I am trying to learn how to use multiprocessing
but I can't get it to work. Here is the code right out of the documentation
from multiprocessing import Process
def f(name):
print 'hello', name
if __name__ == '__main__':
p = Process(target=f, args=('bob',))
p.start()
p.join()
it should output
'hello bob'
but instead i get
>
no errors or other messages, it just sits there, It is running in IDLE
from a saved .py file on a Windows 7 machine with the 32-bit version of Python 2.7
To speed up the program with lots of CPU-bound tasks, you use multiprocessing. Multiprocessing allows two or more processors to simultineously process two or more different part of a program. In Python, you use the multiprocessing module to implement multiprocessing. How it works.
Multiprocessing behaviour depends on the particular machine you run it on, and yours might just be fast enough to swallow the output before you can see it. Downvote all you like but please leave a comment so I can improve the answer. Flushing is not the issue when there is no stdout to flush. Having a stdout stream solve the problem. See my answer.
Below is a simple Python multiprocessing Pool example. from multiprocessing import Pool import time work = ( ["A", 5], ["B", 2], ["C", 1], ["D", 3]) def work_log (work_data): print (" Process %s waiting %s seconds" % (work_data [0], work_data [1])) time.sleep (int (work_data [1])) print (" Process %s Finished."
This is covered in Programming guidelines however it is worth pointing out here. This means that some examples, such as the multiprocessing.Pool examples will not work in the interactive interpreter. The __main__ module is not importable by children in IDLE, even if you run the script as a file with IDLE (which is commonly done with F5).
The problem is not IDLE. The problem is trying to print to sys.stdout in a process that has no sys.stdout. That is why Spyder has the same problem. Any GUI program on Windows is likely to have the same problem.
On Windows, at least, GUI programs are usually run in a process without stdin, stdout, or stderr streams. Windows expects GUI programs to interact with users through widgets that paint pixels on the screen (the G in Graphical) and receive key and mouse events from Windows event system. That is what the IDLE GUI does, using the tkinter wrapper of the tcl tk GUI framework.
When IDLE runs user code in a subprocess, idlelib.run runs first, and it replaces None for the standard streams with objects that interact with IDLE itself through a socket. Then it exec()s user code. When the user code runs multiprocessing, multiprocessing starts further processes that have no std streams, but never get them.
The solution is to start IDLE in a console: python -m idlelib.idle
(the .idle
is not needed on 3.x). Processes started in a console get std streams connect to the console. So do further subprocesses. The real stdout (as opposed to the sys.stdout) of all the processes is the console. If one runs the third example in the doc,
from multiprocessing import Process
import os
def info(title):
print(title)
print('module name:', __name__)
print('parent process:', os.getppid())
print('process id:', os.getpid())
def f(name):
info('function f')
print('hello', name)
if __name__ == '__main__':
info('main line')
p = Process(target=f, args=('bob',))
p.start()
p.join()
then the 'main line' block goes to the IDLE shell and the 'function f' block goes to the console.
This result shows that Justin Barber's claim that the user file run by IDLE cannot be imported into processes started by multiprocessing is not correct.
EDIT: Python saves the original stdout of a process in sys.__stdout__
. Here is the result in IDLE's shell when IDLE is started normally on Windows, as a pure GUI process.
>>> sys.__stdout__
>>>
Here is the result when IDLE is started from CommandPrompt.
>>> import sys
>>> sys.__stdout__
<_io.TextIOWrapper name='<stdout>' mode='w' encoding='utf-8'>
>>> sys.__stdout__.fileno()
1
The standard file numbers for stdin, stdout, and stderr are 0, 1, 2. Run a file with
from multiprocessing import Process
import sys
def f(name):
print('hello', name)
print(sys.__stdout__)
print(sys.__stdout__.fileno())
if __name__ == '__main__':
p = Process(target=f, args=('bob',))
p.start()
p.join()
in IDLE started in the console and the output is the same.
My guess is that you are using IDLE to try to run this script. Unfortunately, this example will not run correctly in IDLE. Note the comment at the beginning of the docs:
Note Functionality within this package requires that the main module be importable by the children. This is covered in Programming guidelines however it is worth pointing out here. This means that some examples, such as the multiprocessing.Pool examples will not work in the interactive interpreter.
The __main__
module is not importable by children in IDLE, even if you run the script as a file with IDLE (which is commonly done with F5).
It works.
I've marked the changes needed to make your sample run using comments:
from multiprocessing import Process
def f(name):
print 'hello', name #indent
if __name__ == '__main__':
p = Process(target=f, args=('bob',))
p.start()
p.join()` # remove ` (grave accent)
result:
from multiprocessing import Process
def f(name):
print 'hello', name
if __name__ == '__main__':
p = Process(target=f, args=('bob',))
p.start()
p.join()
Output from my laptop after saving it as ex1.py:
reuts@reuts-K53SD:~/python_examples$ cat ex1.py
#!/usr/bin/env python
from multiprocessing import Process
def f(name):
print 'hello', name
if __name__ == '__main__':
p = Process(target=f, args=('bob',))
p.start()
p.join()
reuts@reuts-K53SD:~/python_examples$ python ex1.py
hello bob
Most likely your main process exits before sysout is flushed. Try this:
from multiprocessing import Process
import sys
def f(name):
print 'hello', name
if __name__ == '__main__':
p = Process(target=f, args=('bob',))
p.start()
p.join()
# make sure all output has been processed before we exit
sys.stdout.flush()
If this doesn't work, try adding time.sleep(1)
as the last statement.
I had the issue that multiprocessing did not work on Spyder, and always landed here. I solved it by using threading instead of multiprocessing. as described here: https://pymotw.com/2/threading/
import threading
def worker(num):
"""thread worker function"""
print 'Worker: %s' % num
return
threads = []
for i in range(5):
t = threading.Thread(target=worker, args=(i,))
threads.append(t)
t.start()
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