EvoLib – A Modular Framework for Evolutionary Computation

Docs Status Code Quality & Tests License: MIT PyPI version Project Status: Beta

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EvoLib is a lightweight and transparent framework for evolutionary computation, focusing on simplicity, modularity, and clarity — aimed at experimentation, teaching, and small-scale research rather than industrial-scale applications.
Key Features

Transparent design: configuration via YAML, type-checked validation, and clear module boundaries.

Modularity: mutation, selection, crossover, and parameter representations can be freely combined.

Educational value: examples and a clean API make it practical for illustrating evolutionary concepts.

Neuroevolution support: structural mutations (adding/removing neurons and connections) and evolvable networks via EvoNet.

Type-checked: PEP8 compliant, and consistent code style.

Modular framework for evolutionary algorithms and neuroevolution - EvoLib/evo-lib

EvoLib is a clear, modular, and teaching‑friendly Python framework for evolutionary algorithms and neuroevolution.

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