Analyzing Deferred JavaScript with WebPageTest.org

WebPageTest.org Analysis Scaffold.ipynb

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 "metadata": {
  "name": "WebPageTest.org Analysis Scaffold"
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   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "# WebPageTest Analysis Scaffold\n\n[WebPageTest](WebPageTest.org) is a great way to get detailed browser performance data. Since they have the option to record video, they can do a really good job of determining when a page has been painted.\n\nIf you've used the service much, you've probably noticed the high variability of data from run to run. This notebook contains helper functions to download data, combine data from multiple tests, and to draw some box plots to get a feel for performance. I've found this aggregated view to be much more reliable than switching between tabs for multiple runs to get a \"feel\" for the data, as you'd expect."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "import logging\nlogging.getLogger().setLevel(logging.DEBUG)",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 406
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "## Fetching data and extracting metrics\n\nLet's first set up some utility functions for fetching data about a test from WPT. The data structure returned by this response and the test IDs are the core of what this notebook does."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "# Map from WebPageTest.org Test ID to the \"data\" section of a successful JSON response\n# from http://www.webpagetest.org/jsonResult.php?test={Test ID}\nfetched = {}",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 188
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "import copy as copy_module  # numpy has a copy that overrides this when we import * from matplotlib\nimport json\nimport pprint\nimport urllib\n\n\ndef fetch_test_json(test_id):\n    \"\"\"Return the \"data\" section of a JSON response from WPT.\"\"\"\n    response = urllib.urlopen(\"http://www.webpagetest.org/jsonResult.php?test=\" + test_id) \n    response_json = json.loads(response.read())\n    # Avoiding returning bad data.\n    assert response_json[\"statusCode\"] == 200, (response_json[\"statusCode\"], response_json[\"statusText\"])\n    assert \"completed\" in response_json[\"data\"]\n    return response_json[\"data\"]\n\n\ndef cached_fetch(wpt_id):\n    \"\"\"Return the \"data\" section of a JSON response from WPT, maybe from the cache.\"\"\"\n    if wpt_id not in fetched:\n        logging.info(\"Fetching %s\" % wpt_id)\n        fetched[wpt_id] = fetch_test_json(wpt_id)\n    return fetched[wpt_id]\n\n\ndef combine_wpt(*test_ids):\n    \"\"\"Combine multiple tests into one structure with many runs.\n    \n    NOTE: you might need to expose additional metadata here.\n    \"\"\"\n    test_ids = list(set(test_ids))  # de-dupe\n    combined_runs = {}\n    responses = map(cached_fetch, test_ids)\n    run_idx = 1\n    for response in responses:\n        for _, run in response[\"runs\"].iteritems():\n            run = copy_module.copy(run)  # shallow copy since we will add keys\n            run[\"testId\"] = response[\"id\"]\n            combined_runs[str(run_idx)] = run\n            run_idx += 1\n    return {\"summary\": \"(%s)\" % \",\".join(sorted(test_ids)),\n            \"runs\": combined_runs,\n            }\n\n\ndef wpt_response(wpt_id_or_response):\n    \"\"\"For those times when you may have a WPT ID, a JSON response, or a combined response.\"\"\"\n    if isinstance(wpt_id_or_response, basestring):\n        return cached_fetch(wpt_id_or_response)\n    else:\n        # Assume it's already a response.\n        return wpt_id_or_response",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 408
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "A test has a bunch of runs, and if you select the \"capture video\" button, you'll also get information about visual completeness and when a page starts to render.\n\nFor this analysis, firstPaint/render, SpeedIndex, and visualComplete were important metrics, but you could analyze any particular per-run metric. Update `extract_view_metrics` to provide the relevant abstraction for the graphing that comes in a later section."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "def pageload_ttfb(view, ignore_errors=False):\n    \"\"\"wpt.org reports TTFB from first request, which might be a pageload,\n    or maybe a beacong fired from a prior pageload (for the repeat view).\n    \n    We want the TTFB time of the pageload request.\n    \n    Unfortunately this fails for Firefox over HTTPS when WPT seems to list\n    connections and not resources.\n    \"\"\"\n    pageload_request = None\n    url = view[\"URL\"].replace(\"&\", \"&\")  # maybe a bug from serializing to XML?\n    for request in view[\"requests\"]:\n        if request[\"full_url\"] == url:\n            pageload_request = request\n            break\n    if pageload_request:\n        # ttfb_end was Empirically chosen from ttfb_start, ttfb_ms, ttfb_end,\n        # since it matched what I expected for TTFB in cases I looked at.