def benchmark(new_fun, duration):
name = "bench"
new_fun(name)
work_time = 0.0
overhead = 0.0
started_on = time.time()
while True:
now = time.time()
if now - started_on >= duration:
break
latency = random.randint(MIN_LATENCY, MAX_LATENCY) / 1000.0
time.sleep(latency)
t1 = time.time()
metrics.notify(name, latency)
t2 = time.time()
overhead += (t2 - t1)
work_time += latency
elapsed = time.time() - started_on
metric_value = metrics.get(name)
metrics.delete_metric(name)
return elapsed, work_time, overhead, metric_value
def benchmark(new_fun, duration):
name = "bench"
new_fun(name)
work_time = 0.0
overhead = 0.0
started_on = time.time()
while True:
now = time.time()
if now - started_on >= duration:
break
latency = random.randint(MIN_LATENCY, MAX_LATENCY) / 1000.0
time.sleep(latency)
t1 = time.time()
metrics.notify(name, latency)
t2 = time.time()
overhead += (t2 - t1)
work_time += latency
elapsed = time.time() - started_on
metric_value = metrics.get(name)
metrics.delete_metric(name)
return elapsed, work_time, overhead, metric_value
def tearDownClass(cls):
cls.collector.stop()
[metrics.delete_metric(metric) for metric in metrics.metrics()]
def tearDownClass(cls):
cls.collector.stop()
[metrics.delete_metric(metric) for metric in metrics.metrics()]
