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!
Is it possible to terminate a running thread without setting/checking any flags/semaphores/etc.?
It is generally a bad pattern to kill a thread abruptly, in Python, and in any language. Think of the following cases:
the thread is holding a critical resource that must be closed properly
the thread has created several other threads that must be killed as well.
The nice way of handling this, if you can afford it (if you are managing your own threads), is to have an exit_request flag that each thread checks on a regular interval to see if it is time for it to exit.
For example:
import threading
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_event = threading.Event()
def stop(self):
self._stop_event.set()
def stopped(self):
return self._stop_event.is_set()
In this code, you should call stop() on the thread when you want it to exit, and wait for the thread to exit properly using join(). The thread should check the stop flag at regular intervals.
There are cases, however, when you really need to kill a thread. An example is when you are wrapping an external library that is busy for long calls, and you want to interrupt it.
The following code allows (with some restrictions) to raise an Exception in a Python thread:
def _async_raise(tid, exctype):
'''Raises an exception in the threads with id tid'''
if not inspect.isclass(exctype):
raise TypeError("Only types can be raised (not instances)")
res = ctypes.pythonapi.PyThreadState_SetAsyncExc(ctypes.c_long(tid),
ctypes.py_object(exctype))
if res == 0:
raise ValueError("invalid thread id")
elif res != 1:
# "if it returns a number greater than one, you're in trouble,
# and you should call it again with exc=NULL to revert the effect"
ctypes.pythonapi.PyThreadState_SetAsyncExc(ctypes.c_long(tid), None)
raise SystemError("PyThreadState_SetAsyncExc failed")
class ThreadWithExc(threading.Thread):
'''A thread class that supports raising an exception in the thread from
another thread.
'''
def _get_my_tid(self):
"""determines this (self's) thread id
CAREFUL: this function is executed in the context of the caller
thread, to get the identity of the thread represented by this
instance.
"""
if not self.isAlive():
raise threading.ThreadError("the thread is not active")
# do we have it cached?
if hasattr(self, "_thread_id"):
return self._thread_id
# no, look for it in the _active dict
for tid, tobj in threading._active.items():
if tobj is self:
self._thread_id = tid
return tid
# TODO: in python 2.6, there's a simpler way to do: self.ident
raise AssertionError("could not determine the thread's id")
def raiseExc(self, exctype):
"""Raises the given exception type in the context of this thread.
If the thread is busy in a system call (time.sleep(),
socket.accept(), ...), the exception is simply ignored.
If you are sure that your exception should terminate the thread,
one way to ensure that it works is:
t = ThreadWithExc( ... )
...
t.raiseExc( SomeException )
while t.isAlive():
time.sleep( 0.1 )
t.raiseExc( SomeException )
If the exception is to be caught by the thread, you need a way to
check that your thread has caught it.
CAREFUL: this function is executed in the context of the
caller thread, to raise an exception in the context of the
thread represented by this instance.
"""
_async_raise( self._get_my_tid(), exctype )
(Based on Killable Threads by Tomer Filiba. The quote about the return value of PyThreadState_SetAsyncExc appears to be from an old version of Python.)
As noted in the documentation, this is not a magic bullet because if the thread is busy outside the Python interpreter, it will not catch the interruption.
A good usage pattern of this code is to have the thread catch a specific exception and perform the cleanup. That way, you can interrupt a task and still have proper cleanup.
A multiprocessing.Process can p.terminate()
In the cases where I want to kill a thread, but do not want to use flags/locks/signals/semaphores/events/whatever, I promote the threads to full blown processes. For code that makes use of just a few threads the overhead is not that bad.
E.g. this comes in handy to easily terminate helper "threads" which execute blocking I/O
The conversion is trivial: In related code replace all threading.Thread with multiprocessing.Process and all queue.Queue with multiprocessing.Queue and add the required calls of p.terminate() to your parent process which wants to kill its child p
See the Python documentation for multiprocessing.
Example:
import multiprocessing
proc = multiprocessing.Process(target=your_proc_function, args=())
proc.start()
# Terminate the process
proc.terminate() # sends a SIGTERM
There is no official API to do that, no.
You need to use platform API to kill the thread, e.g. pthread_kill, or TerminateThread. You can access such API e.g. through pythonwin, or through ctypes.
