newspaper Documentation

Technical Documentation: codelucas/newspaper

ℹ️ Provenance: Multi-Tier Ingestion · CodeWiki Reference

Index (`docs/index.rst`)

Newspaper3k: Article scraping & curation

.. image:: https://badge.fury.io/py/newspaper3k.svg
:target: http://badge.fury.io/py/newspaper3k.svg
:alt: Latest version

.. image:: https://travis-ci.org/codelucas/newspaper.svg
:target: http://travis-ci.org/codelucas/newspaper/
:alt: Build status

.. image:: https://coveralls.io/repos/github/codelucas/newspaper/badge.svg?branch=master
:target: https://coveralls.io/github/codelucas/newspaper
:alt: Coverage status

Inspired by requests_ for its simplicity and powered by lxml_ for its speed:

text

"Newspaper is an amazing python library for extracting & curating articles."
-- `tweeted by`_ Kenneth Reitz, Author of `requests`_

"Newspaper delivers Instapaper style article extraction." -- `The Changelog`_

.. _tweeted by: https://twitter.com/kennethreitz/status/419520678862548992
.. _The Changelog: http://thechangelog.com/newspaper-delivers-instapaper-style-article-extraction/

Newspaper is a Python3 library! View on Github here, or, view our deprecated and buggy Python2 branch

.. _Python2 branch: https://github.com/codelucas/newspaper/tree/python-2-head
.. _View on Github here: https://github.com/codelucas/newspaper

A Glance:

.. code-block:: pycon

text

>>> from newspaper import Article

>>> url = 'http://fox13now.com/2013/12/30/new-year-new-laws-obamacare-pot-guns-and-drones/'
>>> article = Article(url)

.. code-block:: pycon

text

>>> article.download()

>>> article.html
'<!DOCTYPE HTML><html itemscope itemtype="http://...'

.. code-block:: pycon

text

>>> article.parse()

>>> article.authors
['Leigh Ann Caldwell', 'John Honway']

>>> article.publish_date
datetime.datetime(2013, 12, 30, 0, 0)

>>> article.text
'Washington (CNN) -- Not everyone subscribes to a New Year's resolution...'

>>> article.top_image
'http://someCDN.com/blah/blah/blah/file.png'

>>> article.movies
['http://youtube.com/path/to/link.com', ...]

.. code-block:: pycon

text

>>> article.nlp()

>>> article.keywords
['New Years', 'resolution', ...]

>>> article.summary
'The study shows that 93% of people ...'

.. code-block:: pycon

text

>>> import newspaper

>>> cnn_paper = newspaper.build('http://cnn.com')

>>> for article in cnn_paper.articles:
>>>     print(article.url)
http://www.cnn.com/2013/11/27/justice/tucson-arizona-captive-girls/
http://www.cnn.com/2013/12/11/us/texas-teen-dwi-wreck/index.html
...

>>> for category in cnn_paper.category_urls():
>>>     print(category)

http://lifestyle.cnn.com
http://cnn.com/world
http://tech.cnn.com
...

>>> cnn_article = cnn_paper.articles[0]
>>> cnn_article.download()
>>> cnn_article.parse()
>>> cnn_article.nlp()
...

.. code-block:: pycon

text

>>> from newspaper import fulltext

>>> html = requests.get(...).text
>>> text = fulltext(html)

Newspaper has seamless language extraction and detection.
If no language is specified, Newspaper will attempt to auto detect a language.

.. code-block:: pycon

text

>>> from newspaper import Article
>>> url = 'http://www.bbc.co.uk/zhongwen/simp/chinese_news/2012/12/121210_hongkong_politics.shtml'

>>> a = Article(url, language='zh') # Chinese

>>> a.download()
>>> a.parse()

>>> print(a.text[:150])
香港行政长官梁振英在各方压力下就其大宅的违章建
筑（僭建）问题到立法会接受质询，并向香港民众道歉。
梁振英在星期二（12月10日）的答问大会开始之际
在其演说中道歉，但强调他在违章建筑问题上没有隐瞒的
意图和动机。 一些亲北京阵营议员欢迎梁振英道歉，
且认为应能获得香港民众接受，但这些议员也质问梁振英有

>>> print(a.title)
港特首梁振英就住宅违建事件道歉

If you are certain that an entire news source is in one language, go ahead and use the same api :)

.. code-block:: pycon

text

>>> import newspaper
>>> sina_paper = newspaper.build('http://www.sina.com.cn/', language='zh')

>>> for category in sina_paper.category_urls():
>>>     print(category)
http://health.sina.com.cn
http://eladies.sina.com.cn
http://english.sina.com
...

