Simple, Pythonic text processing. Sentiment analysis, part-of-speech tagging, noun phrase parsing, and more.
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 # [('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 blob.translate(to="es") # 'La amenaza titular de The Blob...'
- 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
- 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
See more examples at the Quickstart guide.
Full documentation is available at https://textblob.readthedocs.io/.
- Python >= 2.7 or >= 3.4
MIT licensed. See the bundled LICENSE file for more details.
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