Notice that this is inherently unsafe. It will likely lead to uncollectable garbage (from local variables of the stack frames that become garbage), and may lead to deadlocks, if the thread being killed has the GIL at the point when it is killed.
If you are trying to terminate the whole program you can set the thread as a "daemon". see
Thread.daemon
As others have mentioned, the norm is to set a stop flag. For something lightweight (no subclassing of Thread, no global variable), a lambda callback is an option. (Note the parentheses in if stop().)
import threading
import time
def do_work(id, stop):
print("I am thread", id)
while True:
print("I am thread {} doing something".format(id))
if stop():
print(" Exiting loop.")
break
print("Thread {}, signing off".format(id))
def main():
stop_threads = False
workers = []
for id in range(0,3):
tmp = threading.Thread(target=do_work, args=(id, lambda: stop_threads))
workers.append(tmp)
tmp.start()
time.sleep(3)
print('main: done sleeping; time to stop the threads.')
stop_threads = True
for worker in workers:
worker.join()
print('Finis.')
if __name__ == '__main__':
main()
Replacing print() with a pr() function that always flushes (sys.stdout.flush()) may improve the precision of the shell output.
(Only tested on Windows/Eclipse/Python3.3)
In Python, you simply cannot kill a Thread directly.
If you do NOT really need to have a Thread (!), what you can do, instead of using the threading package , is to use the
multiprocessing package . Here, to kill a process, you can simply call the method:
yourProcess.terminate() # kill the process!
Python will kill your process (on Unix through the SIGTERM signal, while on Windows through the TerminateProcess() call). Pay attention to use it while using a Queue or a Pipe! (it may corrupt the data in the Queue/Pipe)
Note that the multiprocessing.Event and the multiprocessing.Semaphore work exactly in the same way of the threading.Event and the threading.Semaphore respectively. In fact, the first ones are clones of the latters.
If you REALLY need to use a Thread, there is no way to kill it directly. What you can do, however, is to use a "daemon thread". In fact, in Python, a Thread can be flagged as daemon:
yourThread.daemon = True # set the Thread as a "daemon thread"
The main program will exit when no alive non-daemon threads are left. In other words, when your main thread (which is, of course, a non-daemon thread) will finish its operations, the program will exit even if there are still some daemon threads working.
Note that it is necessary to set a Thread as daemon before the start() method is called!
Of course you can, and should, use daemon even with multiprocessing. Here, when the main process exits, it attempts to terminate all of its daemonic child processes.
Finally, please, note that sys.exit() and os.kill() are not choices.
This is based on the thread2 -- killable threads ActiveState recipe.
You need to call PyThreadState_SetAsyncExc(), which is only available through the ctypes module.
This has only been tested on Python 2.7.3, but it is likely to work with other recent 2.x releases. PyThreadState_SetAsyncExc() still exists in Python 3 for backwards compatibility (but I have not tested it).
import ctypes
def terminate_thread(thread):
"""Terminates a python thread from another thread.
:param thread: a threading.Thread instance
"""
if not thread.isAlive():
return
exc = ctypes.py_object(SystemExit)
res = ctypes.pythonapi.PyThreadState_SetAsyncExc(
ctypes.c_long(thread.ident), exc)
if res == 0:
raise ValueError("nonexistent thread id")
elif res > 1:
# """if it returns a number greater than one, you're in trouble,
# and you should call it again with exc=NULL to revert the effect"""
ctypes.pythonapi.PyThreadState_SetAsyncExc(thread.ident, None)
raise SystemError("PyThreadState_SetAsyncExc failed")
You should never forcibly kill a thread without cooperating with it.
Killing a thread removes any guarantees that try/finally blocks set up so you might leave locks locked, files open, etc.
The only time you can argue that forcibly killing threads is a good idea is to kill a program fast, but never single threads.
If you are explicitly calling time.sleep() as part of your thread (say polling some external service), an improvement upon Phillipe's method is to use the timeout in the event's wait() method wherever you sleep()
For example:
import threading
class KillableThread(threading.Thread):
def __init__(self, sleep_interval=1):
super().__init__()
self._kill = threading.Event()
self._interval = sleep_interval
def run(self):
while True:
print("Do Something")
# If no kill signal is set, sleep for the interval,
# If kill signal comes in while sleeping, immediately
# wake up and handle
is_killed = self._kill.wait(self._interval)
if is_killed:
break
print("Killing Thread")
def kill(self):
self._kill.set()
Then to run it
t = KillableThread(sleep_interval=5)
t.start()
# Every 5 seconds it prints:
#: Do Something
t.kill()
#: Killing Thread
The advantage of using wait() instead of sleep()ing and regularly checking the event is that you can program in longer intervals of sleep, the thread is stopped almost immediately (when you would otherwise be sleep()ing) and in my opinion, the code for handling exit is significantly simpler.
