def test_run(self):
"""
Test drain's run function (in a same thread)
"""
source = range(5)
destination = Queue()
drain = Drain(source, destination)
drain.run()
assert destination.qsize() == 5
def test_run(self):
"""
Test drain's run function (in a same thread)
"""
source = range(5)
destination = Queue()
drain = Drain(source, destination)
drain.run()
assert destination.qsize() == 5
def test_partially_reversed_data(self, data):
results_queue = Queue()
chunks = list(random_split(data))
chunks[5], chunks[6] = chunks[6], chunks[5]
pipeline = Aggregator(
TimeChopper(DataPoller(source=chunks, poll_period=0.1),
cache_size=3), AGGR_CONFIG, False)
drain = Drain(pipeline, results_queue)
drain.run()
assert results_queue.qsize() == MAX_TS
def test_partially_reversed_data(self, data):
results_queue = Queue()
chunks = list(random_split(data))
chunks[5], chunks[6] = chunks[6], chunks[5]
pipeline = Aggregator(
TimeChopper(
DataPoller(
source=chunks, poll_period=0.1), cache_size=3),
AGGR_CONFIG,
False)
drain = Drain(pipeline, results_queue)
drain.run()
assert results_queue.qsize() == MAX_TS
def test_slow_producer(self, data):
results_queue = Queue()
chunks = list(random_split(data))
chunks[5], chunks[6] = chunks[6], chunks[5]
def producer():
for chunk in chunks:
if np.random.random() > 0.5:
yield None
yield chunk
pipeline = Aggregator(
TimeChopper(DataPoller(source=producer(), poll_period=0.1),
cache_size=3), AGGR_CONFIG, False)
drain = Drain(pipeline, results_queue)
drain.run()
assert results_queue.qsize() == MAX_TS
def test_slow_producer(self, data):
results_queue = Queue()
chunks = list(random_split(data))
chunks[5], chunks[6] = chunks[6], chunks[5]
def producer():
for chunk in chunks:
if np.random.random() > 0.5:
yield None
yield chunk
pipeline = Aggregator(
TimeChopper(
DataPoller(
source=producer(), poll_period=0.1), cache_size=3),
AGGR_CONFIG,
False)
drain = Drain(pipeline, results_queue)
drain.run()
assert results_queue.qsize() == MAX_TS