| # Copyright 2009 Brian Quinlan. All Rights Reserved. |
| # Licensed to PSF under a Contributor Agreement. |
| |
| """Implements ProcessPoolExecutor. |
| |
| The follow diagram and text describe the data-flow through the system: |
| |
| |======================= In-process =====================|== Out-of-process ==| |
| |
| +----------+ +----------+ +--------+ +-----------+ +---------+ |
| | | => | Work Ids | => | | => | Call Q | => | | |
| | | +----------+ | | +-----------+ | | |
| | | | ... | | | | ... | | | |
| | | | 6 | | | | 5, call() | | | |
| | | | 7 | | | | ... | | | |
| | Process | | ... | | Local | +-----------+ | Process | |
| | Pool | +----------+ | Worker | | #1..n | |
| | Executor | | Thread | | | |
| | | +----------- + | | +-----------+ | | |
| | | <=> | Work Items | <=> | | <= | Result Q | <= | | |
| | | +------------+ | | +-----------+ | | |
| | | | 6: call() | | | | ... | | | |
| | | | future | | | | 4, result | | | |
| | | | ... | | | | 3, except | | | |
| +----------+ +------------+ +--------+ +-----------+ +---------+ |
| |
| Executor.submit() called: |
| - creates a uniquely numbered _WorkItem and adds it to the "Work Items" dict |
| - adds the id of the _WorkItem to the "Work Ids" queue |
| |
| Local worker thread: |
| - reads work ids from the "Work Ids" queue and looks up the corresponding |
| WorkItem from the "Work Items" dict: if the work item has been cancelled then |
| it is simply removed from the dict, otherwise it is repackaged as a |
| _CallItem and put in the "Call Q". New _CallItems are put in the "Call Q" |
| until "Call Q" is full. NOTE: the size of the "Call Q" is kept small because |
| calls placed in the "Call Q" can no longer be cancelled with Future.cancel(). |
| - reads _ResultItems from "Result Q", updates the future stored in the |
| "Work Items" dict and deletes the dict entry |
| |
| Process #1..n: |
| - reads _CallItems from "Call Q", executes the calls, and puts the resulting |
| _ResultItems in "Result Q" |
| """ |
| |
| __author__ = 'Brian Quinlan (brian@sweetapp.com)' |
| |
| import atexit |
| import os |
| from concurrent.futures import _base |
| import queue |
| from queue import Full |
| import multiprocessing |
| from multiprocessing import SimpleQueue |
| from multiprocessing.connection import wait |
| import threading |
| import weakref |
| from functools import partial |
| import itertools |
| import traceback |
| |
| # Workers are created as daemon threads and processes. This is done to allow the |
| # interpreter to exit when there are still idle processes in a |
| # ProcessPoolExecutor's process pool (i.e. shutdown() was not called). However, |
| # allowing workers to die with the interpreter has two undesirable properties: |
| # - The workers would still be running during interpretor shutdown, |
| # meaning that they would fail in unpredictable ways. |
| # - The workers could be killed while evaluating a work item, which could |
| # be bad if the callable being evaluated has external side-effects e.g. |
| # writing to a file. |
| # |
| # To work around this problem, an exit handler is installed which tells the |
| # workers to exit when their work queues are empty and then waits until the |
| # threads/processes finish. |
| |
| _threads_queues = weakref.WeakKeyDictionary() |
| _shutdown = False |
| |
| def _python_exit(): |
| global _shutdown |
| _shutdown = True |
| items = list(_threads_queues.items()) |
| for t, q in items: |
| q.put(None) |
| for t, q in items: |
| t.join() |
| |
| # Controls how many more calls than processes will be queued in the call queue. |
| # A smaller number will mean that processes spend more time idle waiting for |
| # work while a larger number will make Future.cancel() succeed less frequently |
| # (Futures in the call queue cannot be cancelled). |
| EXTRA_QUEUED_CALLS = 1 |
| |
| # Hack to embed stringification of remote traceback in local traceback |
| |
| class _RemoteTraceback(Exception): |
| def __init__(self, tb): |
| self.tb = tb |
| def __str__(self): |
| return self.tb |
| |
| class _ExceptionWithTraceback: |
| def __init__(self, exc, tb): |
| tb = traceback.format_exception(type(exc), exc, tb) |
| tb = ''.join(tb) |
| self.exc = exc |
| self.tb = '\n"""\n%s"""' % tb |
| def __reduce__(self): |
| return _rebuild_exc, (self.exc, self.tb) |
| |
| def _rebuild_exc(exc, tb): |
| exc.__cause__ = _RemoteTraceback(tb) |
