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Differential D3261

thirdparty: vendor futures 3.2.0
ClosedPublic

Authored by indygreg on Apr 11 2018, 7:42 PM.

Details

Reviewers
durin42
Group Reviewers
hg-reviewers
Commits
rHGeb687c28a915: thirdparty: vendor futures 3.2.0
Summary

Python 3 has a concurrent.futures package in the standard library
for representing futures. The "futures" package on PyPI is a backport
of this package to work with Python 2.

The wire protocol code today has its own future concept for handling
of "batch" requests. The frame-based protocol will also want to
use futures.

I've heavily used the "futures" package on Python 2 in other projects
and it is pretty nice. It even has a built-in thread and process pool
for running functions in parallel. I've used this heavily for concurrent
I/O and other GIL-less activities.

The existing futures API in the wire protocol code is not as nice as
concurrent.futures. Since concurrent.futures is in the Python standard
library and will presumably be the long-term future for futures in our
code base, let's vendor the backport so we can use proper futures today.

  1. no-check-commit because of style violations

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rHG Mercurial
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Automatic diff as part of commit; lint not applicable.
Unit
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Event Timeline

indygreg created this revision.Apr 11 2018, 7:42 PM
durin42 accepted this revision.Apr 13 2018, 5:34 PM
This revision is now accepted and ready to land.Apr 13 2018, 5:34 PM
Closed by commit rHGeb687c28a915: thirdparty: vendor futures 3.2.0 (authored by indygreg). · Explain WhyApr 13 2018, 5:45 PM
This revision was automatically updated to reflect the committed changes.

Revision Contents
Changeset List

Diff 8159

mercurial/thirdparty/concurrent/LICENSE

  • This file was added.
PYTHON SOFTWARE FOUNDATION LICENSE VERSION 2
--------------------------------------------
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("PSF"), and the Individual or Organization ("Licensee") accessing and
otherwise using this software ("Python") in source or binary form and
its associated documentation.
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hereby grants Licensee a nonexclusive, royalty-free, world-wide
license to reproduce, analyze, test, perform and/or display publicly,
prepare derivative works, distribute, and otherwise use Python
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2001, 2002, 2003, 2004, 2005, 2006 Python Software Foundation; All Rights
Reserved" are retained in Python alone or in any derivative version
prepared by Licensee.
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or incorporates Python or any part thereof, and wants to make
the derivative work available to others as provided herein, then
Licensee hereby agrees to include in any such work a brief summary of
the changes made to Python.
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basis. PSF MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR
IMPLIED. BY WAY OF EXAMPLE, BUT NOT LIMITATION, PSF MAKES NO AND
DISCLAIMS ANY REPRESENTATION OR WARRANTY OF MERCHANTABILITY OR FITNESS
FOR ANY PARTICULAR PURPOSE OR THAT THE USE OF PYTHON WILL NOT
INFRINGE ANY THIRD PARTY RIGHTS.
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FOR ANY INCIDENTAL, SPECIAL, OR CONSEQUENTIAL DAMAGES OR LOSS AS
A RESULT OF MODIFYING, DISTRIBUTING, OR OTHERWISE USING PYTHON,
OR ANY DERIVATIVE THEREOF, EVEN IF ADVISED OF THE POSSIBILITY THEREOF.
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Agreement.

mercurial/thirdparty/concurrent/__init__.py

  • This file was added.
from pkgutil import extend_path
__path__ = extend_path(__path__, __name__)

mercurial/thirdparty/concurrent/futures/__init__.py

  • This file was added.
# Copyright 2009 Brian Quinlan. All Rights Reserved.
# Licensed to PSF under a Contributor Agreement.
"""Execute computations asynchronously using threads or processes."""
__author__ = 'Brian Quinlan (brian@sweetapp.com)'
from concurrent.futures._base import (FIRST_COMPLETED,
FIRST_EXCEPTION,
ALL_COMPLETED,
CancelledError,
TimeoutError,
Future,
Executor,
wait,
as_completed)
from concurrent.futures.thread import ThreadPoolExecutor
try:
from concurrent.futures.process import ProcessPoolExecutor
except ImportError:
# some platforms don't have multiprocessing
pass

