Updated_preprocessing_done

TSLA_stock_price.csv

@@ -1,4 +1,5 @@
 date,1. open,2. high,3. low,4. close,5. volume,ticker
+2024-05-03,182.1,184.78,178.42,181.19,75491539.0,TSLA
 2024-05-02,182.86,184.6,176.02,180.01,89148041.0,TSLA
 2024-05-01,182.0,185.86,179.01,179.99,92829719.0,TSLA
 2024-04-30,186.98,190.95,182.8401,183.28,127031787.0,TSLA

feature_pipeline.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -12,136 +12,109 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 25,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
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-      "Using cached great_expectations-0.18.12-py3-none-any.whl (5.4 MB)\n",
-      "Installing collected packages: great_expectations\n",
-      "  Attempting uninstall: great_expectations\n",
-      "    Found existing installation: great-expectations 0.18.13\n",
-      "    Uninstalling great-expectations-0.18.13:\n",
-      "      Successfully uninstalled great-expectations-0.18.13\n",
-      "Successfully installed great_expectations-0.18.12\n"
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+      "Requirement already satisfied: comm>=0.1.1 in /Applications/anaconda3/lib/python3.11/site-packages (from ipykernel>=4.5.1->ipywidgets>=7.5.1->great_expectations==0.18.12) (0.1.2)\n",
+      "Requirement already satisfied: debugpy>=1.0 in /Applications/anaconda3/lib/python3.11/site-packages (from ipykernel>=4.5.1->ipywidgets>=7.5.1->great_expectations==0.18.12) (1.6.7)\n",
+      "Requirement already satisfied: psutil in /Applications/anaconda3/lib/python3.11/site-packages (from ipykernel>=4.5.1->ipywidgets>=7.5.1->great_expectations==0.18.12) (5.9.0)\n",
+      "Requirement already satisfied: parso<0.9.0,>=0.8.0 in /Applications/anaconda3/lib/python3.11/site-packages (from jedi>=0.16->Ipython>=7.16.3->great_expectations==0.18.12) (0.8.3)\n",
+      "Requirement already satisfied: platformdirs>=2.5 in /Applications/anaconda3/lib/python3.11/site-packages (from jupyter-core->nbformat>=5.0->great_expectations==0.18.12) (2.5.2)\n",
+      "Requirement already satisfied: jupyter-server>=1.8 in /Applications/anaconda3/lib/python3.11/site-packages (from nbclassic>=0.4.7->notebook>=6.4.10->great_expectations==0.18.12) (1.23.4)\n",
+      "Requirement already satisfied: notebook-shim>=0.1.0 in /Applications/anaconda3/lib/python3.11/site-packages (from nbclassic>=0.4.7->notebook>=6.4.10->great_expectations==0.18.12) (0.2.2)\n",
+      "Requirement already satisfied: lxml in /Applications/anaconda3/lib/python3.11/site-packages (from nbconvert>=5->notebook>=6.4.10->great_expectations==0.18.12) (4.9.2)\n",
+      "Requirement already satisfied: beautifulsoup4 in /Applications/anaconda3/lib/python3.11/site-packages (from nbconvert>=5->notebook>=6.4.10->great_expectations==0.18.12) (4.12.2)\n",
+      "Requirement already satisfied: bleach in /Applications/anaconda3/lib/python3.11/site-packages (from nbconvert>=5->notebook>=6.4.10->great_expectations==0.18.12) (4.1.0)\n",
+      "Requirement already satisfied: defusedxml in /Applications/anaconda3/lib/python3.11/site-packages (from nbconvert>=5->notebook>=6.4.10->great_expectations==0.18.12) (0.7.1)\n",
+      "Requirement already satisfied: jupyterlab-pygments in /Applications/anaconda3/lib/python3.11/site-packages (from nbconvert>=5->notebook>=6.4.10->great_expectations==0.18.12) (0.1.2)\n",
+      "Requirement already satisfied: nbclient>=0.5.0 in /Applications/anaconda3/lib/python3.11/site-packages (from nbconvert>=5->notebook>=6.4.10->great_expectations==0.18.12) (0.5.13)\n",
+      "Requirement already satisfied: pandocfilters>=1.4.1 in /Applications/anaconda3/lib/python3.11/site-packages (from nbconvert>=5->notebook>=6.4.10->great_expectations==0.18.12) (1.5.0)\n",
+      "Requirement already satisfied: tinycss2 in /Applications/anaconda3/lib/python3.11/site-packages (from nbconvert>=5->notebook>=6.4.10->great_expectations==0.18.12) (1.2.1)\n",
+      "Requirement already satisfied: ptyprocess>=0.5 in /Applications/anaconda3/lib/python3.11/site-packages (from pexpect>4.3->Ipython>=7.16.3->great_expectations==0.18.12) (0.7.0)\n",
+      "Requirement already satisfied: wcwidth in /Applications/anaconda3/lib/python3.11/site-packages (from prompt-toolkit!=3.0.37,<3.1.0,>=3.0.30->Ipython>=7.16.3->great_expectations==0.18.12) (0.2.5)\n",
+      "Requirement already satisfied: argon2-cffi-bindings in /Applications/anaconda3/lib/python3.11/site-packages (from argon2-cffi->notebook>=6.4.10->great_expectations==0.18.12) (21.2.0)\n",
+      "Requirement already satisfied: executing in /Applications/anaconda3/lib/python3.11/site-packages (from stack-data->Ipython>=7.16.3->great_expectations==0.18.12) (0.8.3)\n",
+      "Requirement already satisfied: asttokens in /Applications/anaconda3/lib/python3.11/site-packages (from stack-data->Ipython>=7.16.3->great_expectations==0.18.12) (2.0.5)\n",
+      "Requirement already satisfied: pure-eval in /Applications/anaconda3/lib/python3.11/site-packages (from stack-data->Ipython>=7.16.3->great_expectations==0.18.12) (0.2.2)\n",
+      "Requirement already satisfied: anyio<4,>=3.1.0 in /Applications/anaconda3/lib/python3.11/site-packages (from jupyter-server>=1.8->nbclassic>=0.4.7->notebook>=6.4.10->great_expectations==0.18.12) (3.7.1)\n",
+      "Requirement already satisfied: websocket-client in /Applications/anaconda3/lib/python3.11/site-packages (from jupyter-server>=1.8->nbclassic>=0.4.7->notebook>=6.4.10->great_expectations==0.18.12) (1.7.0)\n",
+      "Requirement already satisfied: soupsieve>1.2 in /Applications/anaconda3/lib/python3.11/site-packages (from beautifulsoup4->nbconvert>=5->notebook>=6.4.10->great_expectations==0.18.12) (2.4)\n",
+      "Requirement already satisfied: webencodings in /Applications/anaconda3/lib/python3.11/site-packages (from bleach->nbconvert>=5->notebook>=6.4.10->great_expectations==0.18.12) (0.5.1)\n",
+      "Requirement already satisfied: sniffio>=1.1 in /Applications/anaconda3/lib/python3.11/site-packages (from anyio<4,>=3.1.0->jupyter-server>=1.8->nbclassic>=0.4.7->notebook>=6.4.10->great_expectations==0.18.12) (1.2.0)\n"
      ]
     }
    ],
@@ -151,7 +124,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -172,23 +145,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 27,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "            1. open  2. high    3. low  4. close    5. volume\n",
-      "date                                                         \n",
-      "2024-05-03   182.10   184.78  178.4200    181.19   75491539.0\n",
-      "2024-05-02   182.86   184.60  176.0200    180.01   89148041.0\n",
-      "2024-05-01   182.00   185.86  179.0100    179.99   92829719.0\n",
-      "2024-04-30   186.98   190.95  182.8401    183.28  127031787.0\n",
-      "2024-04-29   188.42   198.87  184.5400    194.05  243869678.0\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "#from alpha_vantage.timeseries import TimeSeries\n",
     "#import pandas as pd\n",
@@ -206,69 +165,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 28,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "<class 'pandas.core.frame.DataFrame'>\n",
-      "DatetimeIndex: 3483 entries, 2024-04-30 to 2010-06-29\n",
-      "Data columns (total 5 columns):\n",
-      " #   Column     Non-Null Count  Dtype  \n",
-      "---  ------     --------------  -----  \n",
-      " 0   1. open    3483 non-null   float64\n",
-      " 1   2. high    3483 non-null   float64\n",
-      " 2   3. low     3483 non-null   float64\n",
-      " 3   4. close   3483 non-null   float64\n",
-      " 4   5. volume  3483 non-null   float64\n",
-      "dtypes: float64(5)\n",
-      "memory usage: 163.3 KB\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "#data.info()"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 29,
    "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "{'1. Information': 'Daily Prices (open, high, low, close) and Volumes',\n",
-       " '2. Symbol': 'TSLA',\n",
-       " '3. Last Refreshed': '2024-04-30',\n",
-       " '4. Output Size': 'Full size',\n",
-       " '5. Time Zone': 'US/Eastern'}"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "#meta_data"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 30,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Data saved to /Users/manos/Documents/BDS/MLops_mod/TSLA_stock_price.csv\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Define your file path and name\n",
     "#file_path = 'TSLA_stock_price.csv'  # Customize the path and filename\n",
@@ -281,7 +198,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [
     {
@@ -289,11 +206,11 @@
      "output_type": "stream",
      "text": [
       "         date  1. open  2. high    3. low  4. close    5. volume ticker\n",
-      "0  2024-05-02   182.86   184.60  176.0200    180.01   89148041.0   TSLA\n",
-      "1  2024-05-01   182.00   185.86  179.0100    179.99   92829719.0   TSLA\n",
-      "2  2024-04-30   186.98   190.95  182.8401    183.28  127031787.0   TSLA\n",
-      "3  2024-04-29   188.42   198.87  184.5400    194.05  243869678.0   TSLA\n",
-      "4  2024-04-26   168.85   172.12  166.3700    168.29  109815725.0   TSLA\n"
+      "0  2024-05-03   182.10   184.78  178.4200    181.19   75491539.0   TSLA\n",
+      "1  2024-05-02   182.86   184.60  176.0200    180.01   89148041.0   TSLA\n",
+      "2  2024-05-01   182.00   185.86  179.0100    179.99   92829719.0   TSLA\n",
+      "3  2024-04-30   186.98   190.95  182.8401    183.28  127031787.0   TSLA\n",
+      "4  2024-04-29   188.42   198.87  184.5400    194.05  243869678.0   TSLA\n"
      ]
     }
    ],
@@ -306,16 +223,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Connection closed.\n",
       "Connected. Call `.close()` to terminate connection gracefully.\n",
       "\n",
-      "Logged in to project, explore it here https://c.app.hopsworks.ai:443/p/549015\n",
+      "Logged in to project, explore it here https://c.app.hopsworks.ai:443/p/549016\n",
       "Connected. Call `.close()` to terminate connection gracefully.\n"
      ]
     }
@@ -328,7 +246,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 33,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -337,7 +255,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -349,7 +267,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -385,6 +303,16 @@
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
+       "      <td>2024-05-03</td>\n",
+       "      <td>182.10</td>\n",
+       "      <td>184.7800</td>\n",
+       "      <td>178.4200</td>\n",
+       "      <td>181.19</td>\n",
+       "      <td>75491539.0</td>\n",
+       "      <td>TSLA</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
        "      <td>2024-05-02</td>\n",
        "      <td>182.86</td>\n",
        "      <td>184.6000</td>\n",
@@ -394,7 +322,7 @@
        "      <td>TSLA</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1</th>\n",
+       "      <th>2</th>\n",
        "      <td>2024-05-01</td>\n",
        "      <td>182.00</td>\n",
        "      <td>185.8600</td>\n",
@@ -404,7 +332,7 @@
        "      <td>TSLA</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>2</th>\n",
+       "      <th>3</th>\n",
        "      <td>2024-04-30</td>\n",
        "      <td>186.98</td>\n",
        "      <td>190.9500</td>\n",
@@ -414,7 +342,7 @@
        "      <td>TSLA</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3</th>\n",
+       "      <th>4</th>\n",
        "      <td>2024-04-29</td>\n",
        "      <td>188.42</td>\n",
        "      <td>198.8700</td>\n",
@@ -424,16 +352,6 @@
        "      <td>TSLA</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>4</th>\n",
-       "      <td>2024-04-26</td>\n",
-       "      <td>168.85</td>\n",
-       "      <td>172.1200</td>\n",
-       "      <td>166.3700</td>\n",
-       "      <td>168.29</td>\n",
-       "      <td>109815725.0</td>\n",
-       "      <td>TSLA</td>\n",
-       "    </tr>\n",
-       "    <tr>\n",
        "      <th>...</th>\n",
        "      <td>...</td>\n",
        "      <td>...</td>\n",
@@ -444,7 +362,7 @@
        "      <td>...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3480</th>\n",
+       "      <th>3481</th>\n",
        "      <td>2010-07-06</td>\n",
        "      <td>20.00</td>\n",
        "      <td>20.0000</td>\n",
@@ -454,7 +372,7 @@
        "      <td>TSLA</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3481</th>\n",
+       "      <th>3482</th>\n",
        "      <td>2010-07-02</td>\n",
        "      <td>23.00</td>\n",
        "      <td>23.1000</td>\n",
@@ -464,7 +382,7 @@
        "      <td>TSLA</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3482</th>\n",
+       "      <th>3483</th>\n",
        "      <td>2010-07-01</td>\n",
        "      <td>25.00</td>\n",
        "      <td>25.9200</td>\n",
@@ -474,7 +392,7 @@
        "      <td>TSLA</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3483</th>\n",
+       "      <th>3484</th>\n",
        "      <td>2010-06-30</td>\n",
        "      <td>25.79</td>\n",
        "      <td>30.4192</td>\n",
@@ -484,7 +402,7 @@
        "      <td>TSLA</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>3484</th>\n",
+       "      <th>3485</th>\n",
        "      <td>2010-06-29</td>\n",
        "      <td>19.00</td>\n",
        "      <td>25.0000</td>\n",
@@ -495,27 +413,27 @@
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
-       "<p>3485 rows × 7 columns</p>\n",
+       "<p>3486 rows × 7 columns</p>\n",
        "</div>"
       ],
       "text/plain": [
        "            date  1. open   2. high    3. low  4. close    5. volume ticker\n",
-       "0     2024-05-02   182.86  184.6000  176.0200    180.01   89148041.0   TSLA\n",
-       "1     2024-05-01   182.00  185.8600  179.0100    179.99   92829719.0   TSLA\n",
-       "2     2024-04-30   186.98  190.9500  182.8401    183.28  127031787.0   TSLA\n",
-       "3     2024-04-29   188.42  198.8700  184.5400    194.05  243869678.0   TSLA\n",
-       "4     2024-04-26   168.85  172.1200  166.3700    168.29  109815725.0   TSLA\n",
+       "0     2024-05-03   182.10  184.7800  178.4200    181.19   75491539.0   TSLA\n",
+       "1     2024-05-02   182.86  184.6000  176.0200    180.01   89148041.0   TSLA\n",
+       "2     2024-05-01   182.00  185.8600  179.0100    179.99   92829719.0   TSLA\n",
+       "3     2024-04-30   186.98  190.9500  182.8401    183.28  127031787.0   TSLA\n",
+       "4     2024-04-29   188.42  198.8700  184.5400    194.05  243869678.0   TSLA\n",
        "...          ...      ...       ...       ...       ...          ...    ...\n",
-       "3480  2010-07-06    20.00   20.0000   15.8300     16.11    6866900.0   TSLA\n",
-       "3481  2010-07-02    23.00   23.1000   18.7100     19.20    5139800.0   TSLA\n",
-       "3482  2010-07-01    25.00   25.9200   20.2700     21.96    8218800.0   TSLA\n",
-       "3483  2010-06-30    25.79   30.4192   23.3000     23.83   17187100.0   TSLA\n",
-       "3484  2010-06-29    19.00   25.0000   17.5400     23.89   18766300.0   TSLA\n",
+       "3481  2010-07-06    20.00   20.0000   15.8300     16.11    6866900.0   TSLA\n",
+       "3482  2010-07-02    23.00   23.1000   18.7100     19.20    5139800.0   TSLA\n",
+       "3483  2010-07-01    25.00   25.9200   20.2700     21.96    8218800.0   TSLA\n",
+       "3484  2010-06-30    25.79   30.4192   23.3000     23.83   17187100.0   TSLA\n",
+       "3485  2010-06-29    19.00   25.0000   17.5400     23.89   18766300.0   TSLA\n",
        "\n",
-       "[3485 rows x 7 columns]"
+       "[3486 rows x 7 columns]"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -526,7 +444,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -536,7 +454,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
@@ -553,7 +471,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 38,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -566,14 +484,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 39,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2024-05-04 20:50:09,340 WARNING: DeprecationWarning: Providing event_time as a single-element list is deprecated and will be dropped in future versions. Provide the feature_name string instead.\n",
+      "2024-05-06 11:35:29,224 WARNING: DeprecationWarning: Providing event_time as a single-element list is deprecated and will be dropped in future versions. Provide the feature_name string instead.\n",
       "\n"
      ]
     }
@@ -583,7 +501,7 @@
     "tesla_fg = fs.get_or_create_feature_group(\n",
     "    name=\"tesla_stock\",\n",
     "    description=\"Tesla stock dataset from alpha vantage\",\n",
-    "    version=3,\n",
+    "    version=1,\n",
     "    primary_key=[\"ticker\"],\n",
     "    event_time=['date'],\n",
     "    online_enabled=False,\n",
@@ -592,7 +510,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 40,
    "metadata": {},
    "outputs": [
     {
@@ -600,18 +518,18 @@
      "output_type": "stream",
      "text": [
       "Feature Group created successfully, explore it at \n",
-      "https://c.app.hopsworks.ai:443/p/549015/fs/544840/fg/782673\n"
+      "https://c.app.hopsworks.ai:443/p/549016/fs/544838/fg/787790\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "4971a5b3b0854f14ad95992b88f71a16",
+       "model_id": "52bb5493d0dd4abebd6f8b5781a2727c",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Uploading Dataframe: 0.00% |          | Rows 0/3485 | Elapsed Time: 00:00 | Remaining Time: ?"
+       "Uploading Dataframe: 0.00% |          | Rows 0/3486 | Elapsed Time: 00:00 | Remaining Time: ?"
       ]
      },
      "metadata": {},
@@ -621,18 +539,18 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Launching job: tesla_stock_3_offline_fg_materialization\n",
+      "Launching job: tesla_stock_1_offline_fg_materialization\n",
       "Job started successfully, you can follow the progress at \n",
-      "https://c.app.hopsworks.ai/p/549015/jobs/named/tesla_stock_3_offline_fg_materialization/executions\n"
+      "https://c.app.hopsworks.ai/p/549016/jobs/named/tesla_stock_1_offline_fg_materialization/executions\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "(<hsfs.core.job.Job at 0x21d84b9dc10>, None)"
+       "(<hsfs.core.job.Job at 0x304ac0c90>, None)"
       ]
      },
-     "execution_count": 45,
+     "execution_count": 40,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -643,7 +561,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 41,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -652,7 +570,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 29,
+   "execution_count": 42,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -661,7 +579,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 43,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -670,14 +588,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2024-05-04 20:53:43,335 WARNING: DeprecationWarning: Providing event_time as a single-element list is deprecated and will be dropped in future versions. Provide the feature_name string instead.\n",
+      "2024-05-06 11:35:39,174 WARNING: DeprecationWarning: Providing event_time as a single-element list is deprecated and will be dropped in future versions. Provide the feature_name string instead.\n",
       "\n"
      ]
     }
@@ -686,7 +604,7 @@
     "news_sentiment_fg = fs.get_or_create_feature_group(\n",
     "    name='news_sentiment_updated',\n",
     "    description='News sentiment from Polygon',\n",
-    "    version=2,\n",
+    "    version=1,\n",
     "    primary_key=['ticker'],\n",
     "    event_time=['date'],\n",
     "    online_enabled=False,\n",
@@ -695,7 +613,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 45,
    "metadata": {},
    "outputs": [
     {
@@ -703,18 +621,18 @@
      "output_type": "stream",
      "text": [
       "Feature Group created successfully, explore it at \n",
-      "https://c.app.hopsworks.ai:443/p/549015/fs/544840/fg/780662\n"
+      "https://c.app.hopsworks.ai:443/p/549016/fs/544838/fg/785773\n"
      ]
     },
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "868940acc1d74ad987a98daee01a2b75",
+       "model_id": "150c7a2bb8aa49b3a9e2445b1374955e",
        "version_major": 2,
        "version_minor": 0
       },
       "text/plain": [
-       "Uploading Dataframe: 0.00% |          | Rows 0/720 | Elapsed Time: 00:00 | Remaining Time: ?"
+       "Uploading Dataframe: 0.00% |          | Rows 0/66 | Elapsed Time: 00:00 | Remaining Time: ?"
       ]
      },
      "metadata": {},
@@ -724,18 +642,18 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Launching job: news_sentiment_updated_2_offline_fg_materialization\n",
+      "Launching job: news_sentiment_updated_1_offline_fg_materialization\n",
       "Job started successfully, you can follow the progress at \n",
-      "https://c.app.hopsworks.ai/p/549015/jobs/named/news_sentiment_updated_2_offline_fg_materialization/executions\n"
+      "https://c.app.hopsworks.ai/p/549016/jobs/named/news_sentiment_updated_1_offline_fg_materialization/executions\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "(<hsfs.core.job.Job at 0x21d85223610>, None)"
+       "(<hsfs.core.job.Job at 0x17bc96990>, None)"
       ]
      },
-     "execution_count": 50,
+     "execution_count": 45,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -761,7 +679,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.11.4"
   },
   "orig_nbformat": 4
  },

