Metadata-Version: 2.1
Name: Mesa
Version: 1.0.0
Summary: Agent-based modeling (ABM) in Python 3+
Home-page: https://github.com/projectmesa/mesa
Author: Project Mesa Team
Author-email: projectmesa@googlegroups.com
License: Apache 2.0
Description: Mesa: Agent-based modeling in Python 3+
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        .. image:: https://github.com/projectmesa/mesa/workflows/build/badge.svg
                :target: https://github.com/projectmesa/mesa/actions
        
        .. image:: https://codecov.io/gh/projectmesa/mesa/branch/main/graph/badge.svg
                :target: https://codecov.io/gh/projectmesa/mesa
        
        .. image:: https://img.shields.io/badge/code%20style-black-000000.svg
                :target: https://github.com/psf/black
        
        .. image:: https://img.shields.io/matrix/project-mesa:matrix.org?label=chat&logo=Matrix
                :target: https://matrix.to/#/#project-mesa:matrix.org
        
        It 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 3-based alternative to NetLogo, Repast, or MASON.
        
        
        .. image:: https://raw.githubusercontent.com/projectmesa/mesa/main/docs/images/Mesa_Screenshot.png
           :width: 100%
           :scale: 100%
           :alt: A screenshot of the Schelling Model in Mesa
        
        *Above: A Mesa implementation of the Schelling segregation model,
        being visualized in a browser window and analyzed in a Jupyter
        notebook.*
        
        .. _`Mesa` : https://github.com/projectmesa/mesa/
        
        
        Features
        ------------
        
        * Modular components
        * Browser-based visualization
        * Built-in tools for analysis
        * Example model library
        
        Using Mesa
        ------------
        
        Getting started quickly:
        
        .. code-block:: bash
        
            $ pip install mesa
        
        You can also use `pip` to install the github version:
        
        .. code-block:: bash
        
            $ pip install -e git+https://github.com/projectmesa/mesa#egg=mesa
        
        Or any other (development) branch on this repo or your own fork:
        
        .. code-block:: bash
        
            $ pip install -e git+https://github.com/YOUR_FORK/mesa@YOUR_BRANCH#egg=mesa
        
        Take a look at the `examples <https://github.com/projectmesa/mesa/tree/main/examples>`_ folder for sample models demonstrating Mesa features.
        
        For more help on using Mesa, check out the following resources:
        
        * `Intro to Mesa Tutorial`_
        * `Docs`_
        * `Email list for users`_
        * `PyPI`_
        
        .. _`Intro to Mesa Tutorial` : http://mesa.readthedocs.org/en/main/tutorials/intro_tutorial.html
        .. _`Docs` : http://mesa.readthedocs.org/en/main/
        .. _`Email list for users` : https://groups.google.com/d/forum/projectmesa
        .. _`PyPI` : https://pypi.python.org/pypi/Mesa/
        
        Running Mesa in Docker
        ------------------------
        
        You can run Mesa in a Docker container in a few ways.
        
        If you are a Mesa developer, first `install Docker Compose <https://docs.docker.com/compose/install/>`_ and then, in the folder containing the Mesa Git repository, you run:
        
        .. code-block:: bash
        
            $ docker compose up
            # If you want to make it run in the background, you instead run
            $ docker compose up -d
        
        This runs the wolf-sheep predation model, as an example.
        
        With the docker-compose.yml file in this Git repository, the `docker compose up` command does two important things:
        
        * It mounts the mesa root directory (relative to the docker-compose.yml file) into /opt/mesa and runs pip install -e on that directory so your changes to mesa should be reflected in the running container.
        * It binds the docker container's port 8521 to your host system's port 8521 so you can interact with the running model as usual by visiting localhost:8521 on your browser
        
        
        If you are a model developer that wants to run Mesa on a model, you need to:
        
        * make sure that your model folder is inside the folder containing the docker-compose.yml file
        * change the ``MODEL_DIR`` variable in docker-compose.yml to point to the path of your model
        * make sure that the model folder contains a run.py file
        
        Then, you just need to run `docker compose up -d` to make it accessible from ``localhost:8521``.
        
        Contributing to Mesa
        ----------------------------
        
        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`_.
        
        .. _`Matrix chat room` : https://matrix.to/#/#project-mesa:matrix.org
        .. _`Mesa discussions` : https://github.com/projectmesa/mesa/discussions
        .. _`GitHub` : https://github.com/projectmesa/mesa/
        .. _`ticket` : https://github.com/projectmesa/mesa/issues
        .. _`Contributors guide` : https://github.com/projectmesa/mesa/blob/main/CONTRIBUTING.rst
        
        
        Citing Mesa
        ----------------------------
        
        To cite Mesa in your publication, you can use the `CITATION.bib`_.
        
        .. _`CITATION.bib` : https://github.com/projectmesa/mesa/blob/main/CITATION.bib
        
Keywords: agent based modeling model ABM simulation multi-agent
Platform: UNKNOWN
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Life
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Intended Audience :: Science/Research
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 3 - Alpha
Classifier: Natural Language :: English
Requires-Python: >=3.7
Provides-Extra: dev
Provides-Extra: docs
