test: add test_cell_execution_widgets notebook

Author: shuoweil

packages/bigframes/notebooks/dataframes/test_cell_execution_widgets.ipynb

@@ -0,0 +1,106 @@
+{
+ "cells": [
+  {
+   "id": "300728e0",
+   "cell_type": "markdown",
+   "source": [
+    "# Testing TableWidget Cell Execution Count Propagation on Sorting\n",
+    "\n",
+    "This notebook verifies that if multiple `TableWidget`s are rendered across different notebook cells, triggering sorting in a widget preserves and uses the original cell's execution count for the new query, rather than the active cell's execution count."
+   ],
+   "metadata": {}
+  },
+  {
+   "id": "52dfd39a",
+   "cell_type": "code",
+   "source": [
+    "import bigframes\n",
+    "import bigframes.pandas as bpd\n",
+    "\n",
+    "bpd.options.bigquery.location = \"US\"\n",
+    "bpd.options.display.render_mode = \"anywidget\""
+   ],
+   "metadata": {},
+   "execution_count": null,
+   "outputs": []
+  },
+  {
+   "id": "d14207ff",
+   "cell_type": "markdown",
+   "source": [
+    "## Cell 1: Create and render the first DataFrame widget\n",
+    "\n",
+    "We will render a TableWidget in this cell. The captured cell execution count of this widget will be associated with this cell."
+   ],
+   "metadata": {}
+  },
+  {
+   "id": "2e74b4f4",
+   "cell_type": "code",
+   "source": [
+    "df1 = bpd.read_gbq(\"SELECT 10 AS id, 'alice' AS name UNION ALL SELECT 20 AS id, 'bob' AS name\")\n",
+    "df1"
+   ],
+   "metadata": {},
+   "execution_count": null,
+   "outputs": []
+  },
+  {
+   "id": "7228323e",
+   "cell_type": "markdown",
+   "source": [
+    "## Cell 2: Create and render the second DataFrame widget\n",
+    "\n",
+    "Now we render a second TableWidget. It should capture its own cell execution count."
+   ],
+   "metadata": {}
+  },
+  {
+   "id": "4fc5012f",
+   "cell_type": "code",
+   "source": [
+    "df2 = bpd.read_gbq(\"SELECT 100 AS val, 'x' AS label UNION ALL SELECT 200 AS val, 'y' AS label\")\n",
+    "df2"
+   ],
+   "metadata": {},
+   "execution_count": null,
+   "outputs": []
+  },
+  {
+   "id": "00f54ffe",
+   "cell_type": "markdown",
+   "source": [
+    "## Testing Instructions\n",
+    "\n",
+    "1. Sort the **first** widget (`df1`) by clicking on the `name` or `id` column header in the rendered table in Cell 1.\n",
+    "2. Run the code cell below to view the session's execution history.\n",
+    "3. Verify that the new query job triggered by sorting is associated with the cell execution count of Cell 1, rather than subsequent cells."
+   ],
+   "metadata": {}
+  },
+  {
+   "id": "7b313176",
+   "cell_type": "code",
+   "source": [
+    "# Show all execution history with their associated cell execution count\n",
+    "history = bigframes.execution_history(current_cell_only=False)\n",
+    "history.to_dataframe()[[\"job_id\", \"query\", \"cell_execution_count\"]]"
+   ],
+   "metadata": {},
+   "execution_count": null,
+   "outputs": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat_minor": 5,
+ "nbformat": 4
+}