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sloria /TextBlob

Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extractio...

7.1K Stars 954 Forks Last release: almost 7 years ago (0.7.0) MIT License 539 Commits 37 Releases

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TextBlob: Simplified Text Processing

.. image:: :target: :alt: Latest version

.. image:: :target: :alt: Travis-CI

Homepage: <https:></https:>



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.

.. code-block:: python

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


_ and


_, and plays nicely with both.


  • 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\_corpora


See more examples at the

Quickstart guide


.. _

Quickstart guide



Full documentation is available at


  • Python >= 2.7 or >= 3.5

Project Links


MIT licensed. See the bundled

LICENSE <https:></https:>

_ file for more details.

.. _pattern: .. _NLTK:

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