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Threading and multiprocessing Part 5: Multiprocessing
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 - processes are completely isolated
 - no locking :) (and no GIL!)
 - instead of locking: messaging

``multiprocessing`` provides an API very similar to ``threading``, so the transition is easy

use ``multiprocessing.Process`` instead of ``threading.Thread``

.. code-block:: python

    import multiprocessing
    import os
    import time

    def func():
        print "hello from process %s" % os.getpid()
        time.sleep(1)

    proc = multiprocessing.Process(target=func, args=())
    proc.start()
    proc = multiprocessing.Process(target=func, args=())
    proc.start()


Differences with Threading
--------------------------

Multiprocessing has its own ``multiprocessing.Queue`` which handles
interprocess communication.

Also has its own versions of ``Lock``, ``RLock``, ``Semaphore``

.. code-block:: python

    from multiprocessing import Queue, Lock

``multiprocessing.Pipe`` for 2-way process communication:

.. code-block:: python

    from multiprocessing import Pipe
    parent_conn, child_conn = Pipe()
    child_conn.send("foo")
    print parent_conn.recv()

Messaging
---------

Pipes (``multiprocessing.Pipe``)
................................

 - Returns a pair of connected objects.
 - Largely mimics Unix pipes, but higher level.
 - send pickled objects or buffers.


Queues (``multiprocessing.Queue``)
..................................

 - same interface as ``queue.Queue``
 - implemented on top of pipes.
 - means you can pretty easily port threaded programs using queues to multiprocessing.
   - queue is the only shared data.
   - data is all pickled and unpickled to pass between processes -- significant overhead.


Other features of the multiprocessing package
.............................................

 - Pools.
 - Shared objects and arrays.
 - Synchronization primitives.
 - Managed objects.
 - Connections.