{
 "metadata": {
  "layout": "post",
  "name": "",
  "post": {
   "cover": "images/sneeze.jpg",
   "coveralt": "CC BY-NC-ND foshydog@flickr",
   "tags": [
    "python",
    "notebook"
   ],
   "title": "Counting Sneezes from the Web"
  },
  "signature": "sha256:0527d6e0ab33813b4cbc2b8310c6c960bb213ccf75f8dfccb2ab98b6038bce6f"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The [sneeze count](http://sneezecount.joyfeed.com/) website catalogues one person's sneezes since 2007. A work colleague asked how difficult it would be to extract a list of timestamps from the site. Could we then plot sneezes over time? This post shows how easy this is to do using Python.\n",
      "\n",
      "# Fetching the data\n",
      "\n",
      "Conveniently there is an RSS feed available for the site which can be fetched via Python's built in [urlopen](https://docs.python.org/3/library/urllib.request.html#urllib.request.urlopen) function:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from urllib.request import urlopen\n",
      "print('...')\n",
      "print('\\n'.join(urlopen('http://sneezecount.joyfeed.com/feed').read().decode('utf8').splitlines()[20:30]))\n",
      "print('...')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "...\n",
        "\t<item>\n",
        "\t\t<title>Four thousand and nineteen</title>\n",
        "\t\t<link>http://sneezecount.joyfeed.com/four-thousand-and-nineteen/</link>\n",
        "\t\t<comments>http://sneezecount.joyfeed.com/four-thousand-and-nineteen/#comments</comments>\n",
        "\t\t<pubDate>Fri, 22 Aug 2014 12:41:25 +0000</pubDate>\n",
        "\t\t<dc:creator><![CDATA[Peter]]></dc:creator>\n",
        "\t\t\t\t<category><![CDATA[Sneezes]]></category>\n",
        "\n",
        "\t\t<guid isPermaLink=\"false\">http://sneezecount.joyfeed.com/?p=8608</guid>\n",
        "\t\t<description><![CDATA[Seesaw, Twycross Zoo Moderate to strong &#8220;I&#8217;m not heavy enough. And you&#8217;re too heavy.&#8221;]]></description>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "...\n"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "There is also a ``paged`` query parameter whch lets one get the next page of results:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from urllib.request import urlopen\n",
      "print('...')\n",
      "print('\\n'.join(urlopen('http://sneezecount.joyfeed.com/feed?paged=2').read().decode('utf8').splitlines()[20:30]))\n",
      "print('...')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "...\n",
        "\t<item>\n",
        "\t\t<title>Four thousand and nine</title>\n",
        "\t\t<link>http://sneezecount.joyfeed.com/four-thousand-and-nine/</link>\n",
        "\t\t<comments>http://sneezecount.joyfeed.com/four-thousand-and-nine/#comments</comments>\n",
        "\t\t<pubDate>Sat, 09 Aug 2014 17:09:39 +0000</pubDate>\n",
        "\t\t<dc:creator><![CDATA[Peter]]></dc:creator>\n",
        "\t\t\t\t<category><![CDATA[Sneezes]]></category>\n",
        "\n",
        "\t\t<guid isPermaLink=\"false\">http://sneezecount.joyfeed.com/?p=8587</guid>\n",
        "\t\t<description><![CDATA[Dining room, Malt Barn, Brize Norton Moderate Accepting the offer of an elderflower Prosecco]]></description>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "...\n"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Python also has a built in XML parsing module, the [ElementTree](https://docs.python.org/3/library/xml.etree.elementtree.html) module. Usage is, *ahem*, elementary:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import xml.etree.ElementTree as ET\n",
      "\n",
      "def parse_xml_url(url):\n",
      "    tree = ET.parse(urlopen(url))\n",
      "    return tree.getroot()\n",
      "\n",
      "root = parse_xml_url('http://sneezecount.joyfeed.com/feed?paged=2')\n",
      "print(root)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "<Element 'rss' at 0x7f958d5ccf70>\n"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "An RSS feed encodes each post with an ``item`` tag and each publication date within the item as a ``pubDate``. A quick and dirty hack to extract all dates from an RSS feed is simply to list all the ``pubDate`` elements. According to [WordPress's documentation](http://codex.wordpress.org/WordPress_Feeds#RSS_feed_time_and_date_format), the ``pubDate`` tages are RFC822 dates. Python has a module to deal with that too! The [email.utils](https://docs.python.org/2/library/email.util.html) module has a ``parsedate`` function. The value can be passed directly to ``time.mktime()`` to get a timestamp."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from email.utils import parsedate\n",
      "import time\n",
      "\n",
      "def extract_dates(root):\n",
      "    return list(time.mktime(parsedate(elem.text)) for elem in root.iter('pubDate'))\n",
