def test_buggy_factory_raises_on_block():
"""
Tests that if there is an exception thrown in the value factory,
it is caught in the first call to `block_until_target_successes()`.
"""
outcomes, worker = generate_workers(
[(OperatorRule(timeout_min=1, timeout_max=1), 100)],
seed=123)
factory = BuggyFactory(list(outcomes))
# Non-zero stagger timeout to make BuggyFactory raise its error only in 1.5s,
# So that we got enough successes for `block_until_target_successes()`.
pool = WorkerPool(worker, factory, target_successes=10, timeout=10, threadpool_size=10, stagger_timeout=1.5)
pool.start()
time.sleep(2) # wait for the stagger timeout to finish
with pytest.raises(Exception, match="Buggy factory"):
pool.block_until_target_successes()
# Further calls to `block_until_target_successes()` or `join()` don't throw the error.
with pytest.raises(Exception, match="Buggy factory"):
pool.block_until_target_successes()
pool.cancel()
with pytest.raises(Exception, match="Buggy factory"):
pool.join()
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 test_buggy_factory_raises_on_block():
"""
Tests that if there is an exception thrown in the value factory,
it is caught in the first call to `block_until_target_successes()`.
"""
outcomes, worker = generate_workers(
[(OperatorRule(timeout_min=1, timeout_max=1), 100)], seed=123)
factory = BuggyFactory(list(outcomes))
# WorkerPool short circuits once it has sufficient successes. Therefore,
# the stagger timeout needs to be less than worker timeout,
# since BuggyFactory only fails if you do a subsequent batch
# Once the subsequent batch is requested, the BuggyFactory returns an error
# causing WorkerPool to fail
pool = WorkerPool(worker,
factory,
target_successes=10,
timeout=10,
threadpool_size=10,
stagger_timeout=0.75)
pool.start()
time.sleep(2) # wait for the stagger timeout to finish
with pytest.raises(Exception, match="Buggy factory"):
pool.block_until_target_successes()
# Further calls to `block_until_target_successes()` or `join()` don't throw the error.
with pytest.raises(Exception, match="Buggy factory"):
pool.block_until_target_successes()
pool.cancel()
with pytest.raises(Exception, match="Buggy factory"):
pool.join()
def test_cancel_waiting_workers(join_worker_pool):
"""
If we have a small pool and many workers, it is possible for workers to be enqueued
one after another in one thread.
We test that if we call `cancel()`, these enqueued workers are cancelled too.
"""
outcomes, worker = generate_workers(
[
(OperatorRule(timeout_min=1, timeout_max=1), 100),
],
seed=123)
factory = AllAtOnceFactory(list(outcomes))
pool = WorkerPool(worker, factory, target_successes=10, timeout=10, threadpool_size=10)
join_worker_pool(pool)
t_start = time.monotonic()
pool.start()
pool.block_until_target_successes()
pool.cancel()
pool.join()
t_end = time.monotonic()
# We have 10 threads in the pool and 100 workers that are all enqueued at once at the start.
# If we didn't check for the cancel condition, we would have to wait for 10 seconds.
# We get 10 successes after 1s and cancel the workers,
# but the next workers in each thread have already started, so we have to wait for another 1s.
assert t_end - t_start < 2.5
def test_wait_for_successes_timed_out(join_worker_pool):
"""
Checks that if enough successful workers can't finish before the timeout, we get an exception.
"""
outcomes, worker = generate_workers(
[
(OperatorRule(timeout_min=0, timeout_max=0.5), 9),
(OperatorRule(timeout_min=1.5, timeout_max=2.5), 1),
(OperatorRule(fails=True, timeout_min=1.5, timeout_max=2.5), 20),
],
seed=123)
factory = AllAtOnceFactory(list(outcomes))
timeout = 1
pool = WorkerPool(worker, factory, target_successes=10, timeout=timeout, threadpool_size=30)
join_worker_pool(pool)
t_start = time.monotonic()
pool.start()
with pytest.raises(WorkerPool.TimedOut) as exc_info:
successes = pool.block_until_target_successes()
t_end = time.monotonic()
# Even though timeout is 1, there are long-running workers which we can't interupt.
assert t_end - t_start < 3
message = str(exc_info.value)
# None of the workers actually failed, they just timed out
assert f"Execution timed out after {timeout}s" == message
def test_wait_for_successes_out_of_values(join_worker_pool):
"""
Checks that if there weren't enough successful workers, `block_until_target_successes()`
raises an exception when the value factory is exhausted.
"""
outcomes, worker = generate_workers([
(WorkerRule(timeout_min=0.5, timeout_max=1.5), 9),
(WorkerRule(fails=True, timeout_min=0.5, timeout_max=1.5), 20),
],
seed=123)
factory = AllAtOnceFactory(list(outcomes))
pool = WorkerPool(worker,
factory,
target_successes=10,
timeout=10,
threadpool_size=15)
join_worker_pool(pool)
t_start = time.monotonic()
pool.start()
with pytest.raises(WorkerPool.OutOfValues):
successes = pool.block_until_target_successes()
t_end = time.monotonic()
# We have roughly 2 workers per thread, so it shouldn't take longer than 1.5s (max timeout) * 2
assert t_end - t_start < 4
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
class TreasureMapPublisher:
log = Logger('TreasureMapPublisher')
def __init__(self,
worker,
nodes,
percent_to_complete_before_release=5,
threadpool_size=120,
timeout=20):
self._total = len(nodes)
self._block_until_this_many_are_complete = math.ceil(
len(nodes) * percent_to_complete_before_release / 100)
self._worker_pool = WorkerPool(
worker=worker,
value_factory=AllAtOnceFactory(nodes),
target_successes=self._block_until_this_many_are_complete,
timeout=timeout,
stagger_timeout=0,
threadpool_size=threadpool_size)
@property
def completed(self):
# TODO: lock dict before copying?
return self._worker_pool.get_successes()
def start(self):
self.log.info(f"TreasureMapPublisher starting")
self._worker_pool.start()
if reactor.running:
reactor.callInThread(self.block_until_complete)
def block_until_success_is_reasonably_likely(self):
# Note: `OutOfValues`/`TimedOut` may be raised here, which means we didn't even get to
# `percent_to_complete_before_release` successes. For now just letting it fire.
self._worker_pool.block_until_target_successes()
completed = self.completed
self.log.debug(
f"The minimal amount of nodes ({len(completed)}) was contacted "
"while blocking for treasure map publication.")
