I need to pause and resume thread, which continuously executes some task. Execution begins when start() is called, it should not be interrupted and must continue from the point when pause() is called.
How can I do this?
Please remember that using threads in Python will not grant you a parallel processing, except for the case of IO blocking operations. For more information on this, take a look at this and this
You cannot pause a Thread arbitrarily in Python (please keep that in mind before reading further). I am neither sure you have a way to do that at an OS level (e.g. by using pure-C). What you can do is allow the thread to be paused at specific points you consider beforehand. I will give you an example:
class MyThread(threading.Thread):
def __init__(self, *args, **kwargs):
super(MyThread, self).__init__(*args, **kwargs)
self._event = threading.Event()
def run(self):
while True:
self.foo() # please, implement this.
self._event.wait()
self.bar() # please, implement this.
self._event.wait()
self.baz() # please, implement this.
self._event.wait()
def pause(self):
self._event.clear()
def resume(self):
self._event.set()
This approach will work but:
Threading is usually a bad idea, based on the links I gave you.
You have to code the run method by yourself, with this approach. This is because you need to have control over the exact points you'd like to check for pause, and this implies accessing the Thread object (perhaps you'd like to create an additional method instead of calling self._event.wait()).
The former point makes clear that you cannot pause arbitrarily, but just when you specified you could pause. Avoid having long operations between pause points.
Edit I did not test this one, but perhaps this will work without so much subclassing if you need more than one thread like this:
class MyPausableThread(threading.Thread):
def __init__(self, group=None, target=None, name=None, args=(), kwargs={}):
self._event = threading.Event()
if target:
args = (self,) + args
super(MyPausableThread, self).__init__(group, target, name, args, kwargs)
def pause(self):
self._event.clear()
def resume(self):
self._event.set()
def _wait_if_paused(self):
self._event.wait()
This should allow you to create a custom thread without more subclassing, by calling MyPausableThread(target=myfunc).start(), and your callable's first parameter will receive the thread object, from which you can call self._wait_if_paused() when you need to pause-check.
Or even better, if you want to isolate the target from accessing the thread object:
class MyPausableThread(threading.Thread):
def __init__(self, group=None, target=None, name=None, args=(), kwargs={}):
self._event = threading.Event()
if target:
args = ((lambda: self._event.wait()),) + args
super(MyPausableThread, self).__init__(group, target, name, args, kwargs)
def pause(self):
self._event.clear()
def resume(self):
self._event.set()
And your target callable will receive in the first parameter a function that can be called like this: pause_checker() (provided the first param in the target callable is named pause_checker).
You can do this by attaching a trace function that causes all other threads to wait for a signal:
import sys
import threading
import contextlib
# needed to enable tracing
if not sys.gettrace():
sys.settrace(lambda *args: None)
def _thread_frames(thread):
for thread_id, frame in sys._current_frames().items():
if thread_id == thread.ident:
break
else:
raise ValueError("No thread found")
# walk up to the root
while frame:
yield frame
frame = frame.f_back
#contextlib.contextmanager
def thread_paused(thread):
""" Context manager that pauses a thread for its duration """
# signal for the thread to wait on
e = threading.Event()
for frame in _thread_frames(thread):
# attach a new temporary trace handler that pauses the thread
def new(frame, event, arg, old = frame.f_trace):
e.wait()
# call the old one, to keep debuggers working
if old is not None:
return old(frame, event, arg)
frame.f_trace = new
try:
yield
finally:
# wake the other thread
e.set()
Which you can use as:
import time
def run_after_delay(func, delay):
""" Simple helper spawning a thread that runs a function in the future """
def wrapped():
time.sleep(delay)
func()
threading.Thread(target=wrapped).start()
main_thread = threading.current_thread()
def interrupt():
with thread_paused(main_thread):
print("interrupting")
time.sleep(2)
print("done")
run_after_delay(interrupt, 1)
start = time.time()
def actual_time(): return time.time() - start
print("{:.1f} == {:.1f}".format(0.0, actual_time()))
time.sleep(0.5)
print("{:.1f} == {:.1f}".format(0.5, actual_time()))
time.sleep(2)
print("{:.1f} != {:.1f}".format(2.5, actual_time()))
Giving
0.0 0.0
0.5 0.5
interrupting
done
2.5 3.0
Note how the interrupt causes the sleep on the main thread to wait longer
You can do this using Process class from psutil library.
