Interacting with asynchronous parallel tasks in IPython

In this recipe, we will show how to interact with asynchronous tasks running in parallel with ipyparallel.

Getting ready

You need to start the IPython engines (see the previous recipe). The simplest option is to launch them from the IPython Clusters tab in the Notebook dashboard. In this recipe, we use four engines.

How to do it...

1. Let's import a few modules:

   >>> import sys
       import time
       import ipyparallel
       import ipywidgets
       from IPython.display import clear_output, display

2. We create a client:

   >>> rc = ipyparallel.Client()

3. Now, we create a load-balanced view on the IPython engines:

   >>> view = rc.load_balanced_view()

4. We define a simple function for our parallel tasks:

   >>> def f(x):
           import time
           time.sleep(.1)
           return x * x

5. We will run this function on 100 integer numbers in parallel:

   >>> numbers = list(range(100))

6. We execute f on our list numbers in parallel across all...