trafilatura

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从网页抓取正文和元数据的 Python 库与命令行工具，支持爬取、解析并导出为 CSV、JSON、Markdown 等格式，适合构建语料库和 RAG 数据。

Python & Command-line tool to gather text and metadata on the Web: Crawling, scraping, extraction, output as CSV, JSON, HTML, MD, TXT, XML

v2.3.1发布于 2026-10-06 19:31 UTC7,118star +27 / 7 天501fork同步于 2026-11-10 23:34 UTC

网页正文提取语料库构建网页爬虫 HTML转Markdown RAG数据

对比 GitHub 官网 article-extractor corpus-builder corpus-tools crawler html-to-markdown

怎么上手

由 README 提炼，执行前请确认

原文

pip install trafilatura

硬件要求按 README 说明

README 未说明，未提及 GPU 或显存要求

下载：源码 zip·GitHub Releases（安装包）本站不镜像安装包

项目说明

由 README 自动翻译提炼

没人工点评？写下你的经验

从网页抓取正文与元数据的 Python 库和命令行工具，把原始 HTML 变成结构化数据

从网页抓取正文和元数据的 Python 库与命令行工具，支持爬取、解析并导出为 CSV、JSON、Markdown 等格式，适合构建语料库和 RAG 数据。

核心能力

用规则提取器抽取正文，jusText 与 readability-lxml 兜底
提取标题、作者、日期、站点名、分类标签等元数据
支持 sitemap 与 ATOM/JSON/RSS 订阅源发现链接并去重
并行处理在线 URL 与本地 HTML 文件
输出 TXT、Markdown、CSV、JSON、HTML、XML 及 XML-TEI

容易踩的坑

README 未给出命令行用法示例，需查阅官方文档的 CLI 页面；语言检测与速度优化属于可选附加组件，需另行启用

内容由模型根据 README 生成，可能不完整或不准确，以官方文档为准。看原文 README

用户点评

登录用户的真实使用记录，可按版本和硬件筛选

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README 原文

未翻译

在 GitHub 打开

Trafilatura: Discover Web Content, Extract Text and Metadata

>>> from trafilatura import fetch_url, extract
>>> downloaded = fetch_url("https://github.blog/2019-03-29-leader-spotlight-erin-spiceland/")
>>> extract(downloaded)
'Erin Spiceland is a software engineer and ...'
>>> extract(downloaded, output_format="json", with_metadata=True)
'{"title": "Leader spotlight: Erin Spiceland", "author": "Jessica Rudder", "text": "Erin Spiceland is a software engineer and ..."}'

Introduction

Trafilatura is a comprehensive Python package and command-line tool designed to gather text from the Web and turn raw HTML into structured, meaningful data. It includes all necessary discovery and text processing components to perform web crawling, downloads, scraping, and extraction of main texts, metadata and comments. It aims at staying handy and modular: no database is required, the output can be converted to commonly used formats.

Going from raw HTML to essential parts, it focuses on the actual content, avoids noise caused by recurring elements (headers, footers, boilerplate), and makes sense of the data and metadata. The extractor strikes a balance between limiting noise (precision) and including all valid parts (recall). It is robust and reasonably fast.

Trafilatura is widely used across thousands of projects, including by HuggingFace, IBM, Microsoft Research, NVIDIA, the Allen Institute for AI, Stanford, and the Internet Archive.

Features

Advanced web crawling and text discovery:
- Support for sitemaps (TXT, XML) and feeds (ATOM, JSON, RSS)
- Smart crawling and URL management (filtering and deduplication)
Parallel processing of online and offline input:
- Live URLs, efficient and polite processing of download queues
- Previously downloaded HTML files and parsed HTML trees
Robust and configurable extraction of key elements:
- Main text (own rule-based extractor with jusText and readability-lxml as fallbacks)
- Metadata (title, author, date, site name, categories and tags)
- Formatting and structure: paragraphs, titles, lists, quotes, code, line breaks, in-line text formatting
- Optional elements: comments, links, images, tables
- Optional add-ons: language detection, speed optimizations
Multiple output formats:
- TXT and Markdown
- CSV
- JSON
- HTML, XML and XML-TEI

Evaluation

Trafilatura consistently outperforms other open-source libraries in text extraction benchmarks. For more information see the benchmark section and the evaluation readme to run the evaluation with the latest data and packages.

Other evaluations

Most efficient open-source library in ScrapingHub's article extraction benchmark
Best overall tool according to Bien choisir son outil d'extraction de contenu à partir du Web (Lejeune & Barbaresi 2020)
Best single tool by ROUGE-LSum Mean F1 Page Scores in An Empirical Comparison of Web Content Extraction Algorithms (Bevendorff et al. 2023)

Documentation

Getting started with Trafilatura is straightforward. For more information and detailed guides, visit Trafilatura's documentation:

Installation
Usage: On the command-line, With Python, With R
Core Python functions
Interactive Python Notebook: Trafilatura Overview (in the repository)
Tutorials and use cases

See the video tutorials playlist (multiple languages).

License

This package is distributed under the Apache 2.0 license.

Versions prior to v1.8.0 are under GPLv3+ license.

Contributing

Contributions of all kinds are welcome. Visit the Contributing page for more information. Bug reports can be filed on the dedicated issue page.

Many thanks to the contributors who extended the docs or submitted bug reports, features and bugfixes!

Support

If you value this software or depend on it for your product, consider sponsoring it and contributing to its codebase. Your support on GitHub or ko-fi.com will help maintain and enhance this package.

Context

This work started as a PhD project at the crossroads of linguistics and NLP. This expertise has been instrumental in shaping Trafilatura over the years. Initially launched to create text databases for research purposes at the Berlin-Brandenburg Academy of Sciences (DWDS and ZDL units), this package continues to be maintained and its future depends on community support.

Trafilatura is an Italian word for wire drawing symbolizing the refinement and conversion process. It is also the way shapes of pasta are formed.

Author

Reach out via the software repository or the contact page for inquiries, collaborations, or feedback. See also social networks for the latest updates.

Barbaresi, A. Trafilatura: A Web Scraping Library and Command-Line Tool for Text Discovery and Extraction, Proceedings of ACL/IJCNLP 2021: System Demonstrations, 2021, p. 122-131.
Barbaresi, A. "Generic Web Content Extraction with Open-Source Software", Proceedings of KONVENS 2019, Kaleidoscope Abstracts, 2019.
Barbaresi, A. "Efficient construction of metadata-enhanced web corpora", Proceedings of the 10th Web as Corpus Workshop (WAC-X), 2016.

Citing Trafilatura

Trafilatura is widely used in the academic domain, chiefly for data acquisition. Here is how to cite it:

@inproceedings{barbaresi-2021-trafilatura,
  title = {{Trafilatura: A Web Scraping Library and Command-Line Tool for Text Discovery and Extraction}},
  author = "Barbaresi, Adrien",
  booktitle = "Proceedings of the Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations",
  pages = "122--131",
  publisher = "Association for Computational Linguistics",
  url = "https://aclanthology.org/2021.acl-demo.15",
  year = 2021,
}

Software ecosystem

Jointly developed plugins and additional packages also contribute to the field of web data extraction and analysis:

Corresponding posts can be found on Bits of Language.