def test_schedule_matches_expected_target_throughput(self):
target_throughput = random.randint(10, 1000)
# this scheduler does not make use of the task, thus we won't specify it here
s = scheduler.DeterministicScheduler(
task=None, target_throughput=target_throughput)
assert_throughput(s, target_throughput,
f"target throughput=[{target_throughput}] ops/s")
def test_schedule_matches_expected_target_throughput(self):
clients = random.randint(1, 16)
target_throughput = random.randint(10, 1000)
s = scheduler.DeterministicScheduler({
"target-throughput": target_throughput,
"clients": clients
})
self.assertRateEquals(
s, clients / target_throughput,
"%d clients with %d target throughput" %
(clients, target_throughput))
def main():
def n(data, sched):
curr = data[-1] if len(data) > 0 else 0
data.append(sched.next(curr))
tnd = [0]
tnp = [0]
yn = [0]
sd = scheduler.DeterministicScheduler({"target-interval": 1})
sp = scheduler.PoissonScheduler({"target-interval": 1})
# generate data for a little bit longer time frame...
for i in range(0, 20):
n(tnd, sd)
n(tnp, sp)
yn.append(0)
fig, axs = plt.subplots(2, 1, sharex=True)
fig.subplots_adjust(left=0.08, right=0.98, hspace=0.5)
axes = plt.gca()
# ... but only show the first ten seconds which makes for a nicer picture
axes.set_xlim([0, 10])
ax = axs[0]
ax.plot(tnd, yn, "o-")
ax.set_title("Deterministic schedule")
ax = axs[1]
ax.set_title("Poisson schedule")
ax.plot(tnp, yn, "o-")
plt.xlabel("time [s]")
if len(sys.argv) == 2:
output_file_path = sys.argv[1]
print("Saving output to [%s]" % output_file_path)
plt.savefig(output_file_path, bbox_inches="tight")
plt.show()
def test_schedule_unlimited(self):
# no params -> no limit
s = scheduler.DeterministicScheduler({})
self.assertRateEquals(s, 0)
