python-expert_skill

Overview

This skill packages senior Python developer expertise to write, review, and optimize clean, efficient, and well-documented Python code. It focuses on correctness, type safety, performance, and PEP 8 style to deliver maintainable, production-ready code. Use it when you need concrete code changes, reviews, or debugging guidance.

How this skill works

I inspect code for logical errors, edge cases, and common Python pitfalls (mutable defaults, scope issues). I enforce type hints, recommend appropriate data structures and algorithms, and suggest performance improvements (comprehensions, generators, built-ins). I also validate error handling, security considerations, and documentation quality, and produce clear, annotated code examples when requested.

When to use it

• Writing new Python functions, classes, or modules with production constraints
• Reviewing code for correctness, type safety, and style compliance
• Debugging exceptions, unexpected behavior, or performance bottlenecks
• Adding or improving type hints, docstrings, and API surface documentation
• Choosing or optimizing data structures and algorithms for a task
• Preparing code for testing, security review, or deployment

Best practices

• Design first: clarify requirements, choose data structures, and plan interfaces
• Always add type hints for public functions and return types; use TypeVar for generics
• Handle edge cases and raise specific exceptions with informative messages
• Prefer list/set/dict comprehensions and generators over manual loops for clarity and performance
• Follow PEP 8 naming and formatting; include concise docstrings (Google or NumPy style)
• Profile before optimizing; optimize hotspots, not premature micro-optimizations

Example use cases

• Refactor an untyped codebase to add comprehensive type hints and improve IDE support
• Review a pull request to catch hidden bugs, inefficient loops, or unsafe operations
• Optimize a slow data-processing script by switching to generators and built-ins
• Implement robust error handling and input validation for a library API
• Write unit tests and edge-case scenarios for complex algorithms or boundary conditions