Related
There is a socket related function call in my code, that function is from another module thus out of my control, the problem is that it blocks for hours occasionally, which is totally unacceptable, How can I limit the function execution time from my code? I guess the solution must utilize another thread.
An improvement on #rik.the.vik's answer would be to use the with statement to give the timeout function some syntactic sugar:
import signal
from contextlib import contextmanager
class TimeoutException(Exception): pass
#contextmanager
def time_limit(seconds):
def signal_handler(signum, frame):
raise TimeoutException("Timed out!")
signal.signal(signal.SIGALRM, signal_handler)
signal.alarm(seconds)
try:
yield
finally:
signal.alarm(0)
try:
with time_limit(10):
long_function_call()
except TimeoutException as e:
print("Timed out!")
I'm not sure how cross-platform this might be, but using signals and alarm might be a good way of looking at this. With a little work you could make this completely generic as well and usable in any situation.
http://docs.python.org/library/signal.html
So your code is going to look something like this.
import signal
def signal_handler(signum, frame):
raise Exception("Timed out!")
signal.signal(signal.SIGALRM, signal_handler)
signal.alarm(10) # Ten seconds
try:
long_function_call()
except Exception, msg:
print "Timed out!"
Here's a Linux/OSX way to limit a function's running time. This is in case you don't want to use threads, and want your program to wait until the function ends, or the time limit expires.
from multiprocessing import Process
from time import sleep
def f(time):
sleep(time)
def run_with_limited_time(func, args, kwargs, time):
"""Runs a function with time limit
:param func: The function to run
:param args: The functions args, given as tuple
:param kwargs: The functions keywords, given as dict
:param time: The time limit in seconds
:return: True if the function ended successfully. False if it was terminated.
"""
p = Process(target=func, args=args, kwargs=kwargs)
p.start()
p.join(time)
if p.is_alive():
p.terminate()
return False
return True
if __name__ == '__main__':
print run_with_limited_time(f, (1.5, ), {}, 2.5) # True
print run_with_limited_time(f, (3.5, ), {}, 2.5) # False
I prefer a context manager approach because it allows the execution of multiple python statements within a with time_limit statement. Because windows system does not have SIGALARM, a more portable and perhaps more straightforward method could be using a Timer
from contextlib import contextmanager
import threading
import _thread
class TimeoutException(Exception):
def __init__(self, msg=''):
self.msg = msg
#contextmanager
def time_limit(seconds, msg=''):
timer = threading.Timer(seconds, lambda: _thread.interrupt_main())
timer.start()
try:
yield
except KeyboardInterrupt:
raise TimeoutException("Timed out for operation {}".format(msg))
finally:
# if the action ends in specified time, timer is canceled
timer.cancel()
import time
# ends after 5 seconds
with time_limit(5, 'sleep'):
for i in range(10):
time.sleep(1)
# this will actually end after 10 seconds
with time_limit(5, 'sleep'):
time.sleep(10)
The key technique here is the use of _thread.interrupt_main to interrupt the main thread from the timer thread. One caveat is that the main thread does not always respond to the KeyboardInterrupt raised by the Timer quickly. For example, time.sleep() calls a system function so a KeyboardInterrupt will be handled after the sleep call.
Here: a simple way of getting the desired effect:
https://pypi.org/project/func-timeout
This saved my life.
And now an example on how it works: lets say you have a huge list of items to be processed and you are iterating your function over those items. However, for some strange reason, your function get stuck on item n, without raising an exception. You need to other items to be processed, the more the better. In this case, you can set a timeout for processing each item:
import time
import func_timeout
def my_function(n):
"""Sleep for n seconds and return n squared."""
print(f'Processing {n}')
time.sleep(n)
return n**2
def main_controller(max_wait_time, all_data):
"""
Feed my_function with a list of itens to process (all_data).
However, if max_wait_time is exceeded, return the item and a fail info.
