I am trying to use the new shared memory example in python 3.8 from this link https://docs.python.org/3/library/multiprocessing.shared_memory.html
# In the first Python interactive shell import numpy as np a = np.array([1, 1, 2, 3, 5, 8]) # Start with an existing NumPy array from multiprocessing import shared_memory shm = shared_memory.SharedMemory(create=True, size=a.nbytes) # Now create a NumPy array backed by shared memory b = np.ndarray(a.shape, dtype=a.dtype, buffer=shm.buf) b[:] = a[:] # Copy the original data into shared memory shname = shm.name # We did not specify a name so one was chosen for us print(shname) print(a) print(b) # In either the same shell or a new Python shell on the same machine import numpy as np from multiprocessing import shared_memory # Attach to the existing shared memory block existing_shm = shared_memory.SharedMemory(name=shname) # Note that a.shape is (6,) and a.dtype is np.int64 in this example c = np.ndarray((6,), dtype=np.int64, buffer=existing_shm.buf) print(c) c[-1] = 888 print(c) # Back in the first Python interactive shell, b reflects this change # Clean up from within the second Python shell del c # Unnecessary; merely emphasizing the array is no longer used existing_shm.close() # Clean up from within the first Python shell del b # Unnecessary; merely emphasizing the array is no longer used shm.close() shm.unlink() # Free and release the shared memory block at the very end In the example, the output of c should be array([1, 1, 2, 3, 5, 8]) however when I run this I get:
wnsm_26020d1b [1 1 2 3 5 8] [1 1 2 3 5 8] [ 4294967297 12884901890 34359738373 0 0 0] [ 4294967297 12884901890 34359738373 0 0 888] Did I totally miss something? Anyone else have this result?
