Coding Standards

Enforce Python type hints and Pydantic validation by applying coding standards that require 100% type hint coverage and Pydantic models for data crossing boundaries. This reduces runtime errors and improves maintainability across modules.

The best way to replace standard logging with loguru is to apply coding rules that mandate loguru for structured logging instead of print or the standard logging module. This ensures reliable logging across your Python modules.

Check for missing type annotations and improper logging by running a repository analysis against Python coding standards. It reports all violations, listing files, line numbers, and suggested fixes for pull requests.

Yes, this Python coding standard supports a 90-character line limit and import ordering rules. It enforces style and organization by requiring double-quoted strings and focused module layout.

Use Pydantic models for configuration validation to ensure data crossing boundaries is strictly checked. This eliminates configuration validation gaps and reduces runtime errors in Python modules.