\n        return pageload_request[\"ttfb_end\"], pageload_request\n    else:\n        if not ignore_errors:\n            message = \"%s not found in %s\" % (\n                url, tuple(request[\"full_url\"] for request in view[\"requests\"]))\n            logging.warn(message)\n        return None, None\n\n\ndef extract_view_metrics(view, test_id=None):\n    \"\"\"view is a dict, e.g., data.runs.1.firstView\"\"\"\n    page_ttfb, _ = pageload_ttfb(view, ignore_errors=True)\n    if not page_ttfb:\n        page_ttfb = view[\"TTFB\"]\n    metrics = {\"SpeedIndex\": view[\"SpeedIndex\"],\n               \"TTFB\": page_ttfb}\n    # Make absolute metrics relative to TTFB in order to reduce variance.\n    for abs_metric in (\"firstPaint\", \"render\",\n                       \"domContentLoadedEventStart\", \"domContentLoadedEventEnd\",\n                       \"loadEventStart\", \"loadEventEnd\", \"visualComplete\"):\n        # WPT responses sometimes use 0 to indicate \"no value\",\n        # e.g., for firstPaint on Firefox.\n        value = view[abs_metric]\n        if value != 0:\n            value -= page_ttfb\n        else:\n            #logging.info(\"0-value %s (test_id=%s, url=%s)\" % (abs_metric, test_id, view[\"URL\"]))\n            pass\n        metrics[abs_metric] = value\n    return metrics",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 409
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "## Plotting metrics\n\nHere are the graphing helpers. These will extract fields from each run and view and plot them."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "%matplotlib inline\nimport matplotlib.pyplot as plt\nfrom pylab import *\n\n\ndef run_iter(response):\n    \"\"\"yield runs in a response\"\"\"\n    for run_idx in xrange(len(response[\"runs\"])):\n        run_key = str(run_idx + 1)  # 1...N\n        run = response[\"runs\"][run_key]\n        if run and run[\"firstView\"] and run[\"repeatView\"]:  # ignore runs with missing data\n            yield run, run_key, run_idx\n\n\ndef concat_metrics(response, view_name, metric_name):\n    \"\"\"Return list of all data points for a metric in firstView or repeatView\"\"\"\n    return [extract_view_metrics(run[view_name], test_id=run.get(\"testId\", None))[metric_name]\n            for run, _, _ in run_iter(response)]\n        \n\ndef boxplot_it(responses, labels, metric_names=[], title=\"\", figsize=None):\n    \"\"\"Make a box plot for firstView and repeatView over some metrics.\n    \n    responses should be a list of WPT response data objects (or combined objects),\n    and labels should have the same length, each label corresponding to a response.\n    \n    metric_names are read from the structure returned by extract_view_metrics.\n    \"\"\"\n    assert len(responses) == len(labels), (len(responses), labels)\n    plot_data = {\"firstView\": [],\n                 \"repeatView\": [],\n                 }\n    plot_labels = []\n    for response, label in zip(responses, labels):\n        for metric_name in metric_names:\n            plot_labels.append(\"%s %s\" % (metric_name, label))\n            plot_data[\"firstView\"].append(concat_metrics(response, \"firstView\", metric_name))\n            plot_data[\"repeatView\"].append(concat_metrics(response, \"repeatView\", metric_name))\n    \n    plt.figure(figsize=figsize or (16, len(plot_data[\"firstView\"]) - 1))\n    plt.subplot(121)\n    plt.title(\"firstView\")\n    plt.boxplot(plot_data[\"firstView\"], labels=plot_labels, vert=False)\n    _, xmax = plt.xlim()\n    plt.xlim(xmin=0, xmax=min(xmax, 6000))\n    \n    plt.subplot(122)\n    plt.title(\"repeatView\")\n    plt.boxplot(plot_data[\"repeatView\"], labels=plot_labels, vert=False)\n    _, xmax = plt.xlim()\n    plt.xlim(xmin=0, xmax=min(xmax, 6000))\n    \n    plt.suptitle(title)\n    plt.subplots_adjust(wspace=0.6, hspace=0.3)\n    plt.show()",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 410
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "## Putting it all together\n\nEnter the WPT test IDs you care about into this next cell and evaluate it to start fetching results! In this example we'll combine and compare a bunch of data around deferred JavaScript loading.\n\n* The **old** method is just a normal page load, our JavaScript lives at the bottom right before `</body>`.\n* The **attr** method uses the `defer` attribute on a `<script>` and collects inline snippets to run when the DOM is ready.\n* The **labjs** method uses [LABjs](http://labjs.com/) and starts downloading and executing JavaScript as quickly as possible. Note this prevents the preload scanner from starting early JavaScript downloads."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "# Labels should have the same length as the responses list in tests below.\nlabels = ('old',\n          'attr',\n          'labjs',)\n\n# A list of (test_name, (test_response, ...)) pairs.