get_from_brewai.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from faic_toolbox import datalake\n",
    "import pandas as pd\n",
    "import requests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "datalake.config.datalake = datalake.DatalakeConfig(\n",
    "    \"https://akeqm174e7.execute-api.ap-southeast-2.amazonaws.com/v1\",\n",
    "    ''\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "brew_ai_headers = {\"Authorization\": \"Bearer ..zCQ9_2-or7EOcGQnobxYjO_zHVAKGVOyC7kjg3_p-ds\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "sensors = requests.get(\n",
    "    url='https://model.brewai.com/api/sensor_devices',\n",
    "    headers=brew_ai_headers\n",
    ").json()['devices']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'readings': [{'devid': '7BB92D02D696C5C5', 'id': 630538, 'readings': [1, 25.217313766479492, 51.57240676879883, 100.90007781982422, 132, 862.3662109375, 1.1371276378631592], 'ts': 'Tue, 07 Feb 2023 11:29:19 GMT'}, {'devid': '5A744701608421E', 'id': 163738, 'readings': [1, 23.763551712036133, 47.60177230834961, 100.95503997802734, 96, 701.5572509765625, 0.7896832823753357], 'ts': 'Thu, 29 Sep 2022 02:11:38 GMT'}, {'devid': 'B84C4503F361D64A', 'id': 630536, 'readings': [1, 24.92632484436035, 50.81771469116211, 100.90437316894531, 140, 893.4422607421875, 1.2201443910598755], 'ts': 'Tue, 07 Feb 2023 11:29:00 GMT'}, {'devid': 'A9DBA7135C924932', 'id': 84976, 'readings': [1, 24.647851943969727, 44.24776840209961, 99.7659683227539, 62, 621.0745849609375, 0.5634467601776123], 'ts': 'Fri, 16 Sep 2022 00:42:52 GMT'}, {'devid': '1DA36D3BE34D559A', 'id': 630539, 'readings': [1, 25.20366096496582, 51.53173065185547, 100.9321517944336, 125, 831.3306274414062, 1.0598562955856323], 'ts': 'Tue, 07 Feb 2023 11:29:20 GMT'}, {'devid': 'E7184ABA7A055FD1', 'id': 630537, 'readings': [1, 25.673006057739258, 52.50736618041992, 100.87647247314453, 117, 796.0401611328125, 0.9783512353897095], 'ts': 'Tue, 07 Feb 2023 11:29:11 GMT'}, {'devid': '99DD33EFB7990A71', 'id': 593219, 'readings': [1, 23.173173904418945, 42.10139465332031, 101.22635650634766, 132, 862.1188354492188, 1.136489987373352], 'ts': 'Fri, 16 Dec 2022 19:45:54 GMT'}], 'success': True}\n"
     ]
    }
   ],
   "source": [
    "print(requests.get(\n",
    "    url='https://model.brewai.com/api/sensor_readings?latest=true',\n",
    "    headers=brew_ai_headers\n",
    ").json())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .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>devid</th>\n",
       "      <th>name</th>\n",
       "      <th>rloc16</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>99DD33EFB7990A71</td>\n",
       "      <td>Opera Room</td>\n",
       "      <td>5126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>B84C4503F361D64A</td>\n",
       "      <td>Reception</td>\n",
       "      <td>9274</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7BB92D02D696C5C5</td>\n",
       "      <td>Workstations West</td>\n",
       "      <td>2051</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1DA36D3BE34D559A</td>\n",
       "      <td>Bridge Room</td>\n",
       "      <td>62956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>E7184ABA7A055FD1</td>\n",
       "      <td>Workstations East</td>\n",
       "      <td>2050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>A9DBA7135C924932</td>\n",
       "      <td>Mobile Sensor 2</td>\n",
       "      <td>28806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>5A744701608421E</td>\n",
       "      <td>Opera Room (old)</td>\n",
       "      <td>54275</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              devid               name  rloc16\n",
       "0  99DD33EFB7990A71         Opera Room    5126\n",
       "1  B84C4503F361D64A          Reception    9274\n",
       "2  7BB92D02D696C5C5  Workstations West    2051\n",
       "3  1DA36D3BE34D559A        Bridge Room   62956\n",
       "4  E7184ABA7A055FD1  Workstations East    2050\n",
       "5  A9DBA7135C924932    Mobile Sensor 2   28806\n",
       "6   5A744701608421E   Opera Room (old)   54275"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sensors_df = pd.DataFrame(sensors)\n",
    "sensors_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "readings = []\n",
    "\n",
    "start_ts = 1656633600\n",
    "end_ts = 1667260800\n",
    "\n",
    "for devid in sensors_df['devid']:\n",
    "    r = requests.get(\n",
    "        url=f'https://model.brewai.com/api/sensor_readings?devid={devid}&startTs={start_ts}&endTs={end_ts}',\n",
    "        headers=brew_ai_headers\n",
    "    ).json()['readings']\n",
    "    readings += r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.DataFrame(readings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[[\"null\", \"temperature\", \"humidity\", \"pressure\", \"iaq\", \"co2\", \"voc\"]] = pd.DataFrame(df['readings'].tolist())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop(['readings'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_full = df.join(sensors_df.set_index('devid'), on='devid')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .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>devid</th>\n",
