我试图限制允许函数在python(flask)中运行的时间。它看起来像这样:
def my_function:
try:
long_function_time()
catch TimeOutException:
return "Function took too long to execute"
def long_function_time:
#stuff here
我最初尝试使用信号,但被告知这不是一个好方法,因为烧瓶在线程环境中运行。我希望最大执行时间灵活,以便我可以轻松更改它。
我目前使用的代码(有时不起作用,不知道原因):
class TimedOutExc(Exception):
pass
def deadline(timeout, *args):
def decorate(f):
def handler(signum, frame):
signal.alarm(0)
raise TimedOutExc()
def new_f(*args):
signal.signal(signal.SIGALRM, handler)
signal.alarm(timeout)
return f(*args)
new_f.__name__ = f.__name__
return new_f
return decorate
提前致谢!
答案 0 :(得分:5)
这适用于CPython 2(使用2.7测试),显然不使用信号,而是使用CPython解释器循环。因此,您仍然必须处理本机I / O调用中的非Python块和类似的(例如,您必须设置socket.timeout
)。此外,它有一个可能很大的运行时惩罚(你可以让它检查每个* n *次调用超时,以减轻一点)。
仍然有助于解决某类问题(例如计算)。如果您希望它与分析器共存,您将不得不投入一些工作。
import sys
import time
class WatchdogTimeoutError(RuntimeError):
"""Raised in case of runtime limit violations."""
def sleeper(tick):
"""Endless loop."""
while True:
time.sleep(tick)
def watchdog(timeout, code, *args, **kwargs):
"Time-limited execution."
def tracer(frame, event, arg, start=time.time()):
"Helper."
now = time.time()
if now > start + timeout:
raise WatchdogTimeoutError(start, now)
return tracer if event == "call" else None
old_tracer = sys.gettrace()
try:
sys.settrace(tracer)
code(*args, **kwargs)
finally:
sys.settrace(old_tracer)
def demo():
"""Show timeout executor."""
try:
watchdog(5, sleeper, 0.1)
except WatchdogTimeoutError, exc:
start, abort = exc.args
print "Aborted after %.3f secs" % (abort - start,)
else:
print "Ended"
if __name__ == "__main__":
demo()
答案 1 :(得分:3)
尝试使用线程:
from multiprocessing import Pool, TimeoutError
from time import sleep
class TimedOutExc(Exception):
pass
def f(x):
sleep(2)
return x*x
pool = Pool(processes=1)
result = pool.apply_async(f, (1,))
try:
print(result.get(timeout=1))
except TimeoutError:
print 'timeout'
raise TimedOutExc()