TextBlob and spacytextblob
TextBlob is a standalone sentiment analysis library, while spacytextblob is a wrapper that integrates TextBlob's functionality as a pipeline component within spaCy, making them complements rather than competitors—you would use spacytextblob if you're already working in the spaCy NLP framework and want TextBlob's sentiment capabilities integrated into your processing pipeline.
About TextBlob
sloria/TextBlob
Simple, Pythonic, text processing--Sentiment analysis, part-of-speech tagging, noun phrase extraction, translation, and more.
This tool helps developers analyze and process textual data, providing a straightforward way to extract meaning. You feed it raw text, and it outputs insights like sentiment, parts of speech, and key phrases. It's for Python developers who need to integrate text analysis capabilities into their applications.
About spacytextblob
SamEdwardes/spacytextblob
A TextBlob sentiment analysis pipeline component for spaCy.
This tool helps Python developers who are already using spaCy for natural language processing to easily add sentiment analysis to their workflow. It takes text as input and outputs numerical scores for how positive or negative (polarity) and how factual or opinionated (subjectivity) that text is. This is ideal for developers building applications that need to understand the emotional tone of text data.
Scores updated daily from GitHub, PyPI, and npm data. How scores work