TextBlob: Simplified Text Processing

Release v0.16.0. (Changelog)

TextBlob is a Python (2 and 3) library for processing textual data. It provides a simple API for diving into common natural language processing (NLP) tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, and more.

from textblob import TextBlob

text = '''
The titular threat of The Blob has always struck me as the ultimate movie
monster: an insatiably hungry, amoeba-like mass able to penetrate
virtually any safeguard, capable of--as a doomed doctor chillingly
describes it--"assimilating flesh on contact.
Snide comparisons to gelatin be damned, it's a concept with the most
devastating of potential consequences, not unlike the grey goo scenario
proposed by technological theorists fearful of
artificial intelligence run rampant.
'''

blob = TextBlob(text)
blob.tags           # [('The', 'DT'), ('titular', 'JJ'),
                    #  ('threat', 'NN'), ('of', 'IN'), ...]

blob.noun_phrases   # WordList(['titular threat', 'blob',
                    #            'ultimate movie monster',
                    #            'amoeba-like mass', ...])

for sentence in blob.sentences:
    print(sentence.sentiment.polarity)
# 0.060
# -0.341

TextBlob stands on the giant shoulders of NLTK and pattern, and plays nicely with both.

Features

  • Noun phrase extraction
  • Part-of-speech tagging
  • Sentiment analysis
  • Classification (Naive Bayes, Decision Tree)
  • Tokenization (splitting text into words and sentences)
  • Word and phrase frequencies
  • Parsing
  • n-grams
  • Word inflection (pluralization and singularization) and lemmatization
  • Spelling correction
  • Add new models or languages through extensions
  • WordNet integration

Get it now

$ pip install -U textblob
$ python -m textblob.download_corpora

Ready to dive in? Go on to the Quickstart guide.