Python's standard multiprocessing.Queue relies on _winapi.CreateFile for inter-process communication (IPC), introducing significant I/O overhead. This can become a performance bottleneck in demanding ...

This project uses the multiprocessing.shared_memory.SharedMemory class, which allows a block of memory to be used by multiple Python processes. Since Python 2.6, multiprocessing is a built-in module.

Python lets you parallelize workloads using threads, subprocesses, or both. ... look into using multiprocessing with shared memory or a server process. ...

Python's "multiprocessing" module feels like threads, but actually launches processes. Many people, when they start to work with Python, are excited to hear that the language supports threading. And, ...

To overcome this limitation, we recommend leveraging Python’s multiprocessing module. Unlike threads, which share the same memory space and are subject to the GIL, multiprocessing creates separate ...