SharedMemory
- SharedMemory(name=None, create=False, size=0, *, track=True)
Creates a new shared memory block or attaches to an existing shared memory block. Every shared memory block is assigned a unique name. This enables one process to create a shared memory block with a particular name so that 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.
© Python Software Foundation. PSF License Version 2 · Official docs ↗
Changed in 3.13
- 3.13: Added the track parameter.
Members of SharedMemory
b
- buf
- A memoryview of contents of the shared memory block.
c
- close
- Closes access to the shared memory from this instance but does not destroy the shared memory block.
n
- name
- Unique name that identifies the shared memory block.
s
- size
- Size in bytes.
u
- unlink
- Requests that the underlying shared memory block be destroyed.
1 Example
>>> from multiprocessing import shared_memory >>> shm_a = shared_memory.SharedMemory(create=True, size=10) >>> type(shm_a.buf) <class 'memoryview'> >>> buffer = shm_a.buf >>> len(buffer) 10 >>> buffer[:4] = bytearray([22, 33, 44, 55]) # Modify multiple at once >>> buffer[4] = 100 # Modify single byte at a time >>> # Attach to an existing shared memory block >>> shm_b = shared_memory.SharedMemory(shm_a.name) >>> import array >>> array.array('b', shm_b.buf[:5]) # Copy the data into a new array.array array('b', [22, 33, 44, 55, 100]) >>> shm_b.buf[:5] = b'howdy' # Modify via shm_b using bytes >>> bytes(shm_a.buf[:5]) # Access via shm_a b'howdy' >>> shm_b.close() # Close each SharedMemory instance >>> shm_a.close() >>> shm_a.unlink() # Call unlink only once to release the shared memory
from the Python docs