问题
I am facing the problem with collecting logs from the following script.
Once I set up the SLEEP_TIME
to too "small" value, the LoggingThread
threads somehow block the logging module. The script freeze on logging request
in the action
function. If the SLEEP_TIME
is about 0.1 the script collect
all log messages as I expect.
I tried to follow this answer but it does not solve my problem.
import multiprocessing
import threading
import logging
import time
SLEEP_TIME = 0.000001
logger = logging.getLogger()
ch = logging.StreamHandler()
ch.setFormatter(logging.Formatter('%(asctime)s %(levelname)s %(funcName)s(): %(message)s'))
ch.setLevel(logging.DEBUG)
logger.setLevel(logging.DEBUG)
logger.addHandler(ch)
class LoggingThread(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
def run(self):
while True:
logger.debug('LoggingThread: {}'.format(self))
time.sleep(SLEEP_TIME)
def action(i):
logger.debug('action: {}'.format(i))
def do_parallel_job():
processes = multiprocessing.cpu_count()
pool = multiprocessing.Pool(processes=processes)
for i in range(20):
pool.apply_async(action, args=(i,))
pool.close()
pool.join()
if __name__ == '__main__':
logger.debug('START')
#
# multithread part
#
for _ in range(10):
lt = LoggingThread()
lt.setDaemon(True)
lt.start()
#
# multiprocess part
#
do_parallel_job()
logger.debug('FINISH')
How to use logging module in multiprocess and multithread scripts?
回答1:
This is probably bug 6721.
The problem is common in any situation where you have locks, threads and forks. If thread 1 had a lock while thread 2 calls fork, in the forked process, there will only be thread 2 and the lock will be held forever. In your case, that is logging.StreamHandler.lock
.
A fix can be found here for the logging
module. Note that you need to take care of any other locks, too.
回答2:
I've run into similar issue just recently while using logging module together with Pathos multiprocessing library. Still not 100% sure, but it seems, that in my case the problem may have been caused by the fact, that logging handler was trying to reuse a lock object from within different processes.
Was able to fix it with a simple wrapper around default logging Handler:
import threading
from collections import defaultdict
from multiprocessing import current_process
import colorlog
class ProcessSafeHandler(colorlog.StreamHandler):
def __init__(self):
super().__init__()
self._locks = defaultdict(lambda: threading.RLock())
def acquire(self):
current_process_id = current_process().pid
self._locks[current_process_id].acquire()
def release(self):
current_process_id = current_process().pid
self._locks[current_process_id].release()
来源:https://stackoverflow.com/questions/24509650/deadlock-with-logging-multiprocess-multithread-python-script