DevOps Study Application

This project demonstrates DevOps best practices and tooling in a practical application consisting of a FastAPI backend and Flask frontend.

Architecture

• Backend: FastAPI service with CSV-based data storage
• Frontend: Flask web application with HTML templates
• Monorepo: Both services organized in src/ directory structure
• Containerization: Docker support for both services

DevOps Practices Implemented

Code Quality & Standards

• Linting & Formatting: Ruff for Python code quality and consistent formatting
• Pre-commit Hooks: Automated code quality checks before commits
• Line Length: Standardized to 120 characters across both services

Testing & CI/CD

• Unit Testing: Pytest framework for both backend and frontend
• GitHub Actions: Automated testing workflows for each service
• Docker Builds: Automated container image building and pushing

Release Management

• Conventional Commits: Commitizen for standardized commit messages
• Release Please: Automated versioning and changelog generation
• Semantic Versioning: Automatic version bumping based on commit types

Development Environment

• Tool Management: Mise for consistent tool versions across environments
• Package Management: UV for fast Python dependency management
• Development Setup: Automated project initialization scripts

Infrastructure & Operations

• Security Scanning: Trivy for vulnerability assessment
• Environment Configuration: Mise for tool and environment management

Tools Used

• mise - Tool version management
• uv - Python package management
• ruff - Python linting and formatting
• pytest - Testing framework
• pre-commit - Git hook management
• commitizen - Conventional commit formatting
• release-please - Automated releases
• trivy - Security vulnerability scanning