feat(分组权限): 统计接口接入数据范围（dashboard / analytics / screen 共 20 个路由）
这三组接口此前是「上帝视角」且**匿名可访问**，现在全部挂 get_data_scope —— 既要求登录、又按业务分组范围过滤。顺带堵上了 AGENTS.md 点名的风险： /dashboard/people-history/export 此前匿名即可批量导出全员工时台账。 dashboard（11 个函数 / 24 处注入） · Product 主体 → product_where()；Task、TaskLog 主体 → 先 join(Product) 再 task_where() · 「卡片数字」与「下钻明细」成对出现的地方用同一谓词，避免「按钮显示 2、点开却是 0 条」 · get_user_operations 的 func.count() 改为 func.count(TaskLog.id) —— 显式化，不依赖 join 形状（当前是 many-to-one 不会放大，但这样写更稳） · unread_notif **刻意不过滤**：Notification.task_id 可空，按 Product 过滤会漏掉 无任务关联的提醒（就地注释说明） · get_my_stats 本轮不动 —— 它按本人归因，语义上不受分组影响 analytics（4 个函数 / 9 条语句） · get_analytics_options 的 4 条独立语句全部处理 —— 它是筛选栏下拉的选项源， 不过滤的话维修组能在下拉里看到生产组的人（最易漏的一处） · get_device_records 的 product_id 查号是安全闸：范围外 SN 查不出 → 直接返回 [] screen（3 个函数） · month_production **不做特判** —— 维修组的「本月生产数」本来就该是 0 · get_wip_distribution 按范围裁剪工序柱子，但坚持「恒 0 才裁、有数必现」， 保证 total == sum(items) 在任何 scope 下都成立 实测（17 个端点）：超管全部 200、匿名全部 401。 造 1 生产 + 1 售后产品后： 超管 products=2 / wip-matrix 2 行 / options 2 个型号 生产组 products=1 / wip-matrix 1 行 / options 1 个型号 维修组 products=1 / wip-matrix 1 行 / options 1 个型号 列表与统计口径一致；未分组用户在过渡期开关下仍走 ungrouped_fallback。 测试数据已还原。
This commit is contained in:
@ -1,10 +1,16 @@
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"""效能分析 API — ECharts 数据源（个人能力图谱 / 设备流转对比 / 筛选选项）"""
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"""效能分析 API — ECharts 数据源（个人能力图谱 / 设备流转对比 / 筛选选项）
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⚠️ 2026-09 起不再是「上帝视角」：所有端点都挂了 get_data_scope，
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结果按当前用户的业务分组范围过滤（超管不受限），且不再允许匿名访问。
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"""
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from datetime import datetime
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from fastapi import APIRouter, Depends, Query
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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.deps import get_data_scope
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from app.services.data_scope_service import DataScope
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from app.services.analytics_service import (
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get_capability_profile, CapabilityResponse,
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get_flow_compare, FlowResponse,
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@ -23,14 +29,15 @@ async def capability_profile(
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until: str | None = Query(None, description="截止日期 ISO"),
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mode: str = Query("workdays", description="耗时口径: workdays(工作小时,默认) / natural(自然小时)"),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""个人能力图谱 — X 轴=设备身份证，分组柱状图（单台设备总耗时）。"""
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"""个人能力图谱 — X 轴=设备身份证，分组柱状图（单台设备总耗时），按当前用户数据范围过滤。"""
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since_dt = datetime.fromisoformat(since) if since else None
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until_dt = datetime.fromisoformat(until) if until else None
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ids = [s.strip() for s in assignee_ids.split(",") if s.strip()] if assignee_ids else None
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specs = [s.strip() for s in spec_models.split(",") if s.strip()] if spec_models else None
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return await get_capability_profile(
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db, assignee_ids=ids, spec_models=specs,
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db, scope, assignee_ids=ids, spec_models=specs,
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since=since_dt, until=until_dt, mode=mode,
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)
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@ -43,13 +50,14 @@ async def flow_compare(
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since: str | None = Query(None, description="起始日期 ISO"),
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until: str | None = Query(None, description="截止日期 ISO"),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""设备流转对比 — 每台设备各操作人耗时（堆叠柱状，按人堆叠，识别瓶颈）。"""
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"""设备流转对比 — 每台设备各操作人耗时（堆叠柱状，按人堆叠，识别瓶颈），按当前用户数据范围过滤。"""
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sns = [s.strip() for s in product_sns.split(",") if s.strip()] if product_sns else None
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specs = [s.strip() for s in spec_models.split(",") if s.strip()] if spec_models else None
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since_dt = datetime.fromisoformat(since) if since else None
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until_dt = datetime.fromisoformat(until) if until else None
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return await get_flow_compare(db, product_sns=sns, spec_models=specs, mode=mode, since=since_dt, until=until_dt)
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return await get_flow_compare(db, scope, product_sns=sns, spec_models=specs, mode=mode, since=since_dt, until=until_dt)
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@router.get("/options", response_model=AnalyticsOptions)
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@ -57,11 +65,12 @@ async def analytics_options(
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assignee_ids: str | None = Query(None, description="负责人ID，逗号分隔（联动过滤型号）"),
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spec_models: str | None = Query(None, description="规格型号，逗号分隔（联动过滤人员）"),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""顶部筛选栏选项 — 负责人 + 规格型号，支持动态联动。"""
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"""顶部筛选栏选项 — 负责人 + 规格型号 + 设备字典，支持动态联动；按当前用户数据范围过滤。"""
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ids = [s.strip() for s in assignee_ids.split(",") if s.strip()] if assignee_ids else None
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specs = [s.strip() for s in spec_models.split(",") if s.strip()] if spec_models else None
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return await get_analytics_options(db, assignee_ids=ids, spec_models=specs)
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return await get_analytics_options(db, scope, assignee_ids=ids, spec_models=specs)
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@router.get("/device-records", response_model=list[DeviceRecord])
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@ -69,7 +78,8 @@ async def device_records(
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product_sn: str = Query(..., description="设备身份证"),
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assignee_ids: str | None = Query(None, description="负责人ID，逗号分隔（可选，用于过滤）"),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""某台设备的任务备注记录（含图片）；可选按负责人过滤。"""
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"""某台设备的任务备注记录（含图片）；可选按负责人过滤；范围外设备返回空。"""
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ids = [s.strip() for s in assignee_ids.split(",") if s.strip()] if assignee_ids else None
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return await get_device_records(db, product_sn, assignee_ids=ids)
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return await get_device_records(db, scope, product_sn, assignee_ids=ids)
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@ -1,10 +1,18 @@
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"""Dashboard API — 上帝视角（全厂数据，无用户过滤）"""
