如果您在UNIX上运行，则可以使用信号包:

In [1]: import signal

# Register an handler for the timeout
In [2]: def handler(signum, frame):
   ...:     print("Forever is over!")
   ...:     raise Exception("end of time")
   ...: 

# This function *may* run for an indetermined time...
In [3]: def loop_forever():
   ...:     import time
   ...:     while 1:
   ...:         print("sec")
   ...:         time.sleep(1)
   ...:         
   ...:         

# Register the signal function handler
In [4]: signal.signal(signal.SIGALRM, handler)
Out[4]: 0

# Define a timeout for your function
In [5]: signal.alarm(10)
Out[5]: 0

In [6]: try:
   ...:     loop_forever()
   ...: except Exception, exc: 
   ...:     print(exc)
   ....: 
sec
sec
sec
sec
sec
sec
sec
sec
Forever is over!
end of time

# Cancel the timer if the function returned before timeout
# (ok, mine won't but yours maybe will :)
In [7]: signal.alarm(0)
Out[7]: 0

在调用signal.alarm(10)后10秒，调用处理程序。这会引发一个异常，您可以从常规Python代码中拦截该异常。

这个模块不能很好地使用线程(但是，谁能呢?)

注意，由于我们在超时发生时引发异常，它可能最终在函数内部被捕获并忽略，例如这样一个函数:

def loop_forever():
    while 1:
        print('sec')
        try:
            time.sleep(10)
        except:
            continue

我怎么调用函数或者我怎么包装它，如果它超过5秒脚本取消它?

我发布了一个要点，用装饰器和threading.Timer解决了这个问题。下面是它的分类。

导入和设置兼容性

它是用Python 2和3测试的。它也应该在Unix/Linux和Windows下工作。

首先是进口。这些尝试保持代码的一致性，而不管Python版本:

from __future__ import print_function
import sys
import threading
from time import sleep
try:
    import thread
except ImportError:
    import _thread as thread

使用版本独立代码:

try:
    range, _print = xrange, print
    def print(*args, **kwargs): 
        flush = kwargs.pop('flush', False)
        _print(*args, **kwargs)
        if flush:
            kwargs.get('file', sys.stdout).flush()            
except NameError:
    pass

现在我们已经从标准库导入了我们的功能。

exit_after装饰

接下来，我们需要一个函数来终止子线程的main():

def quit_function(fn_name):
    # print to stderr, unbuffered in Python 2.
    print('{0} took too long'.format(fn_name), file=sys.stderr)
    sys.stderr.flush() # Python 3 stderr is likely buffered.
    thread.interrupt_main() # raises KeyboardInterrupt

这是decorator本身:

def exit_after(s):
    '''
    use as decorator to exit process if 
    function takes longer than s seconds
    '''
    def outer(fn):
        def inner(*args, **kwargs):
            timer = threading.Timer(s, quit_function, args=[fn.__name__])
            timer.start()
            try:
                result = fn(*args, **kwargs)
            finally:
                timer.cancel()
            return result
        return inner
    return outer

使用

下面这个用法直接回答了你关于5秒后退出的问题!：

@exit_after(5)
def countdown(n):
    print('countdown started', flush=True)
    for i in range(n, -1, -1):
        print(i, end=', ', flush=True)
        sleep(1)
    print('countdown finished')

演示:

>>> countdown(3)
countdown started
3, 2, 1, 0, countdown finished
>>> countdown(10)
countdown started
10, 9, 8, 7, 6, countdown took too long
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 11, in inner
  File "<stdin>", line 6, in countdown
KeyboardInterrupt

第二个函数调用将不会结束，相反，进程应该退出并返回一个跟踪!

KeyboardInterrupt并不总是停止一个睡眠线程

注意，在Windows上的Python 2中，睡眠并不总是被键盘中断中断，例如:

@exit_after(1)
def sleep10():
    sleep(10)
    print('slept 10 seconds')

>>> sleep10()
sleep10 took too long         # Note that it hangs here about 9 more seconds
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 11, in inner
  File "<stdin>", line 3, in sleep10
KeyboardInterrupt

它也不可能中断扩展中运行的代码，除非它显式地检查PyErr_CheckSignals()，参见忽略Cython, Python和KeyboardInterrupt

在任何情况下，我都会避免让线程休眠超过一秒钟——这在处理器时间上是一eon。

我怎么调用这个函数或者我把它包装在什么里面，这样如果它花费超过5秒脚本就会取消它并做其他事情?