mercurial/thirdparty/concurrent/futures/_base.py

  • This file was added.
# Copyright 2009 Brian Quinlan. All Rights Reserved.
# Licensed to PSF under a Contributor Agreement.
import collections
import logging
import threading
import itertools
import time
import types
__author__ = 'Brian Quinlan (brian@sweetapp.com)'
FIRST_COMPLETED = 'FIRST_COMPLETED'
FIRST_EXCEPTION = 'FIRST_EXCEPTION'
ALL_COMPLETED = 'ALL_COMPLETED'
_AS_COMPLETED = '_AS_COMPLETED'
# Possible future states (for internal use by the futures package).
PENDING = 'PENDING'
RUNNING = 'RUNNING'
# The future was cancelled by the user...
CANCELLED = 'CANCELLED'
# ...and _Waiter.add_cancelled() was called by a worker.
CANCELLED_AND_NOTIFIED = 'CANCELLED_AND_NOTIFIED'
FINISHED = 'FINISHED'
_FUTURE_STATES = [
PENDING,
RUNNING,
CANCELLED,
CANCELLED_AND_NOTIFIED,
FINISHED
]
_STATE_TO_DESCRIPTION_MAP = {
PENDING: "pending",
RUNNING: "running",
CANCELLED: "cancelled",
CANCELLED_AND_NOTIFIED: "cancelled",
FINISHED: "finished"
}
# Logger for internal use by the futures package.
LOGGER = logging.getLogger("concurrent.futures")
class Error(Exception):
"""Base class for all future-related exceptions."""
pass
class CancelledError(Error):
"""The Future was cancelled."""
pass
class TimeoutError(Error):
"""The operation exceeded the given deadline."""
pass
class _Waiter(object):
"""Provides the event that wait() and as_completed() block on."""
def __init__(self):
self.event = threading.Event()
self.finished_futures = []
def add_result(self, future):
self.finished_futures.append(future)
def add_exception(self, future):
self.finished_futures.append(future)
def add_cancelled(self, future):
self.finished_futures.append(future)
class _AsCompletedWaiter(_Waiter):
"""Used by as_completed()."""
def __init__(self):
super(_AsCompletedWaiter, self).__init__()
self.lock = threading.Lock()
def add_result(self, future):
with self.lock:
super(_AsCompletedWaiter, self).add_result(future)
self.event.set()
def add_exception(self, future):
with self.lock:
super(_AsCompletedWaiter, self).add_exception(future)
self.event.set()
def add_cancelled(self, future):
with self.lock:
super(_AsCompletedWaiter, self).add_cancelled(future)
self.event.set()
class _FirstCompletedWaiter(_Waiter):
"""Used by wait(return_when=FIRST_COMPLETED)."""
def add_result(self, future):
super(_FirstCompletedWaiter, self).add_result(future)
self.event.set()
def add_exception(self, future):
super(_FirstCompletedWaiter, self).add_exception(future)
self.event.set()
def add_cancelled(self, future):
super(_FirstCompletedWaiter, self).add_cancelled(future)
self.event.set()
class _AllCompletedWaiter(_Waiter):
"""Used by wait(return_when=FIRST_EXCEPTION and ALL_COMPLETED)."""
def __init__(self, num_pending_calls, stop_on_exception):
self.num_pending_calls = num_pending_calls
self.stop_on_exception = stop_on_exception
self.lock = threading.Lock()
super(_AllCompletedWaiter, self).__init__()
def _decrement_pending_calls(self):
with self.lock:
self.num_pending_calls -= 1
if not self.num_pending_calls:
self.event.set()
def add_result(self, future):
super(_AllCompletedWaiter, self).add_result(future)
self._decrement_pending_calls()
def add_exception(self, future):
super(_AllCompletedWaiter, self).add_exception(future)
if self.stop_on_exception:
self.event.set()
else:
self._decrement_pending_calls()
def add_cancelled(self, future):
super(_AllCompletedWaiter, self).add_cancelled(future)
self._decrement_pending_calls()
class _AcquireFutures(object):
"""A context manager that does an ordered acquire of Future conditions."""
def __init__(self, futures):
self.futures = sorted(futures, key=id)
def __enter__(self):
for future in self.futures:
future._condition.acquire()
def __exit__(self, *args):
for future in self.futures:
future._condition.release()
def _create_and_install_waiters(fs, return_when):
if return_when == _AS_COMPLETED:
waiter = _AsCompletedWaiter()
elif return_when == FIRST_COMPLETED:
waiter = _FirstCompletedWaiter()
else:
pending_count = sum(
f._state not in [CANCELLED_AND_NOTIFIED, FINISHED] for f in fs)
if return_when == FIRST_EXCEPTION:
waiter = _AllCompletedWaiter(pending_count, stop_on_exception=True)
elif return_when == ALL_COMPLETED:
waiter = _AllCompletedWaiter(pending_count, stop_on_exception=False)
else:
raise ValueError("Invalid return condition: %r" % return_when)
for f in fs:
f._waiters.append(waiter)
return waiter
def _yield_finished_futures(fs, waiter, ref_collect):
"""
Iterate on the list *fs*, yielding finished futures one by one in