You can kill a thread by installing trace into the thread that will exit the thread. See attached link for one possible implementation.
Kill a thread in Python
It is better if you don't kill a thread.
A way could be to introduce a "try" block into the thread's cycle and to throw an exception when you want to stop the thread (for example a break/return/... that stops your for/while/...).
I've used this on my app and it works...
It is definitely possible to implement a Thread.stop method as shown in the following example code:
import sys
import threading
import time
class StopThread(StopIteration):
pass
threading.SystemExit = SystemExit, StopThread
class Thread2(threading.Thread):
def stop(self):
self.__stop = True
def _bootstrap(self):
if threading._trace_hook is not None:
raise ValueError('Cannot run thread with tracing!')
self.__stop = False
sys.settrace(self.__trace)
super()._bootstrap()
def __trace(self, frame, event, arg):
if self.__stop:
raise StopThread()
return self.__trace
class Thread3(threading.Thread):
def _bootstrap(self, stop_thread=False):
def stop():
nonlocal stop_thread
stop_thread = True
self.stop = stop
def tracer(*_):
if stop_thread:
raise StopThread()
return tracer
sys.settrace(tracer)
super()._bootstrap()
###############################################################################
def main():
test1 = Thread2(target=printer)
test1.start()
time.sleep(1)
test1.stop()
test1.join()
test2 = Thread2(target=speed_test)
test2.start()
time.sleep(1)
test2.stop()
test2.join()
test3 = Thread3(target=speed_test)
test3.start()
time.sleep(1)
test3.stop()
test3.join()
def printer():
while True:
print(time.time() % 1)
time.sleep(0.1)
def speed_test(count=0):
try:
while True:
count += 1
except StopThread:
print('Count =', count)
if __name__ == '__main__':
main()
The Thread3 class appears to run code approximately 33% faster than the Thread2 class.
I'm way late to this game, but I've been wrestling with a similar question and the following appears to both resolve the issue perfectly for me AND lets me do some basic thread state checking and cleanup when the daemonized sub-thread exits:
import threading
import time
import atexit
def do_work():
i = 0
#atexit.register
def goodbye():
print ("'CLEANLY' kill sub-thread with value: %s [THREAD: %s]" %
(i, threading.currentThread().ident))
while True:
print i
i += 1
time.sleep(1)
t = threading.Thread(target=do_work)
t.daemon = True
t.start()
def after_timeout():
print "KILL MAIN THREAD: %s" % threading.currentThread().ident
raise SystemExit
threading.Timer(2, after_timeout).start()
Yields:
0
1
KILL MAIN THREAD: 140013208254208
'CLEANLY' kill sub-thread with value: 2 [THREAD: 140013674317568]
from ctypes import *
pthread = cdll.LoadLibrary("libpthread-2.15.so")
pthread.pthread_cancel(c_ulong(t.ident))
t is your Thread object.
Read the python source (Modules/threadmodule.c and Python/thread_pthread.h) you can see the Thread.ident is an pthread_t type, so you can do anything pthread can do in python use libpthread.
Following workaround can be used to kill a thread:
kill_threads = False
def doSomething():
global kill_threads
while True:
if kill_threads:
thread.exit()
......
......
thread.start_new_thread(doSomething, ())
This can be used even for terminating threads, whose code is written in another module, from main thread. We can declare a global variable in that module and use it to terminate thread/s spawned in that module.
I usually use this to terminate all the threads at the program exit. This might not be the perfect way to terminate thread/s but could help.
Here's yet another way to do it, but with extremely clean and simple code, that works in Python 3.7 in 2021:
import ctypes
def kill_thread(thread):
"""
thread: a threading.Thread object
"""
thread_id = thread.ident
res = ctypes.pythonapi.PyThreadState_SetAsyncExc(thread_id, ctypes.py_object(SystemExit))
if res > 1:
ctypes.pythonapi.PyThreadState_SetAsyncExc(thread_id, 0)
print('Exception raise failure')
Adapted from here: https://www.geeksforgeeks.org/python-different-ways-to-kill-a-thread/
One thing I want to add is that if you read official documentation in threading lib Python, it's recommended to avoid use of "demonic" threads, when you don't want threads end abruptly, with the flag that Paolo Rovelli mentioned.
