Day 30 Pt.1 | Master 服务开发

# 如果没安装，请先执行
pip install fastapi uvicorn sqlalchemy aiomysql pymysql cryptography

from sqlalchemy import Column, Integer, String, Float, DateTime
from sqlalchemy.sql import func
from database import Base

# ORM 模型：对应数据库表结构
class Metric(Base):
    __tablename__ = "server_metrics"
    
    id = Column(Integer, primary_key=True)
    hostname = Column(String(64), index=True)
    ip = Column(String(15))
    cpu = Column(Float)
    mem = Column(Float)
    disk = Column(Float)
    # server_default 让数据库自己处理时间
    created_at = Column(DateTime, server_default=func.now())

from fastapi import FastAPI, Depends, HTTPException
from sqlalchemy.ext.asyncio import AsyncSession
from sqlalchemy import select, desc
import models, database, schemas

app = FastAPI(title="Hybrid-Monitor Master")

# 启动钩子：自动建表
# 注意：生产环境通常用 Alembic 做迁移，但开发环境这样最快
@app.on_event("startup")
async def startup():
    async with database.engine.begin() as conn:
        await conn.run_sync(models.Base.metadata.create_all)

# 接口 A: 接收上报 (POST)
# response_model=dict 简化返回，我们只需要告诉 Agent 成功了
@app.post("/api/v1/report", status_code=201)
async def report_metric(
    data: schemas.MetricReport, 
    db: AsyncSession = Depends(database.get_db)
):
    # 1. 将 Pydantic Schema 转为 ORM Model
    # **data.dict() 是解包语法，相当于 hostname=data.hostname, ...
    new_metric = models.Metric(**data.dict())
    
    # 2. 添加到 Session
    db.add(new_metric)
    
    # 3. 异步提交
    # ⚠️ 必须 await commit，否则数据不会入库
    await db.commit()
    
    return {"msg": "saved"}

# 接口 B: 获取全网负载最高的 5 台机器 (GET)
@app.get("/api/v1/top")
async def get_top_cpu(db: AsyncSession = Depends(database.get_db)):
    # 异步查询语法: select(模型).order_by(...).limit(...)
    query = select(models.Metric).order_by(desc(models.Metric.cpu)).limit(5)
    
    result = await db.execute(query)
    
    # scalars().all() 将结果转换为 Model 对象列表
    return result.scalars().all()

if __name__ == "__main__":
    import uvicorn
    # 启动服务
    uvicorn.run(app, host="0.0.0.0", port=8000)