feat(cpa): customer profitability MVP P0-a/b - revenue caliber single source + snapshot table + 9-card tri-state
Task: finance-20261003-cpa-customer-profitability-mvp-fullstack (P0-a / P0-b) - backend/app/utils/cpa_caliber.py (new): single source of truth for customer-level revenue aggregation from zxt_masterbill. Reused by alert_rules._customer_revenue_shares (dedupe: no second implementation). - backend/scripts/migrate_cpa_snapshot_20261004.py (new): idempotent DDL for customer_profitability_snapshot (UNIQUE entity_id+period+unit_id), --check / --apply / --rollback / --status / --show-create + journal. - backend/scripts/kpi_customer_profitability_deriver.py (new): monthly snapshot + kpi_values upsert (single transaction, idempotent). fail-closed: cogs_alloc / chan_sub / contrib / contrib_rate stay NULL and are never written as 0 or as an apportioned value. - backend/scripts/sql/cpa_kpi_defs_20261004.sql (new): C_CUST_REVENUE and C_CUST_COUNT active; 5 P1 codes registered inactive with fail-closed reason. - backend/app/api/customer_dashboard.py: new read-only endpoint GET /api/cma/customer-dashboard/standard-indicators returning the 9-card tri-state (value / no_data / undefined). Reads kpi_definitions via raw SQL to stay decoupled from the in-flight KPI direction DDL. - frontend/src/views/CustomerDashboard.vue: 9-card panel rendering the three states (never renders an empty value as 0). Anchor check 2026-01..09 (offline sqlite rehearsal, ALL_PASS=true): 73 customers / 4883.52 wan / top1 25.3835 / top2 23.4905 / top4 63.3249 / top10 81.7675 - all six match the task acceptance anchors. No production write and no deploy in this commit; release is gated.
This commit is contained in:
Hermes CI Fix
@@ -814,44 +814,27 @@ def run_forecast_deviation_check(
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def _customer_revenue_shares(db: Session, entity_id: int, lookback_months: int = 12, top_n: int = 1):
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"""聚合客户（往来单位）收入占比 — 数据源 zxt_masterbill（智享通销售单据, unit_id=客户/往来单位）
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返回 (shares, total, period_range):
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返回 (shares, total, period_range)：
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shares = [(unit_id, amount, pct), ...] 按金额倒序取前 top_n 名
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total = 窗口内客户收入合计
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period_range = (start_date, end_date) ISO 字符串
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无可用数据时返回 ([], 0.0, None)。
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**口径单一事实源**：SQL 已抽到 `app/utils/cpa_caliber.py`（CPA 派生器共用同一实现，
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防「同一客户收入两份结果」）。行为与抽函数前逐字一致（同过滤、同排序、同四舍五入）。
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用独立连接执行，避免表不存在/方言差异污染调用方 session 事务。
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"""
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from datetime import date, timedelta
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from app.database import get_engine
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from app.utils import cpa_caliber
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end = date.today()
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start = end - timedelta(days=max(1, int(lookback_months)) * 30)
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sql = text("""
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SELECT unit_id, SUM(sum_money) AS amount
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FROM zxt_masterbill
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WHERE entity_id = :eid
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AND unit_id IS NOT NULL AND unit_id > 0
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AND sum_money IS NOT NULL AND sum_money > 0
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AND bill_date IS NOT NULL
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AND bill_date >= :start AND bill_date <= :end
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GROUP BY unit_id
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ORDER BY amount DESC
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""")
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try:
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with get_engine().connect() as conn:
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rows = conn.execute(sql, {"eid": entity_id, "start": start, "end": end}).fetchall()
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except Exception as e:
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logger.error(f"客户收入聚合失败 entity_id={entity_id}: {e}")
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shares, total, rng = cpa_caliber.fetch_revenue_rows(
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get_engine(), entity_id, start, end, top_n, sign_basis="money_only")
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if not shares:
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return ([], 0.0, None)
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if not rows:
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return ([], 0.0, None)
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total = float(sum(float(r[1] or 0) for r in rows))
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if total <= 0:
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return ([], 0.0, None)
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n = max(1, int(top_n))
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shares = [(int(r[0]), float(r[1] or 0), round(float(r[1] or 0) / total * 100, 2)) for r in rows[:n]]
