Metadata-Version: 2.1
Name: wefe
Version: 0.1.2
Summary: The Word Embedding Fairness Evaluation Framework
Home-page: https://github.com/dccuchile/wefe
Maintainer: Pablo Badilla
Maintainer-email: pablo.badilla@ug.uchile.cl
License: new BSD
Download-URL: https://github.com/dccuchile/wefe
Platform: UNKNOWN
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: POSIX
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: scikit-learn
Requires-Dist: pandas
Requires-Dist: plotly
Requires-Dist: gensim
Provides-Extra: docs
Requires-Dist: sphinx ; extra == 'docs'
Requires-Dist: sphinx-gallery ; extra == 'docs'
Requires-Dist: sphinx-rtd-theme ; extra == 'docs'
Requires-Dist: numpydoc ; extra == 'docs'
Requires-Dist: matplotlib ; extra == 'docs'
Provides-Extra: tests
Requires-Dist: pytest ; extra == 'tests'
Requires-Dist: pytest-cov ; extra == 'tests'

.. -*- mode: rst -*-

|ReadTheDocs|_

.. |ReadTheDocs| image:: https://readthedocs.org/projects/wefe/badge/?version=latest
.. _ReadTheDocs: https://wefe.readthedocs.io/en/latest/?badge=latest

|CircleCI|_

.. |CircleCI| image:: https://circleci.com/gh/dccuchile/wefe.svg?style=svg
.. _CircleCI: https://circleci.com/gh/dccuchile/wefe.svg?style=svg



WEFE: The Word Embedding Fairness Evaluation Framework
======================================================


WEFE is a package focused on providing an easy and well-designed framework for 
measuring word embedding bias. 

It provides metrics, a framework for creating queries, and a standard interface 
for executing these queries using a metric and a pre-trained Word Embedding 
model.
In addition, it has multiple tools that allow you to run several queries on
several different embedding models, graph them, calculate their associated 
rankings per test, among others.

Although it is only in its early stages of development, it is expected that 
with time it will become more robust, that more metrics will be implemented 
and that it will extend to other types of bias measurement in NLP.

The official documentation can be found at this `link <https://wefe.readthedocs.io/>`_.


Installation
============

There are two different ways to install WEFE: 


To install the package with ``pip``   ::

    pip install wefe

- With conda: 

To install the package with ``conda``::

    conda install wefe


Requirements
------------

These package will be installed along with the package, in case these have not already been installed:

1. numpy
2. scikit-learn
3. scipy
4. pandas
5. gensim
6. plotly
7. patool


Contributing
------------

You can download the code executing ::

    git clone https://github.com/dccuchile/wefe


To contribute, visit the corresponding section in the documentation:

`Contributing <https://wefe.readthedocs.io/en/latest/contribute.html/>`

Testing
-------

All unit tests are in the wefe/test folder. It uses pytest as a framework to run them. 
You can run all tests, first install pytest and pytest-cov::

    pip install -U pytest
    pip install pytest-cov

To run the test, execute::

    pytest wefe

To check the coverage, run::

    py.test wefe --cov-report xml:cov.xml --cov wefe

And then::

    coverage report -m


Build the documentation
-----------------------

The documentation is created using sphinx. It can be found in the doc folder at the root of the project.
Here, the API is described as well as quick start and use cases.
To compile the documentation, run it::

    cd doc
    make html 



