blob: d39b4b19b00263f57778e083b4ccdd41306f884f [file] [log] [blame]
import multiprocessing
import time
import lit.Test
import lit.util
import lit.worker
# No-operation semaphore for supporting `None` for parallelism_groups.
# lit_config.parallelism_groups['my_group'] = None
class NopSemaphore(object):
def acquire(self): pass
def release(self): pass
def create_run(tests, lit_config, workers, progress_callback, timeout=None):
# TODO(yln) assert workers > 0
if workers == 1:
return SerialRun(tests, lit_config, progress_callback, timeout)
return ParallelRun(tests, lit_config, progress_callback, timeout, workers)
class Run(object):
"""A concrete, configured testing run."""
def __init__(self, tests, lit_config, progress_callback, timeout):
self.tests = tests
self.lit_config = lit_config
self.progress_callback = progress_callback
self.timeout = timeout
def execute(self):
"""
Execute the tests in the run using up to the specified number of
parallel tasks, and inform the caller of each individual result. The
provided tests should be a subset of the tests available in this run
object.
The progress_callback will be invoked for each completed test.
If timeout is non-None, it should be a time in seconds after which to
stop executing tests.
Returns the elapsed testing time.
Upon completion, each test in the run will have its result
computed. Tests which were not actually executed (for any reason) will
be given an UNRESOLVED result.
"""
if not self.tests:
return 0.0
self.failure_count = 0
self.hit_max_failures = False
# Larger timeouts (one year, positive infinity) don't work on Windows.
one_week = 7 * 24 * 60 * 60 # days * hours * minutes * seconds
timeout = self.timeout or one_week
start = time.time()
deadline = start + timeout
self._execute(deadline)
end = time.time()
# Mark any tests that weren't run as UNRESOLVED.
for test in self.tests:
if test.result is None:
test.setResult(lit.Test.Result(lit.Test.UNRESOLVED, '', 0.0))
return end - start
def _process_result(self, test, result):
# Don't add any more test results after we've hit the maximum failure
# count. Otherwise we're racing with the main thread, which is going
# to terminate the process pool soon.
if self.hit_max_failures:
return
# Update the parent process copy of the test. This includes the result,
# XFAILS, REQUIRES, and UNSUPPORTED statuses.
test.setResult(result)
self.progress_callback(test)
# If we've finished all the tests or too many tests have failed, notify
# the main thread that we've stopped testing.
self.failure_count += (result.code == lit.Test.FAIL)
if self.lit_config.maxFailures and \
self.failure_count == self.lit_config.maxFailures:
self.hit_max_failures = True
class SerialRun(Run):
def __init__(self, tests, lit_config, progress_callback, timeout):
super(SerialRun, self).__init__(tests, lit_config, progress_callback, timeout)
def _execute(self, deadline):
# TODO(yln): ignores deadline
for test in self.tests:
result = lit.worker._execute(test, self.lit_config)
self._process_result(test, result)
if self.hit_max_failures:
break
class ParallelRun(Run):
def __init__(self, tests, lit_config, progress_callback, timeout, workers):
super(ParallelRun, self).__init__(tests, lit_config, progress_callback, timeout)
self.workers = workers
def _execute(self, deadline):
semaphores = {
k: NopSemaphore() if v is None else
multiprocessing.BoundedSemaphore(v) for k, v in
self.lit_config.parallelism_groups.items()}
# Start a process pool. Copy over the data shared between all test runs.
# FIXME: Find a way to capture the worker process stderr. If the user
# interrupts the workers before we make it into our task callback, they
# will each raise a KeyboardInterrupt exception and print to stderr at
# the same time.
pool = multiprocessing.Pool(self.workers, lit.worker.initialize,
(self.lit_config, semaphores))
# Install a console-control signal handler on Windows.
if lit.util.win32api is not None:
def console_ctrl_handler(type):
print('\nCtrl-C detected, terminating.')
pool.terminate()
pool.join()
lit.util.abort_now()
return True
lit.util.win32api.SetConsoleCtrlHandler(console_ctrl_handler, True)
async_results = [
pool.apply_async(lit.worker.execute, args=[test],
callback=lambda r, t=test: self._process_result(t, r))
for test in self.tests]
pool.close()
for ar in async_results:
timeout = deadline - time.time()
try:
ar.get(timeout)
except multiprocessing.TimeoutError:
# TODO(yln): print timeout error
pool.terminate()
break
if self.hit_max_failures:
pool.terminate()
break