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FastAPI 模式

涵盖專案結構、Pydantic v2 架構、依賴注入、非同步處理常式、身份驗證、授權、交易服務層以及使用 httpx 和 pytest 進行測試的 FastAPI 最佳實踐。在建立或審查 FastAPI 應用程式時使用 — Pydantic 架構、相依性、非同步處理常式、身份驗證或測試。

FastAPI 模式 是什麼?

這個 AI 代理技能提供了一個全面的、生產級別的 FastAPI 開發藍圖,整合了現代最佳實踐。它定義了一個清晰的專案目錄結構,並引導使用者通過關鍵元件,例如使用 pydantic-settings 進行設定管理、用於定義強類型請求/回應模型的 Pydantic v2 架構、用於管理資料庫連線和注入使用者等資源的依賴注入、以及用於身分驗證和授權的非同步處理常式。該技能強調採用服務層模式來封裝業務邏輯,在處理資料庫交易時保持路由處理常式精簡且專注於 HTTP 層面。包含一個使用 pytest-asyncio 的完整測試套件,利用 httpx AsyncClient 進行隔離的端到端測試,並示範如何覆蓋資料庫相依性。該技能旨在與任何可執行 Python 和 FastAPI 的 AI 編碼代理(如 Claude Code、Cursor 或 Codex)搭配使用,為建構現代、可測試的 FastAPI 應用程式提供一個可複製的範本,並內建對 SQLAlchemy 非同步會話的支援。

相容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/fastapi-patterns

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說明文件

FastAPI 模式 是做什麼的?

現代、生產級別的 FastAPI 開發:專案佈局、Pydantic v2 架構、依賴注入、非同步模式、身份驗證、交易服務方法及測試。

專案結構

my_app/
|-- app/
|   |-- main.py               # App factory, lifespan, middleware
|   |-- config.py             # Settings via pydantic-settings
|   |-- dependencies.py       # Shared FastAPI dependencies
|   |-- database.py           # SQLAlchemy engine + session
|   |-- routers/
|   |   `-- users.py
|   |-- models/               # SQLAlchemy ORM models
|   |   `-- user.py
|   |-- schemas/              # Pydantic request/response schemas
|   |   `-- user.py
|   `-- services/             # Business logic layer
|       `-- user_service.py
|-- tests/
|   |-- conftest.py
|   `-- test_users.py
|-- pyproject.toml
`-- .env

App Factory 與 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):
    # 開發/演示環境中,在啟動時自動建立表格以方便使用。
    # 對於嚴格的生產應用程式,請改用 Alembic 遷移來管理架構。
    async with engine.begin() as conn:
        await conn.run_sync(Base.metadata.create_all)
    yield
    # 關閉:釋放池化資源。
    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()

使用 pydantic-settings 的配置

# 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 直接安全地評估可變列表字面量
    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()

Pydantic 架構 (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]

依賴注入

# 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)]

路由與端點設計

# 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"}

服務層

# 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):
    """當唯一使用者欄位與現有行衝突時引發。"""


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:
            # 依賴原子資料庫約束,而非容易發生競爭條件的應用級預先檢查
            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()
        # 強制執行明確的確定性排序,以確保可靠的分頁
        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,
        )

關於資料庫設計的說明: 應用層級的唯一值處理需要底層的資料庫唯一索引(例如,在 SQLAlchemy 映射屬性上使用 unique=True)。若無底層約束,應用層的錯誤捕獲無法安全地防止並發競爭條件。


使用 httpx 和 pytest 進行測試

# 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

反模式

# 糟糕:路由處理常式內的業務邏輯。
@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

# 良好:精簡的路由,交易服務處理。
@router.post("/users/", response_model=UserResponse, status_code=201)
async def create_user(payload: UserCreate, db: DbDep):
    try:
        return await UserService(db).create(payload)
    except DuplicateUserError:
        raise HTTPException(status_code=400, detail="Email already registered")

生產檢查清單

  • 資料庫遷移: 使用 Alembic 管理架構變更;避免在生產環境中的 lifespan 內使用 Base.metadata.create_all。
  • 機密管理: 切勿將 .env 提交到版本控制。使用 secrets manager 或 CI/CD secrets。
  • 記錄: 使用 structlog 或 loguru 進行結構化日誌記錄。
  • 速率限制: 實施速率限制(例如 slowapi 或反向代理)。
  • CORS: 在生產環境中將 allowed_origins 限制為已知來源。
  • 健康檢查: 為編排器(Kubernetes liveness/readiness probe)添加 /health 端點。
  • 非同步驅動程式: 對 PostgreSQL 使用 asyncpg,對 SQLite 使用 aiosqlite。
  • 輸入清理: Pydantic 可防止注入——切勿直接使用 request.body()。
  • 錯誤處理: 對已知故障使用 HTTPException;對未預期的故障使用全域異常處理常式。
  • 並發: 應用層檢查(例如「如果電子郵件存在」)在負載下會失敗;請依賴資料庫唯一約束。

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/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

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.

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