test_kafka.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%pip install plotly\n",
    "%pip install nbformat"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from kafka.admin import KafkaAdminClient, NewTopic\n",
    "from kafka.structs import TopicPartition\n",
    "\n",
    "import plotly.express as px\n",
    "import json\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "b'TEST'\n",
      "b'TEST2'\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Minutes5UTC</th>\n",
       "      <th>Minutes5DK</th>\n",
       "      <th>PriceArea</th>\n",
       "      <th>ProductionLt100MW</th>\n",
       "      <th>ProductionGe100MW</th>\n",
       "      <th>OffshoreWindPower</th>\n",
       "      <th>OnshoreWindPower</th>\n",
       "      <th>SolarPower</th>\n",
       "      <th>ExchangeGreatBelt</th>\n",
       "      <th>ExchangeGermany</th>\n",
       "      <th>ExchangeNetherlands</th>\n",
       "      <th>ExchangeNorway</th>\n",
       "      <th>ExchangeSweden</th>\n",
       "      <th>BornholmSE4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2023-02-06T09:20:00</td>\n",
       "      <td>2023-02-06T10:20:00</td>\n",
       "      <td>DK1</td>\n",
       "      <td>594.280029</td>\n",
       "      <td>1022.679993</td>\n",
       "      <td>-7.280000</td>\n",
       "      <td>28.850000</td>\n",
       "      <td>218.990005</td>\n",
       "      <td>-354.000000</td>\n",
       "      <td>-568.909973</td>\n",
       "      <td>700.380005</td>\n",
       "      <td>1107.680054</td>\n",
       "      <td>236.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2023-02-06T09:20:00</td>\n",
       "      <td>2023-02-06T10:20:00</td>\n",
       "      <td>DK2</td>\n",
       "      <td>195.460007</td>\n",
       "      <td>548.739990</td>\n",
       "      <td>31.840000</td>\n",
       "      <td>25.070000</td>\n",
       "      <td>77.379997</td>\n",
       "      <td>354.000000</td>\n",
       "      <td>-421.899994</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>974.669983</td>\n",
       "      <td>32.049999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2023-02-06T09:25:00</td>\n",
       "      <td>2023-02-06T10:25:00</td>\n",
       "      <td>DK1</td>\n",
       "      <td>592.340027</td>\n",
       "      <td>1012.020020</td>\n",
       "      <td>-6.270000</td>\n",
       "      <td>22.940001</td>\n",
       "      <td>234.770004</td>\n",
       "      <td>-354.000000</td>\n",
       "      <td>-558.880005</td>\n",
       "      <td>700.380005</td>\n",
       "      <td>1107.339966</td>\n",
       "      <td>236.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2023-02-06T09:25:00</td>\n",
       "      <td>2023-02-06T10:25:00</td>\n",
       "      <td>DK2</td>\n",
       "      <td>198.199997</td>\n",
       "      <td>551.010010</td>\n",
       "      <td>24.440001</td>\n",
       "      <td>24.740000</td>\n",
       "      <td>76.830002</td>\n",
       "      <td>354.000000</td>\n",
       "      <td>-421.799988</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1017.760010</td>\n",
       "      <td>33.689999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2023-02-06T09:30:00</td>\n",
       "      <td>2023-02-06T10:30:00</td>\n",
       "      <td>DK1</td>\n",
       "      <td>597.530029</td>\n",
       "      <td>993.780029</td>\n",
       "      <td>-2.800000</td>\n",
       "      <td>20.780001</td>\n",
       "      <td>235.080002</td>\n",
       "      <td>-354.000000</td>\n",
       "      <td>-538.559998</td>\n",
       "      <td>700.380005</td>\n",
       "      <td>1107.770020</td>\n",
       "      <td>236.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>2023-02-06T09:40:00</td>\n",
       "      <td>2023-02-06T10:40:00</td>\n",
       "      <td>DK2</td>\n",
       "      <td>199.220001</td>\n",
       "      <td>548.549988</td>\n",
       "      <td>13.660000</td>\n",
       "      <td>25.559999</td>\n",
       "      <td>86.760002</td>\n",
       "      <td>354.000000</td>\n",
       "      <td>-422.190002</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>980.859985</td>\n",
       "      <td>32.430000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>2023-02-06T09:45:00</td>\n",
       "      <td>2023-02-06T10:45:00</td>\n",
       "      <td>DK1</td>\n",
       "      <td>585.700012</td>\n",
       "      <td>976.580017</td>\n",
       "      <td>2.040000</td>\n",
       "      <td>17.700001</td>\n",
