REST demo.ipynb

{
 "metadata": {
  "name": "REST demo"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Concurrent REST requests with threads"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This is a simple demo of using threads for concurrent consumption of a REST API.\n",
      "\n",
      "First, we define our simple function for processing a single resource ID.\n",
      "It has three basic steps:\n",
      "\n",
      "1. GET the record\n",
      "2. parse / process it\n",
      "3. PUT to update the record"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import requests\n",
      "\n",
      "url_t = \"http://localhost:8000/records/%i\"\n",
      "\n",
      "def process_id(id):\n",
      "    \"\"\"process a single ID\"\"\"\n",
      "    # fetch the data\n",
      "    r = requests.get(url_t % id)\n",
      "    # parse the JSON reply\n",
      "    data = r.json()\n",
      "    # and update some data with PUT\n",
      "    requests.put(url_t % id, data=data)\n",
      "    return data\n",
      "    "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Our dummy webservice is just a simple REST service that serves up the `/usr/share/dict/words` word list:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import os\n",
      "ip = get_ipython()\n",
      "print ip.pycolorize(open(os.path.expanduser(\"~/temp/echo.py\")).read())"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\u001b[1;34m\"\"\"Simple dummy REST webservice\u001b[0m\n",
        "\u001b[1;34m\u001b[0m\n",
        "\u001b[1;34mIncludes artificial delay in requests to allow simulation of concurrent access.\u001b[0m\n",
        "\u001b[1;34m\"\"\"\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;32mimport\u001b[0m \u001b[0mjson\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;32mfrom\u001b[0m \u001b[0mtornado\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mhttpserver\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mHTTPServer\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;32mfrom\u001b[0m \u001b[0mtornado\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mioloop\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mIOLoop\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;32mfrom\u001b[0m \u001b[0mtornado\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mweb\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;32mfrom\u001b[0m \u001b[0mtornado\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0moptions\u001b[0m \u001b[1;32mimport\u001b[0m \u001b[0mdefine\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moptions\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mparse_command_line\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[0mdefine\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"port\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdefault\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m8000\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mhelp\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"run on the given port\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mint\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[0mdefine\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"delay\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mdefault\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m0.1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mhelp\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"artificial delay for GET requests\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtype\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfloat\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;31m# load simple word list, or RESTful data\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[0mwords\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"/usr/share/dict/words\"\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m    \u001b[1;32mfor\u001b[0m \u001b[0mline\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m        \u001b[0mwords\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mline\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstrip\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;32mclass\u001b[0m \u001b[0mMainHandler\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mweb\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mRequestHandler\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m    \u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m    \u001b[1;33m@\u001b[0m\u001b[0mweb\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0masynchronous\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m    \u001b[1;32mdef\u001b[0m \u001b[0mget\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m        \u001b[0mindex\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0marg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m        \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mjson\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdumps\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mindex\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mindex\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mword\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mwords\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mindex\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m        \u001b[1;31m# artificial delay for finish:\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m        \u001b[0mloop\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mIOLoop\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m        \u001b[0mloop\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0madd_timeout\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mloop\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0moptions\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdelay\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfinish\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m    \u001b[1;32mdef\u001b[0m \u001b[0mput\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0marg\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m        \u001b[1;34m\"\"\"put does nothing\"\"\"\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m        \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mjson\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdumps\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdict\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mstatus\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m\"ok\"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;32mdef\u001b[0m \u001b[0mmain\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m    \u001b[0mparse_command_line\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m    \u001b[0mapplication\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mweb\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mApplication\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m        \u001b[1;33m(\u001b[0m\u001b[1;34mr\"/records/(.*)\"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mMainHandler\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m    \u001b[1;33m]\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m    \u001b[0mhttp_server\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mHTTPServer\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mapplication\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m    \u001b[0mhttp_server\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mlisten\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0moptions\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mport\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m    \u001b[0mIOLoop\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minstance\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstart\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m\u001b[1;32mif\u001b[0m \u001b[0m__name__\u001b[0m \u001b[1;33m==\u001b[0m \u001b[1;34m\"__main__\"\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\n",
        "\u001b[1;33m\u001b[0m    \u001b[0mmain\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now fetch some answers from the service (it should take a bit more than N/10 seconds, since we are using an artificial delay of 100ms)."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%time answers = [ process_id(n) for n in range(32) ]\n",
      "answers"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "CPU times: user 116 ms, sys: 16.2 ms, total: 133 ms\n",
        "Wall time: 3.41 s\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 3,
       "text": [
        "[{u'index': 0, u'word': u'A'},\n",
        " {u'index': 1, u'word': u'a'},\n",
        " {u'index': 2, u'word': u'aa'},\n",
        " {u'index': 3, u'word': u'aal'},\n",
        " {u'index': 4, u'word': u'aalii'},\n",
        " {u'index': 5, u'word': u'aam'},\n",
        " {u'index': 6, u'word': u'Aani'},\n",
        " {u'index': 7, u'word': u'aardvark'},\n",
        " {u'index': 8, u'word': u'aardwolf'},\n",
        " {u'index': 9, u'word': u'Aaron'},\n",
        " {u'index': 10, u'word': u'Aaronic'},\n",
        " {u'index': 11, u'word': u'Aaronical'},\n",
        " {u'index': 12, u'word': u'Aaronite'},\n",
        " {u'index': 13, u'word': u'Aaronitic'},\n",
        " {u'index': 14, u'word': u'Aaru'},\n",
        " {u'index': 15, u'word': u'Ab'},\n",
        " {u'index': 16, u'word': u'aba'},\n",
        " {u'index': 17, u'word': u'Ababdeh'},\n",
        " {u'index': 18, u'word': u'Ababua'},\n",
        " {u'index': 19, u'word': u'abac'},\n",
        " {u'index': 20, u'word': u'abaca'},\n",
        " {u'index': 21, u'word': u'abacate'},\n",
        " {u'index': 22, u'word': u'abacay'},\n",
        " {u'index': 23, u'word': u'abacinate'},\n",
        " {u'index': 24, u'word': u'abacination'},\n",
        " {u'index': 25, u'word': u'abaciscus'},\n",
        " {u'index': 26, u'word': u'abacist'},\n",
        " {u'index': 27, u'word': u'aback'},\n",
        " {u'index': 28, u'word': u'abactinal'},\n",
        " {u'index': 29, u'word': u'abactinally'},\n",
        " {u'index': 30, u'word': u'abaction'},\n",
        " {u'index': 31, u'word': u'abactor'}]"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Now we define a function that calls our single-id function for a range of IDs.\n",
      "Simple enough."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def process_id_range(id_range, store=None):\n",
      "    \"\"\"process a number of ids, storing the results in a dict\"\"\"\n",
      "    if store is None:\n",
      "        store = {}\n",
      "    for id in id_range:\n",
      "        store[id] = process_id(id)\n",
      "    return store"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "This does the same thing as the list comprehension above (but with a dict)\n",
      "in a single function call:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%time s = process_id_range(range(32));\n",
