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fastapi-patterns

Melhores práticas FastAPI abrangendo estrutura de projeto, schemas Pydantic v2, injeção de dependência, handlers assíncronos, autenticação, autorização, camadas de serviço transacionais e testes com httpx e pytest. Use ao construir ou revisar aplicações FastAPI — schemas Pydantic, dependências, handlers assíncronos, autenticação ou testes.

O que é fastapi-patterns?

Este skill fornece um conjunto abrangente de padrões e melhores práticas para desenvolvimento moderno e pronto para produção com FastAPI. Ele cobre desde a estruturação inicial do projeto com uma factory de aplicação e ciclo de vida gerenciado, passando por configuração robusta com pydantic-settings, até schemas Pydantic v2 que incluem validação customizada. A injeção de dependência é explorada em profundidade, demonstrando como criar dependências reutilizáveis para sessões de banco de dados assíncronas e autenticação JWT. O skill também detalha o design de rotas e endpoints, a separação de responsabilidades com uma camada de serviços transacionais e a criação de testes integrados usando httpx e pytest com um banco de dados em memória. Ele é especialmente útil para desenvolvedores que desejam construir APIs FastAPI seguindo princípios de Clean Architecture, com código testável e de fácil manutenção. As plataformas suportadas incluem Claude Code, Cursor e Codex, e o conteúdo é baseado em documentação SKILL.md seguindo padrões reais de mercado.

Funciona com~Claude Code~Codex CLI~Cursor
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Documentação

Padrões FastAPI

Desenvolvimento moderno e pronto para produção com FastAPI: layout de projeto, schemas Pydantic v2, injeção de dependência, padrões assíncronos, autenticação, métodos de serviço transacionais e testes.

Estrutura do Projeto

my_app/
|-- app/
|   |-- main.py               # Factory da aplicação, lifespan, middleware
|   |-- config.py             # Configurações com pydantic-settings
|   |-- dependencies.py       # Dependências compartilhadas do FastAPI
|   |-- database.py           # Engine SQLAlchemy + sessão
|   |-- routers/
|   |   `-- users.py
|   |-- models/               # Modelos ORM do SQLAlchemy
|   |   `-- user.py
|   |-- schemas/              # Schemas Pydantic de requisição/resposta
|   |   `-- user.py
|   `-- services/             # Camada de lógica de negócios
|       `-- user_service.py
|-- tests/
|   |-- conftest.py
|   `-- test_users.py
|-- pyproject.toml
`-- .env

Factory da Aplicação e Lifespan

# app/main.py
from contextlib import asynccontextmanager
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware

from app.config import settings
from app.database import engine, Base
from app.routers import users


@asynccontextmanager
async def lifespan(app: FastAPI):
    # Cria as tabelas automaticamente na inicialização para facilitar o uso em ambientes de desenvolvimento/demo.
    # Para aplicações estritamente de produção, gerencie schemas com migrações Alembic.
    async with engine.begin() as conn:
        await conn.run_sync(Base.metadata.create_all)
    yield
    # Desligamento: fecha recursos de pool.
    await engine.dispose()


def create_app() -> FastAPI:
    app = FastAPI(
        title=settings.app_name,
        version=settings.app_version,
        lifespan=lifespan,
    )

    app.add_middleware(
        CORSMiddleware,
        allow_origins=settings.allowed_origins,
        allow_credentials=settings.allow_credentials,
        allow_methods=settings.allowed_methods,
        allow_headers=settings.allowed_headers,
    )

    app.include_router(users.router, prefix="/users", tags=["users"])

    return app


app = create_app()

Configuração com pydantic-settings

# app/config.py
from pydantic_settings import BaseSettings, SettingsConfigDict


class Settings(BaseSettings):
    model_config = SettingsConfigDict(env_file=".env", env_file_encoding="utf-8")

    app_name: str = "My App"
    app_version: str = "0.1.0"
    debug: bool = False

    database_url: str
    secret_key: str
    algorithm: str = "HS256"
    access_token_expire_minutes: int = 30

    # pydantic-settings v2 avalia literais de lista mutável diretamente com segurança
    allowed_origins: list[str] = ["http://localhost:3000"]
    allowed_methods: list[str] = ["GET", "POST", "PATCH", "DELETE", "OPTIONS"]
    allowed_headers: list[str] = ["Authorization", "Content-Type"]
    allow_credentials: bool = True


settings = Settings()