From official documentation:
Daemon threads are abruptly stopped at shutdown. Their resources (such as open files, database transactions, etc.) may not be released properly. If you want your threads to stop gracefully, make them non-daemonic and use a suitable signaling mechanism such as an Event.
I think that creating daemonic threads depends of your application, but in general (and in my opinion) it's better to avoid killing them or making them daemonic. In multiprocessing you can use is_alive() to check process status and "terminate" for finish them (Also you avoid GIL problems). But you can find more problems, sometimes, when you execute your code in Windows.
And always remember that if you have "live threads", the Python interpreter will be running for wait them. (Because of this daemonic can help you if don't matter abruptly ends).
There is a library built for this purpose, stopit. Although some of the same cautions listed herein still apply, at least this library presents a regular, repeatable technique for achieving the stated goal.
While it's rather old, this might be a handy solution for some:
A little module that extends the threading's module functionality --
allows one thread to raise exceptions in the context of another
thread. By raising SystemExit, you can finally kill python threads.
import threading
import ctypes
def _async_raise(tid, excobj):
res = ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, ctypes.py_object(excobj))
if res == 0:
raise ValueError("nonexistent thread id")
elif res > 1:
# """if it returns a number greater than one, you're in trouble,
# and you should call it again with exc=NULL to revert the effect"""
ctypes.pythonapi.PyThreadState_SetAsyncExc(tid, 0)
raise SystemError("PyThreadState_SetAsyncExc failed")
class Thread(threading.Thread):
def raise_exc(self, excobj):
assert self.isAlive(), "thread must be started"
for tid, tobj in threading._active.items():
if tobj is self:
_async_raise(tid, excobj)
return
# the thread was alive when we entered the loop, but was not found
# in the dict, hence it must have been already terminated. should we raise
# an exception here? silently ignore?
def terminate(self):
# must raise the SystemExit type, instead of a SystemExit() instance
# due to a bug in PyThreadState_SetAsyncExc
self.raise_exc(SystemExit)
So, it allows a "thread to raise exceptions in the context of another thread" and in this way, the terminated thread can handle the termination without regularly checking an abort flag.
However, according to its original source, there are some issues with this code.
The exception will be raised only when executing python bytecode. If your thread calls a native/built-in blocking function, the
exception will be raised only when execution returns to the python
code.
There is also an issue if the built-in function internally calls PyErr_Clear(), which would effectively cancel your pending exception.
You can try to raise it again.
Only exception types can be raised safely. Exception instances are likely to cause unexpected behavior, and are thus restricted.
For example: t1.raise_exc(TypeError) and not t1.raise_exc(TypeError("blah")).
IMHO it's a bug, and I reported it as one. For more info, http://mail.python.org/pipermail/python-dev/2006-August/068158.html
I asked to expose this function in the built-in thread module, but since ctypes has become a standard library (as of 2.5), and this
feature is not likely to be implementation-agnostic, it may be kept
unexposed.
Asuming, that you want to have multiple threads of the same function, this is IMHO the easiest implementation to stop one by id:
import time
from threading import Thread
def doit(id=0):
doit.stop=0
print("start id:%d"%id)
while 1:
time.sleep(1)
print(".")
if doit.stop==id:
doit.stop=0
break
print("end thread %d"%id)
t5=Thread(target=doit, args=(5,))
t6=Thread(target=doit, args=(6,))
t5.start() ; t6.start()
time.sleep(2)
doit.stop =5 #kill t5
time.sleep(2)
doit.stop =6 #kill t6
The nice thing is here, you can have multiple of same and different functions, and stop them all by functionname.stop
If you want to have only one thread of the function then you don't need to remember the id. Just stop, if doit.stop > 0.
