def test_speed(self):
# Initialize manually because we change a fundemental setting
initialize(force=True)
# Sync
t_start = time.time()
s_sync = ""
for user in users:
s_sync += expensive_render(user)
duration_sync = time.time() - t_start
# Async. Break into chunks of tasks.
t_start = time.time()
task = Task()
for start, end in ranges(users):
task.run(multi_expensive_render, start, end)
s_async = "".join(task.get())
duration_async = time.time() - t_start
# Hopefully we're on a multicore machine :)
self.assertEqual(s_sync, s_async)
self.failUnless(duration_async < duration_sync)
print(f'{i},')
def expensive_as_string(item):
time.sleep(0.01)
return str(item)
def multi_expensive_as_string(start, end):
return ",".join([expensive_as_string(item) for item in items[start:end]])
if __name__ == "__main__":
# Needs to be called only once for lifetime of process
initialize()
# Example 1: trivial (and slightly pointless) usage
task = Task()
task.run(as_string, 2000)
# Example 2: divide job optimally using ranges function
#task = Task()
#for start, end in ranges(items):
# Note we don't pass items because pickling is expensive and defeats
# the purpose of the exercize.
# task.run(multi_expensive_as_string, start, end)
# print(", ".join(task.get()))
# Stop the multicore workers
def ready(self):
initialize()
def test_no_deadlock(self):
initialize(force=True)
def setUpClass(cls):
super(TaskTestCase, cls).setUpClass()
initialize()