SimPy

Its event dispatcher is based on Python's generators and can be used for asynchronous networking or to implement multi-agent systems (with both, simulated and real communication). 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 lacks features to support them. However, for simulations with a fixed step size where processes don't interact with each other or with shared resources, a simple while loop is sufficient.^[3]

Additionally, SimPy provides different types of shared resources to simulate congestion points that have limited capacity, such as servers, checkout counters, and tunnels. In version 3.1 and above, SimPy offers monitoring capabilities to assist in collecting statistics about processes and resources.

SimPy 3.0 requires Python 3.,^[4] while SimPy 4.0 requires Python 3.6+. SimPy distribution contains tutorials,^[5] documentation, and examples.

The following is a SimPy simulation^[6] showing 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