examples/parallel/taskmap.ipynb

{
 "metadata": {
  "name": ""
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Load balanced map and parallel function decorator"
     ]
    },
    {
     "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": "code",
     "collapsed": false,
     "input": [
      "rc = Client()\n",
      "v = rc.load_balanced_view()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "result = v.map(lambda x: 2*x, range(10))\n",
      "print(\"Simple, default map: \", list(result))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Simple, default map:  "
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "[0, 2, 4, 6, 8, 10, 12, 14, 16, 18]\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ar = v.map_async(lambda x: 2*x, range(10))\n",
      "print(\"Submitted tasks, got ids: \", ar.msg_ids)\n",
      "result = ar.get()\n",
      "print(\"Using a mapper: \", result)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Submitted tasks, got ids:  ['d482fcb3-f8e9-41ff-ba16-9fd4118324f1', 'e4fe38dd-8a4d-4f3a-a111-e4c9fdbea7c3', '580431f4-ac66-4517-b03e-a58aa690a87b', '19a012cf-5d9d-4cf3-9656-d56263958c0e', '012ebbb5-5def-47ad-a247-20f88d2c8980', '0dea6cdb-5b22-4bac-a1bb-7544c0ef44e6', '909d073f-7eee-42a7-8f3b-8f7aa32e7639', 'be6c7466-d541-47a0-b12d-bc408d40ad77', 'b97b5967-a5a3-45c5-95cc-44e0823fd646', '69b06902-9526-42d9-bda6-c943be19cc5a']\n",
        "Using a mapper:  [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]\n"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "@v.parallel(block=True)\n",
      "def f(x): return 2*x\n",
      "\n",
      "result = f.map(range(10))\n",
      "print(\"Using a parallel function: \", result)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using a parallel function:  [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [],
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}