{ "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 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": {} } ] }