| return exc |
| |
| class _WorkItem(object): |
| def __init__(self, future, fn, args, kwargs): |
| self.future = future |
| self.fn = fn |
| self.args = args |
| self.kwargs = kwargs |
| |
| class _ResultItem(object): |
| def __init__(self, work_id, exception=None, result=None): |
| self.work_id = work_id |
| self.exception = exception |
| self.result = result |
| |
| class _CallItem(object): |
| def __init__(self, work_id, fn, args, kwargs): |
| self.work_id = work_id |
| self.fn = fn |
| self.args = args |
| self.kwargs = kwargs |
| |
| def _get_chunks(*iterables, chunksize): |
| """ Iterates over zip()ed iterables in chunks. """ |
| it = zip(*iterables) |
| while True: |
| chunk = tuple(itertools.islice(it, chunksize)) |
| if not chunk: |
| return |
| yield chunk |
| |
| def _process_chunk(fn, chunk): |
| """ Processes a chunk of an iterable passed to map. |
| |
| Runs the function passed to map() on a chunk of the |
| iterable passed to map. |
| |
| This function is run in a separate process. |
| |
| """ |
| return [fn(*args) for args in chunk] |
| |
| def _process_worker(call_queue, result_queue): |
| """Evaluates calls from call_queue and places the results in result_queue. |
| |
| This worker is run in a separate process. |
| |
| Args: |
| call_queue: A multiprocessing.Queue of _CallItems that will be read and |
| evaluated by the worker. |
| result_queue: A multiprocessing.Queue of _ResultItems that will written |
| to by the worker. |
| shutdown: A multiprocessing.Event that will be set as a signal to the |
| worker that it should exit when call_queue is empty. |
| """ |
| while True: |
| call_item = call_queue.get(block=True) |
| if call_item is None: |
| # Wake up queue management thread |
| result_queue.put(os.getpid()) |
| return |
| try: |
| r = call_item.fn(*call_item.args, **call_item.kwargs) |
| except BaseException as e: |
| exc = _ExceptionWithTraceback(e, e.__traceback__) |
| result_queue.put(_ResultItem(call_item.work_id, exception=exc)) |
| else: |
| result_queue.put(_ResultItem(call_item.work_id, |
| result=r)) |
| |
| def _add_call_item_to_queue(pending_work_items, |
| work_ids, |
| call_queue): |
| """Fills call_queue with _WorkItems from pending_work_items. |
| |
| This function never blocks. |
| |
| Args: |
| pending_work_items: A dict mapping work ids to _WorkItems e.g. |
| {5: <_WorkItem...>, 6: <_WorkItem...>, ...} |
| work_ids: A queue.Queue of work ids e.g. Queue([5, 6, ...]). Work ids |
| are consumed and the corresponding _WorkItems from |
| pending_work_items are transformed into _CallItems and put in |
| call_queue. |
| call_queue: A multiprocessing.Queue that will be filled with _CallItems |
| derived from _WorkItems. |
| """ |
| while True: |
| if call_queue.full(): |
| return |
| try: |
| work_id = work_ids.get(block=False) |
| except queue.Empty: |
| return |
| else: |
| work_item = pending_work_items[work_id] |
| |
| if work_item.future.set_running_or_notify_cancel(): |
| call_queue.put(_CallItem(work_id, |
| work_item.fn, |
| work_item.args, |
| work_item.kwargs), |
| block=True) |
| else: |
| del pending_work_items[work_id] |
| continue |
| |
| def _queue_management_worker(executor_reference, |
| processes, |
| pending_work_items, |
| work_ids_queue, |
| call_queue, |
| result_queue): |
| """Manages the communication between this process and the worker processes. |
| |
| This function is run in a local thread. |
| |
| Args: |
| executor_reference: A weakref.ref to the ProcessPoolExecutor that owns |
| this thread. Used to determine if the ProcessPoolExecutor has been |
| garbage collected and that this function can exit. |
| process: A list of the multiprocessing.Process instances used as |
| workers. |
| pending_work_items: A dict mapping work ids to _WorkItems e.g. |
| {5: <_WorkItem...>, 6: <_WorkItem...>, ...} |
| work_ids_queue: A queue.Queue of work ids e.g. Queue([5, 6, ...]). |
| call_queue: A multiprocessing.Queue that will be filled with _CallItems |
| derived from _WorkItems for processing by the process workers. |
| result_queue: A multiprocessing.Queue of _ResultItems generated by the |
| process workers. |
| """ |
| executor = None |
| |
| def shutting_down(): |
| return _shutdown or executor is None or executor._shutdown_thread |
| |
| def shutdown_worker(): |
| # This is an upper bound |
| nb_children_alive = sum(p.is_alive() for p in processes.values()) |
