Python Flask API

A simple Flask REST API with math utility endpoints and a complete CI/CD pipeline.

Features

• Flask REST API with health checks and calculation endpoints
• Comprehensive test suite with pytest
• Automated testing and code quality checks
• Security scanning integration
• Artifact versioning and deployment automation

Quick Start

Prerequisites

• Python 3.11 or higher
• pip

Installation

# Clone the repository
git clone <repository-url>
cd py-gha

# Create a virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements-dev.txt

Running the Application

# Run the Flask app
python app/main.py

# Or using Flask CLI
flask --app app.main run

The application will be available at http://localhost:5000

Running Tests

# Run all tests
pytest

# Run with coverage
pytest --cov=app

# Run with JUnit XML output (for CI)
pytest --junitxml=test-results.xml

Code Quality

# Format code with Black
black app/ tests/

# Check formatting
black --check app/ tests/

# Run linting
flake8 app/ tests/ --max-line-length=100

API Endpoints

Endpoint	Description
GET /	Hello World message
GET /health	Health check endpoint
GET /api/add/<a>/<b>	Add two numbers
GET /api/multiply/<a>/<b>	Multiply two numbers
GET /api/fibonacci/<n>	Calculate Fibonacci number

Example Requests

# Hello endpoint
curl http://localhost:5000/

# Health check
curl http://localhost:5000/health

# Add numbers
curl http://localhost:5000/api/add/5/3

# Calculate Fibonacci
curl http://localhost:5000/api/fibonacci/10

CI/CD Pipeline

The GitHub Actions workflow provides automated testing, code quality checks, and deployment:

• Testing: Automated test execution with coverage reporting
• Code Quality: Format checking with Black and linting with Flake8
• Security: Black Duck SCA scanning for dependency vulnerabilities
• Build & Deploy: Automated versioning, package building, and artifact management

See .github/workflows/ci.yml for the complete pipeline configuration.

Development

This project uses standard Python development tools:

• pytest for testing
• black for code formatting
• flake8 for linting
• pytest-cov for coverage reporting

All dependencies are managed via pip and defined in requirements.txt and requirements-dev.txt.

License

MIT