Codecademy export

script.py

# These are the emails you will be censoring. The open() function is opening the text file that the emails are contained in and the .read() method is allowing us to save their contexts to the following variables:
email_one = open("email_one.txt", "r").read()
email_two = open("email_two.txt", "r").read()
email_three = open("email_three.txt", "r").read()
email_four = open("email_four.txt", "r").read()

punctuation = ['.', '?', '!', ',']
proprietary_terms = ["she", "personality matrix", "sense of self", "self-preservation", "learning algorithms", "her", "herself"]

negative_words = ['concerned', 'behind', 'danger', 'dangerous', 'alarming', 'alarmed', 'out of control', 'help', 'unhappy', 'bad', 'upset', 'awful', 'broken', 'damage', 'damaging', 'dismal', 'distressed', 'distress', 'concerning', 'horrible', 'horribly', 'questionable']


def censor_email_four(email_four):
  email_4 = email_four.split()
  words_with_punctuation = []
  words_to_censor = proprietary_terms + negative_words 
  
  for j in range(len(words_to_censor)):
    for k in range(len(punctuation)):
      if words_to_censor[j]+punctuation[k] in email_4:
        words_with_punctuation.append(words_to_censor[j]+punctuation[k])

  words_to_censor_final = words_to_censor + words_with_punctuation
  
  for i in range(len(email_4)):
    if email_4[i].lower() in words_to_censor_final:
       email_4[i-1] = len(email_4[i-1]) * "x"
       email_4[i] = len(email_4[i]) * "x"
       email_4[i+1] = len(email_4[i+1]) * "x"

  email_4_final = ' '.join(email_4) 

  return email_4_final

print(censor_email_four(email_four))