import sklearn.feature_extraction.text
from nltk.tokenize import TreebankWordTokenizer
ngram_size = 4
string = ["I really like python, it's pretty awesome."]
vect = sklearn.feature_extraction.text.CountVectorizer(ngram_range=(
    ngram_size, ngram_size), tokenizer=TreebankWordTokenizer().tokenize)
How to use sklearn's CountVectorizerand() to get ngrams that include any punctuation as separate tokens?