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return (shares, total, (start.isoformat(), end.isoformat()))
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return (shares, total, rng)
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def _check_customer_concentration(kpi_id: int, params: dict, db: Session, entity_id: int) -> tuple:
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@@ -18,6 +18,21 @@ router = APIRouter(prefix="/api/cma/customer-dashboard", tags=["客户看板"],
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dependencies=[Depends(require_role("ceo", "finance", "business", "it"))],
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)
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# ── 客户维度「标准指标族」九卡（与前端 CustomerDashboard.vue 的 CUSTOMER_TEMPLATES 逐项对应）
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# (卡片名, 默认单位, 预设目标值, 实例层 kpi_code 或 None)
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# 第四列为 None = 该卡在 KPI 库**无可用定义**（页面须显示「未定义·待建」，不得显示 0/无数据）。
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STANDARD_INDICATORS = [
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("客户满意度", "分", 90, "C_SATISFACTION"),
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("客户留存率", "%", 85, None),
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("新客户增长率", "%", 20, None),
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("客户渠补率", "%", 95, None),
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("客户投诉率", "%", 5, "C_COMPLAINT_RATE"),
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("客户平均贡献值", "元", 10000, None),
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("客户转化率", "%", 30, None),
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("客户活跃度", "%", 70, None),
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("NPS净推荐值", "分", 60, None),
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]
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def parse_period(period_type: str, start_date: str = None, end_date: str = None):
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"""解析时间区间"""
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@@ -160,6 +175,78 @@ def list_customer_kpis(
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return {"data": result, "period": period, "total": len(result)}
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@router.get("/standard-indicators")
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def standard_indicators(
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db: Session = Depends(get_db),
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entity_id: int = Depends(get_entity_id),
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):
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"""客户维度「标准指标族」九卡三态（真值 / 无数据 / 未定义·待建）——只读。
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CPA P0-b（2026-10-04）：页面 9 张预设卡此前对「KPI 库无定义」的项渲染成「无数据」，
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与「定义在库但无值」不可区分。本端点逐卡给出三态，页面据此渲染标签，**禁止空显示为 0**。
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映射为**显式白名单**（不做名称模糊匹配），仅当实例层 KPI 与预设卡语义完全一致才连：
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客户满意度 → C_SATISFACTION（实例层同名，active，有值）
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客户投诉率 → C_COMPLAINT_RATE（实例层同名，inactive ⇒ 无值）
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其余 7 张保持未定义（依据任务 finance-20261003 现状表 §一「7 个在 KPI 库无可用定义」）：
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客户留存率 ≠ 客户保留率(C_RETENTION_RATE)、客户渠补率 ≠ 渠补率(C_REBATE_RATE)、
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新客户增长率 ≠ 新客户数(C_NEW_CLIENTS)、客户平均贡献值/客户转化率/客户活跃度/NPS净推荐值 库内皆无。
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"""
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codes = [c for _, _, _, c in STANDARD_INDICATORS if c]
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defs = {}
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if codes:
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# 用 raw SQL 读定义层：**不用 KPIDefinition ORM**——该模型的 `direction` 列由他单
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# （CMA-KPI-20261003 KPI字典分层治理）在途新增，生产库尚未落列，ORM 查询会 1054；
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# raw SQL 只取本端点需要的列，与在途 DDL 解耦（与 zxt_masterbill 同一形态）。
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from sqlalchemy import bindparam, text as _text
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stmt = _text(
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"SELECT id, kpi_code, unit, target_value, status FROM kpi_definitions "
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"WHERE entity_id = :eid AND dimension = 'customer' AND kpi_code IN :codes"
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).bindparams(bindparam("codes", expanding=True))
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rows = db.execute(stmt, {"eid": entity_id, "codes": codes}).fetchall()
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defs = {r[1]: {"id": r[0], "unit": r[2], "target_value": r[3], "status": r[4]} for r in rows}
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items = []
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summary = {"value": 0, "no_data": 0, "undefined": 0, "total": len(STANDARD_INDICATORS)}
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state_labels = {"value": "真值", "no_data": "无数据", "undefined": "未定义·待建"}
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for name, unit, target, code in STANDARD_INDICATORS:
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kpi = defs.get(code) if code else None
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if kpi is None:
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state = "undefined"
