process.py

# Copyright 2009 Brian Quinlan. All Rights Reserved.
# Licensed to PSF under a Contributor Agreement.

"""Implements ProcessPoolExecutor.

The following diagram and text describe the data-flow through the system:

|======================= In-process =====================|== Out-of-process ==|

+----------+ +----------+ +--------+ +-----------+ +---------+
| | => | Work Ids | | | | Call Q | | Process |
| | +----------+ | | +-----------+ | Pool |
| | | ... | | | | ... | +---------+
| | | 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)'

importos
fromconcurrent.futuresimport_base
importqueue
importmultiprocessingasmp
# This import is required to load the multiprocessing.connection submodule
# so that it can be accessed later as `mp.connection`
importmultiprocessing.connection
frommultiprocessing.queuesimportQueue
importthreading
importweakref
fromfunctoolsimportpartial
importitertools
importsys
fromtracebackimportformat_exception


_threads_wakeups=weakref.WeakKeyDictionary()
_global_shutdown=False


class_ThreadWakeup:
def__init__(self):
self._closed=False
self._lock=threading.Lock()
self._reader, self._writer=mp.Pipe(duplex=False)

defclose(self):
# Please note that we do not take the self._lock when
# calling clear() (to avoid deadlocking) so this method can
# only be called safely from the same thread as all calls to
# clear() even if you hold the lock. Otherwise we
# might try to read from the closed pipe.
withself._lock:
ifnotself._closed:
self._closed=True
self._writer.close()
self._reader.close()

defwakeup(self):
withself._lock:
ifnotself._closed:
self._writer.send_bytes(b"")

defclear(self):
ifself._closed:
raiseRuntimeError('operation on closed _ThreadWakeup')
whileself._reader.poll():
self._reader.recv_bytes()


def_python_exit():
global_global_shutdown
_global_shutdown=True
items=list(_threads_wakeups.items())
for_, thread_wakeupinitems:
# call not protected by ProcessPoolExecutor._shutdown_lock
thread_wakeup.wakeup()
fort, _initems:
t.join()

# Register for `_python_exit()` to be called just before joining all
# non-daemon threads. This is used instead of `atexit.register()` for
# compatibility with subinterpreters, which no longer support daemon threads.
# See bpo-39812 for context.
threading._register_atexit(_python_exit)

# 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


# On Windows, WaitForMultipleObjects is used to wait for processes to finish.
# It can wait on, at most, 63 objects. There is an overhead of two objects:
# - the result queue reader
# - the thread wakeup reader
_MAX_WINDOWS_WORKERS=63-2

# Hack to embed stringification of remote traceback in local traceback

class_RemoteTraceback(Exception):
def__init__(self, tb):
self.tb=tb
def__str__(self):
returnself.tb

class_ExceptionWithTraceback:
def__init__(self, exc, tb):
tb=''.join(format_exception(type(exc), exc, tb))
self.exc=exc
# Traceback object needs to be garbage-collected as its frames
# contain references to all the objects in the exception scope
self.exc.__traceback__=None
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)
returnexc

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, exit_pid=None):
self.work_id=work_id
self.exception=exception
self.result=result
self.exit_pid=exit_pid

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


class_SafeQueue(Queue):
"""Safe Queue set exception to the future object linked to a job"""
def__init__(self, max_size=0, *, ctx, pending_work_items, thread_wakeup):
self.pending_work_items=pending_work_items
self.thread_wakeup=thread_wakeup
super().__init__(max_size, ctx=ctx)

def_on_queue_feeder_error(self, e, obj):
ifisinstance(obj, _CallItem):
tb=format_exception(type(e), e, e.__traceback__)
e.__cause__=_RemoteTraceback('\n"""\n{}"""'.format(''.join(tb)))
work_item=self.pending_work_items.pop(obj.work_id, None)
self.thread_wakeup.wakeup()
# work_item can be None if another process terminated. In this
# case, the executor_manager_thread fails all work_items
# with BrokenProcessPool
ifwork_itemisnotNone:
work_item.future.set_exception(e)
else:
super()._on_queue_feeder_error(e, obj)


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) forargsinchunk]


def_sendback_result(result_queue, work_id, result=None, exception=None,
exit_pid=None):
"""Safely send back the given result or exception"""
try:
result_queue.put(_ResultItem(work_id, result=result,
exception=exception, exit_pid=exit_pid))
exceptBaseExceptionase:
exc=_ExceptionWithTraceback(e, e.__traceback__)
result_queue.put(_ResultItem(work_id, exception=exc,
exit_pid=exit_pid))


def_process_worker(call_queue, result_queue, initializer, initargs, max_tasks=None):
"""Evaluates calls from call_queue and places the results in result_queue.

