"""Channel testing""" from test.testlib import * from git.async.pool import * from git.async.task import * from git.async.thread import terminate_threads from git.async.util import cpu_count import threading import time import sys class _TestTaskBase(object): """Note: causes great slowdown due to the required locking of task variables""" def __init__(self, *args, **kwargs): super(_TestTaskBase, self).__init__(*args, **kwargs) self.should_fail = False self.lock = threading.Lock() # yes, can't safely do x = x + 1 :) self.plock = threading.Lock() self.item_count = 0 self.process_count = 0 def do_fun(self, item): self.lock.acquire() self.item_count += 1 self.lock.release() if self.should_fail: raise AssertionError("I am failing just for the fun of it") return item def process(self, count=1): # must do it first, otherwise we might read and check results before # the thread gets here :). Its a lesson ! self.plock.acquire() self.process_count += 1 self.plock.release() super(_TestTaskBase, self).process(count) def _assert(self, pc, fc, check_scheduled=False): """Assert for num process counts (pc) and num function counts (fc) :return: self""" self.lock.acquire() if self.item_count != fc: print self.item_count, fc assert self.item_count == fc self.lock.release() return self class TestThreadTaskNode(_TestTaskBase, InputIteratorThreadTask): pass class TestThreadFailureNode(TestThreadTaskNode): """Fails after X items""" def __init__(self, *args, **kwargs): self.fail_after = kwargs.pop('fail_after') super(TestThreadFailureNode, self).__init__(*args, **kwargs) def do_fun(self, item): item = TestThreadTaskNode.do_fun(self, item) self.lock.acquire() try: if self.item_count > self.fail_after: raise AssertionError("Simulated failure after processing %i items" % self.fail_after) finally: self.lock.release() # END handle fail after return item class TestThreadInputChannelTaskNode(_TestTaskBase, InputChannelTask): """Apply a transformation on items read from an input channel""" def __init__(self, *args, **kwargs): self.fail_after = kwargs.pop('fail_after', 0) super(TestThreadInputChannelTaskNode, self).__init__(*args, **kwargs) def do_fun(self, item): """return tuple(i, i*2)""" item = super(TestThreadInputChannelTaskNode, self).do_fun(item) # fail after support if self.fail_after: self.lock.acquire() try: if self.item_count > self.fail_after: raise AssertionError("Simulated failure after processing %i items" % self.fail_after) finally: self.lock.release() # END handle fail-after if isinstance(item, tuple): i = item[0] return item + (i * self.id, ) else: return (item, item * self.id) # END handle tuple class TestThreadInputChannelVerifyTaskNode(_TestTaskBase, InputChannelTask): """An input channel task, which verifies the result of its input channels, should be last in the chain. Id must be int""" def do_fun(self, item): """return tuple(i, i*2)""" item = super(TestThreadInputChannelVerifyTaskNode, self).do_fun(item) # make sure the computation order matches assert isinstance(item, tuple), "input was no tuple: %s" % item base = item[0] for id, num in enumerate(item[1:]): assert num == base * id, "%i != %i, orig = %s" % (num, base * id, str(item)) # END verify order return item class TestThreadPool(TestBase): max_threads = cpu_count() def _add_task_chain(self, p, ni, count=1, fail_setup=list()): """Create a task chain of feeder, count transformers and order verifcator to the pool p, like t1 -> t2 -> t3 :param fail_setup: a list of pairs, task_id, fail_after, i.e. [(2, 20)] would make the third transformer fail after 20 items :return: tuple(list(task1, taskN, ...), list(rc1, rcN, ...))""" nt = p.num_tasks() feeder = self._make_iterator_task(ni) frc = p.add_task(feeder) assert p.num_tasks() == nt + 1 rcs = [frc] tasks = [feeder] inrc = frc for tc in xrange(count): t = TestThreadInputChannelTaskNode(inrc, tc, None) t.fun = t.do_fun inrc = p.add_task(t) tasks.append(t) rcs.append(inrc) assert p.num_tasks() == nt + 2 + tc # END create count transformers # setup failure for id, fail_after in fail_setup: tasks[1+id].fail_after = fail_after # END setup failure verifier = TestThreadInputChannelVerifyTaskNode(inrc, 'verifier', None) verifier.fun = verifier.do_fun vrc = p.add_task(verifier) assert p.num_tasks() == nt + tc + 3 tasks.append(verifier) rcs.append(vrc) return tasks, rcs def _make_iterator_task(self, ni, taskcls=TestThreadTaskNode, **kwargs): """:return: task which yields ni items :param taskcls: the actual iterator type to use :param **kwargs: additional kwargs to be passed to the task""" t = taskcls(iter(range(ni)), 'iterator', None, **kwargs) t.fun = t.do_fun return t def _assert_single_task(self, p, async=False): """Performs testing in a synchronized environment""" # return # DEBUG TODO: Fixme deactivated it print >> sys.stderr, "Threadpool: Starting single task (async = %i) with %i threads" % (async, p.size()) null_tasks = p.num_tasks() # in case we had some before # add a simple task # it iterates n items ni = 5000 assert ni % 2 == 0, "ni needs to be dividable by 2" assert ni % 4 == 0, "ni needs to be dividable by 4" make_task = lambda *args, **kwargs: self._make_iterator_task(ni, *args, **kwargs) task = make_task() assert p.num_tasks() == null_tasks rc = p.add_task(task) assert p.num_tasks() == 1 + null_tasks assert isinstance(rc, RPoolChannel) assert task._out_wc is not None # pull the result completely - we should get one task, which calls its # function once. In sync mode, the order matches print "read(0)" items = rc.read() assert len(items) == ni task._assert(1, ni) if not async: assert items[0] == 0 and items[-1] == ni-1 # as the task is done, it should have been removed - we have read everything assert task.is_done() del(rc) assert p.num_tasks() == null_tasks task = make_task() # pull individual items rc = p.add_task(task) assert p.num_tasks() == 1 + null_tasks st = time.time() print "read(1) * %i" % ni for i in range(ni): items = rc.read(1) assert len(items) == 1 # can't assert order in async mode if not async: assert i == items[0] # END for each item elapsed = time.time() - st print >> sys.stderr, "Threadpool: processed %i individual items, with %i threads, one at a time, in %f s ( %f items / s )" % (ni, p.size(), elapsed, ni / elapsed) # it couldn't yet notice that the input is depleted as we pulled exaclty # ni items - the next one would remove it. Instead, we delete our channel # which triggers orphan handling assert not task.is_done() assert p.num_tasks() == 1 + null_tasks del(rc) assert p.num_tasks() == null_tasks # test min count # if we query 1 item, it will prepare ni / 2 task = make_task() task.min_count = ni / 2 rc = p.add_task(task) print "read(1)" items = rc.read(1) assert len(items) == 1 and items[0] == 0 # processes ni / 2 print "read(1)" items = rc.read(1) assert len(items) == 1 and items[0] == 1 # processes nothing # rest - it has ni/2 - 2 on the queue, and pulls ni-2 # It wants too much, so the task realizes its done. The task # doesn't care about the items in its output channel nri = ni-2 print "read(%i)" % nri items = rc.read(nri) assert len(items) == nri p.remove_task(task) assert p.num_tasks() == null_tasks task._assert(2, ni) # two chunks, ni calls # its already done, gives us no more, its still okay to use it though # as a task doesn't have to be in the graph to allow reading its produced # items print "read(0) on closed" # it can happen that a thread closes the channel just a tiny fraction of time # after we check this, so the test fails, although it is nearly closed. # When we start reading, we should wake up once it sends its signal # assert task.is_closed() assert len(rc.read()) == 0 # test chunking # we always want 4 chunks, these could go to individual nodes task = make_task() task.min_count = ni / 2 # restore previous value task.max_chunksize = ni / 4 # 4 chunks rc = p.add_task(task) # must read a specific item count # count is still at ni / 2 - here we want more than that # 2 steps with n / 4 items, + 1 step with n/4 items