我有一个合理的解决方案，至少用于调试目的。我目前没有一个可以在主要流程中引发异常的解决方案。我的第一个想法是使用装饰器，但是您只能腌制在模块顶层定义的函数，所以没错。
取而代之的是一个简单的包装类和一个Pool子类，将其用于
apply_async（因此
apply）。我将
map_async作为练习留给读者。
import tracebackfrom multiprocessing.pool import Poolimport multiprocessing# Shortcut to multiprocessing's loggerdef error(msg, *args): return multiprocessing.get_logger().error(msg, *args)class LogExceptions(object): def __init__(self, callable): self.__callable = callable def __call__(self, *args, **kwargs): try: result = self.__callable(*args, **kwargs) except Exception as e: # Here we add some debugging help. If multiprocessing's # debugging is on, it will arrange to log the traceback error(traceback.format_exc()) # Re-raise the original exception so the Pool worker can # clean up raise # It was fine, give a normal answer return resultclass LoggingPool(Pool): def apply_async(self, func, args=(), kwds={}, callback=None): return Pool.apply_async(self, LogExceptions(func), args, kwds, callback)def go(): print(1) raise Exception() print(2)multiprocessing.log_to_stderr()p = LoggingPool(processes=1)p.apply_async(go)p.close()p.join()这给了我：
1[ERROR/PoolWorker-1] Traceback (most recent call last): File "mpdebug.py", line 24, in __call__ result = self.__callable(*args, **kwargs) File "mpdebug.py", line 44, in go raise Exception()Exception