 This worker is run in a separate process.

 Args:
 call_queue: A ctx.Queue of _CallItems that will be read and
 evaluated by the worker.
 result_queue: A ctx.Queue of _ResultItems that will written
 to by the worker.
 initializer: A callable initializer, or None
 initargs: A tuple of args for the initializer
 """
ifinitializerisnotNone:
try:
initializer(*initargs)
exceptBaseException:
_base.LOGGER.critical('Exception in initializer:', exc_info=True)
# The parent will notice that the process stopped and
# mark the pool broken
return
num_tasks=0
exit_pid=None
whileTrue:
call_item=call_queue.get(block=True)
ifcall_itemisNone:
# Wake up queue management thread
result_queue.put(os.getpid())
return

ifmax_tasksisnotNone:
num_tasks+=1
ifnum_tasks>=max_tasks:
exit_pid=os.getpid()

try:
r=call_item.fn(*call_item.args, **call_item.kwargs)
exceptBaseExceptionase:
exc=_ExceptionWithTraceback(e, e.__traceback__)
_sendback_result(result_queue, call_item.work_id, exception=exc,
exit_pid=exit_pid)
else:
_sendback_result(result_queue, call_item.work_id, result=r,
exit_pid=exit_pid)
delr

# Liberate the resource as soon as possible, to avoid holding onto
# open files or shared memory that is not needed anymore
delcall_item

ifexit_pidisnotNone:
return


class_ExecutorManagerThread(threading.Thread):
"""Manages the communication between this process and the worker processes.

 The manager is run in a local thread.

 Args:
 executor: A reference to the ProcessPoolExecutor that owns
 this thread. A weakref will be own by the manager as well as
 references to internal objects used to introspect the state of
 the executor.
 """

def__init__(self, executor):
# Store references to necessary internals of the executor.

# A _ThreadWakeup to allow waking up the queue_manager_thread from the
# main Thread and avoid deadlocks caused by permanently locked queues.
self.thread_wakeup=executor._executor_manager_thread_wakeup
self.shutdown_lock=executor._shutdown_lock

# A weakref.ref to the ProcessPoolExecutor that owns this thread. Used
# to determine if the ProcessPoolExecutor has been garbage collected
# and that the manager can exit.
# When the executor gets garbage collected, the weakref callback
# will wake up the queue management thread so that it can terminate
# if there is no pending work item.
defweakref_cb(_,
thread_wakeup=self.thread_wakeup,
mp_util_debug=mp.util.debug):
mp_util_debug('Executor collected: triggering callback for'
' QueueManager wakeup')
thread_wakeup.wakeup()

self.executor_reference=weakref.ref(executor, weakref_cb)

# A list of the ctx.Process instances used as workers.
self.processes=executor._processes

# A ctx.Queue that will be filled with _CallItems derived from
# _WorkItems for processing by the process workers.
self.call_queue=executor._call_queue

# A ctx.SimpleQueue of _ResultItems generated by the process workers.
self.result_queue=executor._result_queue

# A queue.Queue of work ids e.g. Queue([5, 6, ...]).
self.work_ids_queue=executor._work_ids

# Maximum number of tasks a worker process can execute before
# exiting safely
self.max_tasks_per_child=executor._max_tasks_per_child

# A dict mapping work ids to _WorkItems e.g.
# {5: <_WorkItem...>, 6: <_WorkItem...>, ...}
self.pending_work_items=executor._pending_work_items

super().__init__()

defrun(self):
# Main loop for the executor manager thread.

whileTrue:
# gh-109047: During Python finalization, self.call_queue.put()
# creation of a thread can fail with RuntimeError.
try:
self.add_call_item_to_queue()
exceptBaseExceptionasexc:
cause=format_exception(exc)
self.terminate_broken(cause)
return

result_item, is_broken, cause=self.wait_result_broken_or_wakeup()

ifis_broken:
self.terminate_broken(cause)
return
ifresult_itemisnotNone:
self.process_result_item(result_item)

process_exited=result_item.exit_pidisnotNone
ifprocess_exited:
p=self.processes.pop(result_item.exit_pid)
p.join()

# Delete reference to result_item to avoid keeping references
# while waiting on new results.
delresult_item

ifexecutor:=self.executor_reference():
ifprocess_exited:
withself.shutdown_lock:
executor._adjust_process_count()
else:
executor._idle_worker_semaphore.release()
delexecutor

ifself.is_shutting_down():
self.flag_executor_shutting_down()

