python-pro

Initialize typed Python 3.11+ projects with mypy strict, black, ruff, and pytest.

Updated Mar 18, 2026

Search Tags:#linting #pytest #type hints #mypy #black #async programming #dataclasses

Ready to run

npx skills add https://github.com/bpteam/coder --skill python-pro-bpteam

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: python-pro
Source: https://github.com/bpteam/coder/tree/main/.opencode/skills/python-pro
Command: npx skills add https://github.com/bpteam/coder --skill python-pro-bpteam

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Solves the problem of building robust, type-safe Python 3.11+ applications by guiding async-first design, strict typing, and reliable testing.

Core Features & Use Cases

Type hints everywhere: enforce static type safety across modules.
Async-first design: build scalable I/O-bound components with async/await.
Production-ready workflows: pytest with fixtures, mypy strict, black/ruff formatting, and Poetry packaging.
Reusable patterns: dataclasses, dependency injection, logging configuration, and clear API boundaries.
Use Case: create a fast, type-safe API service with asynchronous data processing and a solid test suite.

Quick Start

Initialize a typed Python 3.11+ project with strict typing, async-ready modules, and a pytest suite configured with mypy, black, and ruff.

Frequently Asked Questions about python-pro

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

FAQPage Schema

How do I set up a Python 3.11+ project with strict type hints and async support?▼

To set up a Python 3.11+ project with strict type hints and async support, initialize modules using async-first design and enforce static typing globally. This approach integrates mypy strict, black, and ruff to ensure type safety and formatting.

What is the best way to structure asynchronous Python applications with dataclasses?▼

The best way to structure asynchronous Python applications with dataclasses involves using async-first design patterns alongside dependency injection. This creates scalable I/O-bound components with clear API boundaries and robust dataclass models.

Does mypy strict work with pytest fixtures for type-safe Python testing?▼

Yes, mypy strict works with pytest fixtures for type-safe Python testing. You can configure a pytest suite that validates asynchronous data processing while enforcing static typing rules across all modules.

Can I use Poetry packaging with ruff and black for Python linting and formatting?▼

Yes, you can use Poetry packaging with ruff and black for Python linting and formatting. This combination establishes production-ready workflows that standardize code formatting and enforce strict linting standards.

When do I need dependency injection in async Python services?▼

You need dependency injection in async Python services when building scalable I/O-bound components with clear API boundaries. It provides reusable patterns for logging configuration and managing asynchronous data processing workflows.

Why use async-first design for building robust Python applications?▼

Use async-first design for building robust Python applications to effectively handle scalable I/O-bound operations. Paired with static typing and pytest testing, it ensures reliable service development and solid test suites.