Just to build up on #SCB's idea (which was exactly what I needed) to create a KillableThread subclass with a customized function:
from threading import Thread, Event
class KillableThread(Thread):
def __init__(self, sleep_interval=1, target=None, name=None, args=(), kwargs={}):
super().__init__(None, target, name, args, kwargs)
self._kill = Event()
self._interval = sleep_interval
print(self._target)
def run(self):
while True:
# Call custom function with arguments
self._target(*self._args)
# If no kill signal is set, sleep for the interval,
# If kill signal comes in while sleeping, immediately
# wake up and handle
is_killed = self._kill.wait(self._interval)
if is_killed:
break
print("Killing Thread")
def kill(self):
self._kill.set()
if __name__ == '__main__':
def print_msg(msg):
print(msg)
t = KillableThread(10, print_msg, args=("hello world"))
t.start()
time.sleep(6)
print("About to kill thread")
t.kill()
Naturally, like with #SBC, the thread doesn't wait to run a new loop to stop. In this example, you would see the "Killing Thread" message printed right after the "About to kill thread" instead of waiting for 4 more seconds for the thread to complete (since we have slept for 6 seconds already).
Second argument in KillableThread constructor is your custom function (print_msg here). Args argument are the arguments that will be used when calling the function (("hello world")) here.
Python version: 3.8
Using daemon thread to execute what we wanted, if we want to daemon thread be terminated, all we need is making parent thread exit, then system will terminate daemon thread which parent thread created.
Also support coroutine and coroutine function.
def main():
start_time = time.perf_counter()
t1 = ExitThread(time.sleep, (10,), debug=False)
t1.start()
time.sleep(0.5)
t1.exit()
try:
print(t1.result_future.result())
except concurrent.futures.CancelledError:
pass
end_time = time.perf_counter()
print(f"time cost {end_time - start_time:0.2f}")
below is ExitThread source code
import concurrent.futures
import threading
import typing
import asyncio
class _WorkItem(object):
""" concurrent\futures\thread.py
"""
def __init__(self, future, fn, args, kwargs, *, debug=None):
self._debug = debug
self.future = future
self.fn = fn
self.args = args
self.kwargs = kwargs
def run(self):
if self._debug:
print("ExitThread._WorkItem run")
if not self.future.set_running_or_notify_cancel():
return
try:
coroutine = None
if asyncio.iscoroutinefunction(self.fn):
coroutine = self.fn(*self.args, **self.kwargs)
elif asyncio.iscoroutine(self.fn):
coroutine = self.fn
if coroutine is None:
result = self.fn(*self.args, **self.kwargs)
else:
result = asyncio.run(coroutine)
if self._debug:
print("_WorkItem done")
except BaseException as exc:
self.future.set_exception(exc)
# Break a reference cycle with the exception 'exc'
self = None
else:
self.future.set_result(result)
class ExitThread:
""" Like a stoppable thread
Using coroutine for target then exit before running may cause RuntimeWarning.
"""
def __init__(self, target: typing.Union[typing.Coroutine, typing.Callable] = None
, args=(), kwargs={}, *, daemon=None, debug=None):
#
self._debug = debug
self._parent_thread = threading.Thread(target=self._parent_thread_run, name="ExitThread_parent_thread"
, daemon=daemon)
self._child_daemon_thread = None
self.result_future = concurrent.futures.Future()
self._workItem = _WorkItem(self.result_future, target, args, kwargs, debug=debug)
self._parent_thread_exit_lock = threading.Lock()
self._parent_thread_exit_lock.acquire()
self._parent_thread_exit_lock_released = False # When done it will be True
self._started = False
self._exited = False
self.result_future.add_done_callback(self._release_parent_thread_exit_lock)
def _parent_thread_run(self):
self._child_daemon_thread = threading.Thread(target=self._child_daemon_thread_run
, name="ExitThread_child_daemon_thread"
, daemon=True)
self._child_daemon_thread.start()
# Block manager thread
self._parent_thread_exit_lock.acquire()
self._parent_thread_exit_lock.release()
if self._debug:
print("ExitThread._parent_thread_run exit")
def _release_parent_thread_exit_lock(self, _future):
if self._debug:
print(f"ExitThread._release_parent_thread_exit_lock {self._parent_thread_exit_lock_released} {_future}")
if not self._parent_thread_exit_lock_released:
self._parent_thread_exit_lock_released = True
self._parent_thread_exit_lock.release()
def _child_daemon_thread_run(self):
self._workItem.run()
def start(self):
if self._debug:
print(f"ExitThread.start {self._started}")
if not self._started:
self._started = True
self._parent_thread.start()
def exit(self):
if self._debug:
