import functools import numpy import os import psutil import pytest 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 # # 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 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, *args, **kwargs): 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, iterations=1, args=args, kwargs=kwargs) return threads.deferToThread(bench) return blockOnThreadWithSetup # # resource monitoring # class ResourceWatcher(threading.Thread): sampling_interval = 0.1 def __init__(self, watch_memory): threading.Thread.__init__(self) self.process = psutil.Process(os.getpid()) self.running = False # monitored resources self.cpu_percent = None self.watch_memory = watch_memory self.memory_samples = [] self.memory_percent = None def run(self): self.running = True self.process.cpu_percent() # decide how long to sleep based on need to sample memory sleep = self.sampling_interval if not self.watch_memory else 1 while self.running: if self.watch_memory: sample = self.process.memory_percent(memtype='rss') self.memory_samples.append(sample) time.sleep(sleep) def stop(self): self.running = False self.join() # save cpu usage info self.cpu_percent = self.process.cpu_percent() # save memory usage info if self.watch_memory: 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, request, *args, **kwargs): # setup resource monitoring watch_memory = _watch_memory(request) watcher = ResourceWatcher(watch_memory) watcher.start() # run benchmarking function benchmark_function(*args, **kwargs) # store results watcher.stop() benchmark_fixture.extra_info.update({ 'cpu_percent': watcher.cpu_percent }) if watch_memory: benchmark_fixture.extra_info.update({ 'memory_percent': watcher.memory_percent, }) # add docstring info if request.scope == 'function': fun = request.function doc = fun.__doc__ or '' benchmark_fixture.extra_info.update({'doc': doc.strip()}) def _watch_memory(request): return request.config.getoption('--watch-memory') @pytest.fixture def monitored_benchmark(benchmark, request): return functools.partial( _monitored_benchmark, benchmark, benchmark, request) @pytest.fixture def monitored_benchmark_with_setup(benchmark, request, *args, **kwargs): return functools.partial( _monitored_benchmark, benchmark, benchmark.pedantic, request, *args, **kwargs)