Can't pickle when using multiprocessing Pool.map()

Question

I\'m trying to use multiprocessing\'s Pool.map() function to divide out work simultaneously. When I use the following code, it works fine:

Answer 1

The solution from parisjohn above works fine with me. Plus the code looks clean and easy to understand. In my case there are a few functions to call using Pool, so I modified parisjohn's code a bit below. I made call to be able to call several functions, and the function names are passed in the argument dict from go():

from multiprocessing import Pool
class someClass(object):
    def __init__(self):
        pass

    def f(self, x):
        return x*x

    def g(self, x):
        return x*x+1    

    def go(self):
        p = Pool(4)
        sc = p.map(self, [{"func": "f", "v": 1}, {"func": "g", "v": 2}])
        print sc

    def __call__(self, x):
        if x["func"]=="f":
            return self.f(x["v"])
        if x["func"]=="g":
            return self.g(x["v"])        

sc = someClass()
sc.go()