feature_pipeline.py

@@ -96,7 +96,7 @@ tsla_df['date'] = pd.to_datetime(tsla_df['date'])
 tesla_fg = fs.get_or_create_feature_group(
     name="tesla_stock",
     description="Tesla stock dataset from alpha vantage",
-    version=3,
+    version=2,
     primary_key=["ticker"],
     event_time=['date'],
     online_enabled=False,

feature_view_freddie.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -23,73 +23,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 17,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "         date  1. open  2. high    3. low  4. close    5. volume ticker\n",
-      "0  2024-05-02   182.86   184.60  176.0200    180.01   89148041.0   TSLA\n",
-      "1  2024-05-01   182.00   185.86  179.0100    179.99   92829719.0   TSLA\n",
-      "2  2024-04-30   186.98   190.95  182.8401    183.28  127031787.0   TSLA\n",
-      "3  2024-04-29   188.42   198.87  184.5400    194.05  243869678.0   TSLA\n",
-      "4  2024-04-26   168.85   172.12  166.3700    168.29  109815725.0   TSLA\n",
-      "Connected. Call `.close()` to terminate connection gracefully.\n",
-      "\n",
-      "Logged in to project, explore it here https://c.app.hopsworks.ai:443/p/549015\n",
-      "Connected. Call `.close()` to terminate connection gracefully.\n",
-      "Index(['date', 'open', 'high', 'low', 'close', 'volume', 'ticker'], dtype='object')\n"
-     ]
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "baf52b6f47c74767b5aecb1df6f17c0c",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Uploading Dataframe: 0.00% |          | Rows 0/3485 | Elapsed Time: 00:00 | Remaining Time: ?"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Launching job: tesla_stock_3_offline_fg_materialization\n",
-      "Job started successfully, you can follow the progress at \n",
-      "https://c.app.hopsworks.ai/p/549015/jobs/named/tesla_stock_3_offline_fg_materialization/executions\n"
-     ]
-    },
-    {
-     "data": {
-      "application/vnd.jupyter.widget-view+json": {
-       "model_id": "3deb8c10be3a44a2b91c63ffe8762725",
-       "version_major": 2,
-       "version_minor": 0
-      },
-      "text/plain": [
-       "Uploading Dataframe: 0.00% |          | Rows 0/720 | Elapsed Time: 00:00 | Remaining Time: ?"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Launching job: news_sentiment_updated_2_offline_fg_materialization\n",
-      "Job started successfully, you can follow the progress at \n",
-      "https://c.app.hopsworks.ai/p/549015/jobs/named/news_sentiment_updated_2_offline_fg_materialization/executions\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from feature_pipeline import tesla_fg\n",
     "from feature_pipeline import news_sentiment_fg"
@@ -97,7 +33,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -106,7 +42,7 @@
        "True"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -120,7 +56,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 19,
    "metadata": {},
    "outputs": [
     {
@@ -130,7 +66,7 @@
       "Connection closed.\n",
       "Connected. Call `.close()` to terminate connection gracefully.\n",
       "\n",
-      "Logged in to project, explore it here https://c.app.hopsworks.ai:443/p/549015\n",
+      "Logged in to project, explore it here https://c.app.hopsworks.ai:443/p/549016\n",
       "Connected. Call `.close()` to terminate connection gracefully.\n"
      ]
     }
@@ -143,23 +79,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
     "def create_stocks_feature_view(fs, version):\n",
     "\n",
     "    # Loading in the feature groups\n",
-    "    tesla_fg = fs.get_feature_group('tesla_stock', version=3)\n",
-    "    news_sentiment_fg = fs.get_feature_group('news_sentiment_updated', version=2)\n",
+    "    tesla_fg = fs.get_feature_group('tesla_stock', version=1)\n",
+    "    news_sentiment_fg = fs.get_feature_group('news_sentiment_updated', version=1)\n",
     "\n",
     "    # Define the query\n",
     "    ds_query = tesla_fg.select(['date', 'open', 'ticker'])\\\n",
-    "        .join(news_sentiment_fg.select_except(['ticker', 'time', 'amp_url', 'image_url']))\n",
+    "        .join(news_sentiment_fg.select(['date', 'sentiment']))\n",
     "\n",
     "    # Create the feature view\n",
     "    feature_view = fs.create_feature_view(\n",
-    "        name='tsla_stocks_fv',\n",
+    "        name='tesla_stocks_fv',\n",
     "        query=ds_query,\n",
     "        labels=['ticker']\n",
     "    )\n",
@@ -169,52 +105,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
-     "ename": "RestAPIError",
-     "evalue": "Metadata operation error: (url: https://c.app.hopsworks.ai/hopsworks-api/api/project/549015/featurestores/544840/featureview). Server response: \nHTTP code: 404, HTTP reason: Not Found, body: b'{\"errorCode\":270046,\"usrMsg\":\"HOPSFS Connector: fklitte_Training_Datasets\",\"errorMsg\":\"HopsFs Connector not found\"}', error code: 270046, error msg: HopsFs Connector not found, user msg: HOPSFS Connector: fklitte_Training_Datasets",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mRestAPIError\u001b[0m                              Traceback (most recent call last)",
-      "Cell \u001b[1;32mIn[19], line 2\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m----> 2\u001b[0m     feature_view \u001b[38;5;241m=\u001b[39m \u001b[43mfs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_feature_view\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtsla_stocks_fv\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mversion\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m      3\u001b[0m     tesla_fg \u001b[38;5;241m=\u001b[39m fs\u001b[38;5;241m.\u001b[39mget_feature_group(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtesla_stock\u001b[39m\u001b[38;5;124m'\u001b[39m, version\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m)\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\usage.py:212\u001b[0m, in \u001b[0;36mmethod_logger.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    211\u001b[0m     exception \u001b[38;5;241m=\u001b[39m e\n\u001b[1;32m--> 212\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m e\n\u001b[0;32m    213\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\usage.py:208\u001b[0m, in \u001b[0;36mmethod_logger.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    206\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m    207\u001b[0m     \u001b[38;5;66;03m# Call the original method\u001b[39;00m\n\u001b[1;32m--> 208\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    209\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m result\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\feature_store.py:1661\u001b[0m, in \u001b[0;36mFeatureStore.get_feature_view\u001b[1;34m(self, name, version)\u001b[0m\n\u001b[0;32m   1660\u001b[0m     version \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mDEFAULT_VERSION\n\u001b[1;32m-> 1661\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_feature_view_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mversion\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\core\\feature_view_engine.py:127\u001b[0m, in \u001b[0;36mFeatureViewEngine.get\u001b[1;34m(self, name, version)\u001b[0m\n\u001b[0;32m    126\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m version:\n\u001b[1;32m--> 127\u001b[0m     fv \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_feature_view_api\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_by_name_version\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mversion\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    128\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mattach_transformation_function(fv)\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\core\\feature_view_api.py:113\u001b[0m, in \u001b[0;36mFeatureViewApi.get_by_name_version\u001b[1;34m(self, name, version)\u001b[0m\n\u001b[0;32m    112\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m--> 113\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m e\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\core\\feature_view_api.py:101\u001b[0m, in \u001b[0;36mFeatureViewApi.get_by_name_version\u001b[1;34m(self, name, version)\u001b[0m\n\u001b[0;32m     99\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m    100\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m feature_view\u001b[38;5;241m.\u001b[39mFeatureView\u001b[38;5;241m.\u001b[39mfrom_response_json(\n\u001b[1;32m--> 101\u001b[0m         \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_client\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    102\u001b[0m \u001b[43m            \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_GET\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mexpand\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mquery\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfeatures\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m}\u001b[49m\n\u001b[0;32m    103\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    104\u001b[0m     )\n\u001b[0;32m    105\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m RestAPIError \u001b[38;5;28;01mas\u001b[39;00m e:\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\decorators.py:35\u001b[0m, in \u001b[0;36mconnected.<locals>.if_connected\u001b[1;34m(inst, *args, **kwargs)\u001b[0m\n\u001b[0;32m     34\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m NoHopsworksConnectionError\n\u001b[1;32m---> 35\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[43minst\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\client\\base.py:176\u001b[0m, in \u001b[0;36mClient._send_request\u001b[1;34m(self, method, path_params, query_params, headers, data, stream, files)\u001b[0m\n\u001b[0;32m    175\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m response\u001b[38;5;241m.\u001b[39mstatus_code \u001b[38;5;241m/\u001b[39m\u001b[38;5;241m/\u001b[39m \u001b[38;5;241m100\u001b[39m \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m2\u001b[39m:\n\u001b[1;32m--> 176\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m exceptions\u001b[38;5;241m.\u001b[39mRestAPIError(url, response)\n\u001b[0;32m    178\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m stream:\n",
-      "\u001b[1;31mRestAPIError\u001b[0m: Metadata operation error: (url: https://c.app.hopsworks.ai/hopsworks-api/api/project/549015/featurestores/544840/featureview/tsla_stocks_fv/version/1). Server response: \nHTTP code: 404, HTTP reason: Not Found, body: b'{\"errorCode\":270181,\"usrMsg\":\"There exists no feature view with the name tsla_stocks_fv and version 1.\",\"errorMsg\":\"Feature view wasn\\'t found.\"}', error code: 270181, error msg: Feature view wasn't found., user msg: There exists no feature view with the name tsla_stocks_fv and version 1.",
-      "\nDuring handling of the above exception, another exception occurred:\n",
-      "\u001b[1;31mRestAPIError\u001b[0m                              Traceback (most recent call last)",
-      "Cell \u001b[1;32mIn[19], line 5\u001b[0m\n\u001b[0;32m      3\u001b[0m     tesla_fg \u001b[38;5;241m=\u001b[39m fs\u001b[38;5;241m.\u001b[39mget_feature_group(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtesla_stock\u001b[39m\u001b[38;5;124m'\u001b[39m, version\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m)\n\u001b[0;32m      4\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[1;32m----> 5\u001b[0m     feature_view, tesla_fg \u001b[38;5;241m=\u001b[39m \u001b[43mcreate_stocks_feature_view\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n",
-      "Cell \u001b[1;32mIn[18], line 12\u001b[0m, in \u001b[0;36mcreate_stocks_feature_view\u001b[1;34m(fs, version)\u001b[0m\n\u001b[0;32m      8\u001b[0m ds_query \u001b[38;5;241m=\u001b[39m tesla_fg\u001b[38;5;241m.\u001b[39mselect([\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdate\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mopen\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mticker\u001b[39m\u001b[38;5;124m'\u001b[39m])\\\n\u001b[0;32m      9\u001b[0m     \u001b[38;5;241m.\u001b[39mjoin(news_sentiment_fg\u001b[38;5;241m.\u001b[39mselect_except([\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mticker\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtime\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mamp_url\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mimage_url\u001b[39m\u001b[38;5;124m'\u001b[39m]))\n\u001b[0;32m     11\u001b[0m \u001b[38;5;66;03m# Create the feature view\u001b[39;00m\n\u001b[1;32m---> 12\u001b[0m feature_view \u001b[38;5;241m=\u001b[39m \u001b[43mfs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate_feature_view\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m     13\u001b[0m \u001b[43m    \u001b[49m\u001b[43mname\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mtsla_stocks_fv\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[0;32m     14\u001b[0m \u001b[43m    \u001b[49m\u001b[43mquery\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mds_query\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m     15\u001b[0m \u001b[43m    \u001b[49m\u001b[43mlabels\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mticker\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m]\u001b[49m\n\u001b[0;32m     16\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     18\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m feature_view, tesla_fg\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\usage.py:212\u001b[0m, in \u001b[0;36mmethod_logger.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    210\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[0;32m    211\u001b[0m     exception \u001b[38;5;241m=\u001b[39m e\n\u001b[1;32m--> 212\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m e\n\u001b[0;32m    213\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[0;32m    214\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\usage.py:208\u001b[0m, in \u001b[0;36mmethod_logger.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    205\u001b[0m exception \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m    206\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m    207\u001b[0m     \u001b[38;5;66;03m# Call the original method\u001b[39;00m\n\u001b[1;32m--> 208\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    209\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m result\n\u001b[0;32m    210\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\feature_store.py:1538\u001b[0m, in \u001b[0;36mFeatureStore.create_feature_view\u001b[1;34m(self, name, query, version, description, labels, inference_helper_columns, training_helper_columns, transformation_functions)\u001b[0m\n\u001b[0;32m   1436\u001b[0m \u001b[38;5;250m\u001b[39m\u001b[38;5;124;03m\"\"\"Create a feature view metadata object and saved it to hopsworks.\u001b[39;00m\n\u001b[0;32m   1437\u001b[0m \n\u001b[0;32m   1438\u001b[0m \u001b[38;5;124;03m!!! example\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1524\u001b[0m \u001b[38;5;124;03m    `FeatureView`: The feature view metadata object.\u001b[39;00m\n\u001b[0;32m   1525\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[0;32m   1526\u001b[0m feat_view \u001b[38;5;241m=\u001b[39m feature_view\u001b[38;5;241m.\u001b[39mFeatureView(\n\u001b[0;32m   1527\u001b[0m     name\u001b[38;5;241m=\u001b[39mname,\n\u001b[0;32m   1528\u001b[0m     query\u001b[38;5;241m=\u001b[39mquery,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m   1536\u001b[0m     transformation_functions\u001b[38;5;241m=\u001b[39mtransformation_functions,\n\u001b[0;32m   1537\u001b[0m )\n\u001b[1;32m-> 1538\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_feature_view_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msave\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfeat_view\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\core\\feature_view_engine.py:113\u001b[0m, in \u001b[0;36mFeatureViewEngine.save\u001b[1;34m(self, feature_view_obj)\u001b[0m\n\u001b[0;32m    104\u001b[0m         feature_view_obj\u001b[38;5;241m.\u001b[39m_features\u001b[38;5;241m.\u001b[39mappend(\n\u001b[0;32m    105\u001b[0m             training_dataset_feature\u001b[38;5;241m.\u001b[39mTrainingDatasetFeature(\n\u001b[0;32m    106\u001b[0m                 name\u001b[38;5;241m=\u001b[39mfeature\u001b[38;5;241m.\u001b[39mname,\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m    109\u001b[0m             )\n\u001b[0;32m    110\u001b[0m         )\n\u001b[0;32m    112\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transformation_function_engine\u001b[38;5;241m.\u001b[39mattach_transformation_fn(feature_view_obj)\n\u001b[1;32m--> 113\u001b[0m updated_fv \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_feature_view_api\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpost\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfeature_view_obj\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    114\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mattach_transformation_function(updated_fv)\n\u001b[0;32m    115\u001b[0m \u001b[38;5;28mprint\u001b[39m(\n\u001b[0;32m    116\u001b[0m     \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFeature view created successfully, explore it at \u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m    117\u001b[0m     \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_feature_view_url(updated_fv)\n\u001b[0;32m    118\u001b[0m )\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\core\\feature_view_api.py:60\u001b[0m, in \u001b[0;36mFeatureViewApi.post\u001b[1;34m(self, feature_view_obj)\u001b[0m\n\u001b[0;32m     57\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mpost\u001b[39m(\u001b[38;5;28mself\u001b[39m, feature_view_obj):\n\u001b[0;32m     58\u001b[0m     headers \u001b[38;5;241m=\u001b[39m {\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcontent-type\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mapplication/json\u001b[39m\u001b[38;5;124m\"\u001b[39m}\n\u001b[0;32m     59\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m feature_view_obj\u001b[38;5;241m.\u001b[39mupdate_from_response_json(\n\u001b[1;32m---> 60\u001b[0m         \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_client\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m     61\u001b[0m \u001b[43m            \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_POST\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m     62\u001b[0m \u001b[43m            \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_base_path\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m     63\u001b[0m \u001b[43m            \u001b[49m\u001b[43mheaders\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mheaders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m     64\u001b[0m \u001b[43m            \u001b[49m\u001b[43mdata\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfeature_view_obj\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjson\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m     65\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m     66\u001b[0m     )\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\decorators.py:35\u001b[0m, in \u001b[0;36mconnected.<locals>.if_connected\u001b[1;34m(inst, *args, **kwargs)\u001b[0m\n\u001b[0;32m     33\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m inst\u001b[38;5;241m.\u001b[39m_connected:\n\u001b[0;32m     34\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m NoHopsworksConnectionError\n\u001b[1;32m---> 35\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[43minst\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\client\\base.py:176\u001b[0m, in \u001b[0;36mClient._send_request\u001b[1;34m(self, method, path_params, query_params, headers, data, stream, files)\u001b[0m\n\u001b[0;32m    171\u001b[0m     response \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_retry_token_expired(\n\u001b[0;32m    172\u001b[0m         request, stream, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mTOKEN_EXPIRED_RETRY_INTERVAL, \u001b[38;5;241m1\u001b[39m\n\u001b[0;32m    173\u001b[0m     )\n\u001b[0;32m    175\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m response\u001b[38;5;241m.\u001b[39mstatus_code \u001b[38;5;241m/\u001b[39m\u001b[38;5;241m/\u001b[39m \u001b[38;5;241m100\u001b[39m \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m2\u001b[39m:\n\u001b[1;32m--> 176\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m exceptions\u001b[38;5;241m.\u001b[39mRestAPIError(url, response)\n\u001b[0;32m    178\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m stream:\n\u001b[0;32m    179\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m response\n",
-      "\u001b[1;31mRestAPIError\u001b[0m: Metadata operation error: (url: https://c.app.hopsworks.ai/hopsworks-api/api/project/549015/featurestores/544840/featureview). Server response: \nHTTP code: 404, HTTP reason: Not Found, body: b'{\"errorCode\":270046,\"usrMsg\":\"HOPSFS Connector: fklitte_Training_Datasets\",\"errorMsg\":\"HopsFs Connector not found\"}', error code: 270046, error msg: HopsFs Connector not found, user msg: HOPSFS Connector: fklitte_Training_Datasets"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Feature view created successfully, explore it at \n",
+      "https://c.app.hopsworks.ai:443/p/549016/fs/544838/fv/tesla_stocks_fv/version/1\n"
      ]
     }
    ],
    "source": [
     "try:\n",
-    "    feature_view = fs.get_feature_view(\"tsla_stocks_fv\", version=1)\n",
-    "    tesla_fg = fs.get_feature_group('tesla_stock', version=3)\n",
+    "    feature_view = fs.get_feature_view(\"tesla_stocks_fv\", version=1)\n",
+    "    tesla_fg = fs.get_feature_group('tesla_stock', version=1)\n",
     "except:\n",
     "    feature_view, tesla_fg = create_stocks_feature_view(fs, 1)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -236,34 +149,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "ename": "AttributeError",
-     "evalue": "'FeatureStore' object has no attribute 'create_tesla_feature_view'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[1;31mRestAPIError\u001b[0m                              Traceback (most recent call last)",
-      "Cell \u001b[1;32mIn[15], line 2\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m----> 2\u001b[0m     feature_view \u001b[38;5;241m=\u001b[39m \u001b[43mfs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_feature_view\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtsla_stocks_fv\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mversion\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[0;32m      3\u001b[0m     tesla_fg \u001b[38;5;241m=\u001b[39m fs\u001b[38;5;241m.\u001b[39mget_feature_group(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtesla_stock\u001b[39m\u001b[38;5;124m'\u001b[39m, version\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m)\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\usage.py:212\u001b[0m, in \u001b[0;36mmethod_logger.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    211\u001b[0m     exception \u001b[38;5;241m=\u001b[39m e\n\u001b[1;32m--> 212\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m e\n\u001b[0;32m    213\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\usage.py:208\u001b[0m, in \u001b[0;36mmethod_logger.<locals>.wrapper\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m    206\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m    207\u001b[0m     \u001b[38;5;66;03m# Call the original method\u001b[39;00m\n\u001b[1;32m--> 208\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    209\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m result\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\feature_store.py:1661\u001b[0m, in \u001b[0;36mFeatureStore.get_feature_view\u001b[1;34m(self, name, version)\u001b[0m\n\u001b[0;32m   1660\u001b[0m     version \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mDEFAULT_VERSION\n\u001b[1;32m-> 1661\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_feature_view_engine\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mversion\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\core\\feature_view_engine.py:127\u001b[0m, in \u001b[0;36mFeatureViewEngine.get\u001b[1;34m(self, name, version)\u001b[0m\n\u001b[0;32m    126\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m version:\n\u001b[1;32m--> 127\u001b[0m     fv \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_feature_view_api\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_by_name_version\u001b[49m\u001b[43m(\u001b[49m\u001b[43mname\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mversion\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    128\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mattach_transformation_function(fv)\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\core\\feature_view_api.py:113\u001b[0m, in \u001b[0;36mFeatureViewApi.get_by_name_version\u001b[1;34m(self, name, version)\u001b[0m\n\u001b[0;32m    112\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m--> 113\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m e\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\core\\feature_view_api.py:101\u001b[0m, in \u001b[0;36mFeatureViewApi.get_by_name_version\u001b[1;34m(self, name, version)\u001b[0m\n\u001b[0;32m     99\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m    100\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m feature_view\u001b[38;5;241m.\u001b[39mFeatureView\u001b[38;5;241m.\u001b[39mfrom_response_json(\n\u001b[1;32m--> 101\u001b[0m         \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_client\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_send_request\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m    102\u001b[0m \u001b[43m            \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_GET\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mexpand\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mquery\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfeatures\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m}\u001b[49m\n\u001b[0;32m    103\u001b[0m \u001b[43m        \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    104\u001b[0m     )\n\u001b[0;32m    105\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m RestAPIError \u001b[38;5;28;01mas\u001b[39;00m e:\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\decorators.py:35\u001b[0m, in \u001b[0;36mconnected.<locals>.if_connected\u001b[1;34m(inst, *args, **kwargs)\u001b[0m\n\u001b[0;32m     34\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m NoHopsworksConnectionError\n\u001b[1;32m---> 35\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfn\u001b[49m\u001b[43m(\u001b[49m\u001b[43minst\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[1;32mc:\\Users\\frede\\OneDrive\\Dokumenter\\Master\\MLops\\MLops_mod-2\\.conda\\Lib\\site-packages\\hsfs\\client\\base.py:176\u001b[0m, in \u001b[0;36mClient._send_request\u001b[1;34m(self, method, path_params, query_params, headers, data, stream, files)\u001b[0m\n\u001b[0;32m    175\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m response\u001b[38;5;241m.\u001b[39mstatus_code \u001b[38;5;241m/\u001b[39m\u001b[38;5;241m/\u001b[39m \u001b[38;5;241m100\u001b[39m \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m2\u001b[39m:\n\u001b[1;32m--> 176\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m exceptions\u001b[38;5;241m.\u001b[39mRestAPIError(url, response)\n\u001b[0;32m    178\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m stream:\n",
-      "\u001b[1;31mRestAPIError\u001b[0m: Metadata operation error: (url: https://c.app.hopsworks.ai/hopsworks-api/api/project/549015/featurestores/544840/featureview/tsla_stocks_fv/version/1). Server response: \nHTTP code: 404, HTTP reason: Not Found, body: b'{\"errorCode\":270181,\"usrMsg\":\"There exists no feature view with the name tsla_stocks_fv and version 1.\",\"errorMsg\":\"Feature view wasn\\'t found.\"}', error code: 270181, error msg: Feature view wasn't found., user msg: There exists no feature view with the name tsla_stocks_fv and version 1.",
-      "\nDuring handling of the above exception, another exception occurred:\n",
-      "\u001b[1;31mAttributeError\u001b[0m                            Traceback (most recent call last)",
-      "Cell \u001b[1;32mIn[15], line 5\u001b[0m\n\u001b[0;32m      3\u001b[0m     tesla_fg \u001b[38;5;241m=\u001b[39m fs\u001b[38;5;241m.\u001b[39mget_feature_group(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtesla_stock\u001b[39m\u001b[38;5;124m'\u001b[39m, version\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m3\u001b[39m)\n\u001b[0;32m      4\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[1;32m----> 5\u001b[0m     feature_view, tesla_fg \u001b[38;5;241m=\u001b[39m \u001b[43mcreate_stocks_feature_view\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n",
-      "Cell \u001b[1;32mIn[14], line 10\u001b[0m, in \u001b[0;36mcreate_stocks_feature_view\u001b[1;34m(fs, version)\u001b[0m\n\u001b[0;32m      5\u001b[0m news_sentiment_fg \u001b[38;5;241m=\u001b[39m fs\u001b[38;5;241m.\u001b[39mget_feature_group(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mnews_sentiment_updated\u001b[39m\u001b[38;5;124m'\u001b[39m, version \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m2\u001b[39m)\n\u001b[0;32m      7\u001b[0m ds_query \u001b[38;5;241m=\u001b[39m tesla_fg\u001b[38;5;241m.\u001b[39mselect([\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mdate\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mopen\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mticker\u001b[39m\u001b[38;5;124m'\u001b[39m])\\\n\u001b[0;32m      8\u001b[0m     \u001b[38;5;241m.\u001b[39mjoin(news_sentiment_fg\u001b[38;5;241m.\u001b[39mselect_except([\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mticker\u001b[39m\u001b[38;5;124m'\u001b[39m,\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtime\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mamp_url\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mimage_url\u001b[39m\u001b[38;5;124m'\u001b[39m]))\n\u001b[1;32m---> 10\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m (\u001b[43mfs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate_tesla_feature_view\u001b[49m(\n\u001b[0;32m     11\u001b[0m     name \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtsla_stocks_fv\u001b[39m\u001b[38;5;124m'\u001b[39m,\n\u001b[0;32m     12\u001b[0m     query \u001b[38;5;241m=\u001b[39m ds_query,\n\u001b[0;32m     13\u001b[0m     labels\u001b[38;5;241m=\u001b[39m[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mticker\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[0;32m     14\u001b[0m ), tesla_fg)\n",
-      "\u001b[1;31mAttributeError\u001b[0m: 'FeatureStore' object has no attribute 'create_tesla_feature_view'"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "#try:\n",
     "#    feature_view = fs.get_feature_view(\"tsla_stocks_fv\", version=1)\n",
@@ -289,7 +177,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.9"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,

