sburns/notebook.ipynb

## notebook.ipynb
{
 "metadata": {
  "name": "dev"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "# Using lxml and pandas to examine PyPI package stats\n",
      "\n",
      "A [post](POST URL) written for [PyNash](http://pynash.org) more clearly describes this notebook. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "from lxml.html import document_fromstring\n",
      "import requests\n",
      "import pandas as pd\n",
      "from dateutil.parser import parse as dateparse\n",
      "%pylab inline"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\n",
        "Welcome to pylab, a matplotlib-based Python environment [backend: module://IPython.zmq.pylab.backend_inline].\n",
        "For more information, type 'help(pylab)'.\n"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "code",
     "collapsed": true,
     "input": [
      "def package_versions(package_name, name_pwd):\n",
      "    \"\"\"\n",
      "    Scrape the package's pkg_edit page for all uploaded versions\n",
      "\n",
      "    package_name: official package name\n",
      "    name_pwd: PyPI username, password tuple\n",
      "\n",
      "    Returns a list of versions for the package\n",
      "    \"\"\"\n",
      "    pl = {':action': 'pkg_edit', 'name': package_name}\n",
      "    r = requests.get('https://pypi.python.org/pypi', params=pl, auth=name_pwd)\n",
      "    html = document_fromstring(r.content)\n",
      "    rows = html.cssselect('table.list tr')[:-1]\n",
      "    header = rows[0]\n",
      "    data = rows[1:]\n",
      "    version_index, _ = filter(lambda x: x[1].text_content().lower() == 'version', enumerate(header))[0]\n",
      "    versions = map(lambda x: x[version_index].text_content(), data)\n",
      "    return versions\n",
      "\n",
      "def package_data(package, version):\n",
      "    \"\"\"\n",
      "    Hit the official json feed for a package and version\n",
      "\n",
      "    Return the package info and url data\n",
      "    \"\"\"\n",
      "    url = 'http://pypi.python.org/pypi/%s/%s/json' % (package, version)\n",
      "    data = requests.get(url).json()\n",
      "    metadata = data['info']\n",
      "    # PyPI publishes the version information as a list, we're interested in first\n",
      "    url_info = data['urls'][0]\n",
      "    return metadata, url_info\n",
      "\n",
      "def get_pypi_auth():\n",
      "    \"\"\"\n",
      "    Try to read ~/.pypirc and return the (username, password) tuple\n",
      "    \"\"\"\n",
      "    from ConfigParser import ConfigParser\n",
      "    import os\n",
      "    cp = ConfigParser()\n",
      "    cp.read(os.path.expanduser('~/.pypirc'))\n",
      "    name = cp.get('pypi', 'username')\n",
      "    passwd = cp.get('pypi', 'password')\n",
      "    return name, passwd\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 15
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Putting it all together..."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "package = 'PyCap'\n",
      "versions = package_versions(package, get_pypi_auth())\n",
      "data = [package_data(package, v)[1] for v in versions]\n",
      "\n",
      "df = pd.DataFrame(data, index=versions)\n",
      "# convert upload_time\n",
      "df['upload_time'] = df['upload_time'].map(dateparse)\n",
      "df['elapsed'] = df['upload_time'] - df['upload_time'].shift(-1)\n",
      "\n",
      "def to_days(x):\n",
      "    days = -1\n",
      "    try:\n",
      "        days = x.days\n",
      "    except:\n",
      "        pass\n",
      "    return days\n",
      "\n",
      "df['elapsed'] = df['elapsed'].map(to_days)\n",
      "# compute downloads / day\n",
      "df['downloads / day'] = df['downloads'] / df['elapsed']"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 16
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "to_plot = df['downloads / day'][:-1]\n",
      "mpl.rc('figure', figsize=(10, 8))\n",
      "to_plot.plot(kind='bar')\n",
      "plt.ylabel('Downloads Per Day')\n",
      "plt.xlabel('Version')\n",
      "plt.title('Downloads/day per version for %s' % package)\n",
      "plt.show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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nKznt8iUna5M5CjAAAICIOekB27x5s6644gotXLhQKSkpGjt2rBo0aKDevXtr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\nAAAiRg8YjPjSF0BOU7702DDnXfHlvPs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      }
     ],
     "prompt_number": 17
    }
   ],
   "metadata": {}
  }
 ]
}