内存存储

_next_id: int = 1 _tasks: Dict[int, Task] = {}

@app.get("/health") def health() -> Dict[str, str]: return {"status": "ok", "service": "taskflow-fastapi"}

@app.post("/tasks", response_model=Task, status_code=201) def create_task(payload: TaskCreate) -> Task: global _next_id task = Task(id=_next_id, **payload.model_dump()) _tasks[task.id] = task _next_id += 1 return task

@app.get("/tasks", response_model=List[Task]) def list_tasks() -> List[Task]: return list(_tasks.values())

@app.get("/tasks/{task_id}", response_model=Task) def get_task(task_id: int) -> Task: task = _tasks.get(task_id) if not task: raise HTTPException(status_code=404, detail="not found") return task

@app.put("/tasks/{task_id}", response_model=Task) def put_task(task_id: int, payload: TaskCreate) -> Task: if task_id not in _tasks: raise HTTPException(status_code=404, detail="not found") updated = Task(id=task_id, **payload.model_dump()) _tasks[task_id] = updated return updated

class TaskPatch(BaseModel): title: Optional[str] = Field(default=None) description: Optional[str] = None completed: Optional[bool] = None

@app.patch("/tasks/{task_id}", response_model=Task) def patch_task(task_id: int, payload: TaskPatch) -> Task: current = _tasks.get(task_id) if not current: raise HTTPException(status_code=404, detail="not found") data = current.model_dump() patch = payload.model_dump(exclude_unset=True) if "title" in patch: if not patch["title"] or not isinstance(patch["title"], str): raise HTTPException(status_code=400, detail="title must be non-empty string") data["title"] = patch["title"] if "description" in patch: data["description"] = patch["description"] if "completed" in patch: data["completed"] = bool(patch["completed"]) updated = Task(**data) _tasks[task_id] = updated return updated

@app.delete("/tasks/{task_id}", status_code=204) def delete_task(task_id: int) -> None: if task_id not in _tasks: raise HTTPException(status_code=404, detail="not found") del _tasks[task_id]

运行它

```bash
python -m venv .venv
source .venv/bin/activate # Windows: .venv\Scripts\activate
pip install -r requirements.txt
uvicorn app:app --reload

访问 http://localhost:8000/health。创建一个任务：

curl -s -X POST http://localhost:8000/tasks \
-H "Content-Type: application/json" \
-d '{"title":"First task","description":"Try Claude prompts"}'

在 http://localhost:8000/docs 浏览交互式文档。

对照表：选择你的入门框架

现在你已经拥有了一个最小但具备生产形态的 API 骨架，使用你选择的框架。这为 Claude 提供了一个具体的上下文，使其能够围绕路由、验证和行为进行推理。在下一节中，你将与 Claude 协作来规划端点和数据模型，把这个入门项目转变为一个具备完整文档、一致模式、测试和防护机制的服务。