Reputation: 21
I have found information on multiprocessing and multithreading in python but I don't understand the basic concepts and all the examples that I found are more difficult than what I'm trying to do.
I have X independent programs that I need to run. I want to launch the first Y programs (where Y is the number of cores of my computer and X>>Y). As soon as one of the independent programs is done, I want the next program to run in the next available core. I thought that this would be straightforward, but I keep getting stuck on it. Any help in solving this problem would be much appreciated.
Edit: Thanks a lot for your answers. I also found another solution using the joblib module that I wanted to share. Suppose that you have a script called 'program.py' that you want to run with different combination of the input parameters (a0,b0,c0) and you want to use all your cores. This is a solution.
import os
from joblib import Parallel, delayed
a0 = arange(0.1,1.1,0.1)
b0 = arange(-1.5,-0.4,0.1)
c0 = arange(1.,5.,0.1)
params = []
for i in range(len(a0)):
for j in range(len(b0)):
for k in range(len(c0)):
params.append((a0[i],b0[j],c0[k]))
def func(parameters):
s = 'python program.py %g %g %g' % parameters[0],parameters[1],parameters[2])
command = os.system(s)
return command
output = Parallel(n_jobs=-1,verbose=1000)(delayed(func)(i) for i in params)
Upvotes: 2
Views: 815
Reputation: 28856
You want to use multiprocessing.Pool
, which represents a "pool" of workers (default one per core, though you can specify another number) that do your jobs. You then submit jobs to the pool, and the workers handle them as they become available. The easiest function to use is Pool.map
, which runs a given function for each of the arguments in the passed sequence, and returns the result for each argument. If you don't need return values, you could also use apply_async
in a loop.
def do_work(arg):
pass # do whatever you actually want to do
def run_battery(args):
# args should be like [arg1, arg2, ...]
pool = multiprocessing.Pool()
ret_vals = pool.map(do_work, arg_tuples)
pool.close()
pool.join()
return ret_vals
If you're trying to call external programs and not just Python functions, use subprocess
. For example, this will call cmd_name
with the list of arguments passed, raise an exception if the return code isn't 0, and return the output:
def do_work(subproc_args):
return subprocess.check_output(['cmd_name'] + list(subproc_args))
Upvotes: 2
Reputation: 125
Hi i'm using the object QThread from pyqt From what i understood, your thread when he is running can only use his own variable and proc, he cannot change your main object variables So before you run it be sur to define all the qthread variables you will need
like this for example:
class worker(QThread)
def define(self, phase):
print 'define'
self.phase=phase
self.start()#will run your thread
def continueJob(self):
self.start()
def run(self):
self.launchProgramme(self.phase)
self.phase+=1
def launchProgramme(self):
print self.phase
i'm not well aware of how work the basic python thread but in pyqt your thread launch a signal to your main object like this:
class mainObject(QtGui.QMainWindow)
def __init__(self):
super(mcMayaClient).__init__()
self.numberProgramme=4
self.thread = Worker()
#create
self.connect(self.thread , QtCore.SIGNAL("finished()"), self.threadStoped)
self.connect(self.thread , QtCore.SIGNAL("terminated()"), self.threadStopped)
connected like this, when the thread.run stop, it will launch your threadStopped proc in your main object where u can get the value of your thread Variables
def threadStopped(self):
value=self.worker.phase
if value<self.numberProgramme:
self.worker.continueJob()
after that you just have to lauch another thread or not depending of the value you get This is for pyqt threading of course, in python basic thread, the way to execute the def threadStopped could be different.
Upvotes: 0