#!/usr/bin/env python
# coding: utf-8

# > This is one of the 100 recipes of the [IPython Cookbook](http://ipython-books.github.io/), the definitive guide to high-performance scientific computing and data science in Python.
# 

# # 5.9. Distributing Python code across multiple cores with IPython

# First, we launch 4 IPython engines with `ipcluster start -n 4` in a console.

# Then, we create a client that will act as a proxy to the IPython engines. The client automatically detects the running engines.

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from IPython.parallel import Client
rc = Client()


# Let's check the number of running engines.

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rc.ids


# To run commands in parallel over the engines, we can use the %px magic or the %%px cell magic.

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get_ipython().run_cell_magic('px', '', 'import os\nprint("Process {0:d}.".format(os.getpid()))\n')


# We can specify which engines to run the commands on using the --targets or -t option.

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get_ipython().run_cell_magic('px', '-t 1,2', '# The os module has already been imported in the previous cell.\nprint("Process {0:d}.".format(os.getpid()))\n')


# By default, the %px magic executes commands in blocking mode: the cell returns when the commands have completed on all engines. It is possible to run non-blocking commands with the --noblock or -a option. In this case, the cell returns immediately, and the task's status and the results can be polled asynchronously from the IPython interactive session.

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get_ipython().run_cell_magic('px', '-a', 'import time\ntime.sleep(5)\n')


# The previous command returned an ASyncResult instance that we can use to poll the task's status.

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print(_.elapsed, _.ready())


# The %pxresult blocks until the task finishes.

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get_ipython().run_line_magic('pxresult', '')


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print(_.elapsed, _.ready())


# IPython provides convenient functions for most common use-cases, like a parallel map function.

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v = rc[:]
res = v.map(lambda x: x*x, range(10))


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print(res.get())


# > You'll find all the explanations, figures, references, and much more in the book (to be released later this summer).
# 
# > [IPython Cookbook](http://ipython-books.github.io/), by [Cyrille Rossant](http://cyrille.rossant.net), Packt Publishing, 2014 (500 pages).