TextBlob: Simplified Text Processing

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.

Guide

Project info