Update nootebook

Author: j-fitas

notebooks/notebook-style-guide/notebook.ipynb

@@ -17,7 +17,7 @@
       ]
     },
     {
-      "id": "bd0ae268",
+      "id": "740cef75",
       "cell_type": "markdown",
       "metadata": {},
       "source": [
@@ -41,27 +41,26 @@
     {
       "attachments": {},
       "cell_type": "markdown",
-      "id": "bcb6e6a7",
       "metadata": {},
       "source": [
         "This Jupyter notebook will help you build your first Python UDF using Notebooks, registering it with your database and calling it as part of SQL query."
-      ]
+      ],
+      "id": "ffb6485e"
     },
     {
       "attachments": {},
       "cell_type": "markdown",
-      "id": "5776ded1",
       "metadata": {},
       "source": [
         "## Create some simple tables\n",
         "\n",
         "This setup establishes a basic relational structure to store some reviews for restaurants. Ensure you have selected a database."
-      ]
+      ],
+      "id": "e048901e"
     },
     {
       "cell_type": "code",
       "execution_count": 1,
-      "id": "2bbf6a44",
       "metadata": {},
       "outputs": [],
       "source": [
@@ -74,7 +73,8 @@
         "    store_name VARCHAR(255) NOT NULL,\n",
         "    review TEXT NOT NULL\n",
         ");"
-      ]
+      ],
+      "id": "9da8c576"
     },
     {
       "attachments": {},
@@ -103,13 +103,13 @@
     {
       "attachments": {},
       "cell_type": "markdown",
-      "id": "d58c8382",
       "metadata": {},
       "source": [
         "## Define Python UDF functions\n",
         "\n",
         "Next, we will be Python UDF function using the `@udf` annotation. We will be using the `VADER` model of `nltk` library to perform sentiment analysis on the review text."
-      ]
+      ],
+      "id": "9797abdb"
     },
     {
       "cell_type": "code",
@@ -124,7 +124,6 @@
     {
       "cell_type": "code",
       "execution_count": 4,
-      "id": "f3f3b047",
       "metadata": {},
       "outputs": [],
       "source": [
@@ -146,29 +145,30 @@
         "    )\n",
         "    print(\"sentiment:\" + sentiment)\n",
         "    return sentiment"
-      ]
+      ],
+      "id": "37e6d3e9"
     },
     {
       "attachments": {},
       "cell_type": "markdown",
-      "id": "40e2ad59",
       "metadata": {},
       "source": [
         "## Start the Python UDF server\n",
         "\n",
         "This will start the server as well as register all the functions annotated with `@udf` as external user defined functions on your selected database."
-      ]
+      ],
+      "id": "2f8feceb"
     },
     {
       "cell_type": "code",
       "execution_count": 5,
-      "id": "ed4b22cd",
       "metadata": {},
       "outputs": [],
       "source": [
         "import singlestoredb.apps as apps\n",
         "connection_info = await apps.run_udf_app(replace_existing=True)"
-      ]
+      ],
+      "id": "aace28b8"
     },
     {
       "attachments": {},
@@ -213,7 +213,6 @@
     {
       "attachments": {},
       "cell_type": "markdown",
-      "id": "4a825f0d",
       "metadata": {},
       "source": [
         "## Publish Python UDF\n",
@@ -226,10 +225,11 @@
         "```\n",
         "\n",
         "enriching your data exploration experience seamlessly!"
-      ]
+      ],
+      "id": "c94b087f"
     },
     {
-      "id": "b6c75678",
+      "id": "84415d55",
       "cell_type": "markdown",
       "metadata": {},
       "source": [

notebooks/python-udf-template/notebook.ipynb

@@ -7,7 +7,7 @@ description="""\
     Workspace Group.
     """
 icon="browser"
-difficulty="medium"
+difficulty="intermediate"
 tags=["starter", "notebooks", "fusion"]
 lesson_areas=[]
 destinations=["spaces"]