return completed
def block_until_complete(self):
self._worker_pool.join()
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 get_ursulas(
self,
quantity: int,
exclude_ursulas: Optional[Sequence[ChecksumAddress]] = None,
include_ursulas: Optional[Sequence[ChecksumAddress]] = None
) -> List[UrsulaInfo]:
reservoir = self._make_reservoir(quantity, exclude_ursulas,
include_ursulas)
value_factory = PrefetchStrategy(reservoir, quantity)
def get_ursula_info(ursula_address) -> Porter.UrsulaInfo:
if to_checksum_address(ursula_address) not in self.known_nodes:
raise ValueError(f"{ursula_address} is not known")
ursula_address = to_checksum_address(ursula_address)
ursula = self.known_nodes[ursula_address]
try:
# ensure node is up and reachable
self.network_middleware.ping(ursula)
return Porter.UrsulaInfo(
checksum_address=ursula_address,
uri=f"{ursula.rest_interface.formal_uri}",
encrypting_key=ursula.public_keys(DecryptingPower))
except Exception as e:
self.log.debug(
f"Ursula ({ursula_address}) is unreachable: {str(e)}")
raise
self.block_until_number_of_known_nodes_is(
quantity,
timeout=self.execution_timeout,
learn_on_this_thread=True,
eager=True)
worker_pool = WorkerPool(worker=get_ursula_info,
value_factory=value_factory,
target_successes=quantity,
timeout=self.execution_timeout,
stagger_timeout=1)
worker_pool.start()
try:
successes = worker_pool.block_until_target_successes()
finally:
worker_pool.cancel()
# don't wait for it to stop by "joining" - too slow...
ursulas_info = successes.values()
return list(ursulas_info)
def get_ursulas(
self,
quantity: int,
duration_periods: int = None, # optional for federated mode
exclude_ursulas: Optional[Sequence[ChecksumAddress]] = None,
include_ursulas: Optional[Sequence[ChecksumAddress]] = None
) -> List[UrsulaInfo]:
reservoir = self._make_staker_reservoir(quantity, duration_periods,
exclude_ursulas,
include_ursulas)
value_factory = PrefetchStrategy(reservoir, quantity)
def get_ursula_info(ursula_address) -> Porter.UrsulaInfo:
if ursula_address not in self.known_nodes:
raise ValueError(f"{ursula_address} is not known")
ursula = self.known_nodes[ursula_address]
try:
# verify node is valid
self.network_middleware.client.verify_and_parse_node_or_host_and_port(
node_or_sprout=ursula, host=None, port=None)
return Porter.UrsulaInfo(
checksum_address=ursula_address,
uri=f"{ursula.rest_interface.formal_uri}",
encrypting_key=ursula.public_keys(DecryptingPower))
except Exception as e:
self.log.debug(
f"Unable to obtain Ursula information ({ursula_address}): {str(e)}"
)
raise
self.block_until_number_of_known_nodes_is(
quantity,
timeout=self.DEFAULT_EXECUTION_TIMEOUT,
learn_on_this_thread=True,
eager=True)
worker_pool = WorkerPool(worker=get_ursula_info,
value_factory=value_factory,
target_successes=quantity,
timeout=self.DEFAULT_EXECUTION_TIMEOUT,
stagger_timeout=1,
threadpool_size=quantity)
worker_pool.start()
successes = worker_pool.block_until_target_successes()
ursulas_info = successes.values()
return list(ursulas_info)
def test_wait_for_successes_out_of_values(join_worker_pool):
"""
Checks that if there weren't enough successful workers, `block_until_target_successes()`
raises an exception when the value factory is exhausted.
"""
outcomes, worker = generate_workers(
[
(OperatorRule(timeout_min=0.5, timeout_max=1.5), 9),
(OperatorRule(fails=True, timeout_min=0.5, timeout_max=1.5), 20),
],
seed=123)
factory = AllAtOnceFactory(list(outcomes))
pool = WorkerPool(worker, factory, target_successes=10, timeout=10, threadpool_size=15)
join_worker_pool(pool)
t_start = time.monotonic()
pool.start()
with pytest.raises(WorkerPool.OutOfValues) as exc_info:
successes = pool.block_until_target_successes()
t_end = time.monotonic()
# We have roughly 2 workers per thread, so it shouldn't take longer than 1.5s (max timeout) * 2
assert t_end - t_start < 4
message = str(exc_info.value)
assert "Execution stopped before completion - not enough available values" in message
# We had 20 workers set up to fail
num_expected_failures = 20
assert f"{num_expected_failures} failures recorded" in message
# check tracebacks
tracebacks = exc_info.value.get_tracebacks()
assert len(tracebacks) == num_expected_failures
for value, traceback in tracebacks.items():
assert 'raise Exception(f"Operator for {value} failed")' in traceback
assert f'Operator for {value} failed' in traceback
# This will be the last line in the displayed traceback;
# That's where the worker actually failed. (Operator for {value} failed)
assert 'raise Exception(f"Operator for {value} failed")' in message
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)
