examples/Parallel/Examples/task1.ipynb

{
 "metadata": {
  "name": "task1"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Simple task farming example"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "from __future__ import print_function\n",
      "from IPython.parallel import Client"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "A `Client.load_balanced_view` is used to get the object used for working with load balanced tasks."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "rc = Client()\n",
      "v = rc.load_balanced_view()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Set the variable `d` on all engines:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "rc[:]['d'] = 30"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Define a function that will be our task:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "def task(a):\n",
      "    return a, 10*d, a*10*d"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Run the task once:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "ar = v.apply(task, 5)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Print the results:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print(\"a, b, c: \", ar.get())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "a, b, c:  [5, 300, 1500]\n"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}