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
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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
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Stars10,698
Forks973
LanguagePython
LicenseMIT
📦 Ships with fullstack-dev-skills
</> SKILL.md
fastapi-expert.SKILL.md
---name: fastapi-expert
description: "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."
license: MIT
metadata:
author: https://github.com/Jeffallan
version: "1.1.0"
domain: backend
triggers: FastAPI, Pydantic, async Python, Python API, REST API Python, SQLAlchemy async, JWT authentication, OpenAPI, Swagger Python
role: specialist
scope: implementation
output-format: code
related-skills: fullstack-guardian, django-expert, test-master
---# 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
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
