{ "info": { "author": "Trevor Stephens", "author_email": "trev.stephens@gmail.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 3 - Alpha", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "License :: OSI Approved", "Operating System :: MacOS", "Operating System :: Microsoft :: Windows", "Operating System :: Unix", "Programming Language :: Python", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Scientific/Engineering", "Topic :: Software Development" ], "description": ".. image:: https://img.shields.io/pypi/v/gplearn.svg\n :target: https://pypi.python.org/pypi/gplearn/\n :alt: Version\n.. image:: https://img.shields.io/pypi/l/gplearn.svg\n :target: https://github.com/trevorstephens/gplearn/blob/master/LICENSE\n :alt: License\n.. image:: https://readthedocs.org/projects/gplearn/badge/?version=stable\n :target: http://gplearn.readthedocs.io/\n :alt: Documentation Status\n.. image:: https://travis-ci.org/trevorstephens/gplearn.svg?branch=master\n :target: https://travis-ci.org/trevorstephens/gplearn\n :alt: Test Status\n.. image:: https://ci.appveyor.com/api/projects/status/wqq9xxaxuyyt7nya?svg=true\n :target: https://ci.appveyor.com/project/trevorstephens/gplearn\n :alt: Windows Test Status\n.. image:: https://coveralls.io/repos/trevorstephens/gplearn/badge.svg\n :target: https://coveralls.io/r/trevorstephens/gplearn\n :alt: Test Coverage\n.. image:: https://api.codacy.com/project/badge/Grade/19c43d7c42c44d15b1ec512656800d8d\n :target: https://www.codacy.com/app/trevorstephens/gplearn\n :alt: Code Health\n\n|\n\n.. image:: https://raw.githubusercontent.com/trevorstephens/gplearn/master/doc/logos/gplearn-wide.png\n :target: https://github.com/trevorstephens/gplearn\n :alt: Genetic Programming in Python, with a scikit-learn inspired API\n\n|\n\nWelcome to gplearn!\n===================\n\n`gplearn` implements Genetic Programming in Python, with a `scikit-learn `_ inspired and compatible API.\n\nWhile Genetic Programming (GP) can be used to perform a `very wide variety of tasks `_, gplearn is purposefully constrained to solving symbolic regression problems. 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