There's also the possibility to use shared ctypes: https://docs.python.org/3/library/multiprocessing.html#shared-ctypes-objects Operations like += which involve a read and write are not atomic. So if,
for instance, you want to atomically increment a shared value it is insufficient to just do
counter.value += 1
Assuming the associated lock is recursive (which it is by default) you can instead do with counter.get_lock(): counter.value += 1
Notice that they use a lock anyway. Maybe the solution of Wes Turner is better. See also RLock: https://docs.python.org/3/library/multiprocessing.html#multiprocessing.RLock
On Sat, 1 Aug 2020 at 22:42, Eric V. Smith <eric@trueblade.com> wrote:
While they're immutable at the Python level, strings (and all other objects) are mutated at the C level, due to reference count updates. You need to consider this if you're sharing objects without locking or other synchronization.
This is interesting. What if you want to have a language that uses only immutable objects and garbage collection? Could smart pointers address this problem?