dipsy exercise

# PROBLEMATIC, DON'T USE THE CODE
import sys
import dispy

# A method calculating the importance of a subgraph
#
# args has three parts
# - args[0]: the graph data structure
# - args[1]: the hash with some precalculated float values
# - args[2]: the node name
def calc_importance(args):
    subgraph = args[0].subgraph_from(args[2])

    importance = 0.0
    for e in subgraph.all_nodes():
        if e in ratio:
            importance += abs(args[1][e])

    return (args[2], importance)

cluster = dispy.JobCluster(calc_importance)
jobs = []
# nodes is a list of string presenting node in a graph
for n in nodes:
    # graph is a unpublished module dealing with graph data structure data
    # ratio is a hash with precalculated float values
    job = cluster.submit((graph, ratio, n))
    jobs.append(job)

for job in jobs:
    n, importance = job()
    print "{}\t{}".format(n, importance)
    sys.stdout.flush()