      "s"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "CPU times: user 118 ms, sys: 15.6 ms, total: 134 ms\n",
        "Wall time: 3.42 s\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "{0: {u'index': 0, u'word': u'A'},\n",
        " 1: {u'index': 1, u'word': u'a'},\n",
        " 2: {u'index': 2, u'word': u'aa'},\n",
        " 3: {u'index': 3, u'word': u'aal'},\n",
        " 4: {u'index': 4, u'word': u'aalii'},\n",
        " 5: {u'index': 5, u'word': u'aam'},\n",
        " 6: {u'index': 6, u'word': u'Aani'},\n",
        " 7: {u'index': 7, u'word': u'aardvark'},\n",
        " 8: {u'index': 8, u'word': u'aardwolf'},\n",
        " 9: {u'index': 9, u'word': u'Aaron'},\n",
        " 10: {u'index': 10, u'word': u'Aaronic'},\n",
        " 11: {u'index': 11, u'word': u'Aaronical'},\n",
        " 12: {u'index': 12, u'word': u'Aaronite'},\n",
        " 13: {u'index': 13, u'word': u'Aaronitic'},\n",
        " 14: {u'index': 14, u'word': u'Aaru'},\n",
        " 15: {u'index': 15, u'word': u'Ab'},\n",
        " 16: {u'index': 16, u'word': u'aba'},\n",
        " 17: {u'index': 17, u'word': u'Ababdeh'},\n",
        " 18: {u'index': 18, u'word': u'Ababua'},\n",
        " 19: {u'index': 19, u'word': u'abac'},\n",
        " 20: {u'index': 20, u'word': u'abaca'},\n",
        " 21: {u'index': 21, u'word': u'abacate'},\n",
        " 22: {u'index': 22, u'word': u'abacay'},\n",
        " 23: {u'index': 23, u'word': u'abacinate'},\n",
        " 24: {u'index': 24, u'word': u'abacination'},\n",
        " 25: {u'index': 25, u'word': u'abaciscus'},\n",
        " 26: {u'index': 26, u'word': u'abacist'},\n",
        " 27: {u'index': 27, u'word': u'aback'},\n",
        " 28: {u'index': 28, u'word': u'abactinal'},\n",
        " 29: {u'index': 29, u'word': u'abactinally'},\n",
        " 30: {u'index': 30, u'word': u'abaction'},\n",
        " 31: {u'index': 31, u'word': u'abactor'}}"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And finally the real point of this whole exercise,\n",
      "we can partition a list of IDs and assign sub-lists to threads,\n",
      "so that we can have some requests running concurrently."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from threading import Thread"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "def threaded_process(nthreads, id_range):\n",
      "    \"\"\"process the id range in a specified number of threads\"\"\"\n",
      "    store = {}\n",
      "    threads = []\n",
      "    # create the threads\n",
      "    for i in range(nthreads):\n",
      "        ids = id_range[i::nthreads]\n",
      "        t = Thread(target=process_id_range, args=(ids,store))\n",
      "        threads.append(t)\n",
      "    \n",
      "    # start the threads\n",
      "    [ t.start() for t in threads ]\n",
      "    # wait for the threads to finish\n",
      "    [ t.join() for t in threads ]\n",
      "    return store\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "If we test this, we will see that adding threads allows this to complete faster.\n",
      "Given the nature of the dummy workload, this should actually scale to almost 100 threads."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import time"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "id_range = range(100)\n",
      "tic = time.time()\n",
      "reference = process_id_range(id_range)\n",
      "reftime = time.time() - tic\n",
      "print 1, reftime\n",
      "\n",
      "nlist = [1,2,4,8,16,32,64]\n",
      "tlist = [reftime]\n",
      "for nthreads in nlist[1:]:\n",
      "    tic = time.time()\n",
      "    ans = threaded_process(nthreads, id_range)\n",
      "    toc = time.time()\n",
      "    print nthreads, toc-tic\n",
      "    assert ans == reference\n",
      "    tlist.append(toc-tic)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1 10.8778159618\n",
        "2"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 5.70237803459\n",
        "4"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 3.02138209343\n",
        "8"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 1.79273200035\n",
        "16"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 1.00950598717\n",
        "32"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 0.682367086411\n",
        "64"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " 0.624274015427\n"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.kernel.zmq.pylab.backend_inline].\n",
        "For more information, type 'help(pylab)'.\n"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.loglog(nlist, [ len(id_range) / t for t in tlist], '-o')\n",
      "plt.xlabel(\"n threads\")\n",
      "plt.ylabel(\"requests / sec\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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w4cPlcrm0f//+wPcqLS3V3r175XA41N7erh07digtLU3z5s1Tbm6u\nKioqPs+/JoBehCNuAIxyLUt63HrrrfrRj36kP//5z4EjY1f7vaOjo/Xss89qzZo12rJli7xer7Kz\ns5Weni5JevDBB7VixQq53W4NHjxYN998cyASv/Wtb2nt2rUqLCyU3+/XwIEDNXv2bEmdR/UuXLig\nZcuWKT4+XvHx8YEbJwDgszisaznHAAAAANtwqhQAAMAQhBsAAIAhCDcAAABDEG4AAACGINwAAAAM\nQbgBAAAYgnADAAAwBOEGAABgiP8PN7XBlv+F9OsAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x108ba6dd0>"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "And, logically enough, we peak around 50 threads, because anything between 50 and 99 threads\n",
      "there is at least one thread that processes two requests.\n",
      "All the other threads end up waiting."
     ]
    }
   ],
   "metadata": {}
  }
 ]
}