python-development_skill

Overview

This skill covers core Python development concepts, idioms, and best practices for Python 3.10+. It focuses on modern language features (type hints, pattern matching), async/await, debugging, performance profiling, and Pythonic design patterns. Use it to write readable, maintainable, and efficient Python code following current conventions.

How this skill works

The skill explains and demonstrates modern syntax (PEP-aligned type hints, structural pattern matching), common idioms (context managers, comprehensions, generators), and async patterns with asyncio and httpx. It also outlines practical debugging and profiling workflows, and maps common design patterns (dependency injection, factory, decorator) to Pythonic implementations. Recommendations include project layout, testing, and tooling integrations.

When to use it

• When writing or refactoring Python 3.10+ code and adopting modern syntax
• When adding or improving type hints and static typing in a codebase
• When implementing async services, concurrent tasks, or I/O-bound code
• When diagnosing performance or memory issues with profilers
• When needing idiomatic patterns: context managers, generators, comprehensions
• When designing maintainable systems using DI, factories, or decorators

Best practices

• Prefer built-in modern type hint syntax (list[str], dict[str, int], X | None)
• Fail fast: validate inputs early and raise clear errors
• Favor immutable transformations and pure functions over in-place mutations
• Use context managers for resource management and custom contextlib managers
• Profile before optimizing and use targeted tools (cProfile, py-spy, scalene)
• Keep single-responsibility separation and follow SOLID where practical

Example use cases

• Add type hints to a legacy module and run static checks with mypy or ruff
• Implement an asyncio-based client that concurrently fetches multiple APIs
• Use structural pattern matching to simplify complex conditional logic
• Create a custom context manager for a database connection lifecycle
• Profile a slow endpoint with cProfile and inspect line-level hotspots
• Apply dependency injection via Protocols to enable easier testing