Simplified Text Processing — TextBlob 0.19.0 documentation (original) (raw)

Release v0.19.0. (Changelog)

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.

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.