reverse order.
Before yielding a future, *waiter* is removed from its waiters
and the future is removed from each set in the collection of sets
*ref_collect*.
The aim of this function is to avoid keeping stale references after
the future is yielded and before the iterator resumes.
"""
while fs:
f = fs[-1]
for futures_set in ref_collect:
futures_set.remove(f)
with f._condition:
f._waiters.remove(waiter)
del f
# Careful not to keep a reference to the popped value
yield fs.pop()
def as_completed(fs, timeout=None):
"""An iterator over the given futures that yields each as it completes.
Args:
fs: The sequence of Futures (possibly created by different Executors) to
iterate over.
timeout: The maximum number of seconds to wait. If None, then there
is no limit on the wait time.
Returns:
An iterator that yields the given Futures as they complete (finished or
cancelled). If any given Futures are duplicated, they will be returned
once.
Raises:
TimeoutError: If the entire result iterator could not be generated
before the given timeout.
"""
if timeout is not None:
end_time = timeout + time.time()
fs = set(fs)
total_futures = len(fs)
with _AcquireFutures(fs):
finished = set(
f for f in fs
if f._state in [CANCELLED_AND_NOTIFIED, FINISHED])
pending = fs - finished
waiter = _create_and_install_waiters(fs, _AS_COMPLETED)
finished = list(finished)
try:
for f in _yield_finished_futures(finished, waiter,
ref_collect=(fs,)):
f = [f]
yield f.pop()
while pending:
if timeout is None:
wait_timeout = None
else:
wait_timeout = end_time - time.time()
if wait_timeout < 0:
raise TimeoutError(
'%d (of %d) futures unfinished' % (
len(pending), total_futures))
waiter.event.wait(wait_timeout)
with waiter.lock:
finished = waiter.finished_futures
waiter.finished_futures = []
waiter.event.clear()
# reverse to keep finishing order
finished.reverse()
for f in _yield_finished_futures(finished, waiter,
ref_collect=(fs, pending)):
f = [f]
yield f.pop()
finally:
# Remove waiter from unfinished futures
for f in fs:
with f._condition:
f._waiters.remove(waiter)
DoneAndNotDoneFutures = collections.namedtuple(
'DoneAndNotDoneFutures', 'done not_done')
def wait(fs, timeout=None, return_when=ALL_COMPLETED):
"""Wait for the futures in the given sequence to complete.
Args:
fs: The sequence of Futures (possibly created by different Executors) to
wait upon.
timeout: The maximum number of seconds to wait. If None, then there
is no limit on the wait time.
return_when: Indicates when this function should return. The options
are:
FIRST_COMPLETED - Return when any future finishes or is
cancelled.
FIRST_EXCEPTION - Return when any future finishes by raising an
exception. If no future raises an exception
then it is equivalent to ALL_COMPLETED.
ALL_COMPLETED - Return when all futures finish or are cancelled.
Returns:
A named 2-tuple of sets. The first set, named 'done', contains the
futures that completed (is finished or cancelled) before the wait
completed. The second set, named 'not_done', contains uncompleted
futures.
"""
with _AcquireFutures(fs):
done = set(f for f in fs
if f._state in [CANCELLED_AND_NOTIFIED, FINISHED])
not_done = set(fs) - done
if (return_when == FIRST_COMPLETED) and done:
return DoneAndNotDoneFutures(done, not_done)
elif (return_when == FIRST_EXCEPTION) and done:
if any(f for f in done
if not f.cancelled() and f.exception() is not None):
return DoneAndNotDoneFutures(done, not_done)
if len(done) == len(fs):
return DoneAndNotDoneFutures(done, not_done)
waiter = _create_and_install_waiters(fs, return_when)
waiter.event.wait(timeout)
for f in fs:
with f._condition:
f._waiters.remove(waiter)
done.update(waiter.finished_futures)
return DoneAndNotDoneFutures(done, set(fs) - done)
class Future(object):
"""Represents the result of an asynchronous computation."""
def __init__(self):
"""Initializes the future. Should not be called by clients."""
self._condition = threading.Condition()
self._state = PENDING
self._result = None
self._exception = None
self._traceback = None
self._waiters = []
self._done_callbacks = []
def _invoke_callbacks(self):
for callback in self._done_callbacks:
try:
callback(self)
except Exception:
LOGGER.exception('exception calling callback for %r', self)
except BaseException:
# Explicitly let all other new-style exceptions through so
# that we can catch all old-style exceptions with a simple
# "except:" clause below.
#
# All old-style exception objects are instances of
# types.InstanceType, but "except types.InstanceType:" does
# not catch old-style exceptions for some reason. Thus, the
# only way to catch all old-style exceptions without catching
# any new-style exceptions is to filter out the new-style
# exceptions, which all derive from BaseException.
raise
