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SimPy ===== SimPy is a process-based discrete-event simulation framework based on standard Python. Its event dispatcher is based on Python’s `generators`__ and can also be used for asynchronous networking or to implement multi-agent systems (with both, simulated and real communication). 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 SimPy distribution contains tutorials, in-depth documentation, and a large number of examples. 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-Users 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 __ http://lists.sourceforge.net/lists/listinfo/simpy-users __ 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 2.7, 3.2, PyPy 2.0 or above. You can install SimPy easily via `pip <http://pypi.python.org/pypi/pip>`_: .. code-block:: bash $ pip install -U simpy You can also download and install SimPy manually: .. code-block:: bash $ cd where/you/put/simpy/ $ python setup.py install To run SimPy’s test suite on your installation, execute: .. code-block:: bash $ python -c "import simpy; simpy.test()" Of course, you can keep working with SimPy 2: .. code-block:: bash $ pip install "simpy>=2.3,<3" 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.org/en/latest/simpy_intro/index.html __ https://simpy.readthedocs.org/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-Users 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.org/en/latest/simpy_intro/index.html __ https://simpy.readthedocs.org/en/latest/examples/index.html __ https://simpy.readthedocs.org/en/latest/topical_guides/index.html __ https://simpy.readthedocs.org/en/latest/api_reference/index.html __ https://simpy.readthedocs.org/en/latest/about/index.html __ https://simpy.readthedocs.org/ __ mailto:[email protected] __ https://bitbucket.org/simpy/simpy/src __ https://bitbucket.org/simpy/simpy/issues?status=new&status=open Enjoy simulation programming in SimPy! Ports ----- An almost feature-complete reimplementation of SimPy in C# was written by Andreas Beham and is available at `github.com/abeham/SimSharp`__ __ http://github.com/abeham/SimSharp
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