Schemas Pydantic (v2)

# app/schemas/user.py
from datetime import datetime
from pydantic import BaseModel, EmailStr, Field, model_validator


class UserBase(BaseModel):
    email: EmailStr
    username: str = Field(min_length=3, max_length=50)


class UserCreate(UserBase):
    password: str = Field(min_length=8)
    password_confirm: str

    @model_validator(mode="after")
    def passwords_match(self) -> "UserCreate":
        if self.password != self.password_confirm:
            raise ValueError("Passwords do not match")
        return self


class UserUpdate(BaseModel):
    username: str | None = Field(default=None, min_length=3, max_length=50)
    email: EmailStr | None = None


class UserResponse(UserBase):
    id: int
    is_active: bool
    created_at: datetime

    model_config = {"from_attributes": True}


class UserListResponse(BaseModel):
    total: int
    items: list[UserResponse]

Injeção de Dependência

# app/dependencies.py
from typing import Annotated, AsyncGenerator
from fastapi import Depends, HTTPException, status
from fastapi.security import OAuth2PasswordBearer
from jose import JWTError, jwt
from sqlalchemy.ext.asyncio import AsyncSession

from app.config import settings
from app.database import AsyncSessionLocal
from app.models.user import User

oauth2_scheme = OAuth2PasswordBearer(tokenUrl="/users/token")


async def get_db() -> AsyncGenerator[AsyncSession, None]:
    async with AsyncSessionLocal() as session:
        try:
            yield session
        except Exception:
            await session.rollback()
            raise


async def get_current_user(
    token: Annotated[str, Depends(oauth2_scheme)],
    db: Annotated[AsyncSession, Depends(get_db)],
) -> User:
    credentials_exception = HTTPException(
        status_code=status.HTTP_401_UNAUTHORIZED,
        detail="Could not validate credentials",
        headers={"WWW-Authenticate": "Bearer"},
    )
    try:
        payload = jwt.decode(token, settings.secret_key, algorithms=[settings.algorithm])
        subject = payload.get("sub")
        if subject is None:
            raise credentials_exception
        user_id = int(subject)
    except (JWTError, TypeError, ValueError):
        raise credentials_exception

    user = await db.get(User, user_id)
    if user is None:
        raise credentials_exception
    return user


async def get_current_active_user(
    current_user: Annotated[User, Depends(get_current_user)],
) -> User:
    if not current_user.is_active:
        raise HTTPException(status_code=status.HTTP_403_FORBIDDEN, detail="Inactive user")
    return current_user


DbDep = Annotated[AsyncSession, Depends(get_db)]
CurrentUserDep = Annotated[User, Depends(get_current_user)]
ActiveUserDep = Annotated[User, Depends(get_current_active_user)]

Design de Roteadores e Endpoints

# app/routers/users.py
from typing import Annotated
from fastapi import APIRouter, HTTPException, Query, status
from fastapi.security import OAuth2PasswordRequestForm

from app.dependencies import ActiveUserDep, DbDep
from app.schemas.user import UserCreate, UserResponse, UserUpdate, UserListResponse
from app.services.user_service import DuplicateUserError, UserService

router = APIRouter()


@router.post("/", response_model=UserResponse, status_code=status.HTTP_201_CREATED)
async def create_user(payload: UserCreate, db: DbDep) -> UserResponse:
    service = UserService(db)
    try:
        return await service.create(payload)
    except DuplicateUserError:
        raise HTTPException(status_code=400, detail="Email already registered")


@router.get("/me", response_model=UserResponse)
async def get_me(current_user: ActiveUserDep) -> UserResponse:
    return current_user


@router.get("/", response_model=UserListResponse)
async def list_users(
    db: DbDep,
    current_user: ActiveUserDep,
    skip: Annotated[int, Query(ge=0)] = 0,
    limit: Annotated[int, Query(ge=1, le=100)] = 20,
) -> UserListResponse:
    service = UserService(db)
    users, total = await service.list(skip=skip, limit=limit)
    return UserListResponse(total=total, items=users)


@router.patch("/{user_id}", response_model=UserResponse)
async def update_user(
    user_id: int,
    payload: UserUpdate,
    db: DbDep,
    current_user: ActiveUserDep,
) -> UserResponse:
    if current_user.id != user_id:
        raise HTTPException(status_code=403, detail="Not authorized")
    service = UserService(db)
    try:
        user = await service.update(user_id, payload)
    except DuplicateUserError:
        raise HTTPException(status_code=400, detail="Email already registered")
    if user is None:
        raise HTTPException(status_code=404, detail="User not found")
    return user


