DEAP 0.8.2 documentation
Welcome! This is
the documentation for DEAP
0.8.2, last updated Feb 06, 2013.
DEAP (Distributed Evolutionary Algorithms in Python) is a novel
evolutionary computation framework for rapid prototyping and testing of
ideas. Its design departs from most other existing frameworks in that it
seeks to make algorithms explicit and data structures transparent, as
opposed to the more common black box type of frameworks. It also
incorporates easy parallelism where users need not concern themselves with
gory implementation details like synchronization and load balancing, only
The five founding hypotheses of DEAP are:
- The user knows best. Users should be able to understand the internal
mechanisms of the framework so that they can extend them easily to better
suit their specific needs.
- User needs in terms of algorithms and operators are so vast that it would
be unrealistic to think of implementing them all in a single framework.
However, it should be possible to build basic tools and generic mechanisms
that enable easy user implementation of most any EA variant.
- Speedy prototyping of ideas is often more precious than speedy execution
of programs. Moreover, code compactness and clarity is also very precious.
- Even though interpreted, Python is fast enough to execute EAs. Whenever
execution time becomes critical, compute intensive components can always
be recoded in C. Many efficient numerical libraries are already available
through Python APIs.
- Easy parallelism can alleviate slow execution.
And these hypotheses lead to the following objectives:
- Rapid prototyping
- Provide an environment allowing users to quickly implement their own
algorithms without compromise.
- Parallelization made easy
- Allow for straightforward parallelization; users should not be forced to
specify more than the granularity level of their functional decomposition.
- Preach by examples
- Although the aim of the framework is not to provide ready made solutions,
it should nevertheless come with a substantial set of real-world examples
to guide the apprenticeship of users.
Parts of the documentation:
complete examples using common problems
the complete api of the framework
list of major changes to the framework
Indices and tables:
Global Module Index
quick access to all modules
all functions, classes, terms
search this documentation
Complete Table of Contents
lists all sections and subsections