historical_news.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 37,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -17,7 +17,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 38,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -26,7 +26,7 @@
        "True"
       ]
      },
-     "execution_count": 38,
+     "execution_count": 2,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -37,30 +37,30 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Fetched 50 articles from 2022-05-03 to 2022-06-22\n",
-      "Fetched 50 articles from 2022-06-23 to 2022-08-12\n",
-      "Fetched 50 articles from 2022-08-13 to 2022-10-02\n",
-      "Fetched 50 articles from 2022-10-03 to 2022-11-22\n",
-      "Fetched 50 articles from 2022-11-23 to 2023-01-12\n",
+      "Fetched 50 articles from 2022-05-06 to 2022-06-25\n",
+      "Fetched 50 articles from 2022-06-26 to 2022-08-15\n",
+      "Fetched 50 articles from 2022-08-16 to 2022-10-05\n",
+      "Fetched 50 articles from 2022-10-06 to 2022-11-25\n",
+      "Fetched 50 articles from 2022-11-26 to 2023-01-15\n",
       "Rate limit reached. Waiting to retry...\n",
-      "Fetched 50 articles from 2023-01-13 to 2023-03-04\n",
-      "Fetched 50 articles from 2023-03-05 to 2023-04-24\n",
-      "Fetched 50 articles from 2023-04-25 to 2023-06-14\n",
-      "Fetched 50 articles from 2023-06-15 to 2023-08-04\n",
-      "Fetched 50 articles from 2023-08-05 to 2023-09-24\n",
+      "Fetched 50 articles from 2023-01-16 to 2023-03-07\n",
+      "Fetched 50 articles from 2023-03-08 to 2023-04-27\n",
+      "Fetched 50 articles from 2023-04-28 to 2023-06-17\n",
+      "Fetched 50 articles from 2023-06-18 to 2023-08-07\n",
+      "Fetched 50 articles from 2023-08-08 to 2023-09-27\n",
       "Rate limit reached. Waiting to retry...\n",
-      "Fetched 50 articles from 2023-09-25 to 2023-11-14\n",
-      "Fetched 50 articles from 2023-11-15 to 2024-01-04\n",
-      "Fetched 50 articles from 2024-01-05 to 2024-02-24\n",
-      "Fetched 50 articles from 2024-02-25 to 2024-04-15\n",
-      "Fetched 50 articles from 2024-04-16 to 2024-05-02\n",
+      "Fetched 50 articles from 2023-09-28 to 2023-11-17\n",
+      "Fetched 50 articles from 2023-11-18 to 2024-01-07\n",
+      "Fetched 50 articles from 2024-01-08 to 2024-02-27\n",
+      "Fetched 50 articles from 2024-02-28 to 2024-04-18\n",
+      "Fetched 50 articles from 2024-04-19 to 2024-05-05\n",
       "Total articles fetched: 750\n"
      ]
     }
@@ -130,7 +130,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -140,7 +140,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -148,26 +148,15 @@
      "output_type": "stream",
      "text": [
       "<class 'pandas.core.frame.DataFrame'>\n",
-      "DatetimeIndex: 720 entries, 1970-01-01 00:00:00 to 1970-01-01 00:00:00.000000719\n",
-      "Data columns (total 14 columns):\n",
-      " #   Column       Non-Null Count  Dtype  \n",
-      "---  ------       --------------  -----  \n",
-      " 0   date         720 non-null    object \n",
-      " 1   id           720 non-null    object \n",
-      " 2   publisher    720 non-null    object \n",
-      " 3   title        720 non-null    object \n",
-      " 4   author       720 non-null    object \n",
-      " 5   article_url  720 non-null    object \n",
-      " 6   tickers      720 non-null    object \n",
-      " 7   amp_url      720 non-null    object \n",
-      " 8   image_url    720 non-null    object \n",
-      " 9   description  720 non-null    object \n",
-      " 10  keywords     720 non-null    object \n",
-      " 11  ticker       720 non-null    object \n",
-      " 12  sentiment    720 non-null    float64\n",
-      " 13  time         720 non-null    object \n",
-      "dtypes: float64(1), object(13)\n",
-      "memory usage: 84.4+ KB\n"
+      "RangeIndex: 66 entries, 0 to 65\n",
+      "Data columns (total 3 columns):\n",
+      " #   Column     Non-Null Count  Dtype  \n",
+      "---  ------     --------------  -----  \n",
+      " 0   date       66 non-null     object \n",
+      " 1   ticker     66 non-null     object \n",
+      " 2   sentiment  66 non-null     float64\n",
+      "dtypes: float64(1), object(2)\n",
+      "memory usage: 1.7+ KB\n"
      ]
     }
    ],
@@ -177,7 +166,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -202,191 +191,55 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>date</th>\n",
-       "      <th>id</th>\n",
-       "      <th>publisher</th>\n",
-       "      <th>title</th>\n",
-       "      <th>author</th>\n",
-       "      <th>article_url</th>\n",
-       "      <th>tickers</th>\n",
-       "      <th>amp_url</th>\n",
-       "      <th>image_url</th>\n",
-       "      <th>description</th>\n",
-       "      <th>keywords</th>\n",
        "      <th>ticker</th>\n",
        "      <th>sentiment</th>\n",
-       "      <th>time</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000000</th>\n",
-       "      <td>2022-06-22</td>\n",
-       "      <td>nVZWipNVQFFoSi87tF0APXW_uRHl13wat_uR1c0iR6A</td>\n",
-       "      <td>{'name': 'Benzinga', 'homepage_url': 'https://...</td>\n",
-       "      <td>Elon Musk Gives New Update On Tesla Cybertruck...</td>\n",
-       "      <td>Chris Katje</td>\n",
-       "      <td>https://www.benzinga.com/news/22/06/27820587/e...</td>\n",
-       "      <td>[F, TSLA, RIVN]</td>\n",
-       "      <td>https://www.benzinga.com/amp/content/27820587</td>\n",
-       "      <td>https://cdn.benzinga.com/files/images/story/20...</td>\n",
-       "      <td>A recent interview between Tesla Inc (NASDAQ: ...</td>\n",
-       "      <td>[News, Interview]</td>\n",
+       "      <th>0</th>\n",
+       "      <td>2022-06-23</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.040</td>\n",
-       "      <td>22:40:56</td>\n",
+       "      <td>0.091056</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000001</th>\n",
-       "      <td>2022-06-22</td>\n",
-       "      <td>x_9M1zYfZoHn_ptJM3USKxrodDtd4TcTsQSldXlViMw</td>\n",
-       "      <td>{'name': 'MarketWatch', 'homepage_url': 'https...</td>\n",
-       "      <td>Tesla's new factories are 'gigantic money furn...</td>\n",
-       "      <td>MarketWatch</td>\n",
-       "      <td>https://www.marketwatch.com/story/teslas-new-f...</td>\n",
-       "      <td>[TSLA]</td>\n",
-       "      <td>No URL provided</td>\n",
-       "      <td>https://images.mktw.net/im-569600/social</td>\n",
-       "      <td>Tesla Inc.’s two newest car factories have bee...</td>\n",
-       "      <td>No keywords</td>\n",
+       "      <th>1</th>\n",
+       "      <td>2022-06-24</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>21:59:00</td>\n",
+       "      <td>0.059212</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000002</th>\n",
-       "      <td>2022-06-22</td>\n",
-       "      <td>SDepdS_qKyhE6vqbR6Fathnn81fYDapZCk3DKT1Xpv4</td>\n",
-       "      <td>{'name': 'The Motley Fool', 'homepage_url': 'h...</td>\n",
-       "      <td>Why Tesla Shares Jumped Initially, Then Retrea...</td>\n",
-       "      <td>newsfeedback@fool.com (Chris Neiger)</td>\n",
-       "      <td>https://www.fool.com/investing/2022/06/22/why-...</td>\n",
-       "      <td>[TSLA]</td>\n",
-       "      <td>No URL provided</td>\n",
-       "      <td>https://g.foolcdn.com/editorial/images/686400/...</td>\n",
-       "      <td>Tesla's Shanghai plant may temporarily suspend...</td>\n",
-       "      <td>[investing]</td>\n",
+       "      <th>2</th>\n",
+       "      <td>2022-06-25</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>19:33:04</td>\n",
+       "      <td>0.250000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000003</th>\n",
-       "      <td>2022-06-22</td>\n",
-       "      <td>xTSACaU2z-Mzqa23BiUeHTEUuY_jbVTWOYFkN3uszxg</td>\n",
-       "      <td>{'name': 'MarketWatch', 'homepage_url': 'https...</td>\n",
-       "      <td>These are the 10 used-car models whose prices ...</td>\n",
-       "      <td>MarketWatch</td>\n",
-       "      <td>https://www.marketwatch.com/story/these-are-th...</td>\n",
-       "      <td>[LOTZ, TSLA]</td>\n",
-       "      <td>https://www.marketwatch.com/amp/story/these-ar...</td>\n",
-       "      <td>https://images.mktw.net/im-569120/social</td>\n",
-       "      <td>Used-car prices rose on average 17% in May, wi...</td>\n",
-       "      <td>No keywords</td>\n",
+       "      <th>3</th>\n",
+       "      <td>2022-08-11</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.225</td>\n",
-       "      <td>17:32:00</td>\n",
+       "      <td>0.171968</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000004</th>\n",
-       "      <td>2022-06-22</td>\n",
-       "      <td>pksGB2t-5ukDnjkRw_VYr9sfcSOExNmQiHzUq9_rBa0</td>\n",
-       "      <td>{'name': 'Zacks Investment Research', 'homepag...</td>\n",
-       "      <td>Tesla (TSLA) to Cut 10% Salaried Jobs, Raise H...</td>\n",
-       "      <td>Zacks Equity Research</td>\n",
-       "      <td>https://www.zacks.com/stock/news/1942395/tesla...</td>\n",
-       "      <td>[SMP, TSLA, WNC, FOXF]</td>\n",
-       "      <td>https://www.zacks.com/amp/stock/news/1942395/t...</td>\n",
-       "      <td>https://staticx-tuner.zacks.com/images/article...</td>\n",
-       "      <td>Tesla (TSLA) to lay off 10% of its salaried wo...</td>\n",
-       "      <td>No keywords</td>\n",
+       "      <th>4</th>\n",
+       "      <td>2022-08-12</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>15:58:00</td>\n",
+       "      <td>0.035351</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                                     date  \\\n",
-       "1970-01-01 00:00:00.000000000  2022-06-22   \n",
-       "1970-01-01 00:00:00.000000001  2022-06-22   \n",
-       "1970-01-01 00:00:00.000000002  2022-06-22   \n",
-       "1970-01-01 00:00:00.000000003  2022-06-22   \n",
-       "1970-01-01 00:00:00.000000004  2022-06-22   \n",
-       "\n",
-       "                                                                        id  \\\n",
-       "1970-01-01 00:00:00.000000000  nVZWipNVQFFoSi87tF0APXW_uRHl13wat_uR1c0iR6A   \n",
-       "1970-01-01 00:00:00.000000001  x_9M1zYfZoHn_ptJM3USKxrodDtd4TcTsQSldXlViMw   \n",
-       "1970-01-01 00:00:00.000000002  SDepdS_qKyhE6vqbR6Fathnn81fYDapZCk3DKT1Xpv4   \n",
-       "1970-01-01 00:00:00.000000003  xTSACaU2z-Mzqa23BiUeHTEUuY_jbVTWOYFkN3uszxg   \n",
-       "1970-01-01 00:00:00.000000004  pksGB2t-5ukDnjkRw_VYr9sfcSOExNmQiHzUq9_rBa0   \n",
-       "\n",
-       "                                                                       publisher  \\\n",
-       "1970-01-01 00:00:00.000000000  {'name': 'Benzinga', 'homepage_url': 'https://...   \n",
-       "1970-01-01 00:00:00.000000001  {'name': 'MarketWatch', 'homepage_url': 'https...   \n",
-       "1970-01-01 00:00:00.000000002  {'name': 'The Motley Fool', 'homepage_url': 'h...   \n",
-       "1970-01-01 00:00:00.000000003  {'name': 'MarketWatch', 'homepage_url': 'https...   \n",
-       "1970-01-01 00:00:00.000000004  {'name': 'Zacks Investment Research', 'homepag...   \n",
-       "\n",
-       "                                                                           title  \\\n",
-       "1970-01-01 00:00:00.000000000  Elon Musk Gives New Update On Tesla Cybertruck...   \n",
-       "1970-01-01 00:00:00.000000001  Tesla's new factories are 'gigantic money furn...   \n",
-       "1970-01-01 00:00:00.000000002  Why Tesla Shares Jumped Initially, Then Retrea...   \n",
-       "1970-01-01 00:00:00.000000003  These are the 10 used-car models whose prices ...   \n",
-       "1970-01-01 00:00:00.000000004  Tesla (TSLA) to Cut 10% Salaried Jobs, Raise H...   \n",
-       "\n",
-       "                                                             author  \\\n",
-       "1970-01-01 00:00:00.000000000                           Chris Katje   \n",
-       "1970-01-01 00:00:00.000000001                           MarketWatch   \n",
-       "1970-01-01 00:00:00.000000002  newsfeedback@fool.com (Chris Neiger)   \n",
-       "1970-01-01 00:00:00.000000003                           MarketWatch   \n",
-       "1970-01-01 00:00:00.000000004                 Zacks Equity Research   \n",
-       "\n",
-       "                                                                     article_url  \\\n",
-       "1970-01-01 00:00:00.000000000  https://www.benzinga.com/news/22/06/27820587/e...   \n",
-       "1970-01-01 00:00:00.000000001  https://www.marketwatch.com/story/teslas-new-f...   \n",
-       "1970-01-01 00:00:00.000000002  https://www.fool.com/investing/2022/06/22/why-...   \n",
-       "1970-01-01 00:00:00.000000003  https://www.marketwatch.com/story/these-are-th...   \n",
-       "1970-01-01 00:00:00.000000004  https://www.zacks.com/stock/news/1942395/tesla...   \n",
-       "\n",
-       "                                              tickers  \\\n",
-       "1970-01-01 00:00:00.000000000         [F, TSLA, RIVN]   \n",
-       "1970-01-01 00:00:00.000000001                  [TSLA]   \n",
-       "1970-01-01 00:00:00.000000002                  [TSLA]   \n",
-       "1970-01-01 00:00:00.000000003            [LOTZ, TSLA]   \n",
-       "1970-01-01 00:00:00.000000004  [SMP, TSLA, WNC, FOXF]   \n",
-       "\n",
-       "                                                                         amp_url  \\\n",
-       "1970-01-01 00:00:00.000000000      https://www.benzinga.com/amp/content/27820587   \n",
-       "1970-01-01 00:00:00.000000001                                    No URL provided   \n",
-       "1970-01-01 00:00:00.000000002                                    No URL provided   \n",
-       "1970-01-01 00:00:00.000000003  https://www.marketwatch.com/amp/story/these-ar...   \n",
-       "1970-01-01 00:00:00.000000004  https://www.zacks.com/amp/stock/news/1942395/t...   \n",
-       "\n",
-       "                                                                       image_url  \\\n",
-       "1970-01-01 00:00:00.000000000  https://cdn.benzinga.com/files/images/story/20...   \n",
-       "1970-01-01 00:00:00.000000001           https://images.mktw.net/im-569600/social   \n",
-       "1970-01-01 00:00:00.000000002  https://g.foolcdn.com/editorial/images/686400/...   \n",
-       "1970-01-01 00:00:00.000000003           https://images.mktw.net/im-569120/social   \n",
-       "1970-01-01 00:00:00.000000004  https://staticx-tuner.zacks.com/images/article...   \n",
-       "\n",
-       "                                                                     description  \\\n",
-       "1970-01-01 00:00:00.000000000  A recent interview between Tesla Inc (NASDAQ: ...   \n",
-       "1970-01-01 00:00:00.000000001  Tesla Inc.’s two newest car factories have bee...   \n",
-       "1970-01-01 00:00:00.000000002  Tesla's Shanghai plant may temporarily suspend...   \n",
-       "1970-01-01 00:00:00.000000003  Used-car prices rose on average 17% in May, wi...   \n",
-       "1970-01-01 00:00:00.000000004  Tesla (TSLA) to lay off 10% of its salaried wo...   \n",
-       "\n",
-       "                                        keywords ticker  sentiment      time  \n",
-       "1970-01-01 00:00:00.000000000  [News, Interview]   TSLA      0.040  22:40:56  \n",
-       "1970-01-01 00:00:00.000000001        No keywords   TSLA      0.000  21:59:00  \n",
-       "1970-01-01 00:00:00.000000002        [investing]   TSLA      0.000  19:33:04  \n",
-       "1970-01-01 00:00:00.000000003        No keywords   TSLA      0.225  17:32:00  \n",
-       "1970-01-01 00:00:00.000000004        No keywords   TSLA      0.000  15:58:00  "
+       "         date ticker  sentiment\n",
+       "0  2022-06-23   TSLA   0.091056\n",
+       "1  2022-06-24   TSLA   0.059212\n",
+       "2  2022-06-25   TSLA   0.250000\n",
+       "3  2022-08-11   TSLA   0.171968\n",
+       "4  2022-08-12   TSLA   0.035351"
       ]
      },
-     "execution_count": 42,
+     "execution_count": 6,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -397,7 +250,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -406,7 +259,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -415,7 +268,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -424,7 +277,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 46,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -433,7 +286,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -458,204 +311,61 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>date</th>\n",
-       "      <th>id</th>\n",
-       "      <th>publisher</th>\n",
-       "      <th>title</th>\n",
-       "      <th>author</th>\n",
-       "      <th>article_url</th>\n",
-       "      <th>tickers</th>\n",
-       "      <th>amp_url</th>\n",
-       "      <th>image_url</th>\n",
-       "      <th>description</th>\n",
-       "      <th>keywords</th>\n",
        "      <th>ticker</th>\n",
        "      <th>sentiment</th>\n",
-       "      <th>time</th>\n",
        "      <th>exp_mean_7_days</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000719</th>\n",
-       "      <td>2024-04-29</td>\n",
-       "      <td>MeWGIZiKn6J3JCwWAkHNqVv6Cc9HToUK-HmodQSesdM</td>\n",
-       "      <td>{'name': 'The Motley Fool', 'homepage_url': 'h...</td>\n",
-       "      <td>Why Baidu Stock Jumped Today</td>\n",
-       "      <td>newsfeedback@fool.com (James Brumley)</td>\n",
-       "      <td>https://www.fool.com/investing/2024/04/29/why-...</td>\n",
-       "      <td>[BIDU, GOOGL, TSLA, GOOG, IQ]</td>\n",
-       "      <td>No URL provided</td>\n",
-       "      <td>https://g.foolcdn.com/editorial/images/774939/...</td>\n",
-       "      <td>It's getting difficult not to notice how impre...</td>\n",
-       "      <td>[investing]</td>\n",
+       "      <th>65</th>\n",
+       "      <td>2024-05-05</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>21:26:09</td>\n",
-       "      <td>0.250000</td>\n",
+       "      <td>0.036190</td>\n",
+       "      <td>0.036190</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000718</th>\n",
-       "      <td>2024-04-29</td>\n",
-       "      <td>T9MgJwXEmlRjWpkmLvcwnBggkbeXWWoGzFISY65WwBc</td>\n",
-       "      <td>{'name': 'Zacks Investment Research', 'homepag...</td>\n",
-       "      <td>Markets Up on Tesla, Q1 Earnings; Q1 Beats Aft...</td>\n",
-       "      <td>Mark Vickery</td>\n",
-       "      <td>https://www.zacks.com/stock/news/2264549/marke...</td>\n",
-       "      <td>[AMZN, AMD, KO, LLY, SBUX, MCD, NXPI, TSLA, YU...</td>\n",
-       "      <td>https://www.zacks.com/amp/stock/news/2264549/m...</td>\n",
-       "      <td>https://staticx-tuner.zacks.com/images/article...</td>\n",
-       "      <td>It's now the third straight day higher going b...</td>\n",
-       "      <td>No keywords</td>\n",
+       "      <th>64</th>\n",