       "      <td>251.490005</td>\n",
       "      <td>-354.079987</td>\n",
       "      <td>-564.239990</td>\n",
       "      <td>700.380005</td>\n",
       "      <td>1107.530029</td>\n",
       "      <td>236.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>2023-02-06T09:45:00</td>\n",
       "      <td>2023-02-06T10:45:00</td>\n",
       "      <td>DK2</td>\n",
       "      <td>194.229996</td>\n",
       "      <td>548.830017</td>\n",
       "      <td>9.590000</td>\n",
       "      <td>26.020000</td>\n",
       "      <td>87.750000</td>\n",
       "      <td>354.079987</td>\n",
       "      <td>-421.250000</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>989.140015</td>\n",
       "      <td>32.840000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>2023-02-06T09:50:00</td>\n",
       "      <td>2023-02-06T10:50:00</td>\n",
       "      <td>DK1</td>\n",
       "      <td>589.419983</td>\n",
       "      <td>972.770020</td>\n",
       "      <td>3.370000</td>\n",
       "      <td>19.629999</td>\n",
       "      <td>257.420013</td>\n",
       "      <td>-287.910004</td>\n",
       "      <td>-706.950012</td>\n",
       "      <td>700.380005</td>\n",
       "      <td>1107.819946</td>\n",
       "      <td>312.000000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>2023-02-06T09:50:00</td>\n",
       "      <td>2023-02-06T10:50:00</td>\n",
       "      <td>DK2</td>\n",
       "      <td>195.300003</td>\n",
       "      <td>542.890015</td>\n",
       "      <td>10.930000</td>\n",
       "      <td>25.299999</td>\n",
       "      <td>88.379997</td>\n",
       "      <td>287.910004</td>\n",
       "      <td>-420.760010</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1067.060059</td>\n",
       "      <td>32.770000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>118 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             Minutes5UTC           Minutes5DK PriceArea  ProductionLt100MW  \\\n",
       "0    2023-02-06T09:20:00  2023-02-06T10:20:00       DK1         594.280029   \n",
       "1    2023-02-06T09:20:00  2023-02-06T10:20:00       DK2         195.460007   \n",
       "2    2023-02-06T09:25:00  2023-02-06T10:25:00       DK1         592.340027   \n",
       "3    2023-02-06T09:25:00  2023-02-06T10:25:00       DK2         198.199997   \n",
       "4    2023-02-06T09:30:00  2023-02-06T10:30:00       DK1         597.530029   \n",
       "..                   ...                  ...       ...                ...   \n",
       "113  2023-02-06T09:40:00  2023-02-06T10:40:00       DK2         199.220001   \n",
       "114  2023-02-06T09:45:00  2023-02-06T10:45:00       DK1         585.700012   \n",
       "115  2023-02-06T09:45:00  2023-02-06T10:45:00       DK2         194.229996   \n",
       "116  2023-02-06T09:50:00  2023-02-06T10:50:00       DK1         589.419983   \n",
       "117  2023-02-06T09:50:00  2023-02-06T10:50:00       DK2         195.300003   \n",
       "\n",
       "     ProductionGe100MW  OffshoreWindPower  OnshoreWindPower  SolarPower  \\\n",
       "0          1022.679993          -7.280000         28.850000  218.990005   \n",
       "1           548.739990          31.840000         25.070000   77.379997   \n",
       "2          1012.020020          -6.270000         22.940001  234.770004   \n",
       "3           551.010010          24.440001         24.740000   76.830002   \n",
       "4           993.780029          -2.800000         20.780001  235.080002   \n",
       "..                 ...                ...               ...         ...   \n",
       "113         548.549988          13.660000         25.559999   86.760002   \n",
       "114         976.580017           2.040000         17.700001  251.490005   \n",
       "115         548.830017           9.590000         26.020000   87.750000   \n",
       "116         972.770020           3.370000         19.629999  257.420013   \n",
       "117         542.890015          10.930000         25.299999   88.379997   \n",
       "\n",
       "     ExchangeGreatBelt  ExchangeGermany  ExchangeNetherlands  ExchangeNorway  \\\n",
       "0          -354.000000      -568.909973           700.380005     1107.680054   \n",
       "1           354.000000      -421.899994                  NaN             NaN   \n",
       "2          -354.000000      -558.880005           700.380005     1107.339966   \n",
       "3           354.000000      -421.799988                  NaN             NaN   \n",
