Python package for modular Bayesian optimization
Latest commit 3be57ad Sep 20, 2015 @mwhoffman Merge branch 'dev'


A Python package for modular Bayesian optimization.

This package provides methods for performing optimization of a possibly noise-corrupted function f. In particular this package allows us to place a prior on the possible behavior of f and select points in order to gather information about the function and its maximum.

Build Status Coverage Status


The easiest way to install this package is by running

pip install -r
pip install git+

which will install the package and any of its dependencies. Once the package is installed the included demos can be run directly via python. For example, by running

python -m pybo.demos.animated

A full list of demos can be viewed here.

Previous versions

The current version of pybo has undergone some change to its interface from previous versions. The previous stable release(s) of the package can be found here. For example, those users interested in a graphical interface to pybo can take a look at ProjectB, however this package requires a previous version which can be installed using:

pip install -r
pip install git+

Note the v0.1 tag in the installation lines which corresponds to the relevant release.