python multiprocessing pickling/manager/misc error (from PMOTW)

Question

I'm having some trouble getting the following code to run on Eclipse via Windows. The code is from Doug Hellman :

import random
import multiprocessing
import time


class ActivePool:

    def __init__(self):
        super(ActivePool, self).__init__()
        self.mgr = multiprocessing.Manager()
        self.active = self.mgr.list()
        self.lock = multiprocessing.Lock()

    def makeActive(self, name):
        with self.lock:
            self.active.append(name)

    def makeInactive(self, name):
        with self.lock:
            self.active.remove(name)

    def __str__(self):
        with self.lock:
            return str(self.active)


def worker(s, pool):
    name = multiprocessing.current_process().name
    with s:
        pool.makeActive(name)
        print('Activating {} now running {}'.format(
            name, pool))
        time.sleep(random.random())
        pool.makeInactive(name)


if __name__ == '__main__':
    pool = ActivePool()
    s = multiprocessing.Semaphore(3)
    jobs = [
        multiprocessing.Process(
            target=worker,
            name=str(i),
            args=(s, pool),
        )
        for i in range(10)
    ]

    for j in jobs:
        j.start()

    for j in jobs:
        j.join()
        print('Now running: %s' % str(pool))

I get the following error, which I assume is due to some pickling issue with passing in pool as an argument to Process .

Traceback (most recent call last):
  File "E:\Eclipse_Workspace\CodeExamples\FromCodes\CodeTest.py", line 50, in <module>
    j.start()
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\process.py", line 105, in start
    self._popen = self._Popen(self)
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\context.py", line 223, in _Popen
    return _default_context.get_context().Process._Popen(process_obj)
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\context.py", line 322, in _Popen
    return Popen(process_obj)
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\popen_spawn_win32.py", line 65, in __init__
    reduction.dump(process_obj, to_child)
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\reduction.py", line 60, in dump
    ForkingPickler(file, protocol).dump(obj)
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\connection.py", line 939, in reduce_pipe_connection
    dh = reduction.DupHandle(conn.fileno(), access)
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\connection.py", line 170, in fileno
    self._check_closed()
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\connection.py", line 136, in _check_closed
    raise OSError("handle is closed")
OSError: handle is closed
Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\spawn.py", line 99, in spawn_main
    new_handle = reduction.steal_handle(parent_pid, pipe_handle)
  File "C:\Users\Bob\AppData\Local\Programs\Python\Python36-32\lib\multiprocessing\reduction.py", line 87, in steal_handle
    _winapi.DUPLICATE_SAME_ACCESS | _winapi.DUPLICATE_CLOSE_SOURCE)
PermissionError: [WinError 5] Access is denied

A similar question's answer seems to suggest that I initialize pool with a function call at the top level, but I don't know how to apply that to this example. Do I initialize ActivePool in worker ? That seems to defeat the spirit of Hellman's example.

Another answer suggests I use __getstate__ , __setstate__ , to remove unpickleable objects and reconstruct them when unpickling, but I don't know a good way to do this with Proxy Objects like Manager, and I actually don't know what the unpickleable object is.

Is there any way I can make this example work with minimal changes? I really wish to understand what is going on under the hood. Thanks!

Edit - Problem Solved:

The pickling issue was pretty obvious in hindsight. The ActivePool's __init__ contained a Manager() object which seems unpicklable. The code runs normally as per Hellman's example if we remove self.mgr , and initialize the list ProxyObject in one line:

def __init__(self):
        super(ActivePool, self).__init__()
        self.active = multiprocessing.Manager().list()
        self.lock = multiprocessing.Lock()

Answer 1

Comment : The 'join()' was in the Hellman example, but I forgot to add it into the code snippet. Any other ideas?

I'm running Linux and it works as expected, Windows behave different read understanding-multiprocessing-shared-memory-management-locks-and-queues-in-pyt

To determine which Parameter of args=(s, pool) raise the Error remove one and use it as global .
Change:

def worker(s):
    ...

        args=(s,),

---

Note : There is no need to enclose a multiprocessing.Manager().list() with a Lock() .
This is not the culprit of your error.

---

Question : Is there any way I can make this example work with minimal changes?

Your __main__ Process terminates, therefore all started Processes die at unpredicted position of execution. Add simple a .join() at the end to let the __main__ wait until all Processes done:

    for j in jobs:
        j.join()

    print('EXIT __main__')

Tested with Python: 3.4.2