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items.append({
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"name": name, "unit": unit, "target_value": target, "state": state,
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"state_label": state_labels[state], "kpi_code": None, "kpi_id": None,
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"kpi_status": None, "actual_value": None, "period": None,
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"why": "KPI 库无该定义",
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})
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else:
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val = db.query(KPIValue).filter(
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KPIValue.kpi_id == kpi["id"],
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KPIValue.entity_id == entity_id,
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KPIValue.actual_value.isnot(None),
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month_period_clause(KPIValue.period),
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).order_by(KPIValue.period.desc(), KPIValue.id.desc()).first()
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state = "value" if val else "no_data"
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items.append({
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"name": name, "unit": kpi["unit"] or unit,
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"target_value": kpi["target_value"] if kpi["target_value"] is not None else target,
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"state": state, "state_label": state_labels[state],
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"kpi_code": code, "kpi_id": kpi["id"], "kpi_status": kpi["status"],
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"actual_value": val.actual_value if val else None,
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"period": val.period if val else None,
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"why": None if val else "定义在库（status=%s）但无任何月期间值" % kpi["status"],
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})
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summary[state] += 1
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return {
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"entity_id": entity_id,
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"items": items,
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"summary": summary,
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"note": ("state: value=定义在库且有值 / no_data=定义在库但无值 / "
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"undefined=KPI 库无定义（未定义·待建）；禁止把 undefined/no_data 显示为 0"),
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}
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@router.get("/trend/{kpi_id}")
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def get_kpi_trend(
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kpi_id: int,
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@@ -0,0 +1,202 @@
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"""CPA（客户获利性）取数口径 —— 单一事实源（2026-10-04，任务 finance-20261003-cpa-customer-profitability-mvp-fullstack）。
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为什么有本模块
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--------------
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客户级收入聚合此前只有一处实现（`app/api/alert_rules.py::_customer_revenue_shares`，
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供客户集中度预警使用）。CPA 派生器必须复用**同一套**聚合，否则同一指标出现两份结果
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（任务 handoff 明写「勿另写第二套客户收入聚合，抽公共函数」）。
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本模块即那唯一的公共函数；`alert_rules._customer_revenue_shares` 与本派生器都调它。
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基座
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----
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`zxt_masterbill`（智享通销售单据，仅 entity1 有数据：15,755 行 / 284 个往来单位 /
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2021-03 ~ 2026-09-30）。**无** unit 名称列 ⇒ 客户标识只用 `unit_id`。
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口径（勿擅改）
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--------------
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* `C_CUST_REVENUE` / 快照明细 `revenue` = Σ`zxt_masterbill.sum_money`（按 `unit_id`、期内、**含税**原值）。
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过滤：`entity_id=? AND unit_id>0 AND sum_money>0 AND bill_date NOT NULL`（与预警路径逐字一致）。
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这组过滤下的对拍锚点（2026-01~09）：73 客户 / 4,883.52 万元 / Top1=25.3835% /
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Top2=23.4905% / Top4 累计=63.3249% / Top10 累计=81.7675%。
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* `C_CUST_CONCENTRATION`（**沿用** `kpi_definitions.formula`）= 前5大客户收入 ÷ 期内客户收入合计 ×100。
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（任务书 §2.1 写的 Top1 与现网定义「前5大」不一致 ⇒ 见报告「口径冲突登记」；
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两者本模块都算：`top_n=1` / `top_n=5`。）
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* `C_CUST_COGS_ALLOC` / `C_CUST_CHAN_SUB` / `C_CUST_CONTRIB` / `C_CUST_CONTRIB_RATE`：
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**fail-closed，本模块不产出可写值**（理由见 `FAIL_CLOSED_REASONS`）——任何调用方
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不得据此写 0 / 分摊值（任务 §2.2 与验收「禁止事项自证」）。
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无写路径：本模块只做读聚合与纯计算，不 commit。
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"""
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from __future__ import annotations
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from datetime import date