| for i in range(0, nb_children_alive): |
| call_queue.put_nowait(None) |
| # Release the queue's resources as soon as possible. |
| call_queue.close() |
| # If .join() is not called on the created processes then |
| # some multiprocessing.Queue methods may deadlock on Mac OS X. |
| for p in processes.values(): |
| p.join() |
| |
| reader = result_queue._reader |
| |
| while True: |
| _add_call_item_to_queue(pending_work_items, |
| work_ids_queue, |
| call_queue) |
| |
| sentinels = [p.sentinel for p in processes.values()] |
| assert sentinels |
| ready = wait([reader] + sentinels) |
| if reader in ready: |
| result_item = reader.recv() |
| else: |
| # Mark the process pool broken so that submits fail right now. |
| executor = executor_reference() |
| if executor is not None: |
| executor._broken = True |
| executor._shutdown_thread = True |
| executor = None |
| # All futures in flight must be marked failed |
| for work_id, work_item in pending_work_items.items(): |
| work_item.future.set_exception( |
| BrokenProcessPool( |
| "A process in the process pool was " |
| "terminated abruptly while the future was " |
| "running or pending." |
| )) |
| # Delete references to object. See issue16284 |
| del work_item |
| pending_work_items.clear() |
| # Terminate remaining workers forcibly: the queues or their |
| # locks may be in a dirty state and block forever. |
| for p in processes.values(): |
| p.terminate() |
| shutdown_worker() |
| return |
| if isinstance(result_item, int): |
| # Clean shutdown of a worker using its PID |
| # (avoids marking the executor broken) |
| assert shutting_down() |
| p = processes.pop(result_item) |
| p.join() |
| if not processes: |
| shutdown_worker() |
| return |
| elif result_item is not None: |
| work_item = pending_work_items.pop(result_item.work_id, None) |
| # work_item can be None if another process terminated (see above) |
| if work_item is not None: |
| if result_item.exception: |
| work_item.future.set_exception(result_item.exception) |
| else: |
| work_item.future.set_result(result_item.result) |
| # Delete references to object. See issue16284 |
| del work_item |
| # Check whether we should start shutting down. |
| executor = executor_reference() |
| # No more work items can be added if: |
| # - The interpreter is shutting down OR |
| # - The executor that owns this worker has been collected OR |
| # - The executor that owns this worker has been shutdown. |
| if shutting_down(): |
| try: |
| # Since no new work items can be added, it is safe to shutdown |
| # this thread if there are no pending work items. |
| if not pending_work_items: |
| shutdown_worker() |
| return |
| except Full: |
| # This is not a problem: we will eventually be woken up (in |
| # result_queue.get()) and be able to send a sentinel again. |
| pass |
| executor = None |
| |
| _system_limits_checked = False |
| _system_limited = None |
| def _check_system_limits(): |
| global _system_limits_checked, _system_limited |
| if _system_limits_checked: |
| if _system_limited: |
| raise NotImplementedError(_system_limited) |
| _system_limits_checked = True |
| try: |
| nsems_max = os.sysconf("SC_SEM_NSEMS_MAX") |
| except (AttributeError, ValueError): |
| # sysconf not available or setting not available |
| return |
| if nsems_max == -1: |
| # indetermined limit, assume that limit is determined |
| # by available memory only |
| return |
| if nsems_max >= 256: |
| # minimum number of semaphores available |
| # according to POSIX |
| return |
| _system_limited = "system provides too few semaphores (%d available, 256 necessary)" % nsems_max |
| raise NotImplementedError(_system_limited) |
| |
| |
| class BrokenProcessPool(RuntimeError): |
| """ |
| Raised when a process in a ProcessPoolExecutor terminated abruptly |
| while a future was in the running state. |
| """ |
| |
| |
| class ProcessPoolExecutor(_base.Executor): |
| def __init__(self, max_workers=None): |
| """Initializes a new ProcessPoolExecutor instance. |
| |
| Args: |
| max_workers: The maximum number of processes that can be used to |
| execute the given calls. If None or not given then as many |
| worker processes will be created as the machine has processors. |
| """ |
| _check_system_limits() |
| |
| if max_workers is None: |
| self._max_workers = os.cpu_count() or 1 |
| else: |
| if max_workers <= 0: |
