Simplified python article discovery & extraction.
Project description
Inspired by requests for its simplicity and powered by lxml for its speed; newspaper is a Python 2 library for extracting & curating articles from the web.
Newspaper wants to change the way people handle article extraction with a new, more precise layer of abstraction. Newspaper caches whatever it can for speed. Also, everything is in unicode
Please refer to The Documentation for a quickstart tutorial!
A Glance:
>>> import newspaper
>>> cnn_paper = newspaper.build('http://cnn.com')
>>> for article in cnn_paper.articles:
>>> print article.url
u'http://www.cnn.com/2013/11/27/justice/tucson-arizona-captive-girls/'
u'http://www.cnn.com/2013/12/11/us/texas-teen-dwi-wreck/index.html'
...
>>> for category in cnn_paper.category_urls():
>>> print category
u'http://lifestyle.cnn.com'
u'http://cnn.com/world'
u'http://tech.cnn.com'
...
>>> article = cnn_paper.articles[0]
>>> article.download()
>>> article.html
u'<!DOCTYPE HTML><html itemscope itemtype="http://...'
>>> article.parse()
>>> article.authors
[u'Leigh Ann Caldwell', 'John Honway']
>>> article.text
u'Washington (CNN) -- Not everyone subscribes to a New Year's resolution...'
>>> article.nlp()
>>> article.keywords
['New Years', 'resolution', ...]
>>> article.summary
u'The study shows that 93% of people ...'
Documentation
Check out The Documentation for full and detailed guides using newspaper.
Features
News url identification
Text extraction from html
Keyword extraction from text
Summary extraction from text
Author extraction from text
Top image extraction from html
All image extraction from html
Multi-threaded article download framework
Google trending terms extraction
Get it now
$ pip install newspaper IMPORTANT If you know for sure that you'll use the natural language features, nlp(), you must download some separate nltk corpora below. You must download everything in python 2.6 - 2.7! $ curl https://raw.github.com/codelucas/newspaper/master/download_corpora.py | python2.7
Todo List
Add a “follow_robots.txt” option in the config object.
Bake in the CSSSelect and BeautifulSoup dependencies
- 0.0.4 - Fully integrated python-goose library into newspaper. Article objects
now have much more options. All configurations are now based on Configuration() objects which can be passed into Source or Article objects. Default configuration setups make this easy. Added simple multithreading article download framework.
Project details
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