Develop Reference

How to terminate a loop early in in a thread?

I have a loop which makes a get request to a webservice to fetch data and do some stuff, but I want to 'manually' terminate the thread/event, which I achieved with the following example:
from threading import Event
exit = Event()
if external_condition():
exit.set()
for _ in range(mins):
fetch_data_and_do_stuff()
exit.wait(10) #wait 10 seconds
With that, the only thing that terminates it's the sleep time between loops. How can I also kill the loop so it doesn't keep running until it gets to the last iteration?

nvm i've solved it like this
from threading import Event
exit = Event()
if external_condition():
exit.set()
for _ in range(mins):
fetch_data_and_do_stuff()
if exit.wait(10):
break
the condition returns true when killed and also sleeps the 10 seconds, so it works

you have 2 options ,
kill the thread or process entirely
or making the loop's boolean false. going that way
you could use a global variable in this way: [Python 3.7] , run it to see
from threading import Thread
from time import sleep
global glob
glob=True
def threaded_function():
while glob:
print("\n [Thread] this thread is running until main function halts this")
sleep(0.8)
if __name__ == "__main__":
thread = Thread(target = threaded_function, args = ())
thread.start()
for i in range(4,0,-1):
print("\n [Main] thread will be terminated in "+str(i)+" seconds")
sleep(1)
glob=False
while True:
print("[Main] program is over")
sleep(1)

Is sys.exit(0) a valid way to exit/kill a thread in python?

I'm writing a timer in python. When the timer reaches 0, I want the thread I made to automatically exit.
class Rollgame:
timer = 0
def timerf(self, timer):
self.timer = timer
while self.timer > 0:
time.sleep(0.1)
self.timer -= 0.1
sys.exit(0)
Is this a valid way to exit a thread? It seems to be working in the context of the program im building, however I'm not sure if it's a good way to do it.
If I ever choose to implement this in something like a flask/django app, will this still be valid?
Sorry if the question seems stupid or too simple, I've never worked with threading in python before.

In general, killing threads abruptly is considered a bad programming practice. Killing a thread abruptly might leave a critical resource that must be closed properly, open. But you might want to kill a thread once some specific time period has passed or some interrupt has been generated. There are the various methods by which you can kill a thread in python.
Set/Reset stop flag :
In order to kill a threads, we can declare a stop flag and this flag will be check occasionally by the thread. For Example:
# Python program showing
# how to kill threads
# using set/reset stop
# flag
import threading
import time
def run():
while True:
print('thread running')
global stop_threads
if stop_threads:
break
stop_threads = False
t1 = threading.Thread(target = run)
t1.start()
time.sleep(1)
stop_threads = True
t1.join()
print('thread killed')
In the above code, as soon as the global variable stop_threads is set, the target function run() ends and the thread t1 can be killed by using t1.join(). But one may refrain from using global variable due to certain reasons. For those situations, function objects can be passed to provide a similar functionality as shown below:
# Python program killing
# threads using stop
# flag
import threading
import time
def run(stop):
while True:
print('thread running')
if stop():
break
def main():
stop_threads = False
t1 = threading.Thread(target = run, args =(lambda : stop_threads, ))
t1.start()
time.sleep(1)
stop_threads = True
t1.join()
print('thread killed')
main()
Using traces to kill threads :
This methods works by installing traces in each thread. Each trace terminates itself on the detection of some stimulus or flag, thus instantly killing the associated thread. For Example:
# Python program using
# traces to kill threads
import sys
import trace
import threading
import time
class thread_with_trace(threading.Thread):
def __init__(self, *args, **keywords):
threading.Thread.__init__(self, *args, **keywords)
self.killed = False
def start(self):
self.__run_backup = self.run
self.run = self.__run
threading.Thread.start(self)
def __run(self):
sys.settrace(self.globaltrace)
self.__run_backup()
self.run = self.__run_backup
def globaltrace(self, frame, event, arg):
if event == 'call':
return self.localtrace
else:
return None
def localtrace(self, frame, event, arg):
if self.killed:
if event == 'line':
raise SystemExit()
return self.localtrace
def kill(self):
self.killed = True
def func():
while True:
print('thread running')
t1 = thread_with_trace(target = func)
t1.start()
time.sleep(2)
t1.kill()
t1.join()
if not t1.isAlive():
print('thread killed')
In this code, start() is slightly modified to set the system trace function using settrace(). The local trace function is defined such that, whenever the kill flag (killed) of the respective thread is set, a SystemExit exception is raised upon the excution of the next line of code, which end the execution of the target function func. Now the thread can be killed with join().
Finally, Using the multiprocessing module to kill threads :
The multiprocessing module of Python allows you to spawn processes in the similar way you spawn threads using the threading module. The interface of the multithreading module is similar to that of the threading module. For Example, in a given code we created three threads(processes) which count from 1 to 9. Now, suppose we wanted to terminate all of the threads. You could use multiprocessing to do that.
# Python program killing
# a thread using multiprocessing
# module
import multiprocessing
import time
def func(number):
for i in range(1, 10):
time.sleep(0.01)
print('Processing ' + str(number) + ': prints ' + str(number*i))
# list of all processes, so that they can be killed afterwards
all_processes = []
for i in range(0, 3):
process = multiprocessing.Process(target=func, args=(i,))
process.start()
all_processes.append(process)
# kill all processes after 0.03s
time.sleep(0.03)
for process in all_processes:
process.terminate()
To sum it up, there are many ways to terminate threads, but I peronally wouldn't use sys.exit().