| raise ValueError("max_workers must be greater than 0") |
| |
| self._max_workers = max_workers |
| |
| # Make the call queue slightly larger than the number of processes to |
| # prevent the worker processes from idling. But don't make it too big |
| # because futures in the call queue cannot be cancelled. |
| self._call_queue = multiprocessing.Queue(self._max_workers + |
| EXTRA_QUEUED_CALLS) |
| # Killed worker processes can produce spurious "broken pipe" |
| # tracebacks in the queue's own worker thread. But we detect killed |
| # processes anyway, so silence the tracebacks. |
| self._call_queue._ignore_epipe = True |
| self._result_queue = SimpleQueue() |
| self._work_ids = queue.Queue() |
| self._queue_management_thread = None |
| # Map of pids to processes |
| self._processes = {} |
| |
| # Shutdown is a two-step process. |
| self._shutdown_thread = False |
| self._shutdown_lock = threading.Lock() |
| self._broken = False |
| self._queue_count = 0 |
| self._pending_work_items = {} |
| |
| def _start_queue_management_thread(self): |
| # When the executor gets lost, the weakref callback will wake up |
| # the queue management thread. |
| def weakref_cb(_, q=self._result_queue): |
| q.put(None) |
| if self._queue_management_thread is None: |
| # Start the processes so that their sentinels are known. |
| self._adjust_process_count() |
| self._queue_management_thread = threading.Thread( |
| target=_queue_management_worker, |
| args=(weakref.ref(self, weakref_cb), |
| self._processes, |
| self._pending_work_items, |
| self._work_ids, |
| self._call_queue, |
| self._result_queue)) |
| self._queue_management_thread.daemon = True |
| self._queue_management_thread.start() |
| _threads_queues[self._queue_management_thread] = self._result_queue |
| |
| def _adjust_process_count(self): |
| for _ in range(len(self._processes), self._max_workers): |
| p = multiprocessing.Process( |
| target=_process_worker, |
| args=(self._call_queue, |
| self._result_queue)) |
| p.start() |
| self._processes[p.pid] = p |
| |
| def submit(self, fn, *args, **kwargs): |
| with self._shutdown_lock: |
| if self._broken: |
| raise BrokenProcessPool('A child process terminated ' |
| 'abruptly, the process pool is not usable anymore') |
| if self._shutdown_thread: |
| raise RuntimeError('cannot schedule new futures after shutdown') |
| |
| f = _base.Future() |
| w = _WorkItem(f, fn, args, kwargs) |
| |
| self._pending_work_items[self._queue_count] = w |
| self._work_ids.put(self._queue_count) |
| self._queue_count += 1 |
| # Wake up queue management thread |
| self._result_queue.put(None) |
| |
| self._start_queue_management_thread() |
| return f |
| submit.__doc__ = _base.Executor.submit.__doc__ |
| |
| def map(self, fn, *iterables, timeout=None, chunksize=1): |
| """Returns a iterator equivalent to map(fn, iter). |
| |
| Args: |
| fn: A callable that will take as many arguments as there are |
| passed iterables. |
| timeout: The maximum number of seconds to wait. If None, then there |
| is no limit on the wait time. |
| chunksize: If greater than one, the iterables will be chopped into |
| chunks of size chunksize and submitted to the process pool. |
| If set to one, the items in the list will be sent one at a time. |
| |
| Returns: |
| An iterator equivalent to: map(func, *iterables) but the calls may |
| be evaluated out-of-order. |
| |
| Raises: |
| TimeoutError: If the entire result iterator could not be generated |
| before the given timeout. |
| Exception: If fn(*args) raises for any values. |
| """ |
| if chunksize < 1: |
| raise ValueError("chunksize must be >= 1.") |
| |
| results = super().map(partial(_process_chunk, fn), |
| _get_chunks(*iterables, chunksize=chunksize), |
| timeout=timeout) |
| return itertools.chain.from_iterable(results) |
| |
| def shutdown(self, wait=True): |
| with self._shutdown_lock: |
| self._shutdown_thread = True |
| if self._queue_management_thread: |
| # Wake up queue management thread |
| self._result_queue.put(None) |
| if wait: |
| self._queue_management_thread.join() |
| # To reduce the risk of opening too many files, remove references to |
| # objects that use file descriptors. |
| self._queue_management_thread = None |
| self._call_queue = None |
| self._result_queue = None |
| self._processes = None |
| shutdown.__doc__ = _base.Executor.shutdown.__doc__ |
| |
| atexit.register(_python_exit) |