analytics.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import dotenv\n",
    "dotenv.load_dotenv(\".env.local\")\n",
    "\n",
    "from supabase import create_client, Client\n",
    "import time\n",
    "from copy import deepcopy\n",
    "\n",
    "import re\n",
    "import json\n",
    "from urllib.request import urlopen\n",
    "import requests\n",
    "import pandas as pd\n",
    "import plotly.express as px\n",
    "px.set_mapbox_access_token(os.environ[\"MAPBOX_TOKEN\"])\n",
    "from datetime import datetime, timedelta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-03-03 15:41:07,770:INFO - HTTP Request: GET https://wvklzyidkkrskdgquocj.supabase.co/rest/v1/visits?select=%2A \"HTTP/1.1 200 OK\"\n"
     ]
    }
   ],
   "source": [
    "client = create_client(\"https://wvklzyidkkrskdgquocj.supabase.co\", os.environ[\"SUPABASE_KEY\"])\n",
    "response = client.table('visits').select(\"*\").execute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th {\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>created_at</th>\n",
       "      <th>ip_address</th>\n",
       "      <th>route</th>\n",
       "      <th>user_agent</th>\n",
       "      <th>is_bot</th>\n",
       "      <th>referrer</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>7</td>\n",
       "      <td>2024-02-27 04:41:20.067741+00:00</td>\n",
       "      <td>64.23.187.48</td>\n",
       "      <td>/</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
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       "      <th>1</th>\n",
       "      <td>8</td>\n",
       "      <td>2024-02-27 04:41:20.795991+00:00</td>\n",
       "      <td>64.23.187.48</td>\n",
       "      <td>/</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9</td>\n",
       "      <td>2024-02-27 04:41:21.213661+00:00</td>\n",
       "      <td>172.69.23.187</td>\n",
       "      <td>/</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>10</td>\n",
       "      <td>2024-02-27 04:42:53.205514+00:00</td>\n",
       "      <td>76.99.220.36</td>\n",
       "      <td>/</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11</td>\n",
       "      <td>2024-02-27 04:43:51.899723+00:00</td>\n",
       "      <td>172.69.22.42</td>\n",
       "      <td>/</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>422</th>\n",
       "      <td>427</td>\n",
       "      <td>2024-03-03 13:05:38.378563+00:00</td>\n",
       "      <td>83.229.85.81</td>\n",
       "      <td>/</td>\n",
       "      <td>python-requests/2.31.0</td>\n",
       "      <td>true</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>423</th>\n",
       "      <td>428</td>\n",
       "      <td>2024-03-03 13:51:14.315301+00:00</td>\n",
       "      <td>17.241.219.73</td>\n",
       "      <td>/cooking</td>\n",
       "      <td>Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_5...</td>\n",
       "      <td>true</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>424</th>\n",
       "      <td>429</td>\n",
       "      <td>2024-03-03 17:44:54.681990+00:00</td>\n",
       "      <td>182.42.104.32</td>\n",
       "      <td>/</td>\n",
       "      <td>Mozilla/5.0 (iPhone; CPU iPhone OS 13_2_3 like...</td>\n",
       "      <td>false</td>\n",
       "      <td>https://www.isaacwasserman.com/</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>425</th>\n",
       "      <td>430</td>\n",
       "      <td>2024-03-03 18:32:28.828089+00:00</td>\n",
       "      <td>116.205.133.55</td>\n",
       "      <td>/</td>\n",
       "      <td>Mozilla/5.0 (Windows NT 10.0; Win64; x64) Appl...</td>\n",
       "      <td>false</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>426</th>\n",
       "      <td>431</td>\n",
       "      <td>2024-03-03 18:54:52.117245+00:00</td>\n",
       "      <td>114.119.139.26</td>\n",
       "      <td>/technology/portrait-shadow-removal</td>\n",
       "      <td>Mozilla/5.0 (Linux; Android 7.0;) AppleWebKit/...</td>\n",
       "      <td>true</td>\n",
       "      <td>https://isaacwasserman.com/technology</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>427 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      id                       created_at      ip_address  \\\n",
       "0      7 2024-02-27 04:41:20.067741+00:00    64.23.187.48   \n",
       "1      8 2024-02-27 04:41:20.795991+00:00    64.23.187.48   \n",
       "2      9 2024-02-27 04:41:21.213661+00:00   172.69.23.187   \n",
       "3     10 2024-02-27 04:42:53.205514+00:00    76.99.220.36   \n",
       "4     11 2024-02-27 04:43:51.899723+00:00    172.69.22.42   \n",
       "..   ...                              ...             ...   \n",
       "422  427 2024-03-03 13:05:38.378563+00:00    83.229.85.81   \n",
       "423  428 2024-03-03 13:51:14.315301+00:00   17.241.219.73   \n",
       "424  429 2024-03-03 17:44:54.681990+00:00   182.42.104.32   \n",
       "425  430 2024-03-03 18:32:28.828089+00:00  116.205.133.55   \n",
       "426  431 2024-03-03 18:54:52.117245+00:00  114.119.139.26   \n",
       "\n",
       "                                   route  \\\n",
       "0                                      /   \n",
       "1                                      /   \n",