# When only canceled futures remain in pending_work_items, our
# next call to wait_result_broken_or_wakeup would hang forever.
# This makes sure we have some running futures or none at all.
self.add_call_item_to_queue()

# Since no new work items can be added, it is safe to shutdown
# this thread if there are no pending work items.
ifnotself.pending_work_items:
self.join_executor_internals()
return

defadd_call_item_to_queue(self):
# Fills call_queue with _WorkItems from pending_work_items.
# This function never blocks.
whileTrue:
ifself.call_queue.full():
return
try:
work_id=self.work_ids_queue.get(block=False)
exceptqueue.Empty:
return
else:
work_item=self.pending_work_items[work_id]

ifwork_item.future.set_running_or_notify_cancel():
self.call_queue.put(_CallItem(work_id,
work_item.fn,
work_item.args,
work_item.kwargs),
block=True)
else:
delself.pending_work_items[work_id]
continue

defwait_result_broken_or_wakeup(self):
# Wait for a result to be ready in the result_queue while checking
# that all worker processes are still running, or for a wake up
# signal send. The wake up signals come either from new tasks being
# submitted, from the executor being shutdown/gc-ed, or from the
# shutdown of the python interpreter.
result_reader=self.result_queue._reader
assertnotself.thread_wakeup._closed
wakeup_reader=self.thread_wakeup._reader
readers= [result_reader, wakeup_reader]
worker_sentinels= [p.sentinelforpinlist(self.processes.values())]
ready=mp.connection.wait(readers+worker_sentinels)

cause=None
is_broken=True
result_item=None
ifresult_readerinready:
try:
result_item=result_reader.recv()
is_broken=False
exceptBaseExceptionasexc:
cause=format_exception(exc)

elifwakeup_readerinready:
is_broken=False

self.thread_wakeup.clear()

returnresult_item, is_broken, cause

defprocess_result_item(self, result_item):
# Process the received a result_item. This can be either the PID of a
# worker that exited gracefully or a _ResultItem

# Received a _ResultItem so mark the future as completed.
work_item=self.pending_work_items.pop(result_item.work_id, None)
# work_item can be None if another process terminated (see above)
ifwork_itemisnotNone:
ifresult_item.exceptionisnotNone:
work_item.future.set_exception(result_item.exception)
else:
work_item.future.set_result(result_item.result)

defis_shutting_down(self):
# Check whether we should start shutting down the executor.
executor=self.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.
return (_global_shutdownorexecutorisNone
orexecutor._shutdown_thread)

def_terminate_broken(self, cause):
# Terminate the executor because it is in a broken state. The cause
# argument can be used to display more information on the error that
# lead the executor into becoming broken.

# Mark the process pool broken so that submits fail right now.
executor=self.executor_reference()
ifexecutorisnotNone:
executor._broken= ('A child process terminated '
'abruptly, the process pool is not '
'usable anymore')
executor._shutdown_thread=True
executor=None

# All pending tasks are to be marked failed with the following
# BrokenProcessPool error
bpe=BrokenProcessPool("A process in the process pool was "
"terminated abruptly while the future was "
"running or pending.")
ifcauseisnotNone:
bpe.__cause__=_RemoteTraceback(
f"\n'''\n{''.join(cause)}'''")

# Mark pending tasks as failed.
forwork_id, work_iteminself.pending_work_items.items():
try:
work_item.future.set_exception(bpe)
except_base.InvalidStateError:
# set_exception() fails if the future is cancelled: ignore it.
# Trying to check if the future is cancelled before calling
# set_exception() would leave a race condition if the future is
# cancelled between the check and set_exception().
pass
# Delete references to object. See issue16284
delwork_item
self.pending_work_items.clear()

# Terminate remaining workers forcibly: the queues or their
# locks may be in a dirty state and block forever.
forpinself.processes.values():
p.terminate()

self.call_queue._terminate_broken()

# clean up resources
self._join_executor_internals(broken=True)

defterminate_broken(self, cause):
withself.shutdown_lock:
self._terminate_broken(cause)

defflag_executor_shutting_down(self):
# Flag the executor as shutting down and cancel remaining tasks if
# requested as early as possible if it is not gc-ed yet.
executor=self.executor_reference()
ifexecutorisnotNone:
executor._shutdown_thread=True
# Cancel pending work items if requested.
ifexecutor._cancel_pending_futures:
# Cancel all pending futures and update pending_work_items
# to only have futures that are currently running.
new_pending_work_items= {}
forwork_id, work_iteminself.pending_work_items.items():
ifnotwork_item.future.cancel():
new_pending_work_items[work_id] =work_item
self.pending_work_items=new_pending_work_items
# Drain work_ids_queue since we no longer need to
# add items to the call queue.
whileTrue:
try:
self.work_ids_queue.get_nowait()
exceptqueue.Empty:
break
# Make sure we do this only once to not waste time looping
# on running processes over and over.
executor._cancel_pending_futures=False

