def test_wait_for_successes(join_worker_pool):
"""
Checks that `block_until_target_successes()` returns in time and gives all the successes,
if there were enough of them.
"""
outcomes, worker = generate_workers(
[
(OperatorRule(timeout_min=0.5, timeout_max=1.5), 10),
(OperatorRule(fails=True, timeout_min=1, timeout_max=3), 20),
],
seed=123)
factory = AllAtOnceFactory(list(outcomes))
pool = WorkerPool(worker, factory, target_successes=10, timeout=10, threadpool_size=30)
join_worker_pool(pool)
t_start = time.monotonic()
pool.start()
successes = pool.block_until_target_successes()
t_end = time.monotonic()
failures = pool.get_failures()
assert all(outcomes[value].fails for value in failures)
assert len(successes) == 10
# We have more threads in the pool than the workers,
# so all the successful ones should be able to finish right away.
assert t_end - t_start < 2
# Should be able to do it several times
successes = pool.block_until_target_successes()
assert len(successes) == 10
def _make_arrangements(self,
network_middleware: RestMiddleware,
handpicked_ursulas: Optional[Iterable[Ursula]] = None,
timeout: int = 10,
) -> Dict[Ursula, Arrangement]:
"""
Pick some Ursula addresses and send them arrangement proposals.
Returns a dictionary of Ursulas to Arrangements if it managed to get `n` responses.
"""
if handpicked_ursulas is None:
handpicked_ursulas = []
handpicked_addresses = [ursula.checksum_address for ursula in handpicked_ursulas]
reservoir = self._make_reservoir(handpicked_addresses)
value_factory = PrefetchStrategy(reservoir, self.n)
def worker(address):
return self._propose_arrangement(address, network_middleware)
self.alice.block_until_number_of_known_nodes_is(self.n, learn_on_this_thread=True, eager=True)
worker_pool = WorkerPool(worker=worker,
value_factory=value_factory,
target_successes=self.n,
timeout=timeout,
stagger_timeout=1,
threadpool_size=self.n)
worker_pool.start()
try:
successes = worker_pool.block_until_target_successes()
except (WorkerPool.OutOfValues, WorkerPool.TimedOut):
# It's possible to raise some other exceptions here,
# but we will use the logic below.
successes = worker_pool.get_successes()
finally:
worker_pool.cancel()
worker_pool.join()
accepted_arrangements = {ursula: arrangement for ursula, arrangement in successes.values()}
failures = worker_pool.get_failures()
accepted_addresses = ", ".join(ursula.checksum_address for ursula in accepted_arrangements)
if len(accepted_arrangements) < self.n:
rejected_proposals = "\n".join(f"{address}: {value}" for address, (type_, value, traceback) in failures.items())
self.log.debug(
"Could not find enough Ursulas to accept proposals.\n"
f"Accepted: {accepted_addresses}\n"
f"Rejected:\n{rejected_proposals}")
raise self._not_enough_ursulas_exception()
else:
self.log.debug(f"Finished proposing arrangements; accepted: {accepted_addresses}")
return accepted_arrangements
def _sample(
self,
network_middleware: RestMiddleware,
ursulas: Optional[Iterable['Ursula']] = None,
timeout: int = 10,
) -> List['Ursula']:
"""Send concurrent requests to the /ping HTTP endpoint of nodes drawn from the reservoir."""
ursulas = ursulas or []
handpicked_addresses = [
ChecksumAddress(ursula.checksum_address) for ursula in ursulas
]
self.publisher.block_until_number_of_known_nodes_is(
self.shares, learn_on_this_thread=True, eager=True)
reservoir = self._make_reservoir(handpicked_addresses)
value_factory = PrefetchStrategy(reservoir, self.shares)
def worker(address) -> 'Ursula':
return self._ping_node(address, network_middleware)
worker_pool = WorkerPool(worker=worker,
value_factory=value_factory,
target_successes=self.shares,
timeout=timeout,
stagger_timeout=1,
threadpool_size=self.shares)
worker_pool.start()
try:
successes = worker_pool.block_until_target_successes()
except (WorkerPool.OutOfValues, WorkerPool.TimedOut):
# It's possible to raise some other exceptions here but we will use the logic below.
successes = worker_pool.get_successes()
finally:
worker_pool.cancel()
worker_pool.join()
failures = worker_pool.get_failures()
accepted_addresses = ", ".join(ursula.checksum_address
for ursula in successes.values())
if len(successes) < self.shares:
rejections = "\n".join(
f"{address}: {value}"
for address, (type_, value, traceback) in failures.items())
message = "Failed to contact enough sampled nodes.\n"\
f"Selected:\n{accepted_addresses}\n" \
f"Unavailable:\n{rejections}"
self.log.debug(message)
raise self.NotEnoughUrsulas(message)
self.log.debug(f"Selected nodes for policy: {accepted_addresses}")
ursulas = list(successes.values())
return ursulas
def test_batched_value_generation(join_worker_pool):
"""
Tests a value factory that gives out value batches in portions.
"""
outcomes, worker = generate_workers([
(OperatorRule(timeout_min=0.5, timeout_max=1.5), 80),
(OperatorRule(fails=True, timeout_min=0.5, timeout_max=1.5), 80),
],
seed=123)
factory = BatchFactory(list(outcomes))
pool = WorkerPool(worker,
factory,
target_successes=10,
timeout=10,
threadpool_size=10,
stagger_timeout=0.5)
join_worker_pool(pool)
t_start = time.monotonic()
pool.start()
successes = pool.block_until_target_successes()
pool.cancel()
pool.join()
t_end = time.monotonic()
assert len(successes) == 10
# Check that batch sizes in the factory were getting progressively smaller
# as the number of successes grew.
assert all(factory.batch_sizes[i] >= factory.batch_sizes[i + 1]
for i in range(len(factory.batch_sizes) - 1))
# Since we canceled the pool, no more workers will be started and we will finish faster
assert t_end - t_start < 4
successes_copy = pool.get_successes()
failures_copy = pool.get_failures()
assert all(value in successes_copy for value in successes)