+       "      <td>2024-05-04</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.111905</td>\n",
-       "      <td>22:10:00</td>\n",
-       "      <td>0.215476</td>\n",
+       "      <td>0.062665</td>\n",
+       "      <td>0.042809</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000717</th>\n",
-       "      <td>2024-04-30</td>\n",
-       "      <td>xaUyg2qUKK7h_EDkKruXR9KdY_drlcXLai14uHvZTsc</td>\n",
-       "      <td>{'name': 'Seeking Alpha', 'homepage_url': 'htt...</td>\n",
-       "      <td>Big Tech Earnings Beats Stymie Q2 2024 Sell-Off</td>\n",
-       "      <td>Christine Short</td>\n",
-       "      <td>https://seekingalpha.com/article/4687390-big-t...</td>\n",
-       "      <td>[AAPL, AMZN, GOOG, GOOGL, HSY, KO, META, MMM, ...</td>\n",
-       "      <td>No URL provided</td>\n",
-       "      <td>https://static.seekingalpha.com/cdn/s3/uploads...</td>\n",
-       "      <td>Markets finally turned positive late last week...</td>\n",
-       "      <td>No keywords</td>\n",
+       "      <th>63</th>\n",
+       "      <td>2024-05-03</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>-0.032955</td>\n",
-       "      <td>04:30:00</td>\n",
-       "      <td>0.153369</td>\n",
+       "      <td>0.027798</td>\n",
+       "      <td>0.039056</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000716</th>\n",
-       "      <td>2024-04-30</td>\n",
-       "      <td>IPVxhBMbT73GJJHLQZYPFb8yQpAxzbEuXrJk0dMSt8U</td>\n",
-       "      <td>{'name': 'Zacks Investment Research', 'homepag...</td>\n",
-       "      <td>Stock Market News for Apr 30, 2024</td>\n",
-       "      <td>Zacks Equity Research</td>\n",
-       "      <td>https://www.zacks.com/stock/news/2264591/stock...</td>\n",
-       "      <td>[AAPL, TSLA, PARA]</td>\n",
-       "      <td>https://www.zacks.com/amp/stock/news/2264591/s...</td>\n",
-       "      <td>https://staticx-tuner.zacks.com/images/article...</td>\n",
-       "      <td>Wall Street closed higher on Monday to start a...</td>\n",
-       "      <td>No keywords</td>\n",
+       "      <th>62</th>\n",
+       "      <td>2024-05-02</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.050000</td>\n",
-       "      <td>07:27:00</td>\n",
-       "      <td>0.127526</td>\n",
+       "      <td>0.001443</td>\n",
+       "      <td>0.029653</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000715</th>\n",
-       "      <td>2024-04-30</td>\n",
-       "      <td>6pQAGkGEZvAd76QYnk6aAhhUCVLrUkdOjgnon-ALmsQ</td>\n",
-       "      <td>{'name': 'Benzinga', 'homepage_url': 'https://...</td>\n",
-       "      <td>'Tesla Has The Endorsement' Of Xi Jinping's Go...</td>\n",
-       "      <td>Benzinga Neuro</td>\n",
-       "      <td>https://www.benzinga.com/analyst-ratings/analy...</td>\n",
-       "      <td>[TSLA]</td>\n",
-       "      <td>https://www.benzinga.com/amp/content/38511044</td>\n",
-       "      <td>https://cdn.benzinga.com/files/images/story/20...</td>\n",
-       "      <td>Tim Higgins, author of “Power Play: Tesla, Elo...</td>\n",
-       "      <td>[News, Analyst Color, Tech, General]</td>\n",
+       "      <th>61</th>\n",
+       "      <td>2024-05-01</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.008333</td>\n",
-       "      <td>07:42:58</td>\n",
-       "      <td>0.097728</td>\n",
+       "      <td>0.162742</td>\n",
+       "      <td>0.062925</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                                     date  \\\n",
-       "1970-01-01 00:00:00.000000719  2024-04-29   \n",
-       "1970-01-01 00:00:00.000000718  2024-04-29   \n",
-       "1970-01-01 00:00:00.000000717  2024-04-30   \n",
-       "1970-01-01 00:00:00.000000716  2024-04-30   \n",
-       "1970-01-01 00:00:00.000000715  2024-04-30   \n",
-       "\n",
-       "                                                                        id  \\\n",
-       "1970-01-01 00:00:00.000000719  MeWGIZiKn6J3JCwWAkHNqVv6Cc9HToUK-HmodQSesdM   \n",
-       "1970-01-01 00:00:00.000000718  T9MgJwXEmlRjWpkmLvcwnBggkbeXWWoGzFISY65WwBc   \n",
-       "1970-01-01 00:00:00.000000717  xaUyg2qUKK7h_EDkKruXR9KdY_drlcXLai14uHvZTsc   \n",
-       "1970-01-01 00:00:00.000000716  IPVxhBMbT73GJJHLQZYPFb8yQpAxzbEuXrJk0dMSt8U   \n",
-       "1970-01-01 00:00:00.000000715  6pQAGkGEZvAd76QYnk6aAhhUCVLrUkdOjgnon-ALmsQ   \n",
-       "\n",
-       "                                                                       publisher  \\\n",
-       "1970-01-01 00:00:00.000000719  {'name': 'The Motley Fool', 'homepage_url': 'h...   \n",
-       "1970-01-01 00:00:00.000000718  {'name': 'Zacks Investment Research', 'homepag...   \n",
-       "1970-01-01 00:00:00.000000717  {'name': 'Seeking Alpha', 'homepage_url': 'htt...   \n",
-       "1970-01-01 00:00:00.000000716  {'name': 'Zacks Investment Research', 'homepag...   \n",
-       "1970-01-01 00:00:00.000000715  {'name': 'Benzinga', 'homepage_url': 'https://...   \n",
-       "\n",
-       "                                                                           title  \\\n",
-       "1970-01-01 00:00:00.000000719                       Why Baidu Stock Jumped Today   \n",
-       "1970-01-01 00:00:00.000000718  Markets Up on Tesla, Q1 Earnings; Q1 Beats Aft...   \n",
-       "1970-01-01 00:00:00.000000717    Big Tech Earnings Beats Stymie Q2 2024 Sell-Off   \n",
-       "1970-01-01 00:00:00.000000716                 Stock Market News for Apr 30, 2024   \n",
-       "1970-01-01 00:00:00.000000715  'Tesla Has The Endorsement' Of Xi Jinping's Go...   \n",
-       "\n",
-       "                                                              author  \\\n",
-       "1970-01-01 00:00:00.000000719  newsfeedback@fool.com (James Brumley)   \n",
-       "1970-01-01 00:00:00.000000718                           Mark Vickery   \n",
-       "1970-01-01 00:00:00.000000717                        Christine Short   \n",
-       "1970-01-01 00:00:00.000000716                  Zacks Equity Research   \n",
-       "1970-01-01 00:00:00.000000715                         Benzinga Neuro   \n",
-       "\n",
-       "                                                                     article_url  \\\n",
-       "1970-01-01 00:00:00.000000719  https://www.fool.com/investing/2024/04/29/why-...   \n",
-       "1970-01-01 00:00:00.000000718  https://www.zacks.com/stock/news/2264549/marke...   \n",
-       "1970-01-01 00:00:00.000000717  https://seekingalpha.com/article/4687390-big-t...   \n",
-       "1970-01-01 00:00:00.000000716  https://www.zacks.com/stock/news/2264591/stock...   \n",
-       "1970-01-01 00:00:00.000000715  https://www.benzinga.com/analyst-ratings/analy...   \n",
-       "\n",
-       "                                                                         tickers  \\\n",
-       "1970-01-01 00:00:00.000000719                      [BIDU, GOOGL, TSLA, GOOG, IQ]   \n",
-       "1970-01-01 00:00:00.000000718  [AMZN, AMD, KO, LLY, SBUX, MCD, NXPI, TSLA, YU...   \n",
-       "1970-01-01 00:00:00.000000717  [AAPL, AMZN, GOOG, GOOGL, HSY, KO, META, MMM, ...   \n",
-       "1970-01-01 00:00:00.000000716                                 [AAPL, TSLA, PARA]   \n",
-       "1970-01-01 00:00:00.000000715                                             [TSLA]   \n",
-       "\n",
-       "                                                                         amp_url  \\\n",
-       "1970-01-01 00:00:00.000000719                                    No URL provided   \n",
-       "1970-01-01 00:00:00.000000718  https://www.zacks.com/amp/stock/news/2264549/m...   \n",
-       "1970-01-01 00:00:00.000000717                                    No URL provided   \n",
-       "1970-01-01 00:00:00.000000716  https://www.zacks.com/amp/stock/news/2264591/s...   \n",
-       "1970-01-01 00:00:00.000000715      https://www.benzinga.com/amp/content/38511044   \n",
-       "\n",
-       "                                                                       image_url  \\\n",
-       "1970-01-01 00:00:00.000000719  https://g.foolcdn.com/editorial/images/774939/...   \n",
-       "1970-01-01 00:00:00.000000718  https://staticx-tuner.zacks.com/images/article...   \n",
-       "1970-01-01 00:00:00.000000717  https://static.seekingalpha.com/cdn/s3/uploads...   \n",
-       "1970-01-01 00:00:00.000000716  https://staticx-tuner.zacks.com/images/article...   \n",
-       "1970-01-01 00:00:00.000000715  https://cdn.benzinga.com/files/images/story/20...   \n",
-       "\n",
-       "                                                                     description  \\\n",
-       "1970-01-01 00:00:00.000000719  It's getting difficult not to notice how impre...   \n",
-       "1970-01-01 00:00:00.000000718  It's now the third straight day higher going b...   \n",
-       "1970-01-01 00:00:00.000000717  Markets finally turned positive late last week...   \n",
-       "1970-01-01 00:00:00.000000716  Wall Street closed higher on Monday to start a...   \n",
-       "1970-01-01 00:00:00.000000715  Tim Higgins, author of “Power Play: Tesla, Elo...   \n",
-       "\n",
-       "                                                           keywords ticker  \\\n",
-       "1970-01-01 00:00:00.000000719                           [investing]   TSLA   \n",
-       "1970-01-01 00:00:00.000000718                           No keywords   TSLA   \n",
-       "1970-01-01 00:00:00.000000717                           No keywords   TSLA   \n",
-       "1970-01-01 00:00:00.000000716                           No keywords   TSLA   \n",
-       "1970-01-01 00:00:00.000000715  [News, Analyst Color, Tech, General]   TSLA   \n",
-       "\n",
-       "                               sentiment      time  exp_mean_7_days  \n",
-       "1970-01-01 00:00:00.000000719   0.250000  21:26:09         0.250000  \n",
-       "1970-01-01 00:00:00.000000718   0.111905  22:10:00         0.215476  \n",
-       "1970-01-01 00:00:00.000000717  -0.032955  04:30:00         0.153369  \n",
-       "1970-01-01 00:00:00.000000716   0.050000  07:27:00         0.127526  \n",
-       "1970-01-01 00:00:00.000000715   0.008333  07:42:58         0.097728  "
+       "          date ticker  sentiment  exp_mean_7_days\n",
+       "65  2024-05-05   TSLA   0.036190         0.036190\n",
+       "64  2024-05-04   TSLA   0.062665         0.042809\n",
+       "63  2024-05-03   TSLA   0.027798         0.039056\n",
+       "62  2024-05-02   TSLA   0.001443         0.029653\n",
+       "61  2024-05-01   TSLA   0.162742         0.062925"
       ]
      },
-     "execution_count": 47,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -666,7 +376,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 48,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -691,204 +401,61 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>date</th>\n",
-       "      <th>id</th>\n",
-       "      <th>publisher</th>\n",
-       "      <th>title</th>\n",
-       "      <th>author</th>\n",
-       "      <th>article_url</th>\n",
-       "      <th>tickers</th>\n",
-       "      <th>amp_url</th>\n",
-       "      <th>image_url</th>\n",
-       "      <th>description</th>\n",
-       "      <th>keywords</th>\n",
        "      <th>ticker</th>\n",
        "      <th>sentiment</th>\n",
-       "      <th>time</th>\n",
        "      <th>exp_mean_7_days</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000004</th>\n",
-       "      <td>2022-06-22</td>\n",
-       "      <td>pksGB2t-5ukDnjkRw_VYr9sfcSOExNmQiHzUq9_rBa0</td>\n",
-       "      <td>{'name': 'Zacks Investment Research', 'homepag...</td>\n",
-       "      <td>Tesla (TSLA) to Cut 10% Salaried Jobs, Raise H...</td>\n",
-       "      <td>Zacks Equity Research</td>\n",
-       "      <td>https://www.zacks.com/stock/news/1942395/tesla...</td>\n",
-       "      <td>[SMP, TSLA, WNC, FOXF]</td>\n",
-       "      <td>https://www.zacks.com/amp/stock/news/1942395/t...</td>\n",
-       "      <td>https://staticx-tuner.zacks.com/images/article...</td>\n",
-       "      <td>Tesla (TSLA) to lay off 10% of its salaried wo...</td>\n",
-       "      <td>No keywords</td>\n",
+       "      <th>4</th>\n",
+       "      <td>2022-08-12</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>15:58:00</td>\n",
-       "      <td>0.195010</td>\n",
+       "      <td>0.035351</td>\n",
+       "      <td>0.053681</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000003</th>\n",
-       "      <td>2022-06-22</td>\n",
-       "      <td>xTSACaU2z-Mzqa23BiUeHTEUuY_jbVTWOYFkN3uszxg</td>\n",
-       "      <td>{'name': 'MarketWatch', 'homepage_url': 'https...</td>\n",
-       "      <td>These are the 10 used-car models whose prices ...</td>\n",
-       "      <td>MarketWatch</td>\n",
-       "      <td>https://www.marketwatch.com/story/these-are-th...</td>\n",
-       "      <td>[LOTZ, TSLA]</td>\n",
-       "      <td>https://www.marketwatch.com/amp/story/these-ar...</td>\n",
-       "      <td>https://images.mktw.net/im-569120/social</td>\n",
-       "      <td>Used-car prices rose on average 17% in May, wi...</td>\n",
-       "      <td>No keywords</td>\n",
+       "      <th>3</th>\n",
+       "      <td>2022-08-11</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.225</td>\n",
-       "      <td>17:32:00</td>\n",
-       "      <td>0.202508</td>\n",
+       "      <td>0.171968</td>\n",
+       "      <td>0.083253</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000002</th>\n",
-       "      <td>2022-06-22</td>\n",
-       "      <td>SDepdS_qKyhE6vqbR6Fathnn81fYDapZCk3DKT1Xpv4</td>\n",
-       "      <td>{'name': 'The Motley Fool', 'homepage_url': 'h...</td>\n",
-       "      <td>Why Tesla Shares Jumped Initially, Then Retrea...</td>\n",
-       "      <td>newsfeedback@fool.com (Chris Neiger)</td>\n",
-       "      <td>https://www.fool.com/investing/2022/06/22/why-...</td>\n",
-       "      <td>[TSLA]</td>\n",
-       "      <td>No URL provided</td>\n",
-       "      <td>https://g.foolcdn.com/editorial/images/686400/...</td>\n",
-       "      <td>Tesla's Shanghai plant may temporarily suspend...</td>\n",
-       "      <td>[investing]</td>\n",
+       "      <th>2</th>\n",
+       "      <td>2022-06-25</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>19:33:04</td>\n",
-       "      <td>0.151881</td>\n",
+       "      <td>0.250000</td>\n",
+       "      <td>0.124940</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000001</th>\n",
-       "      <td>2022-06-22</td>\n",
-       "      <td>x_9M1zYfZoHn_ptJM3USKxrodDtd4TcTsQSldXlViMw</td>\n",
-       "      <td>{'name': 'MarketWatch', 'homepage_url': 'https...</td>\n",
-       "      <td>Tesla's new factories are 'gigantic money furn...</td>\n",
-       "      <td>MarketWatch</td>\n",
-       "      <td>https://www.marketwatch.com/story/teslas-new-f...</td>\n",
-       "      <td>[TSLA]</td>\n",
-       "      <td>No URL provided</td>\n",
-       "      <td>https://images.mktw.net/im-569600/social</td>\n",
-       "      <td>Tesla Inc.’s two newest car factories have bee...</td>\n",
-       "      <td>No keywords</td>\n",
+       "      <th>1</th>\n",
+       "      <td>2022-06-24</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.000</td>\n",
-       "      <td>21:59:00</td>\n",
-       "      <td>0.113910</td>\n",
+       "      <td>0.059212</td>\n",
+       "      <td>0.108508</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000000</th>\n",
-       "      <td>2022-06-22</td>\n",
-       "      <td>nVZWipNVQFFoSi87tF0APXW_uRHl13wat_uR1c0iR6A</td>\n",
-       "      <td>{'name': 'Benzinga', 'homepage_url': 'https://...</td>\n",
-       "      <td>Elon Musk Gives New Update On Tesla Cybertruck...</td>\n",
-       "      <td>Chris Katje</td>\n",
-       "      <td>https://www.benzinga.com/news/22/06/27820587/e...</td>\n",
-       "      <td>[F, TSLA, RIVN]</td>\n",
-       "      <td>https://www.benzinga.com/amp/content/27820587</td>\n",
-       "      <td>https://cdn.benzinga.com/files/images/story/20...</td>\n",
-       "      <td>A recent interview between Tesla Inc (NASDAQ: ...</td>\n",
-       "      <td>[News, Interview]</td>\n",
+       "      <th>0</th>\n",
+       "      <td>2022-06-23</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.040</td>\n",
-       "      <td>22:40:56</td>\n",
-       "      <td>0.095433</td>\n",
+       "      <td>0.091056</td>\n",
+       "      <td>0.104145</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                                     date  \\\n",
-       "1970-01-01 00:00:00.000000004  2022-06-22   \n",
-       "1970-01-01 00:00:00.000000003  2022-06-22   \n",
-       "1970-01-01 00:00:00.000000002  2022-06-22   \n",
-       "1970-01-01 00:00:00.000000001  2022-06-22   \n",
-       "1970-01-01 00:00:00.000000000  2022-06-22   \n",
-       "\n",
-       "                                                                        id  \\\n",
-       "1970-01-01 00:00:00.000000004  pksGB2t-5ukDnjkRw_VYr9sfcSOExNmQiHzUq9_rBa0   \n",
-       "1970-01-01 00:00:00.000000003  xTSACaU2z-Mzqa23BiUeHTEUuY_jbVTWOYFkN3uszxg   \n",
-       "1970-01-01 00:00:00.000000002  SDepdS_qKyhE6vqbR6Fathnn81fYDapZCk3DKT1Xpv4   \n",
-       "1970-01-01 00:00:00.000000001  x_9M1zYfZoHn_ptJM3USKxrodDtd4TcTsQSldXlViMw   \n",
-       "1970-01-01 00:00:00.000000000  nVZWipNVQFFoSi87tF0APXW_uRHl13wat_uR1c0iR6A   \n",
-       "\n",
-       "                                                                       publisher  \\\n",
-       "1970-01-01 00:00:00.000000004  {'name': 'Zacks Investment Research', 'homepag...   \n",
-       "1970-01-01 00:00:00.000000003  {'name': 'MarketWatch', 'homepage_url': 'https...   \n",
-       "1970-01-01 00:00:00.000000002  {'name': 'The Motley Fool', 'homepage_url': 'h...   \n",
-       "1970-01-01 00:00:00.000000001  {'name': 'MarketWatch', 'homepage_url': 'https...   \n",
-       "1970-01-01 00:00:00.000000000  {'name': 'Benzinga', 'homepage_url': 'https://...   \n",
-       "\n",
-       "                                                                           title  \\\n",
-       "1970-01-01 00:00:00.000000004  Tesla (TSLA) to Cut 10% Salaried Jobs, Raise H...   \n",
-       "1970-01-01 00:00:00.000000003  These are the 10 used-car models whose prices ...   \n",
-       "1970-01-01 00:00:00.000000002  Why Tesla Shares Jumped Initially, Then Retrea...   \n",
-       "1970-01-01 00:00:00.000000001  Tesla's new factories are 'gigantic money furn...   \n",
-       "1970-01-01 00:00:00.000000000  Elon Musk Gives New Update On Tesla Cybertruck...   \n",
-       "\n",
-       "                                                             author  \\\n",
-       "1970-01-01 00:00:00.000000004                 Zacks Equity Research   \n",
-       "1970-01-01 00:00:00.000000003                           MarketWatch   \n",
-       "1970-01-01 00:00:00.000000002  newsfeedback@fool.com (Chris Neiger)   \n",
