import logging
import logging.handlers
import multiprocessing
import multiprocessing.util

L = logging.getLogger(__name__)

_globalQueue = None
_globalListener = None

def basicsetup():
    global _globalQueue
    global _globalListener

    cf = logging.Formatter("[{levelname}] {created:.7f} {name} ({process}~{processName}): {message}", style="{")

    handler = logging.StreamHandler()
    handler.setLevel(logging.DEBUG)
    handler.setFormatter(cf)

    # Subprocesses should use the queue to send log messages back to a thread in the main process
    _globalQueue = multiprocessing.Queue()

    _globalListener = logging.handlers.QueueListener(_globalQueue, handler, respect_handler_level=True)
    _globalListener.start()

    # Configure logging for main thread
    process_setup(get_queue())

def get_queue():
    return _globalQueue

def process_setup(queue):
    handler = logging.handlers.QueueHandler(queue)
    logger = logging.getLogger()
    logger.setLevel(logging.DEBUG)
    logger.addHandler(handler)



def do_work(i):
    # Do something that involves logging
    # If nothing is logged, it works fine
    L.info("Hello {} from MP".format(i))

if __name__ == "__main__":
    # Also fails with other startup methods, but this is what I'm using in the actual application
    multiprocessing.set_start_method("spawn")
    # Optional, but more debugging info
    multiprocessing.util.log_to_stderr()
    # Configure logging
    basicsetup()

    # Set up multiprocessing pool, initialising logging in each subprocess
    with multiprocessing.Pool(initializer=process_setup, initargs=(get_queue(),)) as pl:
        # 100 seems to work fine, 500 fails most of the time.
        # If you're having trouble reproducing the error, try bumping this number up to 1000
        pl.map(do_work, range(10000))

    if _globalListener is not None:
        # Stop the listener and join the thread it runs on.
        # If we don't do this, we may lose log messages when we exit.
        _globalListener.stop()