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"""Dashboard API — 管理看板
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⚠️ 2026-09 起不再是「上帝视角」：所有端点都挂了 get_data_scope，
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结果按当前用户的业务分组范围过滤（超管不受限）。
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这同时把这些接口从**匿名可访问**变成了需要登录 —— 顺带堵上了
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`/people-history/export` 匿名批量导出全员工时台账的已知风险。
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"""
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import io
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from datetime import datetime
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from fastapi import APIRouter, Depends, Query
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from fastapi.responses import StreamingResponse
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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.deps import get_data_scope
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from app.services.data_scope_service import DataScope
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from app.core.time_utils import BEIJING_TZ
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from app.services.dashboard_service import (
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get_dashboard_stats, DashboardStats,
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@ -41,16 +49,17 @@ async def dashboard_stats(
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since: str | None = Query(None, description="起始日期 ISO 如 2026-08-01T00:00:00"),
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until: str | None = Query(None, description="截止日期 ISO"),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""
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全局统计（上帝视角）。
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统计概览（按当前用户的数据范围）。
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时间筛选仅影响 COMPLETED / REJECTED 计数；
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PENDING / WIP / 总数永远返回实时快照。
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"""
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since_dt = datetime.fromisoformat(since) if since else None
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until_dt = datetime.fromisoformat(until) if until else None
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return await get_dashboard_stats(db, since=since_dt, until=until_dt)
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return await get_dashboard_stats(db, scope, since=since_dt, until=until_dt)
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@router.get("/my-stats", response_model=MyStats)
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@ -77,9 +86,10 @@ async def my_stats(
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async def wip_tasks(
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limit: int = Query(500, ge=1, le=1000, description="防御性安全上限；默认足以覆盖全部在制品"),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""在制品看板 — 永远实时的 PENDING/WIP 任务（默认全量，不再按 20 条静默截断）"""
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return await get_wip_tasks(db, limit)
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return await get_wip_tasks(db, scope, limit)
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@router.get("/completed-tasks", response_model=list[CompletedTask])
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@ -88,11 +98,12 @@ async def completed_tasks(
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until: str | None = Query(None, description="截止日期 ISO"),
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limit: int = Query(200, ge=1, le=500),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""流转完成率下钻 — 按时段查询已完成任务明细"""
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since_dt = datetime.fromisoformat(since) if since else None
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until_dt = datetime.fromisoformat(until) if until else None
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return await get_completed_tasks(db, since=since_dt, until=until_dt, limit=limit)
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return await get_completed_tasks(db, scope, since=since_dt, until=until_dt, limit=limit)
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@router.get("/rejected-tasks", response_model=list[RejectedTask])
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@ -101,11 +112,12 @@ async def rejected_tasks(
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until: str | None = Query(None, description="截止日期 ISO"),
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limit: int = Query(200, ge=1, le=500),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""驳回/返工下钻 — 按时段查询被驳回任务明细（含返工去向）"""
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since_dt = datetime.fromisoformat(since) if since else None
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until_dt = datetime.fromisoformat(until) if until else None
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return await get_rejected_tasks(db, since=since_dt, until=until_dt, limit=limit)
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return await get_rejected_tasks(db, scope, since=since_dt, until=until_dt, limit=limit)
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@router.get("/user-operations", response_model=list[UserOperation])
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@ -113,11 +125,12 @@ async def user_operations(
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since: str | None = Query(None, description="起始日期 ISO 如 2026-08-01T00:00:00"),
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until: str | None = Query(None, description="截止日期 ISO"),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""人员操作统计 — 按人聚合 接收/转交/上传备注 次数，按时段过滤"""
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since_dt = datetime.fromisoformat(since) if since else None
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until_dt = datetime.fromisoformat(until) if until else None
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return await get_user_operations(db, since=since_dt, until=until_dt)
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return await get_user_operations(db, scope, since=since_dt, until=until_dt)
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@router.get("/user-operations/detail", response_model=list[OperationDetail])
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@ -127,12 +140,13 @@ async def user_operations_detail(
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since: str | None = Query(None, description="起始日期 ISO"),
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until: str | None = Query(None, description="截止日期 ISO"),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""人员操作明细下钻 — 某人在指定时段的接收/转交/上传备注明细"""
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since_dt = datetime.fromisoformat(since) if since else None
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until_dt = datetime.fromisoformat(until) if until else None
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return await get_user_operation_detail(
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db, user_id, action_type, since=since_dt, until=until_dt,
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db, user_id, action_type, scope, since=since_dt, until=until_dt,
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)
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@ -142,11 +156,12 @@ async def wip_matrix(