except:
# Because of the BaseException clause above, this handler only
# executes for old-style exception objects.
LOGGER.exception('exception calling callback for %r', self)
def __repr__(self):
with self._condition:
if self._state == FINISHED:
if self._exception:
return '<%s at %#x state=%s raised %s>' % (
self.__class__.__name__,
id(self),
_STATE_TO_DESCRIPTION_MAP[self._state],
self._exception.__class__.__name__)
else:
return '<%s at %#x state=%s returned %s>' % (
self.__class__.__name__,
id(self),
_STATE_TO_DESCRIPTION_MAP[self._state],
self._result.__class__.__name__)
return '<%s at %#x state=%s>' % (
self.__class__.__name__,
id(self),
_STATE_TO_DESCRIPTION_MAP[self._state])
def cancel(self):
"""Cancel the future if possible.
Returns True if the future was cancelled, False otherwise. A future
cannot be cancelled if it is running or has already completed.
"""
with self._condition:
if self._state in [RUNNING, FINISHED]:
return False
if self._state in [CANCELLED, CANCELLED_AND_NOTIFIED]:
return True
self._state = CANCELLED
self._condition.notify_all()
self._invoke_callbacks()
return True
def cancelled(self):
"""Return True if the future was cancelled."""
with self._condition:
return self._state in [CANCELLED, CANCELLED_AND_NOTIFIED]
def running(self):
"""Return True if the future is currently executing."""
with self._condition:
return self._state == RUNNING
def done(self):
"""Return True of the future was cancelled or finished executing."""
with self._condition:
return self._state in [CANCELLED, CANCELLED_AND_NOTIFIED, FINISHED]
def __get_result(self):
if self._exception:
if isinstance(self._exception, types.InstanceType):
# The exception is an instance of an old-style class, which
# means type(self._exception) returns types.ClassType instead
# of the exception's actual class type.
exception_type = self._exception.__class__
else:
exception_type = type(self._exception)
raise exception_type, self._exception, self._traceback
else:
return self._result
def add_done_callback(self, fn):
"""Attaches a callable that will be called when the future finishes.
Args:
fn: A callable that will be called with this future as its only
argument when the future completes or is cancelled. The callable
will always be called by a thread in the same process in which
it was added. If the future has already completed or been
cancelled then the callable will be called immediately. These
callables are called in the order that they were added.
"""
with self._condition:
if self._state not in [CANCELLED, CANCELLED_AND_NOTIFIED, FINISHED]:
self._done_callbacks.append(fn)
return
fn(self)
def result(self, timeout=None):
"""Return the result of the call that the future represents.
Args:
timeout: The number of seconds to wait for the result if the future
isn't done. If None, then there is no limit on the wait time.
Returns:
The result of the call that the future represents.
Raises:
CancelledError: If the future was cancelled.
TimeoutError: If the future didn't finish executing before the given
timeout.
Exception: If the call raised then that exception will be raised.
"""
with self._condition:
if self._state in [CANCELLED, CANCELLED_AND_NOTIFIED]:
raise CancelledError()
elif self._state == FINISHED:
return self.__get_result()
self._condition.wait(timeout)
if self._state in [CANCELLED, CANCELLED_AND_NOTIFIED]:
raise CancelledError()
elif self._state == FINISHED:
return self.__get_result()
else:
raise TimeoutError()
def exception_info(self, timeout=None):
"""Return a tuple of (exception, traceback) raised by the call that the
future represents.
Args:
timeout: The number of seconds to wait for the exception if the
future isn't done. If None, then there is no limit on the wait
time.
Returns:
The exception raised by the call that the future represents or None
if the call completed without raising.
Raises:
CancelledError: If the future was cancelled.
TimeoutError: If the future didn't finish executing before the given
timeout.
"""
with self._condition:
if self._state in [CANCELLED, CANCELLED_AND_NOTIFIED]:
raise CancelledError()
elif self._state == FINISHED:
return self._exception, self._traceback
self._condition.wait(timeout)
if self._state in [CANCELLED, CANCELLED_AND_NOTIFIED]:
raise CancelledError()
elif self._state == FINISHED:
return self._exception, self._traceback
