Opinionated production Python standards with automatic version detection (3.10-3.13). Use when writing, reviewing, or refactoring Python in repos that want modern type syntax, explicit condition checks where practical, pathlib operations, interface guidance, and pragmatic production patterns.
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The dignified-python skill provides opinionated, production-ready Python coding standards with automatic version detection for Python 3.10 through 3.13. It serves as a comprehensive guide for writing clean, maintainable, and modern Python code by establishing explicit conventions around type annotations, exception handling, path operations, and CLI patterns. This skill addresses the common challenge of maintaining consistent code quality across Python projects by providing clear, actionable guidance on pythonic idioms and best practices.
The skill features intelligent version detection that automatically identifies your project's minimum Python version by checking pyproject.toml, setup.py, setup.cfg, or .python-version files, then loads version-specific syntax and features accordingly. It emphasizes modern type syntax using type hints, explicit condition checks (LBYL-leaning approach), pathlib for file operations, and pragmatic production patterns. The skill includes conditional loading of specialized topics like CLI patterns and subprocess handling, ensuring you get relevant guidance without context bloat.
This skill is designed for Python developers who want to improve code quality, teams establishing coding standards, code reviewers seeking consistent criteria, and anyone refactoring legacy Python code to modern standards. It automatically activates when users ask about pythonic code, type annotations, exception handling patterns, path operations, CLI development, or general Python code review. While it provides general-purpose Python guidance, project-specific conventions can override these standards when needed.
Use dignified-python for general Python code quality, type hints, exception handling, path operations, and CLI patterns. For Dagster-specific guidance, use /dagster-best-practices or /dagster-expert instead. For implementation tasks, use /dg.
The skill automatically detects your Python version by checking pyproject.toml (requires-python field), setup.py/setup.cfg (python_requires), or .python-version file in order. It defaults to Python 3.12 if no version is found, then loads version-specific syntax and features for 3.10, 3.11, 3.12, or 3.13.
The skill takes an opinionated, LBYL-leaning (Look Before You Leap) approach with explicit condition checks, modern type annotations, pathlib for file operations, and pragmatic production patterns. However, project-specific conventions can override these standards.
No, dignified-python is general-purpose Python style guidance, not Dagster-specific. For Dagster best practices, pipeline implementation, or integration decisions, use the dedicated Dagster skills instead.
Core topics include type hints and annotations, exception handling patterns, pathlib usage, CLI patterns with click/argparse, code review standards, and pythonic idioms. Advanced topics like API design, interfaces, and advanced typing are available through reference documentation.
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