674 lines
26 KiB
Python
674 lines
26 KiB
Python
# Copyright 2009 Brian Quinlan. All Rights Reserved.
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# Licensed to PSF under a Contributor Agreement.
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"""Implements ProcessPoolExecutor.
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The follow diagram and text describe the data-flow through the system:
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|======================= In-process =====================|== Out-of-process ==|
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+----------+ +----------+ +--------+ +-----------+ +---------+
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| | => | Work Ids | | | | Call Q | | Process |
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| | +----------+ | | +-----------+ | Pool |
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| | | ... | | | | ... | +---------+
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| | | 6 | => | | => | 5, call() | => | |
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| | | 7 | | | | ... | | |
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| Process | | ... | | Local | +-----------+ | Process |
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| Pool | +----------+ | Worker | | #1..n |
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| Executor | | Thread | | |
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| | +----------- + | | +-----------+ | |
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| | <=> | Work Items | <=> | | <= | Result Q | <= | |
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| | +------------+ | | +-----------+ | |
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| | | 6: call() | | | | ... | | |
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| | | future | | | | 4, result | | |
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| | | ... | | | | 3, except | | |
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+----------+ +------------+ +--------+ +-----------+ +---------+
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Executor.submit() called:
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- creates a uniquely numbered _WorkItem and adds it to the "Work Items" dict
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- adds the id of the _WorkItem to the "Work Ids" queue
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Local worker thread:
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- reads work ids from the "Work Ids" queue and looks up the corresponding
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WorkItem from the "Work Items" dict: if the work item has been cancelled then
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it is simply removed from the dict, otherwise it is repackaged as a
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_CallItem and put in the "Call Q". New _CallItems are put in the "Call Q"
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until "Call Q" is full. NOTE: the size of the "Call Q" is kept small because
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calls placed in the "Call Q" can no longer be cancelled with Future.cancel().
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- reads _ResultItems from "Result Q", updates the future stored in the
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"Work Items" dict and deletes the dict entry
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Process #1..n:
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- reads _CallItems from "Call Q", executes the calls, and puts the resulting
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_ResultItems in "Result Q"
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"""
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__author__ = 'Brian Quinlan (brian@sweetapp.com)'
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import atexit
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import os
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from concurrent.futures import _base
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import queue
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from queue import Full
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import multiprocessing as mp
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from multiprocessing.connection import wait
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from multiprocessing.queues import Queue
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import threading
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import weakref
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from functools import partial
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import itertools
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import traceback
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# Workers are created as daemon threads and processes. This is done to allow the
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# interpreter to exit when there are still idle processes in a
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# ProcessPoolExecutor's process pool (i.e. shutdown() was not called). However,
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# allowing workers to die with the interpreter has two undesirable properties:
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# - The workers would still be running during interpreter shutdown,
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# meaning that they would fail in unpredictable ways.
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# - The workers could be killed while evaluating a work item, which could
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# be bad if the callable being evaluated has external side-effects e.g.
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# writing to a file.
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#
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# To work around this problem, an exit handler is installed which tells the
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# workers to exit when their work queues are empty and then waits until the
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# threads/processes finish.
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_threads_wakeups = weakref.WeakKeyDictionary()
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_global_shutdown = False
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class _ThreadWakeup:
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def __init__(self):
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self._reader, self._writer = mp.Pipe(duplex=False)
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def close(self):
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self._writer.close()
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self._reader.close()
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def wakeup(self):
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self._writer.send_bytes(b"")
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def clear(self):
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while self._reader.poll():
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self._reader.recv_bytes()
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def _python_exit():
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global _global_shutdown
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_global_shutdown = True
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items = list(_threads_wakeups.items())
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for _, thread_wakeup in items:
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thread_wakeup.wakeup()
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for t, _ in items:
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t.join()
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# Controls how many more calls than processes will be queued in the call queue.
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# A smaller number will mean that processes spend more time idle waiting for
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# work while a larger number will make Future.cancel() succeed less frequently
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# (Futures in the call queue cannot be cancelled).
