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Fastapi Development

  • 564 installs
  • 305 repo stars
  • Updated March 4, 2026
  • aj-geddes/useful-ai-prompts

fastapi-development is a Python backend skill that scaffolds production-style FastAPI services with async routes, Pydantic validation, and OpenAPI docs for developers building high-performance Python APIs or microservice

About

fastapi-development is an aj-geddes useful-ai-prompts skill for building modern Python APIs with FastAPI. It teaches async/await route handlers, Pydantic request and response validation, dependency injection, security hooks, CORS configuration, structured logging, and automatic OpenAPI documentation generation. Developers reach for fastapi-development when starting a new microservice, replacing synchronous Flask endpoints, or hardening an API that must expose interactive docs and strict type validation out of the box. The skill includes quick-start patterns, reference guides, and best practices for performance-oriented services where automatic schema generation and async I/O matter. Invoke it during backend scaffolding or when extending existing FastAPI projects with new routers, middleware, or validated models.

  • Async FastAPI app bootstrap with title, version, and configurable docs_url
  • HTTPException and status codes for consistent error handling
  • CORSMiddleware pattern for browser clients hitting your API
  • Structured logging setup via logging.basicConfig and module loggers
  • Oriented toward OpenAPI/Swagger, Pydantic validation, JWT, and SQLAlchemy per skill overview

Fastapi Development by the numbers

  • 564 all-time installs (skills.sh)
  • Ranked #755 of 4,347 Backend & APIs skills by installs in the Skillselion catalog
  • Security screen: LOW risk (skills.sh audit)
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
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Listed on Skillselion
Installs564
repo stars305
Security audit3 / 3 scanners passed
Last updatedMarch 4, 2026
Repositoryaj-geddes/useful-ai-prompts

How do you scaffold production FastAPI async Python APIs?

Scaffold and extend production-style FastAPI services with async routes, Pydantic validation, CORS, logging, and OpenAPI docs for a solo-developer API or microservice.

Who is it for?

Python backend developers creating async REST or microservice APIs who want FastAPI patterns for validation, security, and automatic docs.

Skip if: Django monolith features, non-HTTP batch jobs, or frontends that do not need a Python async API layer.

When should I use this skill?

A developer builds or extends FastAPI services, asks for async Python APIs, Pydantic validation, or automatic OpenAPI documentation.

What you get

FastAPI application modules with async endpoints, Pydantic schemas, dependency injection, and OpenAPI documentation.

  • FastAPI route modules
  • Pydantic schema models
  • OpenAPI documentation

Files

SKILL.mdMarkdownGitHub ↗

FastAPI Development

Table of Contents

Overview

Create fast, modern Python APIs using FastAPI with async/await support, automatic API documentation, type validation using Pydantic, dependency injection, JWT authentication, and SQLAlchemy ORM integration.

When to Use

  • Building high-performance Python REST APIs
  • Creating async API endpoints
  • Implementing automatic OpenAPI/Swagger documentation
  • Leveraging Python type hints for validation
  • Building microservices with async support
  • Integrating Pydantic for data validation

Quick Start

Minimal working example:

# main.py
from fastapi import FastAPI, HTTPException, status
from fastapi.middleware.cors import CORSMiddleware
from contextlib import asynccontextmanager
import logging

# Setup logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

# Create FastAPI instance
app = FastAPI(
    title="API Service",
    description="A modern FastAPI application",
    version="1.0.0",
    docs_url="/api/docs",
    openapi_url="/api/openapi.json"
)

# Add CORS middleware
app.add_middleware(
    CORSMiddleware,
    allow_origins=["http://localhost:3000"],
    allow_credentials=True,
    allow_methods=["*"],
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

GuideContents
FastAPI Application SetupFastAPI Application Setup
Pydantic Models for ValidationPydantic Models for Validation
Async Database Models and QueriesAsync Database Models and Queries
Security and JWT AuthenticationSecurity and JWT Authentication
Service Layer for Business LogicService Layer for Business Logic
API Routes with Async EndpointsAPI Routes with Async Endpoints

Best Practices

✅ DO

  • Use async/await for I/O operations
  • Leverage Pydantic for validation
  • Use dependency injection for services
  • Implement proper error handling with HTTPException
  • Use type hints for automatic OpenAPI documentation
  • Create service layers for business logic
  • Implement authentication on protected routes
  • Use environment variables for configuration
  • Return appropriate HTTP status codes
  • Document endpoints with docstrings and tags

❌ DON'T

  • Use synchronous database operations
  • Trust user input without validation
  • Store secrets in code
  • Ignore type hints
  • Return database models in responses
  • Implement authentication in route handlers
  • Use mutable default arguments
  • Forget to validate query parameters
  • Expose stack traces in production

Related skills

FAQ

Does fastapi-development cover async route handlers?

fastapi-development guides building FastAPI applications with async/await route handlers, Pydantic validation, and high-performance patterns suited to concurrent Python API workloads.

Will fastapi-development generate API documentation automatically?

fastapi-development includes automatic OpenAPI documentation setup so developers get interactive schema docs from Pydantic models and route definitions without manual spec authoring.

Is Fastapi Development safe to install?

skills.sh reports 3 of 3 security scanners passed. Review the Security Audits panel on this page before installing in production.

Backend & APIsbackendintegrations

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