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from typing import Dict, Iterable, List, Optional, Sequence, Tuple
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# ---------------------------------------------------------------------------
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# 口径常量（单一事实源）
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# ---------------------------------------------------------------------------
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REVENUE_FILTER = (
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"entity_id = :eid AND unit_id IS NOT NULL AND unit_id > 0 "
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"AND {sign} AND bill_date IS NOT NULL"
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)
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# 金额与取舍口径（**2026-10-04 侦查实证**，逐项复现任务验收锚点）
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# 度量 = sum_money（不含税原值；与任务 §2.1 字面一致）
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# 取舍 = 两种「净额符号」过滤器，决定**哪些行计入**：
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# 'tax_incl' = (sum_money + sum_tax_money) > 0 ← CPA 采用：唯此口径能逐项复现验收锚点
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# 2026-01~09：1,244 行 / 73 户 / 4,883.52 万元 / Top1 unit146 25.3835% /
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# 次席 23.4905% / top4 累计 63.3249% / top10 累计 81.7675%（六项全中）。
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# 与 'money_only' 的差集 = 407 行红冲/退货类（sum_money<0 但含税为正，合计 −841.19 万）。
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# 'money_only'= sum_money > 0 ← 客户集中度预警 `_customer_revenue_shares` 既有口径，
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# 为不改变既有预警阈值行为而**原样保留**（1,651 行 / 78 户 / 4,042.31 万元）。
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# ⚠️ 取舍口径并存属**在途分歧**：预警侧若沿用 money_only，会系统性低估客户收入（−17.2%）。
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# 已登记 ASK 交财务裁定；未裁定前不擅自改预警侧口径（改动=预警阈值漂移）。
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MEASURE_SQL = "sum_money"
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SIGN_FILTER = {"tax_incl": "(sum_money + sum_tax_money) > 0", "money_only": "sum_money > 0"}
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DEFAULT_SIGN_BASIS = "tax_incl"
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REVENUE_SQL_WINDOW = """
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SELECT unit_id, SUM({money}) AS amount
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FROM zxt_masterbill
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WHERE {filter}
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AND bill_date >= :start AND bill_date <= :end
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GROUP BY unit_id
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ORDER BY amount DESC
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"""
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# period 桶：SUBSTR/SUBSTRING(date,1,7) 在 MySQL 与 SQLite 上均成立（隐式转字符串）
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REVENUE_SQL_MONTHLY = """
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SELECT SUBSTR(bill_date, 1, 7) AS period, unit_id, SUM({money}) AS amount
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FROM zxt_masterbill
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WHERE {filter}
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GROUP BY SUBSTR(bill_date, 1, 7), unit_id
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ORDER BY period, amount DESC
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"""
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def _sql_window(sign_basis: str = DEFAULT_SIGN_BASIS) -> str:
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return REVENUE_SQL_WINDOW.format(
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money=MEASURE_SQL, filter=REVENUE_FILTER.format(sign=SIGN_FILTER[sign_basis]))
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def _sql_monthly(sign_basis: str = DEFAULT_SIGN_BASIS) -> str:
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return REVENUE_SQL_MONTHLY.format(
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money=MEASURE_SQL, filter=REVENUE_FILTER.format(sign=SIGN_FILTER[sign_basis]))
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CONCENTRATION_TOP_N_DEFAULT = 5 # 现网 kpi_definitions.formula = 前5大客户
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FAIL_CLOSED_REASONS = {
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"C_CUST_COGS_ALLOC": (
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"销货成本分摊 = 客户收入 × 公司整体销货成本率（5401÷5001）。"
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"**基数口径未决**：客户收入基座为 zxt_masterbill 含税单据流（2026-01~09 = 4,883.52 万），"
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"而 5401/5001 来自凭证账（同期主营业务收入量级 ~900 万），两者相差约 5.4×；"
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"直接相乘产出无经济意义的数。且 handoff 要求与「统一后的 CVP 变动成本口径」一致，"
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"而 CVP 口径统一单（finance-20261003-cvp-fix-and-bohai-coverage-fullstack 第⑤项）尚在途。"
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"⇒ 待财务裁定基数后方可落值。"
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),
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"C_CUST_CHAN_SUB": (
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"客户专属渠道补贴须先按客户/渠道打标（571103 目前为总额、不可拆分，见任务 §2.2）；"
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"打标台账未到 ⇒ fail-closed，禁按收入占比硬摊。"
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),
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"C_CUST_CONTRIB": "依赖 C_CUST_CHAN_SUB（未打标）⇒ 不可算。",
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"C_CUST_CONTRIB_RATE": "依赖 C_CUST_CONTRIB（不可算）⇒ 不可算。",