\ntests = (\n    # Logged-out homepage\n    # old\thttps://www.khanacademy.org/?perfilek=0\n    # attr\thttps://www.khanacademy.org/?perfilek=0&deferjsk=1&deferjsk_use_attr=1\n    # labjs\thttps://www.khanacademy.org/?perfilek=0&deferjsk=1&labjs_global_queue=0\n    (\"Logged-out homepage\", (\n        combine_wpt(\"150205_VZ_142H\",\"150202_WE_1BVZ\",\"150205_ZS_173A\",\"150205_29_173B\",\"150205_PH_173J\"),\n        combine_wpt(\"150205_2J_142T\",\"150203_QQ_123Z\",\"150205_TX_17BT\",\"150205_M4_17BX\",\"150205_QW_17C1\"),\n        combine_wpt(\"150203_FX_1242\",\"150205_9J_179T\",\"150205_EE_179X\",\"150205_S3_179Y\",\"150205_16_17A2\"),\n        )),\n    # Video page for Creating a number grid\n    # old\thttps://www.khanacademy.org/math/early-math/cc-early-math-counting-topic/cc-early-math-counting/v/number-grid?perfilek=0\n    # attr\thttps://www.khanacademy.org/math/early-math/cc-early-math-counting-topic/cc-early-math-counting/v/number-grid?perfilek=0&deferjsk=1&deferjsk_use_attr=1\n    # labjs\thttps://www.khanacademy.org/math/early-math/cc-early-math-counting-topic/cc-early-math-counting/v/number-grid?perfilek=0&deferjsk=1&labjs_global_queue=0\n    (\"Video page for Creating a number grid\", (\n        combine_wpt(u'150205_9D_13RT', \"150205_1H_17RS\", \"150205_9J_17RW\", \"150205_2Y_17S2\", \"150205_TA_17S9\"),\n        combine_wpt('150205_KS_1A0S', '150205_A9_1A0V', '150205_6R_1A0Y', '150205_V8_1A0Z', '150205_PY_1A10'),\n        combine_wpt(u'150205_C3_13RV', '150205_5T_17Y9', '150205_S7_17YB', '150205_GJ_17YC'),\n        )),\n    # Whole numbers on the number line\n    # old     https://www.khanacademy.org/math/arithmetic/multiplication-division/multiplication_fun/e/number_line?perfilek=0\n    # attr    https://www.khanacademy.org/math/arithmetic/multiplication-division/multiplication_fun/e/number_line?perfilek=0&deferjsk=1&deferjsk_use_attr=1\n    # labjs   https://www.khanacademy.org/math/arithmetic/multiplication-division/multiplication_fun/e/number_line?perfilek=0&deferjsk=1&labjs_global_queue=0\n    (\"Whole numbers on the number line\", (\n        combine_wpt('150209_FD_12XS', '150209_K1_12XW', '150209_W5_12XX', '150209_XJ_12XY', '150209_C4_12XZ'),\n        combine_wpt('150209_54_136C', '150209_34_136E', '150209_GC_136F', '150209_W3_136G', '150209_MH_136J'),\n        combine_wpt('150209_ER_137D', '150209_XZ_137E', '150209_HD_137G', '150209_9C_137J', '150209_PX_137M'),\n        )),\n    # Topic page for Early Math\n    # old\thttps://www.khanacademy.org/math/early-math?perfilek=0\n    # attr\thttps://www.khanacademy.org/math/early-math?perfilek=0&deferjsk=1&deferjsk_use_attr=1\n    # labjs\thttps://www.khanacademy.org/math/early-math?perfilek=0&deferjsk=1&labjs_global_queue=0\n    (\"Topic page for Early Math\", (\n        combine_wpt(\"150205_WF_187X\", '150205_29_1880', '150205_JS_1887', '150205_ZG_196C', ),\n        combine_wpt(\"150205_J7_18AQ\", '150205_KA_18AT', '150205_C6_19F1', '150205_PG_19HM', ),\n        combine_wpt(\"150205_TY_13ZT\", '150205_EA_189H', '150205_Y6_189J', '150205_E9_189N', '150205_W1_196X'),\n        )),\n    # Challenge: H for Hopper\n    # old   https://www.khanacademy.org/computing/computer-programming/programming/drawing-basics/p/challenge-h-for-hopper?perfilek=0\n    # attr\thttps://www.khanacademy.org/computing/computer-programming/programming/drawing-basics/p/challenge-h-for-hopper?perfilek=0&deferjsk=1&deferjsk_use_attr=1\n    # labjs\thttps://www.khanacademy.org/computing/computer-programming/programming/drawing-basics/p/challenge-h-for-hopper?perfilek=0&deferjsk=1&labjs_global_queue=0\n    (\"Challenge: H for Hopper\", (\n        combine_wpt(\"150205_QA_19RS\", '150205_VG_19RY', '150205_C2_19RZ', '150205_TE_19S3', '150205_M0_19S6'),\n        combine_wpt('150205_ZB_1A7C', '150205_E4_1A7D', '150205_C2_1A7F', '150205_CT_1A7G', '150205_QP_1A7J'),\n        combine_wpt('150205_G4_1A5T', '150205_FV_1A5W', '150205_JT_1A5Z', '150205_0T_1A62', '150205_01_1A63'),\n        )),\n\n    (\"Logged-out homepage (IE 10 on https)\", (\n        combine_wpt('150205_Y9_1AJV', '150205_5V_1AJX', '150205_28_1AK0'),\n        combine_wpt('150205_YH_1AMN', '150205_E6_1AMP', '150205_7N_1AMS'),\n        combine_wpt('150205_JM_1AKZ', '150205_18_1AM2', '150205_43_1AM4'),\n        )),\n    (\"Logged-out homepage (Nexus 5 - Chrome)\", (\n        combine_wpt('150205_97_1BCB', '150205_DM_1BCE', '150205_ZC_1BCT'),\n        combine_wpt('150206_KD_RA', '150210_ZZ_1WR'),\n        combine_wpt('150206_5T_QC', '150206_9Z_QQ'),\n        )),\n    (\"Video page for Creating a number grid - DSL\", (\n        combine_wpt('150209_2H_13F1', '150209_32_13F3', '150209_4T_13F4', '150209_C3_13F6', '150209_J3_13F7'),\n        combine_wpt('150209_2X_13JW', '150209_RB_13JX', '150209_1V_13JZ', '150209_4A_13K0', '150209_A5_13K1'),\n        combine_wpt('150209_H9_13KW', '150209_CN_13KX', '150209_2E_13KY', '150209_DS_13M0', '150209_M5_13M1'),\n        )),\n    (\"Video page for Creating a number grid - Firefox\", (\n        combine_wpt('150209_HC_14Q1', '150209_S6_14Q3', '150209_E0_14Q4', '150209_ZD_14Q7', '150209_K9_14QA'),\n        