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Note multiprocessing start method compatibility #529

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Note multiprocessing start method compatibility #529

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Note multiprocessing start method compatibility
Mark2000 Apr 4, 2023
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Update docs/source/limitations.rst
Mark2000 Apr 5, 2023
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17 changes: 17 additions & 0 deletions docs/source/limitations.rst
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Expand Up @@ -67,6 +67,23 @@ run:
...: a
Out[3]: array([1., 1., 1., 2., 2., 2., 3., 3., 4., 4.])

Multiprocessing
~~~~~~~~~~~~~~~

While not supported or guaranteed to be stable, PyJulia tends to work
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with the multiprocessing library if the correct `start method
<https://docs.python.org/3/library/multiprocessing.html#contexts-and-start-methods>`_
is selected: *fork* (default on Unix) segfaults with with `unknown
function` errors, while *spawn* (default on Windows and MacOS) generally,
but not always, runs without memory allocation issues. To select *spawn*,
include the line
Comment on lines +76 to +79
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is selected: *fork* (default on Unix) segfaults with with `unknown
function` errors, while *spawn* (default on Windows and MacOS) generally,
but not always, runs without memory allocation issues. To select *spawn*,
include the line
is selected. *fork* (default on Unix) segfaults with with `unknown
function` errors. *spawn* (default on Windows and MacOS) generally,
but not always, runs without memory allocation issues. To select *spawn*,
include the line

Just using . here simplifies sentence structure. When does using spawn run with memory allocation issues? Could you elaborate on that point?

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@Mark2000 Mark2000 Apr 5, 2023 •
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I wish I could, but I haven't done extensive enough testing to say why it happens. I've just noted that it does occasionally happen in my use case. @davidavdav is this something you've also experienced?


.. code:: python

multiprocessing.set_start_method('spawn')

once in your code prior to using the multiprocessing library.
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once in your code prior to using the multiprocessing library.
once in your code prior to using the multiprocessing library.
Also, consider using the *spawn* or *forkserver* methods with ``multiprocessing.get_context``:
.. code:: python
context = multiprocessing.get_context('fork_server')
queue = context.Queue()
process = context.Process(target=foo, args=(queue,))

@davidavdav does that sound right?


PyJulia does not release GIL
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

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