"""
res = []
for data in all_data:
try:
my_square = func_timeout.func_timeout(
max_wait_time, my_function, args=[data]
)
res.append((my_square, 'processed'))
except func_timeout.FunctionTimedOut:
print('error')
res.append((data, 'fail'))
continue
return res
timeout_time = 2.1 # my time limit
all_data = range(1, 10) # the data to be processed
res = main_controller(timeout_time, all_data)
print(res)
Doing this from within a signal handler is dangerous: you might be inside an exception handler at the time the exception is raised, and leave things in a broken state. For example,
def function_with_enforced_timeout():
f = open_temporary_file()
try:
...
finally:
here()
unlink(f.filename)
If your exception is raised here(), the temporary file will never be deleted.
The solution here is for asynchronous exceptions to be postponed until the code is not inside exception-handling code (an except or finally block), but Python doesn't do that.
Note that this won't interrupt anything while executing native code; it'll only interrupt it when the function returns, so this may not help this particular case. (SIGALRM itself might interrupt the call that's blocking--but socket code typically simply retries after an EINTR.)
Doing this with threads is a better idea, since it's more portable than signals. Since you're starting a worker thread and blocking until it finishes, there are none of the usual concurrency worries. Unfortunately, there's no way to deliver an exception asynchronously to another thread in Python (other thread APIs can do this). It'll also have the same issue with sending an exception during an exception handler, and require the same fix.
You don't have to use threads. You can use another process to do the blocking work, for instance, maybe using the subprocess module. If you want to share data structures between different parts of your program then Twisted is a great library for giving yourself control of this, and I'd recommend it if you care about blocking and expect to have this trouble a lot. The bad news with Twisted is you have to rewrite your code to avoid any blocking, and there is a fair learning curve.
You can use threads to avoid blocking, but I'd regard this as a last resort, since it exposes you to a whole world of pain. Read a good book on concurrency before even thinking about using threads in production, e.g. Jean Bacon's "Concurrent Systems". I work with a bunch of people who do really cool high performance stuff with threads, and we don't introduce threads into projects unless we really need them.
The only "safe" way to do this, in any language, is to use a secondary process to do that timeout-thing, otherwise you need to build your code in such a way that it will time out safely by itself, for instance by checking the time elapsed in a loop or similar. If changing the method isn't an option, a thread will not suffice.
Why? Because you're risking leaving things in a bad state when you do. If the thread is simply killed mid-method, locks being held, etc. will just be held, and cannot be released.
So look at the process way, do not look at the thread way.
I would usually prefer using a contextmanager as suggested by #josh-lee
But in case someone is interested in having this implemented as a decorator, here's an alternative.
Here's how it would look like:
import time
from timeout import timeout
class Test(object):
#timeout(2)
def test_a(self, foo, bar):
print foo
time.sleep(1)
print bar
return 'A Done'
#timeout(2)
def test_b(self, foo, bar):
print foo
time.sleep(3)
print bar
return 'B Done'
t = Test()
print t.test_a('python', 'rocks')
print t.test_b('timing', 'out')
And this is the timeout.py module:
import threading
class TimeoutError(Exception):
pass
class InterruptableThread(threading.Thread):
def __init__(self, func, *args, **kwargs):
threading.Thread.__init__(self)
self._func = func
self._args = args
self._kwargs = kwargs
self._result = None
def run(self):
self._result = self._func(*self._args, **self._kwargs)
#property
def result(self):
return self._result
class timeout(object):
def __init__(self, sec):
self._sec = sec
def __call__(self, f):
def wrapped_f(*args, **kwargs):
it = InterruptableThread(f, *args, **kwargs)
it.start()
it.join(self._sec)
if not it.is_alive():
return it.result
raise TimeoutError('execution expired')
return wrapped_f
The output:
python
rocks
A Done
timing
Traceback (most recent call last):
...
timeout.TimeoutError: execution expired
out
Notice that even if the TimeoutError is thrown, the decorated method will continue to run in a different thread. If you would also want this thread to be "stopped" see: Is there any way to kill a Thread in Python?