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EXTRA_QUEUED_CALLS = 1
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# Hack to embed stringification of remote traceback in local traceback
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class _RemoteTraceback(Exception):
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def __init__(self, tb):
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self.tb = tb
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def __str__(self):
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return self.tb
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class _ExceptionWithTraceback:
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def __init__(self, exc, tb):
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tb = traceback.format_exception(type(exc), exc, tb)
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tb = ''.join(tb)
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self.exc = exc
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self.tb = '\n"""\n%s"""' % tb
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def __reduce__(self):
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return _rebuild_exc, (self.exc, self.tb)
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def _rebuild_exc(exc, tb):
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exc.__cause__ = _RemoteTraceback(tb)
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return exc
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class _WorkItem(object):
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def __init__(self, future, fn, args, kwargs):
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self.future = future
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self.fn = fn
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self.args = args
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self.kwargs = kwargs
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class _ResultItem(object):
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def __init__(self, work_id, exception=None, result=None):
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self.work_id = work_id
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self.exception = exception
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self.result = result
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class _CallItem(object):
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def __init__(self, work_id, fn, args, kwargs):
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self.work_id = work_id
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self.fn = fn
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self.args = args
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self.kwargs = kwargs
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class _SafeQueue(Queue):
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"""Safe Queue set exception to the future object linked to a job"""
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def __init__(self, max_size=0, *, ctx, pending_work_items):
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self.pending_work_items = pending_work_items
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super().__init__(max_size, ctx=ctx)
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def _on_queue_feeder_error(self, e, obj):
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if isinstance(obj, _CallItem):
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tb = traceback.format_exception(type(e), e, e.__traceback__)
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e.__cause__ = _RemoteTraceback('\n"""\n{}"""'.format(''.join(tb)))
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work_item = self.pending_work_items.pop(obj.work_id, None)
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# work_item can be None if another process terminated. In this case,
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# the queue_manager_thread fails all work_items with BrokenProcessPool
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if work_item is not None:
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work_item.future.set_exception(e)
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else:
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super()._on_queue_feeder_error(e, obj)
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def _get_chunks(*iterables, chunksize):
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""" Iterates over zip()ed iterables in chunks. """
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it = zip(*iterables)
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while True:
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chunk = tuple(itertools.islice(it, chunksize))
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if not chunk:
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return
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yield chunk
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def _process_chunk(fn, chunk):
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""" Processes a chunk of an iterable passed to map.
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Runs the function passed to map() on a chunk of the
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iterable passed to map.
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This function is run in a separate process.
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"""
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return [fn(*args) for args in chunk]
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def _sendback_result(result_queue, work_id, result=None, exception=None):
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"""Safely send back the given result or exception"""
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try:
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result_queue.put(_ResultItem(work_id, result=result,
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exception=exception))
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except BaseException as e:
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exc = _ExceptionWithTraceback(e, e.__traceback__)
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result_queue.put(_ResultItem(work_id, exception=exc))
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def _process_worker(call_queue, result_queue, initializer, initargs):
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"""Evaluates calls from call_queue and places the results in result_queue.
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This worker is run in a separate process.
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Args:
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call_queue: A ctx.Queue of _CallItems that will be read and
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evaluated by the worker.
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result_queue: A ctx.Queue of _ResultItems that will written
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to by the worker.
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initializer: A callable initializer, or None
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initargs: A tuple of args for the initializer
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"""
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if initializer is not None:
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try:
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initializer(*initargs)
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except BaseException:
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_base.LOGGER.critical('Exception in initializer:', exc_info=True)
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# The parent will notice that the process stopped and
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# mark the pool broken
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return
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while True:
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call_item = call_queue.get(block=True)
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if call_item is None:
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# Wake up queue management thread
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result_queue.put(os.getpid())
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return
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try:
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r = call_item.fn(*call_item.args, **call_item.kwargs)
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except BaseException as e:
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exc = _ExceptionWithTraceback(e, e.__traceback__)
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_sendback_result(result_queue, call_item.work_id, exception=exc)
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else:
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_sendback_result(result_queue, call_item.work_id, result=r)
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# Liberate the resource as soon as possible, to avoid holding onto
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# open files or shared memory that is not needed anymore
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del call_item
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def _add_call_item_to_queue(pending_work_items,
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work_ids,
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call_queue):
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"""Fills call_queue with _WorkItems from pending_work_items.
