MySQL Connector Python Native TLS Performance.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After [the test I did](http://databaseblog.myname.nl/2015/12/the-performance-of-mysql.html) with the C Extension of MySQL Connector/Python I was curious how costly using Transport Layer Security (TLS) is.\n",
    "\n",
    "Note: TLS is the successor of Secure Sockets Layer (SSL). None of the current MySQL versions support SSL at all, but all variable names still use SSL."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using MySQL Connector/Python 2.1.3\n"
     ]
    }
   ],
   "source": [
    "import random\n",
    "import gzip\n",
    "import time\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import requests\n",
    "import mysql.connector\n",
    "\n",
    "print('Using MySQL Connector/Python {version}'.format(version=mysql.connector.__version__))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "worlddb_url = 'https://downloads.mysql.com/docs/world.sql.gz'\n",
    "worlddb_req = requests.get(worlddb_url)\n",
    "if worlddb_req.status_code == 200:\n",
    "    worldsql = gzip.decompress(worlddb_req.content).decode('iso-8859-15')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I've used [mysql_ssl_rsa_setup](https://dev.mysql.com/doc/refman/5.7/en/mysql-ssl-rsa-setup.html) to enable TLS on MySQL 5.7.10 running in MySQL Sandbox."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "config = {\n",
    "    'host': '127.0.0.1',\n",
    "    'port': 5710,\n",
    "    'user': 'msandbox',\n",
    "    'passwd': 'msandbox',\n",
    "}\n",
    "tls_ca_file = '/home/dvaneeden/sandboxes/msb_5_7_10/data/ca.pem'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "c1 = mysql.connector.connect(ssl_ca=tls_ca_file, **config)\n",
    "cur1 = c1.cursor()\n",
    "cur1.execute('DROP SCHEMA IF EXISTS world')\n",
    "cur1.execute('CREATE SCHEMA world DEFAULT CHARACTER SET latin1')\n",
    "cur1.execute('USE world')\n",
    "result = [x for x in cur1.execute(worldsql, multi=True)]\n",
    "cur1.close()\n",
    "c1.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Using protocol TLSv1 and cipher DHE-RSA-AES256-SHA\n"
     ]
    }
   ],
   "source": [
    "c1 = mysql.connector.connect(ssl_ca=tls_ca_file, **config)\n",
    "cur1 = c1.cursor()\n",
    "cur1.execute(\"SHOW SESSION STATUS LIKE 'SSL%'\")\n",
    "tls_conn = {x[0]: x[1] for x in cur1 if x[0] in ['Ssl_version','Ssl_cipher']}\n",
    "print(\"Using protocol %s and cipher %s\" % (tls_conn['Ssl_version'], tls_conn['Ssl_cipher']))\n",
    "c1.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "config['db'] = 'world'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "perfdata = pd.DataFrame(columns=['connpy','connpy_tls'], index=range(10000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "for it in range(10000):\n",
    "    city_id = random.randint(1,8000)\n",
    "    start = time.perf_counter()\n",
    "    c1 = mysql.connector.connect(ssl_ca=tls_ca_file, **config)\n",
    "    cur1 = c1.cursor()\n",
    "    cur1.execute(\"SELECT * FROM City WHERE ID=%s\", (city_id,))\n",
    "    cur1.fetchone()\n",
    "    c1.close()\n",
    "    perfdata.ix[it]['connpy_tls'] = time.perf_counter() - start"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "for it in range(10000):\n",
    "    city_id = random.randint(1,8000)\n",
    "    start = time.perf_counter()\n",
    "    c1 = mysql.connector.connect(**config)\n",
    "    cur1 = c1.cursor()\n",
    "    cur1.execute(\"SELECT * FROM City WHERE ID=%s\", (city_id,))\n",
    "    cur1.fetchone()\n",
    "    c1.close()\n",
    "    perfdata.ix[it]['connpy'] = time.perf_counter() - start"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's have a look to what our data looks like"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>connpy</th>\n",
       "      <th>connpy_tls</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.00187417</td>\n",
       "      <td>0.0331963</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.00171487</td>\n",
       "      <td>0.0277591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0015613</td>\n",
       "      <td>0.0251479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.00134424</td>\n",
       "      <td>0.024894</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.00149395</td>\n",
       "      <td>0.028625</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       connpy connpy_tls\n",
       "0  0.00187417  0.0331963\n",
       "1  0.00171487  0.0277591\n",
       "2   0.0015613  0.0251479\n",
       "3  0.00134424   0.024894\n",
       "4  0.00149395   0.028625"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "perfdata.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's plot that"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