Using simple decorator
Here's the version I made after studying above answers. Pretty straight forward.
def function_timeout(seconds: int):
"""Wrapper of Decorator to pass arguments"""
def decorator(func):
#contextmanager
def time_limit(seconds_):
def signal_handler(signum, frame): # noqa
raise TimeoutException(f"Timed out in {seconds_} seconds!")
signal.signal(signal.SIGALRM, signal_handler)
signal.alarm(seconds_)
try:
yield
finally:
signal.alarm(0)
#wraps(func)
def wrapper(*args, **kwargs):
with time_limit(seconds):
return func(*args, **kwargs)
return wrapper
return decorator
How to use?
#function_timeout(seconds=5)
def my_naughty_function():
while True:
print("Try to stop me ;-p")
Well of course, don't forget to import the function if it is in a separate file.
Here's a timeout function I think I found via google and it works for me.
From:
http://code.activestate.com/recipes/473878/
def timeout(func, args=(), kwargs={}, timeout_duration=1, default=None):
'''This function will spwan a thread and run the given function using the args, kwargs and
return the given default value if the timeout_duration is exceeded
'''
import threading
class InterruptableThread(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
self.result = default
def run(self):
try:
self.result = func(*args, **kwargs)
except:
self.result = default
it = InterruptableThread()
it.start()
it.join(timeout_duration)
if it.isAlive():
return it.result
else:
return it.result
The method from #user2283347 is tested working, but we want to get rid of the traceback messages. Use pass trick from Remove traceback in Python on Ctrl-C, the modified code is:
from contextlib import contextmanager
import threading
import _thread
class TimeoutException(Exception): pass
#contextmanager
def time_limit(seconds):
timer = threading.Timer(seconds, lambda: _thread.interrupt_main())
timer.start()
try:
yield
except KeyboardInterrupt:
pass
finally:
# if the action ends in specified time, timer is canceled
timer.cancel()
def timeout_svm_score(i):
#from sklearn import svm
#import numpy as np
#from IPython.core.display import display
#%store -r names X Y
clf = svm.SVC(kernel='linear', C=1).fit(np.nan_to_num(X[[names[i]]]), Y)
score = clf.score(np.nan_to_num(X[[names[i]]]),Y)
#scoressvm.append((score, names[i]))
display((score, names[i]))
%%time
with time_limit(5):
i=0
timeout_svm_score(i)
#Wall time: 14.2 s
%%time
with time_limit(20):
i=0
timeout_svm_score(i)
#(0.04541284403669725, '计划飞行时间')
#Wall time: 16.1 s
%%time
with time_limit(5):
i=14
timeout_svm_score(i)
#Wall time: 5h 43min 41s
We can see that this method may need far long time to interrupt the calculation, we asked for 5 seconds, but it work out in 5 hours.
This code works for Windows Server Datacenter 2016 with python 3.7.3 and I didn't tested on Unix, after mixing some answers from Google and StackOverflow, it finally worked for me like this:
from multiprocessing import Process, Lock
import time
import os
def f(lock,id,sleepTime):
lock.acquire()
print("I'm P"+str(id)+" Process ID: "+str(os.getpid()))
lock.release()
time.sleep(sleepTime) #sleeps for some time
print("Process: "+str(id)+" took this much time:"+str(sleepTime))
time.sleep(sleepTime)
print("Process: "+str(id)+" took this much time:"+str(sleepTime*2))
if __name__ == '__main__':
timeout_function=float(9) # 9 seconds for max function time
print("Main Process ID: "+str(os.getpid()))
lock=Lock()
p1=Process(target=f, args=(lock,1,6,)) #Here you can change from 6 to 3 for instance, so you can watch the behavior
start=time.time()
print(type(start))
p1.start()
if p1.is_alive():
print("process running a")
else:
print("process not running a")
while p1.is_alive():
timeout=time.time()
if timeout-start > timeout_function:
p1.terminate()
print("process terminated")
print("watching, time passed: "+str(timeout-start) )
time.sleep(1)
if p1.is_alive():
print("process running b")
else:
print("process not running b")
p1.join()
if p1.is_alive():
print("process running c")
else:
print("process not running c")
end=time.time()
print("I am the main process, the two processes are done")
print("Time taken:- "+str(end-start)+" secs") #MainProcess terminates at approx ~ 5 secs.
time.sleep(5) # To see if on Task Manager the child process is really being terminated, and it is
print("finishing")
The main code is from this link:
Create two child process using python(windows)
Then I used .terminate() to kill the child process. You can see that the function f calls 2 prints, one after 5 seconds and another after 10 seconds. However, with a 7 seconds sleep and the terminate(), it does not show the last print.