combine_wpt('150209_NK_14SD', '150209_PH_14SF', '150209_GQ_14SG', '150209_49_14SJ', '150209_BP_14SM'),\n        combine_wpt('150209_E8_14SR', '150209_CC_14SS', '150209_R0_14SV', '150209_T1_14SW', '150209_AJ_14SY'),\n        )),\n    )\n\n\ndef plot_one(test_name, test_items):\n    responses = map(wpt_response, test_items)\n    print test_name\n    for response, label in zip(responses, labels):\n        print \"%s\\truns:%s\\t%s\" % (label, len(response[\"runs\"]), response[\"summary\"])\n    #boxplot_it(responses, labels, metric_names=(\"firstPaint\", \"visualComplete\", \"SpeedIndex\"), title=key)\n    boxplot_it(responses, labels, [\"TTFB\", \"SpeedIndex\"], title=test_name + \" TTFB, SpeedIndex\")\n    for metric_name in (\"firstPaint\", \"visualComplete\",):\n        # In general, LABjs has artificially low DOMReady, defer attr has slightly lower DOMReady\n        # (since some JS runs after DOMReady and not before it,\n        # thus end-of-DOMReady tends to be the same as before).\n        #                        \"domContentLoadedEventStart\", \"domContentLoadedEventEnd\"):\n        boxplot_it(responses, labels, [metric_name], title=test_name + \" \" + metric_name)\n        \ndef plot_all():\n    for test_name, test_items in tests:\n        plot_one(test_name, test_items)\n",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 413
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "## Logged-out homepage\n\n* SpeedIndex for LABjs on firstView in Chrome is slightly better, but that effect might be explained by the tighter spread for TTFB times.\n  * On IE10, the LABjs benefit is more pronounced, the median looks to be about half a second better, and firstPaint looks ~300ms better.\n  * On the Nexus 5, the LABjs spread for SpeedIndex and for visualComplete is much better.\n* Median visualComplete is better by ~150ms for both deferred measures on Chrome, and about that much worse on IE10."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "for test_name in (\"Logged-out homepage\",\n                  \"Logged-out homepage (IE 10 on https)\",\n                  \"Logged-out homepage (Nexus 5 - Chrome)\"):\n    plot_one(test_name, dict(tests)[test_name])",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "Logged-out homepage\nold\truns:45\t(150202_WE_1BVZ,150205_29_173B,150205_PH_173J,150205_VZ_142H,150205_ZS_173A)\nattr\truns:45\t(150203_QQ_123Z,150205_2J_142T,150205_M4_17BX,150205_QW_17C1,150205_TX_17BT)\nlabjs\truns:45\t(150203_FX_1242,150205_16_17A2,150205_9J_179T,150205_EE_179X,150205_S3_179Y)\n"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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eXWS5L+6edt9995kPP/zQGGPM7NmzTUBAgDEmv3tamzZtzLFjx8zp06dNSEhI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\nAABJRU5ErkJggg==\n",
       "text": "<matplotlib.figure.Figure at 0x142017b90>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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i8ODBD11GeXUjIiKi2sUxCcckRESWQCNS8p1j5UyePBkbNmzAM888g4kTJ6Jl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\n",
       "text": "<matplotlib.figure.Figure at 0x142344c10>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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FdnZ2+Mc//qHMM3PmTBQWFuLOO++Evb19g/XV2bp1KyoqKuDu7o5evXohNDRU5/TACRMm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\nIiIiIiIzwkIAERERERERkRn5/9O2TO72DUtUAAAAAElFTkSuQmCC\n",
       "text": "<matplotlib.figure.Figure at 0x142142f10>"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "Logged-out homepage (IE 10 on https)\nold\truns:27\t(150205_28_1AK0,150205_5V_1AJX,150205_Y9_1AJV)\nattr\truns:27\t(150205_7N_1AMS,150205_E6_1AMP,150205_YH_1AMN)\nlabjs\truns:27\t(150205_18_1AM2,150205_43_1AM4,150205_JM_1AKZ)\n"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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eXr16dUnS8ePH1a1bN4WEhCggIEAJCQkF7W4AAFAA+iX0S+AMcXEluz5QbpkC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\nreZy4S3kBzgEn61A0XHeFF6+beBNNI6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       "text": "<matplotlib.figure.Figure at 0x142329c10>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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DTk5OyM/Pr3OclRuzzp07o6CgADExMZg6darJMdnb2yMvL+++8ebl5ck3Ytm2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\nAAAAAElFTkSuQmCC\n",
       "text": "<matplotlib.figure.Figure at 0x142125fd0>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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9GmfOnFGSBiIioraEeQnzEiIiarx6i/+AgADk5OQgOzsbZ86cgYuLS42D6KhR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\n6wAAAABJRU5ErkJggg==\n",
