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gh-73159 Added clarifications in multiprocessing docs on that objects are pickled. #121686

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gpshead merged 3 commits into from
Jul 13, 2024
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gh-73159 Added clarifications in multiprocessing docs on that objects are pickled. #121686

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Update multiprocessing.rst
digitalfotografen Jul 13, 2024
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Update multiprocessing.rst
digitalfotografen Jul 13, 2024
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Merge branch 'main' into multiprocessing_doc
digitalfotografen Jul 13, 2024
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10 changes: 10 additions & 0 deletions Doc/library/multiprocessing.rst
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Expand Up @@ -254,6 +254,7 @@ processes:
p.join()

Queues are thread and process safe.
Any object put into a :mod:`~multiprocessing` queue will be serialized.

**Pipes**

Expand Down Expand Up @@ -281,6 +282,8 @@ processes:
of corruption from processes using different ends of the pipe at the same
time.

The :meth:`~Connection.send` method serializes the the object and
:meth:`~Connection.recv` re-creates the object.

Synchronization between processes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
Expand Down Expand Up @@ -745,6 +748,11 @@ If you use :class:`JoinableQueue` then you **must** call
semaphore used to count the number of unfinished tasks may eventually overflow,
raising an exception.

One difference from other Python queue implementations, is that :mod:`multiprocessing`
queues serializes all objects that are put into them using :mod:`pickle`.
The object return by the get method is a re-created object that does not share memory
with the original object.

Note that one can also create a shared queue by using a manager object -- see
:ref:`multiprocessing-managers`.

Expand Down Expand Up @@ -811,6 +819,8 @@ For an example of the usage of queues for interprocess communication see
used for receiving messages and ``conn2`` can only be used for sending
messages.

The :meth:`~multiprocessing.Connection.send` method serializes the the object using
:mod:`pickle` and the :meth:`~multiprocessing.Connection.recv` re-creates the object.

.. class:: Queue([maxsize])

Expand Down