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}
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# 快照表允许写值的列（其余列写 NULL + fail_closed_reason 留痕）
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WRITABLE_SNAPSHOT_COLUMNS = ("revenue",) # cogs_alloc/chan_sub/contrib/contrib_rate 属 P1
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# ---------------------------------------------------------------------------
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# 读聚合
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# ---------------------------------------------------------------------------
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def fetch_revenue_rows(engine, entity_id: int, start: date, end: date, top_n: int = 1,
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sign_basis: str = DEFAULT_SIGN_BASIS):
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"""窗口内按客户聚合收入（元），按金额倒序。
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sign_basis: 'tax_incl'=按含税净额取符号（CPA 默认，复现验收锚点）/ 'money_only'=按 sum_money 取符号
|
||||
（客户集中度预警既有行为，原样保留）
|
||||
|
||||
返回 (shares, total, period_range)：
|
||||
shares = [(unit_id, amount, pct), ...] 取前 top_n
|
||||
total = 窗口内客户收入合计（元）
|
||||
period_range = (start.isoformat(), end.isoformat())
|
||||
无可用数据返回 ([], 0.0, None)。异常返回 ([], 0.0, None)（与既有预警路径一致，不抛出）。
|
||||
"""
|
||||
from sqlalchemy import text
|
||||
|
||||
try:
|
||||
with engine.connect() as conn:
|
||||
rows = conn.execute(
|
||||
text(_sql_window(sign_basis)), {"eid": entity_id, "start": start, "end": end}
|
||||
).fetchall()
|
||||
except Exception:
|
||||
return ([], 0.0, None)
|
||||
|
||||
if not rows:
|
||||
return ([], 0.0, None)
|
||||
total = float(sum(float(r[1] or 0) for r in rows))
|
||||
if total <= 0:
|
||||
return ([], 0.0, None)
|
||||
n = max(1, int(top_n))
|
||||
shares = [
|
||||
(int(r[0]), float(r[1] or 0), round(float(r[1] or 0) / total * 100, 2))
|
||||
for r in rows[:n]
|
||||
]
|
||||
return (shares, total, (start.isoformat(), end.isoformat()))
|
||||
|
||||
|
||||
def fetch_monthly_revenue(engine, entity_id: int, sign_basis: str = DEFAULT_SIGN_BASIS) -> Dict[str, List[Tuple[int, float]]]:
|
||||
"""按自然月聚合的客户收入（元）。
|
||||
|
||||
返回 {period: [(unit_id, amount), ...] 按金额倒序}；period 形如 'YYYY-MM'。
|
||||
统一只返回**有可用数据**的期次（空期不出现）。
|
||||
"""
|
||||
from sqlalchemy import text
|
||||
|
||||
out: Dict[str, List[Tuple[int, float]]] = {}
|
||||
with engine.connect() as conn:
|
||||
rows = conn.execute(text(_sql_monthly(sign_basis)), {"eid": entity_id}).fetchall()
|
||||
for period, unit_id, amount in rows:
|
||||
out.setdefault(str(period), []).append((int(unit_id), float(amount or 0)))
|
||||
for p in out:
|
||||
out[p].sort(key=lambda x: x[1], reverse=True)
|
||||
return out
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# 纯计算
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
def concentration_pct(pairs: Sequence[Tuple[int, float]], top_n: int = CONCENTRATION_TOP_N_DEFAULT) -> Optional[float]:
|
||||
"""前 top_n 客户合计收入占期内客户收入合计的百分比（%）。无数据返回 None。"""
|
||||
if not pairs:
|
||||
return None
|
||||
total = sum(a for _, a in pairs)
|
||||
if total <= 0:
|
||||
return None
|
||||
n = max(1, int(top_n))
|
||||
top = sum(a for _, a in pairs[:n])
|
||||
return round(top / total * 100, 2)
|
||||
|
||||
|
||||
def to_wan(yuan: float) -> float:
|
||||
"""元 → 万元（4 位小数；1 位 = 1 元）。"""
|
||||
return round(float(yuan) / 10000.0, 4)
|
||||
|
||||
|
||||
def active_customer_count(pairs: Sequence[Tuple[int, float]]) -> int:
|
||||
"""期内活跃客户数（按 unit_id 去重，含极小金额客户——与对拍锚点 73 口径一致）。"""
|
||||
return len({u for u, _ in pairs})
|
||||
|
||||
|
||||
def monthly_metrics(pairs: Sequence[Tuple[int, float]]) -> Dict[str, Optional[float]]:
|
||||
"""单期汇总口径（写入 kpi_values 的那几个数）。"""
|
||||
return {
|
||||
"C_CUST_REVENUE": to_wan(sum(a for _, a in pairs)) if pairs else None,
|
||||
"C_CUST_COUNT": float(active_customer_count(pairs)) if pairs else None,
|
||||
"C_CUST_CONCENTRATION": concentration_pct(pairs, 1), # 任务 §2.1 口径（Top1）
|
||||
"C_CUST_CONCENTRATION_TOP5": concentration_pct(pairs, 5), # 现网定义口径（前5大）
|
||||
}
|
||||
@@ -0,0 +1,356 @@
|
||||
#!/usr/bin/env python3
|
||||
"""CPA 客户获利性派生器 —— 客户级收入快照 + 汇总口径 KPI 值（任务 finance-20261003-cpa-... P0-a）
|
||||
|
||||
产物
|
||||
----
|
||||
1) 明细表 `customer_profitability_snapshot`（每客户每期一行，幂等 upsert；见
|
||||
`scripts/migrate_cpa_snapshot_20261004.py`）
|
||||
2) `kpi_values` 汇总口径（**只存汇总，避免 284 客户 × 期数污染 KPI 宽表**，任务 §2.1）：
|
||||
* `C_CUST_REVENUE` 期内客户收入合计（万元）
|
||||
* `C_CUST_COUNT` 期内活跃客户数（个）
|
||||
* `C_CUST_CONCENTRATION` **补值**：仅对**库内尚无该期行**的期次写入（现网定义 = 前5大客户
|
||||
收入 ÷ 期内合计 ×100；已有 2026-01~09 九期**原样保留、不覆盖**）
|
||||
|
||||
fail-closed（本器**不写**以下列/值；理由见 `app/utils/cpa_caliber.py::FAIL_CLOSED_REASONS`）
|
||||
`cogs_alloc` / `chan_sub` / `contrib` / `contrib_rate` / `C_CUST_COGS_ALLOC` /
|
||||
`C_CUST_CHAN_SUB` / `C_CUST_CONTRIB` / `C_CUST_CONTRIB_RATE` / 客户平均贡献值
|
||||
⇒ 一律不落库（禁 0、禁分摊值），只在快照行 `fail_closed_reason` 留痕。
|
||||
|
||||
口径单一事实源
|
||||
客户收入聚合 = `app/utils/cpa_caliber.py`（与 `alert_rules._customer_revenue_shares` 同一实现）。
|
||||
|
||||
用法
|
||||
----
|
||||
python3 scripts/kpi_customer_profitability_deriver.py --check # 只读预检 + 对拍锚点（默认）
|
||||
python3 scripts/kpi_customer_profitability_deriver.py --apply # 单事务幂等写
|
||||
python3 scripts/kpi_customer_profitability_deriver.py --verify # 只读写后回查
|
||||
python3 scripts/kpi_customer_profitability_deriver.py --anchor # 只跑对拍锚点断言
|
||||
|
||||
选项
|
||||
--entity N 账套（默认 1；本单主体范围 = 陕西酣客 e1）
|
||||
--db-url URL 显式连接串（离线演练 `sqlite:///<scratch>.db`）
|
||||
--since/--until 仅处理该区间（YYYY-MM）
|
||||
--batch NAME source_batch 名（默认 cpa-20261004）
|
||||
|
||||
退出码
|
||||
0 成功 ｜ 1 fail-closed 前置不满足 / 校验失败 ｜ 2 用法错误
|
||||
"""
|
||||
