Evolutionary Algorithms Python Packages

google-vizier

Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

pygad

Source code of PyGAD, a Python 3 library for building the genetic algorithm and training machine learning algorithms (Keras & PyTorch).

pygmo

A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.

agentdescent

Gradient descent, but the parameters are agents — a parallel, asynchronous framework for self-evolving agents (skills, prompts, harnesses). Diffs are the gradients; the aggregator is the optimizer.

genoxide

Optimization for Rust and Python: genetic algorithms, CMA-ES, differential evolution, multi-objective, L-BFGS-B, Adam, MMA and more. The same results on every platform.

ribs

A bare-bones Python library for quality diversity optimization.

geneticalgorithm

Genetic Algorithm Package for Python

radiate

A fast and flexible evolution engine for implementing artificial evolution and genetic programming techniques

bluepyopt

Blue Brain Python Optimisation Library

evotorch

Advanced evolutionary computation library built directly on top of PyTorch, created at NNAISENSE.

google-vizier-dev

Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

fullseye

Fullseye — a numpy-native operator library for vision, 3-D and measurement: 1,500+ typed ops spanning 2-D imaging, point clouds/meshes/volumes, optics, tomography, interferometry, acoustics, colour and metrology, plus an evolutionary pipeline designer with honest holdout gating. Ships as an AI/RAG operator corpus.

sklearn-genetic-opt

Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.

moptipy

Implementation of metaheuristic optimization methods in Python for scientific, industrial, and educational scenarios. Experiments can be executed in parallel or in a distributed fashion. Experimental results can be evaluated in various ways, including diagrams, tables, and export to Excel.

xcsf

XCSF learning classifier system: rule-based online evolutionary machine learning

pypop7

[JMLR (CCF-A)] PyPop7: A Pure-PYthon LibrarY for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* algorithm variants. In the near future, we will add Learning-Based Optimizers as its extensions. [https://jmlr.org/papers/v25/23-0386.html]

hillclimb

Hillclimbing on verifiable rewards. Use Claude Code and Codex to autonomously search for python programs that optimize a score you define. 🏔️

oppoppopinit

PyPI package containing opposition learning operators and population initializers for evolutionary algorithms

byron

An evolutionary source-code fuzzer

evo-hq-cli

turns your codebase into an autoresearch loop — discovers what to measure, instruments the benchmark, then runs tree search with parallel subagents.

x-evolution

Implementation of various evolutionary algorithms, starting with evolutionary strategies

evo-hq-agent

turns your codebase into an autoresearch loop — discovers what to measure, instruments the benchmark, then runs tree search with parallel subagents.

yabox

Yet another black-box optimization library for Python

hypernets

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.