       "4          -354.000000      -538.559998           700.380005     1107.770020   \n",
       "..                 ...              ...                  ...             ...   \n",
       "113         354.000000      -422.190002                  NaN             NaN   \n",
       "114        -354.079987      -564.239990           700.380005     1107.530029   \n",
       "115         354.079987      -421.250000                  NaN             NaN   \n",
       "116        -287.910004      -706.950012           700.380005     1107.819946   \n",
       "117         287.910004      -420.760010                  NaN             NaN   \n",
       "\n",
       "     ExchangeSweden  BornholmSE4  \n",
       "0        236.000000          NaN  \n",
       "1        974.669983    32.049999  \n",
       "2        236.000000          NaN  \n",
       "3       1017.760010    33.689999  \n",
       "4        236.000000          NaN  \n",
       "..              ...          ...  \n",
       "113      980.859985    32.430000  \n",
       "114      236.000000          NaN  \n",
       "115      989.140015    32.840000  \n",
       "116      312.000000          NaN  \n",
       "117     1067.060059    32.770000  \n",
       "\n",
       "[118 rows x 14 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from kafka import KafkaConsumer\n",
    "\n",
    "# auto_offset_reset & group_id are CRUCIAL for it to work. No idea why\n",
    "consumer = KafkaConsumer('energy_api', consumer_timeout_ms=10000, bootstrap_servers = 'localhost:9092', auto_offset_reset='earliest', group_id=None)\n",
    "\n",
    "dfs = []\n",
    "\n",
    "partitions = consumer.partitions_for_topic('energy_api')\n",
    "\n",
    "for p in partitions:\n",
    "    topic_partition = TopicPartition('energy_api', p)\n",
    "    # Seek offset 0\n",
    "    # consumer.seek(partition=topic_partition, offset=0)\n",
    "    for msg in consumer:\n",
    "        try:\n",
    "            dict = json.loads(msg.value)\n",
    "            df = pd.DataFrame.from_records(dict)\n",
    "            dfs.append(df)\n",
    "            \n",
    "        except:\n",
    "            print(msg.value[:20])\n",
    "            continue\n",
    "df = pd.concat(dfs, ignore_index=True) # concatenate all the data frames in the list.\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"Minutes5DK\"] = pd.to_datetime(df[\"Minutes5DK\"])\n",
    "df[\"Minutes5UTC\"] = pd.to_datetime(df[\"Minutes5UTC\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_9696/1471977883.py:1: FutureWarning:\n",
      "\n",
      "The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "\n"
     ]
    },
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ProductionLt100MW</th>\n",
       "      <th>ProductionGe100MW</th>\n",
       "      <th>OffshoreWindPower</th>\n",
       "      <th>OnshoreWindPower</th>\n",
       "      <th>SolarPower</th>\n",
       "      <th>ExchangeGreatBelt</th>\n",
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       "      <th>ExchangeSweden</th>\n",
       "      <th>BornholmSE4</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Minutes5DK</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "    <tr>\n",
       "      <th>2023-02-02 19:35:00</th>\n",
       "      <td>408.099999</td>\n",
       "      <td>792.309998</td>\n",
       "      <td>246.910005</td>\n",
       "      <td>406.589989</td>\n",
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       "      <td>-1340.479980</td>\n",
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       "      <td>1109.449951</td>\n",
       "      <td>778.239990</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-02 19:40:00</th>\n",
       "      <td>407.565010</td>\n",
       "      <td>788.039978</td>\n",
       "      <td>247.250002</td>\n",
       "      <td>411.050003</td>\n",
       "      <td>0.090</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1350.304993</td>\n",
       "      <td>700.039978</td>\n",
       "      <td>1110.329956</td>\n",
       "      <td>784.709992</td>\n",
       "      <td>26.620001</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-02 19:45:00</th>\n",
       "      <td>408.435013</td>\n",
       "      <td>776.605011</td>\n",
       "      <td>260.690005</td>\n",
       "      <td>419.334999</td>\n",
       "      <td>0.095</td>\n",
       "      <td>0.0</td>\n",
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       "      <td>700.039978</td>\n",
