Commit 4523968b authored by Jesse Noller's avatar Jesse Noller

Merge r67419 to py3k, mp doc fixes

parent 7ca7cb48
......@@ -24,6 +24,29 @@ Windows.
import it will result in an :exc:`ImportError`. See
:issue:`3770` for additional information.
.. note::
Functionality within this package requires that the ``__main__`` method be
importable by the children. This is covered in :ref:`multiprocessing-programming`
however it is worth pointing out here. This means that some examples, such
as the :class:`multiprocessing.Pool` examples will not work in the
interactive interpreter. For example::
>>> from multiprocessing import Pool
>>> p = Pool(5)
>>> def f(x):
... return x*x
...
>>> p.map(f, [1,2,3])
Process PoolWorker-1:
Process PoolWorker-2:
Traceback (most recent call last):
Traceback (most recent call last):
AttributeError: 'module' object has no attribute 'f'
AttributeError: 'module' object has no attribute 'f'
AttributeError: 'module' object has no attribute 'f'
The :class:`Process` class
~~~~~~~~~~~~~~~~~~~~~~~~~~
......@@ -32,17 +55,36 @@ object and then calling its :meth:`~Process.start` method. :class:`Process`
follows the API of :class:`threading.Thread`. A trivial example of a
multiprocess program is ::
from multiprocessing import Process
from multiprocessing import Process
def f(name):
print('hello', name)
if __name__ == '__main__':
p = Process(target=f, args=('bob',))
p.start()
p.join()
Here the function ``f`` is run in a child process.
if __name__ == '__main__':
p = Process(target=f, args=('bob',))
p.start()
p.join()
To show the individual process IDs involved, here is an expanded example::
from multiprocessing import Process
import os
def info(title):
print title
print 'module name:', __name__
print 'parent process:', os.getppid()
print 'process id:', os.getpid()
def f(name):
info('function f')
print 'hello', name
if __name__ == '__main__':
info('main line')
p = Process(target=f, args=('bob',))
p.start()
p.join()
For an explanation of why (on Windows) the ``if __name__ == '__main__'`` part is
necessary, see :ref:`multiprocessing-programming`.
......@@ -231,10 +273,10 @@ For example::
return x*x
if __name__ == '__main__':
pool = Pool(processes=4) # start 4 worker processes
result = pool.apply_async(f, [10]) # evaluate "f(10)" asynchronously
print(result.get(timeout=1)) # prints "100" unless your computer is *very* slow
print(pool.map(f, range(10))) # prints "[0, 1, 4,..., 81]"
pool = Pool(processes=4) # start 4 worker processes
result = pool.apply_async(f, [10]) # evaluate "f(10)" asynchronously
print result.get(timeout=1) # prints "100" unless your computer is *very* slow
print pool.map(f, range(10)) # prints "[0, 1, 4,..., 81]"
Reference
......@@ -305,7 +347,7 @@ The :mod:`multiprocessing` package mostly replicates the API of the
semantics. Multiple processes may be given the same name. The initial
name is set by the constructor.
.. method:: is_alive()
.. method:: is_alive
Return whether the process is alive.
......@@ -814,6 +856,9 @@ object -- see :ref:`multiprocessing-managers`.
acceptable. If *block* is ``True`` and *timeout* is not ``None`` then it
specifies a timeout in seconds. If *block* is ``False`` then *timeout* is
ignored.
Note that on OS/X ``sem_timedwait`` is unsupported, so timeout arguments
for these will be ignored.
.. note::
......@@ -1087,6 +1132,27 @@ their parent process exits. The manager classes are defined in the
A class method which creates a manager object referring to a pre-existing
server process which is using the given address and authentication key.
.. method:: get_server()
Returns a :class:`Server` object which represents the actual server under
the control of the Manager. The :class:`Server` object supports the
:meth:`serve_forever` method::
>>> from multiprocessing.managers import BaseManager
>>> m = BaseManager(address=('', 50000), authkey='abc'))
>>> server = m.get_server()
>>> s.serve_forever()
:class:`Server` additionally have an :attr:`address` attribute.
.. method:: connect()
Connect a local manager object to a remote manager process::
>>> from multiprocessing.managers import BaseManager
>>> m = BaseManager(address='127.0.0.1', authkey='abc))
>>> m.connect()
.. method:: shutdown()
Stop the process used by the manager. This is only available if
......@@ -1265,19 +1331,20 @@ remote clients can access::
>>> queue = queue.Queue()
>>> class QueueManager(BaseManager): pass
...
>>> QueueManager.register('getQueue', callable=lambda:queue)
>>> QueueManager.register('get_queue', callable=lambda:queue)
>>> m = QueueManager(address=('', 50000), authkey='abracadabra')
>>> m.serveForever()
>>> s = m.get_server()
>>> s.serveForever()
One client can access the server as follows::
>>> from multiprocessing.managers import BaseManager
>>> class QueueManager(BaseManager): pass
...
>>> QueueManager.register('getQueue')
>>> m = QueueManager.from_address(address=('foo.bar.org', 50000),
>>> authkey='abracadabra')
>>> queue = m.getQueue()
>>> QueueManager.register('get_queue')
>>> m = QueueManager(address=('foo.bar.org', 50000), authkey='abracadabra')
>>> m.connect()
>>> queue = m.get_queue()
>>> queue.put('hello')
Another client can also use it::
......@@ -1291,6 +1358,27 @@ Another client can also use it::
>>> queue.get()
'hello'
Local processes can also access that queue, using the code from above on the
client to access it remotely::
>>> from multiprocessing import Process, Queue
>>> from multiprocessing.managers import BaseManager
>>> class Worker(Process):
... def __init__(self, q):
... self.q = q
... super(Worker, self).__init__()
... def run(self):
... self.q.put('local hello')
...
>>> queue = Queue()
>>> w = Worker(queue)
>>> w.start()
>>> class QueueManager(BaseManager): pass
...
>>> QueueManager.register('get_queue', callable=lambda: queue)
>>> m = QueueManager(address=('', 50000), authkey='abracadabra')
>>> s = m.get_server()
>>> s.serve_forever()
Proxy Objects
~~~~~~~~~~~~~
......
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