Simple, Pythonic text processing. Sentiment analysis, POS tagging, noun phrase parsing, and more.

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  • License: MIT License (Copyright 2013-2015 Steven Loria)
  • Author: Steven Loria
  • Tags textblob , nlp , linguistics , nltk , pattern
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Project description

Latest version Travis-CI

Homepage: https://textblob.readthedocs.org/

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

blob.translate(to="es")  # 'La amenaza titular de The Blob...'

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)

  • Language translation and detection powered by Google Translate

  • 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

Examples

See more examples at the Quickstart guide.

Documentation

Full documentation is available at https://textblob.readthedocs.org/.

Requirements

  • Python >= 2.6 or >= 3.3

License

MIT licensed. See the bundled LICENSE file for more details.

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