[python] How to do parallel programming in Python?

The solution, as others have said, is to use multiple processes. Which framework is more appropriate, however, depends on many factors. In addition to the ones already mentioned, there is also charm4py and mpi4py (I am the developer of charm4py).

There is a more efficient way to implement the above example than using the worker pool abstraction. The main loop sends the same parameters (including the complete graph G) over and over to workers in each of the 1000 iterations. Since at least one worker will reside on a different process, this involves copying and sending the arguments to the other process(es). This could be very costly depending on the size of the objects. Instead, it makes sense to have workers store state and simply send the updated information.

For example, in charm4py this can be done like this:

class Worker(Chare):

    def __init__(self, Q, G, n):
        self.G = G
        ...

    def setinner(self, node1, node2):
        self.updateGraph(node1, node2)
        ...


def solve(Q, G, n):
    # create 2 workers, each on a different process, passing the initial state
    worker_a = Chare(Worker, onPE=0, args=[Q, G, n])
    worker_b = Chare(Worker, onPE=1, args=[Q, G, n])
    while i < 1000:
        result_a = worker_a.setinner(node1, node2, ret=True)  # execute setinner on worker A
        result_b = worker_b.setouter(node1, node2, ret=True)  # execute setouter on worker B

        inneropt, partition, x = result_a.get()  # wait for result from worker A
        outeropt = result_b.get()  # wait for result from worker B
        ...

Note that for this example we really only need one worker. The main loop could execute one of the functions, and have the worker execute the other. But my code helps to illustrate a couple of things:

1. Worker A runs in process 0 (same as the main loop). While result_a.get() is blocked waiting on the result, worker A does the computation in the same process.
2. Arguments are automatically passed by reference to worker A, since it is in the same process (there is no copying involved).