Schemas are defined in code, not SQL. ORM models are generated dynamically. MySQL tables are created and seeded on demand. Docker/CI builds can bootstrap databases automatically on startup. Queries automatically adapt to MySQL vs. SQLite and dataset-specific differences. #2324

	---
	name: BAR-API

	on:
	push:
	pull_request:
	schedule:
	- cron: '0 0 * * *'

	jobs:
	test:

	runs-on: ubuntu-24.04
	strategy:
	fail-fast: false
	matrix:
	python-version: [3.10.18, 3.11, 3.12, 3.13]

	services:
	redis:
	image: redis
	options: >-
	--health-cmd "redis-cli ping"
	--health-interval 10s
	--health-timeout 5s
	--health-retries 5
	ports:
	- 6379:6379

	steps:
	- uses: actions/checkout@v2

	- name: Set up Python ${{ matrix.python-version }}
	uses: actions/setup-python@v2
	with:
	python-version: ${{ matrix.python-version }}

	- name: Install dependencies
	run: \|
	sudo systemctl start mysql.service
	python -m pip install --upgrade pip setuptools wheel
	pip install -r requirements.txt

	- name: Initial setup
	run: ./config/init.sh

	- name: Lint with flake8
	run: flake8

	- name: Pytest run by coverage
	run: \|
	coverage run
	coverage xml
	env:
	REDIS_HOST: localhost
	REDIS_PORT: 6379
	CI: true

	- name: "Upload coverage to Codecov"
	uses: codecov/codecov-action@v2
	with:
	fail_ci_if_error: false

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