Python Multiprocessing Locks

Question

This multiprocessing code works as expected. It creates 4 Python processes, and uses them to print the numbers 0 through 39, with a delay after each print.

import multiprocessing import time  def job(num):   print num   time.sleep(1)  pool = multiprocessing.Pool(4)  lst = range(40) for i in lst:   pool.apply_async(job, [i])  pool.close() pool.join() 

However, when I try to use a multiprocessing.Lock to prevent multiple processes from printing to standard out, the program just exits immediately without any output.

import multiprocessing import time  def job(lock, num):   lock.acquire()   print num   lock.release()   time.sleep(1)  pool = multiprocessing.Pool(4) l = multiprocessing.Lock()  lst = range(40) for i in lst:   pool.apply_async(job, [l, i])  pool.close() pool.join() 

Why does the introduction of a multiprocessing.Lock make this code not work?

Update: It works when the lock is declared globally (where I did a few non-definitive tests to check that the lock works), as opposed to the code above which passes the lock as an argument (Python's multiprocessing documentation shows locks being passed as arguments). The code below has a lock declared globally, as opposed to passing as an argument in the code above.

import multiprocessing import time  l = multiprocessing.Lock()  def job(num):   l.acquire()   print num   l.release()   time.sleep(1)  pool = multiprocessing.Pool(4)  lst = range(40) for i in lst:   pool.apply_async(job, [i])  pool.close() pool.join() 

Answer 1

If you change pool.apply_async to pool.apply, you get this exception:

Traceback (most recent call last):   File "p.py", line 15, in <module>     pool.apply(job, [l, i])   File "/usr/lib/python2.7/multiprocessing/pool.py", line 244, in apply     return self.apply_async(func, args, kwds).get()   File "/usr/lib/python2.7/multiprocessing/pool.py", line 558, in get     raise self._value RuntimeError: Lock objects should only be shared between processes through inheritance 

pool.apply_async is just hiding it. I hate to say this, but using a global variable is probably the simplest way for your example. Let's just hope the velociraptors don't get you.