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import base64
import functools
import numpy
import os
import psutil
import pytest
import random
import threading
import time
from twisted.internet import threads, reactor
# we have to manually setup the events server in order to be able to signal
# events. This is usually done by the enclosing application using soledad
# client (i.e. bitmask client).
from leap.common.events import server
server.ensure_server()
#
# pytest customizations
#
def pytest_addoption(parser):
parser.addoption(
"--watch-resources", default=False, action="store_true",
help="whether to monitor CPU and memory percentages during test run. "
"**Warning**: enabling this will impact the time taken by the "
"benchmarked code, so use with caution!")
# mark benchmark tests using their group names (thanks ionelmc! :)
def pytest_collection_modifyitems(items):
for item in items:
bench = item.get_marker("benchmark")
if bench and bench.kwargs.get('group'):
group = bench.kwargs['group']
marker = getattr(pytest.mark, 'benchmark_' + group)
item.add_marker(marker)
#
# benchmark fixtures
#
@pytest.fixture()
def payload():
def generate(size):
random.seed(1337) # same seed to avoid different bench results
payload_bytes = bytearray(random.getrandbits(8) for _ in xrange(size))
# encode as base64 to avoid ascii encode/decode errors
return base64.b64encode(payload_bytes)[:size] # remove b64 overhead
return generate
@pytest.fixture()
def txbenchmark(monitored_benchmark):
def blockOnThread(*args, **kwargs):
return threads.deferToThread(
monitored_benchmark, threads.blockingCallFromThread,
reactor, *args, **kwargs)
return blockOnThread
@pytest.fixture()
def txbenchmark_with_setup(monitored_benchmark_with_setup):
def blockOnThreadWithSetup(setup, f):
def blocking_runner(*args, **kwargs):
return threads.blockingCallFromThread(reactor, f, *args, **kwargs)
def blocking_setup():
args = threads.blockingCallFromThread(reactor, setup)
try:
return tuple(arg for arg in args), {}
except TypeError:
return ((args,), {}) if args else None
def bench():
return monitored_benchmark_with_setup(
blocking_runner, setup=blocking_setup,
rounds=4, warmup_rounds=1)
return threads.deferToThread(bench)
return blockOnThreadWithSetup
#
# resource monitoring
#
class ResourceWatcher(threading.Thread):
sampling_interval = 0.1
def __init__(self):
threading.Thread.__init__(self)
self.process = psutil.Process(os.getpid())
self.running = False
# monitored resources
self.cpu_percent = None
self.memory_samples = []
self.memory_percent = None
def run(self):
self.running = True
self.process.cpu_percent()
while self.running:
sample = self.process.memory_percent(memtype='rss')
self.memory_samples.append(sample)
time.sleep(self.sampling_interval)
def stop(self):
self.running = False
self.join()
# save cpu usage info
self.cpu_percent = self.process.cpu_percent()
# save memory usage info
memory_percent = {
'sampling_interval': self.sampling_interval,
'samples': self.memory_samples,
'stats': {},
}
for stat in 'max', 'min', 'mean', 'std':
fun = getattr(numpy, stat)
memory_percent['stats'][stat] = fun(self.memory_samples)
self.memory_percent = memory_percent
def _monitored_benchmark(benchmark_fixture, benchmark_function,
*args, **kwargs):
# setup resource monitoring
watcher = ResourceWatcher()
watcher.start()
# run benchmarking function
benchmark_function(*args, **kwargs)
# store results
watcher.stop()
benchmark_fixture.extra_info.update({
'cpu_percent': watcher.cpu_percent,
'memory_percent': watcher.memory_percent,
})
def _watch_resources(request):
return request.config.getoption('--watch-resources')
@pytest.fixture
def monitored_benchmark(benchmark, request):
if not _watch_resources(request):
return benchmark
return functools.partial(
_monitored_benchmark, benchmark, benchmark)
@pytest.fixture
def monitored_benchmark_with_setup(benchmark, request):
if not _watch_resources(request):
return benchmark.pedantic
return functools.partial(
_monitored_benchmark, benchmark, benchmark.pedantic)
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