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python Programming Glossary: sharedmemShare Large, Read-Only Numpy Array Between Multiprocessing Processes http://stackoverflow.com/questions/17785275/share-large-read-only-numpy-array-between-multiprocessing-processes between 5 multiprocessing Process objects. I've seen numpy sharedmem and read this discussion on the SciPy list. There seem to be.. on the SciPy list. There seem to be two approaches numpy sharedmem and using a multiprocessing.RawArray and mapping NumPy dtypes.. and mapping NumPy dtypes to ctypes. Now numpy sharedmem seems to be the way to go but I've yet to see a good reference..
How do I pass large numpy arrays between python subprocesses without saving to disk? http://stackoverflow.com/questions/5033799/how-do-i-pass-large-numpy-arrays-between-python-subprocesses-without-saving-to-d about the code Joe Kington posted I found the numpy sharedmem package. Judging from this numpy multiprocessing tutorial it.. maybe largely the same authors I'm not sure . Using the sharedmem module you can create a shared memory numpy array awesome and.. awesome and use it with multiprocessing like this import sharedmem as shm import numpy as np import multiprocessing as mp def worker..
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