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FastAPI

作者 Iván · GitHub ↗ · v1.0.0
linuxdarwinwin32 ✓ 安全检测通过
2274
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5
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22
当前安装
1
版本数
在 OpenClaw 中安装
/install fastapi
功能描述
Build fast, production-ready Python APIs with type hints, validation, and async support.
使用说明 (SKILL.md)

FastAPI Patterns

Async Traps

  • Mixing sync database drivers (psycopg2, PyMySQL) in async endpoints blocks the event loop — use async drivers (asyncpg, aiomysql) or run sync code in run_in_executor
  • time.sleep() in async endpoints blocks everything — use await asyncio.sleep() instead
  • CPU-bound work in async endpoints starves other requests — offload to ProcessPoolExecutor or background workers
  • Async endpoints calling sync functions that do I/O still block — the entire call chain must be async

Pydantic Validation

  • Default values in models become shared mutable state: items: list = [] shares the same list across requests — use Field(default_factory=list)
  • Optional[str] doesn't make a field optional in the request — add = None or use Field(default=None)
  • Pydantic v2 uses model_validate() not parse_obj(), and model_dump() not .dict() — v1 methods are deprecated
  • Use Annotated[str, Field(min_length=1)] for reusable validated types instead of repeating constraints

Dependency Injection

  • Dependencies run on every request by default — use lru_cache on expensive dependencies or cache in app.state for singletons
  • Depends() without an argument reuses the type hint as the dependency — clean but can confuse readers
  • Nested dependencies form a DAG — if A depends on B and C, and both B and C depend on D, D runs once (cached per-request)
  • yield dependencies for cleanup (DB sessions, file handles) — code after yield runs even if the endpoint raises

Lifespan and Startup

  • @app.on_event("startup") is deprecated — use lifespan async context manager
  • Store shared resources (DB pool, HTTP client) in app.state during lifespan, not as global variables
  • Lifespan runs once per worker process — with 4 Uvicorn workers you get 4 DB pools
from contextlib import asynccontextmanager
@asynccontextmanager
async def lifespan(app):
    app.state.db = await create_pool()
    yield
    await app.state.db.close()
app = FastAPI(lifespan=lifespan)

Request/Response

  • Return dict from endpoints, not Pydantic models directly — FastAPI handles serialization and it's faster
  • Use status_code=201 on POST endpoints returning created resources — 200 is the default but semantically wrong
  • Response with media_type="text/plain" for non-JSON responses — returning a string still gets JSON-encoded otherwise
  • Set response_model_exclude_unset=True to omit None fields from response — cleaner API output

Error Handling

  • raise HTTPException(status_code=404) — don't return Response objects for errors, it bypasses middleware
  • Custom exception handlers with @app.exception_handler(CustomError) — but remember they don't catch HTTPException
  • Use detail= for user-facing messages, log the actual error separately — don't leak stack traces

Background Tasks

  • BackgroundTasks runs after the response is sent but still in the same process — not suitable for long-running jobs
  • Tasks execute sequentially in order added — don't assume parallelism
  • If a background task fails, the client never knows — add your own error handling and alerting

Security

  • OAuth2PasswordBearer is for documentation only — it doesn't validate tokens, you must implement that in the dependency
  • CORS middleware must come after exception handlers in middleware order — or errors won't have CORS headers
  • Depends(get_current_user) in path operation, not in router — dependencies on routers affect all routes including health checks

Testing

  • TestClient runs sync even for async endpoints — use httpx.AsyncClient with ASGITransport for true async testing
  • Override dependencies with app.dependency_overrides[get_db] = mock_db — cleaner than monkeypatching
  • TestClient context manager ensures lifespan runs — without with TestClient(app) as client: startup/shutdown hooks don't fire
安全使用建议
This skill appears to be a harmless FastAPI best-practices guide. A few practical notes before installing/using it: (1) the skill is instruction-only and will not install FastAPI or its dependencies for you — if you run the example code you must install packages in a controlled environment; (2) the skill's source and homepage are listed as unknown/none, so if provenance matters prefer guidance from known authors or official docs; (3) if you plan to let an agent execute code snippets from this skill, run them in an isolated sandbox (container/venv) to avoid accidental access to your files or secrets. Overall the skill is coherent with its description and does not request excessive access.
功能分析
Type: OpenClaw Skill Name: fastapi Version: 1.0.0 The provided skill bundle contains standard metadata and a comprehensive markdown document detailing best practices and common patterns for FastAPI development. There are no indications of malicious intent, prompt injection attempts, data exfiltration, unauthorized command execution, or any other harmful behaviors. The content is purely informational and educational, aligning with the stated purpose of a skill bundle.
能力评估
Purpose & Capability
The name/description match the SKILL.md content (FastAPI best-practices and patterns). The only declared runtime requirement is python3, which is reasonable for Python examples; nothing else (credentials, unrelated binaries, or config paths) is requested.
Instruction Scope
SKILL.md contains coding guidance and example snippets only. It does not instruct the agent to read arbitrary files, access environment variables, call external endpoints, or exfiltrate data. There are no open-ended directives that would give the agent broad discretion to collect unrelated context.
Install Mechanism
No install spec is provided and there are no code files. As an instruction-only skill it does not write files to disk or download external archives, which minimizes install-time risk.
Credentials
The skill declares no required environment variables, credentials, or config paths. Nothing requested is disproportionate to the stated purpose of giving FastAPI guidance.
Persistence & Privilege
always is false and the skill does not request persistent presence or system-wide configuration changes. Model invocation is allowed (platform default) but that is consistent with an advice/help skill and is not combined with other red flags.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install fastapi
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /fastapi 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release
元数据
Slug fastapi
版本 1.0.0
许可证
累计安装 24
当前安装数 22
历史版本数 1
常见问题

FastAPI 是什么?

Build fast, production-ready Python APIs with type hints, validation, and async support. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 2274 次。

如何安装 FastAPI?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install fastapi」即可一键安装,无需额外配置。

FastAPI 是免费的吗?

是的,FastAPI 完全免费(开源免费),可自由下载、安装和使用。

FastAPI 支持哪些平台?

FastAPI 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(linux, darwin, win32)。

谁开发了 FastAPI?

由 Iván(@ivangdavila)开发并维护,当前版本 v1.0.0。

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