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since: str | None = Query(None, description="起始日期 ISO"),
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until: str | None = Query(None, description="截止日期 ISO"),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""生产分布透视表 — 规格型号 × 人员/工序 的设备数量交叉聚合（含已完成/已入库/已出库）"""
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since_dt = datetime.fromisoformat(since) if since else None
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until_dt = datetime.fromisoformat(until) if until else None
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return await get_wip_matrix(db, dimension=dimension, since=since_dt, until=until_dt)
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return await get_wip_matrix(db, scope, dimension=dimension, since=since_dt, until=until_dt)
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@router.get("/wip-matrix/detail", response_model=list[WipMatrixDetailRow])
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@ -156,19 +171,21 @@ async def wip_matrix_detail(
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since: str | None = Query(None, description="起始日期 ISO"),
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until: str | None = Query(None, description="截止日期 ISO"),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""WIP 矩阵单元格下钻 — 返回某 规格型号×工序 交叉点下的设备明细"""
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since_dt = datetime.fromisoformat(since) if since else None
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until_dt = datetime.fromisoformat(until) if until else None
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return await get_wip_matrix_detail(db, spec_model=spec, process=process, since=since_dt, until=until_dt)
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return await get_wip_matrix_detail(db, scope, spec_model=spec, process=process, since=since_dt, until=until_dt)
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@router.get("/people-workload", response_model=list[PersonWorkload])
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async def people_workload(
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""人员负载 — 按负责人聚合当前在制品设备数（独立人员看板）"""
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return await get_people_workload(db)
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return await get_people_workload(db, scope)
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@router.get("/people-history", response_model=list[PersonHistoryRecord])
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@ -180,12 +197,13 @@ async def people_history(
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product_sn: str | None = Query(None, description="身份证（模糊）"),
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task_name: str | None = Query(None, description="任务名（模糊）"),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""人员效能与工时台账 — 平铺 Task 明细，多维筛选 + 时间交集"""
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since_dt = datetime.fromisoformat(since) if since else None
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until_dt = datetime.fromisoformat(until) if until else None
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return await get_people_history(
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db, since=since_dt, until=until_dt,
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db, scope, since=since_dt, until=until_dt,
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assignee_id=assignee_id, spec_model=spec_model,
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product_sn=product_sn, task_name=task_name,
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)
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@ -200,12 +218,17 @@ async def export_people_history(
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product_sn: str | None = Query(None, description="身份证（模糊）"),
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task_name: str | None = Query(None, description="任务名（模糊）"),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""导出工时台账为 Excel（与查询接口相同筛选条件）"""
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"""导出工时台账为 Excel（与查询接口相同筛选条件）
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⚠️ 本接口此前是**匿名可访问**的，能批量导出全员工时台账。挂上 get_data_scope
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后既要求登录、又按业务分组范围过滤 —— 这是本次改造顺带堵上的已知风险。
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"""
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since_dt = datetime.fromisoformat(since) if since else None
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until_dt = datetime.fromisoformat(until) if until else None
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records = await get_people_history(
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db, since=since_dt, until=until_dt,
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db, scope, since=since_dt, until=until_dt,
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assignee_id=assignee_id, spec_model=spec_model,
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product_sn=product_sn, task_name=task_name,
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)
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@ -247,11 +270,12 @@ async def dashboard_messages(
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skip: int = Query(0, ge=0),
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limit: int = Query(30, ge=1, le=200),
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db: AsyncSession = Depends(get_db),
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scope: DataScope = Depends(get_data_scope),
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):
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"""
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协同留言搜索（上帝视角 — 全厂所有产品留言）。
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协同留言搜索（按当前用户的数据范围过滤）。
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关联 Product 表返回 serial_number + material_name，
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按时间倒序排列。
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"""
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return await search_product_messages(db, keyword=keyword, skip=skip, limit=limit)
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return await search_product_messages(db, scope, keyword=keyword, skip=skip, limit=limit)
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@ -4,11 +4,16 @@
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与 /dashboard 的区别：/dashboard 面向 PC 后台明细下钻（返回大列表），
|
||||
/screen 只返回图表直接可用的扁平聚合数据，字段少、无分页、供高频轮询。
|
||||
|
||||
⚠️ 2026-09 起不再是「上帝视角」：三个端点都挂了 get_data_scope，
|
||||
结果按当前用户的业务分组范围过滤（超管不受限），且不再允许匿名访问。
|
||||
"""
|
||||
from fastapi import APIRouter, Depends, Query
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
|
||||
from app.core.database import get_db
|
||||
from app.core.deps import get_data_scope
|
||||
from app.services.data_scope_service import DataScope
|
||||
from app.services.screen_service import (
|
||||
get_monthly_metrics, MonthlyMetrics,
|
||||
get_wip_distribution, WipDistributionResponse,
|
||||
@ -19,34 +24,42 @@ router = APIRouter(prefix="/screen", tags=["大屏统计"])
|
||||
|
||||
|
||||
@router.get("/monthly-metrics", response_model=MonthlyMetrics)
|
||||
async def monthly_metrics(db: AsyncSession = Depends(get_db)):
|
||||
async def monthly_metrics(
|
||||
db: AsyncSession = Depends(get_db),
|
||||
scope: DataScope = Depends(get_data_scope),
|
||||
):
|
||||
"""
|
||||
当月吞吐 — 大屏顶部四张数字卡。
|
||||
当月吞吐 — 大屏顶部四张数字卡（按当前用户的数据范围）。
|
||||
|
||||
