Pozole | Flask REST API QA Showcase

A REST API built with Flask to manage restaurant employees and work shifts.

Although the application provides a complete backend for employee scheduling, the main purpose of this repository is to showcase my Software QA and Test Automation skills. The project demonstrates how to test REST APIs using unit, integration, smoke, and performance testing, along with automated quality checks and continuous integration.

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What This Project Demonstrates

This repository highlights my experience with:

• Building automated API tests with pytest
• Writing unit, integration, smoke, and performance tests
• Testing REST endpoints, validation, and database workflows
• Measuring API performance with Locust
• Enforcing code quality with Ruff and Git hooks
• Running automated checks with GitHub Actions

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Tech Stack

Backend

• Flask
• Flask-SQLAlchemy
• SQLite
• Marshmallow

Testing

• pytest
• Requests
• Locust
• pytest-cov

Code Quality

• Ruff
• Lefthook
• GitHub Actions

Development

• Astral uv

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Project Structure

backend/
    models/
    app.py
    database.py
    schemas.py

tests/
    integration/
    performance/
    smoke/
    unit/
    conftest.py

.github/workflows/
main.py

The tests/ folder contains different types of automated tests:

• Unit tests for API endpoints and validation
• Integration tests for complete employee and shift workflows
• Smoke tests to verify the API is running and responding
• Performance tests using Locust to simulate API traffic

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Getting Started

Requirements

• Python
• Astral uv

Install the project dependencies:

uv sync

Install the Git hooks:

uv run lefthook install

Start the development server:

uv run main.py

The API will be available at:

http://127.0.0.1:5000

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API Endpoints

Employees

Method	Endpoint
GET	/employees
POST	/employees
GET	/employees/<id>
PUT	/employees/<id>
DELETE	/employees/<id>

Shifts

Method	Endpoint
GET	/shifts
POST	/shifts
GET	/shifts/<id>
PUT	/shifts/<id>
DELETE	/shifts/<id>

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Running Tests

Run the complete test suite:

uv run pytest

Generate a coverage summary:

uv run task cov

Generate an HTML coverage report:

uv run task coverage-report

Run the smoke tests:

uv run pytest tests/smoke/

Run the performance tests:

uv run task perf

Generate a performance report:

uv run task perf-report

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Test Coverage

The project currently has 99% test coverage.

The automated test suite validates:

• REST API endpoints
• Request validation
• CRUD operations
• Database relationships
• Employee and shift workflows
• Error handling
• API availability
• Performance under load

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Code Quality

The project uses Lefthook to automatically run quality checks before code is committed.

The pre-commit workflow includes:

• Ruff formatting
• Ruff linting
• Automated pytest execution

Run the checks manually:

uv run ruff format .
uv run ruff check .

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Continuous Integration

GitHub Actions automatically runs quality checks whenever code is pushed to the repository.

The CI pipeline includes:

• Ruff linting
• Automated test execution
• Continuous validation of the codebase