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       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.send_message('closing', {});\n",
       "    fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f1c05886f98>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "plt.style.use('ggplot')\n",
    "plt.scatter(perfdata.index, perfdata.connpy, s=1, c='r',\n",
    "            label='Connector/Python No TLS')\n",
    "plt.scatter(perfdata.index, perfdata.connpy_tls, s=1, c='g',\n",
    "            label='Connector/Python TLS')\n",
    "plt.ylim(ymin=0, ymax=0.03)\n",
    "plt.xlim(xmin=0, xmax=10000)\n",
    "plt.xlabel('Run #')\n",
    "plt.ylabel('Runtime in seconds')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The performance of MySQL Connector/Python 2.1 with TLS looks much slower than without TLS.\n",
    "\n",
    "But we create a new connection for each query. This is the worst-case senario.\n",
    "\n",
    "What would happen if we would use a persistend connection?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "perfdata2 = pd.DataFrame(columns=['p_connpy','p_connpy_tls'], index=range(10000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "c1 = mysql.connector.connect(**config)\n",
    "for it in range(10000):\n",
    "    city_id = random.randint(1,8000)\n",
    "    start = time.perf_counter()\n",
    "    cur1 = c1.cursor()\n",
    "    cur1.execute(\"SELECT * FROM City WHERE ID=%s\", (city_id,))\n",
    "    cur1.fetchone()\n",
    "    perfdata2.ix[it]['p_connpy'] = time.perf_counter() - start\n",
    "c1.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "c1 = mysql.connector.connect(ssl_ca=tls_ca_file, **config)\n",
    "for it in range(10000):\n",
    "    city_id = random.randint(1,8000)\n",
    "    start = time.perf_counter()\n",
    "    cur1 = c1.cursor()\n",
    "    cur1.execute(\"SELECT * FROM City WHERE ID=%s\", (city_id,))\n",
    "    cur1.fetchone()\n",
    "    perfdata2.ix[it]['p_connpy_tls'] = time.perf_counter() - start\n",
    "c1.close()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "            fig.waiting = false;\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.send_message('closing', {});\n",
       "    fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-danger\" href=\"#\" title=\"Close figure\"><i class=\"fa fa-times icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Close figure', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        event.shiftKey = false;\n",
       "        // Send a \"J\" for go to next cell\n",
       "        event.which = 74;\n",
       "        event.keyCode = 74;\n",
       "        manager.command_mode();\n",
       "        manager.handle_keydown(event);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f1c0716ebe0>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "%matplotlib notebook\n",
    "plt.style.use('ggplot')\n",
    "plt.scatter(perfdata2.index, perfdata2.p_connpy, s=1, c='r',\n",
    "            label='Connector/Python No TLS')\n",
    "plt.scatter(perfdata2.index, perfdata2.p_connpy_tls, s=1, c='g',\n",
    "            label='Connector/Python TLS')\n",
    "plt.ylim(ymin=0, ymax=0.001)\n",
    "plt.xlim(xmin=0, xmax=10000)\n",
    "plt.xlabel('Run #')\n",
    "plt.ylabel('Runtime in seconds')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This shows that not reconnecting for each and every query can make a huge difference when using TLS.\n",
    "\n",
    "The difference doesn't have to be as big. Using [TLS Tickets](https://www.ietf.org/rfc/rfc5077.txt) could reduce the reconnect cost. See also [MySQL Bug #76921](https://bugs.mysql.com/bug.php?id=76921)\n",
    "\n",
    "I did this test also with the C Extension enabled, and the results were similar. But testing was a bit more complicated as there is no option to force TLS to be disabled. See also [MySQL Bug #79825](https://bugs.mysql.com/bug.php?id=79825).\n",
    "\n",
    "The `perf top` output below was taken when running the test with TLS and reconnects for every statement."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ML0/Pg99i1rAkIiIiM+PGjBanV69ZaxZM6szeffvFfgUVCgWGDUkXl2Ua9YP3544daGxs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YjtYGWLgM0Hh7ezPLJSUlVW5X1+vHkpqcf65Y+/vRmz37NUyePIn5WygUIjp6IKKiIvHuuwtw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Hn27FmYOjUR9fX12LRpM+bNexGFhS2bsN0Wyrd2/QFgy5bNSEycgh49JHB2doazszMee+wx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\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AARg4sOGNtLS0DFFRvD003dxcERQUBGvrnliyZCkuX77Shitpfzp16oStW7cwwXptbS2W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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image(filename=\"perf_top_mysql_ssl.png\")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.4.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}