You can since 3.8 :) https://docs.python.org/3/library/multiprocessing.shared_memory.html https://docs.python.org/3/library/multiprocessing.shared_mem... If y

You can since 3.8 :) https://docs.python.org/3/library/multiprocessing.shared_memory.html https://docs.python.org/3/library/multiprocessing.shared_mem... If you use a data structure that supports the buffer protocol (such as a numpy array), you won't even pay a serialization cost. Python has made a LOT of progress, concurrency wise. Between asyncio, process pools, threads releasing the GIL and shared memory, you can get much perfs with the stdlib alone. Then of course you have Dask if you need more later.