Simple, Pythonic text processing. Sentiment analysis, part-of-speech tagging, noun phrase parsing, and more.
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Project description
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.
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
# -0.341TextBlob 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.
Documentation
Full documentation is available at https://textblob.readthedocs.io/.
Project Links
License
MIT licensed. See the bundled LICENSE file for more details.
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