feat(datasets): Implement `spark.GBQQueryDataset` for reading data from BigQuery as a spark dataframe using SQL query #2830

	name: Run checks on kedro-datasets

	on:
	workflow_call:
	push:
	branches:
	- main
	paths-ignore:
	- "kedro-airflow/**"
	- "kedro-docker/**"
	- "kedro-telemetry/**"
	pull_request:
	branches:
	- main
	paths-ignore:
	- "kedro-airflow/**"
	- "kedro-docker/**"
	- "kedro-telemetry/**"

	jobs:
	unit-tests:
	strategy:
	matrix:
	os: [ ubuntu-latest, windows-latest ]
	python-version: [ "3.10", "3.11", "3.12" ]
	uses: ./.github/workflows/unit-tests.yml
	with:
	plugin: kedro-datasets
	os: ${{ matrix.os }}
	python-version: ${{ matrix.python-version }}

	lint:
	uses: ./.github/workflows/lint.yml
	with:
	plugin: kedro-datasets
	os: ubuntu-latest
	python-version: "3.11"

	check-docs:
	runs-on: ubuntu-latest
	steps:
	- name: Checkout code
	uses: actions/checkout@v4
	- name: Set up Python 3.10
	uses: actions/setup-python@v5
	with:
	python-version: "3.10"
	- name: Cache python packages
	uses: actions/cache@v4
	with:
	path: ~/.cache/pip
	key: kedro-datasets-ubuntu-latest-python-"3.10"
	restore-keys: kedro-datasets
	- name: Install uv
	run: \|
	python -m pip install "uv==0.2.21"
	- name: Install dependencies
	run: \|
	cd kedro-datasets
	uv pip install --system "kedro-datasets[docs,test,experimental] @ ."
	- name: Documentation check for kedro-datasets
	run: \|
	make check-datasets-docs

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