I have the following scenario:
res = []
def longfunc(arg):
# function runs arg number of steps
# each step can take 500 ms to 2 seconds to complete
# longfunc keeps adding result of each step into the array res
def getResult(arg,timeout):
# should call longfunc()
# if longfunc() has not provided result by timeout milliseconds then return None
# if there is partial result in res by timeout milliseconds then return res
# if longfunc() ends before timeout milliseconds then return complete result of longfunc i.e. res array
result = getResult(2, 500)
I am thinking of using multiprocessing.Process() to put longfunc() in a separate process, then start another thread to sleep for timeout milliseconds. I can't figure out how to get result from both of them in the main thread and decide which one came first. Any suggestions on this approach or other approaches are appreciated.
You can use time.perf_counterand your code will see:
import time
ProcessTime = time.perf_counter #this returns nearly 0 when first call it if python version <= 3.6
ProcessTime()
def longfunc(arg, timeout):
start = ProcessTime()
while True
# Do anything
delta = start + timeout - ProcessTime()
if delta > 0:
sleep(1)
else:
return #Error or False
you can change While for a for loop an for each task, check timeout
If you are applying multiprocessing then you have to simply apply p.join(timeout=5) where p in a process
Here is a simple example
import time
from itertools import count
from multiprocessing import Process
def inc_forever():
print('Starting function inc_forever()...')
while True:
time.sleep(1)
print(next(counter))
def return_zero():
print('Starting function return_zero()...')
return 0
if __name__ == '__main__':
# counter is an infinite iterator
counter = count(0)
p1 = Process(target=inc_forever, name='Process_inc_forever')
p2 = Process(target=return_zero, name='Process_return_zero')
p1.start()
p2.start()
p1.join(timeout=5)
p2.join(timeout=5)
p1.terminate()
p2.terminate()
if p1.exitcode is None:
print(f'Oops, {p1} timeouts!')
if p2.exitcode == 0:
print(f'{p2} is luck and finishes in 5 seconds!')
I think it may help you
I am running pool.map on big data array and i want to print report in console every minute.
Is it possible? As i understand, python is synchronous language, it can't do this like nodejs.
Perhaps it can be done by threading.. or how?
finished = 0
def make_job():
sleep(1)
global finished
finished += 1
# I want to call this function every minute
def display_status():
print 'finished: ' + finished
def main():
data = [...]
pool = ThreadPool(45)
results = pool.map(make_job, data)
pool.close()
pool.join()
You can use a permanent threaded timer, like those from this question: Python threading.timer - repeat function every 'n' seconds
from threading import Timer,Event
class perpetualTimer(object):
# give it a cycle time (t) and a callback (hFunction)
def __init__(self,t,hFunction):
self.t=t
self.stop = Event()
self.hFunction = hFunction
self.thread = Timer(self.t,self.handle_function)
def handle_function(self):
self.hFunction()
self.thread = Timer(self.t,self.handle_function)
if not self.stop.is_set():
self.thread.start()
def start(self):
self.stop.clear()
self.thread.start()
def cancel(self):
self.stop.set()
self.thread.cancel()
Basically this is just a wrapper for a Timer object that creates a new Timer object every time your desired function is called. Don't expect millisecond accuracy (or even close) from this, but for your purposes it should be ideal.
Using this your example would become:
finished = 0
def make_job():
sleep(1)
global finished
finished += 1
def display_status():
print 'finished: ' + finished
def main():
data = [...]
pool = ThreadPool(45)
# set up the monitor to make run the function every minute
monitor = PerpetualTimer(60,display_status)
monitor.start()
results = pool.map(make_job, data)
pool.close()
pool.join()
monitor.cancel()
EDIT:
A cleaner solution may be (thanks to comments below):
from threading import Event,Thread
class RepeatTimer(Thread):
def __init__(self, t, callback, event):
Thread.__init__(self)
self.stop = event
self.wait_time = t
self.callback = callback
self.daemon = True
def run(self):
while not self.stop.wait(self.wait_time):
self.callback()
Then in your code:
def main():
data = [...]
pool = ThreadPool(45)
stop_flag = Event()
RepeatTimer(60,display_status,stop_flag).start()
results = pool.map(make_job, data)
pool.close()
pool.join()
stop_flag.set()
One way to do this, is to use main thread as the monitoring one. Something like below should work:
def main():
data = [...]
results = []
step = 0
pool = ThreadPool(16)
pool.map_async(make_job, data, callback=results.extend)
pool.close()
while True:
if results:
break
step += 1
sleep(1)
if step % 60 == 0:
print "status update" + ...
