Generate production-grade Python code with type annotations, tests, and security practices.
npx skills add https://github.com/rosmur/logger-trials --skill python-coding
Please help me install this Agent Skill. Skill: python-coding Source: https://github.com/rosmur/logger-trials/tree/main/.claude/skills/python-coding Command: npx skills add https://github.com/rosmur/logger-trials --skill python-coding
This Skill solves the challenge of maintaining high-quality, secure, and consistent Python codebases. It provides a comprehensive framework of best practices and tools, eliminating the need for developers to manually enforce coding standards, manage dependencies, or remember every security guideline. This ensures that all generated or reviewed Python code is production-ready, reducing debugging time and technical debt.
ruff for linting/formatting, pyrefly for type checking, and interrogate for docstring coverage, ensuring code adheres to high standards without manual oversight.uv for project management, pydantic for data validation, structlog for structured logging, and pytest for comprehensive testing, streamlining the development process.Generate a Python function that calculates the factorial of a number, ensuring it follows all best practices for type hinting, docstrings, error handling, and includes a basic unit test.
High-intent search queries and answers about installing and using this skill.
Production-grade Python code requires type annotations, comprehensive docstrings, unit tests, structured logging, and input validation. This Skill automates enforcement of these standards using tools like ruff for linting, pyright for type checking, interrogate for docstring coverage, pytest for testing, and pydantic for data validation, eliminating manual oversight.
Secure Python applications require secret management, SQL injection prevention, command injection protection, and structured error handling. This Skill guides implementation of these security principles alongside comprehensive testing and validation, ensuring applications are resilient and less vulnerable to common attacks.
A robust workflow integrates project management with uv, data validation with pydantic, structured logging with structlog, and testing with pytest. This Skill provides guidance on combining these tools into a streamlined development process that maintains consistency across modules, services, and libraries.
Yes, automated quality assurance integrates linting, formatting, type checking, and docstring coverage verification. This Skill configures tools like ruff, pyright, and interrogate to enforce standards without manual intervention, reducing debugging time and technical debt.
Structured error handling combines try-catch patterns with meaningful error messages and structured logging frameworks. This Skill demonstrates using structlog for consistent log formatting and comprehensive error handling patterns that make production debugging and monitoring more effective.
This Skill covers pytest from setup through comprehensive test writing, making it accessible whether you're new to testing or experienced. It provides patterns for unit tests, error handling validation, and test organization applicable across modules and services of any scale.
tao3kAutomate Python linting, formatting, and type checking with ruff, black, and pyright.
tachiiri-orgPlan and implement Python code changes with ruff, pyright, and pytest validation.
tenzirEnforces Tenzir's Python coding standards using uv, ruff, mypy, and pytest.
nullhackRun ruff, pyright, and pytest coverage checks for Python projects.