Hi! First time poster to the list, long time happy user of NumPy (thank you, devs!!)
I created a bit of a wrapper for using `ndarray` with Py 3.8+ `multiprocessing.shared_memory`. I really like the ability to use `SharedMemory` with `ndarray` via the `buffer` arg. (as in https://docs.python.org/3/library/multiprocessing.shared_memory.html#multiprocessing.shared_memory.SharedMemory) However, it seemed a bit clunky to worry about passing the SharedMemory object or name, dtype, and shape to reconstruct the `ndarray` in other processes. I came up with this SharedNDArray class that encapsulates that information and provides an ephemeral `ndarray` interface: https://gitlab.com/osu-nrsg/shared-ndarray2. It's especially meant for use in a `SharedMemoryManager` context manager. I shared it on r/Python and someone suggested I share it here for your input (and maybe even integration into NumPy rather than the lone-wolf project it currently is). I'm happy to receive any suggestions/input/criticism. As an aside, I discovered that it's not at all trivial and, at the moment, not technically possible to define all the possible typing overloads of ndarray `__setitem__` and `__getitem__`. Stll, I enjoyed making use of np.typing.NDArray. Thanks for your consideration, Randy _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@python.org https://mail.python.org/mailman/listinfo/numpy-discussion