>>> article = sina_paper.articles[0]
>>> article.download()
>>> article.parse()

>>> print(article.text)
新浪武汉汽车综合 随着汽车市场的日趋成熟，
传统的“集全家之力抱得爱车归”的全额购车模式已然过时，
另一种轻松的新兴 车模式――金融购车正逐步成为时下消费者购
买爱车最为时尚的消费理念，他们认为，这种新颖的购车
模式既能在短期内
...

>>> print(article.title)
两年双免0手续0利率 科鲁兹掀背金融轻松购_武汉车市_武汉汽
车网_新浪汽车_新浪网

Documentation

Check out The Documentation_ for full and detailed guides using newspaper.

Interested in adding a new language for us? Refer to: Docs - Adding new languages <https://newspaper.readthedocs.io/en/latest/user_guide/advanced.html#adding-new-languages>_

Features

Multi-threaded article download framework
News url identification
Text extraction from html
Top image extraction from html
All image extraction from html
Keyword extraction from text
Summary extraction from text
Author extraction from text
Google trending terms extraction
Works in 10+ languages (English, Chinese, German, Arabic, ...)

.. code-block:: pycon

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>>> import newspaper
>>> newspaper.languages()

Your available languages are:
input code      full name

  ar              Arabic
  be              Belarusian
  bg              Bulgarian
  da              Danish
  de              German
  el              Greek
  en              English
  es              Spanish
  et              Estonian
  fa              Persian
  fi              Finnish
  fr              French
  he              Hebrew
  hi              Hindi
  hr              Croatian
  hu              Hungarian
  id              Indonesian
  it              Italian
  ja              Japanese
  ko              Korean
  lt              Lithuanian
  mk              Macedonian
  nb              Norwegian (Bokmål)
  nl              Dutch
  no              Norwegian
  pl              Polish
  pt              Portuguese
  ro              Romanian
  ru              Russian
  sl              Slovenian
  sr              Serbian
  sv              Swedish
  sw              Swahili
  th              Thai
  tr              Turkish
  uk              Ukrainian
  vi              Vietnamese
  zh              Chinese

Get it now

Run ✅ pip3 install newspaper3k ✅

NOT ⛔ pip3 install newspaper ⛔

On python3 you must install newspaper3k, not newspaper. newspaper is our python2 library.
Although installing newspaper is simple with pip <http://www.pip-installer.org/>_, you will
run into fixable issues if you are trying to install on ubuntu.

If you are on Debian / Ubuntu, install using the following:

Install pip3 command needed to install newspaper3k package::

$ sudo apt-get install python3-pip
Python development version, needed for Python.h::

$ sudo apt-get install python-dev
lxml requirements::

$ sudo apt-get install libxml2-dev libxslt-dev
For PIL to recognize .jpg images::

$ sudo apt-get install libjpeg-dev zlib1g-dev libpng12-dev

NOTE: If you find problem installing libpng12-dev, try installing libpng-dev.

Download NLP related corpora::

$ curl https://raw.githubusercontent.com/codelucas/newspaper/master/download_corpora.py | python3
Install the distribution via pip::

$ pip3 install newspaper3k

If you are on OSX, install using the following, you may use both homebrew or macports:

text

$ brew install libxml2 libxslt

$ brew install libtiff libjpeg webp little-cms2

$ pip3 install newspaper3k

$ curl https://raw.githubusercontent.com/codelucas/newspaper/master/download_corpora.py | python3

Otherwise, install with the following:

NOTE: You will still most likely need to install the following libraries via your package manager

PIL: libjpeg-dev zlib1g-dev libpng12-dev
lxml: libxml2-dev libxslt-dev
Python Development version: python-dev

text

$ pip3 install newspaper3k

$ curl https://raw.githubusercontent.com/codelucas/newspaper/master/download_corpora.py | python3