       "text": "<matplotlib.figure.Figure at 0x1423cefd0>"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "Logged-out homepage (Nexus 5 - Chrome)\nold\truns:19\t(150205_97_1BCB,150205_DM_1BCE,150205_ZC_1BCT)\nattr\truns:9\t(150206_KD_RA)\nlabjs\truns:18\t(150206_5T_QC,150206_9Z_QQ)\n"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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iyyxZskQTJ04s8LuePXvech0AAEB+xCUFIy4BgOqvyN9537FjhzZs2KCEhATV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\nGxgYsOzsbIvH49bX12fhcNguXbrk97DGrLGx0Vp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       "text": "<matplotlib.figure.Figure at 0x13a87fed0>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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uSdfEBQcH48iRI7h37x6ys7Ph5uYGAHjllVekdTMhIQEvv/wyAMDGxkY6RTAxMRHJycnw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\nAAAAAABJRU5ErkJggg==\n",
       "text": "<matplotlib.figure.Figure at 0x140e46ed0>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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0tDRYWVlh586dWL9+Pbp164a0tDTExcU1Wa45a9euxalTp3D27Fl8+eWX+Oc/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\niIiIiIiIiCzI/wdrRZ2i6ATTGQAAAABJRU5ErkJggg==\n",
       "text": "<matplotlib.figure.Figure at 0x113a7a590>"
      }
     ],
     "prompt_number": 417
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "## Video page for Creating a number grid\n\n* Improved SpeedIndex on repeatView for LABjs.\n* ~200-300ms improved firstPaint on repeatView for deferred methods.\n* However, over DSL the existing method wins for repeatView on SpeedIndex, firstPaint, and visualComplete."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "for test_name in (\"Video page for Creating a number grid\",\n                  \"Video page for Creating a number grid - DSL\",\n                  \"Video page for Creating a number grid - Firefox\"):\n    plot_one(test_name, dict(tests)[test_name])",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "Video page for Creating a number grid\nold\truns:44\t(150205_1H_17RS,150205_2Y_17S2,150205_9D_13RT,150205_9J_17RW,150205_TA_17S9)\nattr\truns:45\t(150205_6R_1A0Y,150205_A9_1A0V,150205_KS_1A0S,150205_PY_1A10,150205_V8_1A0Z)\nlabjs\truns:35\t(150205_5T_17Y9,150205_C3_13RV,150205_GJ_17YC,150205_S7_17YB)\n"
      },
      {
       "metadata": {},
       "output_type": "display_data",
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v374KCQlRQECAtmzZUtbhBoA6LyHB1S1AbUZcQlwCAPWaKcPJkydNcHCw6dix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\n4HH/BziOa/bKn5DzAAAAAElFTkSuQmCC\n",
       "text": "<matplotlib.figure.Figure at 0x13a64c090>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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y5uXlyZO4bNq0SSfN7t27ERUVhYKCAmi1WixdulSnw/3tt9/wyCOPYPbs2bh0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\ng4MD8vLy9L4XGBiIbdu24Y0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       "text": "<matplotlib.figure.Figure at 0x13a6ff610>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Ys2YN1q1bh9TUVLRv377WFZ4/fx4jR46El5cXdu3aheTkZKP5tWW9fvjhB7i4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\nRERERGRB/h9vpIdc5fTFtAAAAABJRU5ErkJggg==\n",
       "text": "<matplotlib.figure.Figure at 0x141db0d10>"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "Video page for Creating a number grid - DSL\nold\truns:45\t(150209_2H_13F1,150209_32_13F3,150209_4T_13F4,150209_C3_13F6,150209_J3_13F7)\nattr\truns:45\t(150209_1V_13JZ,150209_2X_13JW,150209_4A_13K0,150209_A5_13K1,150209_RB_13JX)\nlabjs\truns:45\t(150209_2E_13KY,150209_CN_13KX,150209_DS_13M0,150209_H9_13KW,150209_M5_13M1)\n"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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WrFmzJEnTpk3TsGHDJEm7du2Sy+Wy6yrI1q1b1b59e4WFhalDhw7as2eP/d73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\nAJ+jeQcAAAAAwOf+D4LLNiJEFabdAAAAAElFTkSuQmCC\n",
       "text": "<matplotlib.figure.Figure at 0x141ff3490>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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NfHx8KhXFQMmtFKVF/9SpU3H06FEAwOnTp+Hu7g6lUont27fj7NmzAEoeslNaBJSNU1sc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\nRU5ErkJggg==\n",
       "text": "<matplotlib.figure.Figure at 0x13a5f7510>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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WvB91OtOmM0Ud6rIsU6gysJ84cSK2bdumvN6+fTsmTZoEEVE+SGvWrMHcuXOh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\n",
       "text": "<matplotlib.figure.Figure at 0x141dc0dd0>"
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "Video page for Creating a number grid - Firefox\nold\truns:45\t(150209_E0_14Q4,150209_HC_14Q1,150209_K9_14QA,150209_S6_14Q3,150209_ZD_14Q7)\nattr\truns:45\t(150209_49_14SJ,150209_BP_14SM,150209_GQ_14SG,150209_NK_14SD,150209_PH_14SF)\nlabjs\truns:45\t(150209_AJ_14SY,150209_CC_14SS,150209_E8_14SR,150209_R0_14SV,150209_T1_14SW)\n"
      },
      {
       "metadata": {},
       "output_type": "display_data",
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0dLTWr18vSfL399fecvy2Q1pamoKDg087hsTERPXq1avUMnPmzNHo0aOL/axD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\nddAAAAAASUVORK5CYII=\n",
