sloria/TextBlob

Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.

What it solves

It simplifies the process of performing common natural language processing (NLP) tasks by providing a streamlined, easy-to-use API for Python developers.

How it works

TextBlob acts as a high-level wrapper around other powerful libraries like NLTK and Pattern, allowing users to process textual data through a single interface. It converts text into a "Blob" object that provides built-in methods for analysis.

Who it’s for

Python developers who need to implement NLP features like sentiment analysis or part-of-speech tagging without having to manage the complexities of lower-level NLP frameworks.

Highlights

  • Sentiment Analysis: Quickly determine the polarity of sentences.
  • Text Analysis: Includes part-of-speech tagging, noun phrase extraction, and tokenization.
  • Classification: Supports Naive Bayes and Decision Tree classifiers.
  • Text Manipulation: Offers spelling correction, word inflection (pluralization/singularization), and lemmatization.
  • Extensibility: Allows the addition of new models or languages via extensions.

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