A cleaning function for NLP

cleaning_the_text.py

# A function to open the raw text
def open_file(file_path):

    with open(file_path, 'r') as file:
        raw_text = file.read().replace('\n', ' ')
    
    return raw_text


# A function that takes in the raw text of a string, removes special characters and 
# stop words, and returns the script text as a list where each element represents a word
def cleaned_episode(raw_text, stop_words = False):
    
    #RegEx to delete all text between and including brackets and parenthesis
    raw_text_no_notes = re.sub("[\(\[].*?[\)\]]", "", raw_text)

    #Removes any special characters
    for symbol in "*,#-.?!''\n":
        raw_text_no_notes = raw_text_no_notes.replace(symbol, '').lower()
  
    #Splits the text into a list of words
    cleaned_text = raw_text_no_notes.split(" ")    
    
    #Removes any word that containes a colon, i.e. character speaking indicators
    #Deletes spaces and blank elements
    for i in cleaned_text:
        
        if i.endswith(':') == True or i == '' or i == ' ':
            cleaned_text.remove(i)
        
    #Removes any stop words passed as a list
    if stop_words:
        
        cleaned_text  = [word for word in cleaned_text if word.lower() not in stop_words]
    
    #Returns the raw text as a list of words
    return cleaned_text