I've used .map() instead of .map_async() as the former is synchronous one. Also you probably will need to replace results.extend with something more efficient. And finally, due to GIL, speed improvement may be much smaller than expected.
BTW, it is little bit funny that you wrote that Python is synchronous in a question that asks about ThreadPool ;).
Consider using the time module. The time.time() function returns the current UNIX time.
For example, calling time.time() right now returns 1410384038.967499. One second later, it will return 1410384039.967499.
The way I would do this would be to use a while loop in the place of results = pool(...), and on every iteration to run a check like this:
last_time = time.time()
while (...):
new_time = time.time()
if new_time > last_time+60:
print "status update" + ...
last_time = new_time
(your computation here)
So that will check if (at least) a minute has elapsed since your last status update. It should print a status update approximately every sixty seconds.
Sorry that this is an incomplete answer, but I hope this helps or gives you some useful ideas.
I have a code:
function_1()
function_2()
Normally, function_1() takes 10 hours to end.
But I want function_1() to run for 2 hours, and after 2 hours, function_1 must return and program must continue with function_2(). It shouldn't wait for function_1() to be completed. Is there a way to do this in python?
What makes functions in Python able to interrupt their execution and resuming is the use of the "yield" statement -- your function then will work as a generator object. You call the "next" method on this object to have it start or continue after the last yield
import time
def function_1():
start_time = time.time()
while True:
# do long stuff
running_time = time.time() -start_time
if running_time > 2 * 60 * 60: # 2 hours
yield #<partial results can be yield here, if you want>
start_time = time.time()
runner = function_1()
while True:
try:
runner.next()
except StopIteration:
# function_1 had got to the end
break
# do other stuff
If you don't mind leaving function_1 running:
from threading import Thread
import time
Thread(target=function_1).start()
time.sleep(60*60*2)
Thread(target=function_2).start()
You can try to use module Gevent: start function in thread and kill that thread after some time.
Here is example:
import gevent
# function which you can't modify
def func1(some_arg)
# do something
pass
def func2()
# do something
pass
if __name__ == '__main__':
g = gevent.Greenlet(func1, 'Some Argument in func1')
g.start()
gevent.sleep(60*60*2)
g.kill()
# call the rest of functions
func2()
from multiprocessing import Process
p1 = Process(target=function_1)
p1.start()
p1.join(60*60*2)
if p1.is_alive():p1.terminate()
function_2()
I hope this helps
I just tested this using the following code
import time
from multiprocessing import Process
def f1():
print 0
time.sleep(10000)
print 1
def f2():
print 2
p1 = Process(target=f1)
p1.start()
p1.join(6)
if p1.is_alive():p1.terminate()
f2()
Output is as expected:
0
2
You can time the execution using the datetime module. Probably your optimizer function has a loop somewhere. Inside the loop you can test how much time has passed since you started the function.
def function_1():
t_end = datetime.time.now() + datetime.timedelta(hours=2)
while not converged:
# do your thing
if datetime.time.now() > t_end:
return
I have small repeater Below that keeps ending, How can fix so more stable from crashes, and not stop running....
