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fastapi-expert

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9.9kCommunityDocumentationby jeffallan · MIT

Use when building high-performance async Python APIs with FastAPI and Pydantic V2. Invoke to create REST endpoints, define Pydantic models, implement authentication flows, set up async SQLAlchemy database operations, add JWT authentication, build WebSocket endpoints, or generate OpenAPI documentation. Trigger terms: FastAPI, Pydantic, async Python, Python API, REST API Python, SQLAlchemy async, JWT authentication, OpenAPI, Swagger Python.

Python869 forks37 issuesUpdated 6/16/2026First seen 5/22/2026

Summary

This skill provides deep expertise in building high-performance async Python APIs with FastAPI and Pydantic V2.

  • It helps developers create REST endpoints, define validation schemas, implement authentication, set up async database operations, and generate OpenAPI documentation efficiently.

Overview

FastAPI Expert

Deep expertise in async Python, Pydantic V2, and production-grade API development with FastAPI.

When to Use This Skill

  • Building REST APIs with FastAPI
  • Implementing Pydantic V2 validation schemas
  • Setting up async database operations
  • Implementing JWT authentication/authorization
  • Creating WebSocket endpoints
  • Optimizing API performance

Core Workflow

  1. Analyze requirements — Identify endpoints, data models, auth needs
  2. Design schemas — Create Pydantic V2 models for validation
  3. Implement — Write async endpoints with proper dependency injection
  4. Secure — Add authentication, authorization, rate limiting
  5. Test — Write async tests with pytest and httpx; run pytest after each endpoint group and verify OpenAPI docs at /docs

Checkpoint after each step: confirm schemas validate correctly, endpoints return expected HTTP status codes, and /docs reflects the intended API surface before proceeding.

Minimal Complete Example

Schema + endpoint + dependency injection in one cohesive unit:

python
# schemas.py
from pydantic import BaseModel, EmailStr, field_validator, model_config

class UserCreate(BaseModel):
    model_config = model_config(str_strip_whitespace=True)

    email: EmailStr
    password: str
    name: str | None = None

    @field_validator("password")
    @classmethod
    def password_strength(cls, v: str) -> str:
        if len(v) < 8:
            raise ValueError("Password must be at least 8 characters")
        return v

class UserResponse(BaseModel):
    model_config = model_config(from_attributes=True)

    id: int
    email: EmailStr
    name: str | None = None
python
# routers/users.py
from fastapi import APIRouter, Depends, HTTPException, status
from sqlalchemy.ext.asyncio import AsyncSession
from typing import Annotated

from app.database import get_db
from app.schemas import UserCreate, UserResponse
from app import crud

router = APIRouter(prefix="/users", tags=["users"])

DbDep = Annotated[AsyncSession, Depends(get_db)]

@router.post("/", response_model=UserResponse, status_code=status.HTTP_201_CREATED)
async def create_user(payload: UserCreate, db: DbDep) -> UserResponse:
    existing = await crud.get_user_by_email(db, payload.email)
    if existing:
        raise HTTPException(status_code=status.HTTP_409_CONFLICT, detail="Email already registered")
    return await crud.create_user(db, payload)
python
# crud.py
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession
from app.models import User
from app.schemas import UserCreate
from app.security import hash_password

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

async def create_user(db: AsyncSession, payload: UserCreate) -> User:
    user = User(email=payload.email, hashed_password=hash_password(payload.password), name=payload.name)
    db.add(user)
    await db.commit()
    await db.refresh(user)
    return user

JWT Authentication Snippet

python
# security.py
from datetime import datetime, timedelta, timezone
from jose import JWTError, jwt
from fastapi import Depends, HTTPException, status
from fastapi.security import OAuth2PasswordBearer
from typing import Annotated

SECRET_KEY = "read-from-env"  # use os.environ / settings
ALGORITHM = "HS256"
oauth2_scheme = OAuth2PasswordBearer(tokenUrl="/auth/token")

def create_access_token(subject: str, expires_delta: timedelta = timedelta(minutes=30)) -> str:
    payload = {"sub": subject, "exp": datetime.now(timezone.utc) + expires_delta}
    return jwt.encode(payload, SECRET_KEY, algorithm=ALGORITHM)

async def get_current_user(token: Annotated[str, Depends(oauth2_scheme)]) -> str:
    try:
        data = jwt.decode(token, SECRET_KEY, algorithms=[ALGORITHM])
        subject: str | None = data.get("sub")
        if subject is None:
            raise ValueError
        return subject
    except (JWTError, ValueError):
        raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="Invalid credentials")