killing a thread without waiting for join

I want to kill a thread in python. This thread can run in a blocking operation and join can't terminate it.
Simular to this:
from threading import Thread
import time
def block():
while True:
print("running")
time.sleep(1)
if __name__ == "__main__":
thread = Thread(target = block)
thread.start()
#kill thread
#do other stuff
My problem is that the real blocking operation is in another module that is not from me so there is no place where I can break with a running variable.

The thread will be killed when exiting the main process if you set it up as a daemon:
from threading import Thread
import time
def block():
while True:
print("running")
time.sleep(1)
if __name__ == "__main__":
thread = Thread(target = block, daemon = True)
thread.start()
sys.exit(0)
Otherwise just set a flag, I'm using a bad example (you should use some synchronization not just a plain variable):
from threading import Thread
import time
RUNNING = True
def block():
global RUNNING
while RUNNING:
print("running")
time.sleep(1)
if __name__ == "__main__":
thread = Thread(target = block, daemon = True)
thread.start()
RUNNING = False # thread will stop, not killed until next loop iteration
.... continue your stuff here

Use a running variable:
from threading import Thread
import time
running = True
def block():
global running
while running:
print("running")
time.sleep(1)
if __name__ == "__main__":
thread = Thread(target = block)
thread.start()
running = False
# do other stuff
I would prefer to wrap it all in a class, but this should work (untested though).

EDIT
There is a way to asynchronously raise an exception in a separate thread which could be caught by a try: except: block, but it's a dirty dirty hack: https://gist.github.com/liuw/2407154
Original post
"I want to kill a thread in python." you can't. Threads are only killed when they're daemons when there are no more non-daemonic threads running from the parent process. Any thread can be asked nicely to terminate itself using standard inter-thread communication methods, but you state that you don't have any chance to interrupt the function you want to kill. This leaves processes.
Processes have more overhead, and are more difficult to pass data to and from, but they do support being killed by sending SIGTERM or SIGKILL.
from multiprocessing import Process, Queue
from time import sleep
def workfunction(*args, **kwargs): #any arguments you send to a child process must be picklable by python's pickle module
sleep(args[0]) #really long computation you might want to kill
return 'results' #anything you want to get back from a child process must be picklable by python's pickle module
class daemon_worker(Process):
def __init__(self, target_func, *args, **kwargs):
self.return_queue = Queue()
self.target_func = target_func
self.args = args
self.kwargs = kwargs
super().__init__(daemon=True)
self.start()
def run(self): #called by self.start()
self.return_queue.put(self.target_func(*self.args, **self.kwargs))
def get_result(self): #raises queue.Empty if no result is ready
return self.return_queue.get()
if __name__=='__main__':
#start some work that takes 1 sec:
worker1 = daemon_worker(workfunction, 1)
worker1.join(3) #wait up to 3 sec for the worker to complete
if not worker1.is_alive(): #if we didn't hit 3 sec timeout
print('worker1 got: {}'.format(worker1.get_result()))
else:
print('worker1 still running')
worker1.terminate()
print('killing worker1')
sleep(.1) #calling worker.is_alive() immediately might incur a race condition where it may or may not have shut down yet.
print('worker1 is alive: {}'.format(worker1.is_alive()))
#start some work that takes 100 sec:
worker2 = daemon_worker(workfunction, 100)
worker2.join(3) #wait up to 3 sec for the worker to complete
if not worker2.is_alive(): #if we didn't hit 3 sec timeout
print('worker2 got: {}'.format(worker2.get_result()))
else:
print('worker2 still running')
worker2.terminate()
print('killing worker2')
sleep(.1) #calling worker.is_alive() immediately might incur a race condition where it may or may not have shut down yet.
print('worker2 is alive: {}'.format(worker2.is_alive())

Mutual exclusion thread locking, with dropping of queued functions upon mutex/lock release, in Python?