I would I add a heartbeat to the gui to see that its still running. In Wxpthon, my menu bar goes blank or white.
def TimerSetup():
import threading, time
invl = 300
def dothis():
try:
FetchUpdates()
except Exception as e:
pass
class Repeat(threading.Thread):
def run(self):
dothis()
if __name__ == '__main__':
for x in range(7000):
thread = Repeat(name = "Thread-%d" % (x + 1))
thread.start()
time.sleep(invl)
This runs for 7000 iterations. So if your runtime is at about 7000*300 s, it "works exactly as coded" :-) However, possibly the number of threads or the things you do in FetchUpdates could be a problem. Is there any traceback when it stops? Are reaching a user limit?
seems you need join() to wait the start thread
def TimerSetup():
import threading, time
invl = 300
def dothis():
try:
FetchUpdates()
except Exception as e:
pass
class Repeat(threading.Thread):
def run(self):
dothis()
if __name__ == '__main__':
for x in range(7000):
thread = Repeat(name = "Thread-%d" % (x + 1))
thread.start()
thread.join()
time.sleep(invl)
I need to wait in a script until a certain number of conditions become true?
I know I can roll my own eventing using condition variables and friends, but I don't want to go through all the trouble of implementing it, since some object property changes come from external thread in a wrapped C++ library (Boost.Python), so I can't just hijack __setattr__ in a class and put a condition variable there, which leaves me with either trying to create and signal a Python condition variable from C++, or wrap a native one and wait on it in Python, both of which sound fiddly, needlessly complicated and boring.
Is there an easier way to do it, barring continuous polling of the condition?
Ideally it would be along the lines of
res = wait_until(lambda: some_predicate, timeout)
if (not res):
print 'timed out'
Unfortunately the only possibility to meet your constraints is to periodically poll, e.g....:
import time
def wait_until(somepredicate, timeout, period=0.25, *args, **kwargs):
mustend = time.time() + timeout
while time.time() < mustend:
if somepredicate(*args, **kwargs): return True
time.sleep(period)
return False
or the like. This can be optimized in several ways if somepredicate can be decomposed (e.g. if it's known to be an and of several clauses, especially if some of the clauses are in turn subject to optimization by being detectable via threading.Events or whatever, etc, etc), but in the general terms you ask for, this inefficient approach is the only way out.
Another nice package is waiting - https://pypi.org/project/waiting/
install:
pip install waiting
Usage:
You pass a function that will be called every time as a condition, a timeout, and (this is useful) you can pass a description for the waiting, which will be displayed if you get TimeoutError.
using function:
from waiting import wait
def is_something_ready(something):
if something.ready():
return True
return False
# wait for something to be ready
something = # whatever
wait(lambda: is_something_ready(something), timeout_seconds=120, waiting_for="something to be ready")
# this code will only execute after "something" is ready
print("Done")
Note: the function must return a boolean - True when the wait is over, False otherwise
Here is another solution. The goal was to make threads to wait on each other before doing some work in a very precise order. The work can take unknown amount of time. Constant polling is not good for two reasons: it eats CPU time and action does not start immediately after condition is met.
class Waiter():
def __init__(self, init_value):
self.var = init_value
self.var_mutex = threading.Lock()
self.var_event = threading.Event()
def WaitUntil(self, v):
while True:
self.var_mutex.acquire()
if self.var == v:
self.var_mutex.release()
return # Done waiting
self.var_mutex.release()
self.var_event.wait(1) # Wait 1 sec
def Set(self, v):
self.var_mutex.acquire()
self.var = v
self.var_mutex.release()
self.var_event.set() # In case someone is waiting
self.var_event.clear()
And the way to test it
class TestWaiter():
def __init__(self):
self.waiter = Waiter(0)
threading.Thread(name='Thread0', target=self.Thread0).start()
threading.Thread(name='Thread1', target=self.Thread1).start()
threading.Thread(name='Thread2', target=self.Thread2).start()
def Thread0(self):
while True:
self.waiter.WaitUntil(0)
# Do some work
time.sleep(np.random.rand()*2)
self.waiter.Set(1)
def Thread1(self):
while True:
self.waiter.WaitUntil(1)
# Do some work
time.sleep(np.random.rand())
self.waiter.Set(2)
def Thread2(self):
while True:
self.waiter.WaitUntil(2)
# Do some work
time.sleep(np.random.rand()/10)
self.waiter.Set(0)
Waiter for multiprocessing:
import multiprocessing as mp
import ctypes
class WaiterMP():
def __init__(self, init_value, stop_value=-1):
self.var = mp.Value(ctypes.c_int, init_value)
self.stop_value = stop_value
self.event = mp.Event()
def Terminate(self):
self.Set(self.stop_value)
def Restart(self):
self.var.value = self.init_value
def WaitUntil(self, v):
while True:
if self.var.value == v or self.var.value == self.stop_value:
return
# Wait 1 sec and check aiagn (in case event was missed)
self.event.wait(1)
def Set(self, v):
exit = self.var.value == self.stop_value
if not exit: # Do not set var if threads are exiting
self.var.value = v
self.event.set() # In case someone is waiting
self.event.clear()
Please comment if this is still not the best solution.
