python-patterns

Guide Python architectural decisions for framework selection and async patterns.

Updated Apr 26, 2026
One-click install
npx skills add https://github.com/ThanhNguyenDat/agent-skills --skill python-patterns-thanhnguyendat
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: python-patterns
Source: https://github.com/ThanhNguyenDat/agent-skills/tree/main/python-patterns
Command: npx skills add https://github.com/ThanhNguyenDat/agent-skills --skill python-patterns-thanhnguyendat

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill addresses the common struggle of making architectural decisions in Python, helping developers move beyond rote memorization to understand the principles behind framework selection, async patterns, and project structure.

Core Features & Use Cases

  • Decision Frameworks: Provides clear logic for choosing between FastAPI, Django, and Flask based on project requirements.
  • Async vs. Sync Guidance: Offers a definitive guide on when to utilize asynchronous programming versus synchronous execution to optimize performance.
  • Best Practices: Includes strategies for type hinting, Pydantic validation, and project organization to ensure maintainable, production-ready code.

Quick Start

Use the python-patterns skill to evaluate whether my current project architecture should prioritize FastAPI or Django based on my specific requirements.

Frequently Asked Questions about python-patterns

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

FAQPage Schema
How do I choose between FastAPI and Django for my Python backend architecture?

Choosing between FastAPI and Django requires evaluating architectural decision-making principles based on your specific project requirements. This skill provides clear logic frameworks to help you select the right backend architecture for scalable, maintainable Python systems.

When should I use async patterns instead of synchronous execution in Python?

You should use async patterns in Python when you need to optimize performance for concurrent I/O operations. This skill provides definitive guidance on when asynchronous programming outperforms synchronous execution for backend services.

What are the best practices for structuring a scalable Python project?

Best practices for structuring scalable Python projects include applying type hinting, Pydantic validation, and logical project organization. This skill provides architectural principles to ensure your codebase remains maintainable and production-ready.

Does this skill help with API design and backend service architecture in Python?

Yes, this skill directly helps with API design and backend service architecture in Python. It provides architectural decision-making principles specifically for software engineering tasks involving scalable, type-safe application development.

What's the best way to implement type safety and validation in a FastAPI application?

The best way to implement type safety in FastAPI is by utilizing Pydantic validation and strict type hinting. This skill outlines best practices and architectural principles to standardize code quality for production-ready Python applications.