fastapi-templates

Create FastAPI project templates with layered structure and CRUD repositories.

2|Updated Oct 24, 2025
One-click install
npx skills add https://github.com/onesmartguy/next-level-real-estate --skill fastapi-templates-onesmartguy
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: fastapi-templates
Source: https://github.com/onesmartguy/next-level-real-estate/tree/main/.claude/skills/api-scaffolding/skills/fastapi-templates
Command: npx skills add https://github.com/onesmartguy/next-level-real-estate --skill fastapi-templates-onesmartguy

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires fastapi, sqlalchemy, pydantic, passlib, python-jose, uvicorn, httpx, pytest, asyncio, sqlite+aiosqlite.

What problem does it solve?

This Skill provides production-ready templates and patterns for building high-performance FastAPI applications, streamlining development with best practices for structure, async, and dependency injection. It helps you rapidly develop efficient and maintainable backend services in Python.

Core Features & Use Cases

  • Layered Project Structure: Organize API, Core, Models, Schemas, Services, and Repositories for maintainability and scalability.
  • CRUD Repository Pattern: Implement generic and specific repositories for efficient data access.
  • Service Layer: Encapsulate business logic for clean separation of concerns and testability.
  • Authentication & Authorization: Implement JWT-based security and dependency-driven access control for secure APIs.

Quick Start

Scaffold a new FastAPI project with a layered structure, including a CRUD repository for user management, a service layer, and JWT authentication. Set up a basic user creation endpoint.

Frequently Asked Questions about fastapi-templates

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

FAQPage Schema
How do I structure a production-ready FastAPI project with best practices?

FastAPI project templates organize code into layered components: API routes, core business logic, data models, schemas, services, and repositories. This separation enables maintainability, testability, and scalability by cleanly isolating concerns across the stack.

Can I build async REST APIs with FastAPI and handle concurrent requests efficiently?

FastAPI natively supports async route handlers and async database operations through asyncio and async SQLAlchemy. This enables high-performance, non-blocking request handling and concurrent database access without threads.

How do I implement JWT authentication and access control in a FastAPI application?

JWT authentication integrates with FastAPI's dependency injection system via the Depends function. You define security dependencies that verify tokens, then attach them to route handlers to enforce authorization rules and protect endpoints.

What's the best way to organize database operations in a FastAPI microservice?

A CRUD repository pattern encapsulates all database queries into reusable repository classes, with a service layer on top handling business logic. This architecture decouples data access from API endpoints and simplifies testing.

Does FastAPI work with PostgreSQL and MongoDB for production APIs?

FastAPI integrates with both PostgreSQL via SQLAlchemy and async drivers, and MongoDB through async ODMs. Templates configure either database backend with connection pooling, migrations, and async query patterns for production workloads.

How do I test a FastAPI application with async dependencies and database operations?

Pytest with async fixtures and httpx client simulate requests against FastAPI apps. The layered architecture with dependency injection allows mocking repositories and services, enabling isolated unit tests and end-to-end integration tests.