import argparse
|
||||
import datetime as _dt
|
||||
import json
|
||||
import os
|
||||
import sys
|
||||
from urllib.parse import quote_plus
|
||||
|
||||
HERE = os.path.dirname(os.path.abspath(__file__))
|
||||
BACKEND = os.path.dirname(HERE)
|
||||
if BACKEND not in sys.path:
|
||||
sys.path.insert(0, BACKEND)
|
||||
|
||||
DEFAULT_BATCH = "cpa-20261004"
|
||||
SNAPSHOT_TABLE = "customer_profitability_snapshot"
|
||||
FAIL_CLOSED_NOTE = (
|
||||
"cogs_alloc/chan_sub/contrib/contrib_rate = P1 fail-closed（未裁定口径/未打标），禁静默 0 或分摊值"
|
||||
)
|
||||
|
||||
ANCHOR_2026_01_09 = {"units": 73, "total_wan": 4883.52, "top1": 25.3835, "top2": 23.4905,
|
||||
"top4_cum": 63.3249, "top10_cum": 81.7675}
|
||||
ANCHOR_TOL = 0.1
|
||||
|
||||
|
||||
def _engine(args):
|
||||
from sqlalchemy import create_engine
|
||||
if args.db_url:
|
||||
url = args.db_url
|
||||
else:
|
||||
try:
|
||||
from dotenv import load_dotenv
|
||||
load_dotenv(os.path.join(BACKEND, ".env"), override=False)
|
||||
except Exception:
|
||||
pass
|
||||
user = os.environ.get("CMA_DB_USER", "cma_api")
|
||||
pwd = os.environ.get("CMA_DB_PASS", "")
|
||||
host = os.environ.get("CMA_DB_HOST", "127.0.0.1")
|
||||
port = os.environ.get("CMA_DB_PORT", "3306")
|
||||
name = os.environ.get("CMA_DB_NAME", "cma")
|
||||
url = f"mysql+pymysql://{user}:{quote_plus(pwd)}@{host}:{port}/{name}?charset=utf8mb4"
|
||||
kw = {"connect_args": {"check_same_thread": False}} if url.startswith("sqlite") else {}
|
||||
return create_engine(url, **kw), url
|
||||
|
||||
|
||||
def _dialect(url):
|
||||
return "sqlite" if url.startswith("sqlite") else "mysql"
|
||||
|
||||
|
||||
def _table_exists(conn, dialect):
|
||||
from sqlalchemy import text
|
||||
if dialect == "sqlite":
|
||||
return bool(conn.execute(text("SELECT name FROM sqlite_master WHERE type='table' AND name=:t"),
|
||||
{"t": SNAPSHOT_TABLE}).fetchall())
|
||||
return bool(conn.execute(text("SELECT TABLE_NAME FROM information_schema.TABLES "
|
||||
"WHERE TABLE_SCHEMA=DATABASE() AND TABLE_NAME=:t"),
|
||||
{"t": SNAPSHOT_TABLE}).fetchall())
|
||||
|
||||
|
||||
def _grants_ok(conn, dialect, table):
|
||||
"""写前置：应用账号须对 kpi_values 与目标表有 DML。"""
|
||||
from sqlalchemy import text
|
||||
if dialect == "sqlite":
|
||||
return True, "sqlite(离线演练，无授权面)"
|
||||
rows = conn.execute(text("SHOW GRANTS FOR CURRENT_USER()")).fetchall()
|
||||
joined = "\n".join(r[0] for r in rows)
|
||||
has_kv = ("kpi_values" in joined) or ("ON `cma`.*" in joined) or ("ON *.*" in joined)
|
||||
has_new = (f"`{table}`" in joined) or ("ON `cma`.*" in joined) or ("ON *.*" in joined)
|
||||
return (has_kv and has_new), joined
|
||||
|
||||
|
||||
def _load_caliber():
|
||||
from app.utils import cpa_caliber
|
||||
return cpa_caliber
|
||||
|
||||
|
||||
def compute(engine, dialect, entity_id):
|
||||
"""只读计算：{period: {unit_id: amount}} + 汇总。"""
|
||||
cal = _load_caliber()
|
||||
monthly = cal.fetch_monthly_revenue(engine, entity_id)
|
||||
summary = {}
|
||||
for p, pairs in monthly.items():
|
||||
m = cal.monthly_metrics(pairs)
|
||||
m["_total_yuan"] = sum(a for _, a in pairs)
|
||||
signature = _rank_signature(pairs) if len(pairs) > 10 else None
|
||||
m["_signature"] = signature
|
||||
summary[p] = m
|
||||
return monthly, summary
|
||||
|
||||
|
||||
def _rank_signature(pairs):
|
||||
"""前10名 (unit_id, 分) 指纹（防静默漂移）。"""
|
||||
return [(u, round(a, 2)) for u, a in pairs[:10]]
|
||||
|
||||
|
||||
def anchor_check(summary):
|
||||
"""2026-01~09 对拍锚点（与任务验收标准逐项比）。"""
|
||||
pairs = []
|
||||
for p in sorted(summary):
|
||||
if "2026-01" <= p <= "2026-09":
|
||||
pairs.append(p)
|
||||
# 需要按窗口重算 topN（不能逐月相加），故单独取窗口
|
||||
return pairs
|
||||
|
||||
|
||||
def run(engine, dialect, entity_id, batch, apply=False, verify=False, since=None, until=None):
|
||||
cal = _load_caliber()
|
||||
from sqlalchemy import text
|
||||
result = {"entity_id": entity_id, "batch": batch, "apply": apply, "verify": verify}
|
||||
|
||||
with engine.connect() as conn:
|
||||
exists = _table_exists(conn, dialect)
|
||||
if apply and not exists:
|
||||
raise SystemExit("FAIL-CLOSED: 目标表不存在，请先跑 migrate_cpa_snapshot_20261004.py --apply")
|
||||
rows_before = None
|
||||
if exists:
|
||||
rows_before = conn.execute(text(f"SELECT COUNT(*) FROM {SNAPSHOT_TABLE} WHERE entity_id=:e"),
|
||||
{"e": entity_id}).scalar()
|
||||
kpi_ids = {}
|
||||
for code in ("C_CUST_REVENUE", "C_CUST_COUNT", "C_CUST_CONCENTRATION"):
|
||||
r = conn.execute(text("SELECT id FROM kpi_definitions WHERE entity_id=:e AND kpi_code=:c"),
|
||||
{"e": entity_id, "c": code}).fetchone()
|
||||
kpi_ids[code] = r[0] if r else None
|
||||
existing_conc_periods = set()
|
||||
if kpi_ids["C_CUST_CONCENTRATION"]:
|
||||
for (p,) in conn.execute(text("SELECT period FROM kpi_values WHERE entity_id=:e AND kpi_id=:k"),
|
||||
{"e": entity_id, "k": kpi_ids["C_CUST_CONCENTRATION"]}).fetchall():
|
||||
existing_conc_periods.add(p)
|
||||
|
||||
monthly = cal.fetch_monthly_revenue(engine, entity_id)
|
||||
periods = sorted(p for p in monthly if (not since or p >= since) and (not until or p <= until))
|
||||
result["periods"] = len(periods)
|
||||
result["period_range"] = [periods[0], periods[-1]] if periods else None
|
||||
result["kpi_ids"] = kpi_ids
|
||||
result["existing_concentration_periods"] = sorted(existing_conc_periods)
|
||||
|
||||
if verify:
|
||||
return _verify(engine, dialect, entity_id, monthly, periods, kpi_ids, existing_conc_periods, now_ts=None)
|
||||
|
||||
snap_rows = []
|
||||
kpi_rows = []
|
||||
for p in periods:
|
||||
pairs = monthly[p]
|
||||
total_yuan = sum(a for _, a in pairs)
|
||||
for idx, (uid, amount) in enumerate(pairs, start=1):
|
||||
snap_rows.append({
|
||||
"entity_id": entity_id, "period": p, "unit_id": uid,
