For us who didn't follow: "multiprocessing.shared_memory — Provides shared memory for direct access across processes" https://docs.python.org/3.9/library/mult

For us who didn't follow: "multiprocessing.shared_memory — Provides shared memory for direct access across processes" https://docs.python.org/3.9/library/multiprocessing.shared_memory.html https://docs.python.org/3.9/library/multiprocessing.shared_m... And it has the example which "demonstrates a practical use of the SharedMemory class with NumPy arrays, accessing the same numpy.ndarray from two distinct Python shells." Also, SharedMemory "Creates a new shared memory block or attaches to an existing shared memory block. Each shared memory block is assigned a unique name. In this way, one process can create a shared memory block with a particular name and a different process can attach to that same shared memory block using that same name. As a resource for sharing data across processes, shared memory blocks may outlive the original process that created them. When one process no longer needs access to a shared memory block that might still be needed by other processes, the close() method should be called. When a shared memory block is no longer needed by any process, the unlink() method should be called to ensure proper cleanup." Really nice.