to get + 2 nri = ni / 2 + 2 print "read(%i) chunksize set" % nri items = rc.read(nri) assert len(items) == nri # have n / 4 - 2 items on queue, want n / 4 in first chunk, cause 1 processing # ( 4 in total ). Still want n / 4 - 2 in second chunk, causing another processing nri = ni / 2 - 2 print "read(%i) chunksize set" % nri items = rc.read(nri) assert len(items) == nri task._assert( 5, ni) assert task.is_done() del(rc) assert p.num_tasks() == null_tasks # depleted # but this only hits if we want too many items, if we want less, it could # still do too much - hence we set the min_count to the same number to enforce # at least ni / 4 items to be preocessed, no matter what we request task = make_task() task.min_count = None task.max_chunksize = ni / 4 # match previous setup rc = p.add_task(task) st = time.time() print "read(1) * %i, chunksize set" % ni for i in range(ni): if async: assert len(rc.read(1)) == 1 else: assert rc.read(1)[0] == i # END handle async mode # END pull individual items # too many processing counts ;) elapsed = time.time() - st print >> sys.stderr, "Threadpool: processed %i individual items in chunks of %i, with %i threads, one at a time, in %f s ( %f items / s )" % (ni, ni/4, p.size(), elapsed, ni / elapsed) task._assert(ni, ni) assert p.num_tasks() == 1 + null_tasks assert p.remove_task(task) is p # del manually this time assert p.num_tasks() == null_tasks # now with we set the minimum count to reduce the number of processing counts task = make_task() task.min_count = ni / 4 task.max_chunksize = ni / 4 # match previous setup rc = p.add_task(task) print "read(1) * %i, min_count%i + chunksize" % (ni, task.min_count) for i in range(ni): items = rc.read(1) assert len(items) == 1 if not async: assert items[0] == i # END for each item task._assert(ni / task.min_count, ni) del(rc) assert p.num_tasks() == null_tasks # test failure # on failure, the processing stops and the task is finished, keeping # his error for later task = make_task() task.should_fail = True rc = p.add_task(task) print "read(0) with failure" assert len(rc.read()) == 0 # failure on first item assert isinstance(task.error(), AssertionError) assert task.is_done() # on error, its marked done as well del(rc) assert p.num_tasks() == null_tasks # test failure after ni / 2 items # This makes sure it correctly closes the channel on failure to prevent blocking nri = ni/2 task = make_task(TestThreadFailureNode, fail_after=ni/2) rc = p.add_task(task) assert len(rc.read()) == nri assert task.is_done() assert isinstance(task.error(), AssertionError) print >> sys.stderr, "done with everything" def _assert_async_dependent_tasks(self, pool): # includes failure in center task, 'recursive' orphan cleanup # This will also verify that the channel-close mechanism works # t1 -> t2 -> t3 print >> sys.stderr, "Threadpool: starting async dependency test in %i threads" % pool.size() null_tasks = pool.num_tasks() ni = 5000 count = 3 aic = count + 2 make_task = lambda *args, **kwargs: self._add_task_chain(pool, ni, count, *args, **kwargs) ts, rcs = make_task() assert len(ts) == aic assert len(rcs) == aic assert pool.num_tasks() == null_tasks + len(ts) print pool._tasks.nodes # read(0) ######### st = time.time() items = rcs[-1].read() elapsed = time.time() - st assert len(items) == ni del(rcs) assert pool.num_tasks() == 0 # tasks depleted, all done, no handles print >> sys.stderr, "Dependent Tasks: evaluated %i items of %i dependent in %f s ( %i items / s )" % (ni, aic, elapsed, ni / elapsed) # read(1) ######### ts, rcs = make_task() st = time.time() for i in xrange(ni): items = rcs[-1].read(1) assert len(items) == 1 # END for each item to pull elapsed_single = time.time() - st # another read yields nothing, its empty assert len(rcs[-1].read()) == 0 print >> sys.stderr, "Dependent Tasks: evaluated %i items with read(1) of %i dependent in %f s ( %i items / s )" % (ni, aic, elapsed_single, ni / elapsed_single) # read with min-count size ########################### # must