{
 "metadata": {
  "name": "networkx_demo"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import networkx as nx"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data = \"\"\"traceroute to www.vancouver.ca (199.175.219.246), 64 hops max, 52 byte packets\n",
      " 1  192.168.1.254 (192.168.1.254)  2.381 ms  2.554 ms  0.841 ms\n",
      " 2  10.31.196.1 (10.31.196.1)  27.991 ms  19.714 ms  17.100 ms\n",
      " 3  clgrab31gr01.bb.telus.com (154.11.10.170)  46.593 ms  44.800 ms  270.093 ms\n",
      " 4  154.11.2.218 (154.11.2.218)  43.418 ms  42.816 ms  43.113 ms\n",
      " 5  core3-calgaryqa_gi6-0-0.net.bell.ca (64.230.77.250)  61.020 ms  64.224 ms  61.376 ms\n",
      " 6  * * *\n",
      " 7  * core3-vancouverbg_pos10-1-0.net.bell.ca (64.230.77.205)  62.431 ms  62.479 ms\n",
      " 8  * agg1-vancouverbg_xe5-0-0.net.bell.ca (64.230.77.229)  61.626 ms  128.529 ms\n",
      " 9  dis4-vancouverbg_10-0-0.net.bell.ca (64.230.122.241)  132.342 ms  60.667 ms  62.148 ms\n",
      "10  10.1.7.2 (10.1.7.2)  61.920 ms  61.926 ms  60.517 ms\n",
      "11  204.101.186.34 (204.101.186.34)  61.635 ms  62.415 ms  61.575 ms\n",
      "12  * * *\n",
      "13  * * *\n",
      "14  * * *\n",
      "15  * * *\n",
      "16  * * *\n",
      "17  * * *\n",
      "18  * * *\n",
      "19  * * *\n",
      "20  * * *\n",
      "21  * * *\n",
      "22  * * *\n",
      "23  * * *\n",
      "24  * * *\n",
      "25  * * *\n",
      "26  * * *\n",
      "27  * * *\n",
      "28  * * *\n",
      "29  * * * \"\"\"\n",
      "data = data.split(\"\\n\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 2
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data = data[1:]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 3
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cleaned_ip = [ \",\".join(item.split()[1:4]) for item in data if \"* * *\" not in item ]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 4
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import re\n",
      "pattern = r'[0-9]+\\.[0-9]+\\.[0-9]+\\.[0-9]+'\n",
      "path_list = [re.findall(pattern,line)[0] for line in cleaned_ip]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "node_node = zip(path_list,path_list[1:])\n",
      "node_node"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 6,
       "text": [
        "[('192.168.1.254', '10.31.196.1'),\n",
        " ('10.31.196.1', '154.11.10.170'),\n",
        " ('154.11.10.170', '154.11.2.218'),\n",
        " ('154.11.2.218', '64.230.77.250'),\n",
        " ('64.230.77.250', '64.230.77.205'),\n",
        " ('64.230.77.205', '64.230.77.229'),\n",
        " ('64.230.77.229', '64.230.122.241'),\n",
        " ('64.230.122.241', '10.1.7.2'),\n",
        " ('10.1.7.2', '204.101.186.34')]"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "trace = nx.Graph()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 7
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "[trace.add_edge(a,b) for a,b in node_node] "
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 8,
       "text": [
        "[None, None, None, None, None, None, None, None, None]"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "trace.edges()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 9,
       "text": [
        "[('64.230.77.229', '64.230.122.241'),\n",
        " ('64.230.77.229', '64.230.77.205'),\n",
        " ('10.31.196.1', '154.11.10.170'),\n",
        " ('10.31.196.1', '192.168.1.254'),\n",
        " ('154.11.10.170', '154.11.2.218'),\n",
        " ('10.1.7.2', '64.230.122.241'),\n",
        " ('10.1.7.2', '204.101.186.34'),\n",
        " ('64.230.77.250', '154.11.2.218'),\n",
        " ('64.230.77.250', '64.230.77.205')]"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "trace.nodes()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "pyout",
       "prompt_number": 10,
       "text": [
        "['64.230.77.229',\n",
        " '10.31.196.1',\n",
        " '154.11.10.170',\n",
        " '10.1.7.2',\n",
        " '64.230.77.250',\n",
        " '192.168.1.254',\n",
        " '154.11.2.218',\n",
        " '64.230.122.241',\n",
        " '204.101.186.34',\n",
        " '64.230.77.205']"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "nx.draw(trace)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "display_data",
       "png": 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erjZ8fX3Rrl07ODo6wtLSEtevX0dAQMALRF31+MZPxli1U7iHI5VK0b59ewCA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\n1Gr+7OjRl31rBUH4hkTOsyEgfGvV1tbi98XFuDE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      }
     ],
     "prompt_number": 11
    }
   ],
   "metadata": {}
  }
 ]
}