multiprocessing
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1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 | ## This module shows how to use arbitrary callables with a subclass of# `BaseManager`.## Copyright (c) 2006-2008, R Oudkerk# All rights reserved.#from multiprocessing import freeze_supportfrom multiprocessing.managers import BaseManager, BaseProxyimport operator##class Foo(object): def f(self): print 'you called Foo.f()' def g(self): print 'you called Foo.g()' def _h(self): print 'you called Foo._h()'# A simple generator functiondef baz(): for i in xrange(10): yield i*i# Proxy type for generator objectsclass GeneratorProxy(BaseProxy): _exposed_ = ('next', '__next__') def __iter__(self): return self def next(self): return self._callmethod('next') def __next__(self): return self._callmethod('__next__')# Function to return the operator moduledef get_operator_module(): return operator##class MyManager(BaseManager): pass# register the Foo class; make `f()` and `g()` accessible via proxyMyManager.register('Foo1', Foo)# register the Foo class; make `g()` and `_h()` accessible via proxyMyManager.register('Foo2', Foo, exposed=('g', '_h'))# register the generator function baz; use `GeneratorProxy` to make proxiesMyManager.register('baz', baz, proxytype=GeneratorProxy)# register get_operator_module(); make public functions accessible via proxyMyManager.register('operator', get_operator_module)##def test(): manager = MyManager() manager.start() print '-' * 20 f1 = manager.Foo1() f1.f() f1.g() assert not hasattr(f1, '_h') assert sorted(f1._exposed_) == sorted(['f', 'g']) print '-' * 20 f2 = manager.Foo2() f2.g() f2._h() assert not hasattr(f2, 'f') assert sorted(f2._exposed_) == sorted(['g', '_h']) print '-' * 20 it = manager.baz() for i in it: print '<%d>' % i, print print '-' * 20 op = manager.operator() print 'op.add(23, 45) =', op.add(23, 45) print 'op.pow(2, 94) =', op.pow(2, 94) print 'op.getslice(range(10), 2, 6) =', op.getslice(range(10), 2, 6) print 'op.repeat(range(5), 3) =', op.repeat(range(5), 3) print 'op._exposed_ =', op._exposed_##if __name__ == '__main__': freeze_support() test()Using Pool:## A test of `multiprocessing.Pool` class## Copyright (c) 2006-2008, R Oudkerk# All rights reserved.#import multiprocessingimport timeimport randomimport sys## Functions used by test code#def calculate(func, args): result = func(*args) return '%s says that %s%s = %s' % ( multiprocessing.current_process().name, func.__name__, args, result )def calculatestar(args): return calculate(*args)def mul(a, b): time.sleep(0.5*random.random()) return a * bdef plus(a, b): time.sleep(0.5*random.random()) return a + bdef f(x): return 1.0 / (x-5.0)def pow3(x): return x**3def noop(x): pass## Test code#def test(): print 'cpu_count() = %d\n' % multiprocessing.cpu_count() # # Create pool # PROCESSES = 4 print 'Creating pool with %d processes\n' % PROCESSES pool = multiprocessing.Pool(PROCESSES) print 'pool = %s' % pool print # # Tests # TASKS = [(mul, (i, 7)) for i in range(10)] + \ [(plus, (i, 8)) for i in range(10)] results = [pool.apply_async(calculate, t) for t in TASKS] imap_it = pool.imap(calculatestar, TASKS) imap_unordered_it = pool.imap_unordered(calculatestar, TASKS) print 'Ordered results using pool.apply_async():' for r in results: print '\t', r.get() print print 'Ordered results using pool.imap():' for x in imap_it: print '\t', x print print 'Unordered results using pool.imap_unordered():' for x in imap_unordered_it: print '\t', x print print 'Ordered results using pool.map() --- will block till complete:' for x in pool.map(calculatestar, TASKS): print '\t', x print # # Simple benchmarks # N = 100000 print 'def pow3(x): return x**3' t = time.time() A = map(pow3, xrange(N)) print '\tmap(pow3, xrange(%d)):\n\t\t%s seconds' % \ (N, time.time() - t) t = time.time() B = pool.map(pow3, xrange(N)) print '\tpool.map(pow3, xrange(%d)):\n\t\t%s seconds' % \ (N, time.time() - t) t = time.time() C = list(pool.imap(pow3, xrange(N), chunksize=N//8)) print '\tlist(pool.imap(pow3, xrange(%d), chunksize=%d)):\n\t\t%s' \ ' seconds' % (N, N//8, time.time() - t) assert A == B == C, (len(A), len(B), len(C)) print L = [None] * 1000000 print 'def noop(x): pass' print 'L = [None] * 1000000' t = time.time() A = map(noop, L) print '\tmap(noop, L):\n\t\t%s seconds' % \ (time.time() - t) t = time.time() B = pool.map(noop, L) print '\tpool.map(noop, L):\n\t\t%s seconds' % \ (time.time() - t) t = time.time() C = list(pool.imap(noop, L, chunksize=len(L)//8)) print '\tlist(pool.imap(noop, L, chunksize=%d)):\n\t\t%s seconds' % \ (len(L)//8, time.time() - t) assert A == B == C, (len(A), len(B), len(C)) print del A, B, C, L # # Test error handling # print 'Testing error handling:' try: print pool.apply(f, (5,)) except ZeroDivisionError: print '\tGot ZeroDivisionError as expected from pool.apply()' else: raise AssertionError('expected ZeroDivisionError') try: print pool.map(f, range(10)) except ZeroDivisionError: print '\tGot ZeroDivisionError as expected from pool.map()' else: raise AssertionError('expected ZeroDivisionError') try: print list(pool.imap(f, range(10))) except ZeroDivisionError: print '\tGot ZeroDivisionError as expected from list(pool.imap())' else: raise AssertionError('expected ZeroDivisionError') it = pool.imap(f, range(10)) for i in range(10): try: x = it.next() except ZeroDivisionError: if i == 5: pass except StopIteration: break else: if i == 5: raise AssertionError('expected ZeroDivisionError') assert i == 9 print '\tGot ZeroDivisionError as expected from IMapIterator.next()' print # # Testing timeouts # print 'Testing ApplyResult.get() with timeout:', res = pool.apply_async(calculate, TASKS[0]) while 1: sys.stdout.flush() try: sys.stdout.write('\n\t%s' % res.get(0.02)) break except multiprocessing.TimeoutError: sys.stdout.write('.') print print print 'Testing IMapIterator.next() with timeout:', it = pool.imap(calculatestar, TASKS) while 1: sys.stdout.flush() try: sys.stdout.write('\n\t%s' % it.next(0.02)) except StopIteration: break except multiprocessing.TimeoutError: sys.stdout.write('.') print print # # Testing callback # print 'Testing callback:' A = [] B = [56, 0, 1, 8, 27, 64, 125, 216, 343, 512, 729] r = pool.apply_async(mul, (7, 8), callback=A.append) r.wait() r = pool.map_async(pow3, range(10), callback=A.extend) r.wait() if A == B: print '\tcallbacks succeeded\n' else: print '\t*** callbacks failed\n\t\t%s != %s\n' % (A, B) # # Check there are no outstanding tasks # assert not pool._cache, 'cache = %r' % pool._cache # # Check close() methods # print 'Testing close():' for worker in pool._pool: assert worker.is_alive() result = pool.apply_async(time.sleep, [0.5]) pool.close() pool.join() assert result.get() is None for worker in pool._pool: assert not worker.is_alive() print '\tclose() succeeded\n' # # Check terminate() method # print 'Testing terminate():' pool = multiprocessing.Pool(2) DELTA = 0.1 ignore = pool.apply(pow3, [2]) results = [pool.apply_async(time.sleep, [DELTA]) for i in range(100)] pool.terminate() pool.join() for worker in pool._pool: assert not worker.is_alive() print '\tterminate() succeeded\n' # # Check garbage collection # print 'Testing garbage collection:' pool = multiprocessing.Pool(2) DELTA = 0.1 processes = pool._pool ignore = pool.apply(pow3, [2]) results = [pool.apply_async(time.sleep, [DELTA]) for i in range(100)] results = pool = None time.sleep(DELTA * 2) for worker in processes: assert not worker.is_alive() print '\tgarbage collection succeeded\n'if __name__ == '__main__': multiprocessing.freeze_support() assert len(sys.argv) in (1, 2) if len(sys.argv) == 1 or sys.argv[1] == 'processes': print ' Using processes '.center(79, '-') elif sys.argv[1] == 'threads': print ' Using threads '.center(79, '-') import multiprocessing.dummy as multiprocessing else: print 'Usage:\n\t%s [processes | threads]' % sys.argv[0] raise SystemExit(2) test()Synchronization types like locks, conditions and queues:## A test file for the `multiprocessing` package## Copyright (c) 2006-2008, R Oudkerk# All rights reserved.