pyeasyga 0.2.3

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

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.

• Homepage: https://github.com/remiomosowon/pyeasyga

• PyPI: https://pypi.python.org/pypi/pyeasyga

• Documentation: http://pyeasyga.readthedocs.org.

• Issues / Feedback: https://github.com/remiomosowon/pyeasyga/issues

• Free software: BSD license

Installation

At the command line, simply run:

$ pip install pyeasyga

Or, if you have virtualenvwrapper installed:

$ mkvirtualenv pyeasyga
$ pip install pyeasyga

Examples

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

Note

• Currently under active development

History

2014-07-05 (v0.2.2)

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

• Added link to jeffknupp’s sandman repo in HISTORY

• Modified make release to also upload project documentation

• Added Installation, and Example info to README.rst

• Removed easy_install installation step from docs/installation.rst (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

2014-07-04 (v0.2.0)

• Upload to pypi.

• Reflect changes in HISTORY (pypi upload, new version)

2014-07-03 (v0.1.0)

• 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

2014-06-23 (v0.1.0)

• Start of pyeasyga development.