      "\n",
      "print(', '.join(str(t) for t in extract_dates(root)))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1407600579.0, 1407520308.0, 1407389858.0, 1407381140.0, 1407344647.0, 1407255800.0, 1407141500.0, 1407069426.0, 1407009164.0, 1406970003.0\n"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "To get dates for a given feed, therefore, we need simply page through the feed starting at page 1 until we get a result with no items."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from urllib.parse import urljoin\n",
      "from urllib.request import HTTPError\n",
      "\n",
      "def dates_from_feed_url(url):\n",
      "    paged = 0\n",
      "    all_dates = []\n",
      "    while True:\n",
      "        paged += 1\n",
      "        page_url = urljoin(url, '?paged={0}'.format(paged))\n",
      "        try:\n",
      "            dates = extract_dates(parse_xml_url(page_url))\n",
      "        except HTTPError:\n",
      "            # Interpret a HTTP error (e.g. 404) as us reaching the end of the list\n",
      "            break\n",
      "        all_dates.extend(dates)\n",
      "        if len(dates) == 0:\n",
      "            break\n",
      "    return all_dates\n",
      "\n",
      "# Test with a feed URL for a single month:\n",
      "ts = dates_from_feed_url('http://sneezecount.joyfeed.com/2014/08/feed')\n",
      "print(', '.join(str(t) for t in ts))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "1408707685.0, 1408628545.0, 1408563641.0, 1408537639.0, 1408439866.0, 1408275986.0, 1408256591.0, 1408167669.0, 1408131465.0, 1407820127.0, 1407600579.0, 1407520308.0, 1407389858.0, 1407381140.0, 1407344647.0, 1407255800.0, 1407141500.0, 1407069426.0, 1407009164.0, 1406970003.0, 1406870597.0\n"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We can get all dates for all time by using the full feed URL:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "timestamps = dates_from_feed_url('http://sneezecount.joyfeed.com/feed')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 14
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "If we look at the first page of the website, as of writing there are four thousand and nineteen sneezes. Let's just ckeck that we've got them all:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print('Fetched {0} sneeze timestamps'.format(len(timestamps)))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Fetched 4019 sneeze timestamps\n"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Plotting\n",
      "\n",
      "Let's use matplotlib to plot the timestamps. We first use some IPython magic to load the pylab environment:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "%pylab inline\n",
      "rcParams['figure.figsize'] = (14,9) # Set the default figure size"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Populating the interactive namespace from numpy and matplotlib\n"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plot(timestamps, np.arange(len(timestamps)))\n",
      "\n",
      "title('Sneezes over time')\n",
      "xlabel('Timestamp')\n",
      "ylabel('Sneezes')\n",
      "\n",
      "grid('on')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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JklRi3n03bFc+diy8+WaYg5KkUmE7nyRJqpOuXWGffaB161BMWUBJUt1ZRCl1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\nsd9ZYB5kMjBpEjzyCJxxBvz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1a7q3MzcPBOaBAvNAWeaC4rJK0gFIyp9+/eC//4UXXoCV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\nSZIkqTX/B/mTFb5YBO65AAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f957c65ef50>"
       ]
      }
     ],
     "prompt_number": 27
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Possibly more interesting is a histogram of intervals between sneezes:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "# Use three hour bins out to 5 days\n",
      "hist(np.diff(np.asarray(timestamps) / (60*60)), bins=np.arange(0, 5*24, 3))\n",
      "title('Histogram of times between sneezes')\n",
      "xlabel('Hours')\n",
      "ylabel('Count')\n",
      "grid('on')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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AG6RwYlLsX6bkgEEOmJMFSg5YncIJAABgCT1OC/Q4AQDAFOlxAgAA2CCFE5Ni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\n43Jd3uraCw+4/UOXMdbRWam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       "text": [
        "<matplotlib.figure.Figure at 0x7f957c65e510>"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Summary\n",
      "\n",
      "In this post we showed how the Python standard library has all the tools we require to scrape a website and plot some interesting figures using data from it."
     ]
    }
   ],
   "metadata": {}
  }
 ]
}