       "text": "<matplotlib.figure.Figure at 0x14205c390>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Owd3dHSqVCseOHcPFixcNLnPkyJEAAGdnZ6SmpkrPG1pOWdevX8fAgQOhUqkQ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\n",
       "text": "<matplotlib.figure.Figure at 0x141e08d90>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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69IGHhwemT5+O/Px8ACXR69dffx0ajQbe3t44ceIE/P394ezsjLVr1wIAdDod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\nORlyKqcUrwAAAABJRU5ErkJggg==\n",
       "text": "<matplotlib.figure.Figure at 0x14236a2d0>"
      }
     ],
     "prompt_number": 418
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "## Whole numbers on the number line\n\n* On repeatView, the best case SpeedIndex for the deferred methods is better than the best case for the normal method. However, they're similar at the median."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "test_name = \"Whole numbers on the number line\"\nplot_one(test_name, dict(tests)[test_name])",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "Whole numbers on the number line\nold\truns:45\t(150209_C4_12XZ,150209_FD_12XS,150209_K1_12XW,150209_W5_12XX,150209_XJ_12XY)\nattr\truns:45\t(150209_34_136E,150209_54_136C,150209_GC_136F,150209_MH_136J,150209_W3_136G)\nlabjs\truns:45\t(150209_9C_137J,150209_ER_137D,150209_HD_137G,150209_PX_137M,150209_XZ_137E)\n"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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PuIS4BAAasgqTd0lq1KiRoqKiFBUVpZCQEL3++uv2QbKowt9aGWO0ZcsWNW7c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\nj46bzHX69oyMDGvn4Nq1awqHwyorK/NknhMTEyo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       "text": "<matplotlib.figure.Figure at 0x134358ed0>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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FQgGFQgF7e3tYW1vjsccew7Vr1wBUHOTz9vYGUDHIPnnyJLKysnDhwgWMGTMGarUab775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\nqm2ZhBsIN3bja69JOFF7wn0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       "text": "<matplotlib.figure.Figure at 0x141df5390>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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G6mz9HTNz5kwAQHBwMIKDg+Hl5YXevXvjRz/6ES5dugSg+cBfdHQ0gObA+/Dhwzh37hzO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\nY2JPREREREREpGL/D/4LCmLwbtpFAAAAAElFTkSuQmCC\n",
       "text": "<matplotlib.figure.Figure at 0x141d9ced0>"
      }
     ],
     "prompt_number": 419
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "## Topic page for Early Math\n\n* LABjs improves firstPaint on repeatView by over 200ms at the median.\n* LABjs is a few hundred points worse on SpeedIndex on firstView, and visualComplete on repeatView."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "test_name = \"Topic page for Early Math\"\nplot_one(test_name, dict(tests)[test_name])",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "Topic page for Early Math\nold\truns:36\t(150205_29_1880,150205_JS_1887,150205_WF_187X,150205_ZG_196C)\nattr\truns:36\t(150205_C6_19F1,150205_J7_18AQ,150205_KA_18AT,150205_PG_19HM)\nlabjs\truns:44\t(150205_E9_189N,150205_EA_189H,150205_TY_13ZT,150205_W1_196X,150205_Y6_189J)\n"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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GLFq0yNx6663GGGPuuusu88ILL9jTfPnll8YYYx599FEzfvx4e/jWrVuNMca8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\n",
       "text": "<matplotlib.figure.Figure at 0x1423be050>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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N0aNHIywsDBMnToS9vX2b4vbz80NWVhZOnToFb29vODs74/Llyzhx4gTGjBljorlJ1DQW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\n",
       "text": "<matplotlib.figure.Figure at 0x142132650>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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XHTt2hK+vL7Kzs5XtFW9z3rx5yM7OxoABA2BrawtbW1ssWrQIzZs3x9atWxEQ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\nRU5ErkJggg==\n",
       "text": "<matplotlib.figure.Figure at 0x141ff2b50>"
      }
     ],
     "prompt_number": 421
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "## Challenge: H for Hopper\n\n* LABjs appears worse on repeatView for SpeedIndex and visualComplete."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "test_name = \"Challenge: H for Hopper\"\nplot_one(test_name, dict(tests)[test_name])",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "Challenge: H for Hopper\nold\truns:45\t(150205_C2_19RZ,150205_M0_19S6,150205_QA_19RS,150205_TE_19S3,150205_VG_19RY)\nattr\truns:45\t(150205_C2_1A7F,150205_CT_1A7G,150205_E4_1A7D,150205_QP_1A7J,150205_ZB_1A7C)\nlabjs\truns:45\t(150205_01_1A63,150205_0T_1A62,150205_FV_1A5W,150205_G4_1A5T,150205_JT_1A5Z)\n"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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ISIh54YUXjDHGLF261Nx5553GGGPuv/9+M3v2bHuer776yhhjzJNP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\nBp9pR+nGzB+IAAAAAElFTkSuQmCC\n",