defshutdown_workers(self):
n_children_to_stop=self.get_n_children_alive()
n_sentinels_sent=0
# Send the right number of sentinels, to make sure all children are
# properly terminated.
while (n_sentinels_sent<n_children_to_stop
andself.get_n_children_alive() >0):
foriinrange(n_children_to_stop-n_sentinels_sent):
try:
self.call_queue.put_nowait(None)
n_sentinels_sent+=1
exceptqueue.Full:
break

defjoin_executor_internals(self):
withself.shutdown_lock:
self._join_executor_internals()

def_join_executor_internals(self, broken=False):
# If broken, call_queue was closed and so can no longer be used.
ifnotbroken:
self.shutdown_workers()

# Release the queue's resources as soon as possible.
self.call_queue.close()
self.call_queue.join_thread()
self.thread_wakeup.close()

# If .join() is not called on the created processes then
# some ctx.Queue methods may deadlock on Mac OS X.
forpinself.processes.values():
ifbroken:
p.terminate()
p.join()

defget_n_children_alive(self):
# This is an upper bound on the number of children alive.
returnsum(p.is_alive() forpinself.processes.values())


_system_limits_checked=False
_system_limited=None


def_check_system_limits():
global_system_limits_checked, _system_limited
if_system_limits_checked:
if_system_limited:
raiseNotImplementedError(_system_limited)
_system_limits_checked=True
try:
importmultiprocessing.synchronize
exceptImportError:
_system_limited= (
"This Python build lacks multiprocessing.synchronize, usually due "
"to named semaphores being unavailable on this platform."
 )
raiseNotImplementedError(_system_limited)
try:
nsems_max=os.sysconf("SC_SEM_NSEMS_MAX")
except (AttributeError, ValueError):
# sysconf not available or setting not available
return
ifnsems_max==-1:
# indetermined limit, assume that limit is determined
# by available memory only
return
ifnsems_max>=256:
# minimum number of semaphores available
# according to POSIX
return
_system_limited= ("system provides too few semaphores (%d"
" available, 256 necessary)"%nsems_max)
raiseNotImplementedError(_system_limited)


def_chain_from_iterable_of_lists(iterable):
"""
 Specialized implementation of itertools.chain.from_iterable.
 Each item in *iterable* should be a list. This function is
 careful not to keep references to yielded objects.
 """
forelementiniterable:
element.reverse()
whileelement:
yieldelement.pop()


classBrokenProcessPool(_base.BrokenExecutor):
"""
 Raised when a process in a ProcessPoolExecutor terminated abruptly
 while a future was in the running state.
 """


classProcessPoolExecutor(_base.Executor):
def__init__(self, max_workers=None, mp_context=None,
initializer=None, initargs=(), *, max_tasks_per_child=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.
 mp_context: A multiprocessing context to launch the workers created
 using the multiprocessing.get_context('start method') API. This
 object should provide SimpleQueue, Queue and Process.
 initializer: A callable used to initialize worker processes.
 initargs: A tuple of arguments to pass to the initializer.
 max_tasks_per_child: The maximum number of tasks a worker process
 can complete before it will exit and be replaced with a fresh
 worker process. The default of None means worker process will
 live as long as the executor. Requires a non-'fork' mp_context
 start method. When given, we default to using 'spawn' if no
 mp_context is supplied.
 """
_check_system_limits()

ifmax_workersisNone:
self._max_workers=os.process_cpu_count() or1
ifsys.platform=='win32':
self._max_workers=min(_MAX_WINDOWS_WORKERS,
self._max_workers)
else:
ifmax_workers<=0:
raiseValueError("max_workers must be greater than 0")
elif (sys.platform=='win32'and
max_workers>_MAX_WINDOWS_WORKERS):
raiseValueError(
f"max_workers must be <= {_MAX_WINDOWS_WORKERS}")

self._max_workers=max_workers

ifmp_contextisNone:
ifmax_tasks_per_childisnotNone:
mp_context=mp.get_context("spawn")
else:
mp_context=mp.get_context()
self._mp_context=mp_context