-       "1970-01-01 00:00:00.000000001                           MarketWatch   \n",
-       "1970-01-01 00:00:00.000000000                           Chris Katje   \n",
-       "\n",
-       "                                                                     article_url  \\\n",
-       "1970-01-01 00:00:00.000000004  https://www.zacks.com/stock/news/1942395/tesla...   \n",
-       "1970-01-01 00:00:00.000000003  https://www.marketwatch.com/story/these-are-th...   \n",
-       "1970-01-01 00:00:00.000000002  https://www.fool.com/investing/2022/06/22/why-...   \n",
-       "1970-01-01 00:00:00.000000001  https://www.marketwatch.com/story/teslas-new-f...   \n",
-       "1970-01-01 00:00:00.000000000  https://www.benzinga.com/news/22/06/27820587/e...   \n",
-       "\n",
-       "                                              tickers  \\\n",
-       "1970-01-01 00:00:00.000000004  [SMP, TSLA, WNC, FOXF]   \n",
-       "1970-01-01 00:00:00.000000003            [LOTZ, TSLA]   \n",
-       "1970-01-01 00:00:00.000000002                  [TSLA]   \n",
-       "1970-01-01 00:00:00.000000001                  [TSLA]   \n",
-       "1970-01-01 00:00:00.000000000         [F, TSLA, RIVN]   \n",
-       "\n",
-       "                                                                         amp_url  \\\n",
-       "1970-01-01 00:00:00.000000004  https://www.zacks.com/amp/stock/news/1942395/t...   \n",
-       "1970-01-01 00:00:00.000000003  https://www.marketwatch.com/amp/story/these-ar...   \n",
-       "1970-01-01 00:00:00.000000002                                    No URL provided   \n",
-       "1970-01-01 00:00:00.000000001                                    No URL provided   \n",
-       "1970-01-01 00:00:00.000000000      https://www.benzinga.com/amp/content/27820587   \n",
-       "\n",
-       "                                                                       image_url  \\\n",
-       "1970-01-01 00:00:00.000000004  https://staticx-tuner.zacks.com/images/article...   \n",
-       "1970-01-01 00:00:00.000000003           https://images.mktw.net/im-569120/social   \n",
-       "1970-01-01 00:00:00.000000002  https://g.foolcdn.com/editorial/images/686400/...   \n",
-       "1970-01-01 00:00:00.000000001           https://images.mktw.net/im-569600/social   \n",
-       "1970-01-01 00:00:00.000000000  https://cdn.benzinga.com/files/images/story/20...   \n",
-       "\n",
-       "                                                                     description  \\\n",
-       "1970-01-01 00:00:00.000000004  Tesla (TSLA) to lay off 10% of its salaried wo...   \n",
-       "1970-01-01 00:00:00.000000003  Used-car prices rose on average 17% in May, wi...   \n",
-       "1970-01-01 00:00:00.000000002  Tesla's Shanghai plant may temporarily suspend...   \n",
-       "1970-01-01 00:00:00.000000001  Tesla Inc.’s two newest car factories have bee...   \n",
-       "1970-01-01 00:00:00.000000000  A recent interview between Tesla Inc (NASDAQ: ...   \n",
-       "\n",
-       "                                        keywords ticker  sentiment      time  \\\n",
-       "1970-01-01 00:00:00.000000004        No keywords   TSLA      0.000  15:58:00   \n",
-       "1970-01-01 00:00:00.000000003        No keywords   TSLA      0.225  17:32:00   \n",
-       "1970-01-01 00:00:00.000000002        [investing]   TSLA      0.000  19:33:04   \n",
-       "1970-01-01 00:00:00.000000001        No keywords   TSLA      0.000  21:59:00   \n",
-       "1970-01-01 00:00:00.000000000  [News, Interview]   TSLA      0.040  22:40:56   \n",
-       "\n",
-       "                               exp_mean_7_days  \n",
-       "1970-01-01 00:00:00.000000004         0.195010  \n",
-       "1970-01-01 00:00:00.000000003         0.202508  \n",
-       "1970-01-01 00:00:00.000000002         0.151881  \n",
-       "1970-01-01 00:00:00.000000001         0.113910  \n",
-       "1970-01-01 00:00:00.000000000         0.095433  "
+       "         date ticker  sentiment  exp_mean_7_days\n",
+       "4  2022-08-12   TSLA   0.035351         0.053681\n",
+       "3  2022-08-11   TSLA   0.171968         0.083253\n",
+       "2  2022-06-25   TSLA   0.250000         0.124940\n",
+       "1  2022-06-24   TSLA   0.059212         0.108508\n",
+       "0  2022-06-23   TSLA   0.091056         0.104145"
       ]
      },
-     "execution_count": 48,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -899,15 +466,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 49,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "2022-06-20\n",
-      "2024-05-02\n"
+      "2022-06-23\n",
+      "2024-05-05\n"
      ]
     }
    ],
@@ -918,7 +485,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 50,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -935,16 +502,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 15,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(720, 15)"
+       "(66, 4)"
       ]
      },
-     "execution_count": 51,
+     "execution_count": 15,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -955,7 +522,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 16,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -964,16 +531,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 53,
+   "execution_count": 17,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "(657, 15)"
+       "(0, 4)"
       ]
      },
-     "execution_count": 53,
+     "execution_count": 17,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -984,7 +551,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 54,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
@@ -1009,204 +576,61 @@
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>date</th>\n",
-       "      <th>id</th>\n",
-       "      <th>publisher</th>\n",
-       "      <th>title</th>\n",
-       "      <th>author</th>\n",
-       "      <th>article_url</th>\n",
-       "      <th>tickers</th>\n",
-       "      <th>amp_url</th>\n",
-       "      <th>image_url</th>\n",
-       "      <th>description</th>\n",
-       "      <th>keywords</th>\n",
        "      <th>ticker</th>\n",
        "      <th>sentiment</th>\n",
-       "      <th>time</th>\n",
        "      <th>exp_mean_7_days</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000719</th>\n",
-       "      <td>2024-04-29</td>\n",
-       "      <td>MeWGIZiKn6J3JCwWAkHNqVv6Cc9HToUK-HmodQSesdM</td>\n",
-       "      <td>{'name': 'The Motley Fool', 'homepage_url': 'h...</td>\n",
-       "      <td>Why Baidu Stock Jumped Today</td>\n",
-       "      <td>newsfeedback@fool.com (James Brumley)</td>\n",
-       "      <td>https://www.fool.com/investing/2024/04/29/why-...</td>\n",
-       "      <td>[BIDU, GOOGL, TSLA, GOOG, IQ]</td>\n",
-       "      <td>No URL provided</td>\n",
-       "      <td>https://g.foolcdn.com/editorial/images/774939/...</td>\n",
-       "      <td>It's getting difficult not to notice how impre...</td>\n",
-       "      <td>[investing]</td>\n",
+       "      <th>65</th>\n",
+       "      <td>2024-05-05</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.250000</td>\n",
-       "      <td>21:26:09</td>\n",
-       "      <td>0.250000</td>\n",
+       "      <td>0.036190</td>\n",
+       "      <td>0.036190</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000718</th>\n",
-       "      <td>2024-04-29</td>\n",
-       "      <td>T9MgJwXEmlRjWpkmLvcwnBggkbeXWWoGzFISY65WwBc</td>\n",
-       "      <td>{'name': 'Zacks Investment Research', 'homepag...</td>\n",
-       "      <td>Markets Up on Tesla, Q1 Earnings; Q1 Beats Aft...</td>\n",
-       "      <td>Mark Vickery</td>\n",
-       "      <td>https://www.zacks.com/stock/news/2264549/marke...</td>\n",
-       "      <td>[AMZN, AMD, KO, LLY, SBUX, MCD, NXPI, TSLA, YU...</td>\n",
-       "      <td>https://www.zacks.com/amp/stock/news/2264549/m...</td>\n",
-       "      <td>https://staticx-tuner.zacks.com/images/article...</td>\n",
-       "      <td>It's now the third straight day higher going b...</td>\n",
-       "      <td>No keywords</td>\n",
+       "      <th>64</th>\n",
+       "      <td>2024-05-04</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.111905</td>\n",
-       "      <td>22:10:00</td>\n",
-       "      <td>0.215476</td>\n",
+       "      <td>0.062665</td>\n",
+       "      <td>0.042809</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000717</th>\n",
-       "      <td>2024-04-30</td>\n",
-       "      <td>xaUyg2qUKK7h_EDkKruXR9KdY_drlcXLai14uHvZTsc</td>\n",
-       "      <td>{'name': 'Seeking Alpha', 'homepage_url': 'htt...</td>\n",
-       "      <td>Big Tech Earnings Beats Stymie Q2 2024 Sell-Off</td>\n",
-       "      <td>Christine Short</td>\n",
-       "      <td>https://seekingalpha.com/article/4687390-big-t...</td>\n",
-       "      <td>[AAPL, AMZN, GOOG, GOOGL, HSY, KO, META, MMM, ...</td>\n",
-       "      <td>No URL provided</td>\n",
-       "      <td>https://static.seekingalpha.com/cdn/s3/uploads...</td>\n",
-       "      <td>Markets finally turned positive late last week...</td>\n",
-       "      <td>No keywords</td>\n",
+       "      <th>63</th>\n",
+       "      <td>2024-05-03</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>-0.032955</td>\n",
-       "      <td>04:30:00</td>\n",
-       "      <td>0.153369</td>\n",
+       "      <td>0.027798</td>\n",
+       "      <td>0.039056</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000716</th>\n",
-       "      <td>2024-04-30</td>\n",
-       "      <td>IPVxhBMbT73GJJHLQZYPFb8yQpAxzbEuXrJk0dMSt8U</td>\n",
-       "      <td>{'name': 'Zacks Investment Research', 'homepag...</td>\n",
-       "      <td>Stock Market News for Apr 30, 2024</td>\n",
-       "      <td>Zacks Equity Research</td>\n",
-       "      <td>https://www.zacks.com/stock/news/2264591/stock...</td>\n",
-       "      <td>[AAPL, TSLA, PARA]</td>\n",
-       "      <td>https://www.zacks.com/amp/stock/news/2264591/s...</td>\n",
-       "      <td>https://staticx-tuner.zacks.com/images/article...</td>\n",
-       "      <td>Wall Street closed higher on Monday to start a...</td>\n",
-       "      <td>No keywords</td>\n",
+       "      <th>62</th>\n",
+       "      <td>2024-05-02</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.050000</td>\n",
-       "      <td>07:27:00</td>\n",
-       "      <td>0.127526</td>\n",
+       "      <td>0.001443</td>\n",
+       "      <td>0.029653</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>1970-01-01 00:00:00.000000715</th>\n",
-       "      <td>2024-04-30</td>\n",
-       "      <td>6pQAGkGEZvAd76QYnk6aAhhUCVLrUkdOjgnon-ALmsQ</td>\n",
-       "      <td>{'name': 'Benzinga', 'homepage_url': 'https://...</td>\n",
-       "      <td>'Tesla Has The Endorsement' Of Xi Jinping's Go...</td>\n",
-       "      <td>Benzinga Neuro</td>\n",
-       "      <td>https://www.benzinga.com/analyst-ratings/analy...</td>\n",
-       "      <td>[TSLA]</td>\n",
-       "      <td>https://www.benzinga.com/amp/content/38511044</td>\n",
-       "      <td>https://cdn.benzinga.com/files/images/story/20...</td>\n",
-       "      <td>Tim Higgins, author of “Power Play: Tesla, Elo...</td>\n",
-       "      <td>[News, Analyst Color, Tech, General]</td>\n",
+       "      <th>61</th>\n",
+       "      <td>2024-05-01</td>\n",
        "      <td>TSLA</td>\n",
-       "      <td>0.008333</td>\n",
-       "      <td>07:42:58</td>\n",
-       "      <td>0.097728</td>\n",
+       "      <td>0.162742</td>\n",
+       "      <td>0.062925</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "text/plain": [
-       "                                     date  \\\n",
-       "1970-01-01 00:00:00.000000719  2024-04-29   \n",
-       "1970-01-01 00:00:00.000000718  2024-04-29   \n",
-       "1970-01-01 00:00:00.000000717  2024-04-30   \n",
-       "1970-01-01 00:00:00.000000716  2024-04-30   \n",
-       "1970-01-01 00:00:00.000000715  2024-04-30   \n",
-       "\n",
-       "                                                                        id  \\\n",
-       "1970-01-01 00:00:00.000000719  MeWGIZiKn6J3JCwWAkHNqVv6Cc9HToUK-HmodQSesdM   \n",
-       "1970-01-01 00:00:00.000000718  T9MgJwXEmlRjWpkmLvcwnBggkbeXWWoGzFISY65WwBc   \n",
-       "1970-01-01 00:00:00.000000717  xaUyg2qUKK7h_EDkKruXR9KdY_drlcXLai14uHvZTsc   \n",
-       "1970-01-01 00:00:00.000000716  IPVxhBMbT73GJJHLQZYPFb8yQpAxzbEuXrJk0dMSt8U   \n",
-       "1970-01-01 00:00:00.000000715  6pQAGkGEZvAd76QYnk6aAhhUCVLrUkdOjgnon-ALmsQ   \n",
-       "\n",
-       "                                                                       publisher  \\\n",
-       "1970-01-01 00:00:00.000000719  {'name': 'The Motley Fool', 'homepage_url': 'h...   \n",
-       "1970-01-01 00:00:00.000000718  {'name': 'Zacks Investment Research', 'homepag...   \n",
-       "1970-01-01 00:00:00.000000717  {'name': 'Seeking Alpha', 'homepage_url': 'htt...   \n",
-       "1970-01-01 00:00:00.000000716  {'name': 'Zacks Investment Research', 'homepag...   \n",
-       "1970-01-01 00:00:00.000000715  {'name': 'Benzinga', 'homepage_url': 'https://...   \n",
-       "\n",
-       "                                                                           title  \\\n",
-       "1970-01-01 00:00:00.000000719                       Why Baidu Stock Jumped Today   \n",
-       "1970-01-01 00:00:00.000000718  Markets Up on Tesla, Q1 Earnings; Q1 Beats Aft...   \n",
-       "1970-01-01 00:00:00.000000717    Big Tech Earnings Beats Stymie Q2 2024 Sell-Off   \n",
-       "1970-01-01 00:00:00.000000716                 Stock Market News for Apr 30, 2024   \n",
-       "1970-01-01 00:00:00.000000715  'Tesla Has The Endorsement' Of Xi Jinping's Go...   \n",
-       "\n",
-       "                                                              author  \\\n",
-       "1970-01-01 00:00:00.000000719  newsfeedback@fool.com (James Brumley)   \n",
-       "1970-01-01 00:00:00.000000718                           Mark Vickery   \n",
-       "1970-01-01 00:00:00.000000717                        Christine Short   \n",
-       "1970-01-01 00:00:00.000000716                  Zacks Equity Research   \n",
-       "1970-01-01 00:00:00.000000715                         Benzinga Neuro   \n",
-       "\n",
-       "                                                                     article_url  \\\n",
-       "1970-01-01 00:00:00.000000719  https://www.fool.com/investing/2024/04/29/why-...   \n",
-       "1970-01-01 00:00:00.000000718  https://www.zacks.com/stock/news/2264549/marke...   \n",
-       "1970-01-01 00:00:00.000000717  https://seekingalpha.com/article/4687390-big-t...   \n",
-       "1970-01-01 00:00:00.000000716  https://www.zacks.com/stock/news/2264591/stock...   \n",
-       "1970-01-01 00:00:00.000000715  https://www.benzinga.com/analyst-ratings/analy...   \n",
-       "\n",
-       "                                                                         tickers  \\\n",
-       "1970-01-01 00:00:00.000000719                      [BIDU, GOOGL, TSLA, GOOG, IQ]   \n",
-       "1970-01-01 00:00:00.000000718  [AMZN, AMD, KO, LLY, SBUX, MCD, NXPI, TSLA, YU...   \n",
-       "1970-01-01 00:00:00.000000717  [AAPL, AMZN, GOOG, GOOGL, HSY, KO, META, MMM, ...   \n",
-       "1970-01-01 00:00:00.000000716                                 [AAPL, TSLA, PARA]   \n",
-       "1970-01-01 00:00:00.000000715                                             [TSLA]   \n",
-       "\n",
-       "                                                                         amp_url  \\\n",
-       "1970-01-01 00:00:00.000000719                                    No URL provided   \n",
-       "1970-01-01 00:00:00.000000718  https://www.zacks.com/amp/stock/news/2264549/m...   \n",
-       "1970-01-01 00:00:00.000000717                                    No URL provided   \n",
-       "1970-01-01 00:00:00.000000716  https://www.zacks.com/amp/stock/news/2264591/s...   \n",
-       "1970-01-01 00:00:00.000000715      https://www.benzinga.com/amp/content/38511044   \n",
-       "\n",
-       "                                                                       image_url  \\\n",
-       "1970-01-01 00:00:00.000000719  https://g.foolcdn.com/editorial/images/774939/...   \n",
-       "1970-01-01 00:00:00.000000718  https://staticx-tuner.zacks.com/images/article...   \n",
-       "1970-01-01 00:00:00.000000717  https://static.seekingalpha.com/cdn/s3/uploads...   \n",
-       "1970-01-01 00:00:00.000000716  https://staticx-tuner.zacks.com/images/article...   \n",
-       "1970-01-01 00:00:00.000000715  https://cdn.benzinga.com/files/images/story/20...   \n",
-       "\n",
-       "                                                                     description  \\\n",
-       "1970-01-01 00:00:00.000000719  It's getting difficult not to notice how impre...   \n",
-       "1970-01-01 00:00:00.000000718  It's now the third straight day higher going b...   \n",
-       "1970-01-01 00:00:00.000000717  Markets finally turned positive late last week...   \n",
-       "1970-01-01 00:00:00.000000716  Wall Street closed higher on Monday to start a...   \n",
-       "1970-01-01 00:00:00.000000715  Tim Higgins, author of “Power Play: Tesla, Elo...   \n",
-       "\n",
-       "                                                           keywords ticker  \\\n",
-       "1970-01-01 00:00:00.000000719                           [investing]   TSLA   \n",
-       "1970-01-01 00:00:00.000000718                           No keywords   TSLA   \n",
-       "1970-01-01 00:00:00.000000717                           No keywords   TSLA   \n",
-       "1970-01-01 00:00:00.000000716                           No keywords   TSLA   \n",
-       "1970-01-01 00:00:00.000000715  [News, Analyst Color, Tech, General]   TSLA   \n",
-       "\n",
-       "                               sentiment      time  exp_mean_7_days  \n",
-       "1970-01-01 00:00:00.000000719   0.250000  21:26:09         0.250000  \n",
-       "1970-01-01 00:00:00.000000718   0.111905  22:10:00         0.215476  \n",
-       "1970-01-01 00:00:00.000000717  -0.032955  04:30:00         0.153369  \n",
-       "1970-01-01 00:00:00.000000716   0.050000  07:27:00         0.127526  \n",
-       "1970-01-01 00:00:00.000000715   0.008333  07:42:58         0.097728  "
+       "          date ticker  sentiment  exp_mean_7_days\n",
+       "65  2024-05-05   TSLA   0.036190         0.036190\n",
+       "64  2024-05-04   TSLA   0.062665         0.042809\n",
+       "63  2024-05-03   TSLA   0.027798         0.039056\n",
+       "62  2024-05-02   TSLA   0.001443         0.029653\n",
+       "61  2024-05-01   TSLA   0.162742         0.062925"
       ]
      },
-     "execution_count": 54,
+     "execution_count": 18,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1239,7 +663,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.11.4"
   },
   "orig_nbformat": 4
  },

