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        "author": "Aaron Garrett",
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            "License :: OSI Approved :: GNU General Public License (GPL)",
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        "description": "``ecspy`` -- A framework for creating evolutionary computations in Python.\r\n--------------------------------------------------------------------------\r\n\r\nECsPy (Evolutionary Computations in Python) is a free, open source framework for \r\ncreating evolutionary computations in Python. Additionally, ECsPy \r\nprovides an easy-to-use canonical genetic algorithm (GA), evolution \r\nstrategy (ES), estimation of distribution algorithm (EDA), differential \r\nevolution algorithm (DEA), and particle swarm optimizer (PSO) for users \r\nwho don't need much customization.\r\n\r\n  \r\nRequirements\r\n============\r\n\r\n  * Requires at least Python 2.6 (not compatible with Python 3+).\r\n  * Numpy and Matplotlib are required if the line plot observer is used.\r\n  * Parallel Python (pp) is required if parallel_evaluation_pp is used.\r\n\r\n\r\n\r\nLicense\r\n=======\r\n\r\nThis package is distributed under the GNU General Public License \r\nversion 3.0 (GPLv3). This license can be found online at\r\nhttp://www.opensource.org/licenses/gpl-3.0.html.\r\n\r\n  \r\nPackage Structure\r\n=================\r\n  \r\nECsPy consists of the following modules:\r\n\r\n  * analysis.py -- provides tools for analyzing the results of an EC\r\n  \r\n  * archivers.py -- defines useful archiving methods, particularly for EMO algorithms\r\n  \r\n  * benchmarks.py -- defines several single- and multi-objective benchmark optimization problems\r\n  \r\n  * ec.py -- provides the basic framework for an EvolutionaryComputation and specific ECs\r\n  \r\n  * emo.py -- provides the Pareto class for multiobjective optimization along with specific EMOs (e.g. NSGA-II)\r\n  \r\n  * evaluators.py -- defines useful evaluation schemes, such as parallel evaluation\r\n  \r\n  * migrators.py -- defines a few built-in migrators, including migration via network and migration among concurrent processes\r\n\r\n  * observers.py -- defines a few built-in observers, including screen, file, and plotting observers\r\n  \r\n  * replacers.py -- defines standard replacement schemes such as generational and steady-state replacement\r\n\r\n  * selectors.py -- defines standard selectors (e.g., tournament)\r\n  \r\n  * swarm.py -- provides a basic particle swarm optimizer\r\n  \r\n  * terminators.py -- defines standard terminators (e.g., exceeding a maximum number of generations)\r\n  \r\n  * topologies.py -- defines standard topologies for particle swarms\r\n\r\n  * variators.py -- defines standard variators (crossover and mutation schemes such as n-point crossover)\r\n\r\n\r\nResources\r\n=========\r\n\r\n  * Homepage: http://ecspy.googlecode.com\r\n  \r\n  * Email: aaron.lee.garrett@gmail.com",
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