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Sort profiles in cluster tab.
Sort profiles in cluster tab.

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taskmap.ipynb
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Load balanced map and parallel function decorator

In [1]:
from IPython.parallel import Client
In [3]:
rc = Client()
v = rc.load_balanced_view()
In [4]:
result = v.map(lambda x: 2*x, range(10))
print "Simple, default map: ", list(result)
Simple, default map:  
[0, 2, 4, 6, 8, 10, 12, 14, 16, 18]
In [5]:
ar = v.map_async(lambda x: 2*x, range(10))
print "Submitted tasks, got ids: ", ar.msg_ids
result = ar.get()
print "Using a mapper: ", result
Submitted tasks, got ids:  ['5100a4c7-73a4-4832-aa91-e774f6f3ede8', 'd0cae1cf-2b32-4092-9eb7-f17b43fb3849', 'e08d3ee2-f221-47fe-9556-ed938e692030', '065585e4-cdf9-4240-a5fe-e44b2ae5d023', 'd2162f23-68e5-4318-ba1e-e34fd03a72ac', '5b3b835f-2099-4a70-9896-d1aa810c77e6', 'e2c2a823-bd44-4f91-8db3-c154d0d86e56', '991e0c25-f98a-44b5-9d9e-889d4180b9a5', '4ad41221-28bd-482f-a300-97c404648161', '5b730eb3-e0bb-4cdd-b228-c3b8d158828a']
Using a mapper:  [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]
In [6]:
@v.parallel(block=True)
def f(x): return 2*x

result = f.map(range(10))
print "Using a parallel function: ", result
Using a parallel function:  [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]