A simple and easy-to-use implementation of a Genetic Algorithm library in Python
A simple and easy-to-use implementation of a Genetic Algorithm 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
At the command line, simply run:
$ pip install pyeasyga
Or clone this repository and run python setup.py install from within the project directory. e.g.:
$ git clone https://github.com/remiomosowon/pyeasyga.git $ cd pyeasyga $ python setup.py install
For alternative install methods, see the INSTALL file or the Installation section in the documentation.
See the Usage section in the documentation for examples. The example files can be found in the examples directory.
- Currently under active development
- Added Python 3.4 support without breaking Python 2 compatibility (thanks to yasserglez)
- Added an example that solves the 8 Queens Puzzle
- Modified the GeneticAlgorithm class initialisation parameters
- Made changes to USAGE documentation
- Added EXAMPLE documentation as a separate section
- Refactored most of the code; Made GeneticAlgorithm class more OOP
- Made changes to INSTALLATION documentation
- Fixed breaking python 2.6 build
- 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
- First upload to pypi.
- Added changes made to HISTORY (pypi upload, new version)
- Start of pyeasyga development.
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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