It worked for me, hope it helps!
Suppose I would like to run a function, called run_forever(), in a thread, but still have it 'stoppable' by pressing Ctrl+C. I've seen ways of doing this using a StoppableThread subclass of threading.Thread, but these seem to involve 'copying' the target function into that subclass. I would like to instead keep the function 'where it is'.
Consider the following example:
import time
import threading
def run_forever(): # An externally defined function which runs indefinitely
while True:
print("Hello, world!")
time.sleep(1)
class StoppableThread(threading.Thread):
"""Thread class with a stop() method. The thread itself has to check
regularly for the stopped() condition."""
def __init__(self, *args, **kwargs):
super(StoppableThread, self).__init__(*args, **kwargs)
self._stop = threading.Event()
def stop(self):
self._stop.set()
def stopped(self):
return self._stop.isSet()
def run(self):
while not self.stopped():
run_forever() # This doesn't work
# print("Hello, world!") # This does
self._stop.wait(1)
thread = StoppableThread()
thread.start()
time.sleep(5)
thread.stop()
The target function run_forever is itself a while-loop which never exits. However, to get the desired behavior the wait() command has to be inside that while-loop, as I understand it.
Is there any way of achieving the desired behavior without modifying the run_forever() function?
I doubt it's possible.
BTW, have you tried the second solution with
ThreadWithExc from the post you linked earlier?
It works if the loop is busy pure Python(eg no sleep), otherwise I'd switch to multiprocessing and kill subprocess. Here is the code that hopefully exits gracefully(*nix only):
from multiprocessing import Process
from signal import signal, SIGTERM
import time
def on_sigterm(*va):
raise SystemExit
def fun():
signal(SIGTERM, on_sigterm)
try:
for i in xrange(5):
print 'tick', i
time.sleep(1)
finally:
print 'graceful cleanup'
if __name__=='__main__':
proc = Process(target=fun)
proc.start()
time.sleep(2.5)
proc.terminate()
proc.join()
This is part of a complex project, I will try and simplify it.
I have a class that gets a callable and executes it, the callable can run for any duration of time. If I get a signal (can be using Signal or any other flag I watch) to terminate I want to terminate the callable's execution on the spot (without exiting the process of course)
class FooRunner(object):
def goo(self, foo):
try:
foo()
except:
pass
def on_stop_signal(self):
pass
On a single-threaded signal not running on Windows, (i.e., any Unix flavor) you can use signal.alarm for that.
Check the first example on the documentation - it is more or less what you are asking for:
https://docs.python.org/2/library/signal.html
If anyone ever needs this here is a code sample of it working (One thing to note signal.signal can be called only from the main thread):
#!/usr/bin/python
import time
import signal
import threading
class MyException(Exception):
pass
class FooRunner(object):
def goo(self, foo):
try:
signal.signal(signal.SIGALRM, self.on_stop_signal)
foo()
except MyException:
print('caugt alarm exception')
def on_stop_signal(self, *args):
print('alarm triggered')
raise MyException()
def sample_foo():
time.sleep(30)
def stop_it():
signal.alarm(3)
print('alarm was set for 3 seconds')
if __name__ == "__main__":
print('starting')
fr = FooRunner()
t = threading.Thread(target=stop_it)
t.start()
fr.goo(sample_foo)
Thanks #jsbueno
Im trying to write a module for Python that prints out text for my program and displays a progress bar while i do something in the background. Im using the 'threading' module currently but open to suggestions if something else will make it easier.
what i want to know is two fold, how should i call this class elegantly and how should i stop these threads im creating?
this is what im currently doing:
tmp1 = textprint("hello this is text")
tmp1.start()
# do something
tmp1.stop()
these are the options ive considered and looked into so far:
using thread.name to find the name of the thread or having the thread
return a name to kill afterwards. OR passing a number for similar
thread identification afterwards. (a bit cumbersome and not my
favourite solution.)
sending a thread.event ? - from reading the docs i see an event can
be sent, perhaps that can be used to stop it?
or a with statement but im unclear how to use it in this context, plus i find most of the python docs extremely confusing and not written for me at all.
what i would like to do is something like this:
echo('hello') (prints progress bar etc)
- and then when i want to stop it echo.stop()
the obv. problem there though is that the stop function doesnt know which thread it is trying to stop.