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This function never blocks.
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Args:
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pending_work_items: A dict mapping work ids to _WorkItems e.g.
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{5: <_WorkItem...>, 6: <_WorkItem...>, ...}
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work_ids: A queue.Queue of work ids e.g. Queue([5, 6, ...]). Work ids
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are consumed and the corresponding _WorkItems from
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pending_work_items are transformed into _CallItems and put in
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call_queue.
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call_queue: A multiprocessing.Queue that will be filled with _CallItems
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derived from _WorkItems.
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"""
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while True:
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if call_queue.full():
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return
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try:
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work_id = work_ids.get(block=False)
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except queue.Empty:
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return
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else:
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work_item = pending_work_items[work_id]
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if work_item.future.set_running_or_notify_cancel():
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call_queue.put(_CallItem(work_id,
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work_item.fn,
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work_item.args,
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work_item.kwargs),
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block=True)
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else:
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del pending_work_items[work_id]
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continue
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def _queue_management_worker(executor_reference,
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processes,
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pending_work_items,
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work_ids_queue,
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call_queue,
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result_queue,
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thread_wakeup):
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"""Manages the communication between this process and the worker processes.
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This function is run in a local thread.
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Args:
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executor_reference: A weakref.ref to the ProcessPoolExecutor that owns
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this thread. Used to determine if the ProcessPoolExecutor has been
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garbage collected and that this function can exit.
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process: A list of the ctx.Process instances used as
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workers.
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pending_work_items: A dict mapping work ids to _WorkItems e.g.
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{5: <_WorkItem...>, 6: <_WorkItem...>, ...}
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work_ids_queue: A queue.Queue of work ids e.g. Queue([5, 6, ...]).
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call_queue: A ctx.Queue that will be filled with _CallItems
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derived from _WorkItems for processing by the process workers.
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result_queue: A ctx.SimpleQueue of _ResultItems generated by the
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process workers.
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thread_wakeup: A _ThreadWakeup to allow waking up the
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queue_manager_thread from the main Thread and avoid deadlocks
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caused by permanently locked queues.
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"""
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executor = None
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def shutting_down():
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return (_global_shutdown or executor is None
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or executor._shutdown_thread)
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def shutdown_worker():
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# This is an upper bound on the number of children alive.
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n_children_alive = sum(p.is_alive() for p in processes.values())
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n_children_to_stop = n_children_alive
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n_sentinels_sent = 0
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# Send the right number of sentinels, to make sure all children are
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# properly terminated.
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while n_sentinels_sent < n_children_to_stop and n_children_alive > 0:
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for i in range(n_children_to_stop - n_sentinels_sent):
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try:
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call_queue.put_nowait(None)
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n_sentinels_sent += 1
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except Full:
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break
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n_children_alive = sum(p.is_alive() for p in processes.values())
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# Release the queue's resources as soon as possible.
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call_queue.close()
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# If .join() is not called on the created processes then
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# some ctx.Queue methods may deadlock on Mac OS X.
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for p in processes.values():
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p.join()
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result_reader = result_queue._reader
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wakeup_reader = thread_wakeup._reader
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readers = [result_reader, wakeup_reader]
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while True:
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_add_call_item_to_queue(pending_work_items,
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work_ids_queue,
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call_queue)
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# Wait for a result to be ready in the result_queue while checking
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# that all worker processes are still running, or for a wake up
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# signal send. The wake up signals come either from new tasks being
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# submitted, from the executor being shutdown/gc-ed, or from the
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# shutdown of the python interpreter.
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worker_sentinels = [p.sentinel for p in processes.values()]
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ready = wait(readers + worker_sentinels)
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cause = None
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is_broken = True
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if result_reader in ready:
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try:
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result_item = result_reader.recv()
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is_broken = False
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except BaseException as e:
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cause = traceback.format_exception(type(e), e, e.__traceback__)
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elif wakeup_reader in ready:
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is_broken = False
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result_item = None
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thread_wakeup.clear()
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if is_broken:
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# Mark the process pool broken so that submits fail right now.