Example:
>>> import psutil
>>> pid = 7012
>>> p = psutil.Process(pid)
>>> p.suspend()
>>> p.resume()
See this answer: https://stackoverflow.com/a/14053933
Edit: This method will suspend the whole process, not only one thread. ( I don't delete this answer, so others can know this method won't work.)
while(int(any) < 2000):
sleep(20)
print(waiting any...)
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!
I'm using the threading.Timer package to execute a method after x seconds. However, in some cases I want to execute this method earlier and cancel the timer (so it isn't called twice). How do I unit test this?
I want to know if the timer has stopped so that the method is not called anymore. I am now using the following code, unfortunately the is_alive still returns True
from threading import Timer
Class X():
def __init__(self, timeout):
self.timer = Timer(timeout, self.some_method)
self.timer.start()
def some_method(self):
# Do something
def other_method(self):
self.timer.cancel()
self.some_method()
import unittest
Class TestX(unittest.TestCase):
def test_cancel_timer(self):
x = X(1000)
x.other_method()
self.assertFalse(x.timer.is_alive())
Form the documentation the is_alive method returns True during the run operation;
Return whether the thread is alive.
This method returns True just before the run() method starts until just after the run() method terminates. The module function enumerate() returns a list of all alive threads.
The documentation on the cancel method says the following;
Stop the timer, and cancel the execution of the timer’s action. This will only work if the timer is still in its waiting stage.
Does this mean that the cancel method does not stop the run action? Or is is still in the grey area after the run method and returns True for that reason?
With timer.is_alive() you are just checking if the timer-thread itself is alive, so if you want to "check if timer.cancel() was called", you're testing for the wrong thing.
Does this mean that the cancel method does not stop the run action?
It does not stop the run()-function, right. timer.cancel() just sets a flag in an Event-object which gets checked by run. You can test if the flag is set with:
self.assertTrue(x.timer.finished.is_set())
Unfortunately, checking for cancellation is not enough to prevent repeated execution, since run can have already crossed the check like you can see in the source code:
# threading.py (Python 3.7.1):
class Timer(Thread):
"""Call a function after a specified number of seconds:
t = Timer(30.0, f, args=None, kwargs=None)
t.start()
t.cancel() # stop the timer's action if it's still waiting
"""
def __init__(self, interval, function, args=None, kwargs=None):
Thread.__init__(self)
self.interval = interval
self.function = function
self.args = args if args is not None else []
self.kwargs = kwargs if kwargs is not None else {}
self.finished = Event()
def cancel(self):
"""Stop the timer if it hasn't finished yet."""
self.finished.set()
def run(self):
self.finished.wait(self.interval)
if not self.finished.is_set():
self.function(*self.args, **self.kwargs)
self.finished.set()
Some more effort is needed to ensure unique execution. I've written up a possible solution to this in my answer here.
I want to know how python threading.Timer works.
In more detail, When i run a couple of threading.Timer, does it run separate thread for counting a time and running the handler ?
Or one thread manages and counts a couple of timer together ?
I am asking because my application need to schedule many event, But
If threading.Timer runs separate each thread for counting a timer, and i run many timers, it may affect performance so much.
So i am worry that if i have to implement a scheduler running only one thread if it has big effect in performance.
threading.Timer class is a subclass of threading.Thread and basically it just runs a separate thread in which it sleeps for the specified amount of time and runs the corresponding function.
It is definitely not an efficient way to schedule events. Better way is to do the scheduling in a single thread by using Queue.PriorityQueue in which you would put your events where "priority" actually means "next fire date". Similar to how cron works.
Or even better: use something that already exists, do not reinvent the wheel: Cron, Celery, whatever...
A very simplified example of making a scheduler via Queue.PriorityQueue:
import time
from Queue import PriorityQueue
class Task(object):
def __init__(self, fn, crontab):
# TODO: it should be possible to pass args, kwargs
# so that fn can be called with fn(*args, **kwargs)
self.fn = fn
self.crontab = crontab
def get_next_fire_date(self):
# TODO: evaluate next fire date based on self.crontab
pass
class Scheduler(object):
def __init__(self):
self.event_queue = PriorityQueue()
self.new_task = False
def schedule_task(self, fn, crontab):
# TODO: add scheduling language, crontab or something
task = Task(fn, crontab)
next_fire = task.get_next_fire_date()
if next_fire:
self.new_task = True
self.event_queue.put((next_fire, task))
def run(self):