Here is a skeleton of what im trying to do:
import time
import string
import threading
class print_text(threading.Thread):
def __init__(self,arg=None):
super(print_text,self).__init__()
self._stop = False
self.arg=arg
def run (self):
# start thread for text
print self.txt
while not self._stop:
print "rude words"
def echo (self,txt):
self.txt=txt
self.start()
def stop(self):
self._stop = True
def stopped(self):
return self._stop == True
def __enter__(self):
print "woo"
return thing
def __exit__(self, type, value, traceback):
return isinstance(value, TypeError)
if __name__ == '__main__':
print_text.start.echo('this is text') # dunt werk
with print_text.echo('this is text'):
time.sleep(3)
print "done"
and then call it like so:
echo('this is text')
i also guess to do this i would have to
import echo from print_text
the WITH way of doing things suggests putting an __enter__ and __exit__ bit in. i tried them and they didnt work and also, i didnt know what i was doing, really appreciate any help, thanks.
You were very close to having working code. There just needed to be a few minor fixups:
print_text is a class. It should be instantiated with print_text()
The start method returns an instance of print_text, you need to save that
in order to call stop and echo on it: t = print_text()
The enter method needs to return self instead of thing.
The exit method should either set _stop or call stop().
The echo method should return self so that it can be used with the with-statement.
Here is some working code that includes those minor edits:
import time
import string
import threading
class print_text(threading.Thread):
def __init__(self, arg=None):
super(print_text,self).__init__()
self._stop = False
self.arg=arg
def run (self):
# start thread for text
print self.txt
while not self._stop:
print "rude words"
def echo (self, txt):
self.txt=txt
self.start()
return self
def stop(self):
self._stop = True
def stopped(self):
return self._stop == True
def __enter__(self):
print "woo"
return self
def __exit__(self, type, value, traceback):
self._stop = True
return isinstance(value, TypeError)
if __name__ == '__main__':
t = print_text()
t.echo('this is text')
time.sleep(3)
t.stop()
with print_text().echo('this is text'):
time.sleep(3)
print "done"
The best way to stop a thread in Python is to politely ask it to stop. The best way to pass new data to a thread is with the Queue module.
Both are used in the code in this post, which demonstrates socket communication from a Python thread but is otherwise relevant to your question. If you read the code carefully you'll notice:
Using threading.Event() which is set by a method call from outside, and which the thread periodically checks to know if it was asked to die.
Using Queue.Queue() for both passing commands to the thread and receiving responses from it.
A thread name is useful if you could potentially have multiple subthreads running the same target at once and want to ensure that all of them are stopped. It seems like a useful generalization and doesn't seem too cumbersome to me, but beauty is in the eye of the beholder :-). The following:
starts a subthread to print a message and start a progressbar
stops the subthread using a name given when it was started.
It is much simpler code. Does it do what you want?
import time, threading
class print_text:
def __init__(self):
pass
def progress(self):
while not self._stop: # Update progress bar
print(".", sep="", end="")
time.sleep(.5)
def echo(self, arg="Default"): # Print message and start progress bar
print(arg)
self._stop = False
threading.Thread(target=self.progress, name="_prog_").start()
def stop(self):
self._stop = True
for t in threading.enumerate():
if t.name == "_prog_":
t.join()
tmp1 = print_text()
tmp1.echo("hello this is text")
time.sleep(10)
tmp1.stop()
print("Done")
There is a socket related function call in my code, that function is from another module thus out of my control, the problem is that it blocks for hours occasionally, which is totally unacceptable, How can I limit the function execution time from my code? I guess the solution must utilize another thread.