else:
raise TimeoutError()
def exception(self, timeout=None):
"""Return the exception raised by the call that the future represents.
Args:
timeout: The number of seconds to wait for the exception if the
future isn't done. If None, then there is no limit on the wait
time.
Returns:
The exception raised by the call that the future represents or None
if the call completed without raising.
Raises:
CancelledError: If the future was cancelled.
TimeoutError: If the future didn't finish executing before the given
timeout.
"""
return self.exception_info(timeout)[0]
# The following methods should only be used by Executors and in tests.
def set_running_or_notify_cancel(self):
"""Mark the future as running or process any cancel notifications.
Should only be used by Executor implementations and unit tests.
If the future has been cancelled (cancel() was called and returned
True) then any threads waiting on the future completing (though calls
to as_completed() or wait()) are notified and False is returned.
If the future was not cancelled then it is put in the running state
(future calls to running() will return True) and True is returned.
This method should be called by Executor implementations before
executing the work associated with this future. If this method returns
False then the work should not be executed.
Returns:
False if the Future was cancelled, True otherwise.
Raises:
RuntimeError: if this method was already called or if set_result()
or set_exception() was called.
"""
with self._condition:
if self._state == CANCELLED:
self._state = CANCELLED_AND_NOTIFIED
for waiter in self._waiters:
waiter.add_cancelled(self)
# self._condition.notify_all() is not necessary because
# self.cancel() triggers a notification.
return False
elif self._state == PENDING:
self._state = RUNNING
return True
else:
LOGGER.critical('Future %s in unexpected state: %s',
id(self),
self._state)
raise RuntimeError('Future in unexpected state')
def set_result(self, result):
"""Sets the return value of work associated with the future.
Should only be used by Executor implementations and unit tests.
"""
with self._condition:
self._result = result
self._state = FINISHED
for waiter in self._waiters:
waiter.add_result(self)
self._condition.notify_all()
self._invoke_callbacks()
def set_exception_info(self, exception, traceback):
"""Sets the result of the future as being the given exception
and traceback.
Should only be used by Executor implementations and unit tests.
"""
with self._condition:
self._exception = exception
self._traceback = traceback
self._state = FINISHED
for waiter in self._waiters:
waiter.add_exception(self)
self._condition.notify_all()
self._invoke_callbacks()
def set_exception(self, exception):
"""Sets the result of the future as being the given exception.
Should only be used by Executor implementations and unit tests.
"""
self.set_exception_info(exception, None)
class Executor(object):
"""This is an abstract base class for concrete asynchronous executors."""
def submit(self, fn, *args, **kwargs):
"""Submits a callable to be executed with the given arguments.
Schedules the callable to be executed as fn(*args, **kwargs) and returns
a Future instance representing the execution of the callable.
Returns:
A Future representing the given call.
"""
raise NotImplementedError()
def map(self, fn, *iterables, **kwargs):
"""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.
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.
"""
timeout = kwargs.get('timeout')
if timeout is not None:
end_time = timeout + time.time()
fs = [self.submit(fn, *args) for args in itertools.izip(*iterables)]
# Yield must be hidden in closure so that the futures are submitted
# before the first iterator value is required.
def result_iterator():
try:
# reverse to keep finishing order
fs.reverse()
while fs:
# Careful not to keep a reference to the popped future
if timeout is None:
yield fs.pop().result()
else:
yield fs.pop().result(end_time - time.time())
finally:
for future in fs:
future.cancel()
return result_iterator()
def shutdown(self, wait=True):
"""Clean-up the resources associated with the Executor.
It is safe to call this method several times. Otherwise, no other
methods can be called after this one.
Args:
wait: If True then shutdown will not return until all running
futures have finished executing and the resources used by the
executor have been reclaimed.
"""
pass
def __enter__(self):
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.shutdown(wait=True)
return False