#import time, sys, randomfrom Queue import Emptyimport multiprocessing # may get overwritten#### TEST_VALUEdef value_func(running, mutex): random.seed() time.sleep(random.random()*4) mutex.acquire() print '\n\t\t\t' + str(multiprocessing.current_process()) + ' has finished' running.value -= 1 mutex.release()def test_value(): TASKS = 10 running = multiprocessing.Value('i', TASKS) mutex = multiprocessing.Lock() for i in range(TASKS): p = multiprocessing.Process(target=value_func, args=(running, mutex)) p.start() while running.value > 0: time.sleep(0.08) mutex.acquire() print running.value, sys.stdout.flush() mutex.release() print print 'No more running processes'#### TEST_QUEUEdef queue_func(queue): for i in range(30): time.sleep(0.5 * random.random()) queue.put(i*i) queue.put('STOP')def test_queue(): q = multiprocessing.Queue() p = multiprocessing.Process(target=queue_func, args=(q,)) p.start() o = None while o != 'STOP': try: o = q.get(timeout=0.3) print o, sys.stdout.flush() except Empty: print 'TIMEOUT' print#### TEST_CONDITIONdef condition_func(cond): cond.acquire() print '\t' + str(cond) time.sleep(2) print '\tchild is notifying' print '\t' + str(cond) cond.notify() cond.release()def test_condition(): cond = multiprocessing.Condition() p = multiprocessing.Process(target=condition_func, args=(cond,)) print cond cond.acquire() print cond cond.acquire() print cond p.start() print 'main is waiting' cond.wait() print 'main has woken up' print cond cond.release() print cond cond.release() p.join() print cond#### TEST_SEMAPHOREdef semaphore_func(sema, mutex, running): sema.acquire() mutex.acquire() running.value += 1 print running.value, 'tasks are running' mutex.release() random.seed() time.sleep(random.random()*2) mutex.acquire() running.value -= 1 print '%s has finished' % multiprocessing.current_process() mutex.release() sema.release()def test_semaphore(): sema = multiprocessing.Semaphore(3) mutex = multiprocessing.RLock() running = multiprocessing.Value('i', 0) processes = [ multiprocessing.Process(target=semaphore_func, args=(sema, mutex, running)) for i in range(10) ] for p in processes: p.start() for p in processes: p.join()#### TEST_JOIN_TIMEOUTdef join_timeout_func(): print '\tchild sleeping' time.sleep(5.5) print '\n\tchild terminating'def test_join_timeout(): p = multiprocessing.Process(target=join_timeout_func) p.start() print 'waiting for process to finish' while 1: p.join(timeout=1) if not p.is_alive(): break print '.', sys.stdout.flush()#### TEST_EVENTdef event_func(event): print '\t%r is waiting' % multiprocessing.current_process() event.wait() print '\t%r has woken up' % multiprocessing.current_process()def test_event(): event = multiprocessing.Event() processes = [multiprocessing.Process(target=event_func, args=(event,)) for i in range(5)] for p in processes: p.start() print 'main is sleeping' time.sleep(2) print 'main is setting event' event.set() for p in processes: p.join()#### TEST_SHAREDVALUESdef sharedvalues_func(values, arrays, shared_values, shared_arrays): for i in range(len(values)): v = values[i][1] sv = shared_values[i].value assert v == sv for i in range(len(values)): a = arrays[i][1] sa = list(shared_arrays[i][:]) assert a == sa print 'Tests passed'def test_sharedvalues(): values = [ ('i', 10), ('h', -2), ('d', 1.25) ] arrays = [ ('i', range(100)), ('d', [0.25 * i for i in range(100)]), ('H', range(1000)) ] shared_values = [multiprocessing.Value(id, v) for id, v in values] shared_arrays = [multiprocessing.Array(id, a) for id, a in arrays] p = multiprocessing.Process( target=sharedvalues_func, args=(values, arrays, shared_values, shared_arrays) ) p.start() p.join() assert p.exitcode == 0####def test(namespace=multiprocessing): global multiprocessing multiprocessing = namespace for func in [ test_value, test_queue, test_condition, test_semaphore, test_join_timeout, test_event, test_sharedvalues ]: print '\n\t######## %s\n' % func.__name__ func() ignore = multiprocessing.active_children() # cleanup any old processes if hasattr(multiprocessing, '_debug_info'): info = multiprocessing._debug_info() if info: print info raise ValueError('there should be no positive refcounts left')if __name__ == '__main__': multiprocessing.freeze_support() assert len(sys.argv) in (1, 2) if len(sys.argv) == 1 or sys.argv[1] == 'processes': print ' Using processes '.center(79, '-') namespace = multiprocessing elif sys.argv[1] == 'manager': print ' Using processes and a manager '.center(79, '-') namespace = multiprocessing.Manager() namespace.Process = multiprocessing.Process namespace.current_process = multiprocessing.current_process namespace.active_children = multiprocessing.active_children elif sys.argv[1] == 'threads': print ' Using threads '.center(79, '-') import multiprocessing.dummy as namespace else: print 'Usage:\n\t%s [processes | manager | threads]' % sys.argv[0] raise SystemExit(2) test(namespace)An example showing how to use queues to feed tasks to a collection of worker processes and collect the results:## Simple example which uses a pool of workers to carry out some tasks.