你可以使用多处理。过程来做到这一点。

Code

import multiprocessing
import time

# bar
def bar():
    for i in range(100):
        print "Tick"
        time.sleep(1)

if __name__ == '__main__':
    # Start bar as a process
    p = multiprocessing.Process(target=bar)
    p.start()

    # Wait for 10 seconds or until process finishes
    p.join(10)

    # If thread is still active
    if p.is_alive():
        print "running... let's kill it..."

        # Terminate - may not work if process is stuck for good
        p.terminate()
        # OR Kill - will work for sure, no chance for process to finish nicely however
        # p.kill()

        p.join()

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

下面是一个简单的例子，运行一个带有timeout的方法，并在成功时检索它的值。

import multiprocessing
import time

ret = {"foo": False}


def worker(queue):
    """worker function"""

    ret = queue.get()

    time.sleep(1)

    ret["foo"] = True
    queue.put(ret)


if __name__ == "__main__":
    queue = multiprocessing.Queue()
    queue.put(ret)

    p = multiprocessing.Process(target=worker, args=(queue,))
    p.start()
    p.join(timeout=10)

    if p.exitcode is None:
        print("The worker timed out.")
    else:
        print(f"The worker completed and returned: {queue.get()}")

asyncio的另一个解决方案:

如果你想取消后台任务，而不仅仅是在运行的主代码上超时，那么你需要一个来自主线程的显式通信，要求任务的代码取消，比如threading.Event()

import asyncio
import functools
import multiprocessing
from concurrent.futures.thread import ThreadPoolExecutor


class SingletonTimeOut:
    pool = None

    @classmethod
    def run(cls, to_run: functools.partial, timeout: float):
        pool = cls.get_pool()
        loop = cls.get_loop()
        try:
            task = loop.run_in_executor(pool, to_run)
            return loop.run_until_complete(asyncio.wait_for(task, timeout=timeout))
        except asyncio.TimeoutError as e:
            error_type = type(e).__name__ #TODO
            raise e

    @classmethod
    def get_pool(cls):
        if cls.pool is None:
            cls.pool = ThreadPoolExecutor(multiprocessing.cpu_count())
        return cls.pool

    @classmethod
    def get_loop(cls):
        try:
            return asyncio.get_event_loop()
        except RuntimeError:
            asyncio.set_event_loop(asyncio.new_event_loop())
            # print("NEW LOOP" + str(threading.current_thread().ident))
            return asyncio.get_event_loop()

# ---------------

TIME_OUT = float('0.2')  # seconds

def toto(input_items,nb_predictions):
    return 1

to_run = functools.partial(toto,
                           input_items=1,
                           nb_predictions="a")

results = SingletonTimeOut.run(to_run, TIME_OUT)

你可以使用多处理。过程来做到这一点。

Code

import multiprocessing
import time

# bar
def bar():
    for i in range(100):
        print "Tick"
        time.sleep(1)

if __name__ == '__main__':
    # Start bar as a process
    p = multiprocessing.Process(target=bar)
    p.start()

    # Wait for 10 seconds or until process finishes
    p.join(10)

    # If thread is still active
    if p.is_alive():
        print "running... let's kill it..."

        # Terminate - may not work if process is stuck for good
        p.terminate()
        # OR Kill - will work for sure, no chance for process to finish nicely however
        # p.kill()

        p.join()

#!/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)