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executor = executor_reference()
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if executor is not None:
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executor._broken = ('A child process terminated '
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'abruptly, the process pool is not '
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'usable anymore')
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executor._shutdown_thread = True
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executor = None
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bpe = BrokenProcessPool("A process in the process pool was "
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"terminated abruptly while the future was "
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"running or pending.")
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if cause is not None:
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bpe.__cause__ = _RemoteTraceback(
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f"\n'''\n{''.join(cause)}'''")
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# All futures in flight must be marked failed
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for work_id, work_item in pending_work_items.items():
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work_item.future.set_exception(bpe)
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# Delete references to object. See issue16284
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del work_item
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pending_work_items.clear()
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# Terminate remaining workers forcibly: the queues or their
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# locks may be in a dirty state and block forever.
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for p in processes.values():
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p.terminate()
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shutdown_worker()
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return
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if isinstance(result_item, int):
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# Clean shutdown of a worker using its PID
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# (avoids marking the executor broken)
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assert shutting_down()
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p = processes.pop(result_item)
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p.join()
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if not processes:
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shutdown_worker()
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return
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elif result_item is not None:
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work_item = pending_work_items.pop(result_item.work_id, None)
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# work_item can be None if another process terminated (see above)
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if work_item is not None:
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if result_item.exception:
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work_item.future.set_exception(result_item.exception)
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else:
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work_item.future.set_result(result_item.result)
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# Delete references to object. See issue16284
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del work_item
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# Delete reference to result_item
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del result_item
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# Check whether we should start shutting down.
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executor = executor_reference()
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# No more work items can be added if:
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# - The interpreter is shutting down OR
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# - The executor that owns this worker has been collected OR
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# - The executor that owns this worker has been shutdown.
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if shutting_down():
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try:
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# Flag the executor as shutting down as early as possible if it
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# is not gc-ed yet.
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if executor is not None:
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executor._shutdown_thread = True
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# Since no new work items can be added, it is safe to shutdown
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# this thread if there are no pending work items.
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if not pending_work_items:
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shutdown_worker()
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return
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except Full:
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# This is not a problem: we will eventually be woken up (in
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# result_queue.get()) and be able to send a sentinel again.
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pass
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executor = None
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_system_limits_checked = False
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_system_limited = None
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def _check_system_limits():
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global _system_limits_checked, _system_limited
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if _system_limits_checked:
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if _system_limited:
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raise NotImplementedError(_system_limited)
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_system_limits_checked = True
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try:
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nsems_max = os.sysconf("SC_SEM_NSEMS_MAX")
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except (AttributeError, ValueError):
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# sysconf not available or setting not available
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return
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if nsems_max == -1:
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# indetermined limit, assume that limit is determined
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# by available memory only
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return
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if nsems_max >= 256:
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# minimum number of semaphores available
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# according to POSIX
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return
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_system_limited = ("system provides too few semaphores (%d"
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" available, 256 necessary)" % nsems_max)
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raise NotImplementedError(_system_limited)
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def _chain_from_iterable_of_lists(iterable):
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"""
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Specialized implementation of itertools.chain.from_iterable.
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Each item in *iterable* should be a list. This function is
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careful not to keep references to yielded objects.
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"""
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for element in iterable:
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element.reverse()
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while element:
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yield element.pop()
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class BrokenProcessPool(_base.BrokenExecutor):
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"""
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Raised when a process in a ProcessPoolExecutor terminated abruptly
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while a future was in the running state.
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"""
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class ProcessPoolExecutor(_base.Executor):
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def __init__(self, max_workers=None, mp_context=None,
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initializer=None, initargs=()):
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"""Initializes a new ProcessPoolExecutor instance.
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Args:
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max_workers: The maximum number of processes that can be used to
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execute the given calls. If None or not given then as many
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worker processes will be created as the machine has processors.
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mp_context: A multiprocessing context to launch the workers. This
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object should provide SimpleQueue, Queue and Process.
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initializer: An callable used to initialize worker processes.
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initargs: A tuple of arguments to pass to the initializer.
