Based on this pretty useful tutorial I have tried to make a simple implementation of Python multiprocessing to measure its effectivity. The modules multi1, multi2, multi3 contain an ODE integration and exporting the calculated values in a csv (it does not matter, they are here for a script to do something).
import multiprocessing
import multi1
import multi2
import multi3
import time
t0 = time.time()
if __name__ == '__main__':
p1 = multiprocessing.Process(target = multi1.main(), args=())
p2 = multiprocessing.Process(target = multi2.main(), args=())
p3 = multiprocessing.Process(target = multi3.main(), args=())
p1.start()
p2.start()
p3.start()
p1.join()
p2.join()
p3.join()
t1 = time.time()
multi1.main()
multi2.main()
multi3.main()
t2 = time.time()
print t1-t0
print t2-t1
The problem is that the printed times are equal, so the multiprocessing didn't speed up the process. Why?
You called main in the main thread, and passed the return value (probably None) as the target, so no actual work is done in your worker processes. Remove the call parens, so you pass the function itself without calling it, e.g.:
p1 = multiprocessing.Process(target=multi1.main, args=())
p2 = multiprocessing.Process(target=multi2.main, args=())
p3 = multiprocessing.Process(target=multi3.main, args=())
This is the same basic problem seen in the threaded case.
Related
I'm just studying about multiprocessing in Python. I have a code that updates the value of a variable in a process, and other processes read the value of this variable. This is working as I expected.
Now I just want to know if there is some way to do the same using the Ray library to improve the speed of execution if I need to run lots of processes reading it
from multiprocessing import Process, Manager
def write_to_dict(d, value):
while True:
value = value + 1
d['key'] = value
def read_from_dict(d):
while True:
read = d['key']
print(read)
if __name__ == '__main__':
manager = Manager()
shared_dict = manager.dict()
p1 = Process(target=write_to_dict, args=(shared_dict, 0))
p2 = Process(target=read_from_dict, args=(shared_dict,))
p1.start()
p2.start()
p1.join()
p2.join()
I have two functions and needed the return values to proceed with the further part of the script...but currently my code giving only the output of the first function...
import multiprocessing
def gm(name):
h = "Good Morning"+str(name)
qout.put(h)
def sal(name):
k="Hi "+str(name)
qout.put(k)
if __name__ == '__main__':
qout = multiprocessing.Queue()
p1 = multiprocessing.Process(target=gm, args=("ashin",))
p2 = multiprocessing.Process(target=sal, args=("ashin",))
p1.start()
p2.start()
p1.join()
p2.join()
result = qout.get()
#output - "Good Morning ashin"
#required output - "Good Morning ashin" & "Hi ashin"
Appreciate your help......
qout.get() gets you the first element from queue. I do not know the bigger picture of what you're are trying to achieve, but you can get all elements from queue like in the following.
from multiprocessing import Process, Queue
def gm(name):
h = "Good Morning"+str(name)
qout.put(h)
def sal(name):
k="Hi "+str(name)
qout.put(k)
if __name__ == '__main__':
qout = Queue()
p1 = Process(target=gm, args=("ashin",))
p2 = Process(target=sal, args=("ashin",))
p1.start()
p2.start()
p1.join()
p2.join()
list1 = []
while not qout.empty():
list1.append(qout.get())
temp = list(map(str, list1))
print(" & ".join(temp))
output
Hi ashin & Good Morningashin
Instead of managing your own output queue, just use the latest Python 3 concurrency features:
from concurrent.futures import as_completed, ProcessPoolExecutor
def gm(name):
return f'Good Morning {name}'
def sal(name):
return f'Hi {name}'
if __name__ == '__main__':
with ProcessPoolExecutor() as exe:
futures = [exe.submit(x, 'ashin') for x in (gm, sal)]
for future in as_completed(futures):
print(future.result())
I am new with multiprocessing in python and so far all the example I've seen are this kind (with one or more methods in the file and then 'main'):
from multiprocessing import Process
def f1(a):
#do something
def f2(b):
#do something
if __name__ == '__main__':
f1(a1)
p = Process(target=f2, args=(b2,))
p.start()
p.join()
If I have instead a method who calls 2 functions in another file to be concurrent like in the following lines,
def function():
#do something
file2.f1(a) #first concurrent method
file2.f2(b) #second concurrent method
how should I do?
Can anyone make a simple example? I tried in this way, but it starts all the program again after the first loop :
def function():
#do something
for i in range(3):
p1 = Process(target=file2.f1, args=(a)) #first concurrent method
p2 = Process(target=file2.f2, args=(b)) #second concurrent method
p1.start()
p2.start()
p1.join()
p2.join()
The issue seems to be that args varialbe is incorrectly defined, it should be tuple and not a single variable:
def function():
#do something
for i in range(3):
p1 = Process(target=file2.f1, args=(a, )) #first concurrent method
p2 = Process(target=file2.f2, args=(b, )) #second concurrent method
p1.start()
p2.start()
p1.join()
p2.join()
If you the order of the executions is flexible, you can use the Pool class to trigger multiple calls:
from multiprocessing.pool import Pool
pool = Pool()
pool.map_async(f1, [(arg, )] * 3)
pool.map_async(f2, [(arg, )] * 3)
pool.close()
pool.join()
I have 2 process running and I want them to complete before further down command executes (at the end of script it prints out that the program has ended). How can I make sure the process completes before printing out that it has ended?
from multiprocessing import Process
import datetime
class foo:
def fun1():
do sthn
def fun2():
do sthn
ob = foo()
if __name__ == '__main__':
p1 = Process(target = ob.fun1)
p1.start()
p2 = Process(target = ob.fun2)
p2.start()
endTime=datetime.datetime.now()
print 'Program Ending time is: ', endTime
You would use the .join() method, which blocks until the process is complete.
p1.join()
p2.join()
I'm trying to run 2 separate processes in my python application. So I have code like this:
from multiprocessing import Process
def f1():
while 1:
print('Hello')
def f2():
while 1:
print('Goodbye')
def main():
p1 = Process(target=f1, args=())
p1.start()
p1.join()
p2 = Process(target=f2, args=())
p2.start()
p2.join()
if __name__ == '__main__':
main()
This code does nothing on my machine, it doesn't produce any output. I thought initially that maybe it was an IDE-related problem, but it's the same on both my IDEs, PyScripter and IDLE.
Any ideas, why this doesn't print anything?
How about using Queue?
from multiprocessing import Process, Queue
def f1(q):
while 1:
q.put('Hello')
def f2(q):
while 1:
q.put('Goodbye')
def main():
q = Queue()
p1 = Process(target=f1, args=(q,))
p1.start()
p2 = Process(target=f2, args=(q,))
p2.start()
while True:
try:
print q.get()
except:
break
if __name__ == '__main__':
main()
You should save it and run outside the IDE:
C:\> python multi.py
then it infinitely prints out Hello. You should change your main to see both Hello and Goodbye:
def main():
p1 = Process(target=f1, args=())
p2 = Process(target=f2, args=())
p1.start()
p2.start()
p1.join()
p2.join()
Then you have a little happy race condition that constantly prints out GHoodbyeello because both processes use the same stdout resource concurrently.