## Notice that the results will probably not come out of the output# queue in the same in the same order as the corresponding tasks were# put on the input queue. If it is important to get the results back# in the original order then consider using `Pool.map()` or# `Pool.imap()` (which will save on the amount of code needed anyway).## Copyright (c) 2006-2008, R Oudkerk# All rights reserved.#import timeimport randomfrom multiprocessing import Process, Queue, current_process, freeze_support## Function run by worker processes#def worker(input, output): for func, args in iter(input.get, 'STOP'): result = calculate(func, args) output.put(result)## Function used to calculate result#def calculate(func, args): result = func(*args) return '%s says that %s%s = %s' % \ (current_process().name, func.__name__, args, result)## Functions referenced by tasks#def mul(a, b): time.sleep(0.5*random.random()) return a * bdef plus(a, b): time.sleep(0.5*random.random()) return a + b###def test(): NUMBER_OF_PROCESSES = 4 TASKS1 = [(mul, (i, 7)) for i in range(20)] TASKS2 = [(plus, (i, 8)) for i in range(10)] # Create queues task_queue = Queue() done_queue = Queue() # Submit tasks for task in TASKS1: task_queue.put(task) # Start worker processes for i in range(NUMBER_OF_PROCESSES): Process(target=worker, args=(task_queue, done_queue)).start() # Get and print results print 'Unordered results:' for i in range(len(TASKS1)): print '\t', done_queue.get() # Add more tasks using `put()` for task in TASKS2: task_queue.put(task) # Get and print some more results for i in range(len(TASKS2)): print '\t', done_queue.get() # Tell child processes to stop for i in range(NUMBER_OF_PROCESSES): task_queue.put('STOP')if __name__ == '__main__': freeze_support() test()An example of how a pool of worker processes can each run a SimpleHTTPServer.HttpServer instance while sharing a single listening socket.## Example where a pool of http servers share a single listening socket## On Windows this module depends on the ability to pickle a socket# object so that the worker processes can inherit a copy of the server# object. (We import `multiprocessing.reduction` to enable this pickling.)## Not sure if we should synchronize access to `socket.accept()` method by# using a process-shared lock -- does not seem to be necessary.## Copyright (c) 2006-2008, R Oudkerk# All rights reserved.#import osimport sysfrom multiprocessing import Process, current_process, freeze_supportfrom BaseHTTPServer import HTTPServerfrom SimpleHTTPServer import SimpleHTTPRequestHandlerif sys.platform == 'win32': import multiprocessing.reduction # make sockets pickable/inheritabledef note(format, *args): sys.stderr.write('[%s]\t%s\n' % (current_process().name, format%args))class RequestHandler(SimpleHTTPRequestHandler): # we override log_message() to show which process is handling the request def log_message(self, format, *args): note(format, *args)def serve_forever(server): note('starting server') try: server.serve_forever() except KeyboardInterrupt: passdef runpool(address, number_of_processes): # create a single server object -- children will each inherit a copy server = HTTPServer(address, RequestHandler) # create child processes to act as workers for i in range(number_of_processes-1): Process(target=serve_forever, args=(server,)).start() # main process also acts as a worker serve_forever(server)def test(): DIR = os.path.join(os.path.dirname(__file__), '..') ADDRESS = ('localhost', 8000) NUMBER_OF_PROCESSES = 4 print 'Serving at http://%s:%d using %d worker processes' % \ (ADDRESS[0], ADDRESS[1], NUMBER_OF_PROCESSES) print 'To exit press Ctrl-' + ['C', 'Break'][sys.platform=='win32'] os.chdir(DIR) runpool(ADDRESS, NUMBER_OF_PROCESSES)if __name__ == '__main__': freeze_support() test()Some simple benchmarks comparing multiprocessing with threading:## Simple benchmarks for the multiprocessing package## Copyright (c) 2006-2008, R Oudkerk# All rights reserved.