historical_stock.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 1,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -25,7 +25,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [
     {
@@ -34,11 +34,11 @@
      "text": [
       "            1. open  2. high    3. low  4. close    5. volume ticker\n",
       "date                                                                \n",
+      "2024-05-03   182.10   184.78  178.4200    181.19   75491539.0   TSLA\n",
       "2024-05-02   182.86   184.60  176.0200    180.01   89148041.0   TSLA\n",
       "2024-05-01   182.00   185.86  179.0100    179.99   92829719.0   TSLA\n",
       "2024-04-30   186.98   190.95  182.8401    183.28  127031787.0   TSLA\n",
-      "2024-04-29   188.42   198.87  184.5400    194.05  243869678.0   TSLA\n",
-      "2024-04-26   168.85   172.12  166.3700    168.29  109815725.0   TSLA\n"
+      "2024-04-29   188.42   198.87  184.5400    194.05  243869678.0   TSLA\n"
      ]
     }
    ],
@@ -67,7 +67,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -125,7 +125,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -198,7 +198,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -236,7 +236,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.11.4"
   },
   "orig_nbformat": 4
  },

news_preprocessing.ipynb

@@ -46,6 +46,7 @@
     "    df = df.set_index(\"date\")\n",
     "    df.reset_index(inplace=True)\n",
     "    df.index = pd.to_datetime(df.index)\n",
+    "    df = df.groupby(['date', 'ticker'])['sentiment'].mean().reset_index()\n",
     "\n",
     "    return df"
    ]

news_preprocessing.py

@@ -33,6 +33,7 @@ def process_news_articles(news_articles):
     df = df.set_index("date")
     df.reset_index(inplace=True)
     df.index = pd.to_datetime(df.index)
+    df = df.groupby(['date', 'ticker'])['sentiment'].mean().reset_index(name='sentiment')
 
     return df
 

requirements.txt

@@ -4,7 +4,7 @@ parsedatetime==2.6
 #plotly==5.9.0
 #streamlit_folium==0.17.4
 dataframe_image==0.2.3
-hopsworks
+hopsworks==3.7.0
 hsml
 joblib
 matplotlib==3.6.3

