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Merge pull request #3 from tswast/b375472297-js-libraries
try to setup github actions to test workload identity federation
2 parents 6977d10 + 7d57305 commit 8534340

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Diff for: ‎.github/workflows/bigquery.yml

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# Simple workflow for deploying static content to GitHub Pages
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name: Run BigQuery snippets as a test
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on:
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push:
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paths-ignore:
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- ".gitignore"
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branches:
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- main
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pull_request_target:
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types:
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- labeled
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jobs:
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build:
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runs-on: ubuntu-latest
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if: github.event_name == 'push' || github.event.label.name == 'ci-run-cloud'
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# Add "id-token" with the intended permissions.
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permissions:
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contents: 'read'
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# required for GCP workload identity federation
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id-token: 'write'
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steps:
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- name: checkout
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uses: actions/checkout@v4
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if: github.event.label.name != 'ci-run-cloud'
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- name: checkout
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if: github.event.label.name == 'ci-run-cloud'
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uses: actions/checkout@v4
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with:
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fetch-depth: 0
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ref: ${{ github.event.pull_request.head.sha }}
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- name: Set up Python
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# This is the version of the action for setting up Python, not the Python version.
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uses: actions/setup-python@v5
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with:
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# Semantic version range syntax or exact version of a Python version
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python-version: '3.12'
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# Optional - x64 or x86 architecture, defaults to x64
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architecture: 'x64'
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- uses: 'google-github-actions/auth@v2'
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with:
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project_id: 'friendliness-dev-demo'
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workload_identity_provider: 'projects/368174856750/locations/global/workloadIdentityPools/github/providers/code-snippets'
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- name: Display Python version
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run: python -c "import sys; print(sys.version)"
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- name: Install packages
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run: python -m pip install -r requirements.txt
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- name: Test the notebook
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run: python -m jupyter nbconvert --to html --execute 2024/12-bigquery-utils/bigquery-utils.ipynb

Diff for: ‎2017/acl-weather/acl-weather.ipynb

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Diff for: ‎2024/12-bigquery-utils/bigquery-utils.ipynb

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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"%load_ext bigquery_magics"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Try a query that doesn't require any additional libraries."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "e44fc98d1439478482520de48f1e4b6c",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Query is running: 0%| |"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "aa559ce9c11540af9b8a7f9c94138063",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Downloading: 0%| |"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>x</th>\n",
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" <th>hex</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>1</td>\n",
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" <td>0000000000000001</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>1</th>\n",
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" <td>123456</td>\n",
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" <td>000000000001e240</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>2</th>\n",
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" <td>9876543210</td>\n",
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" <td>000000024cb016ea</td>\n",
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" </tr>\n",
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" <tr>\n",
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" <th>3</th>\n",
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" <td>-1001</td>\n",
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" <td>fffffffffffffc17</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" x hex\n",
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"0 1 0000000000000001\n",
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"1 123456 000000000001e240\n",
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"2 9876543210 000000024cb016ea\n",
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"3 -1001 fffffffffffffc17"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"%%bigquery\n",
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"SELECT\n",
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" x,\n",
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" bqutil.fn.to_hex(x) AS hex\n",
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"FROM\n",
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" UNNEST([1, 123456, 9876543210, -1001]) AS x;"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Try a function that uses a JS library hosted in GCS. See: https://github.com/GoogleCloudPlatform/bigquery-utils/pull/434 and https://github.com/GoogleCloudPlatform/bigquery-utils/blob/master/udfs/community/README.md#xml_to_jsonxml-string\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "9a7df3ece0584d909681ec621cdbbfd6",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Query is running: 0%| |"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"application/vnd.jupyter.widget-view+json": {
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"model_id": "38ff038524e84cc39d7c6adf5ae33807",
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"version_major": 2,
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"version_minor": 0
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},
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"text/plain": [
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"Downloading: 0%| |"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/html": [
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"<div>\n",
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"<style scoped>\n",
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" .dataframe tbody tr th:only-of-type {\n",
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" vertical-align: middle;\n",
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" }\n",
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"\n",
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" .dataframe tbody tr th {\n",
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" vertical-align: top;\n",
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" }\n",
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"\n",
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" .dataframe thead th {\n",
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" text-align: right;\n",
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" }\n",
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"</style>\n",
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"<table border=\"1\" class=\"dataframe\">\n",
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" <thead>\n",
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" <tr style=\"text-align: right;\">\n",
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" <th></th>\n",
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" <th>output_json</th>\n",
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" </tr>\n",
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" </thead>\n",
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" <tbody>\n",
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" <tr>\n",
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" <th>0</th>\n",
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" <td>{\"xml\":{\"_attributes\":{\"foo\":\"FOO\"},\"bar\":{\"ba...</td>\n",
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" </tr>\n",
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" </tbody>\n",
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"</table>\n",
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"</div>"
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],
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"text/plain": [
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" output_json\n",
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"0 {\"xml\":{\"_attributes\":{\"foo\":\"FOO\"},\"bar\":{\"ba..."
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"%%bigquery\n",
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"SELECT bqutil.fn.xml_to_json(\n",
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" '<xml foo=\"FOO\"><bar><baz>BAZ</baz></bar></xml>'\n",
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") AS output_json"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "scratch",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.12.6"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}

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