Python sharing a lock between processes

Here's a version (using Barrier instead of Lock, but you get the idea) which would also work on Windows (where the missing fork is causing additional troubles):

import multiprocessing as mp

def procs(uid_barrier):
    uid, barrier = uid_barrier
    print(uid, 'waiting')
    barrier.wait()
    print(uid, 'past barrier')    

def main():
    N_PROCS = 10
    with mp.Manager() as man:
        barrier = man.Barrier(N_PROCS)
        with mp.Pool(N_PROCS) as p:
            p.map(procs, ((uid, barrier) for uid in range(N_PROCS)))

if __name__ == '__main__':
    mp.freeze_support()
    main()

You can't pass normal multiprocessing.Lock objects to Pool methods, because they can't be pickled. There are two ways to get around this. One is to create Manager() and pass a Manager.Lock():

def main():
    iterable = [1, 2, 3, 4, 5]
    pool = multiprocessing.Pool()
    m = multiprocessing.Manager()
    l = m.Lock()
    func = partial(target, l)
    pool.map(func, iterable)
    pool.close()
    pool.join()

This is a little bit heavyweight, though; using a Manager requires spawning another process to host the Manager server. And all calls to acquire/release the lock have to be sent to that server via IPC.

The other option is to pass the regular multiprocessing.Lock() at Pool creation time, using the initializer kwarg. This will make your lock instance global in all the child workers:

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()

The second solution has the side-effect of no longer requiring partial.