我在Python中调用一个函数,我知道这个函数可能会暂停,并迫使我重新启动脚本。
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?
我在Python中调用一个函数,我知道这个函数可能会暂停,并迫使我重新启动脚本。
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?
当前回答
我有一个不同的建议,这是一个纯函数(与线程建议相同的API),似乎工作得很好(基于这个线程的建议)
def timeout(func, args=(), kwargs={}, timeout_duration=1, default=None):
import signal
class TimeoutError(Exception):
pass
def handler(signum, frame):
raise TimeoutError()
# set the timeout handler
signal.signal(signal.SIGALRM, handler)
signal.alarm(timeout_duration)
try:
result = func(*args, **kwargs)
except TimeoutError as exc:
result = default
finally:
signal.alarm(0)
return result
其他回答
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}")
Tim Savannah的func_timeout包对我来说工作得很好。
安装:
PIP安装func_timeout
用法:
import time
from func_timeout import func_timeout, FunctionTimedOut
def my_func(n):
time.sleep(n)
time_to_sleep = 10
# time out after 2 seconds using kwargs
func_timeout(2, my_func, kwargs={'n' : time_to_sleep})
# time out after 2 seconds using args
func_timeout(2, my_func, args=(time_to_sleep,))
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
我们也可以用信号来表示。我认为下面的例子会对你有用。与线程相比,它非常简单。
import signal
def timeout(signum, frame):
raise myException
#this is an infinite loop, never ending under normal circumstances
def main():
print 'Starting Main ',
while 1:
print 'in main ',
#SIGALRM is only usable on a unix platform
signal.signal(signal.SIGALRM, timeout)
#change 5 to however many seconds you need
signal.alarm(5)
try:
main()
except myException:
print "whoops"
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)