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fastapi skill

This skill helps you build high-performance APIs with FastAPI, enabling async endpoints, automatic docs, and type-safe request handling.

npx playbooks add skill pluginagentmarketplace/custom-plugin-python --skill fastapi

Review the files below or copy the command above to add this skill to your agents.

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SKILL.md

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---
name: FastAPI
description: FastAPI web framework for building modern APIs with async support
version: "2.1.0"
sasmp_version: "1.3.0"
bonded_agent: 02-web-development
bond_type: PRIMARY_BOND

# Skill Configuration
retry_strategy: exponential_backoff
observability:
  logging: true
  metrics: request_latency
---

# FastAPI Skill

## Overview
Build modern, high-performance APIs with FastAPI, including async endpoints, automatic documentation, and type-safe request handling.

## Topics Covered

### FastAPI Basics
- Application structure
- Route decorators
- Path and query parameters
- Request body handling
- Response models

### Pydantic Integration
- Request validation
- Response serialization
- Custom validators
- Settings management
- Nested models

### Async Programming
- Async endpoint handlers
- Background tasks
- Async database access
- Concurrent requests
- Event handlers

### Security
- OAuth2 implementation
- JWT authentication
- API key authentication
- Dependency injection
- CORS configuration

### Advanced Features
- WebSocket support
- File uploads
- Streaming responses
- Middleware creation
- Testing FastAPI

## Prerequisites
- Python fundamentals
- Async/await basics
- HTTP concepts

## Learning Outcomes
- Build production APIs
- Implement authentication
- Create async endpoints
- Generate API documentation

Overview

This skill teaches how to build modern, high-performance APIs using FastAPI. It focuses on async endpoints, automatic OpenAPI documentation, and type-safe request/response handling. You will learn practical patterns for validation, security, and production readiness.

How this skill works

The skill walks through application structure, route definitions, and Pydantic model usage to validate and serialize data. It introduces async endpoint handlers, background tasks, and integration points for databases and authentication. Hands-on examples cover middleware, WebSockets, file uploads, and testing strategies to produce robust API services.

When to use it

Building new REST or WebSocket APIs that need high throughput and low latency
Creating services that require automatic API docs and schema validation
Implementing async I/O with databases or external services
Adding type-safe request/response models and strict validation
Securing endpoints with OAuth2, JWT, or API keys

Best practices

Structure projects with clear routers, dependencies, and settings modules
Use Pydantic models for request validation and response serialization to avoid runtime errors
Prefer async database drivers and non-blocking libraries for scalability
Centralize authentication and authorization via dependencies to keep handlers small
Write tests for routes, dependencies, and middleware to prevent regressions
Configure CORS, rate limiting, and sensible exception handlers for production safety

Example use cases

Public REST API for a SaaS product with automatic docs and versioned routes
Internal microservice handling async tasks and database operations
Real-time features using WebSockets for chat or live updates
File upload and streaming endpoints for media services
Secured API with OAuth2 and JWT for third-party integrations

FAQ

Do I need to know async/await to use FastAPI?

Basic async/await knowledge is recommended to write scalable endpoints, but synchronous handlers are supported. Use async when performing I/O-bound work like DB or network calls.

How does validation work with FastAPI?

FastAPI uses Pydantic models to validate and serialize request bodies and responses. Define models for inputs and outputs to get automatic validation and helpful error messages.