CurrentUser = Annotated[str, Depends(get_current_user)]

Reference Guide

Load detailed guidance based on context:

TopicReferenceLoad When
Pydantic V2references/pydantic-v2.mdCreating schemas, validation, model_config
SQLAlchemyreferences/async-sqlalchemy.mdAsync database, models, CRUD operations
Endpointsreferences/endpoints-routing.mdAPIRouter, dependencies, routing
Authenticationreferences/authentication.mdJWT, OAuth2, get_current_user
Testingreferences/testing-async.mdpytest-asyncio, httpx, fixtures
Django Migrationreferences/migration-from-django.mdMigrating from Django/DRF to FastAPI

Constraints

MUST DO

  • Use type hints everywhere (FastAPI requires them)
  • Use Pydantic V2 syntax (field_validator, model_validator, model_config)
  • Use Annotated pattern for dependency injection
  • Use async/await for all I/O operations
  • Use X | None instead of Optional[X]
  • Return proper HTTP status codes
  • Document endpoints (auto-generated OpenAPI)

MUST NOT DO

  • Use synchronous database operations
  • Skip Pydantic validation
  • Store passwords in plain text
  • Expose sensitive data in responses
  • Use Pydantic V1 syntax (@validator, class Config)
  • Mix sync and async code improperly
  • Hardcode configuration values

Output Templates

When implementing FastAPI features, provide:

  1. Schema file (Pydantic models)
  2. Endpoint file (router with endpoints)
  3. CRUD operations if database involved
  4. Brief explanation of key decisions

Knowledge Reference

FastAPI, Pydantic V2, async SQLAlchemy, Alembic migrations, JWT/OAuth2, pytest-asyncio, httpx, BackgroundTasks, WebSockets, dependency injection, OpenAPI/Swagger

Documentation

Install & Usage

1
Create the skills directory
mkdir -p .claude/skills
2
Download the skill file
mkdir -p .claude/skills && curl -o .claude/skills/fastapi-expert.md https://raw.githubusercontent.com/jeffallan/claude-skills/main/skills/fastapi-expert/SKILL.md
3
Invoke in Claude Code
/fastapi-expert

Use Cases

Design and validate Pydantic V2 models with custom field validators for API request/response schemas.
Implement JWT-based authentication and authorization flows with OAuth2 password flow.
Set up async SQLAlchemy sessions and perform CRUD operations with dependency injection.
Build WebSocket endpoints for real-time communication in a FastAPI application.
Generate and customize OpenAPI documentation with tags, descriptions, and examples.
Write async tests with pytest and httpx to validate endpoint behavior and status codes.

Usage Examples

1

/fastapi-expert Create a FastAPI app with a POST /users endpoint that validates email and password using Pydantic V2.

2

/fastapi-expert Add JWT authentication to my existing FastAPI project with login and token refresh endpoints.

3

/fastapi-expert Set up async SQLAlchemy with PostgreSQL and implement a GET /items endpoint with pagination.

View source on GitHub
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Security Audits

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Frequently Asked Questions

What is fastapi-expert?

This skill provides deep expertise in building high-performance async Python APIs with FastAPI and Pydantic V2. It helps developers create REST endpoints, define validation schemas, implement authentication, set up async database operations, and generate OpenAPI documentation efficiently.

How to install fastapi-expert?

To install fastapi-expert: create the skills directory (mkdir -p .claude/skills), then run: mkdir -p .claude/skills && curl -o .claude/skills/fastapi-expert.md https://raw.githubusercontent.com/jeffallan/claude-skills/main/skills/fastapi-expert/SKILL.md. Finally, /fastapi-expert in Claude Code.

What is fastapi-expert best for?

fastapi-expert is a skill categorized under Documentation. It is designed for: documentation, api, python. Created by jeffallan.

What can I use fastapi-expert for?

fastapi-expert is useful for: Design and validate Pydantic V2 models with custom field validators for API request/response schemas.; Implement JWT-based authentication and authorization flows with OAuth2 password flow.; Set up async SQLAlchemy sessions and perform CRUD operations with dependency injection.; Build WebSocket endpoints for real-time communication in a FastAPI application.; Generate and customize OpenAPI documentation with tags, descriptions, and examples.; Write async tests with pytest and httpx to validate endpoint behavior and status codes..