There are so many guides on how to tokenize a sentence, but i didn\'t find any on how to do the opposite.
import nltk
words = nltk.word_tokenize(\"I\'ve found
use token_utils.untokenize
from here
import re
def untokenize(words):
"""
Untokenizing a text undoes the tokenizing operation, restoring
punctuation and spaces to the places that people expect them to be.
Ideally, `untokenize(tokenize(text))` should be identical to `text`,
except for line breaks.
"""
text = ' '.join(words)
step1 = text.replace("`` ", '"').replace(" ''", '"').replace('. . .', '...')
step2 = step1.replace(" ( ", " (").replace(" ) ", ") ")
step3 = re.sub(r' ([.,:;?!%]+)([ \'"`])', r"\1\2", step2)
step4 = re.sub(r' ([.,:;?!%]+)$', r"\1", step3)
step5 = step4.replace(" '", "'").replace(" n't", "n't").replace(
"can not", "cannot")
step6 = step5.replace(" ` ", " '")
return step6.strip()
tokenized = ['I', "'ve", 'found', 'a', 'medicine', 'for', 'my','disease', '.']
untokenize(tokenized)
"I've found a medicine for my disease."