Mesa: Agent-based modeling in Python#
Mesa is an Apache2 licensed agent-based modeling (or ABM) framework in Python.
The original conference paper is available here.
Mesa allows users to quickly create agent-based models using built-in core components (such as spatial grids and agent schedulers) or customized implementations; visualize them using a browser-based interface; and analyze their results using Python’s data analysis tools. Its goal is to be the Python-based counterpart to NetLogo, Repast, or MASON.
Above: A Mesa implementation of the Schelling segregation model, being visualized in a browser window and analyzed in a Jupyter notebook.
Features#
Modular components
Browser-based visualization
Built-in tools for analysis
Using Mesa#
Getting started quickly:
pip install mesa
To launch an example model, clone the repository folder and invoke mesa runserver for one of the examples/ subdirectories:
mesa runserver examples/wolf_sheep
For more help on using Mesa, check out the following resources:
Contributing back to Mesa#
If you run into an issue, please file a ticket for us to discuss. If possible, follow up with a pull request.
If you would like to add a feature, please reach out via ticket or the [email list] for discussion. A feature is most likely to be added if you build it!
Mesa Packages#
ABM features users have shared that you may want to use in your model
Mesa-Packages