training_pipeline.ipynb

@@ -0,0 +1,245 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import hopsworks\n",
+    "from dotenv import load_dotenv\n",
+    "import os\n",
+    "\n",
+    "load_dotenv()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fetching feature view from hopsworks...\n",
+      "Connection closed.\n",
+      "Connected. Call `.close()` to terminate connection gracefully.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Logged in to project, explore it here https://c.app.hopsworks.ai:443/p/549016\n",
+      "Connected. Call `.close()` to terminate connection gracefully.\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "../src/arrow/status.cc:137: DoAction result was not fully consumed: Cancelled: Flight cancelled call, with message: CANCELLED. Detail: Cancelled\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2024-05-06 12:27:55,071 WARNING: DeprecationWarning: ssl.PROTOCOL_TLS is deprecated\n",
+      "\n",
+      "Error: Reading data from Hopsworks, using Hive           \n"
+     ]
+    },
+    {
+     "ename": "DatabaseError",
+     "evalue": "Execution failed on sql: WITH right_fg0 AS (SELECT *\nFROM (SELECT `fg1`.`date` `date`, `fg1`.`open` `open`, `fg1`.`ticker` `ticker`, `fg1`.`ticker` `join_pk_ticker`, `fg1`.`date` `join_evt_date`, `fg0`.`date` `date`, `fg0`.`sentiment` `sentiment`, RANK() OVER (PARTITION BY `fg1`.`ticker`, `fg1`.`date` ORDER BY `fg0`.`date` DESC) pit_rank_hopsworks\nFROM `mtzeve_featurestore`.`tesla_stock_1` `fg1`\nINNER JOIN `mtzeve_featurestore`.`news_sentiment_updated_1` `fg0` ON `fg1`.`ticker` = `fg0`.`ticker` AND `fg1`.`date` >= `fg0`.`date`\nWHERE `fg1`.`date` >= TIMESTAMP '1970-01-01 00:16:40.000' AND `fg1`.`date` < TIMESTAMP '2024-05-06 10:27:51.000') NA\nWHERE `pit_rank_hopsworks` = 1) (SELECT `right_fg0`.`date` `date`, `right_fg0`.`open` `open`, `right_fg0`.`ticker` `ticker`, `right_fg0`.`date` `date`, `right_fg0`.`sentiment` `sentiment`\nFROM right_fg0)\nTExecuteStatementResp(status=TStatus(statusCode=3, infoMessages=['*org.apache.hive.service.cli.HiveSQLException:Error while compiling statement: FAILED: SemanticException [Error 10007]: Ambiguous column reference date in na:28:27', 'org.apache.hive.service.cli.operation.Operation:toSQLException:Operation.java:343', 'org.apache.hive.service.cli.operation.SQLOperation:prepare:SQLOperation.java:203', 'org.apache.hive.service.cli.operation.SQLOperation:runInternal:SQLOperation.java:266', 'org.apache.hive.service.cli.operation.Operation:run:Operation.java:255', 'org.apache.hive.service.cli.session.HiveSessionImpl:executeStatementInternal:HiveSessionImpl.java:541', 'org.apache.hive.service.cli.session.HiveSessionImpl:executeStatement:HiveSessionImpl.java:516', 'sun.reflect.GeneratedMethodAccessor216:invoke::-1', 'sun.reflect.DelegatingMethodAccessorImpl:invoke:DelegatingMethodAccessorImpl.java:43', 'java.lang.reflect.Method:invoke:Method.java:498', 'org.apache.hive.service.cli.session.HiveSessionProxy:invoke:HiveSessionProxy.java:78', 'org.apache.hive.service.cli.session.HiveSessionProxy:access$000:HiveSessionProxy.java:36', 'org.apache.hive.service.cli.session.HiveSessionProxy$1:run:HiveSessionProxy.java:63', 'java.security.AccessController:doPrivileged:AccessController.java:-2', 'javax.security.auth.Subject:doAs:Subject.java:422', 'org.apache.hadoop.security.UserGroupInformation:doAs:UserGroupInformation.java:1821', 'org.apache.hive.service.cli.session.HiveSessionProxy:invoke:HiveSessionProxy.java:59', 'com.sun.proxy.$Proxy53:executeStatement::-1', 'org.apache.hive.service.cli.CLIService:executeStatement:CLIService.java:281', 'org.apache.hive.service.cli.thrift.ThriftCLIService:ExecuteStatement:ThriftCLIService.java:712', 'org.apache.hive.service.rpc.thrift.TCLIService$Processor$ExecuteStatement:getResult:TCLIService.java:1557', 'org.apache.hive.service.rpc.thrift.TCLIService$Processor$ExecuteStatement:getResult:TCLIService.java:1542', 'org.apache.thrift.ProcessFunction:process:ProcessFunction.java:39', 'org.apache.thrift.TBaseProcessor:process:TBaseProcessor.java:39', 'org.apache.hive.service.auth.TSetIpAddressProcessor:process:TSetIpAddressProcessor.java:56', 'org.apache.thrift.server.TThreadPoolServer$WorkerProcess:run:TThreadPoolServer.java:286', 'java.util.concurrent.ThreadPoolExecutor:runWorker:ThreadPoolExecutor.java:1149', 'java.util.concurrent.ThreadPoolExecutor$Worker:run:ThreadPoolExecutor.java:624', 'java.lang.Thread:run:Thread.java:750', '*org.apache.hadoop.hive.ql.parse.SemanticException:Ambiguous column reference date in na:44:17', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:rewriteRRForSubQ:SemanticAnalyzer.java:11359', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11338', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11188', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11215', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11188', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11215', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11201', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genOPTree:SemanticAnalyzer.java:11987', 'org.apache.hadoop.hive.ql.parse.CalcitePlanner:genOPTree:CalcitePlanner.java:597', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:analyzeInternal:SemanticAnalyzer.java:12066', 'org.apache.hadoop.hive.ql.parse.CalcitePlanner:analyzeInternal:CalcitePlanner.java:334', 'org.apache.hadoop.hive.ql.parse.BaseSemanticAnalyzer:analyze:BaseSemanticAnalyzer.java:285', 'org.apache.hadoop.hive.ql.Driver:compile:Driver.java:643', 'org.apache.hadoop.hive.ql.Driver:compileInternal:Driver.java:1683', 'org.apache.hadoop.hive.ql.Driver:compileAndRespond:Driver.java:1630', 'org.apache.hadoop.hive.ql.Driver:compileAndRespond:Driver.java:1625', 'org.apache.hadoop.hive.ql.reexec.ReExecDriver:compileAndRespond:ReExecDriver.java:126', 'org.apache.hive.service.cli.operation.SQLOperation:prepare:SQLOperation.java:201'], sqlState='42000', errorCode=10007, errorMessage='Error while compiling statement: FAILED: SemanticException [Error 10007]: Ambiguous column reference date in na'), operationHandle=None)\nunable to rollback",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mOperationalError\u001b[0m                          Traceback (most recent call last)",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/pandas/io/sql.py:2018\u001b[0m, in \u001b[0;36mSQLiteDatabase.execute\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   2017\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m-> 2018\u001b[0m     cur\u001b[39m.\u001b[39mexecute(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[1;32m   2019\u001b[0m     \u001b[39mreturn\u001b[39;00m cur\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/pyhive/hive.py:408\u001b[0m, in \u001b[0;36mCursor.execute\u001b[0;34m(self, operation, parameters, **kwargs)\u001b[0m\n\u001b[1;32m    407\u001b[0m response \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_connection\u001b[39m.\u001b[39mclient\u001b[39m.\u001b[39mExecuteStatement(req)\n\u001b[0;32m--> 408\u001b[0m _check_status(response)\n\u001b[1;32m    409\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_operationHandle \u001b[39m=\u001b[39m response\u001b[39m.\u001b[39moperationHandle\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/pyhive/hive.py:538\u001b[0m, in \u001b[0;36m_check_status\u001b[0;34m(response)\u001b[0m\n\u001b[1;32m    537\u001b[0m \u001b[39mif\u001b[39;00m response\u001b[39m.\u001b[39mstatus\u001b[39m.\u001b[39mstatusCode \u001b[39m!=\u001b[39m ttypes\u001b[39m.\u001b[39mTStatusCode\u001b[39m.\u001b[39mSUCCESS_STATUS:\n\u001b[0;32m--> 538\u001b[0m     \u001b[39mraise\u001b[39;00m OperationalError(response)\n",
+      "\u001b[0;31mOperationalError\u001b[0m: TExecuteStatementResp(status=TStatus(statusCode=3, infoMessages=['*org.apache.hive.service.cli.HiveSQLException:Error while compiling statement: FAILED: SemanticException [Error 10007]: Ambiguous column reference date in na:28:27', 'org.apache.hive.service.cli.operation.Operation:toSQLException:Operation.java:343', 'org.apache.hive.service.cli.operation.SQLOperation:prepare:SQLOperation.java:203', 'org.apache.hive.service.cli.operation.SQLOperation:runInternal:SQLOperation.java:266', 'org.apache.hive.service.cli.operation.Operation:run:Operation.java:255', 'org.apache.hive.service.cli.session.HiveSessionImpl:executeStatementInternal:HiveSessionImpl.java:541', 'org.apache.hive.service.cli.session.HiveSessionImpl:executeStatement:HiveSessionImpl.java:516', 'sun.reflect.GeneratedMethodAccessor216:invoke::-1', 'sun.reflect.DelegatingMethodAccessorImpl:invoke:DelegatingMethodAccessorImpl.java:43', 'java.lang.reflect.Method:invoke:Method.java:498', 'org.apache.hive.service.cli.session.HiveSessionProxy:invoke:HiveSessionProxy.java:78', 'org.apache.hive.service.cli.session.HiveSessionProxy:access$000:HiveSessionProxy.java:36', 'org.apache.hive.service.cli.session.HiveSessionProxy$1:run:HiveSessionProxy.java:63', 'java.security.AccessController:doPrivileged:AccessController.java:-2', 'javax.security.auth.Subject:doAs:Subject.java:422', 'org.apache.hadoop.security.UserGroupInformation:doAs:UserGroupInformation.java:1821', 'org.apache.hive.service.cli.session.HiveSessionProxy:invoke:HiveSessionProxy.java:59', 'com.sun.proxy.$Proxy53:executeStatement::-1', 'org.apache.hive.service.cli.CLIService:executeStatement:CLIService.java:281', 'org.apache.hive.service.cli.thrift.ThriftCLIService:ExecuteStatement:ThriftCLIService.java:712', 'org.apache.hive.service.rpc.thrift.TCLIService$Processor$ExecuteStatement:getResult:TCLIService.java:1557', 'org.apache.hive.service.rpc.thrift.TCLIService$Processor$ExecuteStatement:getResult:TCLIService.java:1542', 'org.apache.thrift.ProcessFunction:process:ProcessFunction.java:39', 'org.apache.thrift.TBaseProcessor:process:TBaseProcessor.java:39', 'org.apache.hive.service.auth.TSetIpAddressProcessor:process:TSetIpAddressProcessor.java:56', 'org.apache.thrift.server.TThreadPoolServer$WorkerProcess:run:TThreadPoolServer.java:286', 'java.util.concurrent.ThreadPoolExecutor:runWorker:ThreadPoolExecutor.java:1149', 'java.util.concurrent.ThreadPoolExecutor$Worker:run:ThreadPoolExecutor.java:624', 'java.lang.Thread:run:Thread.java:750', '*org.apache.hadoop.hive.ql.parse.SemanticException:Ambiguous column reference date in na:44:17', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:rewriteRRForSubQ:SemanticAnalyzer.java:11359', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11338', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11188', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11215', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11188', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11215', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11201', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genOPTree:SemanticAnalyzer.java:11987', 'org.apache.hadoop.hive.ql.parse.CalcitePlanner:genOPTree:CalcitePlanner.java:597', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:analyzeInternal:SemanticAnalyzer.java:12066', 'org.apache.hadoop.hive.ql.parse.CalcitePlanner:analyzeInternal:CalcitePlanner.java:334', 'org.apache.hadoop.hive.ql.parse.BaseSemanticAnalyzer:analyze:BaseSemanticAnalyzer.java:285', 'org.apache.hadoop.hive.ql.Driver:compile:Driver.java:643', 'org.apache.hadoop.hive.ql.Driver:compileInternal:Driver.java:1683', 'org.apache.hadoop.hive.ql.Driver:compileAndRespond:Driver.java:1630', 'org.apache.hadoop.hive.ql.Driver:compileAndRespond:Driver.java:1625', 'org.apache.hadoop.hive.ql.reexec.ReExecDriver:compileAndRespond:ReExecDriver.java:126', 'org.apache.hive.service.cli.operation.SQLOperation:prepare:SQLOperation.java:201'], sqlState='42000', errorCode=10007, errorMessage='Error while compiling statement: FAILED: SemanticException [Error 10007]: Ambiguous column reference date in na'), operationHandle=None)",
+      "\nDuring handling of the above exception, another exception occurred:\n",
+      "\u001b[0;31mNotSupportedError\u001b[0m                         Traceback (most recent call last)",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/pandas/io/sql.py:2022\u001b[0m, in \u001b[0;36mSQLiteDatabase.execute\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   2021\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m-> 2022\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mcon\u001b[39m.\u001b[39mrollback()\n\u001b[1;32m   2023\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mException\u001b[39;00m \u001b[39mas\u001b[39;00m inner_exc:  \u001b[39m# pragma: no cover\u001b[39;00m\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/pyhive/hive.py:285\u001b[0m, in \u001b[0;36mConnection.rollback\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    284\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mrollback\u001b[39m(\u001b[39mself\u001b[39m):\n\u001b[0;32m--> 285\u001b[0m     \u001b[39mraise\u001b[39;00m NotSupportedError(\u001b[39m\"\u001b[39m\u001b[39mHive does not have transactions\u001b[39m\u001b[39m\"\u001b[39m)\n",
+      "\u001b[0;31mNotSupportedError\u001b[0m: Hive does not have transactions",
+      "\nThe above exception was the direct cause of the following exception:\n",
+      "\u001b[0;31mDatabaseError\u001b[0m                             Traceback (most recent call last)",
+      "\u001b[1;32m/Users/manos/Documents/BDS/Mlops_2version/MLops_mod/training_pipeline.ipynb Cell 3\u001b[0m line \u001b[0;36m1\n\u001b[1;32m      <a href='vscode-notebook-cell:/Users/manos/Documents/BDS/Mlops_2version/MLops_mod/training_pipeline.ipynb#W4sZmlsZQ%3D%3D?line=6'>7</a>\u001b[0m fv \u001b[39m=\u001b[39m fs\u001b[39m.\u001b[39mget_feature_view(\n\u001b[1;32m      <a href='vscode-notebook-cell:/Users/manos/Documents/BDS/Mlops_2version/MLops_mod/training_pipeline.ipynb#W4sZmlsZQ%3D%3D?line=7'>8</a>\u001b[0m     name \u001b[39m=\u001b[39m \u001b[39m'\u001b[39m\u001b[39mtesla_stocks_fv\u001b[39m\u001b[39m'\u001b[39m,\n\u001b[1;32m      <a href='vscode-notebook-cell:/Users/manos/Documents/BDS/Mlops_2version/MLops_mod/training_pipeline.ipynb#W4sZmlsZQ%3D%3D?line=8'>9</a>\u001b[0m     version \u001b[39m=\u001b[39m \u001b[39m1\u001b[39m\n\u001b[1;32m     <a href='vscode-notebook-cell:/Users/manos/Documents/BDS/Mlops_2version/MLops_mod/training_pipeline.ipynb#W4sZmlsZQ%3D%3D?line=9'>10</a>\u001b[0m )\n\u001b[1;32m     <a href='vscode-notebook-cell:/Users/manos/Documents/BDS/Mlops_2version/MLops_mod/training_pipeline.ipynb#W4sZmlsZQ%3D%3D?line=10'>11</a>\u001b[0m \u001b[39m# Get dataframe of training data from feature view\u001b[39;00m\n\u001b[0;32m---> <a href='vscode-notebook-cell:/Users/manos/Documents/BDS/Mlops_2version/MLops_mod/training_pipeline.ipynb#W4sZmlsZQ%3D%3D?line=11'>12</a>\u001b[0m df, _ \u001b[39m=\u001b[39m fv\u001b[39m.\u001b[39mtraining_data(read_options\u001b[39m=\u001b[39m{\u001b[39m\"\u001b[39m\u001b[39muse_hive\u001b[39m\u001b[39m\"\u001b[39m: \u001b[39mTrue\u001b[39;00m})\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/usage.py:212\u001b[0m, in \u001b[0;36mmethod_logger.<locals>.wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    210\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mException\u001b[39;00m \u001b[39mas\u001b[39;00m e:\n\u001b[1;32m    211\u001b[0m     exception \u001b[39m=\u001b[39m e\n\u001b[0;32m--> 212\u001b[0m     \u001b[39mraise\u001b[39;00m e\n\u001b[1;32m    213\u001b[0m \u001b[39mfinally\u001b[39;00m:\n\u001b[1;32m    214\u001b[0m     \u001b[39mtry\u001b[39;00m:\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/usage.py:208\u001b[0m, in \u001b[0;36mmethod_logger.<locals>.wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    205\u001b[0m exception \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n\u001b[1;32m    206\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m    207\u001b[0m     \u001b[39m# Call the original method\u001b[39;00m\n\u001b[0;32m--> 208\u001b[0m     result \u001b[39m=\u001b[39m func(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[1;32m    209\u001b[0m     \u001b[39mreturn\u001b[39;00m result\n\u001b[1;32m    210\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mException\u001b[39;00m \u001b[39mas\u001b[39;00m e:\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/feature_view.py:2222\u001b[0m, in \u001b[0;36mFeatureView.training_data\u001b[0;34m(self, start_time, end_time, description, extra_filter, statistics_config, read_options, spine, primary_keys, event_time, training_helper_columns)\u001b[0m\n\u001b[1;32m   2109\u001b[0m \u001b[39m\u001b[39m\u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m   2110\u001b[0m \u001b[39mCreate the metadata for a training dataset and get the corresponding training data from the offline feature store.\u001b[39;00m\n\u001b[1;32m   2111\u001b[0m \u001b[39mThis returns the training data in memory and does not materialise data in storage.\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   2205\u001b[0m \u001b[39m    (X, y): Tuple of dataframe of features and labels. If there are no labels, y returns `None`.\u001b[39;00m\n\u001b[1;32m   2206\u001b[0m \u001b[39m\"\"\"\u001b[39;00m\n\u001b[1;32m   2207\u001b[0m td \u001b[39m=\u001b[39m training_dataset\u001b[39m.\u001b[39mTrainingDataset(\n\u001b[1;32m   2208\u001b[0m     name\u001b[39m=\u001b[39m\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mname,\n\u001b[1;32m   2209\u001b[0m     version\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   2220\u001b[0m     extra_filter\u001b[39m=\u001b[39mextra_filter,\n\u001b[1;32m   2221\u001b[0m )\n\u001b[0;32m-> 2222\u001b[0m td, df \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_feature_view_engine\u001b[39m.\u001b[39mget_training_data(\n\u001b[1;32m   2223\u001b[0m     \u001b[39mself\u001b[39m,\n\u001b[1;32m   2224\u001b[0m     read_options,\n\u001b[1;32m   2225\u001b[0m     training_dataset_obj\u001b[39m=\u001b[39mtd,\n\u001b[1;32m   2226\u001b[0m     spine\u001b[39m=\u001b[39mspine,\n\u001b[1;32m   2227\u001b[0m     primary_keys\u001b[39m=\u001b[39mprimary_keys,\n\u001b[1;32m   2228\u001b[0m     event_time\u001b[39m=\u001b[39mevent_time,\n\u001b[1;32m   2229\u001b[0m     training_helper_columns\u001b[39m=\u001b[39mtraining_helper_columns,\n\u001b[1;32m   2230\u001b[0m )\n\u001b[1;32m   2231\u001b[0m warnings\u001b[39m.\u001b[39mwarn(\n\u001b[1;32m   2232\u001b[0m     \u001b[39m\"\u001b[39m\u001b[39mIncremented version to `\u001b[39m\u001b[39m{}\u001b[39;00m\u001b[39m`.\u001b[39m\u001b[39m\"\u001b[39m\u001b[39m.\u001b[39mformat(td\u001b[39m.\u001b[39mversion),\n\u001b[1;32m   2233\u001b[0m     util\u001b[39m.\u001b[39mVersionWarning,\n\u001b[1;32m   2234\u001b[0m )\n\u001b[1;32m   2235\u001b[0m \u001b[39mreturn\u001b[39;00m df\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/core/feature_view_engine.py:346\u001b[0m, in \u001b[0;36mFeatureViewEngine.get_training_data\u001b[0;34m(self, feature_view_obj, read_options, splits, training_dataset_obj, training_dataset_version, spine, primary_keys, event_time, training_helper_columns)\u001b[0m\n\u001b[1;32m    333\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_check_feature_group_accessibility(feature_view_obj)\n\u001b[1;32m    334\u001b[0m     query \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mget_batch_query(\n\u001b[1;32m    335\u001b[0m         feature_view_obj,\n\u001b[1;32m    336\u001b[0m         training_dataset_version\u001b[39m=\u001b[39mtd_updated\u001b[39m.\u001b[39mversion,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    344\u001b[0m         spine\u001b[39m=\u001b[39mspine,\n\u001b[1;32m    345\u001b[0m     )\n\u001b[0;32m--> 346\u001b[0m     split_df \u001b[39m=\u001b[39m engine\u001b[39m.\u001b[39mget_instance()\u001b[39m.\u001b[39mget_training_data(\n\u001b[1;32m    347\u001b[0m         td_updated, feature_view_obj, query, read_options\n\u001b[1;32m    348\u001b[0m     )\n\u001b[1;32m    349\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mcompute_training_dataset_statistics(\n\u001b[1;32m    350\u001b[0m         feature_view_obj, td_updated, split_df\n\u001b[1;32m    351\u001b[0m     )\n\u001b[1;32m    353\u001b[0m \u001b[39m# split df into features and labels df\u001b[39;00m\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/engine/python.py:648\u001b[0m, in \u001b[0;36mEngine.get_training_data\u001b[0;34m(self, training_dataset_obj, feature_view_obj, query_obj, read_options)\u001b[0m\n\u001b[1;32m    644\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_prepare_transform_split_df(\n\u001b[1;32m    645\u001b[0m         query_obj, training_dataset_obj, feature_view_obj, read_options\n\u001b[1;32m    646\u001b[0m     )\n\u001b[1;32m    647\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[0;32m--> 648\u001b[0m     df \u001b[39m=\u001b[39m query_obj\u001b[39m.\u001b[39mread(read_options\u001b[39m=\u001b[39mread_options)\n\u001b[1;32m    649\u001b[0m     transformation_function_engine\u001b[39m.\u001b[39mTransformationFunctionEngine\u001b[39m.\u001b[39mpopulate_builtin_transformation_functions(\n\u001b[1;32m    650\u001b[0m         training_dataset_obj, feature_view_obj, df\n\u001b[1;32m    651\u001b[0m     )\n\u001b[1;32m    652\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_apply_transformation_function(\n\u001b[1;32m    653\u001b[0m         training_dataset_obj\u001b[39m.\u001b[39mtransformation_functions, df\n\u001b[1;32m    654\u001b[0m     )\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/constructor/query.py:173\u001b[0m, in \u001b[0;36mQuery.read\u001b[0;34m(self, online, dataframe_type, read_options)\u001b[0m\n\u001b[1;32m    168\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mlen\u001b[39m(\u001b[39mself\u001b[39m\u001b[39m.\u001b[39mjoins) \u001b[39m>\u001b[39m \u001b[39m0\u001b[39m \u001b[39mor\u001b[39;00m \u001b[39mNone\u001b[39;00m \u001b[39min\u001b[39;00m [f\u001b[39m.\u001b[39mtype \u001b[39mfor\u001b[39;00m f \u001b[39min\u001b[39;00m schema]:\n\u001b[1;32m    169\u001b[0m         \u001b[39mraise\u001b[39;00m \u001b[39mValueError\u001b[39;00m(\n\u001b[1;32m    170\u001b[0m             \u001b[39m\"\u001b[39m\u001b[39mPandas types casting only supported for feature_group.read()/query.select_all()\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m    171\u001b[0m         )\n\u001b[0;32m--> 173\u001b[0m \u001b[39mreturn\u001b[39;00m engine\u001b[39m.\u001b[39mget_instance()\u001b[39m.\u001b[39msql(\n\u001b[1;32m    174\u001b[0m     sql_query,\n\u001b[1;32m    175\u001b[0m     \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_feature_store_name,\n\u001b[1;32m    176\u001b[0m     online_conn,\n\u001b[1;32m    177\u001b[0m     dataframe_type,\n\u001b[1;32m    178\u001b[0m     read_options,\n\u001b[1;32m    179\u001b[0m     schema,\n\u001b[1;32m    180\u001b[0m )\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/engine/python.py:139\u001b[0m, in \u001b[0;36mEngine.sql\u001b[0;34m(self, sql_query, feature_store, online_conn, dataframe_type, read_options, schema)\u001b[0m\n\u001b[1;32m    129\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39msql\u001b[39m(\n\u001b[1;32m    130\u001b[0m     \u001b[39mself\u001b[39m,\n\u001b[1;32m    131\u001b[0m     sql_query,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    136\u001b[0m     schema\u001b[39m=\u001b[39m\u001b[39mNone\u001b[39;00m,\n\u001b[1;32m    137\u001b[0m ):\n\u001b[1;32m    138\u001b[0m     \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m online_conn:\n\u001b[0;32m--> 139\u001b[0m         \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_sql_offline(\n\u001b[1;32m    140\u001b[0m             sql_query,\n\u001b[1;32m    141\u001b[0m             feature_store,\n\u001b[1;32m    142\u001b[0m             dataframe_type,\n\u001b[1;32m    143\u001b[0m             schema,\n\u001b[1;32m    144\u001b[0m             hive_config\u001b[39m=\u001b[39mread_options\u001b[39m.