# https://github.com/python/cpython/issues/90622
self._safe_to_dynamically_spawn_children= (
self._mp_context.get_start_method(allow_none=False) !="fork")

ifinitializerisnotNoneandnotcallable(initializer):
raiseTypeError("initializer must be a callable")
self._initializer=initializer
self._initargs=initargs

ifmax_tasks_per_childisnotNone:
ifnotisinstance(max_tasks_per_child, int):
raiseTypeError("max_tasks_per_child must be an integer")
elifmax_tasks_per_child<=0:
raiseValueError("max_tasks_per_child must be >= 1")
ifself._mp_context.get_start_method(allow_none=False) =="fork":
# https://github.com/python/cpython/issues/90622
raiseValueError("max_tasks_per_child is incompatible with"
" the 'fork' multiprocessing start method;"
" supply a different mp_context.")
self._max_tasks_per_child=max_tasks_per_child

# Management thread
self._executor_manager_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._idle_worker_semaphore=threading.Semaphore(0)
self._broken=False
self._queue_count=0
self._pending_work_items= {}
self._cancel_pending_futures=False

# _ThreadWakeup is a communication channel used to interrupt the wait
# of the main loop of executor_manager_thread from another thread (e.g.
# when calling executor.submit or executor.shutdown). We do not use the
# _result_queue to send wakeup signals to the executor_manager_thread
# as it could result in a deadlock if a worker process dies with the
# _result_queue write lock still acquired.
#
# Care must be taken to only call clear and close from the
# executor_manager_thread, since _ThreadWakeup.clear() is not protected
# by a lock.
self._executor_manager_thread_wakeup=_ThreadWakeup()

# 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,
thread_wakeup=self._executor_manager_thread_wakeup)
# 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()

def_start_executor_manager_thread(self):
ifself._executor_manager_threadisNone:
# Start the processes so that their sentinels are known.
ifnotself._safe_to_dynamically_spawn_children: # ie, using fork.
self._launch_processes()
self._executor_manager_thread=_ExecutorManagerThread(self)
self._executor_manager_thread.start()
_threads_wakeups[self._executor_manager_thread] = \
self._executor_manager_thread_wakeup

def_adjust_process_count(self):
# if there's an idle process, we don't need to spawn a new one.
ifself._idle_worker_semaphore.acquire(blocking=False):
return

process_count=len(self._processes)
ifprocess_count<self._max_workers:
# Assertion disabled as this codepath is also used to replace a
# worker that unexpectedly dies, even when using the 'fork' start
# method. That means there is still a potential deadlock bug. If a
# 'fork' mp_context worker dies, we'll be forking a new one when
# we know a thread is running (self._executor_manager_thread).
#assert self._safe_to_dynamically_spawn_children or not self._executor_manager_thread, 'https://github.com/python/cpython/issues/90622'
self._spawn_process()

def_launch_processes(self):
# https://github.com/python/cpython/issues/90622
assertnotself._executor_manager_thread, (
'Processes cannot be fork()ed after the thread has started, '
'deadlock in the child processes could result.')
for_inrange(len(self._processes), self._max_workers):
self._spawn_process()

def_spawn_process(self):
p=self._mp_context.Process(
target=_process_worker,
args=(self._call_queue,
self._result_queue,
self._initializer,
self._initargs,
self._max_tasks_per_child))
p.start()
self._processes[p.pid] =p

defsubmit(self, fn, /, *args, **kwargs):
withself._shutdown_lock:
ifself._broken:
raiseBrokenProcessPool(self._broken)
ifself._shutdown_thread:
raiseRuntimeError('cannot schedule new futures after shutdown')
if_global_shutdown:
raiseRuntimeError('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._executor_manager_thread_wakeup.wakeup()

ifself._safe_to_dynamically_spawn_children:
self._adjust_process_count()
self._start_executor_manager_thread()
returnf
submit.__doc__=_base.Executor.submit.__doc__

defmap(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.
 """
ifchunksize<1:
raiseValueError("chunksize must be >= 1.")

results=super().map(partial(_process_chunk, fn),
itertools.batched(zip(*iterables), chunksize),
timeout=timeout)
return_chain_from_iterable_of_lists(results)

defshutdown(self, wait=True, *, cancel_futures=False):
withself._shutdown_lock:
self._cancel_pending_futures=cancel_futures
self._shutdown_thread=True
ifself._executor_manager_thread_wakeupisnotNone:
# Wake up queue management thread
self._executor_manager_thread_wakeup.wakeup()

ifself._executor_manager_threadisnotNoneandwait:
self._executor_manager_thread.join()
# To reduce the risk of opening too many files, remove references to
# objects that use file descriptors.
self._executor_manager_thread=None
self._call_queue=None
ifself._result_queueisnotNoneandwait:
self._result_queue.close()
self._result_queue=None
self._processes=None
self._executor_manager_thread_wakeup=None

shutdown.__doc__=_base.Executor.shutdown.__doc__