self.new_task = False
# TODO: do we really want an infinite loop?
while True:
# TODO: actually we want .get() with timeout and to handle
# the case when the queue is empty
next_fire, task = self.event_queue.get()
# incremental sleep so that we can check
# if new tasks arrived in the meantime
sleep_for = int(next_fire - time.time())
for _ in xrange(sleep_for):
time.sleep(1)
if self.new_task:
self.new_task = False
self.event_queue.put((next_fire, task))
continue
# TODO: run in separate thread?
task.fn()
time.sleep(1)
next_fire = task.get_next_fire_date()
if next_fire:
event_queue.put((next_fire, task))
def test():
return 'hello world'
sch = Scheduler()
sch.schedule_task(test, '5 * * * *')
sch.schedule_task(test, '0 22 * * 1-5')
sch.schedule_task(test, '1 1 * * *')
sch.run()
It's just an idea. You would have to properly implement both Task and Scheduler classes, i.e. get_next_fire_date method plus some kind of scheduling language (crontab?) and error handling. I still strongly suggest to use one of the existing libraries.
From the CPython 2.7 source:
def Timer(*args, **kwargs):
"""Factory function to create a Timer object.
Timers call a function after a specified number of seconds:
t = Timer(30.0, f, args=[], kwargs={})
t.start()
t.cancel() # stop the timer's action if it's still waiting
"""
return _Timer(*args, **kwargs)
class _Timer(Thread):
"""Call a function after a specified number of seconds:
t = Timer(30.0, f, args=[], kwargs={})
t.start()
t.cancel() # stop the timer's action if it's still waiting
"""
def __init__(self, interval, function, args=[], kwargs={}):
Thread.__init__(self)
self.interval = interval
self.function = function
self.args = args
self.kwargs = kwargs
self.finished = Event()
def cancel(self):
"""Stop the timer if it hasn't finished yet"""
self.finished.set()
def run(self):
self.finished.wait(self.interval)
if not self.finished.is_set():
self.function(*self.args, **self.kwargs)
self.finished.set()
As said in another answer, it is a separate thread (since it subclasses Thread). The callback function when the timer runs out is called from the new thread.
What's the proper way to tell a looping thread to stop looping?
I have a fairly simple program that pings a specified host in a separate threading.Thread class. In this class it sleeps 60 seconds, the runs again until the application quits.
I'd like to implement a 'Stop' button in my wx.Frame to ask the looping thread to stop. It doesn't need to end the thread right away, it can just stop looping once it wakes up.
Here is my threading class (note: I haven't implemented looping yet, but it would likely fall under the run method in PingAssets)
class PingAssets(threading.Thread):
def __init__(self, threadNum, asset, window):
threading.Thread.__init__(self)
self.threadNum = threadNum
self.window = window
self.asset = asset
def run(self):
config = controller.getConfig()
fmt = config['timefmt']
start_time = datetime.now().strftime(fmt)
try:
if onlinecheck.check_status(self.asset):
status = "online"
else:
status = "offline"
except socket.gaierror:
status = "an invalid asset tag."
msg =("{}: {} is {}. \n".format(start_time, self.asset, status))
wx.CallAfter(self.window.Logger, msg)
And in my wxPyhton Frame I have this function called from a Start button:
def CheckAsset(self, asset):
self.count += 1
thread = PingAssets(self.count, asset, self)
self.threads.append(thread)
thread.start()
Threaded stoppable function
Instead of subclassing threading.Thread, one can modify the function to allow
stopping by a flag.
We need an object, accessible to running function, to which we set the flag to stop running.
We can use threading.currentThread() object.
import threading
import time
def doit(arg):
t = threading.currentThread()
while getattr(t, "do_run", True):
print ("working on %s" % arg)
time.sleep(1)
print("Stopping as you wish.")
def main():
t = threading.Thread(target=doit, args=("task",))
t.start()
time.sleep(5)
t.do_run = False
if __name__ == "__main__":
main()
The trick is, that the running thread can have attached additional properties. The solution builds
on assumptions:
the thread has a property "do_run" with default value True
driving parent process can assign to started thread the property "do_run" to False.
Running the code, we get following output:
$ python stopthread.py
working on task
working on task
working on task
working on task
working on task
Stopping as you wish.
Pill to kill - using Event
Other alternative is to use threading.Event as function argument. It is by
default False, but external process can "set it" (to True) and function can
learn about it using wait(timeout) function.
