docs: update read_gbq_colab_callback notebook with new parameter name

Author: shuoweil

packages/bigframes/notebooks/dataframes/read_gbq_colab_callback.ipynb

@@ -0,0 +1,133 @@
+{
+ "cells": [
+  {
+   "id": "7fb27b941602401d91542211134fc71a",
+   "cell_type": "markdown",
+   "source": [
+    "# Testing Automatic Per-Cell Execution History Filtering in BigQuery DataFrames\n",
+    "\n",
+    "This notebook demonstrates automatic per-cell execution history filtering in BigQuery DataFrames.\n",
+    "In notebook environments (like Colab or Jupyter), `bigframes.execution_history()` automatically isolates and filters query executions to only include those initiated within the current cell."
+   ],
+   "metadata": {}
+  },
+  {
+   "id": "acae54e37e7d407bbb7b55eff062a284",
+   "cell_type": "code",
+   "source": [
+    "# Copyright 2026 Google LLC\n",
+    "#\n",
+    "# Licensed under the Apache License, Version 2.0 (the \"License\");\n",
+    "# you may not use this file except in compliance with the License.\n",
+    "# You may obtain a copy of the License at\n",
+    "#\n",
+    "#     http://www.apache.org/licenses/LICENSE-2.0\n",
+    "#\n",
+    "# Unless required by applicable law or agreed to in writing, software\n",
+    "# distributed under the License is distributed on an \"AS IS\" BASIS,\n",
+    "# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
+    "# See the License for the specific language governing permissions and\n",
+    "# limitations under the License."
+   ],
+   "metadata": {},
+   "execution_count": 1,
+   "outputs": []
+  },
+  {
+   "id": "9a63283cbaf04dbcab1f6479b197f3a8",
+   "cell_type": "code",
+   "source": [
+    "import bigframes\n",
+    "import bigframes.pandas as bpd\n",
+    "\n",
+    "bpd.options.bigquery.location = \"US\""
+   ],
+   "metadata": {},
+   "execution_count": 2,
+   "outputs": []
+  },
+  {
+   "id": "8dd0d8092fe74a7c96281538738b07e2",
+   "cell_type": "markdown",
+   "source": [
+    "## Cell 1: Executing a query\n",
+    "We will execute a standard query in this cell. Any BigFrames operations that trigger query compilation and execution will be automatically associated with this cell's execution count."
+   ],
+   "metadata": {}
+  },
+  {
+   "id": "72eea5119410473aa328ad9291626812",
+   "cell_type": "code",
+   "source": [
+    "df1 = bpd.read_gbq(\"SELECT 1 AS col1, 'hello' AS col2\")\n",
+    "df1.to_pandas()\n",
+    "\n",
+    "# Retrieve history for the current cell\n",
+    "history1 = bigframes.execution_history()\n",
+    "print(\"Execution history for Cell 1:\")\n",
+    "print(history1.to_dataframe()[[\"job_id\", \"query\", \"status\"]])"
+   ],
+   "metadata": {},
+   "execution_count": 3,
+   "outputs": []
+  },
+  {
+   "id": "8edb47106e1a46a883d545849b8ab81b",
+   "cell_type": "markdown",
+   "source": [
+    "## Cell 2: Executing a different query (Demonstrating Cell Isolation)\n",
+    "If we execute a different query in a new cell, the execution history automatically filters to only include the new query from this cell, effectively isolating executions cell-by-cell."
+   ],
+   "metadata": {}
+  },
+  {
+   "id": "10185d26023b46108eb7d9f57d49d2b3",
+   "cell_type": "code",
+   "source": [
+    "df2 = bpd.read_gbq(\"SELECT 2 AS col1, 'world' AS col2\")\n",
+    "df2.to_pandas()\n",
+    "\n",
+    "# Retrieve history for the current cell\n",
+    "history2 = bigframes.execution_history()\n",
+    "print(\"Execution history for Cell 2:\")\n",
+    "print(history2.to_dataframe()[[\"job_id\", \"query\", \"status\"]])"
+   ],
+   "metadata": {},
+   "execution_count": 4,
+   "outputs": []
+  },
+  {
+   "id": "8763a12b2bbd4a93a75aff182afb95dc",
+   "cell_type": "markdown",
+   "source": [
+    "## Retrieving Complete Execution History (Unfiltered)\n",
+    "If you want to see all executions across the entire session (spanning all cells), you can pass `current_cell_only=False`."
+   ],
+   "metadata": {}
+  },
+  {
+   "id": "7623eae2785240b9bd12b16a66d81610",
+   "cell_type": "code",
+   "source": [
+    "full_history = bigframes.execution_history(current_cell_only=False)\n",
+    "print(\"Complete, unfiltered session execution history:\")\n",
+    "print(full_history.to_dataframe()[[\"job_id\", \"query\", \"status\"]])"
+   ],
+   "metadata": {},
+   "execution_count": 5,
+   "outputs": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat_minor": 5,
+ "nbformat": 4
+}