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Mesa-Adapted-0.8.7.3
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Forked Agent-based modeling (ABM) in Python 3+
| ویژگی | مقدار |
|---|---|
| سیستم عامل | OS Independent |
| نام فایل | Mesa-Adapted-0.8.7.3 |
| نام | Mesa-Adapted |
| نسخه کتابخانه | 0.8.7.3 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Project Mesa Team / Stefano Probst |
| ایمیل نویسنده | senden9@gmail.com |
| آدرس صفحه اصلی | https://github.com/senden9/mesa/tree/pipy-fork |
| آدرس اینترنتی | https://pypi.org/project/Mesa-Adapted/ |
| مجوز | Apache 2.0 |
Mesa: Fork of the Agent-based modeling in Python 3+
===================================================
Fork of the original Mesa project till https://github.com/projectmesa/mesa/pull/944 and/or https://github.com/projectmesa/mesa/issues/943 are soved.
.. image:: https://api.travis-ci.org/projectmesa/mesa.svg?branch=master
:target: https://travis-ci.org/projectmesa/mesa
.. image:: https://codecov.io/gh/projectmesa/mesa/branch/master/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
`Mesa`_ is an Apache2 licensed agent-based modeling (or ABM) framework in Python.
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://github.com/projectmesa/mesa/blob/master/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
Take a look at the `examples <https://github.com/projectmesa/mesa/tree/master/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/master/tutorials/intro_tutorial.html
.. _`Docs` : http://mesa.readthedocs.org/en/master/
.. _`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 run:
.. code-block:: bash
$ docker-compose build --pull
...
$ docker-compose up -d dev # start the docker container
$ docker-compose exec dev bash # enter the docker container that has your current version of Mesa installed at /opt/mesa
$ mesa runserver examples/Schelling # or any other example model in examples
The docker-compose file does two important things:
* 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
* 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.
If you are a model developer that wants to run Mesa on a model (assuming you are currently in your top-level model
directory with the run.py file):
.. code-block:: bash
$ docker run --rm -it -p127.0.0.1:8521:8521 -v${PWD}:/code comses/mesa:dev mesa runserver /code
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 `dev email list`_ for discussion. A feature is most likely to be added if you build it!
* `Contributors guide`_
* `Github`_
.. _`ticket` : https://github.com/projectmesa/mesa/issues
.. _`dev email list` : https://groups.google.com/forum/#!forum/projectmesa-dev
.. _`Contributors guide` : https://github.com/projectmesa/mesa/blob/master/CONTRIBUTING.rst
.. _`Github` : https://github.com/projectmesa/mesa/
نیازمندی
| مقدار | نام |
|---|---|
| - | click |
| - | cookiecutter |
| - | networkx |
| - | numpy |
| - | pandas |
| - | tornado |
| - | tqdm |
| - | coverage |
| - | flake8 |
| >=4.6 | pytest |
| - | pytest-cov |
| - | sphinx |
| - | sphinx |
| - | ipython |
نحوه نصب
نصب پکیج whl Mesa-Adapted-0.8.7.3:
pip install Mesa-Adapted-0.8.7.3.whl
نصب پکیج tar.gz Mesa-Adapted-0.8.7.3:
pip install Mesa-Adapted-0.8.7.3.tar.gz