TextBlob: Simplified Text Processing — TextBlob 0.19.0 documentation
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.
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Citation Level
2013
English, etc
Website Key Features
Part-of-speech tagging
Identifies the part of speech for each word in a text.
Noun phrase extraction
Extracts noun phrases from a text.
Sentiment analysis
Determines the sentiment of a text, whether it is positive, negative, or neutral.
Classification
Classifies text into categories using a Naive Bayes classifier.
Translation
Translates text between languages using Google Translate.
Tokenization
Breaks text into words and sentences.
Word and phrase frequencies
Calculates the frequency of words and phrases in a text.
Spelling correction
Corrects spelling errors in text.
Word inflection
Inflects words, such as pluralizing nouns or conjugating verbs.
n-grams
Generates n-grams from text.
Additional information
License
MIT License
Repository
https://github.com/sloria/TextBlob
Documentation
Comprehensive documentation available at textblob.readthedocs.io
Dependencies
Requires NLTK and pattern. NLTK is used for tokenization, part-of-speech tagging, and noun phrase extraction. Pattern is used for sentiment analysis and translation.
Community
Active community support available through GitHub issues and Stack Overflow.
Contributing
Contributions are welcome. Please see the contributing guide on GitHub.
HTTP headers
Security headers report is a very important part of user data protection. Learn more about http headers for textblob.readthedocs.io