DEAP/deap
Distributed Evolutionary Algorithms in Python observed · 2026-08-28
Health v2 · maintenance only
67/100
- Activity 77
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 4487
- days_rel: n/a
- days_push: 138
- n_releases_24m: 0
Adoption not part of the score
6436 stars · 1164 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded
DEAP is a Python framework for evolutionary computation that supports genetic algorithms, genetic programming, evolution strategies, and multi-objective optimization. It emphasizes explicit algorithms and transparent data structures, and integrates with parallelization tools like multiprocessing and SCOOP.
Use cases
- run a genetic algorithm to optimize parameters
- perform multi-objective optimization with NSGA-II
- do genetic programming with prefix trees
- implement CMA-ES evolution strategies
- parallelize fitness evaluations across processes
- evolve multiple cooperating or competing populations
- benchmark optimization test functions
When to choose
- you need flexible evolutionary algorithms with custom representations in Python
- you want multi-objective optimizers like NSGA-II/III or SPEA2 out of the box
- you need to parallelize fitness evaluation easily
- you want rapid prototyping of novel evolutionary methods
When to avoid
- you need gradient-based deep learning training
- you want a turnkey hyperparameter tuning tool with a high-level API
- your project requires a non-Python environment
Facets
library · maturity stable
machine-learning simulation benchmarking concurrency artificial-intelligence machine-learning performance python cross-platform evolutionary-computation genetic-algorithm genetic-programming multi-objective-optimization cma-es nsga-ii particle-swarm-optimization parallelization algorithms
1 source
- readme: https://github.com/DEAP/deap · fetched 2026-08-28 · 1c0738baf918
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| DEAP/deap | main | 67 |
For agents
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem