fast html to text parser (article readability tool) with python3 support
This code is under the Apache License 2.0. http://www.apache.org/licenses/LICENSE-2.0
This is a python port of a ruby port of arc90’s readability project
In few words, Given a html document, it pulls out the main body text and cleans it up. It also can clean up title based on latest readability.js code.
- Based on:
- Latest readability.js ( https://github.com/MHordecki/readability-redux/blob/master/readability/readability.js )
- Ruby port by starrhorne and iterationlabs
- Python port by gfxmonk ( https://github.com/gfxmonk/python-readability , based on BeautifulSoup )
- Decruft effort to move to lxml ( http://www.minvolai.com/blog/decruft-arc90s-readability-in-python/ )
- “BR to P” fix from readability.js which improves quality for smaller texts.
- Github users contributions.
easy_install readability-lxml or pip install readability-lxml
from readability.readability import Document import urllib html = urllib.urlopen(url).read() readable_article = Document(html).summary() readable_title = Document(html).short_title()
python -m readability.readability -u http://pypi.python.org/pypi/readability-lxml
To open resulting page in browser:
python -m readability.readability -b -u http://pypi.python.org/pypi/readability-lxml
Using positive/negative keywords example:
python -m readability.readability -p intro -n newsindex,homepage-box,news-section -u http://python.org
Document() kwarg options:
- debug: output debug messages
- url: will allow adjusting links to be absolute
- positive_keywords: the list of positive search patterns in classes and ids, for example: [“news-item”, “block”]
- negative_keywords: the list of negative search patterns in classes and ids, for example: [“mysidebar”, “related”, “ads”]
- 0.3 Added Document.encoding, positive_keywords and negative_keywords
- 0.4 Added Videos loading and allowed more images per paragraph
- 0.5 Preparing a release to support Python versions 2.6, 2.7, 3.3 and 3.4
- 0.6 Finally a release which supports Python versions 2.6, 2.7, 3.3 and 3.4
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