Metadata-Version: 2.1
Name: articlequality
Version: 0.4.2
Summary: A library for performing automatic detection of assessment classes of Wikipedia articles.
Home-page: https://github.com/wikimedia/articlequality
Author: Aaron Halfaker / Morten Warncke-Wang
Author-email: ahalfaker@wikimedia.org
License: MIT
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Text Processing :: Linguistic
Classifier: Topic :: Text Processing :: General
Classifier: Topic :: Utilities
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/markdown
Requires-Dist: mwapi
Requires-Dist: mwbase (<0.1.999,>=0.1.0)
Requires-Dist: mwreverts
Requires-Dist: mwtypes
Requires-Dist: mwxml (>=0.3.3)
Requires-Dist: revscoring (<2.6.999,>=2.6.7)

# Wikipedia article quality classification

This library provides a set of utilities for performing automatic detection of
assessment classes of Wikipedia articles.  For more information, see the full
documentation at https://articlequality.readthedocs.io .

**Compatible with Python 3.x only.**  Sorry.

* **Install:** ``pip install articlequality``
* **Models:** https://github.com/wikimedia/articlequality/tree/master/models
* **Documentation:** https://articlequality.readthedocs.io

## Basic usage

    >>> import articlequality
    >>> from revscoring import Model
    >>>
    >>> scorer_model = Model.load(open("models/enwiki.nettrom_wp10.gradient_boosting.model", "rb"))
    >>>
    >>> text = "I am the text of a page.  I have a <ref>word</ref>"
    >>> articlequality.score(scorer_model, text)
    {'prediction': 'stub',
     'probability': {'stub': 0.27156163795807853,
                     'b': 0.14707452309674252,
                     'fa': 0.16844898943510833,
                     'c': 0.057668704007171959,
                     'ga': 0.21617801281707663,
                     'start': 0.13906813268582238}}

## Authors
* Aaron Halfaker -- https://github.com/halfak
* Morten Warncke-Wang -- https://github.com/nettrom