Using python 2.X? We support python 2, however development work has stopped on the 2.X branch for a
few years now so it is behind in features and is more buggy. See python 2 installation instructions here <https://github.com/codelucas/newspaper/blob/python-2-head/README.rst/>_

Development

If you'd like to contribute and hack on the newspaper project, feel free to clone
a development version of this repository locally::

text

git clone git://github.com/codelucas/newspaper.git

Once you have a copy of the source, you can embed it in your Python package,
or install it into your site-packages easily::

text

$ pip3 install -r requirements.txt
$ python3 setup.py install

Feel free to give our testing suite a shot, everything is mocked!::

text

$ python3 tests/unit_tests.py

Planning on tweaking our full-text algorithm? Add the fulltext parameter::

text

$ python3 tests/unit_tests.py fulltext

User Guide

.. toctree::
:maxdepth: 2

user_guide/quickstart
user_guide/advanced

Demo

View a working online demo here: http://newspaper-demo.herokuapp.com
This is another working online demo: http://newspaper.chinazt.cc/

LICENSE

Authored and maintained by Lucas Ou-Yang_.

Parse.ly_ sponsored some work on newspaper, specifically focused on
automatic extraction.

Newspaper uses a lot of python-goose's_ parsing code. View their license here_.

Please feel free to email & contact me_ if you run into issues or just would like
to talk about the future of this library and news extraction in general!

krTheme Sphinx Style

This repository contains sphinx styles Kenneth Reitz uses in most of
his projects. It is a derivative of Mitsuhiko's themes for Flask and Flask related
projects. To use this style in your Sphinx documentation, follow
this guide:

put this folder as _themes into your docs folder. Alternatively
you can also use git submodules to check out the contents there.
add this to your conf.py: ::

sys.path.append(os.path.abspath('_themes'))
html_theme_path = ['_themes']
html_theme = 'flask'

The following themes exist:

kr
the standard flask documentation theme for large projects

kr_small
small one-page theme. Intended to be used by very small addon libraries.

User Guide Advanced (`docs/user_guide/advanced.rst`)

.. _advanced:

Advanced

This section of the docs shows how to do some useful but advanced things
with newspaper.

Multi-threading article downloads

Downloading articles one at a time is slow. But spamming a single news source
like cnn.com with tons of threads or with ASYNC-IO will cause rate limiting
and also doing that is very mean.

We solve this problem by allocating 1-2 threads per news source to both greatly
speed up the download time while being respectful.

.. code-block:: pycon

text

>>> import newspaper
>>> from newspaper import news_pool

>>> slate_paper = newspaper.build('http://slate.com')
>>> tc_paper = newspaper.build('http://techcrunch.com')
>>> espn_paper = newspaper.build('http://espn.com')

>>> papers = [slate_paper, tc_paper, espn_paper]
>>> news_pool.set(papers, threads_per_source=2) # (3*2) = 6 threads total
>>> news_pool.join()

At this point, you can safely assume that download() has been
called on every single article for all 3 sources.

>>> print(slate_paper.articles[10].html)
u'<html> ...'

Keeping Html of main body article

Keeping the html of just an article's body text is helpbut because it allows you
to retain some of the semantic information in the html. Also it will help if you
end up displaying the extracted article somehow.

Here is how to do so:

.. code-block:: pycon

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>>> from newspaper import Article

>>> a = Article('http://www.cnn.com/2014/01/12/world/asia/north-korea-charles-smith/index.html'
    , keep_article_html=True)

>>> a.download()
>>> a.parse()

>>> a.article_html
u' \n**(CNN)** -- Charles Smith insisted Sunda...'

The lxml (dom object) and top_node (chunk of dom that contains our 'Article') are also
cached incase users would like to use them.

Access after parsing() with:

.. code-block:: pycon

text

>>> a.download()
>>> a.parse()
>>> a.clean_dom
<lxml object ...  >

>>> a.clean_top_node
<lxml object ...  >

Adding new languages

First, please reference this file and read from the highlighted line all the way
down to the end of the file.

https://github.com/codelucas/newspaper/blob/master/newspaper/text.py#L57 <https://github.com/codelucas/newspaper/blob/master/newspaper/text.py#L57>_

One aspect of our text extraction algorithm revolves around counting the number of
stopwords present in a text. Stopwords are: some of the most common, short
function words, such as the, is, at, which, and on in a language.

