# DEAP documentation

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 parallelisation mechanism such as multiprocessing and SCOOP. The following documentation presents the key concepts and many features to build your own evolutions.

- First steps:

  - Overview (Start Here!)

  - Installation

  - Porting Guide

- Basic tutorials:

  - Part 1: creating types

  - Part 2: operators and algorithms

  - Part 3: logging statistics

  - Part 4: using multiple processors

- Advanced tutorials:

  - Genetic Programming

  - Checkpointing

  - Constraint Handling

  - Benchmarking Against the Bests (BBOB)

  - Inheriting from Numpy

- Examples

- Library Reference

- Release Highlights

- Contributing

- About DEAP