@router.post("/token")
async def login(
    form_data: Annotated[OAuth2PasswordRequestForm, Depends()],
    db: DbDep,
) -> dict[str, str]:
    service = UserService(db)
    token = await service.authenticate(form_data.username, form_data.password)
    if token is None:
        raise HTTPException(
            status_code=status.HTTP_401_UNAUTHORIZED,
            detail="Incorrect username or password",
            headers={"WWW-Authenticate": "Bearer"},
        )
    return {"access_token": token, "token_type": "bearer"}

Camada de Serviço

# app/services/user_service.py
from datetime import datetime, timedelta, timezone

from jose import jwt
from passlib.context import CryptContext
from sqlalchemy import func, select
from sqlalchemy.exc import IntegrityError
from sqlalchemy.ext.asyncio import AsyncSession

from app.config import settings
from app.models.user import User
from app.schemas.user import UserCreate, UserUpdate

pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto")


class DuplicateUserError(Exception):
    """Lançada quando um campo único de usuário conflita com uma linha existente."""


class UserService:
    def __init__(self, db: AsyncSession) -> None:
        self.db = db

    async def get_by_email(self, email: str) -> User | None:
        result = await self.db.execute(select(User).where(User.email == email))
        return result.scalar_one_or_none()

    async def create(self, payload: UserCreate) -> User:
        user = User(
            email=payload.email,
            username=payload.username,
            hashed_password=pwd_context.hash(payload.password),
        )
        self.db.add(user)
        try:
            # Confia em constraints atômicas do banco de dados em vez de verificações propensas a race condition
            await self.db.commit()
        except IntegrityError as exc:
            await self.db.rollback()
            raise DuplicateUserError from exc
        await self.db.refresh(user)
        return user

    async def list(self, skip: int = 0, limit: int = 20) -> tuple[list[User], int]:
        total_result = await self.db.execute(select(func.count(User.id)))
        total = total_result.scalar_one()
        # Aplica ordenação determinística explícita para garantir paginação confiável
        result = await self.db.execute(
            select(User).order_by(User.id).offset(skip).limit(limit)
        )
        return list(result.scalars()), total

    async def update(self, user_id: int, payload: UserUpdate) -> User | None:
        user = await self.db.get(User, user_id)
        if user is None:
            return None
        for field, value in payload.model_dump(exclude_unset=True).items():
            setattr(user, field, value)
        try:
            await self.db.commit()
        except IntegrityError as exc:
            await self.db.rollback()
            raise DuplicateUserError from exc
        await self.db.refresh(user)
        return user

    async def authenticate(self, email: str, password: str) -> str | None:
        user = await self.get_by_email(email)
        if user is None or not pwd_context.verify(password, user.hashed_password):
            return None
        expire = datetime.now(timezone.utc) + timedelta(
            minutes=settings.access_token_expire_minutes
        )
        return jwt.encode(
            {"sub": str(user.id), "exp": expire},
            settings.secret_key,
            algorithm=settings.algorithm,
        )

Nota sobre Design de Banco de Dados: O tratamento de unicidade em nível de aplicação requer um índice único subjacente no banco de dados (ex.: unique=True nos atributos de mapeamento do SQLAlchemy). Sem constraints subjacentes, a captura de erros na camada de aplicação não pode prevenir com segurança condições de corrida concorrentes.


Testes com httpx e pytest

# tests/conftest.py
import pytest_asyncio
from httpx import ASGITransport, AsyncClient
from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine

from app.database import Base
from app.dependencies import get_db
from app.main import create_app

TEST_DATABASE_URL = "sqlite+aiosqlite:///:memory:"

engine = create_async_engine(TEST_DATABASE_URL)
TestingSessionLocal = async_sessionmaker(engine, expire_on_commit=False)


@pytest_asyncio.fixture(autouse=True)
async def setup_db():
    async with engine.begin() as conn:
        await conn.run_sync(Base.metadata.create_all)
    yield
    async with engine.begin() as conn:
        await conn.run_sync(Base.metadata.drop_all)


@pytest_asyncio.fixture
async def db_session():
    async with TestingSessionLocal() as session:
        yield session
        await session.rollback()


