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

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)

在pypi上找到的stopit包似乎可以很好地处理超时。

我喜欢@stopit。Threading_timeoutable装饰器，它向被装饰的函数添加了一个超时参数，该参数执行您所期望的操作，它将停止该函数。

在pypi上查看:https://pypi.python.org/pypi/stopit

以防对任何人都有帮助，在@piro的回答的基础上，我做了一个函数装饰器:

import time
import signal
from functools import wraps


def timeout(timeout_secs: int):
    def wrapper(func):
        @wraps(func)
        def time_limited(*args, **kwargs):
            # Register an handler for the timeout
            def handler(signum, frame):
                raise Exception(f"Timeout for function '{func.__name__}'")

            # Register the signal function handler
            signal.signal(signal.SIGALRM, handler)

            # Define a timeout for your function
            signal.alarm(timeout_secs)

            result = None
            try:
                result = func(*args, **kwargs)
            except Exception as exc:
                raise exc
            finally:
                # disable the signal alarm
                signal.alarm(0)

            return result

        return time_limited

    return wrapper

在一个有20秒超时的函数上使用包装器看起来像这样:

    @timeout(20)
    def my_slow_or_never_ending_function(name):
        while True:
            time.sleep(1)
            print(f"Yet another second passed {name}...")

    try:
        results = my_slow_or_never_ending_function("Yooo!")
    except Exception as e:
        print(f"ERROR: {e}")

下面是一个POSIX版本，它结合了前面的许多答案来提供以下特性:

子进程阻塞执行。 timeout函数在类成员函数上的使用。 严格要求终止时间。

下面是代码和一些测试用例:

import threading
import signal
import os
import time

class TerminateExecution(Exception):
    """
    Exception to indicate that execution has exceeded the preset running time.
    """


def quit_function(pid):
    # Killing all subprocesses
    os.setpgrp()
    os.killpg(0, signal.SIGTERM)

    # Killing the main thread
    os.kill(pid, signal.SIGTERM)


def handle_term(signum, frame):
    raise TerminateExecution()


def invoke_with_timeout(timeout, fn, *args, **kwargs):
    # Setting a sigterm handler and initiating a timer
    old_handler = signal.signal(signal.SIGTERM, handle_term)
    timer = threading.Timer(timeout, quit_function, args=[os.getpid()])
    terminate = False

    # Executing the function
    timer.start()
    try:
        result = fn(*args, **kwargs)
    except TerminateExecution:
        terminate = True
    finally:
        # Restoring original handler and cancel timer
        signal.signal(signal.SIGTERM, old_handler)
        timer.cancel()

    if terminate:
        raise BaseException("xxx")

    return result

### Test cases
def countdown(n):
    print('countdown started', flush=True)
    for i in range(n, -1, -1):
        print(i, end=', ', flush=True)
        time.sleep(1)
    print('countdown finished')
    return 1337


def really_long_function():
    time.sleep(10)


def really_long_function2():
    os.system("sleep 787")


# Checking that we can run a function as expected.
assert invoke_with_timeout(3, countdown, 1) == 1337

# Testing various scenarios
t1 = time.time()
try:
    print(invoke_with_timeout(1, countdown, 3))
    assert(False)
except BaseException:
    assert(time.time() - t1 < 1.1)
    print("All good", time.time() - t1)

t1 = time.time()
try:
    print(invoke_with_timeout(1, really_long_function2))
    assert(False)
except BaseException:
    assert(time.time() - t1 < 1.1)
    print("All good", time.time() - t1)


t1 = time.time()
try:
    print(invoke_with_timeout(1, really_long_function))
    assert(False)
except BaseException:
    assert(time.time() - t1 < 1.1)
    print("All good", time.time() - t1)

# Checking that classes are referenced and not
# copied (as would be the case with multiprocessing)


class X:
    def __init__(self):
        self.value = 0

    def set(self, v):
        self.value = v


x = X()
invoke_with_timeout(2, x.set, 9)
assert x.value == 9

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