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Project Summary

DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data structures transparent. It works in perfect harmony with parallelization mechanism such as multiprocessing and SCOOP. The following documentation presents the key concepts and many features to build your own evolutions.

Tags

evolutionarycomputing geneticalgorithms geneticprogramming particleswarmoptimization python

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Project Security

Vulnerabilities per Version ( last 10 releases )

There are no reported vulnerabilities

Project Vulnerability Report

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Many reported vulnerabilities
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About Project Security

Languages

Python
86%
C
7%
5 Other
7%

30 Day Summary

Jan 28 2026 — Feb 27 2026

12 Month Summary

Feb 27 2025 — Feb 27 2026
  • 11 Commits
    Down -6 (35%) from previous 12 months
  • 4 Contributors
    Down 0 (0%) from previous 12 months