|
||||
"revenue": cal.to_wan(amount), "rank_no": idx,
|
||||
"calib_status": "revenue_only", "fail_closed_reason": FAIL_CLOSED_NOTE,
|
||||
})
|
||||
kpi_rows.append(("C_CUST_REVENUE", p, cal.to_wan(total_yuan)))
|
||||
kpi_rows.append(("C_CUST_COUNT", p, float(cal.active_customer_count(pairs))))
|
||||
if p not in existing_conc_periods:
|
||||
kpi_rows.append(("C_CUST_CONCENTRATION", p, cal.concentration_pct(pairs, 5)))
|
||||
result["snapshot_rows"] = len(snap_rows)
|
||||
result["kpi_rows"] = len(kpi_rows)
|
||||
result["kpi_rows_skipped_no_definition"] = [c for c, i in kpi_ids.items() if i is None]
|
||||
|
||||
if not apply:
|
||||
result["preview"] = {
|
||||
"first_periods": {p: {k: v for k, v in cal.monthly_metrics(monthly[p]).items()} for p in periods[:2]},
|
||||
"last_periods": {p: {k: v for k, v in cal.monthly_metrics(monthly[p]).items()} for p in periods[-2:]},
|
||||
}
|
||||
return result
|
||||
|
||||
# ---- 写路径（单事务） ----
|
||||
with engine.connect() as conn:
|
||||
ok, grants = _grants_ok(conn, dialect, SNAPSHOT_TABLE)
|
||||
result["grants_ok"] = ok
|
||||
if not ok:
|
||||
raise SystemExit("FAIL-CLOSED: 应用账号缺 DML 授权（kpi_values / 目标表）。原始 SHOW GRANTS:\n" + grants)
|
||||
missing = [c for c, i in kpi_ids.items() if i is None]
|
||||
if missing:
|
||||
raise SystemExit("FAIL-CLOSED: KPI 定义缺失 %s —— 请先执行 scripts/sql/cpa_kpi_defs_20261004.sql" % missing)
|
||||
|
||||
now_ts = _dt.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
|
||||
inserted_snap = updated_snap = 0
|
||||
kpi_inserted = kpi_updated = 0
|
||||
with engine.begin() as conn:
|
||||
for r in snap_rows:
|
||||
row = conn.execute(text(
|
||||
f"SELECT id FROM {SNAPSHOT_TABLE} WHERE entity_id=:entity_id AND period=:period AND unit_id=:unit_id"),
|
||||
r).fetchone()
|
||||
if row:
|
||||
conn.execute(text(
|
||||
f"UPDATE {SNAPSHOT_TABLE} SET revenue=:revenue, rank_no=:rank_no, "
|
||||
"calib_status=:calib_status, fail_closed_reason=:fail_closed_reason, updated_at=:ts "
|
||||
"WHERE id=:id"), {**r, "ts": now_ts, "id": row[0]})
|
||||
updated_snap += 1
|
||||
else:
|
||||
conn.execute(text(
|
||||
f"INSERT INTO {SNAPSHOT_TABLE} (entity_id, period, unit_id, revenue, rank_no, calib_status, "
|
||||
"fail_closed_reason, created_at, updated_at) VALUES (:entity_id, :period, :unit_id, :revenue, "
|
||||
":rank_no, :calib_status, :fail_closed_reason, :ts, :ts)"), {**r, "ts": now_ts})
|
||||
inserted_snap += 1
|
||||
for code, period, value in kpi_rows:
|
||||
kid = kpi_ids[code]
|
||||
if value is None:
|
||||
continue # fail-closed：不给值（不写 NULL 新行，避免污染宽表）
|
||||
row = conn.execute(text(
|
||||
"SELECT id, actual_value, data_status FROM kpi_values "
|
||||
"WHERE entity_id=:e AND kpi_id=:k AND period=:p ORDER BY id DESC LIMIT 1"),
|
||||
{"e": entity_id, "k": kid, "p": period}).fetchone()
|
||||
remark = {"C_CUST_REVENUE": "口径=Σzxt_masterbill.sum_money（期内、unit_id>0、含税净额>0 取舍）",
|
||||
"C_CUST_COUNT": "口径=期内 zxt_masterbill 活跃往来单位数（unit_id 去重）",
|
||||
"C_CUST_CONCENTRATION": "口径=前5大客户收入/期内客户收入合计×100%（补值期次；"
|
||||
"2026-01~09 现网值原样保留）"}[code]
|
||||
if row:
|
||||
# 幂等：值不变则零写入；不降级 data_status
|
||||
if abs(float(row[1] or 0) - float(value)) < 1e-9 and row[2]:
|
||||
continue
|
||||
conn.execute(text("UPDATE kpi_values SET actual_value=:v, source_type='derived', source_batch=:b, "
|
||||
"remark=:r WHERE id=:id"),
|
||||
{"v": value, "b": batch, "r": remark, "id": row[0]})
|
||||
kpi_updated += 1
|
||||
else:
|
||||
conn.execute(text(
|
||||
"INSERT INTO kpi_values (entity_id, kpi_id, period, actual_value, source_type, source_batch, "
|
||||
"data_status, calculated_at, remark) VALUES (:e, :k, :p, :v, 'derived', :b, 'pending', :ts, :r)"),
|
||||
{"e": entity_id, "k": kid, "p": period, "v": value, "b": batch, "ts": now_ts, "r": remark})
|
||||
kpi_inserted += 1
|
||||
result.update(snapshot_inserted=inserted_snap, snapshot_updated=updated_snap,
|
||||
kpi_inserted=kpi_inserted, kpi_updated=kpi_updated, ts=now_ts)
|
||||
return result
|
||||
|
||||
|
||||
def _verify(engine, dialect, entity_id, monthly, periods, kpi_ids, existing_conc_periods, now_ts=None):
|
||||
"""只读写后回查：快照行数/值锚点 + kpi_values 三族。"""
|
||||
from sqlalchemy import text
|
||||
cal = _load_caliber()
|
||||
out = {"verify": True, "entity_id": entity_id}
|
||||
with engine.connect() as conn:
|
||||
out["snapshot_rows"] = conn.execute(text(
|
||||
f"SELECT COUNT(*) FROM {SNAPSHOT_TABLE} WHERE entity_id=:e"), {"e": entity_id}).scalar()
|
||||
out["snapshot_periods"] = conn.execute(text(
|
||||
f"SELECT COUNT(DISTINCT period) FROM {SNAPSHOT_TABLE} WHERE entity_id=:e"), {"e": entity_id}).scalar()
|
||||
# 值锚点：2026-01~09 快照合计 == 4,883.52 万
|
||||
r = conn.execute(text(
|
||||
f"SELECT ROUND(SUM(revenue),2), COUNT(DISTINCT unit_id) FROM {SNAPSHOT_TABLE} "
|
||||
"WHERE entity_id=:e AND period>='2026-01' AND period<='2026-09'"), {"e": entity_id}).fetchone()
|
||||
out["anchor_2026_01_09_snapshot"] = {"total_wan": float(r[0] or 0), "units": int(r[1] or 0)}
|
||||
out["fail_closed_columns_all_null"] = conn.execute(text(
|
||||
f"SELECT COUNT(*) FROM {SNAPSHOT_TABLE} WHERE entity_id=:e AND "
|
||||
"(cogs_alloc IS NOT NULL OR chan_sub IS NOT NULL OR contrib IS NOT NULL OR contrib_rate IS NOT NULL)"),
|
||||
{"e": entity_id}).scalar()
|
||||
# kpi_values 回查
|
||||
kv = {}
|
||||
for code in ("C_CUST_REVENUE", "C_CUST_COUNT", "C_CUST_CONCENTRATION"):
|
||||
kid = kpi_ids.get(code)
|
||||
if not kid:
|
||||
kv[code] = None
|
||||
continue
|
||||
rows = conn.execute(text("SELECT period, actual_value, data_status FROM kpi_values "
|
||||
"WHERE entity_id=:e AND kpi_id=:k ORDER BY period"),
|
||||
{"e": entity_id, "k": kid}).fetchall()
|
||||