An improvement on #rik.the.vik's answer would be to use the with statement to give the timeout function some syntactic sugar:
import signal
from contextlib import contextmanager
class TimeoutException(Exception): pass
#contextmanager
def time_limit(seconds):
def signal_handler(signum, frame):
raise TimeoutException("Timed out!")
signal.signal(signal.SIGALRM, signal_handler)
signal.alarm(seconds)
try:
yield
finally:
signal.alarm(0)
try:
with time_limit(10):
long_function_call()
except TimeoutException as e:
print("Timed out!")
I'm not sure how cross-platform this might be, but using signals and alarm might be a good way of looking at this. With a little work you could make this completely generic as well and usable in any situation.
http://docs.python.org/library/signal.html
So your code is going to look something like this.
import signal
def signal_handler(signum, frame):
raise Exception("Timed out!")
signal.signal(signal.SIGALRM, signal_handler)
signal.alarm(10) # Ten seconds
try:
long_function_call()
except Exception, msg:
print "Timed out!"
Here's a Linux/OSX way to limit a function's running time. This is in case you don't want to use threads, and want your program to wait until the function ends, or the time limit expires.
from multiprocessing import Process
from time import sleep
def f(time):
sleep(time)
def run_with_limited_time(func, args, kwargs, time):
"""Runs a function with time limit
:param func: The function to run
:param args: The functions args, given as tuple
:param kwargs: The functions keywords, given as dict
:param time: The time limit in seconds
:return: True if the function ended successfully. False if it was terminated.
"""
p = Process(target=func, args=args, kwargs=kwargs)
p.start()
p.join(time)
if p.is_alive():
p.terminate()
return False
return True
if __name__ == '__main__':
print run_with_limited_time(f, (1.5, ), {}, 2.5) # True
print run_with_limited_time(f, (3.5, ), {}, 2.5) # False
I prefer a context manager approach because it allows the execution of multiple python statements within a with time_limit statement. Because windows system does not have SIGALARM, a more portable and perhaps more straightforward method could be using a Timer
from contextlib import contextmanager
import threading
import _thread
class TimeoutException(Exception):
def __init__(self, msg=''):
self.msg = msg
#contextmanager
def time_limit(seconds, msg=''):
timer = threading.Timer(seconds, lambda: _thread.interrupt_main())
timer.start()
try:
yield
except KeyboardInterrupt:
raise TimeoutException("Timed out for operation {}".format(msg))
finally:
# if the action ends in specified time, timer is canceled
timer.cancel()
import time
# ends after 5 seconds
with time_limit(5, 'sleep'):
for i in range(10):
time.sleep(1)
# this will actually end after 10 seconds
with time_limit(5, 'sleep'):
time.sleep(10)
The key technique here is the use of _thread.interrupt_main to interrupt the main thread from the timer thread. One caveat is that the main thread does not always respond to the KeyboardInterrupt raised by the Timer quickly. For example, time.sleep() calls a system function so a KeyboardInterrupt will be handled after the sleep call.
Here: a simple way of getting the desired effect:
https://pypi.org/project/func-timeout
This saved my life.
And now an example on how it works: lets say you have a huge list of items to be processed and you are iterating your function over those items. However, for some strange reason, your function get stuck on item n, without raising an exception. You need to other items to be processed, the more the better. In this case, you can set a timeout for processing each item:
import time
import func_timeout
def my_function(n):
"""Sleep for n seconds and return n squared."""
print(f'Processing {n}')
time.sleep(n)
return n**2
def main_controller(max_wait_time, all_data):
"""
Feed my_function with a list of itens to process (all_data).
However, if max_wait_time is exceeded, return the item and a fail info.
"""
res = []
for data in all_data:
try:
my_square = func_timeout.func_timeout(
max_wait_time, my_function, args=[data]
)
res.append((my_square, 'processed'))
except func_timeout.FunctionTimedOut:
print('error')
res.append((data, 'fail'))
continue
return res
timeout_time = 2.1 # my time limit
all_data = range(1, 10) # the data to be processed
res = main_controller(timeout_time, all_data)
print(res)
Doing this from within a signal handler is dangerous: you might be inside an exception handler at the time the exception is raised, and leave things in a broken state. For example,
def function_with_enforced_timeout():
f = open_temporary_file()
try:
...
finally:
here()
unlink(f.filename)
If your exception is raised here(), the temporary file will never be deleted.
