SimPy offers three types of
resources that help you modeling
problems, where multiple processes want to use a resource of limited capacity
(e.g., cars at a fuel station with a limited number of fuel pumps) or classical
In this section, we’ll briefly introduce SimPy’s
Basic Resource Usage¶
We’ll slightly modify our electric vehicle process
car that we introduced in
the last sections.
The car will now drive to a battery charging station (BCS) and request one of its two charging spots. If both of these spots are currently in use, it waits until one of them becomes available again. It then starts charging its battery and leaves the station afterwards:
>>> def car(env, name, bcs, driving_time, charge_duration): ... # Simulate driving to the BCS ... yield env.timeout(driving_time) ... ... # Request one of its charging spots ... print('%s arriving at %d' % (name, env.now)) ... with bcs.request() as req: ... yield req ... ... # Charge the battery ... print('%s starting to charge at %s' % (name, env.now)) ... yield env.timeout(charge_duration) ... print('%s leaving the bcs at %s' % (name, env.now))
generates an event that lets you wait until the resource becomes available
again. If you are resumed, you “own” the resource until you release it.
If you use the resource with the
with statement as shown above, the
resource is automatically being released. If you call
with, you are responsible to call
release() once you are done using
When you release a resource, the next waiting process is resumed and now “owns”
one of the resource’s slots. The basic
Resource sorts waiting processes in a FIFO
(first in—first out) way.
A resource needs a reference to an
a capacity when it is created:
>>> import simpy >>> env = simpy.Environment() >>> bcs = simpy.Resource(env, capacity=2)
We can now create the
car processes and pass a reference to our resource as
well as some additional parameters to them:
>>> for i in range(4): ... env.process(car(env, 'Car %d' % i, bcs, i*2, 5)) <Process(car) object at 0x...> <Process(car) object at 0x...> <Process(car) object at 0x...> <Process(car) object at 0x...>
Finally, we can start the simulation. Since the car processes all terminate on their own in this simulation, we don’t need to specify an until time—the simulation will automatically stop when there are no more events left:
>>> env.run() Car 0 arriving at 0 Car 0 starting to charge at 0 Car 1 arriving at 2 Car 1 starting to charge at 2 Car 2 arriving at 4 Car 0 leaving the bcs at 5 Car 2 starting to charge at 5 Car 3 arriving at 6 Car 1 leaving the bcs at 7 Car 3 starting to charge at 7 Car 2 leaving the bcs at 10 Car 3 leaving the bcs at 12
Note that the first two cars can start charging immediately after they arrive at the BCS, while cars 2 and 3 have to wait.