adewes/hacker_school_effect.ipynb

## hacker_school_effect.ipynb
{
 "metadata": {
  "name": "hacker_school_effect"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "#The Hacker School Effect\n\nSince a few months I track how I spent time on my computer using a small time-tracking script (https://github.com/adewes/timetracker) that I wrote in Python. Since I'm attending the current batch of HS in NY (which is awesome!) I was curious to see if there is any **\"Hacker School Effect\"** visible in that data. \n\nTo answer this, I analyzed data from a window- and a keylogger: The former records the amount of time I spent in a given application (e.g. Sublime Text or the Gnome Terminal) and the latter the number of keys pressed during a given time slot. The data looks roughly like this:\n\n"
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "import pprint\npprint.pprint({\"active_window\": {\"/opt/sublime_text/sublime_text\": {\"[window title]\": 5.01396369934082}, \"/opt/google/chrome/chrome\": {\"******** - andreas.*******@*****.com - Gmail - Google Chrome\": 3.009580135345459}}, \"timestamp\": 1394463430, \"keyboard_and_mouse\": {\"buttons_pressed\": 2, \"mouse_moved\": 1882.0899665194609, \"keys_pressed\": {\"64\": 1, \"65\": 2, \"32\": 1, \"22\": 2, \"39\": 1, \"41\": 1, \"43\": 1, \"46\": 1, \"58\": 1, \"9\": 1, \"30\": 1, \"54\": 2, \"23\": 3, \"25\": 3, \"26\": 3, \"27\": 2, \"28\": 2, \"37\": 2, \"62\": 1, \"31\": 2}}}\n)",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": "{'active_window': {'/opt/google/chrome/chrome': {'******** - andreas.*******@*****.com - Gmail - Google Chrome': 3.009580135345459},\n                   '/opt/sublime_text/sublime_text': {'[window title]': 5.01396369934082}},\n 'keyboard_and_mouse': {'buttons_pressed': 2,\n                        'keys_pressed': {'22': 2,\n                                         '23': 3,\n                                         '25': 3,\n                                         '26': 3,\n                                         '27': 2,\n                                         '28': 2,\n                                         '30': 1,\n                                         '31': 2,\n                                         '32': 1,\n                                         '37': 2,\n                                         '39': 1,\n                                         '41': 1,\n                                         '43': 1,\n                                         '46': 1,\n                                         '54': 2,\n                                         '58': 1,\n                                         '62': 1,\n                                         '64': 1,\n                                         '65': 2,\n                                         '9': 1},\n                        'mouse_moved': 1882.0899665194609},\n 'timestamp': 1394463430}\n"
      }
     ],
     "prompt_number": 270
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "For slices of 10 seconds it contains the time spent in a given application, the number of key presses for each character code and the distance the mouse has been moved, as well the number of mouse buttons klicked. OK, let's load it!"
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "import os\nimport re\nimport json\nfrom collections import defaultdict",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 11
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "data_dir = \"./data\"\nfiles = os.listdir(data_dir)",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 12
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "We just pick out all JSON files in the data directory, parse them using the *json* module and store the data entries in a *defaultdict*."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "data_by_timestamp = defaultdict(lambda: {})\nfiles_by_date = {}\nfor filename in files:\n    date_re = r\"(\\d{4})-(\\d{2})-(\\d{2})\\.json\"\n    if re.match(date_re,filename):\n        with open(data_dir+\"/\"+filename,\"r\") as input_file:\n            json_objects = [json.loads(s) for s in input_file.read().split(\"\\n\") if s.strip()]\n            for obj in json_objects:\n                timestamp = obj['timestamp']\n                del obj['timestamp']\n                for data_type,entry in obj.items():\n                    data_by_timestamp[timestamp][data_type] = entry",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 220
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "OK, now for the interesting part: We determine the amount of time actually spent programming, and the number of key strokes. For this analysis, we only count the time spent actively (i.e. with more than  10 key presses in 10 seconds!) in either *Sublime Text* (my current code\neditor) or the GNome terminal. We then sum up the total time conforming to this criterion as well as and the number of keystrokes."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "def programming_time(entry):\n    relevant_tools = [\"/opt/sublime_text/sublime_text\",'/usr/bin/gnome-terminal']\n    tool_sum = 0.0\n    for tool in relevant_tools:\n        if tool in entry['active_window'] and 'keyboard_and_mouse' in entry and sum(entry['keyboard_and_mouse']['keys_pressed'].values()) > 10:\n            tool_sum+=sum(entry['active_window'][tool].values())\n    return tool_sum\n\nkeystrokes_by_timestamp = sorted(\n                                [(ts,sum(data_entry['keyboard_and_mouse']['keys_pressed'].values())*programming_time(data_entry)/10.0) \n                                     for ts,data_entry in data_by_timestamp.items() if 'keyboard_and_mouse' in data_entry and 'active_window' in data_entry\n                                ],key = lambda x:x[0])\n\n\nprogramming_time_by_timestamp = sorted(\n                                [(ts,programming_time(data_entry)) \n                                     for ts,data_entry in data_by_timestamp.items() if 'keyboard_and_mouse' in data_entry and 'active_window' in data_entry\n                                ],key = lambda x:x[0])\n",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 181
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "Finally, we aggregate the data by day and store it in a dictionary."
