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https://github.com/sloria/textblob

Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
https://github.com/sloria/textblob

natural-language-processing nlp nltk pattern python python-3

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Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.

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TextBlob: Simplified Text Processing
====================================

.. image:: https://badgen.net/pypi/v/TextBlob
:target: https://pypi.org/project/textblob/
:alt: Latest version

.. image:: https://github.com/sloria/TextBlob/actions/workflows/build-release.yml/badge.svg
:target: https://github.com/sloria/TextBlob/actions/workflows/build-release.yml
:alt: Build status

Homepage: `https://textblob.readthedocs.io/ `_

`TextBlob` is a Python 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, 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 `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

Examples
--------

See more examples at the `Quickstart guide`_.

.. _`Quickstart guide`: https://textblob.readthedocs.io/en/latest/quickstart.html#quickstart

Documentation
-------------

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

Project Links
-------------

- Docs: https://textblob.readthedocs.io/
- Changelog: https://textblob.readthedocs.io/en/latest/changelog.html
- PyPI: https://pypi.python.org/pypi/TextBlob
- Issues: https://github.com/sloria/TextBlob/issues

License
-------

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

.. _pattern: https://github.com/clips/pattern/
.. _NLTK: http://nltk.org/