       "text": "<matplotlib.figure.Figure at 0x1423456d0>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Yv349ACA8PBxBQUGYOnUq5HI5wsPDkZSUhAcPHiAhIQHt2rXD4MGDIZPJYGtr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\niIiIyEj+H6wpbFq3XK86AAAAAElFTkSuQmCC\n",
       "text": "<matplotlib.figure.Figure at 0x1423333d0>"
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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+iIjowfD4So2F/RIydPwc6FOpgCbfHE1YabPEZ2Dq22cacp+q9x4BhuRunp3b\nUrz77rs4ceKEcqMhIiIiMizsl5ChYxKA6N405T5jVCMCDBkzrkREjYPHV6J7x/2GqLrmyPsJVFCh\nafZFCwvg+vUmqcpoNeSxtd57BBAREREREdGDaZ7cmDRRGoBaG6P6aQARERERERGRsWMigIiIiIiI\niMiIMBFAREREREREZESYCCAiIiIiIiIyIkwEEBERERERERkRJgKIiIiIiIiIjAgTAURERERERERG\nhIkAIiIiIiIiIiPCRAARERERERGREWEigIiIiIiIiMiIMBFAREREREREZESYCCAiIiIiIiIyIkwE\nEBERERERERkRJgKIiIiIiIiIjAgTAURERERERERGhIkAIiIiIiIiIiPCRAARERERERGREWEigIiI\niIiIiMiIMBFAREREREREZESYCCAiIiIiIiIyIkwEEBERERERERkRJgKIiIiIiIiIjAgTAURERERE\nRERGhIkAIiIiIiIiIiPSprkbQERERERE1JC6dgXy8pq7FTUTqKCCNEldFhbA9etNUhW1Mg02IuDy\n5cvw9/dvqNUBACIiIrBixQrldVRUFBwdHaFWq6HRaBATE9Og9d3Jzs4O1+vZc5YuXdpg9W3evBnZ\n2dnK67///e8oKipqsPUTEREZA/ZJHhz7JNTa5eUBIi3zD2i6ulpqMoSaX4MlAnr16oX4+PiGWh0A\nQKVSKf+vXbsWCQkJOHHiBLRaLRISEiBVe1Ijub3+2kRGRjZYfZs2bcLly5eV1ytXrsTvv/9eY9mK\niooGq5eIiMiQsE/y4NgnISIybPecCFiwYAGio6OV11UZ8qysLDg7OwMAzp49C29vb6jVari5uSEj\nIwOZmZlwcXFRlouKisLixYsBAOvXr4dGo4G7uzumTp2ql3GuOvFFRkZizZo16NSpEwDA3NwcM2bM\nAAAkJCRg8ODBcHV1xaxZs1BSUgKgMnv+zjvvQK1Ww9PTE6mpqfDz84O9vT3WrVsHAEhKSoKPjw8m\nTJgABwcHzJs3r8aT+datW5WY5s6di4qKCrz99tsoKiqCWq1GUFBQreXutGTJEmg0Gri4uODFF18E\nAGzfvh0nT57Ec889B7VajVWrVuHy5csYOXIkRo8eDQDo1KkTwsLC4O7ujqNHj97rW0dERHfpbr50\nUfNjn4R9EmoePEZSS8bP512Se6TVamXEiBHKaycnJ/nll19Ep9OJs7OziIiEhoZKbGysiIiUlpZK\nUVGR3nyjUk4AAAAUqUlEQVQRkaioKImIiBARkdzcXGX6X//6V1m9erWIiERERMiKFSvk5s2bYmFh\nUWN7ioqKpHfv3nLhwgUREZkxY4b8/e9/FxEROzs7Wbt2rYiIvP766+Li4iKFhYXy22+/iaWlpYiI\nJCYmSvv27UWn00l5ebmMHTtWtm/friyfm5sr6enpMnHiRCkrKxMRkXnz5smWLVtERKRTp05KW+oq\nd7vr168r/wcFBcnu3btFRMTX11dSUlKUeVX1V1GpVBIfH1/jdriPt5KIiGpx+zGVx9eWi32Sltkn\nEeF+Y+haw/vbopvYhI1r0duhkbSGz+f9asjY7vlmge7u7sjJyUF2djZycnJgYWEBa2trZGZmKmWG\nDRuGDz74AL/88gueeeYZ2Nvb17nOM2fO4K9//Stu3ryJwsJCPPHEE3rz68rqnD9/Hn379lXqCA4O\nxqeffopXX30VADBp0iQAgIuLC27duoWOHTuiY8eOaNeuHfLz8wEAGo0GdnZ2AIDAwEAcOnQIU6ZM\nAQCICBISEpCSkgJPT08AQFFREXr27FmtLXdbbt++ffjoo4/w+++/4/r163B2dsaECROU+mpjamqq\ntIuIiMjYsU/CPgkREd2f+3pqgL+/P7Zv344rV64gICCg2vzAwEAMGTIEX331FcaPH49169ahf//+\nekPSioqKlJNpSEgIdu3aBRcXF2zevBlJSUl66zM3N0enTp2g0+nQt29fvXl3npBFRG9au3btAAAm\nJiZo27atMt3ExARlZWXV1iEiMDGp/ouJ4ODgu7oJT33liouL8dJLLyElJQXW1tZYvHgxiouLa43n\ndu3bt69zfkREhPK/r68vfH19620vERHpqzoH3X5MpZaLfZLaNWefBGC/xNDd+faHhwM1HTYjIoD/\n/vKmScvT/9S0q7a096shyxuSpKSkauehBnM/wwjOnj0rQ4cOlQEDBsiVK1dERPSG2WVkZChlw8LC\nZOXKlVJaWirdunWT3NxcKS4uFm9vb1m8eLGIiHTr1k1ycnKkpKRExowZIzNnzhQRkfDwcImKihIR\nkejoaBk3bpzk5+eLiEhBQYFs2bJFiouLxdbWVi5evCgiIsHBwbJq1SoR0R/GtnHjRgkNDVXaVTUv\nMTFROnTooAzD8/Pzkx07duiVSU9Pl/79+0tOTo6IVA4bzMrKEhERCwsLKS0tFRGps1yVvLw8sbS0\nlKKiIikoKJBBgwYp22HixImSmJiolHVxcRGdTqe8vn3I353u860kIqIagD8NaDXYJ2l5fRIR7jeG\nrjW8vy26ifxpQKNqDZ/P+9WQsd3XiAAnJycUFhbCxsYGlpaWyvSqzHBcXBy2bt0KMzMzWFlZYeHC\nhWjTpg0WLVoEjUYDa2trODk5KcstWbIE3t7e6N69O7y9vVFYWKisr2qd8+bNQ2FhIby8vGBmZgYz\nMzOEhYWhXbt22LhxI/z9/VFWVgaNRoO5c+fqtefOdd05z8vLC6Ghobh48SJGjRqFyZMn65VxdHTE\n+++/Dz8/P1RUVMDMzAzR0dGwtbXFnDlz4OrqCg8PD8TExNRarkqXLl0we/ZsODs7o2fPnvD29lbm\nhYSEYO7cuXjooYeQnJyMOXPm4IknnoC1tTUSEhJ44wsiIqI7sE/CPgkREd071X8zC0YrKSkJK1as\nwO7du5u7KQ9EpVI1+qOLiIiMxe3HVB5fqakYSp8E4H5j6FrD+6tSAS22iU3YuBa9HRpJa/h83q+G\njO2eHx9oaO7MyhMRERlqB4JaNvZJqLXgMZJaMn4+747RjwgwFIac+SIiak48vhLdO+431Nxa9JVw\njgig+9SQx9b7ukcAERERERFRS9ZSB9gImq5tFhZNUw+1PkwEEBERERGRQWnZV8EFLbp5ZBSM/h4B\nRERERERERMaEiQAiIiIiIiIiI8JEABEREREREZERYSKAiIiIiIiIyIgwEUBERERERERkRJgIICIi\nIiIiIjIiTAQQERERERERGREmAoiIiIiIiIiMCBMBREREREREREaEiQAiIiIiIiIiI8JEABERERER\nEZERYSKAiIiIiIiIyIgwEUBERERERERkRJgIICIiIiIiIjIiTAQQERERERERGREmAoiIiIiIiIiM\nCBMBREREREREREaEiQAiIiIiIiIiI8JEABEREREREZERYSKAiIiIiIiIyIgwEUBERERERERkRJgI\nICIiIiIiIjIiTAQQERERERERGREmAoiIiIiIiIiMSKMlAi5fvgx/f/8GXWdERARWrFihvI6KioKj\noyPUajU0Gg1iYmIatL472dnZ4fr163WWWbp0aYPV5+vri5SUlGrTN23ahJdffrnB6iEiIjJk7JM8\nOPZJqLXq2hVQqQzjDypVs7ehuf66dm3uT5LhabREQK9evRAfH9+g61SpVMr/a9euRUJCAk6cOAGt\nVouEhASISIPWV1f9tYmMjGzQ+u6mTiIiIqod+yQNUx/7JNQa5eUBIobxBzR/G5rrLy+veT9HhuiB\nEwELFixAdHS08roqQ56VlQVnZ2cAwNmzZ+Ht7Q21Wg03NzdkZGQgMzMTLi4uynJRUVFYvHgxAGD9\n+vXQaDRwd3fH1KlTUVRUpJSrOglFRkZizZo16NSpEwDA3NwcM2bMAAAkJCRg8ODBcHV1xaxZs1BS\nUgKgMnv+zjvvQK1Ww9PTE6mpqfDz84O9vT3WrVsHAEhKSoKPjw8mTJgABwcHzJs3r8aT+datW5WY\n5s6di4qKCrz99tsoKiqCWq1GUFBQreXuVFt7b7dx40YMHDgQ3t7eSE5Ovtu3h4iIyGiwT8I+CTUN\nJoWIWr8HTgRMnz4dcXFxyuv4+HgEBARARJSDxNq1a/Hqq69Cq9UiJSUF1tbW1dZz+wFlypQpOH78\nOE6dOgVHR0ds2LBBr2x+fj4KCgpgZ2dXbT3FxcWYOXMm4uLikJaWhrKyMqxZs0apo0+fPtBqtfDx\n8UFISAh27tyJo0ePIjw8XFnHiRMn8MknnyA9PR0ZGRnYsWOHXh0//PAD4uLikJycDK1WCxMTE8TG\nxmLZsmXo0KEDtFotYmJiai13t+2tkp2djYiICCQnJ+PQoUNIT0/nAZiIiOgO7JOwT0JERHfngRMB\n7u7uyMnJQXZ2Nk6fPg0LC4tqJ9Vhw4Zh6dKlWL58OTIzM9G+ffs613nmzBkMHz4crq6uiI2NRXp6\nut78uk4458+fR9++fWFvbw8ACA4OxoEDB5T5kyZNAgC4uLhg6NCh6NixI7p164Z27dohPz8fAKDR\naGBnZwcTExMEBgbi0KFDyvIigoSEBKSkpMDT0xNqtRr79u2DTqer1pa7KVdfe0UEx44dg6+vLx5+\n+GGYmZlh+vTpjT7kkIiIqLVhn4R9EiIiujsNco8Af39/bN++HXFxcQgICKg2PzAwELt370aHDh0w\nfvx4JCYmok2bNnpD0oqKipSTaUhICKKjo5GWlobw8HC9YXhA5ZC7Tp061Xiiu/OEfPtVAABo164d\nAMDExARt27ZVppuYmKCsrKzaOkQEJibVN1NwcDC0Wi20Wi3OnTuHRYsW1bht6itXU3vvJqaaRERE\nKH9JSUk1liEiorolJSXpHU+pdWGfpGX0SQD2SwxdRETNN3Wr7bDZXOXJcLSGz1vDl0+CShWh/DUo\naQBnz56VoUOHyoABA+TKlSsiIqLT6cTZ2VlERDIyMpSyYWFhsnLlSiktLZVu3bpJbm6uFBcXi7e3\ntyxevFhERLp16yY5OTlSUlIiY8aMkZkzZ4qISHh4uERFRYmISHR0tIwbN07y8/NFRKSgoEC2bNki\nxcXFYmtrKxcvXhQRkeDgYFm1apWIiNjZ2Ulubq6IiGzcuFFCQ0OVdlXNS0xMlA4dOohOp5Py8nLx\n8/OTHTt26JVJT0+X/v37S05OjoiI5ObmSlZWloiIWFhYSGlpqYhIneWqFBUV1dpeX19fSUlJkezs\nbOnTp4/k5uZKSUmJPPbYY3ptFxFpoLeSiIjuwONr68I+SfP3SUS43xi61vT+tqKm1s+ggrk3Rhy6\nnobc99o0RDLByckJhYWFsLGxgaWlpTK9KmscFxeHrVu3wszMDFZWVli4cCHatGmDRYsWQaPRwNra\nGk5OTspyS5Ysgbe3N7p37w5vb28UFhYq66ta57x581BYWAgvLy+YmZnBzMwMYWFhaNeuHTZu3Ah/\nf3+UlZVBo9Fg7ty5eu25c113zvPy8kJoaCguXryIUaNGYfLkyXplHB0d8f7778PPzw8VFRUwMzND\ndHQ0bG1tMWfOHLi6usLDwwMxMTG1lqvSvn37WttbpWfPnoiIiMDQoUPRpUsXqNVq/h6PiIioBuyT\nsE9CRET1U/03s0D/lZSUhBUrVmD37t3N3ZR7olKp+Bs9IqJGwOMrNZfW2icBuN8Yutb0/qpU/3v0\nXqtnUMHcGyMOXU9D7nsNco8AQ8Ln5BIREVFLwD4JtVStJQlARLXjiAAD0Zoys0RErQmPr0T3jvsN\ntRQGdSXZoIK5N0Ycup6GPLY2yD0CiIiIiIiIWiJDGVgjMJxY7pWFRXO3wPAwEUBERERERAbJsK4i\nCwwqHGpWvEcAERERERERkRFhIoCIiIiIiIjIiDARQERERERERGREmAggIiIiIiIiMiJMBBARERER\nEREZESYCiIiIiIiIiIwIEwFERERERERERoSJAGpVkpKSmrsJjY4xGgbGSERk2IzhGMgYDYcxxGkM\nMTYkJgKoVTGGHZwxGgbGSERk2IzhGMgYDYcxxGkMMTYkJgKIiIiIiIiIjAgTAURERERERERGRCUi\n0tyNoAenUqmauwlERAaLp0qie8N+CRFR42ioPgkTAURERERERERGhD8NICIiIiIiIjIiTAQQERER\nERERGREmAgzAt99+CwcHB/Tv3x8ffvhhczfnnrzwwguwtLSEi4uLMu369esYO3YsBgwYAD8/P9y4\ncUOZFxkZif79+8PBwQF79+5VpqekpMDFxQX9+/fHq6++2qQx1OfSpUsYOXIkBg0aBGdnZ6xatQqA\nYcVZXFwMb29vuLu7w8nJCQsWLABgWDFWKS8vh1qtxsSJEwEYZox2dnZwdXWFWq2GRqMBYHhx3rhx\nA1OnToWjoyOcnJxw7Ngxg4uRqDmwT9KyjwvskxhGjLcz9H4J+ySNGKNQq1ZWVib9+vUTnU4nJSUl\n4ubmJunp6c3drLt24MABSU1NFWdnZ2Xam2++KR9++KGIiCxbtkzeeustERE5e/asuLm5SUlJieh0\nOunXr59UVFSIiIiXl5ccO3ZMRETGjRsne/bsaeJIapednS1arVZERAoKCmTAgAGSnp5ucHHeunVL\nRERKS0vF29tbDh48aHAxioisWLFCnn32WZk4caKIGN7nVUTEzs5OcnNz9aYZWpwzZsyQDRs2iEjl\nZ/bGjRsGFyNRU2OfpOUfF9gnMZwYqxh6v4R9ksaLkYmAVi45OVkef/xx5XVkZKRERkY2Y4vunU6n\n0zvpDhw4UK5cuSIilSesgQMHiojI0qVLZdmyZUq5xx9/XI4cOSKXL18WBwcHZfpnn30mL774YhO1\n/t499dRT8t133xlsnLdu3RJPT0/5/vvvDS7GS5cuyejRo2Xfvn0yYcIEETHMz6udnZ1cu3ZNb5oh\nxXnjxg3p27dvtemGFCNRc2CfpPUdF9gnad0xGkO/hH2SxouRPw1o5X799Vf07t1beW1jY4Nff/21\nGVv04K5evQpLS0sAgKWlJa5evQoAuHz5MmxsbJRyVbHeOd3a2rrFboPMzExotVp4e3sbXJwVFRVw\nd3eHpaWlMuzQ0GJ8/fXX8dFHH8HE5H+HTkOLEah87NeYMWPg6emJ9evXAzCsOHU6Hbp3746ZM2di\n8ODBmD17Nm7dumVQMRI1B/ZJWtdxgX2S1h0jYBz9EvZJGi9GJgJaOUN/Tq9KpTKYGAsLCzFlyhSs\nXLkS5ubmevMMIU4TExOcOnUKv/zyCw4cOIDExES9+a09xq+++go9evSAWq2u9fmtrT3GKocPH4ZW\nq8WePXvw6aef4uDBg3rzW3ucZWVlSE1Nxfz585GamoqOHTti2bJlemVae4xEzcHQ9xlDOi6wT9L6\nYzSWfgn7JI0XIxMBrZy1tTUuXbqkvL506ZJeNqg1srS0xJUrVwAA2dnZ6NGjB4Dqsf7yyy+wsbGB\ntbU1fvnlF73p1tbWTdvoepSWlmLKlCkICgrC008/DcAw4wSAP/3pT3jyySeRkpJiUDEmJydj165d\n6Nu3LwIDA7Fv3z4EBQUZVIxVrKysAADdu3fH5MmTcfz4cYOK08bGBjY2NvDy8gIATJ06FampqejZ\ns6fBxEjUHNgnaR3HBfZJDCNGY+mXsE/SeDEyEdDKeXp64sKFC8jMzERJSQk+//xzTJo0qbmb9UAm\nTZqEzZs3AwA2b96snKQmTZqEbdu2oaSkBDqdDhcuXIBGo0HPnj3RuXNnHDt2DCKCmJgYZZmWQEQw\na9YsODk54bXXXlOmG1Kc165dU+5mWlRUhO+++w5qtdqgYly6dCkuXboEnU6Hbdu2YdSoUYiJiTGo\nGAHg999/R0FBAQDg1q1b2Lt3L1xcXAwqzp49e6J379748ccfAQD/+c9/MGjQIEycONFgYiRqDuyT\ntPzjAvskhhEjYBz9EvZJGjnG+7mpAbUs33zzjQwYMED69esnS5cube7m3JOAgACxsrISMzMzsbGx\nkf/7v/+T3NxcGT16tPTv31/Gjh0reXl5SvkPPvhA+vXrJwMHDpRvv/1WmX7y5ElxdnaWfv36ycsv\nv9wcodTq4MGDolKpxM3NTdzd3cXd3V327NljUHGmpaWJWq0WNzc3cXFxkeXLl4uIGFSMt0tKSlLu\nzmtoMf7000/i5uYmbm5uMmjQIOWYYmhxnjp1Sjw9PcXV1VUmT54sN27cMLgYiZoD+yQt+7jAPolh\nxHgnQ+2XsE/SuDGqRGr5UQkRERERERERGRz+NICIiIiIiIjIiDARQERERERERGREmAggIiIiIiIi\nMiJMBBAREREREREZESYCiIiIiIiIiIwIEwFERERERERERoSJACIiIiIiIiIjwkQAERERERERkRH5\nf5r1XX+4gBA/AAAAAElFTkSuQmCC\n",
       "text": "<matplotlib.figure.Figure at 0x14210da10>"
      }
     ],
     "prompt_number": 420
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "## In conclusion\n\nSo, sometimes it pays to have deferred JavaScript. I put the most weight on comparing median times. See the repeat view's first paint times for the logged-out homepage or the video page. They look better, maybe 100-200ms better. But, most of the time it appears not to make much of a difference, and the usual method of `<script>` before `</body>` wins out.\n\nIn IE10 on the video page, there are few cases where LABjs is a clear winner over both the defer attribute and the normal method.\n\nThe take-away is that because the scripts are already at the bottom of the page, there isn't much benefit in deferring their execution. Modern browsers (latest Chrome, Firefox) are smart enough to paint before running script (since first paint times are similar across the board) without needing the deferring to let the DOM construction complete before running scripts."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "",
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}