Reference this line to see it in action:
https://github.com/codelucas/newspaper/blob/master/newspaper/extractors.py#L668 <https://github.com/codelucas/newspaper/blob/master/newspaper/extractors.py#L668>_

So for latin languages, it is pretty basic. We first provide a list of
stopwords in stopwords-<language-code>.txt form. We then take some input text and
tokenize it into words by splitting the white space. After that we perform some
bookkeeping and then proceed to count the number of stopwords present.

For non-latin languages, as you may have noticed in the code above, we need to
tokenize the words in a different way, splitting by whitespace simply won't work for
languages like Chinese or Arabic. For the Chinese language we are using a whole new
open source library called jieba to split the text into words. For arabic we are
using a special nltk tokenizer to do the same job.

So, to add full text extraction to a new (non-latin) language, we need:

Push up a stopwords file in the format of stopwords-<2-char-language-code>.txt
in newspaper/resources/text/.
Provide a way of splitting/tokenizing text in that foreign language into words.
Here are some examples for Chinese, Arabic, English <https://github.com/codelucas/newspaper/blob/master/newspaper/text.py#L105>_

For latin languages:

Push up a stopwords file in the format of stopwords-<2-char-language-code>.txt
in newspaper/resources/text/. and we are done!

Finally, add the new language to the list of available languages in the following files:

README.rst
docs/index.rst
docs/user_guide/quickstart.rst
newspaper/utils.py

Explicitly building a news source

Instead of using the newspaper.build(..) api, we can take one step lower
into newspaper's Source api.

.. code-block:: pycon

text

>>> from newspaper import Source
>>> cnn_paper = Source('http://cnn.com')

>>> print(cnn_paper.size()) # no articles, we have not built the source
0

>>> cnn_paper.build()
>>> print(cnn_paper.size())
3100

Note the build() method above. You may go lower level and de-abstract it
for absolute control over how your sources are constructed.

.. code-block:: pycon

text

>>> cnn_paper = Source('http://cnn.com')
>>> cnn_paper.download()
>>> cnn_paper.parse()
>>> cnn_paper.set_categories()
>>> cnn_paper.download_categories()
>>> cnn_paper.parse_categories()
>>> cnn_paper.set_feeds()
>>> cnn_paper.download_feeds()
>>> cnn_paper.generate_articles()

>>> print(cnn_paper.size())
3100

And voila, we have mimic'd the build() method. In the above sequence,
every method is dependant on the method above it. Stop whenever you wish.

Parameters and Configurations

Newspaper provides two api's for users to configure their Article and
Source objects. One is via named parameter passing recommended and
the other is via Config objects.

Here are some named parameter passing examples:

.. code-block:: pycon

text

>>> import newspaper
>>> from newspaper import Article, Source

>>> cnn = newspaper.build('http://cnn.com', language='en', memoize_articles=False)

>>> article = Article(url='http://cnn.com/french/...', language='fr', fetch_images=False)

>>> cnn = Source(url='http://latino.cnn.com/...', language='es', request_timeout=10,
                                                            number_threads=20)

Here are some examples of how Config objects are passed.

.. code-block:: pycon

text

>>> import newspaper
>>> from newspaper import Config, Article, Source

>>> config = Config()
>>> config.memoize_articles = False

>>> cbs_paper = newspaper.build('http://cbs.com', config)

>>> article_1 = Article(url='http://espn/2013/09/...', config)

>>> cbs_paper = Source('http://cbs.com', config)

Here is a full list of the configuration options:

keep_article_html, default False, "set to True if you want to preserve html of body text"

http_success_only, default True, "set to False to capture non 2XX responses as well"

MIN_WORD_COUNT, default 300, "num of word tokens in article text"

MIN_SENT_COUNT, default 7, "num of sentence tokens"

MAX_TITLE, default 200, "num of chars in article title"

MAX_TEXT, default 100000, "num of chars in article text"

