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()
Related
Why while loop is ignored in work1? I would like to update value from string to another value in loop and output this value in process work2. Also already tried with Queue, but problem is I have only one variable which I would like to update in work1 and access to it at work2.
from multiprocessing import Process, Manager, Value
from ctypes import c_char_p
import time
def work1(string):
i = 2
string.value = i
# while True:
# print("work1")
# string.value = i + 1
# time.sleep(2)
def work2(string):
while True:
print("Value set in work1 " + str(string.value))
time.sleep(2)
if __name__ == '__main__':
manager = Manager()
string = manager.Value(int, 0);
p1=Process(target=work1, args=(string,))
p1.start()
p1.join()
p2=Process(target=work2, args=(string,))
p2.start()
p2.join()
That is because you didn't make your program parallel with two processes, but instead, two processes run in tandem. What you need to do is to start both process before any join. Like my modification below:
from multiprocessing import Process, Manager, Value
from ctypes import c_char_p
import time
def work1(string):
i = 2
string.value = i
while True:
i = i+1
string.value = i
print("work1 set value to "+str(string.value))
time.sleep(2)
def work2(string):
while True:
print("Value set in work1 " + str(string.value))
time.sleep(2)
if __name__ == '__main__':
manager = Manager()
string = manager.Value(int, 0, lock=False);
p1=Process(target=work1, args=(string,))
p2=Process(target=work2, args=(string,))
p1.start()
p2.start()
p2.join()
p1.join()
Indeed, if you write the code in this way, the join never happened due to the infinite while loop.
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.
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've just tested python multiprocessing for reading file or a global variable, but there is something strange happen.
for expample:
import multiprocessing
a = 0
def test(lock, name):
global a
with lock:
for i in range(10):
a = a + 1
print "in process %d : %d" % (name, a)
def main():
lock = multiprocessing.Lock()
p1 = multiprocessing.Process(target=test, args=(lock, 1))
p2 = multiprocessing.Process(target=test, args=(lock, 2))
p1.start()
p2.start()
p1.join()
p2.join()
print "in main process : %d" % a
if __name__=='__main__':
main()
The program read a global variable, but the output is:
in process 1 : 10
in process 2 : 10
in main process : 0
It seems that the sub-process cannot get and edit the global variable properly. Also, if I change the program to read the file, each sub-process will read the file completely, ignoring the lock.
So how does these happen? And how to solve this problem?
Global variables are not shared between processes. When you create and start a new Process(), that process runs inside a separate "cloned" copy of the current Python interpreter. Updating the variable from within a Process() will only update the variable locally to the particular process it is updated in.
To share data between Python processes, we need a multiprocessing.Pipe(), a multiprocessing.Queue(), a multiprocessing.Value(), a multiprocessing.Array() or one of the other multiprocessing-safe containers.
Here's an example based on your code:
import multiprocessing
def worker(lock, counter, name):
with lock:
for i in range(10):
counter.value += 1
print "In process {}: {}".format(name, counter.value)
def main():
lock = multiprocessing.Lock()
counter = multiprocessing.Value('i', 0)
p1 = multiprocessing.Process(target=worker, args=(lock, counter, 1))
p2 = multiprocessing.Process(target=worker, args=(lock, counter, 2))
p1.start()
p2.start()
p1.join()
p2.join()
print "In main process: {}".format(counter.value)
if __name__=='__main__':
main()
This gives me:
In process 1: 10
In process 2: 20
In main process: 20
Now, if you really want to use a global variable, you can use a multiprocessing.Manager(), but I think the first method is preferable, and this is a "heavier" solution. Here's an example:
import multiprocessing
manager = multiprocessing.Manager()
counter = manager.Value('i', 0);
def worker(lock, name):
global counter
with lock:
for i in range(10):
counter.value += 1
print "In process {}: {}".format(name, counter.value)
def main():
global counter
lock = multiprocessing.Lock()
p1 = multiprocessing.Process(target=worker, args=(lock, 1))
p2 = multiprocessing.Process(target=worker, args=(lock, 2))
p1.start()
p2.start()
p1.join()
p2.join()
print "In main process: {}".format(counter.value)
if __name__=='__main__':
main()
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.