返回：本月生产流转 / 本月已入库 / 本月已出库 / 本月返厂回流。
|
||||
统计区间为北京时间当月 1 日 00:00 至此刻。
|
||||
"""
|
||||
return await get_monthly_metrics(db)
|
||||
return await get_monthly_metrics(db, scope)
|
||||
|
||||
|
||||
@router.get("/wip-distribution", response_model=WipDistributionResponse)
|
||||
async def wip_distribution(db: AsyncSession = Depends(get_db)):
|
||||
async def wip_distribution(
|
||||
db: AsyncSession = Depends(get_db),
|
||||
scope: DataScope = Depends(get_data_scope),
|
||||
):
|
||||
"""
|
||||
工序积压分布 — 当前未完结设备按 overall_status 聚合的**纯数量**。
|
||||
工序积压分布 — 当前数据范围内未完结设备按 overall_status 聚合的**纯数量**。
|
||||
|
||||
返回固定阶段列表（含 0 值），保证柱状图类目稳定、不因缺数据而塌陷。
|
||||
返回固定阶段列表（含 0 值），保证柱状图类目稳定、不因缺数据而塌陷；
|
||||
工序柱本身也按数据范围裁剪（不属于本组阶段的工序不画）。
|
||||
"""
|
||||
return await get_wip_distribution(db)
|
||||
return await get_wip_distribution(db, scope)
|
||||
|
||||
|
||||
@router.get("/active-users", response_model=ActiveUsersResponse)
|
||||
async def active_users(
|
||||
top_n: int = Query(5, ge=1, le=20, description="返回的活跃人员数量"),
|
||||
db: AsyncSession = Depends(get_db),
|
||||
scope: DataScope = Depends(get_data_scope),
|
||||
):
|
||||
"""
|
||||
本月系统使用活跃度排行 — 接收 / 转交 / 上传备注次数。
|
||||
本月系统使用活跃度排行 — 接收 / 转交 / 上传备注次数（按当前用户的数据范围）。
|
||||
|
||||
桥接 /dashboard/user-operations 的统计口径，仅返回本月确实有操作的人员。
|
||||
"""
|
||||
return await get_active_users(db, top_n=top_n)
|
||||
return await get_active_users(db, scope, top_n=top_n)
|
||||
|
||||
@ -8,6 +8,9 @@
|
||||
耗时口径：
|
||||
- 单台真实耗时 = (completed_at or now) - (received_at or created_at)，单位小时。
|
||||
- naive datetime 按 UTC 处理，统一换算北京时间。
|
||||
|
||||
2026-09 起不再是「上帝视角」：统计函数一律接收调用方解析好的 DataScope，
|
||||
查询里按 Product.lifecycle_phase 过滤（谓词只在 data_scope_service 生成，见该模块红线）。
|
||||
"""
|
||||
from datetime import datetime, timezone
|
||||
|
||||
@ -15,6 +18,8 @@ from sqlalchemy import select, func
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
from pydantic import BaseModel
|
||||
|
||||
from app.services.data_scope_service import DataScope
|
||||
|
||||
|
||||
# ============================================================
|
||||
# Schemas（与前端 src/services/analyticsApi.ts 对齐）
|
||||
@ -133,6 +138,7 @@ def _duration_hours(start: datetime | None, end: datetime, holidays: set = None,
|
||||
|
||||
async def get_capability_profile(
|
||||
db: AsyncSession,
|
||||
scope: DataScope,
|
||||
assignee_ids: list[str] | None = None,
|
||||
spec_models: list[str] | None = None,
|
||||
since: datetime | None = None,
|
||||
@ -144,6 +150,8 @@ async def get_capability_profile(
|
||||
按 (负责人, 设备) 分组，累加该人在该设备所有工序的耗时，
|
||||
series.data 与 categories 严格对齐，未触及设备补 0。
|
||||
耗时口径：(coalesce(completed_at, now) - coalesce(received_at, created_at))。
|
||||
|
||||
按当前用户的业务分组数据范围过滤。
|
||||
"""
|
||||
from app.models.task import (
|
||||
Task, TASK_STATUS_WIP, TASK_STATUS_PENDING, TASK_STATUS_COMPLETED,
|
||||
@ -169,6 +177,7 @@ async def get_capability_profile(
|
||||
.where(
|
||||
Task.status.in_([TASK_STATUS_WIP, TASK_STATUS_PENDING, TASK_STATUS_COMPLETED]),
|
||||
Task.assignee_id.isnot(None),
|
||||
scope.task_where(), # 🚀 业务分组数据范围（已 join Product）
|
||||
)
|
||||
)
|
||||
if assignee_ids:
|
||||
@ -282,6 +291,7 @@ async def get_capability_profile(
|
||||
|
||||
async def get_flow_compare(
|
||||
db: AsyncSession,
|
||||
scope: DataScope,
|
||||
product_sns: list[str] | None = None,
|
||||
spec_models: list[str] | None = None,
|
||||
mode: str = "natural",
|
||||
@ -311,11 +321,13 @@ async def get_flow_compare(
|
||||
now = get_beijing_time()
|
||||
|
||||
if product_sns:
|
||||
# 🚀 业务分组数据范围：主体是 Product，直接挂 product_where
|
||||
# （范围外的身份证查不出来 → 与下钻接口同口径，不会泄露别组设备）
|
||||
product_rows = (await db.execute(
|
||||
select(
|
||||
Product.id, Product.serial_number, Product.external_serial,
|
||||
Product.material_name, Product.spec_model,
|
||||
).where(Product.serial_number.in_(product_sns))
|
||||
).where(Product.serial_number.in_(product_sns), scope.product_where())
|
||||
)).all()
|
||||
elif spec_models:
|
||||
latest_subq = (
|
||||
@ -332,7 +344,7 @@ async def get_flow_compare(
|
||||
Product.material_name, Product.spec_model,
|
||||
)
|
||||
.join(latest_subq, latest_subq.c.product_id == Product.id)
|
||||
.where(Product.spec_model.in_(spec_models))
|
||||
.where(Product.spec_model.in_(spec_models), scope.product_where()) # 🚀 业务分组数据范围（主体 Product）
|
||||
.order_by(latest_subq.c.latest.desc())
|
||||
.limit(20)
|
||||
)).all()
|
||||
@ -346,16 +358,20 @@ async def get_flow_compare(
|
||||
product_ids = [r[0] for r in product_rows]
|
||||
|
||||
# ── 候选设备的全部任务（含工序名，用于区间图） ──
|
||||
# 🚀 业务分组数据范围：product_ids 已来自上方受限结果，这里把口径写全
|
||||
# （Task 主体，必须先 join Product 再挂 task_where；结果集不变）
|
||||
task_rows = (await db.execute(
|
||||
select(
|
||||
Task.product_id, Task.assignee_id, Task.task_name,
|
||||
Task.received_at, Task.created_at, Task.completed_at,
|
||||
Task.task_type,
|
||||
)
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(
|
||||
Task.product_id.in_(product_ids),
|
||||
Task.status.in_([TASK_STATUS_WIP, TASK_STATUS_PENDING, TASK_STATUS_COMPLETED]),
|
||||
Task.assignee_id.isnot(None),
|
||||
scope.task_where(),
|
||||
)
|
||||
)).all()
|
||||
|
||||
@ -497,28 +513,39 @@ async def get_flow_compare(
|
||||
|
||||
async def get_device_records(
|
||||
db: AsyncSession,
|
||||
scope: DataScope,
|
||||
product_sn: str,
|
||||
assignee_ids: list[str] | None = None,
|
||||
) -> list[DeviceRecord]:
|
||||
"""查询某台设备（身份证）的所有任务备注记录，含图片，按时间倒序。
|
||||
可选按负责人过滤（assignee_ids）。"""
|
||||
可选按负责人过滤（assignee_ids）。
|
||||
|
||||
按当前用户的业务分组数据范围过滤 —— 范围外的身份证查不出 product_id，
|
||||
直接返回空列表（否则维修组拿生产组的身份证就能读到别组的备注与照片）。
|
||||
"""
|
||||
import json
|
||||
from app.models.task import Task, TaskRecord
|
||||
from app.models.product import Product
|
||||
|
||||
# 🚀 业务分组数据范围：主体 Product，范围外查不出 product_id → 下方直接空返回
|
||||
product_id = await db.scalar(
|
||||
select(Product.id).where(Product.serial_number == product_sn)
|
||||
select(Product.id).where(
|
||||
Product.serial_number == product_sn,
|
||||
scope.product_where(),
|
||||
)
|
||||
)
|
||||
if not product_id:
|
||||
return []
|
||||
|
||||
# 🚀 业务分组数据范围：product_id 已受限，这里把口径写全（Task 主体，先 join Product）
|
||||
stmt = (
|
||||
select(
|
||||
TaskRecord.remark, TaskRecord.images, TaskRecord.created_at,
|
||||
Task.task_name, Task.assignee_id, Task.status,
|
||||
)
|
||||
.join(Task, TaskRecord.task_id == Task.id)
|
||||
.where(Task.product_id == product_id)
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(Task.product_id == product_id, scope.task_where())
|
||||
)
|
||||
if assignee_ids:
|
||||
stmt = stmt.where(Task.assignee_id.in_(assignee_ids))
|
||||
@ -558,31 +585,45 @@ async def get_device_records(
|
||||
|
||||
async def get_analytics_options(
|
||||
db: AsyncSession,
|
||||
scope: DataScope,
|
||||
assignee_ids: list[str] | None = None,
|
||||
spec_models: list[str] | None = None,
|
||||
) -> AnalyticsOptions:
|
||||
"""返回筛选栏选项，支持动态联动：
|
||||
- 传入 spec_models：只返回碰过这些型号的人；
|
||||
- 传入 assignee_ids：只返回这些人处理过的型号；
|
||||
- devices：根据筛选条件返回关联设备（无筛选则返回最近流转的设备）。"""
|
||||
- devices：根据筛选条件返回关联设备（无筛选则返回最近流转的设备）。
|
||||
|
||||
⚠️ 本函数是**筛选栏下拉的选项源**，四条语句（负责人 / 型号 / 设备，各含
|
||||
带筛选与不带筛选两个分支）必须条条挂上数据范围谓词 —— 漏掉任意一条，
|
||||
维修组就能在下拉里看到生产组的人与型号，点开却是空的。
|
||||
"""
|
||||
from app.models.task import Task
|
||||
from app.models.product import Product
|
||||
|
||||
# ── 负责人：从 tasks 去重（可选按 spec_models 过滤） ──
|
||||
if spec_models:
|
||||
# 🚀 业务分组数据范围：已 join Product，直接挂 task_where
|
||||
assignee_stmt = (
|
||||
select(Task.assignee_id)
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(
|
||||
Task.assignee_id.isnot(None),
|
||||
Product.spec_model.in_(spec_models),