@pytest_asyncio.fixture
async def client(db_session: AsyncSession):
    app = create_app()

    async def override_get_db():
        yield db_session

    app.dependency_overrides[get_db] = override_get_db

    async with AsyncClient(
        transport=ASGITransport(app=app), base_url="http://test"
    ) as ac:
        yield ac


@pytest_asyncio.fixture
async def registered_user(client: AsyncClient) -> dict:
    resp = await client.post("/users/", json={
        "email": "[email protected]",
        "username": "testuser",
        "password": "securepass1",
        "password_confirm": "securepass1",
    })
    assert resp.status_code == 201
    return resp.json()


@pytest_asyncio.fixture
async def auth_token(client: AsyncClient, registered_user: dict) -> str:
    resp = await client.post("/users/token", data={
        "username": "[email protected]",
        "password": "securepass1",
    })
    assert resp.status_code == 200
    return resp.json()["access_token"]


@pytest_asyncio.fixture
async def auth_client(client: AsyncClient, auth_token: str) -> AsyncClient:
    client.headers.update({"Authorization": f"Bearer {auth_token}"})
    return client

Anti-padrões

# Ruim: lógica de negócios dentro dos handlers de rota.
@router.post("/users/")
async def create_user(payload: UserCreate, db: DbDep):
    hashed = bcrypt.hash(payload.password)
    user = User(email=payload.email, hashed_password=hashed)
    db.add(user)
    await db.commit()
    return user

# Bom: rota enxuta, tratamento transacional no serviço.
@router.post("/users/", response_model=UserResponse, status_code=201)
async def create_user(payload: UserCreate, db: DbDep):
    try:
        return await UserServ

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/content-engine

Create platform-native content systems for X, LinkedIn, TikTok, YouTube, newsletters, and repurposed multi-platform campaigns. Use when the user wants social posts, threads, scripts, content calendars, or one source asset adapted cleanly across platforms.

affaan-m/ECC

Multi-platform content distribution across X, LinkedIn, Threads, and Bluesky. Adapts content per platform using content-engine patterns. Never posts identical content cross-platform. Use when the user wants to distribute content across social platforms.

affaan-m/fal-ai-media

Unified media generation via fal.ai MCP — image, video, and audio. Covers text-to-image (Nano Banana), text/image-to-video (Seedance, Kling, Veo 3), text-to-speech (CSM-1B), and video-to-audio (ThinkSound). Use when the user wants to generate images, videos, or audio with AI.

affaan-m/manim-video

日本語翻訳:このファイルは manim-video 用の日本語翻訳が必要です

affaan-m/remotion-video-creation

Remotion のベストプラクティス - React で動画を作成する。3D、アニメーション、音声、字幕、チャート、トランジションなどをカバーするドメイン固有の29のルール。

affaan-m/video-editing

AI-assisted video editing workflows for cutting, structuring, and augmenting real footage. Covers the full pipeline from raw capture through FFmpeg, Remotion, ElevenLabs, fal.ai, and final polish in Descript or CapCut. Use when the user wants to edit video, cut footage, create vlogs, or build video content.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

agent-sort

Build an evidence-backed ECC install plan for a specific repo by sorting skills, commands, rules, hooks, and extras into DAILY vs LIBRARY buckets using parallel repo-aware review passes. Use when ECC should be trimmed to what a project actually needs instead of loading the full bundle.

ai-first-engineering

Engineering operating model for teams where AI agents generate a large share of implementation output. Use when setting team process, review gates, or ownership rules for a codebase largely written by agents.

ai-regression-testing

Regression testing strategies for AI-assisted development. Sandbox-mode API testing without database dependencies, automated bug-check workflows, and patterns to catch AI blind spots where the same model writes and reviews code. Use when adding regression coverage to AI-assisted code, or when the same model both wrote and reviewed a change.

android-clean-architecture

Clean Architecture patterns for Android and Kotlin Multiplatform projects — module structure, dependency rules, UseCases, Repositories, and data layer patterns. Use when structuring modules, layers, or data flow in an Android or KMP project.

angular-developer

Generates Angular code and provides architectural guidance. Trigger when creating projects, components, or services, or for best practices on reactivity (signals, linkedSignal, resource), forms, dependency injection, routing, SSR, accessibility (ARIA), animations, styling (component styles, Tailwind CSS), testing, or CLI tooling.

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