python-readability: Extract Clean Main Content from HTML Documents
This repository profile is provided by osrepos.com, an open source repository discovery platform.

Summary
python-readability is a fast Python port of arc90's Readability tool, designed to extract and clean the main body text and title from any given HTML document. It provides an efficient way to process web content, making it easier to focus on essential information. This library is regularly updated to match the latest readability.js functionalities, ensuring modern compatibility and performance.
Repository Information
Topics
Click on any tag to explore related repositories
Use at your own risk
OSRepos shares public repositories for knowledge and discovery only. Any installation, execution, configuration, or use of code from these repositories is the user's own responsibility. Always review the repository, source code, dependencies, licenses, and security implications before running or installing anything. OSRepos is not responsible for issues, damages, or losses resulting from third-party repositories.
Introduction
python-readability is a powerful and fast Python library that allows developers to extract the main body text and title from any HTML document. It is a robust port of arc90's original Readability project, continuously updated to align with the latest readability.js features. This tool is invaluable for tasks requiring clean, focused content extraction from web pages, such as building RSS feeds, content aggregators, or text analysis tools.
Installation
Installation is straightforward using pip or conda.
$ pip install readability-lxml
Alternatively, with conda:
$ conda install -c conda-forge readability-lxml
Examples
Using python-readability is simple. Here's a quick example demonstrating how to fetch a web page and extract its title and summary:
import requests
from readability import Document
response = requests.get('http://example.com')
doc = Document(response.content)
print(doc.title())
# Output: 'Example Domain'
print(doc.summary())
# Output: "<html><body><div><body id=\"readabilityBody\">\n<div>\n <h1>Example Domain</h1>\n\n<p>This domain is established to be used for illustrative examples in documents. You may\nuse this\n domain in examples without prior coordination or asking for permission.</p>\n\n <p><a href=\"http://www.iana.org/domains/example\">More information...</a></p>\n</div>\n\n</body>\n</div></body></html>"
Why use it
python-readability stands out for several reasons:
- Speed and Efficiency: It's a fast implementation, crucial for processing large volumes of data.
- Modern Compatibility: Regularly updated to match
readability.js, ensuring it works well with contemporary web content. - Comprehensive Extraction: Beyond just text, it can extract titles, handle images (including saving all images with
keep_all_images=True), and supports CJK characters. - Python 3.x Support: Fully compatible with a wide range of Python 3 versions (3.8 - 3.13).
- Clean Output: Replaces XHTML output with HTML5 in
summary()calls, providing modern and cleaner HTML. - Active Development: The change log indicates continuous improvements and bug fixes, reflecting an actively maintained project.
Links
- GitHub Repository: https://github.com/buriy/python-readability
- PyPI Package: https://pypi.python.org/pypi/readability-lxml
Related repositories
Similar repositories that may be relevant next.

oh-my-hermes: Enhance Hermes Agent with Advanced AI Workflow and Memory
September 17, 2026
oh-my-hermes is an all-in-one plugin designed to significantly enhance the Hermes Agent. It provides advanced coding intelligence, a robust long-term memory system, and optimized workflow packages, transforming standard Hermes requests into structured, actionable tasks with clear operational layers.
ASC: A Super Fast Android Decompiler for Mobile Reverse Engineering
September 17, 2026
ASC is an innovative and exceptionally fast Android decompiler front-end, specifically designed for mobile researchers and agents. It redefines traditional decompilation by directly querying compiled artifacts, offering on-demand code extraction and analysis without heavy preprocessing. This approach results in significantly reduced memory usage and lightning-fast performance, even on large APKs.

Open Index: A Deterministic Memory Layer for Your AI Agents
September 16, 2026
Open Index is a powerful tool for building domain-specific, accurate, and structured data that AI agents can effectively operate on. It enables the creation of a "brain," a searchable and continuously improving context graph tailored to any domain. This system ensures agents have access to reliable, up-to-date information, enhancing their capabilities and decision-making processes.
tooltrim: Drastically Reduce LLM Agent Tool Output Tokens, Improve Accuracy
September 16, 2026
tooltrim provides drop-in compression for LLM agent tool outputs, drastically cutting tokens while often improving answer accuracy. This provider-agnostic solution offers content-aware compression, faithfulness benchmarks, and seamless integration with popular frameworks or as an OpenAI-compatible proxy.
Source repository
Open the original repository on GitHub.
15 counted GitHub visits