要捕获它并做其他事情，你可以捕获KeyboardInterrupt。

>>> try:
...     countdown(10)
... except KeyboardInterrupt:
...     print('do something else')
... 
countdown started
10, 9, 8, 7, 6, countdown took too long
do something else

我是wrapt_timeout_decorator的作者。

这里介绍的大多数解决方案乍一看在Linux下都工作得很好——因为我们有fork()和signals()——但在windows上看起来有点不同。 当涉及到Linux上的子线程时，你不能再使用信号了。

为了在Windows下生成一个进程，它需要是可pickle的——许多装饰函数或Class方法都不是。

所以你需要使用一个更好的pickler像莳萝和multiprocess(不是pickle和multiprocessing) -这就是为什么你不能使用ProcessPoolExecutor(或只有有限的功能)。

For the timeout itself - You need to define what timeout means - because on Windows it will take considerable (and not determinable) time to spawn the process. This can be tricky on short timeouts. Lets assume, spawning the process takes about 0.5 seconds (easily !!!). If You give a timeout of 0.2 seconds what should happen? Should the function time out after 0.5 + 0.2 seconds (so let the method run for 0.2 seconds)? Or should the called process time out after 0.2 seconds (in that case, the decorated function will ALWAYS timeout, because in that time it is not even spawned)?

嵌套的装饰器也很讨厌，你不能在子线程中使用信号。如果你想要创建一个真正通用的、跨平台的装饰器，所有这些都需要考虑(并测试)。

其他问题是将异常传递回调用者，以及记录问题(如果在装饰函数中使用-不支持记录到另一个进程中的文件)

我试图涵盖所有的边缘情况，您可以查看包wrapt_timeout_decorator，或者至少测试您自己的解决方案，受到那里使用的单元测试的启发。

@Alexis Eggermont -不幸的是，我没有足够的分数来评论-也许其他人可以通知你-我认为我解决了你的进口问题。

在@piro答案的基础上，您可以构建一个contextmanager。这允许非常易读的代码，将在成功运行后禁用警报信号(sets signal.alarm(0))

from contextlib import contextmanager
import signal
import time

@contextmanager
def timeout(duration):
    def timeout_handler(signum, frame):
        raise TimeoutError(f'block timedout after {duration} seconds')
    signal.signal(signal.SIGALRM, timeout_handler)
    signal.alarm(duration)
    try:
        yield
    finally:
        signal.alarm(0)

def sleeper(duration):
    time.sleep(duration)
    print('finished')

使用示例:

In [19]: with timeout(2):
    ...:     sleeper(1)
    ...:     
finished

In [20]: with timeout(2):
    ...:     sleeper(3)
    ...:         
---------------------------------------------------------------------------
Exception                                 Traceback (most recent call last)
<ipython-input-20-66c78858116f> in <module>()
      1 with timeout(2):
----> 2     sleeper(3)
      3 

<ipython-input-7-a75b966bf7ac> in sleeper(t)
      1 def sleeper(t):
----> 2     time.sleep(t)
      3     print('finished')
      4 

<ipython-input-18-533b9e684466> in timeout_handler(signum, frame)
      2 def timeout(duration):
      3     def timeout_handler(signum, frame):
----> 4         raise Exception(f'block timedout after {duration} seconds')
      5     signal.signal(signal.SIGALRM, timeout_handler)
      6     signal.alarm(duration)

Exception: block timedout after 2 seconds

#!/usr/bin/python2
import sys, subprocess, threading
proc = subprocess.Popen(sys.argv[2:])
timer = threading.Timer(float(sys.argv[1]), proc.terminate)
timer.start()
proc.wait()
timer.cancel()
exit(proc.returncode)

如果工作没有完成，我打算杀死进程，使用线程和进程来实现这一点。

from concurrent.futures import ThreadPoolExecutor

from time import sleep
import multiprocessing


# test case 1
def worker_1(a,b,c):
    for _ in range(2):
        print('very time consuming sleep')
        sleep(1)

    return a+b+c

# test case 2
def worker_2(in_name):
    for _ in range(10):
        print('very time consuming sleep')
        sleep(1)

    return 'hello '+in_name

作为上下文管理器的实际类

class FuncTimer():
    def __init__(self,fn,args,runtime):
        self.fn = fn
        self.args = args
        self.queue = multiprocessing.Queue()
        self.runtime = runtime
        self.process = multiprocessing.Process(target=self.thread_caller)

    def thread_caller(self):
        with ThreadPoolExecutor() as executor:
            future = executor.submit(self.fn, *self.args)
            self.queue.put(future.result())

    def  __enter__(self):
        return self

    def start_run(self):
        self.process.start()
        self.process.join(timeout=self.runtime)
        if self.process.exitcode is None:
            self.process.kill()
        if self.process.exitcode is None:
            out_res = None
            print('killed premature')
        else:
            out_res = self.queue.get()
        return out_res


    def __exit__(self, exc_type, exc_value, exc_traceback):
        self.process.kill()

如何使用

print('testing case 1') 
with FuncTimer(fn=worker_1,args=(1,2,3),runtime = 5) as fp: 
    res = fp.start_run()
    print(res)

print('testing case 2')
with FuncTimer(fn=worker_2,args=('ram',),runtime = 5) as fp: 
    res = fp.start_run()
    print(res)