This is the problem I have: I'm using Python 2.7, and I have a code which runs in a thread, which has a critical region that only one thread should execute at the time. That code currently has no mutex mechanisms, so I wanted to inquire what I could use for my specific use case, which involves "dropping" of "queued" functions. I've tried to simulate that behavior with the following minimal working example:
useThreading=False # True
if useThreading: from threading import Thread, Lock
else: from multiprocessing import Process, Lock
mymutex = Lock()
import time
tstart = None
def processData(data):
#~ mymutex.acquire()
try:
print('thread {0} [{1:.5f}] Do some stuff'.format(data, time.time()-tstart))
time.sleep(0.5)
print('thread {0} [{1:.5f}] 1000'.format(data, time.time()-tstart))
time.sleep(0.5)
print('thread {0} [{1:.5f}] done'.format(data, time.time()-tstart))
finally:
#~ mymutex.release()
pass
# main:
tstart = time.time()
for ix in xrange(0,3):
if useThreading: t = Thread(target = processData, args = (ix,))
else: t = Process(target = processData, args = (ix,))
t.start()
time.sleep(0.001)
Now, if you run this code, you get a printout like this:
thread 0 [0.00173] Do some stuff
thread 1 [0.00403] Do some stuff
thread 2 [0.00642] Do some stuff
thread 0 [0.50261] 1000
thread 1 [0.50487] 1000
thread 2 [0.50728] 1000
thread 0 [1.00330] done
thread 1 [1.00556] done
thread 2 [1.00793] done
That is to say, the three threads quickly get "queued" one after another (something like 2-3 ms after each other). Actually, they don't get queued, they simply start executing in parallel after 2-3 ms after each other.
Now, if I enable the mymutex.acquire()/.release() commands, I get what would be expected:
thread 0 [0.00174] Do some stuff
thread 0 [0.50263] 1000
thread 0 [1.00327] done
thread 1 [1.00350] Do some stuff
thread 1 [1.50462] 1000
thread 1 [2.00531] done
thread 2 [2.00547] Do some stuff
thread 2 [2.50638] 1000
thread 2 [3.00706] done
Basically, now with locking, the threads don't run in parallel, but they run one after another thanks to the lock - as long as one thread is working, the others will block at the .acquire(). But this is not exactly what I want to achieve, either.
What I want to achieve is this: let's assume that when .acquire() is first triggered by a thread function, it registers an id of a function (say a pointer to it) in a queue. After that, the behavior is basically the same as with the Lock - while the one thread works, the others block at .acquire(). When the first thread is done, it goes in the finally: block - and here, I'd like to check to see how many threads are waiting in the queue; then I'd like to delete/drop all waiting threads except for the very last one - and finally, I'd .release() the lock; meaning that after this, what was the last thread in the queue would execute next. I'd imagine, I would want to write something like the following pseudocode:
...
finally:
if (len(mymutex.queue) > 2): # more than this instance plus one other waiting:
while (len(mymutex.queue) > 2):
mymutex.queue.pop(1) # leave alone [0]=this instance, remove next element
# at this point, there should be only queue[0]=this instance, and queue[1]= what was the last thread queued previously
mymutex.release() # once we releace, queue[0] should be gone, and the next in the queue should acquire the mutex/lock..
pass
...
With that, I'd expect a printout like this:
thread 0 [0.00174] Do some stuff
thread 0 [0.50263] 1000
thread 0 [1.00327] done
# here upon lock release, thread 1 would be deleted - and the last one in the queue, thread 2, would acquire the lock next:
thread 2 [1.00350] Do some stuff
thread 2 [1.50462] 1000
thread 2 [2.00531] done
What would be the most straightforward way to achieve this in Python?

Seems like you want a queue-like behaviour, so why not use Queue?
import threading
from Queue import Queue
import time
# threads advertise to this queue when they're waiting
wait_queue = Queue()
# threads get their task from this queue
task_queue = Queue()
def do_stuff():
print "%s doing stuff" % str(threading.current_thread())
time.sleep(5)
def queue_thread(sleep_time):
# advertise current thread waiting
time.sleep(sleep_time)
wait_queue.put("waiting")
# wait for permission to pass
message = task_queue.get()
print "%s got task: %s" % (threading.current_thread(), message)
# unregister current thread waiting
wait_queue.get()
if message == "proceed":
do_stuff()
# kill size-1 threads waiting
for _ in range(wait_queue.qsize() - 1):
task_queue.put("die")
# release last
task_queue.put("proceed")
if message == "die":
print "%s died without doing stuff" % threading.current_thread()
pass
t1 = threading.Thread(target=queue_thread, args=(1, ))
t2 = threading.Thread(target=queue_thread, args=(2, ))
t3 = threading.Thread(target=queue_thread, args=(3, ))
t4 = threading.Thread(target=queue_thread, args=(4, ))
# allow first thread to pass
task_queue.put("proceed")
t1.start()
t2.start()
t3.start()
t4.start()
thread-1 arrives first and "acquires" the section, other threads come later to wait at the queue (and advertise they're waiting). Then, when thread-1 leaves it gives permission to the last thread at the queue by telling all other thread to die, and the last thread to proceed.
You can have finer control using different messages, a typical one would be a thread-id in the wait_queue (so you know who is waiting, and the order in which it arrived).
You can probably utilize non-blocking operations (queue.put(block=False) and queue.get(block=False)) in your favour when you're set on what you need.

