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A simple and easy-to-use Genetic Algorithm implementation library in Python

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Introduction

A simple and easy-to-use Genetic Algorithm implementation library in Python.

pyeasyga provides a simple interface to the power of Genetic Algorithms (GAs). You don’t have to have expert GA knowledge in order to use it.

Installation

At the command line, simply run:

$ pip install pyeasyga

For alternative install methods, see the INSTALL file or the Installation section in the documentation.

Examples

See the Usage section in the documentation for examples. The example files can be found in the examples directory.

Note

  • Currently under active development

History

v0.2.5

2014-07-09

2014-07-09

  • Modified the GeneticAlgorithm class initialisation parameters

  • Made changes to USAGE documentation

  • Added EXAMPLE documentation as a separate section

v0.2.4

2014-07-07

  • Refactored most of the code; Made GeneticAlgorithm class more OOP

  • Made changes to INSTALLATION documentation

v0.2.3

2014-07-05

  • Fixed breaking python 2.6 build

v0.2.2

2014-07-05

  • Removed duplicate ‘Example’ documentation; now maintaining only one copy in examples/README.rst

  • Added link to jeffknupp’s sandman repo in HISTORY

  • Modified release option in Makefile to also upload project documentation

  • Added INSTALLATION and EXAMPLE sections to README.rst

  • Removed easy_install installation step from documentation (pip is sufficient)

  • Added a simple example of usage to docs/usage.rst

  • Reduced the default GA population and generation size (to allow applications that use the different parameters to run quickly)

  • Modified tests to account for the new default population, generation size

  • Added docstrings to all methods

v0.2.0

2014-07-04

  • First upload to pypi.

  • Added changes made to HISTORY (pypi upload, new version)

v0.1.0

2014-06-23

  • Start of pyeasyga development.

2014-07-03

  • Implemented all of basic GA functionality

  • Fix issue with odd-numbered population that causes an off-by-one error in the population size

  • Set default ga selection function to tournament_selection

  • Created examples to show how to use the library

  • Start versioning (better late than never); copied jeffknupp’s update_version.sh from sandman

    selected versioning standard: major.minor.micro (e.g. 2.1.5)

    • major => big changes that can break compatibility

    • minor => new features

    • micro => bug fixes

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