|
||||
scope.task_where(),
|
||||
)
|
||||
.distinct()
|
||||
)
|
||||
else:
|
||||
# 🚀 业务分组数据范围：本分支原先没有 join，必须补上 Product 才能挂
|
||||
# task_where（tasks 表没有 lifecycle_phase）
|
||||
assignee_stmt = (
|
||||
select(Task.assignee_id)
|
||||
.where(Task.assignee_id.isnot(None))
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(
|
||||
Task.assignee_id.isnot(None),
|
||||
scope.task_where(),
|
||||
)
|
||||
.distinct()
|
||||
)
|
||||
assignee_rows = (await db.execute(assignee_stmt)).all()
|
||||
@ -600,6 +641,7 @@ async def get_analytics_options(
|
||||
|
||||
# ── 规格型号 + 物料名（可选按 assignee_ids 过滤；同型号取首个非空物料名） ──
|
||||
if assignee_ids:
|
||||
# 🚀 业务分组数据范围：主体 Product，直接挂 product_where
|
||||
spec_stmt = (
|
||||
select(Product.spec_model, Product.material_name)
|
||||
.join(Task, Task.product_id == Product.id)
|
||||
@ -607,13 +649,19 @@ async def get_analytics_options(
|
||||
Product.spec_model.isnot(None),
|
||||
func.trim(Product.spec_model) != "",
|
||||
Task.assignee_id.in_(assignee_ids),
|
||||
scope.product_where(),
|
||||
)
|
||||
.distinct()
|
||||
)
|
||||
else:
|
||||
# 🚀 业务分组数据范围：主体 Product，直接挂 product_where
|
||||
spec_stmt = (
|
||||
select(Product.spec_model, Product.material_name)
|
||||
.where(Product.spec_model.isnot(None), func.trim(Product.spec_model) != "")
|
||||
.where(
|
||||
Product.spec_model.isnot(None),
|
||||
func.trim(Product.spec_model) != "",
|
||||
scope.product_where(),
|
||||
)
|
||||
.distinct()
|
||||
)
|
||||
spec_rows = (await db.execute(spec_stmt)).all()
|
||||
@ -632,10 +680,12 @@ async def get_analytics_options(
|
||||
|
||||
# ── 设备字典（可选按 assignee_ids / spec_models 过滤；无筛选返回最近流转 100 台） ──
|
||||
if assignee_ids or spec_models:
|
||||
# 🚀 业务分组数据范围：主体 Product，直接挂 product_where
|
||||
# （即使上面 join 了 Task，产品去重后条数仍由 Product 决定）
|
||||
device_stmt = select(
|
||||
Product.serial_number, Product.external_serial,
|
||||
Product.material_name, Product.spec_model,
|
||||
)
|
||||
).where(scope.product_where())
|
||||
if assignee_ids:
|
||||
device_stmt = device_stmt.join(
|
||||
Task, Task.product_id == Product.id
|
||||
@ -658,6 +708,7 @@ async def get_analytics_options(
|
||||
Product.material_name, Product.spec_model,
|
||||
)
|
||||
.join(latest_subq, latest_subq.c.product_id == Product.id)
|
||||
.where(scope.product_where()) # 🚀 业务分组数据范围（主体 Product）
|
||||
.order_by(latest_subq.c.latest.desc())
|
||||
.limit(100)
|
||||
)
|
||||
|
||||
@ -1,4 +1,9 @@
|
||||
"""Dashboard 统计服务 — 上帝视角（全厂全系统数据，不按用户过滤）"""
|
||||
"""Dashboard 统计服务 — 按当前用户的**业务分组数据范围**过滤(超管不受限)
|
||||
|
||||
2026-09 起不再是「上帝视角」：统计函数一律接收调用方解析好的 DataScope，
|
||||
查询里按 Product.lifecycle_phase 过滤（谓词只在 data_scope_service 生成，见该模块红线）。
|
||||
唯一例外见 get_dashboard_stats 的 unread_notif（刻意不过滤，理由就地写明）。
|
||||
"""
|
||||
from datetime import datetime
|
||||
from sqlalchemy import select, func, or_
|
||||
from sqlalchemy.ext.asyncio import AsyncSession
|
||||
@ -6,6 +11,7 @@ from pydantic import BaseModel
|
||||
|
||||
from app.core.config import settings
|
||||
from app.core.lifecycle import normalize_after_sales_step
|
||||
from app.services.data_scope_service import DataScope
|
||||
|
||||
|
||||
# ============================================================
|
||||
@ -242,11 +248,12 @@ def _rework_visible_condition(
|
||||
|
||||
async def get_dashboard_stats(
|
||||
db: AsyncSession,
|
||||
scope: DataScope,
|
||||
since: datetime | None = None,
|
||||
until: datetime | None = None,
|
||||
) -> DashboardStats:
|
||||
"""
|
||||
上帝视角 — 全厂全系统统计。
|
||||
看板统计 — 按当前用户的业务分组数据范围过滤。
|
||||
|
||||
时间筛选规则：
|
||||
- PENDING / WIP / 总数：永远忽略时间筛选，返回实时快照。
|
||||
@ -305,36 +312,63 @@ async def get_dashboard_stats(
|
||||
select(Task.id).where(*done_time_conds).exists(),
|
||||
)
|
||||
|
||||
p_unfinished = await db.scalar(select(func.count(Product.id)).where(not_finished)) or 0
|
||||
p_progress = await db.scalar(
|
||||
select(func.count(Product.id)).where(not_finished, has_active_task)
|
||||
# 🚀 业务分组数据范围：产品三态计数均以 Product 为主体，直接挂 product_where
|
||||
p_unfinished = await db.scalar(
|
||||
select(func.count(Product.id)).where(not_finished, scope.product_where())
|
||||
) or 0
|
||||
p_progress = await db.scalar(
|
||||
select(func.count(Product.id)).where(not_finished, has_active_task, scope.product_where())
|
||||
) or 0
|
||||
p_done = await db.scalar(
|
||||
select(func.count(Product.id)).where(done_in_range, scope.product_where())
|
||||
) or 0
|
||||
p_done = await db.scalar(select(func.count(Product.id)).where(done_in_range)) or 0
|
||||
|
||||
# 待流转 = 未完结 - 在制；展示总数 = 未完结 + 所选时段已完结
|
||||
# （三段互斥，保证进度条总和 = 展示总数）
|
||||
p_pending = max(p_unfinished - p_progress, 0)
|
||||
p_total = p_unfinished + p_done
|
||||
|
||||
# ── 任务实时快照（PENDING/WIP — 永远不过滤） ──
|
||||
t_pending = await db.scalar(select(func.count(Task.id)).where(Task.status == TASK_STATUS_PENDING))
|
||||
t_progress = await db.scalar(select(func.count(Task.id)).where(Task.status == TASK_STATUS_WIP))
|
||||
# ── 任务实时快照（PENDING/WIP — 永不受时间筛选，但受业务分组数据范围约束） ──
|
||||
# 🚀 业务分组数据范围：Task 为主体，先 join Product 再 task_where（tasks 表无 lifecycle_phase）
|
||||
t_pending = await db.scalar(
|
||||
select(func.count(Task.id))
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(Task.status == TASK_STATUS_PENDING, scope.task_where())
|
||||
)
|
||||
t_progress = await db.scalar(
|
||||
select(func.count(Task.id))
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(Task.status == TASK_STATUS_WIP, scope.task_where())
|
||||
)
|
||||
|
||||
# 返工数不再是无边界的全时段快照：未完结卡点永远计入，已了结的只算本月。
|
||||
# 与 get_rejected_tasks 的 kind="rework" 共用同一份可见性条件，
|
||||
# 保证「品质异常」卡片数字与点开后的明细条数对得上。
|
||||
from app.services.screen_service import _month_bounds
|
||||
month_start_utc, _, _ = _month_bounds()
|
||||
# 🚀 业务分组数据范围：Task 为主体，先 join Product 再 task_where
|
||||
t_rework = await db.scalar(
|
||||
select(func.count(Task.id)).where(
|
||||
select(func.count(Task.id))
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(
|
||||
Task.is_rework.is_(True),
|
||||
_rework_visible_condition(month_start_utc, since, until),
|
||||
scope.task_where(),
|
||||
)
|
||||
)
|
||||
|
||||
# ── 任务已完成/驳回（时间可过滤） ──
|
||||
t_done_q = select(func.count(Task.id)).where(Task.status == TASK_STATUS_COMPLETED)
|
||||
t_rej_q = select(func.count(Task.id)).where(Task.status == TASK_STATUS_REJECTED)
|
||||
# 🚀 业务分组数据范围：同上，两条独立语句各自挂 task_where
|
||||
t_done_q = (
|
||||
select(func.count(Task.id))
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(Task.status == TASK_STATUS_COMPLETED, scope.task_where())
|
||||
)
|
||||
t_rej_q = (
|
||||
select(func.count(Task.id))
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(Task.status == TASK_STATUS_REJECTED, scope.task_where())
|
||||
)
|
||||
if since:
|
||||
t_done_q = t_done_q.where(Task.completed_at >= since)
|
||||
t_rej_q = t_rej_q.where(Task.completed_at >= since)
|
||||
@ -348,10 +382,19 @@ async def get_dashboard_stats(
|
||||
t_total = (t_pending or 0) + (t_progress or 0) + (t_done or 0) + (t_rejected or 0)
|
||||
|
||||
# ── 通知 & 留言（实时快照） ──
|
||||
# 🚀 业务分组数据范围：**有意不过滤** —— Notification.task_id 允许为空
|
||||
# （ondelete=SET NULL，且留言提醒类通知本就不挂任务），按 Product 过滤会
|
||||
# 把这些「无任务关联」的提醒整条漏掉，未读角标会凭空少几颗。
|
||||
# 这是刻意为之，不要「顺手补上」过滤。
|
||||
unread_notif = await db.scalar(
|
||||
select(func.count(Notification.id)).where(Notification.is_read.is_(False))
|
||||
)
|
||||
unread_msg = await db.scalar(select(func.count(ProductMessage.id)))
|
||||
# 🚀 业务分组数据范围：ProductMessage.product_id 非空，join Product 后按阶段过滤
|
||||
unread_msg = await db.scalar(
|
||||
select(func.count(ProductMessage.id))
|
||||
.join(Product, ProductMessage.product_id == Product.id)
|
||||
