python-patterns

Idiomatic Python patterns improve code readability by prescribing PEP 8 conventions, explicit configuration, and sensible naming. You align modules with these practices during writing and refactoring to ensure clear, maintainable code.

EAFP (Easier to Ask Forgiveness than Permission) handles errors by encouraging specific exception catching, exception chaining, and clean custom hierarchies. This approach replaces предварительных checks with direct execution attempts, catching failures only when they occur to maintain robust control flow.

Modern type hints and Protocol-based typing are added by prescribing specific annotations for function signatures and variable declarations. This ensures type safety and maintainable structure, utilizing aliases and Protocols to define structural subtyping without requiring explicit inheritance.

Python context manager usage ensures safe resource management by prescribing correct setup and teardown patterns. This prevents resource leaks and complements performance-minded practices like using generators and __slots__ to avoid costly patterns such as string concatenation in loops.

These Python best practices are fully applicable for reviewing pull requests and establishing consistent engineering standards across a codebase. The patterns prescribe specific idioms for correctness and maintainability, ensuring team-wide alignment during code review and refactoring.

Python generators provide memory efficiency by yielding items lazily, but they are limited by being single-use iterators that cannot be indexed or reset without recreation. They should replace costly list comprehensions only when you need to handle large data streams without loading everything into memory.