We can wait with zero timeout, but we can also use it as the sleeping timer (used below).
def doit(stop_event, arg):
while not stop_event.wait(1):
print ("working on %s" % arg)
print("Stopping as you wish.")
def main():
pill2kill = threading.Event()
t = threading.Thread(target=doit, args=(pill2kill, "task"))
t.start()
time.sleep(5)
pill2kill.set()
t.join()
Edit: I tried this in Python 3.6. stop_event.wait() blocks the event (and so the while loop) until release. It does not return a boolean value. Using stop_event.is_set() works instead.
Stopping multiple threads with one pill
Advantage of pill to kill is better seen, if we have to stop multiple threads
at once, as one pill will work for all.
The doit will not change at all, only the main handles the threads a bit differently.
def main():
pill2kill = threading.Event()
tasks = ["task ONE", "task TWO", "task THREE"]
def thread_gen(pill2kill, tasks):
for task in tasks:
t = threading.Thread(target=doit, args=(pill2kill, task))
yield t
threads = list(thread_gen(pill2kill, tasks))
for thread in threads:
thread.start()
time.sleep(5)
pill2kill.set()
for thread in threads:
thread.join()
This has been asked before on Stack. See the following links:
Is there any way to kill a Thread in Python?
Stopping a thread after a certain amount of time
Basically you just need to set up the thread with a stop function that sets a sentinel value that the thread will check. In your case, you'll have the something in your loop check the sentinel value to see if it's changed and if it has, the loop can break and the thread can die.
I read the other questions on Stack but I was still a little confused on communicating across classes. Here is how I approached it:
I use a list to hold all my threads in the __init__ method of my wxFrame class: self.threads = []
As recommended in How to stop a looping thread in Python? I use a signal in my thread class which is set to True when initializing the threading class.
class PingAssets(threading.Thread):
def __init__(self, threadNum, asset, window):
threading.Thread.__init__(self)
self.threadNum = threadNum
self.window = window
self.asset = asset
self.signal = True
def run(self):
while self.signal:
do_stuff()
sleep()
and I can stop these threads by iterating over my threads:
def OnStop(self, e):
for t in self.threads:
t.signal = False
I had a different approach. I've sub-classed a Thread class and in the constructor I've created an Event object. Then I've written custom join() method, which first sets this event and then calls a parent's version of itself.
Here is my class, I'm using for serial port communication in wxPython app:
import wx, threading, serial, Events, Queue
class PumpThread(threading.Thread):
def __init__ (self, port, queue, parent):
super(PumpThread, self).__init__()
self.port = port
self.queue = queue
self.parent = parent
self.serial = serial.Serial()
self.serial.port = self.port
self.serial.timeout = 0.5
self.serial.baudrate = 9600
self.serial.parity = 'N'
self.stopRequest = threading.Event()
def run (self):
try:
self.serial.open()
except Exception, ex:
print ("[ERROR]\tUnable to open port {}".format(self.port))
print ("[ERROR]\t{}\n\n{}".format(ex.message, ex.traceback))
self.stopRequest.set()
else:
print ("[INFO]\tListening port {}".format(self.port))
self.serial.write("FLOW?\r")
while not self.stopRequest.isSet():
msg = ''
if not self.queue.empty():
try:
command = self.queue.get()
self.serial.write(command)
except Queue.Empty:
continue
while self.serial.inWaiting():
char = self.serial.read(1)
if '\r' in char and len(msg) > 1:
char = ''
#~ print('[DATA]\t{}'.format(msg))
event = Events.PumpDataEvent(Events.SERIALRX, wx.ID_ANY, msg)
wx.PostEvent(self.parent, event)
msg = ''
break
msg += char
self.serial.close()
def join (self, timeout=None):
self.stopRequest.set()
super(PumpThread, self).join(timeout)
def SetPort (self, serial):
self.serial = serial
def Write (self, msg):
if self.serial.is_open:
self.queue.put(msg)
else:
print("[ERROR]\tPort {} is not open!".format(self.port))
def Stop(self):
if self.isAlive():
self.join()
The Queue is used for sending messages to the port and main loop takes responses back. I've used no serial.readline() method, because of different end-line char, and I have found the usage of io classes to be too much fuss.
Depends on what you run in that thread.
If that's your code, then you can implement a stop condition (see other answers).
