Initial Commit

lib/concurrent/futures/process.py

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+# 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"
+"""
+
+from __future__ import with_statement
+import atexit
+import multiprocessing
+import threading
+import weakref
+import sys
+
+from concurrent.futures import _base
+
+try:
+    import queue
+except ImportError:
+    import Queue as queue
+
+__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())
+    for t, q in items:
+        q.put(None)
+    for t, q in items:
+        t.join()
+
+# Controls how many more calls than processes will be queued in the call queue.
+# A smaller number will mean that processes spend more time idle waiting for
+# work while a larger number will make Future.cancel() succeed less frequently
+# (Futures in the call queue cannot be cancelled).
+EXTRA_QUEUED_CALLS = 1
+
+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 BaseException:
+            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)
+        # 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:
+            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()
+        # 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)