Add python UDF template for Free shared Tier users

authors/bharath-swamy.toml

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+name="Bharath Swamy"
+title="Product Team"
+image="singlestore"
+external=false

notebooks/python-udf-template/meta.toml

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+[meta]
+authors=["bharath-swamy"]
+title="Run your first Python UDF"
+description="""\
+    Learn how to connect to create and\
+    publish a python UDF and call it in SQL.
+    """
+icon="browser"
+difficulty="beginner"
+tags=["starter", "notebooks", "python"]
+lesson_areas=[]
+destinations=["spaces"]
+minimum_tier="free-shared"

notebooks/python-udf-template/notebook.ipynb

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+{
+  "cells": [
+    {
+      "id": "1ae3a481",
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "<div id=\"singlestore-header\" style=\"display: flex; background-color: rgba(235, 249, 245, 0.25); padding: 5px;\">\n",
+        "    <div id=\"icon-image\" style=\"width: 90px; height: 90px;\">\n",
+        "        <img width=\"100%\" height=\"100%\" src=\"https://raw.githubusercontent.com/singlestore-labs/spaces-notebooks/master/common/images/header-icons/browser.png\" />\n",
+        "    </div>\n",
+        "    <div id=\"text\" style=\"padding: 5px; margin-left: 10px;\">\n",
+        "        <div id=\"badge\" style=\"display: inline-block; background-color: rgba(0, 0, 0, 0.15); border-radius: 4px; padding: 4px 8px; align-items: center; margin-top: 6px; margin-bottom: -2px; font-size: 80%\">SingleStore Notebooks</div>\n",
+        "        <h1 style=\"font-weight: 500; margin: 8px 0 0 4px;\">Run your first Python UDF</h1>\n",
+        "    </div>\n",
+        "</div>"
+      ]
+    },
+    {
+      "id": "bd0ae268",
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "<div class=\"alert alert-block alert-warning\">\n",
+        "    <b class=\"fa fa-solid fa-exclamation-circle\"></b>\n",
+        "    <div>\n",
+        "        <p><b>Note</b></p>\n",
+        "        <p>This notebook can be run on a Free Starter Workspace. To create a Free Starter Workspace navigate to <tt>Start</tt> using the left nav. You can also use your existing Standard or Premium workspace with this Notebook.</p>\n",
+        "    </div>\n",
+        "</div>"
+      ]
+    },
+    {
+      "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."
+      ]
+    },
+    {
+      "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."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 1,
+      "id": "2bbf6a44",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "%%sql\n",
+        "DROP TABLE IF EXISTS reviews;\n",
+        "\n",
+        "CREATE TABLE IF NOT EXISTS\n",
+        "reviews (\n",
+        "    review_id INT PRIMARY KEY,\n",
+        "    store_name VARCHAR(255) NOT NULL,\n",
+        "    review TEXT NOT NULL\n",
+        ");"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "id": "3aace2e9",
+      "metadata": {},
+      "source": [
+        "## Insert sample data"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 2,
+      "id": "0a123cd7",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "%%sql INSERT into reviews (review_id, store_name, review) values\n",
+        "(\"1\", \"Single Pizza\", \"The staff were very respectful and made thoughtful suggestions. I will definitely go again. 10/10!\"),\n",
+        "(\"2\", \"Single Pizza\", \"The food was absolutely amazing and the service was fantastic!\"),\n",
+        "(\"3\", \"Single Pizza\", \"The experience was terrible. The food was cold and the waiter was rude.\"),\n",
+        "(\"4\", \"Single Pizza\", \"I loved the ambiance and the desserts were out of this world!\"),\n",
+        "(\"5\", \"Single Pizza\", \"Not worth the price. I expected more based on the reviews\");"
+      ]
+    },
+    {
+      "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."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 3,
+      "id": "1556ad3c",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "!pip install nltk"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 4,
+      "id": "f3f3b047",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "from singlestoredb.functions import udf\n",
+        "import nltk\n",
+        "from nltk.sentiment import SentimentIntensityAnalyzer\n",
+        "\n",
+        "nltk.download('vader_lexicon')\n",
+        "sia = SentimentIntensityAnalyzer()\n",
+        "\n",
+        "@udf\n",
+        "def review_sentiment(review: str) -> str:\n",
+        "    print(\"review:\" + review)\n",
+        "    scores = sia.polarity_scores(review)\n",
+        "    sentiment = (\n",
+        "        \"Positive\" if scores['compound'] > 0.05 else\n",
+        "        \"Negative\" if scores['compound'] < -0.05 else\n",
+        "        \"Neutral\"\n",
+        "    )\n",
+        "    print(\"sentiment:\" + sentiment)\n",
+        "    return sentiment"
+      ]
+    },
+    {
+      "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."
+      ]
+    },
+    {
+      "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)"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "id": "b53cd3d1",
+      "metadata": {},
+      "source": [
+        "## List all registered UDFs\n",
+        "\n",
+        "In interactive notebooks, the udf function will be suffixed with `_test` to differentiate it from the published version"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": 6,
+      "id": "6008982d",
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "%%sql\n",
+        "SHOW functions"
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "id": "58560b03",
+      "metadata": {},
+      "source": [
+        "## Call the UDF from SQL\n",
+        "\n",
+        "You will now be able to run queries like\n",
+        "\n",
+        "```\n",
+        "SELECT review_id, store_name, review, review_sentiment_test(review) from reviews order by review_id;\n",
+        "```\n",
+        "from the SQL editor or any other SQL client. Try it out by opening another notebook, selecting the current Database and running this query in a new cell."
+      ]
+    },
+    {
+      "attachments": {},
+      "cell_type": "markdown",
+      "id": "4a825f0d",
+      "metadata": {},
+      "source": [
+        "## Publish Python UDF\n",
+        "\n",
+        "After validating the Python UDF interactively, you can publish it and access it like\n",
+        "\n",
+        "```\n",
+        "%%sql\n",
+        "SELECT review_id, store_name, review, review_sentiment(review) from reviews order by review_id\n",
+        "```\n",
+        "\n",
+        "enriching your data exploration experience seamlessly!"
+      ]
+    },
+    {
+      "id": "b6c75678",
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "<div id=\"singlestore-footer\" style=\"background-color: rgba(194, 193, 199, 0.25); height:2px; margin-bottom:10px\"></div>\n",
+        "<div><img src=\"https://raw.githubusercontent.com/singlestore-labs/spaces-notebooks/master/common/images/singlestore-logo-grey.png\" style=\"padding: 0px; margin: 0px; height: 24px\"/></div>"
+      ]
+    }
+  ],
+  "metadata": {
+    "jupyterlab": {
+      "notebooks": {
+        "version_major": 6,
+        "version_minor": 4
+      }
+    },
+    "kernelspec": {
+      "display_name": "Python 3 (ipykernel)",
+      "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": "3.11.9"
+    }
+  },
+  "nbformat": 4,
+  "nbformat_minor": 5
+}