Python - Is it possible to "stop" or "pause" a thread

I have two threads, and, I want one thread to run for 10 seconds, and then have this thread stop, whilst another thread executes and then the first thread starts up again; this process is repeated. So e.g.
from threading import Thread
import sys
import time
class Worker(Thread):
Listened = False;
def __init__(self):
while 1:
if(self.Listened == False):
time.sleep(0)
else:
time.sleep(20)
for x in range(0, 10):
print "I'm working"
self.Listened = True
class Processor(Thread):
Listened = False;
def __init__(self):
# this is where I'm confused!!
Worker().start()
Processer().start()
(P.S. I have indented correctly, however, SO seems to have messed it up a bit)
Basically, what I want is:
The worker thread works for 10 seconds (or so) and then stops, the "processor" starts up and, once the processor has processed the data from the last run of the "Worker" thread, it then re-starts the "worker" thread up. I don't specifically have to re-start the "worker" thread from that current position, it can start from the beginning.
Does anyone have any ideas?

You can use a counting semaphore to block a thread, and then wake-it-up later.
A counting semaphore is an object that has a non-negative integer count. If a thread calls acquire() on the semaphore when the count is 0, the thead will block until the semaphore's count becomes greater than zero. To unblock the thread, another thread must increase the count of the semaphore by calling release() on the semaphore.
Create two semaphores, one to block the worker, and one to block the processor. Start the worker semaphore's count a 1 since we want it to run right away. Start the processor's semaphore's count to 0 since we want it to block until the worker is done.
Pass the semaphores to the worker and processor classes. After the worker has run for 10 seconds, it should wake-up the processor by calling processorSemaphore.release(), then it should sleep on its semaphore by calling workerSemaphore.acquire(). The processor does the same.
#!/usr/bin/env python
from threading import Thread, Semaphore
import sys
import time
INTERVAL = 10
class Worker(Thread):
def __init__(self, workerSemaphore, processorSemaphore):
super(Worker, self).__init__()
self.workerSemaphore = workerSemaphore
self.processorSemaphore = processorSemaphore
def run(self):
while True:
# wait for the processor to finish
self.workerSemaphore.acquire()
start = time.time()
while True:
if time.time() - start > INTERVAL:
# wake-up the processor
self.processorSemaphore.release()
break
# do work here
print "I'm working"
class Processor(Thread):
def __init__(self, workerSemaphore, processorSemaphore):
super(Processor, self).__init__()
print "init P"
self.workerSemaphore = workerSemaphore
self.processorSemaphore = processorSemaphore
def run(self):
print "running P"
while True:
# wait for the worker to finish
self.processorSemaphore.acquire()
start = time.time()
while True:
if time.time() - start > INTERVAL:
# wake-up the worker
self.workerSemaphore.release()
break
# do processing here
print "I'm processing"
workerSemaphore = Semaphore(1)
processorSemaphore = Semaphore(0)
worker = Worker(workerSemaphore, processorSemaphore)
processor = Processor(workerSemaphore, processorSemaphore)
worker.start()
processor.start()
worker.join()
processor.join()

See Alvaro's answer. But if you must really use threads then you can do something like below. However you can call start() on a Thread object only once. So either your data should preserve state as to where the next Worker thread should start from and you create a new worker thread in Processor every time or try to use a critical section so that the Worker and Processor threads can take turns to access it.
#!/usr/bin/env python
from threading import Thread
import time
class Worker(Thread):
def __init__(self):
Thread.__init__(self)
pass
def run(self):
for x in range(0, 10):
print "I'm working"
time.sleep(1)
class Processor(Thread):
def __init__(self, w):
Thread.__init__(self)
self.worker = w
def run(self):
# process data from worker thread, add your logic here
self.worker.start()
w = Worker()
p = Processor(w)
p.start()