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Analyzed 4 months ago. based on code collected 7 months ago.

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.

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evolutionarycomputing geneticalgorithms geneticprogramming particleswarmoptimization python

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GNU Lesser General Public License v3.0 only
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Project Security

Vulnerabilities per Version ( last 10 releases )

There are no reported vulnerabilities

Project Vulnerability Report

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Vulnerability Exposure Index

Many reported vulnerabilities
Few reported vulnerabilities

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About Project Security

Languages

Languages?height=75&width=75
Python
85%
C
8%
5 Other
7%

30 Day Summary

Jul 29 2019 — Aug 28 2019

12 Month Summary

Aug 28 2018 — Aug 28 2019
  • 95 Commits
    Up + 63 (196%) from previous 12 months
  • 11 Contributors
    Down -1 (8%) from previous 12 months