MAX_KEYWORDS, default 35, "num of keywords in article"

MAX_AUTHORS, default 10, "num of author names in article"

MAX_SUMMARY, default 5000, "num of chars of the summary"

MAX_SUMMARY_SENT, default 5, "num of sentences in summary"

MAX_FILE_MEMO, default 20000, "python setup.py sdist bdist_wininst upload"

memoize_articles, default True, "cache and save articles run after run"

fetch_images, default True, "set this to false if you don't care about getting images"

follow_meta_refresh, default False, "follows a redirect url in a meta refresh html tag"

image_dimension_ration, default 16/9.0, "max ratio for height/width, we ignore if greater"

language, default 'en', "run newspaper.languages() to see available options."

browser_user_agent, default 'newspaper/%s' % version

request_timeout, default 7

number_threads, default 10, "number of threads when mthreading"

verbose, default False, "turn this on when debugging"

You may notice other config options in the newspaper/configuration.py file,
however, they are private, please do not toggle them.

Caching

TODO

Specifications

Here, we will define exactly how newspaper handles a lot of the data extraction.

TODO

User Guide Contributors (`docs/user_guide/contributors.rst`)

.. _contributors:

Contributors

Maintained and authored by:

Lucas Ou-Yang -- http://codelucas.com, [email protected]

Thanks to the following contributors:

https://github.com/codelucas/newspaper/graphs/contributors

Newspaper relied on some code of a few other open source projects:

Thanks to all who have contributed to python-goose.
You can find the contributors list here:
https://github.com/grangier/python-goose/graphs/contributors

Thanks to all who have contributed to PyTeaser.
You can find the contributors list here:
https://github.com/xiaoxu193/PyTeaser/graphs/contributors

Thanks to all who have contributed to gravity-goose.
You can find the contributors list here:
https://github.com/GravityLabs/goose/graphs/contributors

Thanks to all who have contributed to jieba.
You can find the contributors list here:
https://github.com/fxsjy/jieba/graphs/contributors

Thanks to all who have contributed to nltk.
You can find the contributors list here:
https://github.com/nltk/nltk/graphs/contributors

Thanks to all who have contributed to lxml.
You can find the contributors list here:
http://lxml.de/credits.html

Thanks to all who have contributed to requests.
You can find the contributors list here:
https://github.com/kennethreitz/requests/graphs/contributors

User Guide Quickstart (`docs/user_guide/quickstart.rst`)

.. _quickstart:

Quickstart

Eager to get started? This page gives a good introduction in how to get started
with newspaper. This assumes you already have newspaper installed. If you do not,
head over to the :ref:Installation section.

Building a news source

Source objects are an abstraction of online news media websites like CNN or ESPN.
You can initialize them in two different ways.

Building a Source will extract its categories, feeds, articles, brand, and description for you.

You may also provide configuration parameters like language, browser_user_agent, and etc seamlessly. Navigate to the :ref:advanced <advanced> section for details.

.. code-block:: pycon

text

>>> import newspaper
>>> cnn_paper = newspaper.build('http://cnn.com')

>>> sina_paper = newspaper.build('http://www.lemonde.fr/', language='fr')

However, if needed, you may also play with the lower level Source object as described
in the :ref:advanced <advanced> section.

Extracting articles

Every news source has a set of recent articles.

The following examples assume that a news source has been
initialized and built.

.. code-block:: pycon

text

>>> 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'
...

>>> print(cnn_paper.size()) # cnn has 3100 articles
3100

Article caching

By default, newspaper caches all previously extracted articles and eliminates any
article which it has already extracted.

This feature exists to prevent duplicate articles and to increase extraction speed.

.. code-block:: pycon

text

>>> cbs_paper = newspaper.build('http://cbs.com')
>>> cbs_paper.size()
1030

>>> cbs_paper = newspaper.build('http://cbs.com')
>>> cbs_paper.size()
2

The return value of cbs_paper.size() changes from 1030 to 2 because when we first
crawled cbs we found 1030 articles. However, on our second crawl, we eliminate all
articles which have already been crawled.

This means 2 new articles have been published since our first extraction.

You may opt out of this feature with the memoize_articles parameter.

You may also pass in the lower levelConfig objects as covered in the :ref:advanced <advanced> section.

