In case you don't have access to functools.partial, you could use a wrapper function for this, as well.
def target(lock):
def wrapped_func(items):
for item in items:
# Do cool stuff
if (... some condition here ...):
lock.acquire()
# Write to stdout or logfile, etc.
lock.release()
return wrapped_func
def main():
iterable = [1, 2, 3, 4, 5]
pool = multiprocessing.Pool()
lck = multiprocessing.Lock()
pool.map(target(lck), iterable)
pool.close()
pool.join()
This makes target() into a function that accepts a lock (or whatever parameters you want to give), and it will return a function that only takes in an iterable as input, but can still use all your other parameters. That's what is ultimately passed in to pool.map(), which then should execute with no problems.