be faster, as it will read ni / 4 chunks # Its enough to set one task, as it will force all others in the chain # to min_size as well. ts, rcs = make_task() assert pool.num_tasks() == len(ts) nri = ni / 4 ts[-1].min_count = nri st = time.time() for i in xrange(ni): items = rcs[-1].read(1) assert len(items) == 1 # END for each item to read elapsed_minsize = time.time() - st # its empty assert len(rcs[-1].read()) == 0 print >> sys.stderr, "Dependent Tasks: evaluated %i items with read(1), min_size=%i, of %i dependent in %f s ( %i items / s )" % (ni, nri, aic, elapsed_minsize, ni / elapsed_minsize) # it should have been a bit faster at least, and most of the time it is # Sometimes, its not, mainly because: # * The test tasks lock a lot, hence they slow down the system # * Each read will still trigger the pool to evaluate, causing some overhead # even though there are enough items on the queue in that case. Keeping # track of the scheduled items helped there, but it caused further inacceptable # slowdown # assert elapsed_minsize < elapsed_single # read with failure ################### # it should recover and give at least fail_after items # t1 -> x -> t3 fail_after = ni/2 ts, rcs = make_task(fail_setup=[(0, fail_after)]) items = rcs[-1].read() assert len(items) == fail_after # MULTI-POOL # If two pools are connected, this shold work as well. # The second one has just one more thread if False: p2 = ThreadPool(1) assert p2.size() == 1 p2ts, p2rcs = self._add_task_chain(p2, ni, count) ts, rcs = make_task() del(p2ts) del(p2rcs) assert p2.num_tasks() == 0 del(p2) # in the end, we expect all tasks to be gone, automatically # order of deletion doesnt matter del(ts) del(rcs) assert pool.num_tasks() == null_tasks # for some reason, sometimes it has multiple workerthreads already when he # enters the method ... dunno yet, pools should clean up themselvess #@terminate_threads def test_base(self): assert len(threading.enumerate()) == 1 p = ThreadPool() # default pools have no workers assert p.size() == 0 # increase and decrease the size num_threads = len(threading.enumerate()) for i in range(self.max_threads): p.set_size(i) assert p.size() == i assert len(threading.enumerate()) == num_threads + i for i in range(self.max_threads, -1, -1): p.set_size(i) assert p.size() == i assert p.size() == 0 # threads should be killed already, but we let them a tiny amount of time # just to be sure time.sleep(0.05) assert len(threading.enumerate()) == num_threads # SINGLE TASK SERIAL SYNC MODE ############################## # put a few unrelated tasks that we forget about urc1 = p.add_task(TestThreadTaskNode(iter(list()), "nothing", None)) urc2 = p.add_task(TestThreadTaskNode(iter(list()), "nothing", None)) assert p.num_tasks() == 2 ## SINGLE TASK ################# self._assert_single_task(p, False) assert p.num_tasks() == 2 del(urc1) del(urc2) assert p.num_tasks() == 0 # DEPENDENT TASKS SYNC MODE ########################### self._assert_async_dependent_tasks(p) # SINGLE TASK THREADED ASYNC MODE ( 1 thread ) ############################################## # step one gear up - just one thread for now. p.set_size(1) assert p.size() == 1 assert len(threading.enumerate()) == num_threads + 1 # deleting the pool stops its threads - just to be sure ;) # Its not synchronized, hence we wait a moment del(p) time.sleep(0.05) assert len(threading.enumerate()) == num_threads p = ThreadPool(1) assert len(threading.enumerate()) == num_threads + 1 # here we go self._assert_single_task(p, True) # SINGLE TASK ASYNC MODE ( 2 threads ) ###################################### # two threads to compete for a single task p.set_size(2) self._assert_single_task(p, True) # real stress test- should be native on every dual-core cpu with 2 hardware # threads per core p.set_size(4) self._assert_single_task(p, True) # DEPENDENT TASK ASYNC MODE ########################### self._assert_async_dependent_tasks(p) print >> sys.stderr, "Done with everything" # TODO: test multi-pool connections