\u001b[39mget(\u001b[39m\"\u001b[39m\u001b[39mhive_config\u001b[39m\u001b[39m\"\u001b[39m) \u001b[39mif\u001b[39;00m read_options \u001b[39melse\u001b[39;00m \u001b[39mNone\u001b[39;00m,\n\u001b[1;32m    145\u001b[0m             arrow_flight_config\u001b[39m=\u001b[39mread_options\u001b[39m.\u001b[39mget(\u001b[39m\"\u001b[39m\u001b[39marrow_flight_config\u001b[39m\u001b[39m\"\u001b[39m, {})\n\u001b[1;32m    146\u001b[0m             \u001b[39mif\u001b[39;00m read_options\n\u001b[1;32m    147\u001b[0m             \u001b[39melse\u001b[39;00m {},\n\u001b[1;32m    148\u001b[0m         )\n\u001b[1;32m    149\u001b[0m     \u001b[39melse\u001b[39;00m:\n\u001b[1;32m    150\u001b[0m         \u001b[39mreturn\u001b[39;00m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_jdbc(\n\u001b[1;32m    151\u001b[0m             sql_query, online_conn, dataframe_type, read_options, schema\n\u001b[1;32m    152\u001b[0m         )\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/engine/python.py:180\u001b[0m, in \u001b[0;36mEngine._sql_offline\u001b[0;34m(self, sql_query, feature_store, dataframe_type, schema, hive_config, arrow_flight_config)\u001b[0m\n\u001b[1;32m    178\u001b[0m         \u001b[39mwith\u001b[39;00m warnings\u001b[39m.\u001b[39mcatch_warnings():\n\u001b[1;32m    179\u001b[0m             warnings\u001b[39m.\u001b[39msimplefilter(\u001b[39m\"\u001b[39m\u001b[39mignore\u001b[39m\u001b[39m\"\u001b[39m, \u001b[39mUserWarning\u001b[39;00m)\n\u001b[0;32m--> 180\u001b[0m             result_df \u001b[39m=\u001b[39m util\u001b[39m.\u001b[39mrun_with_loading_animation(\n\u001b[1;32m    181\u001b[0m                 \u001b[39m\"\u001b[39m\u001b[39mReading data from Hopsworks, using Hive\u001b[39m\u001b[39m\"\u001b[39m,\n\u001b[1;32m    182\u001b[0m                 pd\u001b[39m.\u001b[39mread_sql,\n\u001b[1;32m    183\u001b[0m                 sql_query,\n\u001b[1;32m    184\u001b[0m                 hive_conn,\n\u001b[1;32m    185\u001b[0m             )\n\u001b[1;32m    187\u001b[0m \u001b[39mif\u001b[39;00m schema:\n\u001b[1;32m    188\u001b[0m     result_df \u001b[39m=\u001b[39m Engine\u001b[39m.\u001b[39mcast_columns(result_df, schema)\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/util.py:427\u001b[0m, in \u001b[0;36mrun_with_loading_animation\u001b[0;34m(message, func, *args, **kwargs)\u001b[0m\n\u001b[1;32m    424\u001b[0m end \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m\n\u001b[1;32m    426\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[0;32m--> 427\u001b[0m     result \u001b[39m=\u001b[39m func(\u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n\u001b[1;32m    428\u001b[0m     end \u001b[39m=\u001b[39m time\u001b[39m.\u001b[39mtime()\n\u001b[1;32m    429\u001b[0m     \u001b[39mreturn\u001b[39;00m result\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/pandas/io/sql.py:564\u001b[0m, in \u001b[0;36mread_sql\u001b[0;34m(sql, con, index_col, coerce_float, params, parse_dates, columns, chunksize)\u001b[0m\n\u001b[1;32m    561\u001b[0m pandas_sql \u001b[39m=\u001b[39m pandasSQL_builder(con)\n\u001b[1;32m    563\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39misinstance\u001b[39m(pandas_sql, SQLiteDatabase):\n\u001b[0;32m--> 564\u001b[0m     \u001b[39mreturn\u001b[39;00m pandas_sql\u001b[39m.\u001b[39mread_query(\n\u001b[1;32m    565\u001b[0m         sql,\n\u001b[1;32m    566\u001b[0m         index_col\u001b[39m=\u001b[39mindex_col,\n\u001b[1;32m    567\u001b[0m         params\u001b[39m=\u001b[39mparams,\n\u001b[1;32m    568\u001b[0m         coerce_float\u001b[39m=\u001b[39mcoerce_float,\n\u001b[1;32m    569\u001b[0m         parse_dates\u001b[39m=\u001b[39mparse_dates,\n\u001b[1;32m    570\u001b[0m         chunksize\u001b[39m=\u001b[39mchunksize,\n\u001b[1;32m    571\u001b[0m     )\n\u001b[1;32m    573\u001b[0m \u001b[39mtry\u001b[39;00m:\n\u001b[1;32m    574\u001b[0m     _is_table_name \u001b[39m=\u001b[39m pandas_sql\u001b[39m.\u001b[39mhas_table(sql)\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/pandas/io/sql.py:2078\u001b[0m, in \u001b[0;36mSQLiteDatabase.read_query\u001b[0;34m(self, sql, index_col, coerce_float, params, parse_dates, chunksize, dtype)\u001b[0m\n\u001b[1;32m   2066\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mread_query\u001b[39m(\n\u001b[1;32m   2067\u001b[0m     \u001b[39mself\u001b[39m,\n\u001b[1;32m   2068\u001b[0m     sql,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   2074\u001b[0m     dtype: DtypeArg \u001b[39m|\u001b[39m \u001b[39mNone\u001b[39;00m \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m,\n\u001b[1;32m   2075\u001b[0m ) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m DataFrame \u001b[39m|\u001b[39m Iterator[DataFrame]:\n\u001b[1;32m   2077\u001b[0m     args \u001b[39m=\u001b[39m _convert_params(sql, params)\n\u001b[0;32m-> 2078\u001b[0m     cursor \u001b[39m=\u001b[39m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mexecute(\u001b[39m*\u001b[39margs)\n\u001b[1;32m   2079\u001b[0m     columns \u001b[39m=\u001b[39m [col_desc[\u001b[39m0\u001b[39m] \u001b[39mfor\u001b[39;00m col_desc \u001b[39min\u001b[39;00m cursor\u001b[39m.\u001b[39mdescription]\n\u001b[1;32m   2081\u001b[0m     \u001b[39mif\u001b[39;00m chunksize \u001b[39mis\u001b[39;00m \u001b[39mnot\u001b[39;00m \u001b[39mNone\u001b[39;00m:\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/pandas/io/sql.py:2027\u001b[0m, in \u001b[0;36mSQLiteDatabase.execute\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   2023\u001b[0m \u001b[39mexcept\u001b[39;00m \u001b[39mException\u001b[39;00m \u001b[39mas\u001b[39;00m inner_exc:  \u001b[39m# pragma: no cover\u001b[39;00m\n\u001b[1;32m   2024\u001b[0m     ex \u001b[39m=\u001b[39m DatabaseError(\n\u001b[1;32m   2025\u001b[0m         \u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mExecution failed on sql: \u001b[39m\u001b[39m{\u001b[39;00margs[\u001b[39m0\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m\\n\u001b[39;00m\u001b[39m{\u001b[39;00mexc\u001b[39m}\u001b[39;00m\u001b[39m\\n\u001b[39;00m\u001b[39munable to rollback\u001b[39m\u001b[39m\"\u001b[39m\n\u001b[1;32m   2026\u001b[0m     )\n\u001b[0;32m-> 2027\u001b[0m     \u001b[39mraise\u001b[39;00m ex \u001b[39mfrom\u001b[39;00m \u001b[39minner_exc\u001b[39;00m\n\u001b[1;32m   2029\u001b[0m ex \u001b[39m=\u001b[39m DatabaseError(\u001b[39mf\u001b[39m\u001b[39m\"\u001b[39m\u001b[39mExecution failed on sql \u001b[39m\u001b[39m'\u001b[39m\u001b[39m{\u001b[39;00margs[\u001b[39m0\u001b[39m]\u001b[39m}\u001b[39;00m\u001b[39m'\u001b[39m\u001b[39m: \u001b[39m\u001b[39m{\u001b[39;00mexc\u001b[39m}\u001b[39;00m\u001b[39m\"\u001b[39m)\n\u001b[1;32m   2030\u001b[0m \u001b[39mraise\u001b[39;00m ex \u001b[39mfrom\u001b[39;00m \u001b[39mexc\u001b[39;00m\n",
+      "\u001b[0;31mDatabaseError\u001b[0m: Execution failed on sql: WITH right_fg0 AS (SELECT *\nFROM (SELECT `fg1`.`date` `date`, `fg1`.`open` `open`, `fg1`.`ticker` `ticker`, `fg1`.`ticker` `join_pk_ticker`, `fg1`.`date` `join_evt_date`, `fg0`.`date` `date`, `fg0`.`sentiment` `sentiment`, RANK() OVER (PARTITION BY `fg1`.`ticker`, `fg1`.`date` ORDER BY `fg0`.`date` DESC) pit_rank_hopsworks\nFROM `mtzeve_featurestore`.`tesla_stock_1` `fg1`\nINNER JOIN `mtzeve_featurestore`.`news_sentiment_updated_1` `fg0` ON `fg1`.`ticker` = `fg0`.`ticker` AND `fg1`.`date` >= `fg0`.`date`\nWHERE `fg1`.`date` >= TIMESTAMP '1970-01-01 00:16:40.000' AND `fg1`.`date` < TIMESTAMP '2024-05-06 10:27:51.000') NA\nWHERE `pit_rank_hopsworks` = 1) (SELECT `right_fg0`.`date` `date`, `right_fg0`.`open` `open`, `right_fg0`.`ticker` `ticker`, `right_fg0`.`date` `date`, `right_fg0`.`sentiment` `sentiment`\nFROM right_fg0)\nTExecuteStatementResp(status=TStatus(statusCode=3, infoMessages=['*org.apache.hive.service.cli.HiveSQLException:Error while compiling statement: FAILED: SemanticException [Error 10007]: Ambiguous column reference date in na:28:27', 'org.apache.hive.service.cli.operation.Operation:toSQLException:Operation.java:343', 'org.apache.hive.service.cli.operation.SQLOperation:prepare:SQLOperation.java:203', 'org.apache.hive.service.cli.operation.SQLOperation:runInternal:SQLOperation.java:266', 'org.apache.hive.service.cli.operation.Operation:run:Operation.java:255', 'org.apache.hive.service.cli.session.HiveSessionImpl:executeStatementInternal:HiveSessionImpl.java:541', 'org.apache.hive.service.cli.session.HiveSessionImpl:executeStatement:HiveSessionImpl.java:516', 'sun.reflect.GeneratedMethodAccessor216:invoke::-1', 'sun.reflect.DelegatingMethodAccessorImpl:invoke:DelegatingMethodAccessorImpl.java:43', 'java.lang.reflect.Method:invoke:Method.java:498', 'org.apache.hive.service.cli.session.HiveSessionProxy:invoke:HiveSessionProxy.java:78', 'org.apache.hive.service.cli.session.HiveSessionProxy:access$000:HiveSessionProxy.java:36', 'org.apache.hive.service.cli.session.HiveSessionProxy$1:run:HiveSessionProxy.java:63', 'java.security.AccessController:doPrivileged:AccessController.java:-2', 'javax.security.auth.Subject:doAs:Subject.java:422', 'org.apache.hadoop.security.UserGroupInformation:doAs:UserGroupInformation.java:1821', 'org.apache.hive.service.cli.session.HiveSessionProxy:invoke:HiveSessionProxy.java:59', 'com.sun.proxy.$Proxy53:executeStatement::-1', 'org.apache.hive.service.cli.CLIService:executeStatement:CLIService.java:281', 'org.apache.hive.service.cli.thrift.ThriftCLIService:ExecuteStatement:ThriftCLIService.java:712', 'org.apache.hive.service.rpc.thrift.TCLIService$Processor$ExecuteStatement:getResult:TCLIService.java:1557', 'org.apache.hive.service.rpc.thrift.TCLIService$Processor$ExecuteStatement:getResult:TCLIService.java:1542', 'org.apache.thrift.ProcessFunction:process:ProcessFunction.java:39', 'org.apache.thrift.TBaseProcessor:process:TBaseProcessor.java:39', 'org.apache.hive.service.auth.TSetIpAddressProcessor:process:TSetIpAddressProcessor.java:56', 'org.apache.thrift.server.TThreadPoolServer$WorkerProcess:run:TThreadPoolServer.java:286', 'java.util.concurrent.ThreadPoolExecutor:runWorker:ThreadPoolExecutor.java:1149', 'java.util.concurrent.ThreadPoolExecutor$Worker:run:ThreadPoolExecutor.java:624', 'java.lang.Thread:run:Thread.java:750', '*org.apache.hadoop.hive.ql.parse.SemanticException:Ambiguous column reference date in na:44:17', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:rewriteRRForSubQ:SemanticAnalyzer.java:11359', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11338', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11188', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11215', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11188', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11215', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genPlan:SemanticAnalyzer.java:11201', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:genOPTree:SemanticAnalyzer.java:11987', 'org.apache.hadoop.hive.ql.parse.CalcitePlanner:genOPTree:CalcitePlanner.java:597', 'org.apache.hadoop.hive.ql.parse.SemanticAnalyzer:analyzeInternal:SemanticAnalyzer.java:12066', 'org.apache.hadoop.hive.ql.parse.CalcitePlanner:analyzeInternal:CalcitePlanner.java:334', 'org.apache.hadoop.hive.ql.parse.BaseSemanticAnalyzer:analyze:BaseSemanticAnalyzer.java:285', 'org.apache.hadoop.hive.ql.Driver:compile:Driver.java:643', 'org.apache.hadoop.hive.ql.Driver:compileInternal:Driver.java:1683', 'org.apache.hadoop.hive.ql.Driver:compileAndRespond:Driver.java:1630', 'org.apache.hadoop.hive.ql.Driver:compileAndRespond:Driver.java:1625', 'org.apache.hadoop.hive.ql.reexec.ReExecDriver:compileAndRespond:ReExecDriver.java:126', 'org.apache.hive.service.cli.operation.SQLOperation:prepare:SQLOperation.java:201'], sqlState='42000', errorCode=10007, errorMessage='Error while compiling statement: FAILED: SemanticException [Error 10007]: Ambiguous column reference date in na'), operationHandle=None)\nunable to rollback"
+     ]
+    }
+   ],
+   "source": [
+    "print('Fetching feature view from hopsworks...')\n",
+    "api_key = os.environ.get('hopsworks_api')\n",
+    "project = hopsworks.login(api_key_value=api_key)\n",
+    "fs = project.get_feature_store()\n",
+    "\n",
+    "# Get feature view \n",
+    "fv = fs.get_feature_view(\n",
+    "    name = 'tesla_stocks_fv',\n",
+    "    version = 1\n",
+    ")\n",
+    "# Get dataframe of training data from feature view\n",
+    "df, _ = fv.training_data(read_options={\"use_hive\": True})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ExternalClientError",
+     "evalue": "host cannot be of type NoneType, host is a non-optional argument to connect to hopsworks from an external environment.",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mExternalClientError\u001b[0m                       Traceback (most recent call last)",
+      "\u001b[1;32m/Users/manos/Documents/BDS/Mlops_2version/MLops_mod/training_pipeline.ipynb Cell 2\u001b[0m line \u001b[0;36m7\n\u001b[1;32m      <a href='vscode-notebook-cell:/Users/manos/Documents/BDS/Mlops_2version/MLops_mod/training_pipeline.ipynb#W3sZmlsZQ%3D%3D?line=2'>3</a>\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mdotenv\u001b[39;00m \u001b[39mimport\u001b[39;00m load_dotenv\n\u001b[1;32m      <a href='vscode-notebook-cell:/Users/manos/Documents/BDS/Mlops_2version/MLops_mod/training_pipeline.ipynb#W3sZmlsZQ%3D%3D?line=4'>5</a>\u001b[0m load_dotenv\n\u001b[0;32m----> <a href='vscode-notebook-cell:/Users/manos/Documents/BDS/Mlops_2version/MLops_mod/training_pipeline.ipynb#W3sZmlsZQ%3D%3D?line=6'>7</a>\u001b[0m connection \u001b[39m=\u001b[39m hsfs\u001b[39m.\u001b[39mconnection()\n\u001b[1;32m      <a href='vscode-notebook-cell:/Users/manos/Documents/BDS/Mlops_2version/MLops_mod/training_pipeline.ipynb#W3sZmlsZQ%3D%3D?line=7'>8</a>\u001b[0m api_key \u001b[39m=\u001b[39m os\u001b[39m.\u001b[39menviron\u001b[39m.\u001b[39mget(\u001b[39m'\u001b[39m\u001b[39mhopsworks_api\u001b[39m\u001b[39m'\u001b[39m)\n\u001b[1;32m      <a href='vscode-notebook-cell:/Users/manos/Documents/BDS/Mlops_2version/MLops_mod/training_pipeline.ipynb#W3sZmlsZQ%3D%3D?line=8'>9</a>\u001b[0m project \u001b[39m=\u001b[39m hopsworks\u001b[39m.\u001b[39mlogin(api_key_value\u001b[39m=\u001b[39mapi_key)\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/connection.py:303\u001b[0m, in \u001b[0;36mConnection.connection\u001b[0;34m(cls, host, port, project, engine, region_name, secrets_store, hostname_verification, trust_store_path, cert_folder, api_key_file, api_key_value)\u001b[0m\n\u001b[1;32m    287\u001b[0m \u001b[39m@classmethod\u001b[39m\n\u001b[1;32m    288\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mconnection\u001b[39m(\n\u001b[1;32m    289\u001b[0m     \u001b[39mcls\u001b[39m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    300\u001b[0m     api_key_value: \u001b[39mstr\u001b[39m \u001b[39m=\u001b[39m \u001b[39mNone\u001b[39;00m,\n\u001b[1;32m    301\u001b[0m ):\n\u001b[1;32m    302\u001b[0m \u001b[39m    \u001b[39m\u001b[39m\"\"\"Connection factory method, accessible through `hsfs.connection()`.\"\"\"\u001b[39;00m\n\u001b[0;32m--> 303\u001b[0m     \u001b[39mreturn\u001b[39;00m \u001b[39mcls\u001b[39m(\n\u001b[1;32m    304\u001b[0m         host,\n\u001b[1;32m    305\u001b[0m         port,\n\u001b[1;32m    306\u001b[0m         project,\n\u001b[1;32m    307\u001b[0m         engine,\n\u001b[1;32m    308\u001b[0m         region_name,\n\u001b[1;32m    309\u001b[0m         secrets_store,\n\u001b[1;32m    310\u001b[0m         hostname_verification,\n\u001b[1;32m    311\u001b[0m         trust_store_path,\n\u001b[1;32m    312\u001b[0m         cert_folder,\n\u001b[1;32m    313\u001b[0m         api_key_file,\n\u001b[1;32m    314\u001b[0m         api_key_value,\n\u001b[1;32m    315\u001b[0m     )\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/connection.py:154\u001b[0m, in \u001b[0;36mConnection.__init__\u001b[0;34m(self, host, port, project, engine, region_name, secrets_store, hostname_verification, trust_store_path, cert_folder, api_key_file, api_key_value)\u001b[0m\n\u001b[1;32m    151\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_api_key_value \u001b[39m=\u001b[39m api_key_value\n\u001b[1;32m    152\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_connected \u001b[39m=\u001b[39m \u001b[39mFalse\u001b[39;00m\n\u001b[0;32m--> 154\u001b[0m \u001b[39mself\u001b[39m\u001b[39m.\u001b[39mconnect()\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/decorators.py:25\u001b[0m, in \u001b[0;36mnot_connected.<locals>.if_not_connected\u001b[0;34m(inst, *args, **kwargs)\u001b[0m\n\u001b[1;32m     23\u001b[0m \u001b[39mif\u001b[39;00m inst\u001b[39m.\u001b[39m_connected:\n\u001b[1;32m     24\u001b[0m     \u001b[39mraise\u001b[39;00m HopsworksConnectionError\n\u001b[0;32m---> 25\u001b[0m \u001b[39mreturn\u001b[39;00m fn(inst, \u001b[39m*\u001b[39margs, \u001b[39m*\u001b[39m\u001b[39m*\u001b[39mkwargs)\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/connection.py:233\u001b[0m, in \u001b[0;36mConnection.connect\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    231\u001b[0m \u001b[39m# init client\u001b[39;00m\n\u001b[1;32m    232\u001b[0m \u001b[39mif\u001b[39;00m client\u001b[39m.\u001b[39mbase\u001b[39m.\u001b[39mClient\u001b[39m.\u001b[39mREST_ENDPOINT \u001b[39mnot\u001b[39;00m \u001b[39min\u001b[39;00m os\u001b[39m.\u001b[39menviron:\n\u001b[0;32m--> 233\u001b[0m     client\u001b[39m.\u001b[39minit(\n\u001b[1;32m    234\u001b[0m         \u001b[39m\"\u001b[39m\u001b[39mexternal\u001b[39m\u001b[39m\"\u001b[39m,\n\u001b[1;32m    235\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_host,\n\u001b[1;32m    236\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_port,\n\u001b[1;32m    237\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_project,\n\u001b[1;32m    238\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_engine,\n\u001b[1;32m    239\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_region_name,\n\u001b[1;32m    240\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_secrets_store,\n\u001b[1;32m    241\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_hostname_verification,\n\u001b[1;32m    242\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_trust_store_path,\n\u001b[1;32m    243\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_cert_folder,\n\u001b[1;32m    244\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_api_key_file,\n\u001b[1;32m    245\u001b[0m         \u001b[39mself\u001b[39m\u001b[39m.\u001b[39m_api_key_value,\n\u001b[1;32m    246\u001b[0m     )\n\u001b[1;32m    247\u001b[0m \u001b[39melse\u001b[39;00m:\n\u001b[1;32m    248\u001b[0m     client\u001b[39m.\u001b[39minit(\u001b[39m\"\u001b[39m\u001b[39mhopsworks\u001b[39m\u001b[39m\"\u001b[39m)\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/client/__init__.py:41\u001b[0m, in \u001b[0;36minit\u001b[0;34m(client_type, host, port, project, engine, region_name, secrets_store, hostname_verification, trust_store_path, cert_folder, api_key_file, api_key_value)\u001b[0m\n\u001b[1;32m     39\u001b[0m     _client \u001b[39m=\u001b[39m hopsworks\u001b[39m.\u001b[39mClient()\n\u001b[1;32m     40\u001b[0m \u001b[39melif\u001b[39;00m client_type \u001b[39m==\u001b[39m \u001b[39m\"\u001b[39m\u001b[39mexternal\u001b[39m\u001b[39m\"\u001b[39m:\n\u001b[0;32m---> 41\u001b[0m     _client \u001b[39m=\u001b[39m external\u001b[39m.\u001b[39mClient(\n\u001b[1;32m     42\u001b[0m         host,\n\u001b[1;32m     43\u001b[0m         port,\n\u001b[1;32m     44\u001b[0m         project,\n\u001b[1;32m     45\u001b[0m         engine,\n\u001b[1;32m     46\u001b[0m         region_name,\n\u001b[1;32m     47\u001b[0m         secrets_store,\n\u001b[1;32m     48\u001b[0m         hostname_verification,\n\u001b[1;32m     49\u001b[0m         trust_store_path,\n\u001b[1;32m     50\u001b[0m         cert_folder,\n\u001b[1;32m     51\u001b[0m         api_key_file,\n\u001b[1;32m     52\u001b[0m         api_key_value,\n\u001b[1;32m     53\u001b[0m     )\n",
+      "File \u001b[0;32m/Applications/anaconda3/lib/python3.11/site-packages/hsfs/client/external.py:54\u001b[0m, in \u001b[0;36mClient.__init__\u001b[0;34m(self, host, port, project, engine, region_name, secrets_store, hostname_verification, trust_store_path, cert_folder, api_key_file, api_key_value)\u001b[0m\n\u001b[1;32m     52\u001b[0m \u001b[39m\u001b[39m\u001b[39m\"\"\"Initializes a client in an external environment such as AWS Sagemaker.\"\"\"\u001b[39;00m\n\u001b[1;32m     53\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m host:\n\u001b[0;32m---> 54\u001b[0m     \u001b[39mraise\u001b[39;00m exceptions\u001b[39m.\u001b[39mExternalClientError(\u001b[39m\"\u001b[39m\u001b[39mhost\u001b[39m\u001b[39m\"\u001b[39m)\n\u001b[1;32m     55\u001b[0m \u001b[39mif\u001b[39;00m \u001b[39mnot\u001b[39;00m project:\n\u001b[1;32m     56\u001b[0m     \u001b[39mraise\u001b[39;00m exceptions\u001b[39m.\u001b[39mExternalClientError(\u001b[39m\"\u001b[39m\u001b[39mproject\u001b[39m\u001b[39m\"\u001b[39m)\n",
+      "\u001b[0;31mExternalClientError\u001b[0m: host cannot be of type NoneType, host is a non-optional argument to connect to hopsworks from an external environment."
+     ]
+    }
+   ],
+   "source": [
+    "import hsfs\n",
+    "import os \n",
+    "from dotenv import load_dotenv\n",
+    "\n",
+    "load_dotenv\n",
+    "\n",
+    "api_key = os.environ.get('hopsworks_api')\n",
+    "project = hopsworks.login(api_key_value=api_key)\n",
+    "\n",
+    "\n",
+    "\n",
+    "fv = fs.get_feature_view('tesla_stocks_fv', version=1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Fetching feature view from hopsworks...\n",
+      "Connection closed.\n",
+      "Connected. Call `.close()` to terminate connection gracefully.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Logged in to project, explore it here https://c.app.hopsworks.ai:443/p/549016\n",
+      "Connected. Call `.close()` to terminate connection gracefully.\n"
+     ]
+    }
+   ],
+   "source": [
+    "print('Fetching feature view from hopsworks...')\n",
+    "project = hopsworks.login()\n",
+    "fs = project.get_feature_store()\n",
+    "\n",
+    "# Get feature view \n",
+    "fv = fs.get_feature_view(\n",
+    "        name = 'tesla_stocks_fv',\n",
+    "        version = 1\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Failed to load data: Metadata operation error: (url: https://c.app.hopsworks.ai/hopsworks-api/api/project/549016/dataset/Projects%2Fmtzeve%2Fmtzeve_Training_Datasets%2Ftesla_stocks_fv_1_1%2Ftesla_stocks_fv_1). Server response: \n",
+      "HTTP code: 400, HTTP reason: Bad Request, body: b'{\"errorCode\":110018,\"errorMsg\":\"Path not found\"}', error code: 110018, error msg: Path not found, user msg: \n"
+     ]
+    }
+   ],
+   "source": [
+    "# Assuming 'fv' is your FeatureView object and you've verified the version number.\n",
+    "# Here, you will use the method to retrieve training data.\n",
+    "\n",
+    "try:\n",
+    "    df_train, _ = fv.get_training_data(training_dataset_version=1)\n",
+    "    print(df_train.head())\n",
+    "except Exception as e:\n",
+    "    print(\"Failed to load data:\", e)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "base",
+   "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": "3.11.4"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}