ML/AutoML: Reworked connection string for easier usage

topic/machine-learning/automl/automl_timeseries_forecasting_with_pycaret.ipynb

@@ -120,20 +120,48 @@
     "sign up for a free account at https://console.cratedb.cloud and \n",
     "[deploy a cluster].\n",
     "\n",
+    "[deploy a cluster]: https://cratedb.com/docs/cloud/en/latest/tutorials/deploy/stripe.html#deploy-cluster\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
     "To populate your environment with corresponding database access credentials,\n",
     "create an `.env` file with the following content:\n",
     "\n",
     "```env\n",
-    "CRATE_HOST=<your-crate-host> # set this to localhost if you're running crate locally\n",
-    "CRATE_USER=<your-crate-user> # set this to crate if you're running crate locally\n",
-    "CRATE_PASSWORD=<your-crate-password> # set this to \"\" if you're running crate locally\n",
-    "CRATE_SSL=true # set this to false if you're running crate locally\n",
+    "# use this string for a connection to CrateDB Cloud\n",
+    "CONNECTION_STRING=crate://username:password@hostname/?ssl=true \n",
+    "\n",
+    "# use this string for a local connection to CrateDB\n",
+    "# CONNECTION_STRING=crate://crate@localhost/?ssl=false \n",
     "```\n",
     "\n",
     "You can find your CrateDB credentials in the [CrateDB Cloud Console].\n",
     "\n",
-    "[CrateDB Cloud Console]: https://cratedb.com/docs/cloud/en/latest/reference/overview.html#cluster\n",
-    "[deploy a cluster]: https://cratedb.com/docs/cloud/en/latest/tutorials/deploy/stripe.html#deploy-cluster\n"
+    "[CrateDB Cloud Console]: https://cratedb.com/docs/cloud/en/latest/reference/overview.html#cluster"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "# For CrateDB Cloud, use:\n",
+    "CONNECTION_STRING = os.environ.get(\n",
+    "    \"CRATEDB_CONNECTION_STRING\",\n",
+    "    \"crate://username:password@hostname/?ssl=true\",\n",
+    ")\n",
+    "\n",
+    "# For an self-deployed CrateDB, e.g. via Docker, please use:\n",
+    "# CONNECTION_STRING = os.environ.get(\n",
+    "#     \"CRATEDB_CONNECTION_STRING\",\n",
+    "#     \"crate://crate@localhost/?ssl=false\",\n",
+    "# )"
    ]
   },
   {
@@ -203,8 +231,7 @@
     "data[\"date\"] = pd.to_datetime(data[\"date\"])\n",
     "\n",
     "# Insert the data into CrateDB\n",
-    "dburi = f\"crate://{os.environ['CRATE_USER']}:{os.environ['CRATE_PASSWORD']}@{os.environ['CRATE_HOST']}:4200?ssl={os.environ['CRATE_SSL']}\"\n",
-    "engine = sa.create_engine(dburi, echo=os.environ.get(\"DEBUG\"))\n",
+    "engine = sa.create_engine(CONNECTION_STRING, echo=os.environ.get(\"DEBUG\"))\n",
     "\n",
     "with engine.connect() as conn:\n",
     "    data.to_sql(\n",
@@ -253,7 +280,7 @@
     "data[\"month\"] = pd.to_datetime(data['month'], unit='ms')\n",
     "\n",
     "# We set the MLFLOW_TRACKING_URI to our CrateDB instance. We'll see later why\n",
-    "os.environ[\"MLFLOW_TRACKING_URI\"] = f\"{dburi}&schema=mlflow\""
+    "os.environ[\"MLFLOW_TRACKING_URI\"] = f\"{CONNECTION_STRING}&schema=mlflow\""
    ]
   },
   {
@@ -1277,28 +1304,28 @@
      "output_type": "display_data"
     },
     {
-     "name": "stdout",
      "metadata": {
       "nbreg": {
        "diff_ignore": [
         "/outputs"
        ]
       }
      },
+     "name": "stdout",
      "output_type": "stream",
      "text": [
       "Fitting 3 folds for each of 10 candidates, totalling 30 fits\n"
      ]
     },
     {
-     "name": "stderr",
      "metadata": {
       "nbreg": {
        "diff_ignore": [
         "/outputs"
        ]
       }
      },
+     "name": "stderr",
      "output_type": "stream",
      "text": [
       "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 24 concurrent workers.\n",
@@ -1433,28 +1460,28 @@
      "output_type": "display_data"
     },
     {
-     "name": "stdout",
      "metadata": {
       "nbreg": {
        "diff_ignore": [
         "/outputs"
        ]
       }
      },
+     "name": "stdout",
      "output_type": "stream",
      "text": [
       "Fitting 3 folds for each of 10 candidates, totalling 30 fits\n"
      ]
     },
     {
-     "name": "stderr",
      "metadata": {
       "nbreg": {
        "diff_ignore": [
         "/outputs"
        ]
       }
      },
+     "name": "stderr",
      "output_type": "stream",
      "text": [
       "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 24 concurrent workers.\n",
@@ -1583,28 +1610,28 @@
      "output_type": "display_data"
     },
     {
-     "name": "stdout",
-     "output_type": "stream",
      "metadata": {
       "nbreg": {
        "diff_ignore": [
         "/outputs"
        ]
       }
      },
+     "name": "stdout",
+     "output_type": "stream",
      "text": [
       "Fitting 3 folds for each of 10 candidates, totalling 30 fits\n"
      ]
     },
     {
-     "name": "stderr",
      "metadata": {
       "nbreg": {
        "diff_ignore": [
         "/outputs"
        ]
       }
      },
+     "name": "stderr",
      "output_type": "stream",
      "text": [
       "[Parallel(n_jobs=-1)]: Using backend LokyBackend with 24 concurrent workers.\n",
@@ -2086,7 +2113,7 @@
    "source": [
     "os.environ[\n",
     "    \"MLFLOW_TRACKING_URI\"\n",
-    "] = f\"crate://{os.environ['CRATE_USER']}:{os.environ['CRATE_PASSWORD']}@{os.environ['CRATE_HOST']}:4200?ssl={os.environ['CRATE_SSL']}&schema=mlflow\""
+    "] = f\"{CONNECTION_STRING}&schema=mlflow\""
    ]
   },
   {
@@ -2182,7 +2209,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "crate",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
    "name": "python3"
   },
@@ -2196,7 +2223,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.0"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,