textblob
Simple, Pythonic text processing. Sentiment analysis, part-of-speech tagging, noun phrase parsing, and more.
Decision gist · record as of 2026-08-14
Yes, if you need straightforward NLP tasks without deep learning complexity. TextBlob is well-maintained, has no security vulnerabilities, and offers a gentle entry point to text processing. Install it for sentiment analysis, phrase extraction, or basic classification. Skip it if you require state-of-the-art accuracy or modern transformer-based models.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- The download_corpora step must be run once to fetch required linguistic data before sentiment analysis and other NLP features work.
- Low install friction with a single runtime dependency on nltk.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions, making it suitable for most projects without licensing concerns.
last release 2026-07-18 (27 days) · last repo commit 2026-08-11 · 9,546 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 7,600,176 downloads/mo, #1,717 on PyPI
Alternatives
Verify before relying
pip install textblob
python -m textblob.download_corpora
from textblob import TextBlob
blob = TextBlob('The movie was great!')
print(blob.sentiment.polarity)- Performance characteristics on large text volumes or real-time processing scenarios
- Accuracy of sentiment analysis and classification compared to modern transformer-based alternatives
What it is and what it does
TextBlob is a Python library that wraps NLTK and pattern to provide a simplified interface for common natural language processing tasks. It lets you work with text through an intuitive API, extracting linguistic features like parts of speech, noun phrases, and sentiment polarity from strings without deep NLP expertise.
The library handles tokenization, tagging, phrase extraction, and sentiment scoring out of the box. It also supports text classification, spelling correction, word inflection, and n-gram analysis. You create a TextBlob object from a string and access properties like .tags, .noun_phrases, and .sentences.sentiment to get results. It requires downloading linguistic corpora once after installation.
Use it for
- Analyze sentiment polarity of customer reviews or social media posts to gauge positive/negative feedback
- Extract key noun phrases from documents for topic identification or keyword extraction
- Tag parts of speech in text for grammatical analysis or downstream NLP pipelines
- Classify text documents using built-in Naive Bayes or Decision Tree classifiers
- Correct spelling errors and normalize text before further processing
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need straightforward NLP tasks without deep learning complexity.
TextBlob is well-maintained, has no security vulnerabilities, and offers a gentle entry point to text processing. Install it for sentiment analysis, phrase extraction, or basic classification. Skip it if you require state-of-the-art accuracy or modern transformer-based models.
Install
textblob on PyPI
Before you install
Low install friction with a single runtime dependency on nltk. The project is actively maintained with a recent release (27 days old) and a substantial repository history since 2013, indicating stable long-term support.
Requires Python 3.10 or later. The download_corpora step must be run once to fetch required linguistic data before sentiment analysis and other NLP features work.
License in practice
MIT license permits commercial and private use with minimal restrictions, making it suitable for most projects without licensing concerns.
Quickstart
pip install textblob
python -m textblob.download_corpora
from textblob import TextBlob
blob = TextBlob('The movie was great!')
print(blob.sentiment.polarity)Verify before relying
- Performance characteristics on large text volumes or real-time processing scenarios
- Accuracy of sentiment analysis and classification compared to modern transformer-based alternatives
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packagenltk |
| Maintenance | Actively maintained 27 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 7,600,176 / month, #1,717 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Intended Audience :: DevelopersProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Text Processing :: Linguistic |
Evidence: textblob-0.20.1-py3-none-any.whl
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