python-patterns

# Python Development Patterns Idiomatic Python patterns and best practices for building robust, efficient, and maintainable applications. ## When to Activate - Writing new Python code - Reviewing Python code - Refactoring existing Python code - Designing Python packages/modules ## Core Principles ### 1. Readability Counts Python prioritizes readability. Code should be obvious and easy to understand. ```python # Good: Clear and readable def get_active_users(users: list[User]) -> list[User]: """Return only active users from the provided list.""" return [user for user in users if user.is_active] # Bad: Clever but confusing def get_active_users(u): return [x for x in u if x.a] ``` ### 2. Explicit is Better Than Implicit Avoid magic; be clear about what your code does. ```python # Good: Explicit configuration import logging logging.basicConfig( level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s' ) # Bad: Hidden side effects import some_module some_module.setup() # What does this do? ``` ### 3. EAFP - Easier to Ask Forgiveness Than Permission Python prefers exception handling over checking conditions. ```python # Good: EAFP style def get_value(dictionary: dict, key: str) -> Any: try: return dictionary[key] except KeyError: return default_value # Bad: LBYL (Look Before You Leap) style def get_value(dictionary: dict, key: str) -> Any...