The solution here is for asynchronous exceptions to be postponed until the code is not inside exception-handling code (an except or finally block), but Python doesn't do that.
Note that this won't interrupt anything while executing native code; it'll only interrupt it when the function returns, so this may not help this particular case. (SIGALRM itself might interrupt the call that's blocking--but socket code typically simply retries after an EINTR.)
Doing this with threads is a better idea, since it's more portable than signals. Since you're starting a worker thread and blocking until it finishes, there are none of the usual concurrency worries. Unfortunately, there's no way to deliver an exception asynchronously to another thread in Python (other thread APIs can do this). It'll also have the same issue with sending an exception during an exception handler, and require the same fix.
You don't have to use threads. You can use another process to do the blocking work, for instance, maybe using the subprocess module. If you want to share data structures between different parts of your program then Twisted is a great library for giving yourself control of this, and I'd recommend it if you care about blocking and expect to have this trouble a lot. The bad news with Twisted is you have to rewrite your code to avoid any blocking, and there is a fair learning curve.
You can use threads to avoid blocking, but I'd regard this as a last resort, since it exposes you to a whole world of pain. Read a good book on concurrency before even thinking about using threads in production, e.g. Jean Bacon's "Concurrent Systems". I work with a bunch of people who do really cool high performance stuff with threads, and we don't introduce threads into projects unless we really need them.
The only "safe" way to do this, in any language, is to use a secondary process to do that timeout-thing, otherwise you need to build your code in such a way that it will time out safely by itself, for instance by checking the time elapsed in a loop or similar. If changing the method isn't an option, a thread will not suffice.
Why? Because you're risking leaving things in a bad state when you do. If the thread is simply killed mid-method, locks being held, etc. will just be held, and cannot be released.
So look at the process way, do not look at the thread way.
I would usually prefer using a contextmanager as suggested by #josh-lee
But in case someone is interested in having this implemented as a decorator, here's an alternative.
Here's how it would look like:
import time
from timeout import timeout
class Test(object):
#timeout(2)
def test_a(self, foo, bar):
print foo
time.sleep(1)
print bar
return 'A Done'
#timeout(2)
def test_b(self, foo, bar):
print foo
time.sleep(3)
print bar
return 'B Done'
t = Test()
print t.test_a('python', 'rocks')
print t.test_b('timing', 'out')
And this is the timeout.py module:
import threading
class TimeoutError(Exception):
pass
class InterruptableThread(threading.Thread):
def __init__(self, func, *args, **kwargs):
threading.Thread.__init__(self)
self._func = func
self._args = args
self._kwargs = kwargs
self._result = None
def run(self):
self._result = self._func(*self._args, **self._kwargs)
#property
def result(self):
return self._result
class timeout(object):
def __init__(self, sec):
self._sec = sec
def __call__(self, f):
def wrapped_f(*args, **kwargs):
it = InterruptableThread(f, *args, **kwargs)
it.start()
it.join(self._sec)
if not it.is_alive():
return it.result
raise TimeoutError('execution expired')
return wrapped_f
The output:
python
rocks
A Done
timing
Traceback (most recent call last):
...
timeout.TimeoutError: execution expired
out
Notice that even if the TimeoutError is thrown, the decorated method will continue to run in a different thread. If you would also want this thread to be "stopped" see: Is there any way to kill a Thread in Python?
Using simple decorator
Here's the version I made after studying above answers. Pretty straight forward.
def function_timeout(seconds: int):
"""Wrapper of Decorator to pass arguments"""
def decorator(func):
#contextmanager
def time_limit(seconds_):
def signal_handler(signum, frame): # noqa
raise TimeoutException(f"Timed out in {seconds_} seconds!")
signal.signal(signal.SIGALRM, signal_handler)
signal.alarm(seconds_)
try:
yield
finally:
signal.alarm(0)
#wraps(func)
def wrapper(*args, **kwargs):
with time_limit(seconds):
return func(*args, **kwargs)
return wrapper
return decorator
How to use?