.. code-block:: pycon

text

>>> import newspaper

>>> cbs_paper = newspaper.build('http://cbs.com', memoize_articles=False)
>>> cbs_paper.size()
1030

>>> cbs_paper = newspaper.build('http://cbs.com', memoize_articles=False)
>>> cbs_paper.size()
1030

Extracting Source categories

.. code-block:: pycon

text

>>> for category in cnn_paper.category_urls():
>>>     print(category)

u'http://lifestyle.cnn.com'
u'http://cnn.com/world'
u'http://tech.cnn.com'
...

Extracting Source feeds

.. code-block:: pycon

text

>>> for feed_url in cnn_paper.feed_urls():
>>>     print(feed_url)

u'http://rss.cnn.com/rss/cnn_crime.rss'
u'http://rss.cnn.com/rss/cnn_tech.rss'
...

Extracting Source brand & description

.. code-block:: pycon

text

>>> print(cnn_paper.brand)
u'cnn'

>>> print(cnn_paper.description)
u'CNN.com delivers the latest breaking news and information on the latest...'

News Articles

Article objects are abstractions of news articles. For example, a news Source
would be CNN while a news Article would be a specific CNN article.
You may reference an Article from an existing news Source or initialize
one by itself.

Referencing it from a Source.

.. code-block:: pycon

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>>> first_article = cnn_paper.articles[0]

Initializing an Article by itself.

.. code-block:: pycon

text

>>> from newspaper import Article
>>> first_article = Article(url="http://www.lemonde.fr/...", language='fr')

Note the similar language= named paramater above. All the config parameters as described for Source objects also apply for Article objects! Source and Article objects have a very similar api.

Initializing an Article with the particular content-type ignoring.

There is option to skip loading of articles with particular content-type,
that can be useful if it is not desired to have delays because of long PDF resources.
The default html value for the particular content type can be provided and then used in order to define the actual content-type of the article

.. code-block:: pycon

text

>>> from newspaper import Article
>>> pdf_defaults = {"application/pdf": "%PDF-",
                  "application/x-pdf": "%PDF-",
                  "application/x-bzpdf": "%PDF-",
                  "application/x-gzpdf": "%PDF-"}
>>> pdf_article = Article(url='https://www.adobe.com/pdf/pdfs/ISO32000-1PublicPatentLicense.pdf',
                                        ignored_content_types_defaults=pdf_defaults)
>>> pdf_article.download()
>>> print(pdf_article.html)
%PDF-

There are endless possibilities on how we can manipulate and build articles.

Downloading an Article

We begin by calling download() on an article. If you are interested in how to
quickly download articles concurrently with multi-threading check out the
:ref:advanced <advanced> section.

.. code-block:: pycon

text

>>> first_article = cnn_paper.articles[0]

>>> first_article.download()

>>> print(first_article.html)
u'<!DOCTYPE HTML><html itemscope itemtype="http://...'

>>> print(cnn_paper.articles[7].html)
u'' fail, not downloaded yet

Parsing an Article

You may also extract meaningful content from the html, like authors and body-text.
You must have called download() on an article before calling parse().

.. code-block:: pycon

text

>>> first_article.parse()

>>> print(first_article.text)
u'Three sisters who were imprisoned for possibly...'

>>> print(first_article.top_image)
u'http://some.cdn.com/3424hfd4565sdfgdg436/

>>> print(first_article.authors)
[u'Eliott C. McLaughlin', u'Some CoAuthor']

>>> print(first_article.title)
u'Police: 3 sisters imprisoned in Tucson home'

>>> print(first_article.images)
['url_to_img_1', 'url_to_img_2', 'url_to_img_3', ...]

>>> print(first_article.movies)
['url_to_youtube_link_1', ...] # youtube, vimeo, etc

Performing NLP on an Article

Finally, you may extract out natural language properties from the text.
You must have called both download() and parse() on the article
before calling nlp().

As of the current build, nlp() features only work on western languages.

.. code-block:: pycon

text

>>> first_article.nlp()

>>> print(first_article.summary)
u'...imprisoned for possibly a constant barrage...'