.where(scope.product_where())
|
||||
)
|
||||
|
||||
return DashboardStats(
|
||||
products_total=p_total or 0,
|
||||
@ -482,8 +525,8 @@ async def get_my_stats(
|
||||
# 在制品看板（永远实时）
|
||||
# ============================================================
|
||||
|
||||
async def get_wip_tasks(db: AsyncSession, limit: int = 500) -> list[WipTask]:
|
||||
"""在制品看板 — 永远实时的 PENDING/WIP 任务。
|
||||
async def get_wip_tasks(db: AsyncSession, scope: DataScope, limit: int = 500) -> list[WipTask]:
|
||||
"""在制品看板 — 永远实时的 PENDING/WIP 任务（按业务分组数据范围过滤）。
|
||||
|
||||
默认返回**全部**活跃任务，limit 只是防御性安全上限。
|
||||
|
||||
@ -502,10 +545,14 @@ async def get_wip_tasks(db: AsyncSession, limit: int = 500) -> list[WipTask]:
|
||||
holidays = {r[0] for r in hres}
|
||||
|
||||
# 不在 SQL 层做预取限制：排序在内存里按滞留时长进行，截断只作为上限保护
|
||||
# 🚀 业务分组数据范围：已 join Product，直接挂 task_where
|
||||
stmt = (
|
||||
select(Task, Product.serial_number, Product.external_serial, Product.material_name, Product.spec_model)
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(Task.status.in_([TASK_STATUS_PENDING, TASK_STATUS_WIP]))
|
||||
.where(
|
||||
Task.status.in_([TASK_STATUS_PENDING, TASK_STATUS_WIP]),
|
||||
scope.task_where(),
|
||||
)
|
||||
)
|
||||
result = await db.execute(stmt)
|
||||
rows = result.all()
|
||||
@ -551,19 +598,24 @@ async def get_wip_tasks(db: AsyncSession, limit: int = 500) -> list[WipTask]:
|
||||
|
||||
async def get_completed_tasks(
|
||||
db: AsyncSession,
|
||||
scope: DataScope,
|
||||
since: datetime | None = None,
|
||||
until: datetime | None = None,
|
||||
limit: int = 200,
|
||||
) -> list[CompletedTask]:
|
||||
"""按时段查询已完成任务明细（上帝视角），用于「流转完成率」卡片下钻。"""
|
||||
"""按时段查询已完成任务明细（按业务分组数据范围过滤），用于「流转完成率」卡片下钻。
|
||||
|
||||
与 get_dashboard_stats 的 t_done 同一口径 + 同一数据范围，保证点进来条数对得上。
|
||||
"""
|
||||
from app.models.task import Task, TASK_STATUS_COMPLETED
|
||||
from app.models.product import Product
|
||||
from app.core.time_utils import BEIJING_TZ
|
||||
|
||||
# 🚀 业务分组数据范围：已 join Product，直接挂 task_where
|
||||
stmt = (
|
||||
select(Task, Product.serial_number, Product.external_serial, Product.material_name, Product.spec_model)
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(Task.status == TASK_STATUS_COMPLETED)
|
||||
.where(Task.status == TASK_STATUS_COMPLETED, scope.task_where())
|
||||
)
|
||||
if since:
|
||||
stmt = stmt.where(Task.completed_at >= since)
|
||||
@ -608,11 +660,15 @@ async def get_completed_tasks(
|
||||
|
||||
async def get_rejected_tasks(
|
||||
db: AsyncSession,
|
||||
scope: DataScope,
|
||||
since: datetime | None = None,
|
||||
until: datetime | None = None,
|
||||
limit: int = 200,
|
||||
) -> list[RejectedTask]:
|
||||
"""查询驳回/返工任务明细（上帝视角），用于「驳回/返工」卡片下钻。
|
||||
"""查询驳回/返工任务明细（按业务分组数据范围过滤），用于「驳回/返工」卡片下钻。
|
||||
|
||||
⚠️ 两条语句（已驳回 / 返工）都要挂同一个 task_where，否则与
|
||||
get_dashboard_stats 的 tasks_rejected + tasks_rework 卡片数字对不上。
|
||||
|
||||
返回两类（与卡片数字 tasks_rejected + tasks_rework 口径一致）：
|
||||
- kind="rejected"：被驳回任务，按 completed_at 时间过滤
|
||||
@ -641,10 +697,11 @@ async def get_rejected_tasks(
|
||||
return dt.isoformat()
|
||||
|
||||
# ── 1. 已驳回任务（按时间过滤）──
|
||||
# 🚀 业务分组数据范围：已 join Product，直接挂 task_where
|
||||
stmt = (
|
||||
select(Task, Product.serial_number, Product.external_serial, Product.material_name, Product.spec_model)
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(Task.status == TASK_STATUS_REJECTED)
|
||||
.where(Task.status == TASK_STATUS_REJECTED, scope.task_where())
|
||||
)
|
||||
if since:
|
||||
stmt = stmt.where(Task.completed_at >= since)
|
||||
@ -659,6 +716,7 @@ async def get_rejected_tasks(
|
||||
# 统一约束 —— 未完结卡点永远展示，已了结的仅限本月（详见该函数说明）。
|
||||
from app.services.screen_service import _month_bounds
|
||||
month_start_utc, _, _ = _month_bounds()
|
||||
# 🚀 业务分组数据范围：同口径挂 task_where，保证与卡片 tasks_rework 一致
|
||||
rework_stmt = (
|
||||
select(Task, Product.serial_number, Product.external_serial, Product.material_name, Product.spec_model)
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
@ -666,6 +724,7 @@ async def get_rejected_tasks(
|
||||
Task.is_rework.is_(True),
|
||||
Task.status != TASK_STATUS_REJECTED,
|
||||
_rework_visible_condition(month_start_utc, since, until),
|
||||
scope.task_where(),
|
||||
)
|
||||
.order_by(Task.created_at.desc())
|
||||
.limit(limit)
|
||||
@ -710,9 +769,16 @@ async def get_rejected_tasks(
|
||||
rework_candidates: dict = {}
|
||||
product_ids = {t.product_id for t, *_ in rejected_rows if t.product_id}
|
||||
if product_ids:
|
||||
# 🚀 业务分组数据范围：本查询也是 Task 主体，一并挂 task_where
|
||||
# （product_ids 已来自上方受限结果，这里只是把口径写全，结果集不变）
|
||||
cand_rows = await db.execute(
|
||||
select(Task.parent_task_id, Task.product_id, Task.created_at, Task.assignee_id)
|
||||
.where(Task.is_rework.is_(True), Task.product_id.in_(product_ids))
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(
|
||||
Task.is_rework.is_(True),
|
||||
Task.product_id.in_(product_ids),
|
||||
scope.task_where(),
|
||||
)
|
||||
.order_by(Task.created_at.asc())
|
||||
)
|
||||
for parent_id, prod_id, created_at, assignee_id in cand_rows.all():
|
||||
@ -787,10 +853,11 @@ async def get_rejected_tasks(
|
||||
|
||||
async def get_user_operations(
|
||||
db: AsyncSession,
|
||||
scope: DataScope,
|
||||
since: datetime | None = None,
|
||||
until: datetime | None = None,
|
||||
) -> list[UserOperation]:
|
||||
"""上帝视角 — 统计**全部人员**的操作次数（按时段过滤）。
|
||||
"""统计**当前数据范围内人员**的操作次数（按时段过滤）。
|
||||
|
||||
返回本部门（ORG_DEPARTMENT）全部人员（该时段无操作的计 0），并追加有操作
|
||||
记录但不在人员清单中的账号（如历史/已离职）。
|
||||
@ -803,17 +870,24 @@ async def get_user_operations(
|
||||
"""
|
||||
from app.models.task_log import TaskLog
|
||||
from app.models.task import Task, TaskRecord
|
||||
from app.models.product import Product
|
||||
from app.core.mom_database import MomSessionLocal
|
||||
from sqlalchemy import text, or_
|
||||
|
||||
# ── 1. 接收 / 转交（task_logs 按 operator_id 聚合）──
|
||||
rcv = func.count().filter(TaskLog.action_type == "receive")
|
||||
cpl = func.count().filter(TaskLog.action_type == "complete")
|
||||
# ⚠️ 必须指明具体列：为接入数据范围本查询已 join Product，若写裸 count()
|
||||
# 会按 join 出的行数重复计数，卡片数字虚高。
|
||||
rcv = func.count(TaskLog.id).filter(TaskLog.action_type == "receive")
|
||||
cpl = func.count(TaskLog.id).filter(TaskLog.action_type == "complete")
|
||||
# 🚀 业务分组数据范围：TaskLog → Task → Product 两级 join 后挂 task_where
|
||||
stmt = (
|
||||
select(TaskLog.operator_id, rcv.label("receive"), cpl.label("complete"))
|
||||
.join(Task, TaskLog.task_id == Task.id)
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(
|
||||
TaskLog.action_type.in_(["receive", "complete"]),
|
||||
TaskLog.operator_id.isnot(None),
|
||||
scope.task_where(),
|
||||
)
|
||||
.group_by(TaskLog.operator_id)
|
||||
)
|
||||
@ -825,12 +899,15 @@ async def get_user_operations(
|
||||
op_map = {r[0]: (r[1] or 0, r[2] or 0) for r in op_rows}
|
||||
|
||||
# ── 2. 上传备注（task_records 按任务 assignee 归因，排除系统自动备注）──
|
||||
# 🚀 业务分组数据范围：TaskRecord 经 Task 关联到 Product 后挂 task_where
|
||||
rcd_stmt = (
|
||||
select(Task.assignee_id, func.count(TaskRecord.id))
|
||||
.join(Task, TaskRecord.task_id == Task.id)
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(
|
||||
Task.assignee_id.isnot(None),
|
||||
or_(TaskRecord.remark.is_(None), ~TaskRecord.remark.like("[%")),
|
||||
scope.task_where(),
|
||||
)
|
||||
.group_by(Task.assignee_id)
|
||||
)
|
||||
@ -896,11 +973,12 @@ async def get_user_operations(
|
||||
|
||||
async def get_wip_matrix(
|
||||
db: AsyncSession,
|
||||
scope: DataScope,
|
||||
dimension: str = "assignee",
|
||||
since: datetime | None = None,
|
||||
until: datetime | None = None,
|
||||
) -> list[WipMatrixRow]:
|
||||