mercurial/thirdparty/concurrent/futures/process.py

  • This file was added.
# 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 "Request Q"
"""
import atexit
from concurrent.futures import _base
import Queue as queue
import multiprocessing
import threading
import weakref
import sys
__author__ = 'Brian Quinlan (brian@sweetapp.com)'
# 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()) if _threads_queues else ()
for t, q in items:
q.put(None)
for t, q in items:
t.join(sys.maxint)
# 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
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 _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(None)
return
try:
r = call_item.fn(*call_item.args, **call_item.kwargs)
except:
e = sys.exc_info()[1]
result_queue.put(_ResultItem(call_item.work_id,
exception=e))
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.
"""
nb_shutdown_processes = [0]
def shutdown_one_process():
"""Tell a worker to terminate, which will in turn wake us again"""
call_queue.put(None)
nb_shutdown_processes[0] += 1
while True:
_add_call_item_to_queue(pending_work_items,
work_ids_queue,
call_queue)
result_item = result_queue.get(block=True)
if result_item is not None:
work_item = pending_work_items[result_item.work_id]
del pending_work_items[result_item.work_id]
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 _shutdown or executor is None or executor._shutdown_thread:
# 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:
while nb_shutdown_processes[0] < len(processes):
shutdown_one_process()
# If .join() is not called on the created processes then
# some multiprocessing.Queue methods may deadlock on Mac OS
# X.
for p in processes:
p.join()
call_queue.close()
return
del executor
_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:
import os
nsems_max = os.sysconf("SC_SEM_NSEMS_MAX")
except (AttributeError, ValueError):
# sysconf not available or setting not available
return
if nsems_max == -1:
# indetermine 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 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 = multiprocessing.cpu_count()
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)
self._result_queue = multiprocessing.Queue()
self._work_ids = queue.Queue()
self._queue_management_thread = None
self._processes = set()
# Shutdown is a two-step process.
self._shutdown_thread = False
self._shutdown_lock = threading.Lock()
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:
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.add(p)
def submit(self, fn, *args, **kwargs):
with self._shutdown_lock:
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()
self._adjust_process_count()
return f
submit.__doc__ = _base.Executor.submit.__doc__
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(sys.maxint)
# To reduce the risk of openning 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)

