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.
Warning
If your are inheriting from numpy.ndarray see the Inheriting from Numpy tutorial and the One Max Problem: Using Numpy example.
Project Homepage