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language-python

Write idiomatic Python code with type hints, context managers, and pytest tests.

2|8|Updated Apr 20, 2026
Search Tags:#pytest#python#type hints#asyncio#idioms#context managers
One-click install
npx skills add https://github.com/lugassawan/swe-workbench --skill language-python-lugassawan
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: language-python
Source: https://github.com/lugassawan/swe-workbench/tree/main/skills/language-python
Command: npx skills add https://github.com/lugassawan/swe-workbench --skill language-python-lugassawan

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Writing Python code that is readable, maintainable, and reliable—without accidentally adopting anti-patterns around typing, errors, context management, concurrency, and testing.

Core Features & Use Cases

  • Type-hint and data modeling guidance: Prefer dataclass, TypedDict, and Protocol, and use from __future__ import annotations for forward references.
  • Correct exception and resource handling: Use specific exceptions, avoid broad except Exception, and manage lifetimes with with and contextlib.
  • Pythonic performance, concurrency, and testing: Use generators, itertools, structured concurrency with asyncio, and pytest-first testing patterns.

Quick Start

Ask an AI to refactor your Python function so it follows these idioms: “Refactor my .py code to use idiomatic type hints, safe exceptions, proper context managers, and pytest-based tests.”

Frequently Asked Questions about language-python

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I write idiomatic Python code with proper type hints and dataclasses?▼

Idiomatic Python code uses dataclasses for modeling, enforces strong type hints, and applies `from __future__ import annotations` for forward references to ensure maintainability and correct static analysis.

What is the best way to handle exceptions and manage resources in Python?▼

Safe resource handling in Python uses specific exceptions, avoids broad `except Exception` blocks, and manages lifetimes with `with` statements and `contextlib` to guarantee proper cleanup.

How do I structure concurrency in Python using asyncio?▼

Structured concurrency in Python uses `asyncio` to manage asynchronous tasks, ensuring reliable execution and safe cancellation while maintaining performance-minded implementation choices.

Can I use pytest to test Python modules that use generators and context managers?▼

Yes, pytest-first testing patterns effectively validate Python modules that use generators, `itertools`, and context managers, ensuring your idiomatic code remains correct and maintainable.

Why does my Python code fail PEP 8 conventions and lack maintainability?▼

Code fails PEP 8 conventions when it ignores idiomatic patterns like TypedDict, Protocol, and disciplined exception handling, leading to unmaintainable and error-prone application logic.

When do I need to use Protocol and TypedDict for Python type hinting?▼

Use Protocol and TypedDict in Python when you need structural subtyping and typed dictionary structures, ensuring strong type-hint usage and maintainable data modeling.

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