textblob_lemmatize.py

from textblob import TextBlob
from textblob import blob

nltk.download('averaged_perceptron_tagger')
nltk.download('punkt')
nltk.download('wordnet')

def to_wordnet(tag):
    _wordnet = _wordnet
    if tag in ("NN", "NNS", "NNP", "NNPS"):
        return blob._wordnet.NOUN
    if tag in ("JJ", "JJR", "JJS"):
        return blob._wordnet.ADJ
    if tag in ("VB", "VBD", "VBG", "VBN", "VBP", "VBZ"):
        return blob._wordnet.VERB
    if tag in ("RB", "RBR", "RBS"):
        return blob._wordnet.ADV
    return blob._wordnet.NOUN
    
  text = "Some texts"
  text = TextBlob(text).tags
  text = [Word(word).lemmatize(to_wordnet(tag)) for (word, tag) in text]
  text = ' '.join(text)