Metadata-Version: 2.1
Name: pythovolve
Version: 0.1.1
Summary: Object oriented framework for genetic algorithms
Home-page: https://github.com/peter-schmidbauer/pythovolve
Author: Peter Schmidbauer
Author-email: peter.schmidb@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Description-Content-Type: text/markdown
Requires-Dist: matplotlib
Requires-Dist: seaborn
Requires-Dist: sympy
Requires-Dist: pandas
Requires-Dist: scipy

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![PyPI - Python Version](https://img.shields.io/pypi/pyversions/pythovolve.svg)

# pythovolve
A modular, object-oriented framework for evolutionary and genetic algorithms in Python 3.

## Quick start

### Installation using pip

Make sure you have Python 3.6 installed by executing `python --version` in your command line.

Next, simply execute 

    pip install --upgrade pythovolve 

to install pythovolve.

### Try it out (as a Library)

Check out the examples in the examples directory. To do that, clone the repository using git:

    git clone https://github.com/peter-schmidbauer/pythovolve.git

If you have already installed pythovolve, you can now run

    python pythovolve/examples/<example_script.py>

to execute one of the examples.

### Try it out (as a CLI)

If you have already installed pythovolve, check out a simple CLI example by running:

    python -m pythovolve GA -r 30 -p

To run an ES on a difficult multi dimensional test function, try

    python -m pythovolve ES -d hoelder_table -m gauss -c single_point -p

For a full list and explanation of all CLI parameters, run

    python -m pythovolve -h