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"""
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_check_system_limits()
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if max_workers is None:
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self._max_workers = os.cpu_count() or 1
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else:
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if max_workers <= 0:
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raise ValueError("max_workers must be greater than 0")
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self._max_workers = max_workers
|
|
|
|
if mp_context is None:
|
|
mp_context = mp.get_context()
|
|
self._mp_context = mp_context
|
|
|
|
if initializer is not None and not callable(initializer):
|
|
raise TypeError("initializer must be a callable")
|
|
self._initializer = initializer
|
|
self._initargs = initargs
|
|
|
|
# Management thread
|
|
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 = {}
|
|
|
|
# Create communication channels for the executor
|
|
# 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.
|
|
queue_size = self._max_workers + EXTRA_QUEUED_CALLS
|
|
self._call_queue = _SafeQueue(
|
|
max_size=queue_size, ctx=self._mp_context,
|
|
pending_work_items=self._pending_work_items)
|
|
# 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 = mp_context.SimpleQueue()
|
|
self._work_ids = queue.Queue()
|
|
|
|
# _ThreadWakeup is a communication channel used to interrupt the wait
|
|
# of the main loop of queue_manager_thread from another thread (e.g.
|
|
# when calling executor.submit or executor.shutdown). We do not use the
|
|
# _result_queue to send the wakeup signal to the queue_manager_thread
|
|
# as it could result in a deadlock if a worker process dies with the
|
|
# _result_queue write lock still acquired.
|
|
self._queue_management_thread_wakeup = _ThreadWakeup()
|
|
|
|
def _start_queue_management_thread(self):
|
|
if self._queue_management_thread is None:
|
|
# When the executor gets garbarge collected, the weakref callback
|
|
# will wake up the queue management thread so that it can terminate
|
|
# if there is no pending work item.
|
|
def weakref_cb(_,
|
|
thread_wakeup=self._queue_management_thread_wakeup):
|
|
mp.util.debug('Executor collected: triggering callback for'
|
|
' QueueManager wakeup')
|
|
thread_wakeup.wakeup()
|
|
# 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_wakeup),
|
|
name="QueueManagerThread")
|
|
self._queue_management_thread.daemon = True
|
|
self._queue_management_thread.start()
|
|
_threads_wakeups[self._queue_management_thread] = \
|
|
self._queue_management_thread_wakeup
|
|
|
|
def _adjust_process_count(self):
|
|
for _ in range(len(self._processes), self._max_workers):
|
|
p = self._mp_context.Process(
|
|
target=_process_worker,
|
|
args=(self._call_queue,
|
|
self._result_queue,
|
|
self._initializer,
|
|
self._initargs))
|
|
p.start()
|
|
self._processes[p.pid] = p
|
|
|
|
def submit(self, fn, *args, **kwargs):
|
|
with self._shutdown_lock:
|
|
if self._broken:
|
|
raise BrokenProcessPool(self._broken)
|
|
if self._shutdown_thread:
|
|
raise RuntimeError('cannot schedule new futures after shutdown')
|
|
if _global_shutdown:
|
|
raise RuntimeError('cannot schedule new futures after '
|
|
'interpreter 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._queue_management_thread_wakeup.wakeup()
|
|
|
|
self._start_queue_management_thread()
|
|
return f
|
|
submit.__doc__ = _base.Executor.submit.__doc__
|
|
|
|
def map(self, fn, *iterables, timeout=None, chunksize=1):
|
|
"""Returns an 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 _chain_from_iterable_of_lists(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._queue_management_thread_wakeup.wakeup()
|
|
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
|
|
if self._call_queue is not None:
|
|
self._call_queue.close()
|
|
if wait:
|
|
self._call_queue.join_thread()
|
|
self._call_queue = None
|
|
self._result_queue = None
|
|
self._processes = None
|
|
|
|
if self._queue_management_thread_wakeup:
|
|
self._queue_management_thread_wakeup.close()
|
|
self._queue_management_thread_wakeup = None
|
|
|
|
shutdown.__doc__ = _base.Executor.shutdown.__doc__
|
|
|
|
atexit.register(_python_exit)
|