-time to the filname
  timestr = time.strftime("%Y%m%d-%H%M%S")
  filename = 'tmp/test_results/who_tests_processed_' + timestr + '.csv'
  print('---> completed tests ---, %s' % success_percentage, '% correct --- outputting to file', filename)
  tests_df.to_csv(filename)
  
subject: update filepath