I am trying to make 2 functions run at the same time.
def func1(): print 'Working' def func2(): print 'Working' func1() func2()Does anyone know how to do this?
asked Jun 2, 2010 at 11:16
1
Do this:
from threading import Thread def func1(): print('Working') def func2(): print("Working") if __name__ == '__main__': Thread(target = func1).start() Thread(target = func2).start()
answered Jun 2, 2010 at 11:19
chrisgchrisg
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The answer about threading is good, but you need to be a bit more specific about what you want to do.
If you have two functions that both use a lot of CPU, threading (in CPython) will probably get you nowhere. Then you might want to have a look at the multiprocessing module or possibly you might want to use jython/IronPython.
If CPU-bound performance is the reason, you could even implement things in (non-threaded) C and get a much bigger speedup than doing two parallel things in python.
Without more information, it isn't easy to come up with a good answer.
answered Jun 2, 2010 at 11:38
Mattias NilssonMattias Nilsson
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This can be done elegantly with Ray, a system that allows you to easily parallelize and distribute your Python code.
To parallelize your example, you'd need to define your functions with the @ray.remote decorator, and then invoke them with .remote.
import ray ray.init() # Define functions you want to execute in parallel using # the ray.remote decorator. @ray.remote def func1(): print("Working") @ray.remote def func2(): print("Working") # Execute func1 and func2 in parallel. ray.get([func1.remote(), func2.remote()])If func1() and func2() return results, you need to rewrite the above code a bit, by replacing ray.get([func1.remote(), func2.remote()]) with:
ret_id1 = func1.remote() ret_id2 = func1.remote() ret1, ret2 = ray.get([ret_id1, ret_id2])There are a number of advantages of using Ray over the multiprocessing module or using multithreading. In particular, the same code will run on a single machine as well as on a cluster of machines.
For more advantages of Ray see this related post.
answered Feb 4, 2019 at 0:39
Ion StoicaIon Stoica
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One option, that looks like it makes
two functions run at the same
time, is using the threading module (example in this answer).
However, it has a small delay, as an Official Python Documentation
page describes. A better module to try using is multiprocessing.
Also, there's other Python modules that can be used for asynchronous execution (two pieces of code working at the same time). For some information about them and help to choose one, you can read this Stack Overflow question.
Comment from another user about the threading module
He might want to know that because of the Global Interpreter Lock
they will not execute at the exact same time even if the machine in
question has multiple CPUs. wiki.python.org/moin/GlobalInterpreterLock
– Jonas Elfström Jun 2 '10 at 11:39
Quote from the Documentation about threading module not working
CPython implementation detail: In CPython, due to the Global Interpreter
Lock, only one thread can execute Python code at once (even though
certain performance-oriented libraries might overcome this limitation).If you want your application to make better use of the computational resources of multi-core machines, you are advised to use multiprocessing or concurrent.futures.ProcessPoolExecutor.
However, threading is still an appropriate model if you
want to run multiple I/O-bound tasks simultaneously.
answered Oct 11, 2015 at 11:07
EdwardEdward
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The thread module does work simultaneously unlike multiprocess, but the timing is a bit off. The code below prints a "1" and a "2". These are called by different functions respectively. I did notice that when printed to the console, they would have slightly different timings.
from threading import Thread def one(): while(1 == num): print("1") time.sleep(2) def two(): while(1 == num): print("2") time.sleep(2) p1 = Thread(target = one) p2 = Thread(target = two) p1.start() p2.start()Output: (Note the space is for the wait in between printing)
1 2 2 1 12 21 12 1 2Not sure if there is a way to correct this, or if it matters at all. Just something I noticed.
answered Jul 28, 2018 at 4:59
Try this
from threading import Thread def fun1(): print("Working1") def fun2(): print("Working2") t1 = Thread(target=fun1) t2 = Thread(target=fun2) t1.start() t2.start()answered Jun 27, 2018 at 13:34
2
I think what you are trying to convey can be achieved through multiprocessing. However if you want to do it through threads you can do this. This might help
from threading import Thread import time def func1(): print 'Working' time.sleep(2) def func2(): print 'Working' time.sleep(2) th = Thread(target=func1) th.start() th2=Thread(target=func2) th2.start()answered Aug 14, 2018 at 12:22
test using APscheduler:
from apscheduler.schedulers.background import BackgroundScheduler import datetime dt = datetime.datetime Future = dt.now() + datetime.timedelta(milliseconds=2550) # 2.55 seconds from now testing start accuracy def myjob1(): print('started job 1: ' + str(dt.now())[:-3]) # timed to millisecond because thats where it varies time.sleep(5) print('job 1 half at: ' + str(dt.now())[:-3]) time.sleep(5) print('job 1 done at: ' + str(dt.now())[:-3]) def myjob2(): print('started job 2: ' + str(dt.now())[:-3]) time.sleep(5) print('job 2 half at: ' + str(dt.now())[:-3]) time.sleep(5) print('job 2 done at: ' + str(dt.now())[:-3]) print(' current time: ' + str(dt.now())[:-3]) print(' do job 1 at: ' + str(Future)[:-3] + ''' do job 2 at: ''' + str(Future)[:-3]) sched.add_job(myjob1, 'date', run_date=Future) sched.add_job(myjob2, 'date', run_date=Future)i got these results. which proves they are running at the same time.
current time: 2020-12-15 01:54:26.526 do job 1 at: 2020-12-15 01:54:29.072 # i figure these both say .072 because its 1 line of print code do job 2 at: 2020-12-15 01:54:29.072 started job 2: 2020-12-15 01:54:29.075 # notice job 2 started before job 1, but code calls job 1 first. started job 1: 2020-12-15 01:54:29.076 job 2 half at: 2020-12-15 01:54:34.077 # halfway point on each job completed same time accurate to the millisecond job 1 half at: 2020-12-15 01:54:34.077 job 1 done at: 2020-12-15 01:54:39.078 # job 1 finished first. making it .004 seconds faster. job 2 done at: 2020-12-15 01:54:39.091 # job 2 was .002 seconds faster the second testanswered Dec 15, 2020 at 10:14
In case you also want to wait until both functions have been completed:
from threading import Thread def func1(): print 'Working' def func2(): print 'Working' # Define the threads and put them in an array threads = [ Thread(target = self.func1), Thread(target = self.func2) ] # Func1 and Func2 run in separate threads for thread in threads: thread.start() # Wait until both Func1 and Func2 have finished for thread in threads: thread.join()answered Jul 4, 2021 at 10:28
thanos.athanos.a
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