You've basically answered your own question: no.
Since you're dealing with external libraries in boost.python, which may change objects at their leisure, you need to either have those routines call an event handler refresh, or work with a condition.
Here is the threading extention to Alex's solution:
import time
import threading
# based on https://stackoverflow.com/a/2785908/1056345
def wait_until(somepredicate, timeout, period=0.25, *args, **kwargs):
must_end = time.time() + timeout
while time.time() < must_end:
if somepredicate(*args, **kwargs):
return True
time.sleep(period)
return False
def wait_until_par(*args, **kwargs):
t = threading.Thread(target=wait_until, args=args, kwargs=kwargs)
t.start()
print ('wait_until_par exits, thread runs in background')
def test():
print('test')
wait_until_par(test, 5)
From the computational perspective there must be a check for all conditions somewhere, sometime. If you have two parts of code, one that generates conditions changes and the other one that should be executed when some are true, you can do the following:
Have the code that changes conditions in, say, main thread, and the code that should be launched when some conditions are true, in a worker thread.
from threading import Thread,Event
locker = Event()
def WhenSomeTrue(locker):
locker.clear() # To prevent looping, see manual, link below
locker.wait(2.0) # Suspend the thread until woken up, or 2s timeout is reached
if not locker.is_set(): # when is_set() false, means timeout was reached
print('TIMEOUT')
else:
#
# Code when some conditions are true
#
worker_thread = Thread(target=WhenSomeTrue, args=(locker,))
worker_thread.start()
cond1 = False
cond2 = False
cond3 = False
def evaluate():
true_conditions = 0
for i in range(1,4):
if globals()["cond"+str(i)]: #access a global condition variable one by one
true_conditions += 1 #increment at each true value
if true_conditions > 1:
locker.set() # Resume the worker thread executing the else branch
#Or just if true_conditions > 1: locker.set();
#true_conditions would need be incremented when 'True' is written to any of those variables
#
# some condition change code
#
evaluate()
For more information concerning this method, visit: https://docs.python.org/3/library/threading.html#event-objects
Proposed solution:
def wait_until(delegate, timeout: int):
end = time.time() + timeout
while time.time() < end:
if delegate():
return True
else:
time.sleep(0.1)
return False
Usage:
wait_until(lambda: True, 2)
I once used this in my code:
while not condition:
pass
Hope this helps
In 2022 now you could use https://trio-util.readthedocs.io/en/latest/#trio_util.AsyncValue
I think this comes closest to what you want in its "smoothest" form
This worked for me
direction = ''
t = 0
while direction == '' and t <= 1:
sleep(0.1)
t += 0.1
This is for waiting for a signal while making sure time limit of 1 second
here's how:
import time
i = false
while i == false:
if (condition):
i = true
break
Here's my Code I used during one of my Projects :
import time
def no() :
if (Condition !!!) :
it got true
oh()
else:
time.sleep(1) /Don't remove or don't blame me if ur system gets ""DEAD""
no()
def oh() : /Ur main program
while True:
if(bla) :
.......
no()
else :
time.sleep(1)
oh()
oh()
Hope it Helps