多重处理功能上的超时装饰器


问题内容

我直接从网上发现的一个例子中得到了这个装饰器:

class TimedOutExc(Exception):
    pass


def timeout(timeout):
    def decorate(f):
        def handler(signum, frame):
            raise TimedOutExc()

        def new_f(*args, **kwargs):

            old = signal.signal(signal.SIGALRM, handler)
            signal.alarm(timeout)

            try:
                result = f(*args, **kwargs)
            except TimedOutExc:
                return None
            finally:
                signal.signal(signal.SIGALRM, old)
            signal.alarm(0)
            return result

        new_f.func_name = f.func_name
        return new_f

    return decorate

如果f函数超时,它将引发异常。

很好,它可以工作,但是当我在多处理功能上使用此装饰器并由于超时而停止时,它不会终止计算中涉及的进程。我怎样才能做到这一点?

我不想启动异常并停止程序。基本上我想要的是f超时时,让它返回None,然后终止所涉及的进程。


问题答案:

尽管我同意亚伦的回答的要点,但我想详细说明一下。

由启动的过程multiprocessing必须 在要装饰的功能中 停止;
我认为一般不能从装饰器本身简单地完成此操作(装饰的函数是唯一知道它启动了哪些计算的实体)。

除了具有修饰的功能catch之外SIGALARM,您还可以捕获您的自定义TimedOutExc异常-这可能更灵活。您的示例将变为:

import signal
import functools

class TimedOutExc(Exception):
    """
    Raised when a timeout happens
    """

def timeout(timeout):
    """
    Return a decorator that raises a TimedOutExc exception
    after timeout seconds, if the decorated function did not return.
    """

    def decorate(f):

        def handler(signum, frame):
            raise TimedOutExc()

        @functools.wraps(f)  # Preserves the documentation, name, etc.
        def new_f(*args, **kwargs):

            old_handler = signal.signal(signal.SIGALRM, handler)
            signal.alarm(timeout)

            result = f(*args, **kwargs)  # f() always returns, in this scheme

            signal.signal(signal.SIGALRM, old_handler)  # Old signal handler is restored
            signal.alarm(0)  # Alarm removed

            return result

        return new_f

    return decorate

@timeout(10)
def function_that_takes_a_long_time():
    try:
        # ... long, parallel calculation ...
    except TimedOutExc:
        # ... Code that shuts down the processes ...
        # ...
        return None  # Or exception raised, which means that the calculation is not complete