{ "nbformat": 2, "metadata": { "name": "task_1" }, "worksheets": [ { "cells": [ { "source": "# Simple task farming example", "cell_type": "markdown" }, { "cell_type": "code", "language": "python", "outputs": [], "collapsed": true, "prompt_number": 3, "input": "from IPython.parallel import Client" }, { "source": "A `Client.load_balanced_view` is used to get the object used for working with load balanced tasks.", "cell_type": "markdown" }, { "cell_type": "code", "language": "python", "outputs": [], "collapsed": true, "prompt_number": 4, "input": "rc = Client()\nv = rc.load_balanced_view()" }, { "source": "Set the variable `d` on all engines:", "cell_type": "markdown" }, { "cell_type": "code", "language": "python", "outputs": [], "collapsed": true, "prompt_number": 5, "input": "rc[:]['d'] = 30" }, { "source": "Define a function that will be our task:", "cell_type": "markdown" }, { "cell_type": "code", "language": "python", "outputs": [], "collapsed": true, "prompt_number": 6, "input": "def task(a):\n return a, 10*d, a*10*d" }, { "source": "Run the task once:", "cell_type": "markdown" }, { "cell_type": "code", "language": "python", "outputs": [], "collapsed": true, "prompt_number": 7, "input": "ar = v.apply(task, 5)" }, { "source": "Print the results:", "cell_type": "markdown" }, { "cell_type": "code", "language": "python", "outputs": [ { "output_type": "stream", "text": "a, b, c: [5, 300, 1500]" } ], "collapsed": false, "prompt_number": 8, "input": "print \"a, b, c: \", ar.get()" } ] } ] }