However, if what you want is to run someone else's code, then you should fork and start a process. Like this:
import multiprocessing
proc = multiprocessing.Process(target=your_proc_function, args=())
proc.start()
now, whenever you want to stop that process, send it a SIGTERM like this:
proc.terminate()
proc.join()
And it's not slow: fractions of a second.
Enjoy :)
My solution is:
import threading, time
def a():
t = threading.currentThread()
while getattr(t, "do_run", True):
print('Do something')
time.sleep(1)
def getThreadByName(name):
threads = threading.enumerate() #Threads list
for thread in threads:
if thread.name == name:
return thread
threading.Thread(target=a, name='228').start() #Init thread
t = getThreadByName('228') #Get thread by name
time.sleep(5)
t.do_run = False #Signal to stop thread
t.join()
I find it useful to have a class, derived from threading.Thread, to encapsulate my thread functionality. You simply provide your own main loop in an overridden version of run() in this class. Calling start() arranges for the object’s run() method to be invoked in a separate thread.
Inside the main loop, periodically check whether a threading.Event has been set. Such an event is thread-safe.
Inside this class, you have your own join() method that sets the stop event object before calling the join() method of the base class. It can optionally take a time value to pass to the base class's join() method to ensure your thread is terminated in a short amount of time.
import threading
import time
class MyThread(threading.Thread):
def __init__(self, sleep_time=0.1):
self._stop_event = threading.Event()
self._sleep_time = sleep_time
"""call base class constructor"""
super().__init__()
def run(self):
"""main control loop"""
while not self._stop_event.isSet():
#do work
print("hi")
self._stop_event.wait(self._sleep_time)
def join(self, timeout=None):
"""set stop event and join within a given time period"""
self._stop_event.set()
super().join(timeout)
if __name__ == "__main__":
t = MyThread()
t.start()
time.sleep(5)
t.join(1) #wait 1s max
Having a small sleep inside the main loop before checking the threading.Event is less CPU intensive than looping continuously. You can have a default sleep time (e.g. 0.1s), but you can also pass the value in the constructor.
Sometimes you don't have control over the running target. In those cases you can 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
I have a Manager (main thread), that creates other Threads to handle various operations.
I would like my Manager to be notified when a Thread it created ends (when run() method execution is finished).
I know I could do it by checking the status of all my threads with the Thread.isActive() method, but polling sucks, so I wanted to have notifications.
I was thinking of giving a callback method to the Threads, and call this function at the end of the run() method:
class Manager():
...
MyThread(self.on_thread_finished).start() # How do I pass the callback
def on_thread_finished(self, data):
pass
...
class MyThread(Thread):
...
def run(self):
....
self.callback(data) # How do I call the callback?
...
Thanks!
The thread can't call the manager unless it has a reference to the manager. The easiest way for that to happen is for the manager to give it to the thread at instantiation.
class Manager(object):
def new_thread(self):
return MyThread(parent=self)
def on_thread_finished(self, thread, data):
print thread, data
class MyThread(Thread):
def __init__(self, parent=None):
self.parent = parent
super(MyThread, self).__init__()
def run(self):
# ...
self.parent and self.parent.on_thread_finished(self, 42)
mgr = Manager()
thread = mgr.new_thread()
thread.start()
If you want to be able to assign an arbitrary function or method as a callback, rather than storing a reference to the manager object, this becomes a bit problematic because of method wrappers and such. It's hard to design the callback so it gets a reference to both the manager and the thread, which is what you will want. I worked on that for a while and did not come up with anything I'd consider useful or elegant.
Anything wrong with doing it this way?
from threading import Thread
class Manager():
def Test(self):
MyThread(self.on_thread_finished).start()
def on_thread_finished(self, data):
print "on_thread_finished:", data
class MyThread(Thread):
def __init__(self, callback):
Thread.__init__(self)
self.callback = callback
def run(self):
data = "hello"
self.callback(data)
m = Manager()
m.Test() # prints "on_thread_finished: hello"
If you want the main thread to wait for children threads to finish execution, you are probably better off using some kind of synchronization mechanism. If simply being notified when one or more threads has finished executing, a Condition is enough:
import threading
class MyThread(threading.Thread):
def __init__(self, condition):
threading.Thread.__init__(self)
self.condition = condition
def run(self):
print "%s done" % threading.current_thread()
with self.condition:
self.condition.notify()
condition = threading.Condition()
condition.acquire()
thread = MyThread(condition)
thread.start()
condition.wait()
However, using a Queue is probably better, as it makes handling multiple worker threads a bit easier.