#import time, sys, multiprocessing, threading, Queue, gcif sys.platform == 'win32': _timer = time.clockelse: _timer = time.timedelta = 1#### TEST_QUEUESPEEDdef queuespeed_func(q, c, iterations): a = '0' * 256 c.acquire() c.notify() c.release() for i in xrange(iterations): q.put(a) q.put('STOP')def test_queuespeed(Process, q, c): elapsed = 0 iterations = 1 while elapsed < delta: iterations *= 2 p = Process(target=queuespeed_func, args=(q, c, iterations)) c.acquire() p.start() c.wait() c.release() result = None t = _timer() while result != 'STOP': result = q.get() elapsed = _timer() - t p.join() print iterations, 'objects passed through the queue in', elapsed, 'seconds' print 'average number/sec:', iterations/elapsed#### TEST_PIPESPEEDdef pipe_func(c, cond, iterations): a = '0' * 256 cond.acquire() cond.notify() cond.release() for i in xrange(iterations): c.send(a) c.send('STOP')def test_pipespeed(): c, d = multiprocessing.Pipe() cond = multiprocessing.Condition() elapsed = 0 iterations = 1 while elapsed < delta: iterations *= 2 p = multiprocessing.Process(target=pipe_func, args=(d, cond, iterations)) cond.acquire() p.start() cond.wait() cond.release() result = None t = _timer() while result != 'STOP': result = c.recv() elapsed = _timer() - t p.join() print iterations, 'objects passed through connection in',elapsed,'seconds' print 'average number/sec:', iterations/elapsed#### TEST_SEQSPEEDdef test_seqspeed(seq): elapsed = 0 iterations = 1 while elapsed < delta: iterations *= 2 t = _timer() for i in xrange(iterations): a = seq[5] elapsed = _timer()-t print iterations, 'iterations in', elapsed, 'seconds' print 'average number/sec:', iterations/elapsed#### TEST_LOCKdef test_lockspeed(l): elapsed = 0 iterations = 1 while elapsed < delta: iterations *= 2 t = _timer() for i in xrange(iterations): l.acquire() l.release() elapsed = _timer()-t print iterations, 'iterations in', elapsed, 'seconds' print 'average number/sec:', iterations/elapsed#### TEST_CONDITIONdef conditionspeed_func(c, N): c.acquire() c.notify() for i in xrange(N): c.wait() c.notify() c.release()def test_conditionspeed(Process, c): elapsed = 0 iterations = 1 while elapsed < delta: iterations *= 2 c.acquire() p = Process(target=conditionspeed_func, args=(c, iterations)) p.start() c.wait() t = _timer() for i in xrange(iterations): c.notify() c.wait() elapsed = _timer()-t c.release() p.join() print iterations * 2, 'waits in', elapsed, 'seconds' print 'average number/sec:', iterations * 2 / elapsed####def test(): manager = multiprocessing.Manager() gc.disable() print '\n\t######## testing Queue.Queue\n' test_queuespeed(threading.Thread, Queue.Queue(), threading.Condition()) print '\n\t######## testing multiprocessing.Queue\n' test_queuespeed(multiprocessing.Process, multiprocessing.Queue(), multiprocessing.Condition()) print '\n\t######## testing Queue managed by server process\n' test_queuespeed(multiprocessing.Process, manager.Queue(), manager.Condition()) print '\n\t######## testing multiprocessing.Pipe\n' test_pipespeed() print print '\n\t######## testing list\n' test_seqspeed(range(10)) print '\n\t######## testing list managed by server process\n' test_seqspeed(manager.list(range(10))) print '\n\t######## testing Array("i", ..., lock=False)\n' test_seqspeed(multiprocessing.Array('i', range(10), lock=False)) print '\n\t######## testing Array("i", ..., lock=True)\n' test_seqspeed(multiprocessing.Array('i', range(10), lock=True)) print print '\n\t######## testing threading.Lock\n' test_lockspeed(threading.Lock()) print '\n\t######## testing threading.RLock\n' test_lockspeed(threading.RLock()) print '\n\t######## testing multiprocessing.Lock\n' test_lockspeed(multiprocessing.Lock()) print '\n\t######## testing multiprocessing.RLock\n' test_lockspeed(multiprocessing.RLock()) print '\n\t######## testing lock managed by server process\n' test_lockspeed(manager.Lock()) print '\n\t######## testing rlock managed by server process\n' test_lockspeed(manager.RLock()) print print '\n\t######## testing threading.Condition\n' test_conditionspeed(threading.Thread, threading.Condition()) print '\n\t######## testing multiprocessing.Condition\n' test_conditionspeed(multiprocessing.Process, multiprocessing.Condition()) print '\n\t######## testing condition managed by a server process\n' test_conditionspeed(multiprocessing.Process, manager.Condition()) gc.enable()if __name__ == '__main__': multiprocessing.freeze_support() test() |
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