"""生产分布透视表：Y=规格型号，X=人员 或 工序，单元格=设备数量。
|
||||
"""生产分布透视表：Y=规格型号，X=人员 或 工序，单元格=设备数量（按业务分组数据范围过滤）。
|
||||
|
||||
核心口径：**每台设备只统计一次**，按它「当前所处工序」归属——
|
||||
1. 取该设备最新的一条主分支任务（parent_task_id IS NULL 或 TRANSFER/RECOVERY）
|
||||
@ -927,6 +1005,9 @@ async def get_wip_matrix(
|
||||
_ActiveTask = aliased(Task, name="active_task")
|
||||
|
||||
# 每台设备按主任务创建时间倒序，取第一条即「最新主任务」
|
||||
# 🚀 业务分组数据范围：主体是 Product（outerjoin tasks 不影响主体），挂 product_where。
|
||||
# 矩阵格子的设备数与被过滤掉的设备在这里一次性拦掉，下钻（get_wip_matrix_detail）
|
||||
# 必须用同一谓词，否则「格子里有数、点进去是空的」。
|
||||
result = await db.execute(
|
||||
select(
|
||||
Product.id,
|
||||
@ -957,7 +1038,8 @@ async def get_wip_matrix(
|
||||
Task.id.is_(None), # 🔧 允许该产品完全没有任务记录（新建档/待接收）
|
||||
Task.parent_task_id.is_(None),
|
||||
Task.task_type.in_(["TRANSFER", "RECOVERY", "WAREHOUSE"]),
|
||||
)
|
||||
),
|
||||
scope.product_where(), # 🚀 业务分组数据范围
|
||||
)
|
||||
.order_by(Product.id, Task.created_at.desc())
|
||||
)
|
||||
@ -1104,6 +1186,7 @@ async def get_wip_matrix(
|
||||
|
||||
async def get_wip_matrix_detail(
|
||||
db: AsyncSession,
|
||||
scope: DataScope,
|
||||
spec_model: str,
|
||||
process: str,
|
||||
since: datetime | None = None,
|
||||
@ -1113,6 +1196,7 @@ async def get_wip_matrix_detail(
|
||||
|
||||
口径与 get_wip_matrix 完全一致：每台设备取最新一条主分支任务，
|
||||
按其在库三态（已完成/已入库/已出库）或工序名归类到 process。
|
||||
数据范围也必须与 get_wip_matrix 同谓词，否则格子里有数、点进来却是空的。
|
||||
"""
|
||||
from datetime import timezone as dt_timezone
|
||||
from sqlalchemy.orm import aliased
|
||||
@ -1157,7 +1241,8 @@ async def get_wip_matrix_detail(
|
||||
Task.id.is_(None), # 🔧 允许该产品完全没有任务记录（新建档/待接收）
|
||||
Task.parent_task_id.is_(None),
|
||||
Task.task_type.in_(["TRANSFER", "RECOVERY", "WAREHOUSE"]),
|
||||
)
|
||||
),
|
||||
scope.product_where(), # 🚀 业务分组数据范围（与 get_wip_matrix 同谓词）
|
||||
)
|
||||
.order_by(Product.id, Task.created_at.desc())
|
||||
)
|
||||
@ -1269,13 +1354,16 @@ async def get_wip_matrix_detail(
|
||||
import uuid as uuid_mod
|
||||
from sqlalchemy import func as sa_func
|
||||
uuid_list = [uuid_mod.UUID(m.product_id) for m in matched]
|
||||
# 🚀 业务分组数据范围：本查询也是 Task 主体，一并挂 task_where
|
||||
# （uuid_list 已来自上方受限结果，这里只是把口径写全，结果集不变）
|
||||
range_rows = (await db.execute(
|
||||
select(
|
||||
Task.product_id,
|
||||
sa_func.min(sa_func.coalesce(Task.received_at, Task.created_at)).label("t0"),
|
||||
sa_func.max(sa_func.coalesce(Task.completed_at, now)).label("tmax"),
|
||||
)
|
||||
.where(Task.product_id.in_(uuid_list))
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(Task.product_id.in_(uuid_list), scope.task_where())
|
||||
.group_by(Task.product_id)
|
||||
)).all()
|
||||
row_by_pid = {m.product_id: m for m in matched}
|
||||
@ -1297,10 +1385,13 @@ async def get_user_operation_detail(
|
||||
db: AsyncSession,
|
||||
user_id: str,
|
||||
action_type: str,
|
||||
scope: DataScope,
|
||||
since: datetime | None = None,
|
||||
until: datetime | None = None,
|
||||
) -> list[OperationDetail]:
|
||||
"""查询某人在指定时段内的某类操作明细。
|
||||
"""查询某人在指定时段内的某类操作明细（按业务分组数据范围过滤）。
|
||||
|
||||
与 get_user_operations 的数字同口径，否则「点数字看到的条数」对不上。
|
||||
|
||||
action_type:
|
||||
- receive: 接收（task_logs.action_type='receive'）
|
||||
@ -1326,11 +1417,16 @@ async def get_user_operation_detail(
|
||||
|
||||
if action_type in ("receive", "transfer"):
|
||||
act = "receive" if action_type == "receive" else "complete"
|
||||
# 🚀 业务分组数据范围：TaskLog 已 join Task 与 Product，直接挂 task_where
|
||||
stmt = (
|
||||
select(TaskLog.created_at, Task.task_name, Product.serial_number, Product.material_name, TaskLog.remark)
|
||||
.join(Task, TaskLog.task_id == Task.id)
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(TaskLog.operator_id == user_id, TaskLog.action_type == act)
|
||||
.where(
|
||||
TaskLog.operator_id == user_id,
|
||||
TaskLog.action_type == act,
|
||||
scope.task_where(),
|
||||
)
|
||||
.order_by(TaskLog.created_at.desc())
|
||||
)
|
||||
if since:
|
||||
@ -1354,6 +1450,7 @@ async def get_user_operation_detail(
|
||||
.where(
|
||||
Task.assignee_id == user_id,
|
||||
or_(TaskRecord.remark.is_(None), ~TaskRecord.remark.like("[%")),
|
||||
scope.task_where(), # 🚀 业务分组数据范围（已 join Product）
|
||||
)
|
||||
.order_by(TaskRecord.created_at.desc())
|
||||
)
|
||||
@ -1377,8 +1474,11 @@ async def get_user_operation_detail(
|
||||
# 人员负载（按人聚合在制品设备 — 独立「人员看板」）
|
||||
# ============================================================
|
||||
|
||||
async def get_people_workload(db: AsyncSession) -> list[PersonWorkload]:
|
||||
"""上帝视角 — 按负责人聚合当前在制品设备（WIP/PENDING 任务，product 去重，含滞留时长）。"""
|
||||
async def get_people_workload(db: AsyncSession, scope: DataScope) -> list[PersonWorkload]:
|
||||
"""按负责人聚合当前在制品设备（WIP/PENDING 任务，product 去重，含滞留时长）。
|
||||
|
||||
按业务分组数据范围过滤。
|
||||
"""
|
||||
from app.models.task import Task, TASK_STATUS_PENDING, TASK_STATUS_WIP
|
||||
from app.models.product import Product
|
||||
from app.models.holiday import Holiday
|
||||
@ -1399,6 +1499,7 @@ async def get_people_workload(db: AsyncSession) -> list[PersonWorkload]:
|
||||
.where(
|
||||
Task.status.in_([TASK_STATUS_PENDING, TASK_STATUS_WIP]),
|
||||
Task.assignee_id.isnot(None),
|
||||
scope.task_where(), # 🚀 业务分组数据范围（已 join Product）
|
||||
)
|
||||
.order_by(Task.assignee_id, Product.created_at.desc())
|
||||
)
|
||||
@ -1473,6 +1574,7 @@ async def get_people_workload(db: AsyncSession) -> list[PersonWorkload]:
|
||||
|
||||
async def get_people_history(
|
||||
db: AsyncSession,
|
||||
scope: DataScope,
|
||||
since: datetime | None = None,
|
||||
until: datetime | None = None,
|
||||
assignee_id: str | None = None,
|
||||
@ -1480,7 +1582,12 @@ async def get_people_history(
|
||||
product_sn: str | None = None,
|
||||
task_name: str | None = None,
|
||||
) -> list[PersonHistoryRecord]:
|
||||
"""上帝视角 — 人员效能与工时台账（平铺 Task 明细，含 WIP/PENDING/COMPLETED）。"""
|
||||
"""人员效能与工时台账（平铺 Task 明细，含 WIP/PENDING/COMPLETED，按业务分组数据范围过滤）。
|
||||
|
||||
⚠️ 两个子查询（最新有效备注 / 记录总数）只扫 task_records，靠下面的 outerjoin
|
||||
挂到本语句的 Task 上，会被主查询的 WHERE（含数据范围谓词）一并收窄，
|
||||
故无需在子查询内部再过滤一次。
|
||||
"""
|
||||
from app.models.task import Task, TASK_STATUS_WIP, TASK_STATUS_PENDING, TASK_STATUS_COMPLETED
|
||||
from app.models.product import Product
|
||||
from app.core.time_utils import get_beijing_time, BEIJING_TZ, to_beijing, working_duration_hours
|
||||
@ -1554,6 +1661,7 @@ async def get_people_history(
|
||||
.where(
|
||||
Task.status.in_([TASK_STATUS_WIP, TASK_STATUS_PENDING, TASK_STATUS_COMPLETED]),
|
||||
Task.assignee_id.isnot(None),
|
||||
scope.task_where(), # 🚀 业务分组数据范围（已 join Product）
|
||||
)
|
||||
)
|
||||
|
||||
@ -1642,12 +1750,13 @@ async def get_people_history(
|
||||
|
||||
async def search_product_messages(
|
||||
db: AsyncSession,
|
||||
scope: DataScope,
|
||||
keyword: str = "",
|
||||
skip: int = 0,
|
||||
limit: int = 50,
|
||||
) -> ProductMessageList:
|
||||
"""
|
||||
上帝视角 — 全厂所有产品的协同留言。
|
||||
协同留言搜索 — 只返回当前业务分组数据范围内产品的留言。
|
||||
|
||||
关联链: ProductMessage → Product → (material_name, serial_number)
|
||||
搜索支持: SN码、物料名称、留言人
|
||||
@ -1658,9 +1767,12 @@ async def search_product_messages(
|
||||
from app.core.time_utils import BEIJING_TZ
|
||||
|
||||
# 基础查询 — 同时取出 16位追溯码 + 业务序列号
|
||||
# 🚀 业务分组数据范围：已 join Product，直接挂 product_where
|
||||
# （下方 total 由本 stmt 派生子查询，自动继承同一谓词，条数不会对不上）
|
||||
stmt = (
|
||||
select(ProductMessage, Product.serial_number, Product.material_name, Product.external_serial)
|
||||
.join(Product, ProductMessage.product_id == Product.id)
|
||||
.where(scope.product_where())
|
||||
)
|
||||
|
||||
# 关键词搜索
|
||||
|
||||
@ -10,6 +10,9 @@
|
||||
视角说明：
|
||||
管理层每天要看的是「这个月干得怎么样、现在卡在哪、系统有没有在跑」，
|
||||
而不是历史品质排名。故本模块聚焦三件事 —— 当月吞吐、当前卡点、使用活跃度。
