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 <e...@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?
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