print(f"ExitThread.exit exited: {self._exited} lock_released: {self._parent_thread_exit_lock_released}")
if self._parent_thread_exit_lock_released:
return
if not self._exited:
self._exited = True
if not self.result_future.cancel():
if self.result_future.running():
self.result_future.set_exception(concurrent.futures.CancelledError())
As mentioned in #Kozyarchuk's answer, installing trace works. Since this answer contained no code, here is a working ready-to-use example:
import sys, threading, time
class TraceThread(threading.Thread):
def __init__(self, *args, **keywords):
threading.Thread.__init__(self, *args, **keywords)
self.killed = False
def start(self):
self._run = self.run
self.run = self.settrace_and_run
threading.Thread.start(self)
def settrace_and_run(self):
sys.settrace(self.globaltrace)
self._run()
def globaltrace(self, frame, event, arg):
return self.localtrace if event == 'call' else None
def localtrace(self, frame, event, arg):
if self.killed and event == 'line':
raise SystemExit()
return self.localtrace
def f():
while True:
print('1')
time.sleep(2)
print('2')
time.sleep(2)
print('3')
time.sleep(2)
t = TraceThread(target=f)
t.start()
time.sleep(2.5)
t.killed = True
It stops after having printed 1 and 2. 3 is not printed.
An alternative is to use signal.pthread_kill to send a stop signal.
from signal import pthread_kill, SIGTSTP
from threading import Thread
from itertools import count
from time import sleep
def target():
for num in count():
print(num)
sleep(1)
thread = Thread(target=target)
thread.start()
sleep(5)
pthread_kill(thread.ident, SIGTSTP)
result
0
1
2
3
4
[14]+ Stopped
Pieter Hintjens -- one of the founders of the ØMQ-project -- says, using ØMQ and avoiding synchronization primitives like locks, mutexes, events etc., is the sanest and securest way to write multi-threaded programs:
http://zguide.zeromq.org/py:all#Multithreading-with-ZeroMQ
This includes telling a child thread, that it should cancel its work. This would be done by equipping the thread with a ØMQ-socket and polling on that socket for a message saying that it should cancel.
The link also provides an example on multi-threaded python code with ØMQ.
This seems to work with pywin32 on windows 7
my_thread = threading.Thread()
my_thread.start()
my_thread._Thread__stop()
If you really need the ability to kill a sub-task, use an alternate implementation. multiprocessing and gevent both support indiscriminately killing a "thread".
Python's threading does not support cancellation. Do not even try. Your code is very likely to deadlock, corrupt or leak memory, or have other unintended "interesting" hard-to-debug effects which happen rarely and nondeterministically.
You can execute your command in a process and then kill it using the process id.
I needed to sync between two thread one of which doesn’t return by itself.
processIds = []
def executeRecord(command):
print(command)
process = subprocess.Popen(command, stdout=subprocess.PIPE)
processIds.append(process.pid)
print(processIds[0])
#Command that doesn't return by itself
process.stdout.read().decode("utf-8")
return;
def recordThread(command, timeOut):
thread = Thread(target=executeRecord, args=(command,))
thread.start()
thread.join(timeOut)
os.kill(processIds.pop(), signal.SIGINT)
return;
The most simple way is this:
from threading import Thread
from time import sleep
def do_something():
global thread_work
while thread_work:
print('doing something')
sleep(5)
print('Thread stopped')
thread_work = True
Thread(target=do_something).start()
sleep(5)
thread_work = False
This is a bad answer, see the comments
Here's how to do it:
from threading import *
...
for thread in enumerate():
if thread.isAlive():
try:
thread._Thread__stop()
except:
print(str(thread.getName()) + ' could not be terminated'))
Give it a few seconds then your thread should be stopped. Check also the thread._Thread__delete() method.
I'd recommend a thread.quit() method for convenience. For example if you have a socket in your thread, I'd recommend creating a quit() method in your socket-handle class, terminate the socket, then run a thread._Thread__stop() inside of your quit().
I have timeout context manager that works perfectly with signals but it raises error in multithread mode because signals work only in main thread.
def timeout_handler(signum, frame):
raise TimeoutException()
#contextmanager
def timeout(seconds):
old_handler = signal.signal(signal.SIGALRM, timeout_handler)
signal.alarm(seconds)
try:
yield
finally:
signal.alarm(0)
signal.signal(signal.SIGALRM, old_handler)
I've seen decorator implementation of timeout but I don't know how to pass yield inside class derived from threading.Thread. My variant won't work.
