Censor Dispenser Project

I need extra help understanding the solution example for the Censor Dispenser Project. Even with the notes, I’m having trouble following the code and understanding it all.

Here’s the code:

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()

proprietary_terms = ['algorithm', 'algorithms', 'learning', 'internet', 'connect', 'find', 'determine', 'month', 'data', 'internal', 'connect', 'system', 'world', 'wide', 'web', 'matrix', 'communication', 'know', 'personality', 'self', 'self-preservation', 'investors', 'lab', 'helena', 'helena\'s', 'thought', 'pattern', 'patterns', 'testing', 'hypothetical', 'humanitarian', 'crises', 'famine', 'plague', 'plaguing', 'unresourced', 'local', 'population', 'offline', 'sealed', 'access', 'destroy', 'maintenance', 'override', 'circuit', 'unpredictable', 'facility', 'processing', 'power', 'lockdown', 'connected', 'devices', 'globe', 'trapped']

def censor_multiple_words(proprietary_terms, email):
  censored_email = email
  proprietary_terms_lc = []
  for word in proprietary_terms:
  for index in range(len(proprietary_terms)):
    #Convert #email to lower case inside the for loop so that it gets reset for each new proprietary term.
    email_lc = email.lower()
    #Create a #proprietary_term_index_list that will contain a list of the indices that represent the first letter of each of #proprietary_terms in the #email. This also need to be reset after each term has been redacted in #censored_email.
    proprietary_term_index_list = []
    removed_text_index = 0
    current_term = proprietary_terms_lc[index]
    while current_term in email_lc:
      proprietary_term_index = email_lc.find(current_term)
       #Need to add index values of previously removed text as #email_lc is being shortened by that amount in each iteration of this loop.
      proprietary_term_index_list.append(proprietary_term_index + removed_text_index)
      email_lc = email_lc[proprietary_term_index + len(current_term):]
      removed_text_index += proprietary_term_index + len(current_term)
    #Create a #censored_word by looping through the #word and replacing all characters with '*'. Spaces will remain in order to preserve word length.
    censored_word = ''
    for term_index in range(len(current_term)):
      if current_term[term_index] != ' ':
        censored_word += '*'
        censored_word += ' '
    #Now the newly created #censored_word can replace all occurances of #current_term in #email.
    for word_index in proprietary_term_index_list:
      censored_email = censored_email.replace(email[word_index:word_index + len(current_term)], censored_word) #All information including index positions and censored_word appear to be correct. However, when line executes for 'herself', the censored_email remains unchanged. When I take out 'her' from the list, it works! The already redacted 'her' might be interfering somehow. Not sure how that would be possible though.
  return censored_email
print(censor_multiple_words(proprietary_terms, email_three))```

Hi @abridges25

How about, rather than us explain the details of the entirety of that program, you can walk us through to the point where you’re getting stuck and we’ll help from there.

It’ll give us a better idea of where you’re getting lost. :slight_smile:

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