[IPython-user] Iterator version of TaskClient.map() that returns results as they become available?

Jon Olav Vik jonovik@gmail....
Thu Feb 11 03:37:37 CST 2010

I have lots of trivially parallel computations and will store the results to 
disk. Output order does not matter.

The TaskClient.map() function or TaskClient.parallel() decorator is convenient 
and load-balanced, but blocks until all the results are in. What I would like 
instead is a map()-like iterator that returns each result as it becomes 
available; similarly, an iparallel() decorator that returns an iterator. Then I 
could do:

from IPython.kernel import client
tc = client.TaskClient()
# Tasks that take an varying amount of time
import numpy as np
import time
@tc.iparallel()   # <-- nifty feature to be written
def f(x):
    return -x
N = 1000
for result in f(range(N)):
    print result # or save to file, or plot a data point

By flushing the output from time to time, I could then watch results take shape 
as they get computed.

I tried digging into the source code for TaskClient.map(), but was overwhelmed 
by the layers and intricacies of Twisted. Any pointers in the right direction 
would be highly appreciated.

Jon Olav

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