python-best-practices

What problem does it solve? Python codebases often accumulate inconsistent class designs, missing type hints, broad exception handling, and print-based debugging that make code hard to maintain and test. This Skill provides a concrete set of patterns to write clean, typed, and testable Python code. ## Core Features & Use Cases - Class Design Patterns: Guides use of dataclasses, frozen and slotted dataclasses, and Pydantic models for validation instead of boilerplate-heavy classes. - SOLID and Dependency Injection: Demonstrates single-responsibility class separation and constructor injection against abstract interfaces for testability. - Typing, Errors, and Logging: Covers modern type hints (generics, TypedDict, union syntax), custom domain exceptions, context managers for resources, and structured logging. - Use Case: When refactoring a service module, apply the dependency injection pattern with an abstract EmailSender so the UserService can be unit tested with a mock sender. ## Quick Start Review my Python module and refactor it to use dataclasses, type hints, custom exceptions, and proper logging following these best practices.