       "2                                      /   \n",
       "3                                      /   \n",
       "4                                      /   \n",
       "..                                   ...   \n",
       "422                                    /   \n",
       "423                             /cooking   \n",
       "424                                    /   \n",
       "425                                    /   \n",
       "426  /technology/portrait-shadow-removal   \n",
       "\n",
       "                                            user_agent is_bot  \\\n",
       "0                                                 None   None   \n",
       "1                                                 None   None   \n",
       "2                                                 None   None   \n",
       "3                                                 None   None   \n",
       "4                                                 None   None   \n",
       "..                                                 ...    ...   \n",
       "422                             python-requests/2.31.0   true   \n",
       "423  Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_5...   true   \n",
       "424  Mozilla/5.0 (iPhone; CPU iPhone OS 13_2_3 like...  false   \n",
       "425  Mozilla/5.0 (Windows NT 10.0; Win64; x64) Appl...  false   \n",
       "426  Mozilla/5.0 (Linux; Android 7.0;) AppleWebKit/...   true   \n",
       "\n",
       "                                  referrer  \n",
       "0                                     None  \n",
       "1                                     None  \n",
       "2                                     None  \n",
       "3                                     None  \n",
       "4                                     None  \n",
       "..                                     ...  \n",
       "422                                   None  \n",
       "423                                   None  \n",
       "424        https://www.isaacwasserman.com/  \n",
       "425                                   None  \n",
       "426  https://isaacwasserman.com/technology  \n",
       "\n",
       "[427 rows x 7 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "visits = deepcopy(response.data)\n",
    "visits_df = pd.DataFrame(visits)\n",
    "visits_df['created_at'] = pd.to_datetime(visits_df['created_at'])\n",
    "visits_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "maximum_session_gap = 30\n",
    "sessions = []\n",
    "for ip_address in visits_df['ip_address'].unique():\n",
    "    visitors_visits = visits_df[visits_df['ip_address'] == ip_address]\n",
    "    visitors_visits = visitors_visits.sort_values('created_at')\n",
    "    session = []\n",
    "    for i in range(1, len(visitors_visits)):\n",
    "        if session == []:\n",
    "            session.append(visitors_visits.iloc[i])\n",
    "        previous_visit = session[-1]\n",
    "        current_visit = visitors_visits.iloc[i]\n",
    "        time_difference = (current_visit['created_at'] - previous_visit['created_at']).seconds / 60\n",
    "        if time_difference > maximum_session_gap:\n",
    "            sessions.append(session)\n",
    "            session = []\n",
    "        session.append(current_visit)\n",
    "    if session != []:\n",
    "        sessions.append(session)\n",
    "\n",
    "sessions_df = {\n",
    "    \"ip_address\": [],\n",
    "    \"start_time\": [],\n",
    "    \"end_time\": [],\n",
    "    \"visit_ids\": []\n",
    "}\n",
    "\n",
    "for session in sessions:\n",
    "    sessions_df[\"ip_address\"].append(session[0]['ip_address'])\n",
    "    sessions_df[\"start_time\"].append(session[0]['created_at'])\n",
    "    sessions_df[\"end_time\"].append(session[-1]['created_at'])\n",
    "    sessions_df[\"visit_ids\"].append([visit['id'] for visit in session])\n",
    "\n",
    "sessions_df = pd.DataFrame(sessions_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-03-03 15:47:30,911:INFO - HTTP Request: GET https://wvklzyidkkrskdgquocj.supabase.co/rest/v1/visitors?select=%2A \"HTTP/1.1 200 OK\"\n"
     ]
    }
   ],
   "source": [
    "response = client.table('visitors').select(\"*\").execute()\n",
    "visitors = deepcopy(response.data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2024-03-03 15:47:32,314:INFO - HTTP Request: POST https://wvklzyidkkrskdgquocj.supabase.co/rest/v1/visitors \"HTTP/1.1 201 Created\"\n"
     ]
    }
   ],
   "source": [
    "visitors_df = pd.DataFrame(visitors)\n",
    "new_visitors = []\n",
    "ip_addresses_in_sessions = sessions_df['ip_address'].unique()\n",
    "for ip_address in ip_addresses_in_sessions:\n",
    "    if ip_address in visitors_df['ip_address'].values:\n",
    "        continue\n",
    "    ip_info = json.load(urlopen(f\"https://ipinfo.io/{ip_address}/json\"))\n",
    "    loc = ip_info.get('loc', None)\n",
    "    if loc:\n",
    "        lat, lon = loc.split(',')\n",
    "        ip_info['lat'] = float(lat)\n",
    "        ip_info['lon'] = float(lon)\n",
    "    else:\n",
    "        ip_info['lat'] = None\n",
    "        ip_info['lon'] = None\n",
    "    visitor = {\n",
    "        \"ip_address\": ip_address,\n",
