Compiled Knowledge is a Python package for compiling and querying discrete probabilistic graphical models. The aim of the project is:

• to provide a Python library for compiling and querying probabilistic graphical models, specifically discrete factor graphs, which includes Bayesian networks
• to be extremely efficient, flexible, and easy to use
• to exhibit excellent design, code, and documentation
• to support researchers and businesses wanting to explore and use probabilistic artificial intelligence.

MIT license (see the file LICENSE.txt).

Refer to the project online documentation at compiled-knowledge.readthedocs.io.

The primary repository for the project is github.com/ropeless/compiled_knowledge.

The Python package is available on PyPI, see pypi.org/project/compiled-knowledge.

For more information email info@compiledknowledge.org.