fastapi

Name: fastapi
Availability: InStock
Author: DanKof

Automate FastAPI API development with JWT authentication and async SQLAlchemy.

Updated Mar 5, 2026

Search Tags:#authentication #fastapi #jwt #async #pydantic-v2 #sqlalchemy-2

Ready to run

npx skills add https://github.com/dankofly/Swing_B2B --skill fastapi-dankofly

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: fastapi
Source: https://github.com/dankofly/Swing_B2B/tree/main/.claude/skills/fastapi
Command: npx skills add https://github.com/dankofly/Swing_B2B --skill fastapi-dankofly

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The FastAPI skill provides production-ready patterns and guidance to build robust Python APIs quickly, reducing boilerplate and engineering risk.

Core Features & Use Cases

Separation of concerns: distinct Pydantic schemas from SQLAlchemy models for validation and persistence.
Async by default: encourages non-blocking IO and scalable endpoints with JWT authentication and domain-based project structure.
Use cases include building REST APIs with JWT auth, validation, and OpenAPI/Swagger documentation.

Quick Start

Start the sample app with uvicorn and verify the endpoints using the interactive docs at /docs.

Frequently Asked Questions about fastapi

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

FAQPage Schema

How do I structure a FastAPI project with JWT authentication and async SQLAlchemy?▼

Structure your FastAPI project using a clean domain-based layout that separates Pydantic v2 schemas from SQLAlchemy 2 models. This approach enforces dependency injection and implements JWT authentication with async SQLAlchemy for scalable, non-blocking IO endpoints.

Should I separate Pydantic schemas from SQLAlchemy models in FastAPI?▼

Yes, separating Pydantic schemas from SQLAlchemy models is a best practice for FastAPI validation and persistence. This separation of concerns ensures robust data handling, reduces boilerplate, and maintains clean boundaries between API validation and database ORM operations.

Does this FastAPI approach support Pydantic v2 and SQLAlchemy 2?▼

Yes, the FastAPI approach fully supports Pydantic v2 validation and SQLAlchemy 2 async integration. It applies production-grade patterns to ensure your API project uses modern, non-blocking IO with proper OpenAPI-compliant documentation and domain-based structure.

What is the best way to generate OpenAPI-compliant documentation for a FastAPI app?▼

The best way to generate OpenAPI-compliant documentation is by applying production-grade FastAPI patterns with Pydantic v2 validation. This automatically produces interactive Swagger docs at the /docs endpoint, ensuring your REST API maintains proper status codes and schema definitions.

How do I implement dependency injection for JWT authentication in FastAPI?▼

Implement FastAPI dependency injection for JWT authentication by structuring endpoints around a domain-based project layout. This pattern automates production-grade security, enforces proper status codes, and integrates seamlessly with async SQLAlchemy database sessions.