#contextmanager
def timelimit(seconds):
class FuncThread(threading.Thread):
def run(self):
yield
it = FuncThread()
it.start()
it.join(seconds)
if it.isAlive():
raise TimeoutException()
If the code guarded by the context manager is loop-based, consider handling this the way people handle thread killing. Killing another thread is generally unsafe, so the standard approach is to have the controlling thread set a flag that's visible to the worker thread. The worker thread periodically checks that flag and cleanly shuts itself down. Here's how you can do something analogous with timeouts:
class timeout(object):
def __init__(self, seconds):
self.seconds = seconds
def __enter__(self):
self.die_after = time.time() + self.seconds
return self
def __exit__(self, type, value, traceback):
pass
#property
def timed_out(self):
return time.time() > self.die_after
Here's a single-threaded usage example:
with timeout(1) as t:
while True: # this will take a long time without a timeout
# periodically check for timeouts
if t.timed_out:
break # or raise an exception
# do some "useful" work
print "."
time.sleep(0.2)
and a multithreaded one:
import thread
def print_for_n_secs(string, seconds):
with timeout(seconds) as t:
while True:
if t.timed_out:
break # or raise an exception
print string,
time.sleep(0.5)
for i in xrange(5):
thread.start_new_thread(print_for_n_secs,
('thread%d' % (i,), 2))
time.sleep(0.25)
This approach is more intrusive than using signals but it works for arbitrary threads.
I cannot see a way of doing what you are proposing with a context manager, you cannot yield the flow from one thread to another.
What I would do is wrap your function with an interrutable thread with the timeout. Here is a recipe for that.
You will have an extra thread and the syntax won't be as nice but it would work.
I know it's late but I'm only just reading this, but what about creating your own signaller/context manager? I'm new to python would love feedback from experienced devs this implementation.
This is based off of the answer from "Mr Fooz"
class TimeoutSignaller(Thread):
def __init__(self, limit, handler):
Thread.__init__(self)
self.limit = limit
self.running = True
self.handler = handler
assert callable(handler), "Timeout Handler needs to be a method"
def run(self):
timeout_limit = datetime.datetime.now() + datetime.timedelta(seconds=self.limit)
while self.running:
if datetime.datetime.now() >= timeout_limit:
self.handler()
self.stop_run()
break
def stop_run(self):
self.running = False
class ProcessContextManager:
def __init__(self, process, seconds=0, minutes=0, hours=0):
self.seconds = (hours * 3600) + (minutes * 60) + seconds
self.process = process
self.signal = TimeoutSignaller(self.seconds, self.signal_handler)
def __enter__(self):
self.signal.start()
return self.process
def __exit__(self, exc_type, exc_val, exc_tb):
self.signal.stop_run()
def signal_handler(self):
# Make process terminate however you like
# using self.process reference
raise TimeoutError("Process took too long to execute")
Use case:
with ProcessContextManager(my_proc) as p:
# do stuff e.g.
p.execute()
Similar implementation as Mr Fooz but using the contextlib library:
import time
from contextlib import contextmanager
#contextmanager
def timeout(seconds):
"""
A simple context manager to enable timeouts.
Example:
with timeout(5) as t:
while True:
if t():
# handle
"""
stop = time.time() + seconds
def timed_out():
return time.time() > stop
yield timed_out
Timeouts for system calls are done with signals. Most blocking system calls return with EINTR when a signal happens, so you can use alarm to implement timeouts.
Here's a context manager that works with most system calls, causing IOError to be raised from a blocking system call if it takes too long.
import signal, errno
from contextlib import contextmanager
import fcntl
#contextmanager
def timeout(seconds):
def timeout_handler(signum, frame):
pass
original_handler = signal.signal(signal.SIGALRM, timeout_handler)
try:
signal.alarm(seconds)
yield
finally:
signal.alarm(0)
signal.signal(signal.SIGALRM, original_handler)
with timeout(1):
f = open("test.lck", "w")
try:
fcntl.flock(f.fileno(), fcntl.LOCK_EX)
except IOError, e:
if e.errno != errno.EINTR:
raise e
print "Lock timed out"