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1. Dashboard: stats新增queryStats查询统计, trend API真实工单趋势数据 2. Layout铃铛: 显示真实待审批工单数量 3. 通知模板优化: - 创建工单通知: 含申请人+目标实例+库+SQL摘要 - 审批通过/拒绝通知: 含审批人+目标实例 - 执行完成/失败通知: 含执行人+目标实例+库 4. 飞书卡片颜色: 创建=turquoise, 审批=blue, 成功=green, 失败=red 5. 钉钉消息: 添加状态emoji标签(🆕✅❌⚠️) 6. TicketCreatePage: 底部操作栏(SQL检测+提交审批) 7. ticket_executor: 移除aiomysql不支持的read_timeout/write_timeout Tests: 1057 passed, 17 pre-existing failures (notification 35/35 passed)
134 lines
4.7 KiB
Python
134 lines
4.7 KiB
Python
from datetime import datetime, timedelta, timezone
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from fastapi import APIRouter, Depends, Query
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from sqlalchemy import select, func, case, extract
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.core.database import get_db
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from app.core.security import get_current_user
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from app.models.user import User
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from app.models.ticket import Ticket
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from app.models.instance import Instance
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from app.models.audit_log import AuditLog
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from app.models.query_history import QueryHistory
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from app.schemas.dashboard import DashboardStats, TrendData, TrendPoint
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router = APIRouter(prefix="/dashboard", tags=["仪表盘"])
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@router.get("/stats", response_model=DashboardStats)
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async def get_stats(
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db: AsyncSession = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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now = datetime.now(timezone.utc)
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month_ago = now - timedelta(days=30)
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today_start = now.replace(hour=0, minute=0, second=0, microsecond=0)
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ticket_total = (await db.execute(select(func.count(Ticket.id)))).scalar() or 0
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ticket_pending = (await db.execute(
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select(func.count(Ticket.id)).where(Ticket.status.in_(["pending", "reviewing"]))
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)).scalar() or 0
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ticket_month = (await db.execute(
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select(func.count(Ticket.id)).where(Ticket.create_time >= month_ago)
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)).scalar() or 0
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ticket_executing = (await db.execute(
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select(func.count(Ticket.id)).where(Ticket.status == "executing")
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)).scalar() or 0
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instance_total = (await db.execute(select(func.count(Instance.id)))).scalar() or 0
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instance_online = (await db.execute(
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select(func.count(Instance.id)).where(Instance.status == "connected")
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)).scalar() or 0
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user_total = (await db.execute(
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select(func.count(User.id)).where(User.is_active == True)
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)).scalar() or 0
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queries_today = (await db.execute(
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select(func.count(QueryHistory.id)).where(
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QueryHistory.created_at >= today_start,
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)
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)).scalar() or 0
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# --- 查询统计 ---
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qh_today = select(QueryHistory).where(QueryHistory.created_at >= today_start)
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total_q = (await db.execute(
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select(func.count(QueryHistory.id))
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)).scalar() or 0
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avg_time = (await db.execute(
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select(func.avg(QueryHistory.execution_time_ms))
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)).scalar() or 0
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slow_count = (await db.execute(
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select(func.count(QueryHistory.id)).where(QueryHistory.execution_time_ms > 1000)
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)).scalar() or 0
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# 按数据库类型分布
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type_rows = (await db.execute(
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select(QueryHistory.db_type, func.count(QueryHistory.id).label('cnt'))
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.group_by(QueryHistory.db_type)
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)).all()
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type_distribution = [
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{"label": row[0] or "unknown", "count": row[1]}
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for row in type_rows
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]
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from app.schemas.dashboard import QueryStatsData
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query_stats = QueryStatsData(
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total=total_q,
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avg_time_ms=int(avg_time),
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slow_count=slow_count,
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type_distribution=type_distribution,
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)
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return DashboardStats(
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ticket_total=ticket_total,
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ticket_pending=ticket_pending,
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ticket_month=ticket_month,
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ticket_executing=ticket_executing,
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instance_total=instance_total,
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instance_online=instance_online,
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user_total=user_total,
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queries_today=queries_today,
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query_stats=query_stats,
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)
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@router.get("/trend", response_model=TrendData)
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async def get_trend(
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days: int = Query(7, ge=1, le=90),
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db: AsyncSession = Depends(get_db),
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current_user: User = Depends(get_current_user),
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):
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"""工单趋势数据 — 按天聚合最近 N 天的提交/成功/失败数"""
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now = datetime.now(timezone.utc)
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start = now - timedelta(days=days)
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# 按天聚合工单数
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rows = (await db.execute(
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select(
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func.date(Ticket.create_time).label('d'),
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func.count(Ticket.id).label('total'),
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func.sum(case((Ticket.status.in_(['completed', 'success']), 1), else_=0)).label('success'),
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func.sum(case((Ticket.status.in_(['failed', 'rejected']), 1), else_=0)).label('failed'),
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)
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.where(Ticket.create_time >= start)
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.group_by(func.date(Ticket.create_time))
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.order_by(func.date(Ticket.create_time))
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)).all()
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# 构建日期映射
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data_map = {}
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for row in rows:
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d = str(row[0])
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data_map[d] = {"submitted": row[1], "success": int(row[2] or 0), "failed": int(row[3] or 0)}
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# 填充缺失日期
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items = []
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for i in range(days):
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dt = (start + timedelta(days=i)).strftime('%Y-%m-%d')
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d = data_map.get(dt, {"submitted": 0, "success": 0, "failed": 0})
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label = dt[5:] # MM-DD
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items.append(TrendPoint(date=label, **d))
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return TrendData(items=items)
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