       "      <td>1109.199951</td>\n",
       "      <td>771.200012</td>\n",
       "      <td>26.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-02 19:50:00</th>\n",
       "      <td>403.229996</td>\n",
       "      <td>766.269989</td>\n",
       "      <td>272.569985</td>\n",
       "      <td>428.825012</td>\n",
       "      <td>0.100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1403.049988</td>\n",
       "      <td>700.039978</td>\n",
       "      <td>1104.819946</td>\n",
       "      <td>784.600006</td>\n",
       "      <td>26.719999</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-02-03 18:10:00</th>\n",
       "      <td>256.095009</td>\n",
       "      <td>598.299988</td>\n",
       "      <td>960.029999</td>\n",
       "      <td>998.109970</td>\n",
       "      <td>2.150</td>\n",
       "      <td>0.0</td>\n",
       "      <td>63.964996</td>\n",
       "      <td>-700.109985</td>\n",
       "      <td>-813.000000</td>\n",
       "      <td>446.144989</td>\n",
       "      <td>-1.250000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     ProductionLt100MW  ProductionGe100MW  OffshoreWindPower  \\\n",
       "Minutes5DK                                                                     \n",
       "2023-02-02 19:35:00         408.099999         792.309998         246.910005   \n",
       "2023-02-02 19:40:00         407.565010         788.039978         247.250002   \n",
       "2023-02-02 19:45:00         408.435013         776.605011         260.690005   \n",
       "2023-02-02 19:50:00         403.229996         766.269989         272.569985   \n",
       "2023-02-03 18:10:00         256.095009         598.299988         960.029999   \n",
       "\n",
       "                     OnshoreWindPower  SolarPower  ExchangeGreatBelt  \\\n",
       "Minutes5DK                                                             \n",
       "2023-02-02 19:35:00        406.589989       0.095                0.0   \n",
       "2023-02-02 19:40:00        411.050003       0.090                0.0   \n",
       "2023-02-02 19:45:00        419.334999       0.095                0.0   \n",
       "2023-02-02 19:50:00        428.825012       0.100                0.0   \n",
       "2023-02-03 18:10:00        998.109970       2.150                0.0   \n",
       "\n",
       "                     ExchangeGermany  ExchangeNetherlands  ExchangeNorway  \\\n",
       "Minutes5DK                                                                  \n",
       "2023-02-02 19:35:00     -1340.479980           700.039978     1109.449951   \n",
       "2023-02-02 19:40:00     -1350.304993           700.039978     1110.329956   \n",
       "2023-02-02 19:45:00     -1371.515015           700.039978     1109.199951   \n",
       "2023-02-02 19:50:00     -1403.049988           700.039978     1104.819946   \n",
       "2023-02-03 18:10:00        63.964996          -700.109985     -813.000000   \n",
       "\n",
       "                     ExchangeSweden  BornholmSE4  \n",
       "Minutes5DK                                        \n",
       "2023-02-02 19:35:00      778.239990    26.549999  \n",
       "2023-02-02 19:40:00      784.709992    26.620001  \n",
       "2023-02-02 19:45:00      771.200012    26.650000  \n",
       "2023-02-02 19:50:00      784.600006    26.719999  \n",
       "2023-02-03 18:10:00      446.144989    -1.250000  "
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     "execution_count": 30,
     "metadata": {},
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    "avg_by_minute = df.groupby(df.Minutes5DK).mean()\n",
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          1
         ],
         "title": {
          "text": "Minutes5DK"
         }
        },
        "yaxis": {
         "anchor": "x",
         "domain": [
          0,
          1
         ],
         "title": {
          "text": "value"
         }
        }
       }
      }
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "px.line(data_frame = avg_by_minute, x=avg_by_minute.index, y=[\"ExchangeGermany\", \"ExchangeNetherlands\", \"ExchangeNorway\", \"ExchangeSweden\"])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.10 64-bit",
   "language": "python",
   "name": "python3"
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   "codemirror_mode": {
    "name": "ipython",
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  },
  "orig_nbformat": 4,
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