replace_explitives.py

import nltk
from nltk.tokenize import word_tokenize, sent_tokenize
import re


nltk.download('punkt') # For tokenization
nltk.download('averaged_perceptron_tagger') # For POS tagging (optional)


def sub_explitives(textfile, selection):

 replacetext = "person"

 # text = word_tokenize(textfile)
 # print(text)
 # sentences = sent_tokenize(textfile)

 if selection == "B":
 target_word = r"\bbitch\b"
 elif selection == "N":
 target_word = r"\bnigg\b"
 elif selection == "all":
 target_word = r"\bshit\b"
 else:
 target_word = None
 
 print("selection:", selection, "target_word:", target_word)

 if target_word:
 print("target word was found, ", target_word)
 print(text)
 textfile = re.sub(target_word, replacetext, textfile, flags=re.IGNORECASE)
 return textfile