SimPy

SimPy is a process-based discrete-event simulation framework based on standard
Python. Processes in SimPy are defined by Python generator__ functions and
can, for example, be used to model active components like customers, vehicles or
agents. SimPy also provides various types of shared resources to model
limited capacity congestion points (like servers, checkout counters and
tunnels).

Simulations can be performed “as fast as possible”, in real time (wall clock
time) or by manually stepping through the events.

Though it is theoretically possible to do continuous simulations with SimPy, it
has no features that help you with that. Also, SimPy is not really required for
simulations with a fixed step size and where your processes don’t interact with
each other or with shared resources.

The documentation__ contains a tutorial, several guides explaining key
concepts, a number of examples__ and the API reference__.

SimPy is released under the MIT License. Simulation model developers are
encouraged to share their SimPy modeling techniques with the SimPy community.
Please post a message to the SimPy mailing list__.

There is an introductory talk that explains SimPy’s concepts and provides some
examples: watch the video__ or get the slides__.

__ http://docs.python.org/3/glossary.html#term-generator
__ https://simpy.readthedocs.io/en/latest/
__ https://simpy.readthedocs.io/en/latest/simpy_intro/index.html
__ https://simpy.readthedocs.io/en/latest/topical_guides/index.html
__ https://simpy.readthedocs.io/en/latest/examples/index.html
__ https://simpy.readthedocs.io/en/latest/api_reference/index.html
__ https://groups.google.com/forum/#!forum/python-simpy
__ https://www.youtube.com/watch?v=Bk91DoAEcjY
__ http://stefan.sofa-rockers.org/downloads/simpy-ep14.pdf

A Simple Example

One of SimPy's main goals is to be easy to use. Here is an example for a simple
SimPy simulation: a clock process that prints the current simulation time at
each step:

.. code-block:: python

>>> import simpy
>>>
>>> def clock(env, name, tick):
...     while True:
...         print(name, env.now)
...         yield env.timeout(tick)
...
>>> env = simpy.Environment()
>>> env.process(clock(env, 'fast', 0.5))
<Process(clock) object at 0x...>
>>> env.process(clock(env, 'slow', 1))
<Process(clock) object at 0x...>
>>> env.run(until=2)
fast 0
slow 0
fast 0.5
slow 1
fast 1.0
fast 1.5

Installation

SimPy requires Python >= 3.8, both CPython and PyPy3 are known to work.

You can install SimPy easily via pip <http://pypi.python.org/pypi/pip>_:

.. code-block:: bash

$ python -m pip install simpy

You can also download and install SimPy manually:

.. code-block:: bash

$ cd where/you/put/simpy/
$ python -m build
$ python -m pip install dist/simpy-*.whl

To run SimPy’s test suite on your installation, execute:

.. code-block:: bash

$ python -m tox

Getting started

If you’ve never used SimPy before, the SimPy tutorial__ is a good starting
point for you. You can also try out some of the Examples__ shipped with
SimPy.

__ https://simpy.readthedocs.io/en/latest/simpy_intro/index.html
__ https://simpy.readthedocs.io/en/latest/examples/index.html

Documentation and Help

You can find a tutorial, examples, topical guides__ and an API reference, as well as some information about SimPy and its history in
our online documentation. For more help, contact the SimPy mailing list. SimPy users are pretty helpful. You can, of course, also dig through
the source code__.

If you find any bugs, please post them on our issue tracker__.

__ https://simpy.readthedocs.io/en/latest/simpy_intro/index.html
__ https://simpy.readthedocs.io/en/latest/examples/index.html
__ https://simpy.readthedocs.io/en/latest/topical_guides/index.html
__ https://simpy.readthedocs.io/en/latest/api_reference/index.html
__ https://simpy.readthedocs.io/en/latest/about/index.html
__ https://simpy.readthedocs.io/
__ mailto:python-simpy@googlegroups.com
__ https://gitlab.com/team-simpy/simpy/-/tree/master
__ https://gitlab.com/team-simpy/simpy/-/issues

Enjoy simulation programming in SimPy!

Ports and comparable libraries

Re-implementations of SimPy and libraries similar to SimPy are available in the
following languages:

C#: SimSharp <https://github.com/abeham/SimSharp>_ (written by Andreas Beham)
Julia: ConcurrentSim <https://github.com/JuliaDynamics/ConcurrentSim.jl>_
R: Simmer <https://github.com/r-simmer/simmer>_

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