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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.
fromtextblobimportTextBlobtext="""The titular threat of The Blob has always struck me as the ultimate moviemonster: an insatiably hungry, amoeba-like mass able to penetratevirtually any safeguard, capable of--as a doomed doctor chillinglydescribes it--"assimilating flesh on contact.Snide comparisons to gelatin be damned, it's a concept with the mostdevastating of potential consequences, not unlike the grey goo scenarioproposed by technological theorists fearful ofartificial 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', ...])forsentenceinblob.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