       "      <th>id</th>\n",
       "      <th>row_number</th>\n",
       "      <th>ts</th>\n",
       "      <th>null</th>\n",
       "      <th>temperature</th>\n",
       "      <th>humidity</th>\n",
       "      <th>pressure</th>\n",
       "      <th>iaq</th>\n",
       "      <th>co2</th>\n",
       "      <th>voc</th>\n",
       "      <th>name</th>\n",
       "      <th>rloc16</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>99DD33EFB7990A71</td>\n",
       "      <td>37270</td>\n",
       "      <td>1</td>\n",
       "      <td>Mon, 05 Sep 2022 03:20:30 GMT</td>\n",
       "      <td>0</td>\n",
       "      <td>25.92</td>\n",
       "      <td>39.04</td>\n",
       "      <td>101.55</td>\n",
       "      <td>50</td>\n",
       "      <td>600.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Opera Room</td>\n",
       "      <td>5126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>99DD33EFB7990A71</td>\n",
       "      <td>37275</td>\n",
       "      <td>1</td>\n",
       "      <td>Mon, 05 Sep 2022 03:21:30 GMT</td>\n",
       "      <td>0</td>\n",
       "      <td>25.46</td>\n",
       "      <td>39.67</td>\n",
       "      <td>101.56</td>\n",
       "      <td>50</td>\n",
       "      <td>600.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Opera Room</td>\n",
       "      <td>5126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>99DD33EFB7990A71</td>\n",
       "      <td>37280</td>\n",
       "      <td>1</td>\n",
       "      <td>Mon, 05 Sep 2022 03:22:30 GMT</td>\n",
       "      <td>0</td>\n",
       "      <td>25.33</td>\n",
       "      <td>39.98</td>\n",
       "      <td>101.55</td>\n",
       "      <td>50</td>\n",
       "      <td>600.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Opera Room</td>\n",
       "      <td>5126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>99DD33EFB7990A71</td>\n",
       "      <td>37285</td>\n",
       "      <td>1</td>\n",
       "      <td>Mon, 05 Sep 2022 03:23:30 GMT</td>\n",
       "      <td>0</td>\n",
       "      <td>25.27</td>\n",
       "      <td>39.97</td>\n",
       "      <td>101.54</td>\n",
       "      <td>50</td>\n",
       "      <td>600.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Opera Room</td>\n",
       "      <td>5126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>99DD33EFB7990A71</td>\n",
       "      <td>37290</td>\n",
       "      <td>1</td>\n",
       "      <td>Mon, 05 Sep 2022 03:24:30 GMT</td>\n",
       "      <td>0</td>\n",
       "      <td>25.11</td>\n",
       "      <td>40.38</td>\n",
       "      <td>101.55</td>\n",
       "      <td>50</td>\n",
       "      <td>600.0</td>\n",
       "      <td>0.5</td>\n",
       "      <td>Opera Room</td>\n",
       "      <td>5126</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              devid     id  row_number                             ts  null  \\\n",
       "0  99DD33EFB7990A71  37270           1  Mon, 05 Sep 2022 03:20:30 GMT     0   \n",
       "1  99DD33EFB7990A71  37275           1  Mon, 05 Sep 2022 03:21:30 GMT     0   \n",
       "2  99DD33EFB7990A71  37280           1  Mon, 05 Sep 2022 03:22:30 GMT     0   \n",
       "3  99DD33EFB7990A71  37285           1  Mon, 05 Sep 2022 03:23:30 GMT     0   \n",
       "4  99DD33EFB7990A71  37290           1  Mon, 05 Sep 2022 03:24:30 GMT     0   \n",
       "\n",
       "   temperature  humidity  pressure  iaq    co2  voc        name  rloc16  \n",
       "0        25.92     39.04    101.55   50  600.0  0.5  Opera Room    5126  \n",
       "1        25.46     39.67    101.56   50  600.0  0.5  Opera Room    5126  \n",
       "2        25.33     39.98    101.55   50  600.0  0.5  Opera Room    5126  \n",
       "3        25.27     39.97    101.54   50  600.0  0.5  Opera Room    5126  \n",
       "4        25.11     40.38    101.55   50  600.0  0.5  Opera Room    5126  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_full.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df_full.copy()\n",
    "df.ts = pd.to_datetime(df.ts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Timestamp('2022-08-30 01:43:34+0000', tz='UTC')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.ts.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Response [200]>"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datalake.pandas.save_dataframe(df, layer='bronze', source_type='brewai', source_name='sensors', ts='exports', table='aug-oct.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_full = datalake.pandas.dataframe_from_datalake(layer='bronze', source_type='brewai', source_name='sensors', ts='2022Sept-Nov', table='all.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot: xlabel='ts'>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_full[df_full['devid'] == '1DA36D3BE34D559A'].plot(x='ts', y='temperature')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.10.4 ('venv': venv)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.4"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "4050f9686abf1246cf601aac195d2b060e623e3cd58cd405239d502df97611e7"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}