python-fastapi

Standardize FastAPI routing, dependency injection, and error handling patterns.

1|Updated Mar 30, 2026
One-click install
npx skills add https://github.com/anicdh/agstack --skill python-fastapi-anicdh
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: python-fastapi
Source: https://github.com/anicdh/agstack/tree/main/.claude/skills/python/python-fastapi
Command: npx skills add https://github.com/anicdh/agstack --skill python-fastapi-anicdh

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Inconsistent FastAPI implementations slow development, cause bugs, and hinder maintenance. This guide provides a standardized approach to building modular FastAPI apps with router patterns, dependency injection, and robust error handling. Always read python-dev first.

Core Features & Use Cases

  • Standardized router patterns using APIRouter with prefixes and tags.
  • Dependency injection with Depends and reusable services.
  • Consistent request/response handling with Pydantic v2 models and explicit status codes.
  • Use Case: Ship a scalable API quickly with well-structured code and predictable error handling.

Quick Start

Read this guide and apply FastAPI patterns to your project now.

Frequently Asked Questions about python-fastapi

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

FAQPage Schema
How do I structure a scalable FastAPI project using APIRouter?

To structure a scalable FastAPI project, use APIRouter with explicit prefixes and tags to modularize routing. This pattern separates route definitions into independent modules, ensuring maintainable and well-organized API endpoints across large codebases.

What is the best way to handle dependency injection in FastAPI?

The best way to handle FastAPI dependency injection is using the Depends function to inject reusable services. This standardizes component lifecycles and decouples business logic from route handlers, improving code consistency and testability.

How do I standardize request and response models with Pydantic v2 in FastAPI?

To standardize FastAPI request and response handling, define Pydantic v2 models and declare them using the response_model parameter. Combine this with explicit status codes to ensure predictable API payloads and consistent data validation.

Why do I need explicit status codes and response_model in FastAPI routes?

You need explicit status codes and response_model in FastAPI routes to enforce predictable API behavior and robust error handling. This practice prevents ambiguous HTTP responses, validates outgoing data structures, and maintains consistent API contracts.

Can I use FastAPI dependency injection for reusable services across multiple routers?

Yes, you can use FastAPI dependency injection via Depends to share reusable services across multiple APIRouter instances. This approach centralizes service logic, standardizes data access, and ensures consistent behavior throughout modular backend applications.