I want to be able to use the Values module from the multiprocessing library to be able to keep track of data. As far as I know, when it comes to multiprocessing in Python, each process has it's own copy, so I can't edit global variables. I want to be able to use Values to solve this issue. Does anyone know how I can pass Values data into a pooled function?
from multiprocessing import Pool, Value
import itertools
arr = [2,6,8,7,4,2,5,6,2,4,7,8,5,2,7,4,2,5,6,2,4,7,8,5,2,9,3,2,0,1,5,7,2,8,9,3,2,]
def hello(g, data):
data.value += 1
if __name__ == '__main__':
data = Value('i', 0)
func = partial(hello, data)
p = Pool(processes=1)
p.map(hello,itertools.izip(arr,itertools.repeat(data)))
print data.value
Here is the runtime error i'm getting:
RuntimeError: Synchronized objects should only be shared between processes through inheritance
Does anyone know what I'm doing wrong?
I don't know why, but there seems to be some issue using the Pool
that you don't get if creating subprocesses manually. E.g. The following works:
from multiprocessing import Process, Value
arr = [1,2,3,4,5,6,7,8,9]
def hello(data, g):
with data.get_lock():
data.value += 1
print id(data), g, data.value
if __name__ == '__main__':
data = Value('i')
print id(data)
processes = []
for n in arr:
p = Process(target=hello, args=(data, n))
processes.append(p)
p.start()
for p in processes:
p.join()
print "sub process tasks completed"
print data.value
However, if you do basically the same think using Pool
, then you get an error "RuntimeError: Synchronized objects should only be shared between processes through inheritance". I have seen that error when using a pool before, and never fully got to the bottom of it.
An alternative to using Value
that seems to work with Pool
is to use a Manager to give you a 'shared' list:
from multiprocessing import Pool, Manager
from functools import partial
arr = [1,2,3,4,5,6,7,8,9]
def hello(data, g):
data[0] += 1
if __name__ == '__main__':
m = Manager()
data = m.list([0])
hello_data = partial(hello, data)
p = Pool(processes=5)
p.map(hello_data, arr)
print data[0]
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