|
||||
|
||||
2026-09 起不再是「上帝视角」：统计函数一律接收调用方解析好的 DataScope，
|
||||
查询里按 Product.lifecycle_phase 过滤（谓词只在 data_scope_service 生成，见该模块红线）。
|
||||
"""
|
||||
from __future__ import annotations
|
||||
|
||||
@ -23,11 +26,13 @@ from app.core.lifecycle import (
|
||||
AFTER_SALES_ONLY_STEPS,
|
||||
LIFECYCLE_AFTER_SALES,
|
||||
LIFECYCLE_PRODUCTION,
|
||||
allowed_steps,
|
||||
)
|
||||
from app.core.time_utils import get_beijing_time
|
||||
from app.models.product import Product
|
||||
from app.models.task import Task
|
||||
from app.models.task_log import TaskLog
|
||||
from app.services.data_scope_service import DataScope
|
||||
|
||||
# 已完结的宏观状态 —— 与 dashboard_service.get_dashboard_stats 同口径
|
||||
FINISHED_OVERALL = ("待仓库收货", "已入库", "在库", "已出库")
|
||||
@ -78,8 +83,8 @@ class MonthlyMetrics(BaseModel):
|
||||
month_returned: int # 本月进入售后/回流状态的设备数
|
||||
|
||||
|
||||
async def get_monthly_metrics(db: AsyncSession) -> MonthlyMetrics:
|
||||
"""当月吞吐四联指标。
|
||||
async def get_monthly_metrics(db: AsyncSession, scope: DataScope) -> MonthlyMetrics:
|
||||
"""当月吞吐四联指标（按当前用户的业务分组数据范围过滤）。
|
||||
|
||||
口径：
|
||||
- month_production：lifecycle_phase = PRODUCTION，且「本月新建」或
|
||||
@ -90,6 +95,9 @@ async def get_monthly_metrics(db: AsyncSession) -> MonthlyMetrics:
|
||||
- month_returned：本月创建过售后专属工序任务（发货测试 / 售后维修）的
|
||||
设备数（去重）。Product 表无 updated_at，无法直接查「转为 AFTER_SALES
|
||||
的时刻」，故以售后工序任务的创建时间作为进入售后阶段的时间锚点。
|
||||
|
||||
⚠️ month_production 上两条口径叠加（phase=PRODUCTION AND phase IN 范围），
|
||||
维修组的本月生产数自然为 0 —— 这正是正确行为，不要为它加特判绕开范围。
|
||||
"""
|
||||
month_start_utc, now_utc, month_label = _month_bounds()
|
||||
|
||||
@ -103,24 +111,33 @@ async def get_monthly_metrics(db: AsyncSession) -> MonthlyMetrics:
|
||||
)
|
||||
.exists()
|
||||
)
|
||||
# 🚀 业务分组数据范围：主体 Product，直接追加 product_where
|
||||
month_production = await db.scalar(
|
||||
select(func.count(func.distinct(Product.id))).where(
|
||||
Product.lifecycle_phase == LIFECYCLE_PRODUCTION,
|
||||
or_(Product.created_at >= month_start_utc, has_activity),
|
||||
scope.product_where(),
|
||||
)
|
||||
) or 0
|
||||
|
||||
async def _count_log(action_type: str) -> int:
|
||||
# 🚀 业务分组数据范围：TaskLog 无阶段字段，两级 join 到 Product 后挂 task_where
|
||||
# （计数列已是 TaskLog.id，join 不会放大行数）
|
||||
return await db.scalar(
|
||||
select(func.count(TaskLog.id)).where(
|
||||
select(func.count(TaskLog.id))
|
||||
.join(Task, Task.id == TaskLog.task_id)
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
.where(
|
||||
TaskLog.action_type == action_type,
|
||||
TaskLog.created_at >= month_start_utc,
|
||||
scope.task_where(),
|
||||
)
|
||||
) or 0
|
||||
|
||||
month_inbound = await _count_log(LOG_WAREHOUSE_INBOUND)
|
||||
month_outbound = await _count_log(LOG_WAREHOUSE_OUTBOUND)
|
||||
|
||||
# 🚀 业务分组数据范围：已 join Product，直接挂 product_where
|
||||
month_returned = await db.scalar(
|
||||
select(func.count(func.distinct(Task.product_id)))
|
||||
.join(Product, Task.product_id == Product.id)
|
||||
@ -128,6 +145,7 @@ async def get_monthly_metrics(db: AsyncSession) -> MonthlyMetrics:
|
||||
Product.lifecycle_phase == LIFECYCLE_AFTER_SALES,
|
||||
Task.task_name.in_(tuple(AFTER_SALES_ONLY_STEPS)),
|
||||
Task.created_at >= month_start_utc,
|
||||
scope.product_where(),
|
||||
)
|
||||
) or 0
|
||||
|
||||
@ -170,17 +188,50 @@ WIP_STAGES: tuple[tuple[str, str], ...] = (
|
||||
# 「待启动」对应的真实分组键（overall_status IS NULL / 空串）
|
||||
_UNSTARTED_KEY = ""
|
||||
|
||||
# 词表内工序 → 声明的阶段（补画「有数但被范围裁掉」的工序时，用它还原分区着色）
|
||||
_STAGE_PHASE: dict[str, str] = {
|
||||
(_UNSTARTED_KEY if s == "待启动" else s): p for s, p in WIP_STAGES
|
||||
}
|
||||
|
||||
async def get_wip_distribution(db: AsyncSession) -> WipDistributionResponse:
|
||||
"""工序积压分布 —— 当前未完结设备按 overall_status 聚合的数量。
|
||||
|
||||
def _visible_stages(scope: DataScope) -> tuple[tuple[str, str], ...]:
|
||||
"""按当前业务分组范围裁剪工序柱 —— 只保留本组阶段内的工序。
|
||||
|
||||
维修组（AFTER_SALES）的大屏上挂一排恒为 0 的「备货 / 生产 / 测试」柱子没有意义，
|
||||
反而让人误以为"有活压着没干"。判定取并集（宁可多留、不可错删）：
|
||||
· 工序自己声明的 phase 落在范围内 ——「待启动」这类合成列按 PRODUCTION 论；
|
||||
· 或工序名属于该阶段的合法工序词表（词表取自 core.lifecycle，本模块不另抄一份）：
|
||||
「发货测试」两个阶段都合法，故生产组也照常保留。
|
||||
范围不限（超管 / 未分组主管）时原样返回，保证大屏类目与改造前完全一致。
|
||||
"""
|
||||
if scope.phases is None:
|
||||
return WIP_STAGES
|
||||
allowed: set[str] = set()
|
||||
for phase in scope.phases:
|
||||
allowed |= set(allowed_steps(phase))
|
||||
return tuple(
|
||||
(stage, phase)
|
||||
for stage, phase in WIP_STAGES
|
||||
if phase in scope.phases or stage in allowed
|
||||
)
|
||||
|
||||
|
||||
async def get_wip_distribution(db: AsyncSession, scope: DataScope) -> WipDistributionResponse:
|
||||
"""工序积压分布 —— 当前数据范围内未完结设备按 overall_status 聚合的数量。
|
||||
|
||||
返回**固定阶段列表**（含 0 值），保证大屏布局稳定、柱子不因某天缺数据而
|
||||
整根消失；同时把数据里出现但不在词表内的状态追加在末尾，确保 items 的
|
||||
count 之和恒等于 total（避免统计悄悄漏数）。
|
||||
|
||||
⚠️ 「恒 0 才裁、有数必现」是裁剪的铁律：被 `_visible_stages` 裁掉的工序若
|
||||
名下**真有设备**（如上个阶段的设备卡在旧工序名上没流转走），它会带着
|
||||
真实计数回到列表末尾 —— 宁可多画一根柱子，也绝不把设备藏起来变成
|
||||
「合计 1 台、柱子全是 0」的鬼故事。恒 0 的柱子才真正不画。
|
||||
"""
|
||||
# 🚀 业务分组数据范围：主体 Product，直接挂 product_where（计数列是 Product.id，无 join 放大）
|
||||
rows = await db.execute(
|
||||
select(Product.overall_status, func.count(Product.id))
|
||||
.where(_not_finished())
|
||||
.where(_not_finished(), scope.product_where())
|
||||
.group_by(Product.overall_status)
|
||||
)
|
||||
counts: dict[str, int] = {}
|
||||
@ -190,17 +241,22 @@ async def get_wip_distribution(db: AsyncSession) -> WipDistributionResponse:
|
||||
|
||||
total = sum(counts.values())
|
||||
|
||||
# 🚀 业务分组数据范围：只画本组阶段的工序柱（范围不限时即 WIP_STAGES 原样）
|
||||
stages = _visible_stages(scope)
|
||||
items: list[WipStage] = []
|
||||
for stage, phase in WIP_STAGES:
|
||||
for stage, phase in stages:
|
||||
key = _UNSTARTED_KEY if stage == "待启动" else stage
|
||||
items.append(WipStage(stage=stage, phase=phase, count=counts.get(key, 0)))
|
||||
|
||||
known_keys = {_UNSTARTED_KEY if s == "待启动" else s for s, _ in WIP_STAGES}
|
||||
# 词表外的状态追加在末尾。known_keys 只按**可见**柱子算：被裁掉的工序若名下
|
||||
# 真有设备，就走这条追加路径回来（阶段着色按词表还原），保证合计不漏数；
|
||||
# cnt 为 0 的则被下面的 `and cnt` 挡掉 —— 那才是本次裁剪要除掉的那排空柱。
|
||||
known_keys = {_UNSTARTED_KEY if s == "待启动" else s for s, _ in stages}
|
||||
for key, cnt in counts.items():
|
||||
if key not in known_keys and cnt:
|
||||
items.append(WipStage(
|
||||
stage=key or "待启动",
|
||||
phase=LIFECYCLE_PRODUCTION,
|
||||
phase=_STAGE_PHASE.get(key, LIFECYCLE_PRODUCTION),
|
||||
count=cnt,
|
||||
))
|
||||
|
||||
@ -225,17 +281,23 @@ class ActiveUsersResponse(BaseModel):
|
||||
items: list[ActiveUser]
|
||||
|
||||
|
||||
async def get_active_users(db: AsyncSession, top_n: int = 5) -> ActiveUsersResponse:
|
||||
async def get_active_users(db: AsyncSession, scope: DataScope, top_n: int = 5) -> ActiveUsersResponse:
|
||||
"""本月系统活跃度排行 —— 直接桥接 /dashboard/user-operations 的口径。
|
||||
|
||||
不重复实现聚合逻辑：转交/接收取 task_logs（action_type = receive / complete），
|
||||
上传备注取 task_records（排除系统自动备注）。仅返回本月**确实有操作**的人员，
|
||||
避免排行榜被一串 0 稀释 —— 领导要看到的是"系统真的有人在用"。
|
||||
|
||||
按当前用户的业务分组数据范围过滤：范围直接透传给 get_user_operations，
|
||||
两处口径共用一份谓词，不在这里另抄一遍。
|
||||
"""
|
||||
from app.services.dashboard_service import get_user_operations
|
||||
|
||||
month_start_utc, _now, month_label = _month_bounds()
|
||||
operations = await get_user_operations(db, since=month_start_utc, until=None)
|
||||
# 🚀 业务分组数据范围：由调用方解析好的真实 scope 透传（不再是「不限」占位）
|
||||
operations = await get_user_operations(
|
||||
db, scope, since=month_start_utc, until=None,
|
||||
)
|
||||
active = [op for op in operations if op.total > 0][:top_n]
|
||||
|
||||
return ActiveUsersResponse(
|
||||
|
||||
Reference in New Issue
Block a user