#313 enabled fix differing versions of dependency scikit learn

doc/changes/changes_2.1.0.md

@@ -27,6 +27,7 @@ Version: 2.1.0
 ## Bug Fixes
 
 * #303: Fixed AWS Codebuild
+* #313: Fixed differing versions of dependency `scikit-learn`
 
 ## Documentation
 

exasol/ds/sandbox/runtime/ansible/roles/jupyter/files/notebook/sklearn/sklearn_fix_version.ipynb

@@ -0,0 +1,130 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "289d2a8c-953d-46e5-8c73-ad810c29b20f",
+   "metadata": {},
+   "source": [
+    "# Fix the Version of Python Library Scikit-learn\n",
+    "\n",
+    "This notebook ensures the AI-Lab using the same version of python library `scikit-learn` as the one used by the <a href=\"https://docs.exasol.com/db/latest/database_concepts/udf_scripts/adding_new_packages_script_languages.htm\" target=\"_blank\" rel=\"noopener\">Script Language Container (SLC)</a> inside Exasol database.\n",
+    "\n",
+    "## Rationale\n",
+    "\n",
+    "Using identical versions is required when transferring the sklearn model from the AI-Lab to the database SLC.\n",
+    "\n",
+    "The AI-Lab serializes the sklearn model and uploads it into the database SLC. The SLC can only _deserialize_ the model if using the same version of the `scikit-learn` library. The specific version of the library used by the default SLC depends on the release version of the database and cannot be controlled by the AI-Lab. Running the following script will update the version of the library used in the AI-Lab, if required.\n",
+    "\n",
+    "## Open Secure Configuration Storage"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d86ca808-044e-4fbd-be30-5ba8324f501e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%run ../utils/access_store_ui.ipynb\n",
+    "display(get_access_store_ui('../'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "055ed302-69aa-426c-b5ec-861c63b82d33",
+   "metadata": {},
+   "source": [
+    "## Detect the Version of sklearn Used in the SLC\n",
+    "\n",
+    "The following cell creates a User Defined Function (UDF) called `detect_skikit_learn_version()` to be run in the SLC and then executes the UDF via an SQL statement.\n",
+    "\n",
+    "The UDF inquires and returns the version of sklearn installed in the SLC which is then stored in variable `slc_version`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "fa6c628f-853e-4850-8bab-46f7f645856e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import textwrap\n",
+    "import sklearn\n",
+    "from importlib import reload\n",
+    "from exasol.nb_connector.connections import open_pyexasol_connection\n",
+    "\n",
+    "# Create script to test the model\n",
+    "sql = textwrap.dedent(\"\"\"\n",
+    "CREATE OR REPLACE PYTHON3 SCALAR SCRIPT {schema!q}.detect_skikit_learn_version() RETURNS VARCHAR(100) AS\n",
+    "import sklearn\n",
+    "def run(ctx):\n",
+    "    return sklearn.__version__ \n",
+    "/\n",
+    "\"\"\")\n",
+    "\n",
+    "with open_pyexasol_connection(ai_lab_config, compression=True) as conn:\n",
+    "    query_params={'schema': ai_lab_config.db_schema}\n",
+    "    conn.execute(sql, query_params)\n",
+    "    result = conn.execute(\"select {schema!q}.detect_skikit_learn_version()\", query_params).fetchone()\n",
+    "    slc_version = result[0]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e4b0dc24-6e02-4305-8fa1-15f68afac360",
+   "metadata": {},
+   "source": [
+    "## Compare the Version and Update the AI-Lab if Required\n",
+    "\n",
+    "The next cell compares the version returned by the UDF with the version in the AI-Lab environment. If they differ, then the cell installs the UDF's version in the AI-Lab environment."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "50b88871-4c37-4cc1-ac85-841a22e98153",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "my_version = sklearn.__version__\n",
+    "\n",
+    "if slc_version == my_version:\n",
+    "    print(f\"AI-Lab scikit-learn version {my_version} is identical to that of the SLC.\\nNothing to do.\")\n",
+    "else:\n",
+    "    print(f\"AI-Lab scikit-learn version {my_version} differs from SLC.\\nInstalling version {slc_version} ...\")\n",
+    "    %pip install \"scikit_learn=={slc_version}\"\n",
+    "    sklearn = reload(sklearn)\n",
+    "    print(f\"Updated AI-Lab scikit-learn to version {sklearn.__version__}.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b0ea6891-d171-4841-a2d8-edf8ac252d86",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "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": "3.10.12"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

exasol/ds/sandbox/runtime/ansible/roles/jupyter/files/notebook/sklearn/sklearn_introduction.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "c2aa3433-eb40-495e-a80e-38ab0bee10cf",
+   "id": "c7b3a9b5-1b5f-4613-bd8d-6c14f00af33e",
    "metadata": {},
    "source": [
     "# Introduction\n",
@@ -16,9 +16,10 @@
     "## Prerequisites\n",
     "\n",
     "Before using this set of notebooks the following steps need to be completed:\n",
-    "1. [Configure the AI-Lab](../main_config.ipynb).\n",
-    "2. [Load the MAGIC Gamma Telescope data](../data/data_telescope.ipynb).\n",
-    "3. [Load the Abalone data](../data/data_abalone.ipynb).\n",
+    "1. [Configure the AI-Lab](../main_config.ipynb)\n",
+    "2. [Fix the Version of Python Library Scikit-learn](./sklearn_fix_version.ipynb)\n",
+    "3. [Load the MAGIC Gamma Telescope data](../data/data_telescope.ipynb)\n",
+    "4. [Load the Abalone data](../data/data_abalone.ipynb)\n",
     "\n",
     "## Content\n",
     "\n",
@@ -58,7 +59,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

exasol/ds/sandbox/runtime/ansible/roles/jupyter/files/notebook/sklearn/sklearn_train_telescope.ipynb

@@ -91,7 +91,7 @@
     "\n",
     "# Create and train the model.\n",
     "model = tree.DecisionTreeClassifier()\n",
-    "model.fit(X_train, y_train)\n",
+    "model.fit(X_train.values, y_train)\n",
     "\n",
     "print(f\"Training took: {stopwatch}\")"
    ]

test/notebooks/nbtest_sklearn.py

@@ -22,6 +22,7 @@ def test_regression(notebook_runner) -> None:
         os.chdir('./data')
         notebook_runner('data_abalone.ipynb')
         os.chdir('../sklearn')
+        notebook_runner('sklearn_fix_version.ipynb')
         notebook_runner('sklearn_predict_udf.ipynb')
         notebook_runner('sklearn_train_abalone.ipynb')
         notebook_runner('sklearn_predict_abalone.ipynb')
@@ -38,6 +39,7 @@ def test_classification(notebook_runner) -> None:
         os.chdir('./data')
         notebook_runner('data_telescope.ipynb')
         os.chdir('../sklearn')
+        notebook_runner('sklearn_fix_version.ipynb')
         notebook_runner('sklearn_predict_udf.ipynb')
         notebook_runner('sklearn_train_telescope.ipynb')
         notebook_runner('sklearn_predict_telescope.ipynb')