This issue tracker has been migrated to GitHub, and is currently read-only.
For more information, see the GitHub FAQs in the Python's Developer Guide.

Author Dariusz Trawinski
Recipients Dariusz Trawinski
Date 2020-02-26.23:46:31
SpamBayes Score -1.0
Marked as misclassified Yes
Message-id <1582760791.31.0.349985357098.issue39767@roundup.psfhosted.org>
In-reply-to
Content
Currently, in order to share numpy array between processes via multiprocessing.SharedMemory object, it is required to copy the memory content with:
input = np.ones((1,10,10,10))
shm = shared_memory.SharedMemory(create=True, size=input.nbytes)
write_array = np.ndarray(input.shape, dtype=input.dtype,buffer=shm.buf)
write_array1[:] = input[:]
In result the original numpy array is duplicated in RAM. It also adds extra cpu cycles to copy the content.

I would like to recommend adding an option to create shared memory object by pointing it to existing memoryview object, beside current method of using shared memory name. 
Is that doable?
History
Date User Action Args
2020-02-26 23:46:31Dariusz Trawinskisetrecipients: + Dariusz Trawinski
2020-02-26 23:46:31Dariusz Trawinskisetmessageid: <1582760791.31.0.349985357098.issue39767@roundup.psfhosted.org>
2020-02-26 23:46:31Dariusz Trawinskilinkissue39767 messages
2020-02-26 23:46:31Dariusz Trawinskicreate