conventions

To standardize Python coding conventions, adopt a src-layout and enforce typing, Google-style docstrings, and centralized logging practices. This removes ambiguity and improves readability, maintainability, and collaboration across your codebase.

The best way to enforce Python typing and linting is configuring Ruff for linting and Pyright for type checking. These tools catch issues early and ensure code quality consistency across your contracts, core, models, services, and interfaces modules.

You need Ruff and Pyright to maintain Python coding conventions effectively. Configuring Ruff for linting and Pyright for type checking ensures code quality, enforces typing guidelines, and automates the detection of structural inconsistencies across your project.

Centralized logging improves Python project maintainability by standardizing error handling and logging practices across all modules. Consistent logging conventions boost reliability and ensure structured outputs across contracts, core, models, services, and interfaces.

Yes, you can apply Google-style docstrings to existing Python services and interfaces to improve API clarity and tooling support. Enforcing these docstrings alongside typing guidelines ensures consistent documentation practices across your entire project structure.

Your Python project structure needs separate contracts and models directories to provide a clear layout that standardizes project structure. This separation enforces consistent coding conventions, improves readability, and standardizes structure across modules.