Sharing a Lock Between Processes in Python

When attempting to use pool.map() to target a function with multiple parameters, including a Lock() object, it's crucial to address the issue of sharing the lock between subprocesses. The conventional multiprocessing.Lock() cannot be passed directly to Pool methods due to pickling limitations.

Option 1: Using Manager and Manager.Lock()

One approach is to utilize Manager() and instantiate a Manager.Lock(). While this method is reliable, it involves more overhead due to the additional process that hosts the Manager server. Additionally, lock operations require communication with this server via IPC.

Option 2: Pass Lock at Pool Creation with initializer

Alternatively, you can pass the regular multiprocessing.Lock() during Pool initialization using the initializer keyword argument. This ensures that the lock instance is global in all child workers. This method eliminates the necessity for partial functions and streamlines the process.

Here's an example using Option 2:

def target(iterable_item):
    for item in items:
        # Do cool stuff
        if (... some condition here ...):
            lock.acquire()
            # Write to stdout or logfile, etc.
            lock.release()

def init(l):
    global lock
    lock = l

def main():
    iterable = [1, 2, 3, 4, 5]
    l = multiprocessing.Lock()
    pool = multiprocessing.Pool(initializer=init, initargs=(l,))
    pool.map(target, iterable)
    pool.close()
    pool.join()