>>> print(first_article.keywords)
[u'music', u'Tucson', ... ]

>>> print(cnn_paper.articles[100].nlp()) # fail, not been downloaded yet
Traceback (...
ArticleException: You must parse an article before you try to..

nlp() is expensive, as is parse(), make sure you actually need them before calling them on
all of your articles! In some cases, if you just need urls, even download() is not necessary.

Easter Eggs

Here are random but hopefully useful features! hot() returns a list of the top
trending terms on Google using a public api. popular_urls() returns a list
of popular news source urls.. In case you need help choosing a news source!

.. code-block:: pycon

text

>>> import newspaper

>>> newspaper.hot()
['Ned Vizzini', Brian Boitano', Crossword Inventor', 'Alex & Sierra', ... ]

>>> newspaper.popular_urls()
['http://slate.com', 'http://cnn.com', 'http://huffingtonpost.com', ... ]

>>> newspaper.languages()

Your available languages are:
input code      full name

  ar              Arabic
  de              German
  en              English
  es              Spanish
  fr              French
  he              Hebrew
  it              Italian
  ko              Korean
  no              Norwegian
  fa              Persian
  pl              Polish
  pt              Portuguese
  sv              Swedish
  zh              Chinese
  uk              Ukrainian
  sw              Swahili
  bg              Bulgarian
  hr              Croatian
  ro              Romanian
  sl              Slovenian
  sr              Serbian
  et              Estonian
  ja              Japanese
  be              Belarusian
  lt              Lithuanian

--- METRICS ---

Files Extracted: 5
Estimated Token Budget: ~7671 tokens
Canonical Reference: https://codewiki.google/github.com/codelucas/newspaper

Technical Documentation: codelucas/newspaper

Index (`docs/index.rst`) Copy Section

Newspaper3k: Article scraping & curation

A Glance: Copy Chapter

Documentation Copy Chapter

Features Copy Chapter

Get it now Copy Chapter

Development Copy Chapter

User Guide Copy Chapter

Demo Copy Chapter

LICENSE Copy Chapter

Sponsored by SerpApi Copy Chapter

Themes README (`docs/_themes/README.rst`) Copy Section

krTheme Sphinx Style

User Guide Advanced (`docs/user_guide/advanced.rst`) Copy Section

Advanced

Multi-threading article downloads Copy Chapter

Keeping Html of main body article Copy Chapter

Adding new languages Copy Chapter

Explicitly building a news source Copy Chapter

Parameters and Configurations Copy Chapter

Caching Copy Chapter

Specifications Copy Chapter

User Guide Contributors (`docs/user_guide/contributors.rst`) Copy Section

Contributors

Maintained and authored by: Copy Chapter

Thanks to the following contributors: Copy Chapter

Newspaper relied on some code of a few other open source projects: Copy Chapter

User Guide Quickstart (`docs/user_guide/quickstart.rst`) Copy Section

Quickstart

Building a news source Copy Chapter

Extracting articles Copy Chapter

Article caching Copy Chapter

Extracting Source categories Copy Chapter

Extracting Source feeds Copy Chapter

Extracting Source brand & description Copy Chapter

News Articles Copy Chapter

Downloading an Article Copy Chapter

Parsing an Article Copy Chapter

Performing NLP on an Article Copy Chapter

Easter Eggs Copy Chapter

Explore Related Technologies & Topics

Index (`docs/index.rst`)

A Glance:

Documentation

Features

Get it now

Development

User Guide

Demo

LICENSE

Sponsored by SerpApi

Themes README (`docs/_themes/README.rst`)

User Guide Advanced (`docs/user_guide/advanced.rst`)

Multi-threading article downloads

Keeping Html of main body article

Adding new languages

Explicitly building a news source

Parameters and Configurations

Caching

Specifications

User Guide Contributors (`docs/user_guide/contributors.rst`)

Maintained and authored by:

Thanks to the following contributors:

Newspaper relied on some code of a few other open source projects:

User Guide Quickstart (`docs/user_guide/quickstart.rst`)

Building a news source

Extracting articles

Article caching

Extracting Source categories

Extracting Source feeds

Extracting Source brand & description

News Articles

Downloading an Article

Parsing an Article

Performing NLP on an Article

Easter Eggs