Metadata-Version: 2.1
Name: articlequality
Version: 0.4.3
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
Description: # 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}}
        
        ## Install
        
        ### Requirements
        
        * Python 3.5, 3.6 or 3.7
        * All the system requirements of [revscoring](https://github.com/wikimedia/revscoring)
        
        ### Installation steps
        
        1. clone this repository
        2. install the package itself and its dependencies `python setup.py install`
        3. You can verify that your installation worked by running `make enwiki_models` to build the English Wikipedia article quality model or `make wikidatawiki_models` to build the item quality model for Wikidata
        
        ### Retraining the models
        
        To retrain a model, run `make -B MODEL` e.g. `make -B wikidatawiki_models`. This will redownload the labels, re-extract the features from the revisions, and then retrain and rescore the model.
        
        To skip re-downloading the training labels and re-extracting the features, it is enough `touch` the files in the `datasets/` directory and run the `make` command without the `-B` flag.
        
        ### Running tests
        
        Example:
        
        ```
        pytest -vv tests/feature_lists/test_wikidatawiki.py
        ```
        
        ## Authors
        * Aaron Halfaker -- https://github.com/halfak
        * Morten Warncke-Wang -- https://github.com/nettrom
        
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
