现在我在框架中有一个中心模块，它使用Python 2.6 multiprocessing模块生成多个进程。因为它使用多处理，所以有一个模块级的多处理感知日志，log = multiprocessing.get_logger()。根据文档，这个日志记录器(EDIT)没有进程共享锁，所以你不会在sys. exe中弄乱东西。Stderr(或任何文件句柄)，让多个进程同时写入它。
我现在遇到的问题是框架中的其他模块不支持多处理。在我看来，我需要让这个中心模块上的所有依赖都使用多处理感知日志。这在框架内很烦人，更不用说对框架的所有客户端了。还有我想不到的选择吗?
当前回答
下面是另一个简单的解决方案，适用于从谷歌到这里的其他人(比如我)。日志记录应该很简单!仅适用于3.2或更高版本。
import multiprocessing
import logging
from logging.handlers import QueueHandler, QueueListener
import time
import random
def f(i):
time.sleep(random.uniform(.01, .05))
logging.info('function called with {} in worker thread.'.format(i))
time.sleep(random.uniform(.01, .05))
return i
def worker_init(q):
# all records from worker processes go to qh and then into q
qh = QueueHandler(q)
logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
logger.addHandler(qh)
def logger_init():
q = multiprocessing.Queue()
# this is the handler for all log records
handler = logging.StreamHandler()
handler.setFormatter(logging.Formatter("%(levelname)s: %(asctime)s - %(process)s - %(message)s"))
# ql gets records from the queue and sends them to the handler
ql = QueueListener(q, handler)
ql.start()
logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
# add the handler to the logger so records from this process are handled
logger.addHandler(handler)
return ql, q
def main():
q_listener, q = logger_init()
logging.info('hello from main thread')
pool = multiprocessing.Pool(4, worker_init, [q])
for result in pool.map(f, range(10)):
pass
pool.close()
pool.join()
q_listener.stop()
if __name__ == '__main__':
main()
其他回答
到2020年，似乎有一种更简单的多处理日志记录方式。
这个函数将创建记录器。你可以在这里设置格式和你想要输出的位置(文件，stdout):
def create_logger():
import multiprocessing, logging
logger = multiprocessing.get_logger()
logger.setLevel(logging.INFO)
formatter = logging.Formatter(\
'[%(asctime)s| %(levelname)s| %(processName)s] %(message)s')
handler = logging.FileHandler('logs/your_file_name.log')
handler.setFormatter(formatter)
# this bit will make sure you won't have
# duplicated messages in the output
if not len(logger.handlers):
logger.addHandler(handler)
return logger
在init中实例化记录器:
if __name__ == '__main__':
from multiprocessing import Pool
logger = create_logger()
logger.info('Starting pooling')
p = Pool()
# rest of the code
现在，你只需要在每个需要记录日志的函数中添加这个引用:
logger = create_logger()
并输出消息:
logger.info(f'My message from {something}')
希望这能有所帮助。
有一个很棒的套餐
包: https://pypi.python.org/pypi/multiprocessing-logging/
代码: https://github.com/jruere/multiprocessing-logging
安装:
pip install multiprocessing-logging
然后添加:
import multiprocessing_logging
# This enables logs inside process
multiprocessing_logging.install_mp_handler()
下面是另一个简单的解决方案，适用于从谷歌到这里的其他人(比如我)。日志记录应该很简单!仅适用于3.2或更高版本。
import multiprocessing
import logging
from logging.handlers import QueueHandler, QueueListener
import time
import random
def f(i):
time.sleep(random.uniform(.01, .05))
logging.info('function called with {} in worker thread.'.format(i))
time.sleep(random.uniform(.01, .05))
return i
def worker_init(q):
# all records from worker processes go to qh and then into q
qh = QueueHandler(q)
logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
logger.addHandler(qh)
def logger_init():
q = multiprocessing.Queue()
# this is the handler for all log records
handler = logging.StreamHandler()
handler.setFormatter(logging.Formatter("%(levelname)s: %(asctime)s - %(process)s - %(message)s"))
# ql gets records from the queue and sends them to the handler
ql = QueueListener(q, handler)
ql.start()
logger = logging.getLogger()
logger.setLevel(logging.DEBUG)
# add the handler to the logger so records from this process are handled
logger.addHandler(handler)
return ql, q
def main():
q_listener, q = logger_init()
logging.info('hello from main thread')
pool = multiprocessing.Pool(4, worker_init, [q])
for result in pool.map(f, range(10)):
pass
pool.close()
pool.join()
q_listener.stop()
if __name__ == '__main__':
main()
只需将日志记录器的实例发布到某个地方。这样，其他模块和客户端就可以使用您的API来获取记录器，而不必导入multiprocessing。
其中一个替代方案是将多处理日志写入一个已知文件，并注册一个atexit处理程序来加入这些进程，并在stderr上读取它;但是，您无法通过这种方式获得stderr上输出消息的实时流。