mercurial/thirdparty/concurrent/futures/thread.py

  • This file was added.
# Copyright 2009 Brian Quinlan. All Rights Reserved.
# Licensed to PSF under a Contributor Agreement.
"""Implements ThreadPoolExecutor."""
import atexit
from concurrent.futures import _base
import itertools
import Queue as queue
import threading
import weakref
import sys
try:
from multiprocessing import cpu_count
except ImportError:
# some platforms don't have multiprocessing
def cpu_count():
return None
__author__ = 'Brian Quinlan (brian@sweetapp.com)'
# Workers are created as daemon threads. This is done to allow the interpreter
# to exit when there are still idle threads in a ThreadPoolExecutor's thread
# 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 finish.
_threads_queues = weakref.WeakKeyDictionary()
_shutdown = False
def _python_exit():
global _shutdown
_shutdown = True
items = list(_threads_queues.items()) if _threads_queues else ()
for t, q in items:
q.put(None)
for t, q in items:
t.join(sys.maxint)
atexit.register(_python_exit)
class _WorkItem(object):
def __init__(self, future, fn, args, kwargs):
self.future = future
self.fn = fn
self.args = args
self.kwargs = kwargs
def run(self):
if not self.future.set_running_or_notify_cancel():
return
try:
result = self.fn(*self.args, **self.kwargs)
except:
e, tb = sys.exc_info()[1:]
self.future.set_exception_info(e, tb)
else:
self.future.set_result(result)
def _worker(executor_reference, work_queue):
try:
while True:
work_item = work_queue.get(block=True)
if work_item is not None:
work_item.run()
# Delete references to object. See issue16284
del work_item
continue
executor = executor_reference()
# Exit if:
# - The interpreter is shutting down OR
# - The executor that owns the worker has been collected OR
# - The executor that owns the worker has been shutdown.
if _shutdown or executor is None or executor._shutdown:
# Notice other workers
work_queue.put(None)
return
del executor
except:
_base.LOGGER.critical('Exception in worker', exc_info=True)
class ThreadPoolExecutor(_base.Executor):
# Used to assign unique thread names when thread_name_prefix is not supplied.
_counter = itertools.count().next
def __init__(self, max_workers=None, thread_name_prefix=''):
"""Initializes a new ThreadPoolExecutor instance.
Args:
max_workers: The maximum number of threads that can be used to
execute the given calls.
thread_name_prefix: An optional name prefix to give our threads.
"""
if max_workers is None:
# Use this number because ThreadPoolExecutor is often
# used to overlap I/O instead of CPU work.
max_workers = (cpu_count() or 1) * 5
if max_workers <= 0:
raise ValueError("max_workers must be greater than 0")
self._max_workers = max_workers
self._work_queue = queue.Queue()
self._threads = set()
self._shutdown = False
self._shutdown_lock = threading.Lock()
self._thread_name_prefix = (thread_name_prefix or
("ThreadPoolExecutor-%d" % self._counter()))
def submit(self, fn, *args, **kwargs):
with self._shutdown_lock:
if self._shutdown:
raise RuntimeError('cannot schedule new futures after shutdown')
f = _base.Future()
w = _WorkItem(f, fn, args, kwargs)
self._work_queue.put(w)
self._adjust_thread_count()
return f
submit.__doc__ = _base.Executor.submit.__doc__
def _adjust_thread_count(self):
# When the executor gets lost, the weakref callback will wake up
# the worker threads.
def weakref_cb(_, q=self._work_queue):
q.put(None)
# TODO(bquinlan): Should avoid creating new threads if there are more
# idle threads than items in the work queue.
num_threads = len(self._threads)
if num_threads < self._max_workers:
thread_name = '%s_%d' % (self._thread_name_prefix or self,
num_threads)
t = threading.Thread(name=thread_name, target=_worker,
args=(weakref.ref(self, weakref_cb),
self._work_queue))
t.daemon = True
t.start()
self._threads.add(t)
_threads_queues[t] = self._work_queue
def shutdown(self, wait=True):
with self._shutdown_lock:
self._shutdown = True
self._work_queue.put(None)
if wait:
for t in self._threads:
t.join(sys.maxint)
shutdown.__doc__ = _base.Executor.shutdown.__doc__