Mesa is an open-source Python library for agent-based modeling, ideal for simulating complex systems and exploring emergent behaviors.
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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 alternative to NetLogo, Repast, or MASON.
Above: A Mesa implementation of the Schelling segregation model, this can be displayed in browser windows or Jupyter.
Getting started quickly:
pip install mesa
You can also use pip
to install the github version:
pip install -U -e git+https://github.com/projectmesa/mesa@main#egg=mesa
Or any other (development) branch on this repo or your own fork:
pip install -U -e git+https://github.com/YOUR_FORK/mesa@YOUR_BRANCH#egg=mesa
For resources or help on using Mesa, check out the following:
You can run Mesa in a Docker container in a few ways.
If you are a Mesa developer, first install Docker Compose and then, in the folder containing the Mesa Git repository, you run:
$ docker compose up
# If you want to make it run in the background, you instead run
$ docker compose up -d
This runs the Schelling model, as an example.
With the docker-compose.yml file in this Git repository, the docker compose up
command does two important things:
If you are a model developer that wants to run Mesa on a model, you need to:
MODEL_DIR
variable in docker-compose.yml to point to
the path of your modelThen, you just need to run docker compose up -d
to have it
accessible from localhost:8765
.
Want to join the Mesa team or just curious about what is happening with Mesa? You can...
- Join our Matrix chat room in which questions, issues, and ideas can be (informally) discussed.
- Come to a monthly dev session (you can find dev session times, agendas and notes on Mesa discussions).
- Just check out the code on GitHub.
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 join a dev session (see Mesa discussions). A feature is most likely to be added if you build it!
Don't forget to checkout the Contributors guide.
To cite Mesa in your publication, you can use the CITATION.bib.