#function_timeout(seconds=5)
def my_naughty_function():
while True:
print("Try to stop me ;-p")
Well of course, don't forget to import the function if it is in a separate file.
Here's a timeout function I think I found via google and it works for me.
From:
http://code.activestate.com/recipes/473878/
def timeout(func, args=(), kwargs={}, timeout_duration=1, default=None):
'''This function will spwan a thread and run the given function using the args, kwargs and
return the given default value if the timeout_duration is exceeded
'''
import threading
class InterruptableThread(threading.Thread):
def __init__(self):
threading.Thread.__init__(self)
self.result = default
def run(self):
try:
self.result = func(*args, **kwargs)
except:
self.result = default
it = InterruptableThread()
it.start()
it.join(timeout_duration)
if it.isAlive():
return it.result
else:
return it.result
The method from #user2283347 is tested working, but we want to get rid of the traceback messages. Use pass trick from Remove traceback in Python on Ctrl-C, the modified code is:
from contextlib import contextmanager
import threading
import _thread
class TimeoutException(Exception): pass
#contextmanager
def time_limit(seconds):
timer = threading.Timer(seconds, lambda: _thread.interrupt_main())
timer.start()
try:
yield
except KeyboardInterrupt:
pass
finally:
# if the action ends in specified time, timer is canceled
timer.cancel()
def timeout_svm_score(i):
#from sklearn import svm
#import numpy as np
#from IPython.core.display import display
#%store -r names X Y
clf = svm.SVC(kernel='linear', C=1).fit(np.nan_to_num(X[[names[i]]]), Y)
score = clf.score(np.nan_to_num(X[[names[i]]]),Y)
#scoressvm.append((score, names[i]))
display((score, names[i]))
%%time
with time_limit(5):
i=0
timeout_svm_score(i)
#Wall time: 14.2 s
%%time
with time_limit(20):
i=0
timeout_svm_score(i)
#(0.04541284403669725, '计划飞行时间')
#Wall time: 16.1 s
%%time
with time_limit(5):
i=14
timeout_svm_score(i)
#Wall time: 5h 43min 41s
We can see that this method may need far long time to interrupt the calculation, we asked for 5 seconds, but it work out in 5 hours.
This code works for Windows Server Datacenter 2016 with python 3.7.3 and I didn't tested on Unix, after mixing some answers from Google and StackOverflow, it finally worked for me like this:
from multiprocessing import Process, Lock
import time
import os
def f(lock,id,sleepTime):
lock.acquire()
print("I'm P"+str(id)+" Process ID: "+str(os.getpid()))
lock.release()
time.sleep(sleepTime) #sleeps for some time
print("Process: "+str(id)+" took this much time:"+str(sleepTime))
time.sleep(sleepTime)
print("Process: "+str(id)+" took this much time:"+str(sleepTime*2))
if __name__ == '__main__':
timeout_function=float(9) # 9 seconds for max function time
print("Main Process ID: "+str(os.getpid()))
lock=Lock()
p1=Process(target=f, args=(lock,1,6,)) #Here you can change from 6 to 3 for instance, so you can watch the behavior
start=time.time()
print(type(start))
p1.start()
if p1.is_alive():
print("process running a")
else:
print("process not running a")
while p1.is_alive():
timeout=time.time()
if timeout-start > timeout_function:
p1.terminate()
print("process terminated")
print("watching, time passed: "+str(timeout-start) )
time.sleep(1)
if p1.is_alive():
print("process running b")
else:
print("process not running b")
p1.join()
if p1.is_alive():
print("process running c")
else:
print("process not running c")
end=time.time()
print("I am the main process, the two processes are done")
print("Time taken:- "+str(end-start)+" secs") #MainProcess terminates at approx ~ 5 secs.
time.sleep(5) # To see if on Task Manager the child process is really being terminated, and it is
print("finishing")
The main code is from this link:
Create two child process using python(windows)
Then I used .terminate() to kill the child process. You can see that the function f calls 2 prints, one after 5 seconds and another after 10 seconds. However, with a 7 seconds sleep and the terminate(), it does not show the last print.
It worked for me, hope it helps!