TextBlob: Simplified Text Processing

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           # [(u'The', u'DT'), (u'titular', u'JJ'),
                    #  (u'threat', u'NN'), (u'of', u'IN'), ...]

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

for sentence in blob.sentences:
    print(sentence.sentiment)  # returns (polarity, subjectivity)
# (0.060, 0.605)
# (-0.341, 0.767)

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
JSON serialization
Add new models or languages through extensions
WordNet integration

Get it now

$ pip install -U textblob
$ curl https://raw.github.com/sloria/TextBlob/master/download_corpora.py | python

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.