|Original author(s)||Klaus G. Müller, Tony Vignaux|
|Developer(s)||Ontje Lünsdorf, Stefan Scherfke|
|Initial release||September 17, 2002|
|Stable release||3.0 / October 11, 2013|
|Type||Discrete event simulation|
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 simple Python generator functions and are 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). From version 3.1, it will also provide monitoring capabilities to aid in gathering statistics about resources and processes.
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. On the other hand, SimPy is overkill for simulations with a fixed step size where your processes don’t interact with each other or with shared resources — use a simple
while loop in this case.
The SimPy distribution contains tutorials, in-depth documentation, and a large number of examples.
SimPy GUI is available as Devsimpy, it is an advanced wxPython GUI for the modeling and simulation of systems based on the DEVS (Discrete EVent system Specification) formalism. Features include powerful built-in editor, advanced modeling approach, powerful discrete event simulation algorithm, import/export DEVS components library and more.
The first version was released in December 2002.
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:
>>> 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
- "DEVSimPy". Univ-corse.fr. Retrieved 2014-01-28.
- "Devsimpy - Python-based GUI for discrete event system simulation - Google Project Hosting". Code.google.com. Retrieved 2012-10-16.