python-backend

Python backend best practices involve standardizing tooling with uv for dependency management, Ruff for linting, mypy for type-checking, and pytest for testing. This ensures clear, well-typed, and maintainable code following PEP 8 standards.

You set up a FastAPI service by managing dependencies with uv, linting code with Ruff, and type-annotating public APIs with mypy. This workflow enforces consistent tooling and secure configuration management for robust backend services.

Yes, the approach works with polars for data processing. It recommends polars for efficient data handling and enforces secure .env patterns for configuration management within your backend application or service.

Using uv and Ruff standardizes dependency management and linting, replacing traditional tools to improve performance and maintainability. This approach enforces consistent tooling decisions for packaging, linting, and type-checking across Python backend projects.

Yes, you can use this workflow for background jobs and CLIs. The enforced best-practice guardrails cover APIs, services, data access, background jobs, and command-line interfaces, ensuring comprehensive backend code quality.

You should not skip mypy for public APIs. The workflow mandates type-annotating public APIs with mypy to enforce code quality and maintainability, though internal implementations may have more flexible typing requirements.