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "keystrokes_by_day = defaultdict(lambda :0)\nprogramming_time_by_day = defaultdict(lambda :0)\n\ndef increase_keystrokes(day,keystrokes):\n    keystrokes_by_day[day]+=keystrokes\n    \ndef increase_time(day,programming_time):\n    programming_time_by_day[day]+=programming_time\n    \n[increase_keystrokes(datetime.date.fromtimestamp(ts),keystrokes) for ts,keystrokes in keystrokes_by_timestamp];\n[increase_time(datetime.date.fromtimestamp(ts),programming_time) for ts,programming_time in programming_time_by_timestamp];",
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 182
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "OK, let's plot this :)"
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "from matplotlib.pylab import *\nfrom matplotlib.ticker import MaxNLocator\nimport matplotlib.dates as mdates\n\nfrom matplotlib import rc\n\nfont = {'family' : 'normal',\n        'weight' : 'normal',\n        'size'   : 16}\n\nrc('font',**font)\n\nfigure(figsize = (14,8))\ncla()\nax = subplot(1,1,1)\n\nkeystrokes_items = sorted(keystrokes_by_day.items(),key = lambda x:x[0])\ntime_items = sorted(programming_time_by_day.items(),key = lambda x:x[0])\n\nbar([d[0] for d in keystrokes_items],[d[1] for d in keystrokes_items],width = 0.5)\nylabel(\"keystrokes / day\")\n\n#ax.xaxis.set_major_locator(MaxNLocator(8))\n\nfmt = mdates.DateFormatter('%Y-%m-%d')\nloc = plticker.MultipleLocator(base=12) # this locator puts ticks at regular intervals\nax.xaxis.set_major_locator(loc)\nax.xaxis.set_major_formatter(fmt)\n\nax_twin  = ax.twinx()\n\nax_twin.bar([datetime.datetime(d[0].year,d[0].month,d[0].day,0,0,0)+datetime.timedelta(hours = 12) for d in time_items],[d[1]/3600.0 for d in time_items],color = 'red',width = 0.5)\naxvline(datetime.date(2014,02,10),ls = '--',color = 'black',lw = 4)\n\nxlim(datetime.date(2014,1,14),datetime.date(2014,3,10))\n\nfigtext(0.2,0.8,\"before Hacker School\",size = 'x-large')\nfigtext(0.58,0.8,\"during Hacker School\",size = 'x-large')\n\nimport matplotlib.ticker as plticker\n\n\ntitle(\"My Productivity\")\nylabel(\"active hours spent in terminal / code editor\");",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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BwQE9evTAhg0bkJ2dDQDa3wXHKuvTpw8OHDiA1NRUAMDPP/+MtLQ0q3R9+/bF+fPnsW3b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\nIrdhEEpERERERERu8/8ZCW0k8GVN2QAAAABJRU5ErkJggg==\n",
       "text": "<matplotlib.figure.Figure at 0x753c1950>"
      }
     ],
     "prompt_number": 293
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": "Well, sometimes a diagram says more than a thousand words ;)"
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "from IPython.core.display import HTML\n\n\ndef css_styling():\n    styles = open(\"styles.css\", \"r\").read()\n    return HTML(styles)\ncss_styling()",
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": "<style>\n    @font-face {\n        font-family: \"Computer Modern\";\n        src: url('http://9dbb143991406a7c655e-aa5fcb0a5a4ec34cff238a2d56ca4144.r56.cf5.rackcdn.com/cmunss.otf');\n    }\n    @font-face {\n        font-family: \"Computer Modern\";\n        font-weight: bold;\n        src: url('http://9dbb143991406a7c655e-aa5fcb0a5a4ec34cff238a2d56ca4144.r56.cf5.rackcdn.com/cmunsx.otf');\n    }\n    @font-face {\n        font-family: \"Computer Modern\";\n        font-style: oblique;\n        src: url('http://9dbb143991406a7c655e-aa5fcb0a5a4ec34cff238a2d56ca4144.r56.cf5.rackcdn.com/cmunsi.otf');\n    }\n    @font-face {\n        font-family: \"Computer Modern\";\n        font-weight: bold;\n        font-style: oblique;\n        src: url('http://9dbb143991406a7c655e-aa5fcb0a5a4ec34cff238a2d56ca4144.r56.cf5.rackcdn.com/cmunso.otf');\n    }\n    div.cell{\n        width:800px;\n        margin-left:16% !important;\n        margin-right:auto;\n    }\n    h1 {\n        font-family: Helvetica, serif;\n    }\n    h4{\n        margin-top:12px;\n        margin-bottom: 3px;\n       }\n    div.text_cell_render{\n        font-family: Computer Modern, \"Helvetica Neue\", Arial, Helvetica, Geneva, sans-serif;\n        line-height: 145%;\n        font-size: 130%;\n        width:800px;\n        margin-left:auto;\n        margin-right:auto;\n    }\n    .CodeMirror{\n            font-family: \"Source Code Pro\", source-code-pro,Consolas, monospace;\n    }\n    .prompt{\n        display: None;\n    }\n    .text_cell_render h5 {\n        font-weight: 300;\n        font-size: 22pt;\n        color: #4057A1;\n        font-style: italic;\n        margin-bottom: .5em;\n        margin-top: 0.5em;\n        display: block;\n    }\n    \n    .warning{\n        color: rgb( 240, 20, 20 )\n        }  \n</style>\n<script>\n    MathJax.Hub.Config({\n                        TeX: {\n                           extensions: [\"AMSmath.js\"]\n                           },\n                tex2jax: {\n                    inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ],\n                    displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ]\n                },\n                displayAlign: 'center', // Change this to 'center' to center equations.\n                \"HTML-CSS\": {\n                    styles: {'.MathJax_Display': {\"margin\": 4}}\n                }\n        });\n</script>",
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 273,
       "text": "<IPython.core.display.HTML at 0x140a9150>"
      }
     ],
     "prompt_number": 273
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": "",
     "language": "python",
     "metadata": {},
     "outputs": []
    }
   ],
   "metadata": {}
  }
 ]
}