    "        \"city\": ip_info.get('city', None),\n",
    "        \"region\": ip_info.get('region', None),\n",
    "        \"country\": ip_info.get('country', None),\n",
    "        \"postal\": ip_info.get('postal', None),\n",
    "        \"lat\": ip_info.get('lat', None),\n",
    "        \"lon\": ip_info.get('lon', None),\n",
    "        \"timezone\": ip_info.get('timezone', None),\n",
    "        \"hostname\": ip_info.get('hostname', None),\n",
    "        \"org\": ip_info.get('org', None),\n",
    "        \"is_bot\": visits_df[visits_df['ip_address'] == ip_address].iloc[-1]['is_bot']\n",
    "    }\n",
    "    new_visitors.append(visitor)\n",
    "\n",
    "response = client.table('visitors').insert(new_visitors).execute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "55"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(visitors_df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.plotly.v1+json": {
       "config": {
        "plotlyServerURL": "https://plot.ly"
       },
       "data": [
        {
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           "",
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          ],
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           "",
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           "",
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           "Washington",
           "",
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          [
           "Des Moines",
           "",
           "",
           "2024-03-01T18:11:22.462967+00:00",
           "2024-03-01T18:12:34.734200+00:00"
          ],
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           "Philadelphia",
           "",
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           "2024-03-01T19:47:24.730054+00:00",
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           "Coudersport",
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           "",
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           "Bridgeton",
           "https://www.linkedin.com/",
           "c-174-57-54-19.hsd1.nj.comcast.net",
           "2024-03-02T13:26:26.320521+00:00",
           "2024-03-02T13:30:08.873503+00:00"
          ],
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           "Bridgeton",
           "",
           "c-73-197-50-4.hsd1.nj.comcast.net",
           "2024-03-01T20:43:17.061324+00:00",
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           "Bridgeton",
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           "Bridgeton",
           "",
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           "2024-03-02T22:18:10.971387+00:00",
           "2024-03-02T22:18:12.662688+00:00"
          ],
          [
           "Philadelphia",
           "",
           "",
           "2024-03-01T22:23:31.992595+00:00",
           "2024-03-01T22:23:32.215134+00:00"
          ]
         ],
         "hovertemplate": "<b>%{hovertext}</b><br><br>is_bot=False<br>lat=%{lat}<br>lon=%{lon}<br>city=%{customdata[0]}<br>referrer=%{customdata[1]}<br>hostname=%{customdata[2]}<br>start_time=%{customdata[3]}<br>end_time=%{customdata[4]}<extra></extra>",
         "hovertext": [
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   "source": [
    "dots_df = sessions_df.copy()\n",
    "dots_df['lat'] = None\n",
    "dots_df['lon'] = None\n",
    "dots_df['city'] = None\n",
    "dots_df['is_bot'] = None\n",
    "dots_df['referrer'] = None\n",
    "dots_df['hostname'] = None\n",
    "for i, row in dots_df.iterrows():\n",
    "    lat = visitors_df[visitors_df['ip_address'] == row['ip_address']].iloc[0]['lat']\n",
    "    lon = visitors_df[visitors_df['ip_address'] == row['ip_address']].iloc[0]['lon']\n",
    "    city = visitors_df[visitors_df['ip_address'] == row['ip_address']].iloc[0]['city']\n",
    "    is_bot = visitors_df[visitors_df['ip_address'] == row['ip_address']].iloc[0]['is_bot']\n",
    "    referrer = visits_df[visits_df['id'].isin(row['visit_ids'])].iloc[0]['referrer']\n",
    "    hostname = visitors_df[visitors_df['ip_address'] == row['ip_address']].iloc[0]['hostname']\n",
    "    dots_df.at[i, 'lat'] = lat\n",
    "    dots_df.at[i, 'lon'] = lon\n",
    "    dots_df.at[i, 'city'] = city\n",
    "    dots_df.at[i, 'is_bot'] = is_bot\n",
    "    if not referrer:\n",
    "        referrer = \"\"\n",
    "    dots_df.at[i, 'referrer'] = referrer\n",
    "    if not hostname:\n",
    "        hostname = \"\"\n",
    "    dots_df.at[i, 'hostname'] = hostname\n",
    "\n",
    "num_last_days = 4\n",
    "\n",
    "dots_df['start_time'] = pd.to_datetime(dots_df['start_time'])\n",
    "timezone = dots_df['start_time'].dt.tz\n",
    "seven_days_ago = datetime.now(timezone) - timedelta(days=num_last_days)\n",
    "dots_df = dots_df[dots_df['start_time'] > seven_days_ago]\n",
    "\n",
    "fig = px.scatter_mapbox(dots_df, lat=\"lat\", lon=\"lon\", color=\"is_bot\", hover_name=\"ip_address\", hover_data=[\"city\", \"referrer\", \"hostname\", \"start_time\", \"end_time\",], zoom=1)\n",
    "fig.update_layout(mapbox_style=\"open-street-map\")\n",
    "fig.show()"
   ]
  }
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