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        "author": "Brandon Schabell",
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            "Development Status :: 5 - Production/Stable",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: MIT License",
            "Programming Language :: Python :: 3.4",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Programming Language :: Python :: 3.7",
            "Programming Language :: Python :: 3.8",
            "Topic :: Scientific/Engineering :: Artificial Intelligence",
            "Topic :: Utilities"
        ],
        "description": "# GeneticPy\n\n[![Build Status](https://travis-ci.com/geneticpy/geneticpy.svg?branch=master)](https://travis-ci.com/geneticpy/geneticpy)\n[![codecov](https://codecov.io/gh/geneticpy/geneticpy/branch/master/graph/badge.svg)](https://codecov.io/gh/geneticpy/geneticpy)\n[![PyPI version](https://badge.fury.io/py/geneticpy.svg)](https://badge.fury.io/py/geneticpy)\n[![PyPI pyversions](https://img.shields.io/pypi/pyversions/geneticpy.svg)](https://pypi.python.org/pypi/geneticpy/)\n[![Downloads](https://pepy.tech/badge/geneticpy/week)](https://pepy.tech/project/geneticpy)\n\nGeneticPy is an optimizer that uses a genetic algorithm to quickly search through custom parameter spaces for optimal solutions.\n\n### Installation\n\nGeneticPy requires Python 3.4+\n\n```sh\npip install geneticpy\n```\n\n### Example Usage:\n\nA brief example to get you started is included below:\n\n```python\ndef loss_function(params):\n  if params['type'] == 'add':\n    return params['x'] + params['y']\n  elif params['type'] == 'multiply':\n    return params['x'] * params['y']\n\nparam_space = {'type': geneticpy.ChoiceDistribution(choice_list=['add', 'multiply']),\n               'x': geneticpy.UniformDistribution(low=5, high=10, q=1),\n               'y': geneticpy.GaussianDistribution(mean=0, standard_deviation=1)}\n\nresults = geneticpy.optimize(loss_function, param_space, size=200, generation_count=500, verbose=True)\nbest_params = results['top_params']\nloss = results['top_score']\ntotal_time = results['total_time']\n\n```\n\n### PyPi Project\nhttps://pypi.org/project/geneticpy/\n\n### Contact\n\nPlease feel free to email me at brandonschabell@gmail.com with any questions or feedback.\n\n\n",
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