Does it support asynchronous programming?

Yes, it provides optimized patterns for asyncio, including concurrent task execution and asynchronous data streaming.

Does it include linting and formatting tools?

Yes, it includes configurations for Ruff for linting/formatting and Mypy for strict static type checking.

Can I use this for web API development?

Absolutely. It provides specific patterns for FastAPI, including Pydantic models, dependency injection, and async database operations.

What Python versions does this skill support?

The skill is optimized for Python 3.12 and newer, utilizing the latest language features and performance improvements.

How does it handle project configuration?

It follows modern PEP standards by using pyproject.toml for managing dependencies, build systems, and tool configurations.

Modern Python Development

Name: Modern Python Development
Author: julianromli

byjulianromli

•

101

Desarrollo de API

Accelerates the creation of production-ready Python applications using modern standards, type safety, and asynchronous patterns.

Acerca de

This skill equips Claude with specialized knowledge for building robust Python 3.12+ applications, focusing on industry-standard tools like FastAPI, Pydantic, and Ruff. It streamlines project initialization with standardized structures, implements strict type hinting for better maintainability, and provides optimized patterns for asynchronous I/O operations and database interactions. It is particularly useful for developers looking to migrate to modern Python features or build high-performance APIs, data processing systems, and automation scripts from scratch using production-grade best practices.

Características Principales

High-performance asynchronous patterns for I/O and data streaming
Standardized Python 3.12+ project scaffolding with pyproject.toml
Pre-configured linting and strict type-checking with Ruff and Mypy
Advanced type hinting and generic class implementations
101 GitHub stars
Production-ready FastAPI endpoint and dependency injection patterns

Casos de Uso

Bootstrapping a new FastAPI web service with best-practice folder structures
Refactoring legacy Python code to use modern async/await patterns and type hints
Implementing comprehensive unit and integration tests using Pytest and AsyncMock

Acerca de

Características Principales

High-performance asynchronous patterns for I/O and data streaming
Standardized Python 3.12+ project scaffolding with pyproject.toml
Pre-configured linting and strict type-checking with Ruff and Mypy
Advanced type hinting and generic class implementations
101 GitHub stars
Production-ready FastAPI endpoint and dependency injection patterns

Casos de Uso

Bootstrapping a new FastAPI web service with best-practice folder structures
Refactoring legacy Python code to use modern async/await patterns and type hints
Implementing comprehensive unit and integration tests using Pytest and AsyncMock