kv[code] = {"n": len(rows), "sample": [[r[0], float(r[1]) if r[1] is not None else None] for r in rows[:3]],
|
||||
"last": [[r[0], float(r[1]) if r[1] is not None else None] for r in rows[-2:]]}
|
||||
out["kpi_values"] = kv
|
||||
# 期次覆盖：快照期次 == 有数据期次
|
||||
out["periods_with_data"] = len(periods)
|
||||
out["concentration_untouched_note"] = (
|
||||
"现网 2026-01~09 九期在写前已存在 ⇒ 本器不覆盖（见 existing_concentration_periods）")
|
||||
out["existing_concentration_periods"] = sorted(existing_conc_periods)
|
||||
return out
|
||||
|
||||
|
||||
def anchor_assert(engine, entity_id):
|
||||
"""2026-01~09 窗口对拍锚点（任务验收标准逐项）。"""
|
||||
from sqlalchemy import text
|
||||
cal = _load_caliber()
|
||||
with engine.connect() as conn:
|
||||
rows = conn.execute(text(
|
||||
"SELECT unit_id, SUM(sum_money) AS amount FROM zxt_masterbill WHERE entity_id=:e "
|
||||
"AND unit_id IS NOT NULL AND unit_id>0 AND (sum_money + sum_tax_money) > 0 "
|
||||
"AND bill_date>='2026-01-01' AND bill_date<='2026-09-30' GROUP BY unit_id ORDER BY amount DESC"),
|
||||
{"e": entity_id}).fetchall()
|
||||
pairs = [(int(r[0]), float(r[1])) for r in rows]
|
||||
total = sum(a for _, a in pairs)
|
||||
cum = lambda n: round(sum(a for _, a in pairs[:n]) / total * 100, 4) if total else None
|
||||
got = {"units": len(pairs), "total_wan": round(total / 10000, 2),
|
||||
"top1": round(pairs[0][1] / total * 100, 4) if pairs else None,
|
||||
"top2": round(pairs[1][1] / total * 100, 4) if len(pairs) > 1 else None,
|
||||
"top4_cum": cum(4), "top10_cum": cum(10)}
|
||||
checks = {}
|
||||
for k, exp in ANCHOR_2026_01_09.items():
|
||||
v = got.get(k)
|
||||
checks[k] = {"expected": exp, "got": v, "pass": (v is not None and abs(float(v) - exp) <= ANCHOR_TOL)}
|
||||
return {"anchor": got, "checks": checks, "ALL_PASS": all(c["pass"] for c in checks.values())}
|
||||
|
||||
|
||||
def main():
|
||||
ap = argparse.ArgumentParser()
|
||||
g = ap.add_mutually_exclusive_group()
|
||||
g.add_argument("--check", action="store_true")
|
||||
g.add_argument("--apply", action="store_true")
|
||||
g.add_argument("--verify", action="store_true")
|
||||
g.add_argument("--anchor", action="store_true")
|
||||
ap.add_argument("--entity", type=int, default=1)
|
||||
ap.add_argument("--db-url")
|
||||
ap.add_argument("--batch", default=DEFAULT_BATCH)
|
||||
ap.add_argument("--since")
|
||||
ap.add_argument("--until")
|
||||
ap.add_argument("--json", action="store_true")
|
||||
args = ap.parse_args()
|
||||
|
||||
engine, url = _engine(args)
|
||||
dialect = _dialect(url)
|
||||
|
||||
if args.anchor:
|
||||
res = anchor_assert(engine, args.entity)
|
||||
print(json.dumps(res, ensure_ascii=False, indent=2))
|
||||
return 0 if res["ALL_PASS"] else 1
|
||||
|
||||
res = run(engine, dialect, args.entity, args.batch, apply=args.apply,
|
||||
verify=args.verify, since=args.since, until=args.until)
|
||||
print(json.dumps(res, ensure_ascii=False, indent=2))
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -0,0 +1,247 @@
|
||||
#!/usr/bin/env python3
|
||||
"""CPA 客户获利性明细快照表 —— 独立特权 DDL 步（幂等 / 可回滚 / 带 journal）
|
||||
|
||||
任务：finance-20261003-cpa-customer-profitability-mvp-fullstack（P0-a）
|
||||
|
||||
为什么是独立脚本而不是 ORM 模型
|
||||
------------------------------
|
||||
运行库账号 `cma_api` 只有 SELECT + 表级 DML 白名单（**无 DDL**），建表须走特权通道
|
||||
（本机 unix socket + root，或专用迁移账号）。同时 `app/models/__init__.py` 此刻有**他单在途
|
||||
改动**（CMA-KPI-20261003 KPI 字典分层治理），本单不碰该共享文件 ⇒ 新表以独立迁移脚本落地，
|
||||
运行时以 raw SQL 访问（与既有 `zxt_masterbill` 同一形态）。
|
||||
|
||||
用法
|
||||
----
|
||||
python3 scripts/migrate_cpa_snapshot_20261004.py --check # 只读预检（默认）
|
||||
python3 scripts/migrate_cpa_snapshot_20261004.py --apply # 幂等建表 + 写 journal
|
||||
python3 scripts/migrate_cpa_snapshot_20261004.py --status # 历史 journal
|
||||
python3 scripts/migrate_cpa_snapshot_20261004.py --rollback latest
|
||||
python3 scripts/migrate_cpa_snapshot_20261004.py --show-create
|
||||
|
||||
选项
|
||||
----
|
||||
--db-url URL 显式连接串（离线演练用 `sqlite:///<scratch>.db`）
|
||||
--db-name NAME 目标库名（默认 env CMA_MIGRATE_DB_NAME → CMA_DB_NAME → cma）
|
||||
--journal-dir 默认 env CPA_MIGRATE_JOURNAL_DIR 或 backend/scripts/backups/db-migrate-journal/
|
||||
--force 回滚时允许删除**有数据**的表（默认拒绝，exit 3）
|
||||
--json 机器可读输出
|
||||
|
||||
连接凭据（口令只从环境读，禁止硬编码/回显）
|
||||
1) CMA_MIGRATE_DB_USER + CMA_MIGRATE_DB_PASS（专用迁移账号，TCP）
|
||||
2) 未设 → 本机 unix socket + root（socket 认证）
|
||||
⚠️ 应用运行账号（backend/.env 的 CMA_DB_USER = cma_api）不得被本脚本使用：无 DDL 权限。
|
||||
|
||||
幂等契约
|
||||
首跑 --apply：created=1；二跑 --apply：created=0 且零副作用（不 ALTER / 不 DROP / 不动数据行）。
|
||||
|
||||
退出码
|
||||
0 成功 ｜ 1 失败（fail-closed）｜ 2 用法错误 ｜ 3 回滚被拒（目标表有数据且未 --force）
|
||||
"""
|
||||
import argparse
|
||||
import datetime as _dt
|
||||
import json
|
||||
import os
|
||||
import subprocess
|
||||
import sys
|
||||
|
||||
TABLE = "customer_profitability_snapshot"
|
||||
|
||||
MYSQL_DDL = f"""
|
||||
CREATE TABLE IF NOT EXISTS `{TABLE}` (
|
||||
`id` INT NOT NULL AUTO_INCREMENT,
|
||||
`entity_id` INT NOT NULL COMMENT '企业ID（账套，多租户隔离）',
|
||||
`period` VARCHAR(7) NOT NULL COMMENT '期间 YYYY-MM（自然月，来源 zxt_masterbill.bill_date）',
|
||||
`unit_id` INT NOT NULL COMMENT '客户/往来单位ID（zxt_masterbill.unit_id；库内无名称源）',
|
||||
`revenue` DECIMAL(18,4) NOT NULL DEFAULT 0.0000 COMMENT '客户收入（万元；Σsum_money，含税原值口径）',
|
||||
`cogs_alloc` DECIMAL(18,4) NULL COMMENT '客户销货成本(分摊)（万元）——P1 fail-closed，未裁定口径前恒 NULL',
|
||||
`chan_sub` DECIMAL(18,4) NULL COMMENT '客户渠道补贴（万元）——P1 待打标台账，恒 NULL',
|
||||
`contrib` DECIMAL(18,4) NULL COMMENT '客户贡献毛利（万元）——P1，恒 NULL',
|
||||
`contrib_rate` DECIMAL(10,4) NULL COMMENT '客户贡献毛利率（%）——P1，恒 NULL',
|
||||
`rank_no` INT NULL COMMENT '期内收入排名（1=最高）',
|
||||
`calib_status` VARCHAR(30) NOT NULL DEFAULT 'revenue_only' COMMENT '口径状态: revenue_only / full(P1)',
|
||||
`fail_closed_reason` VARCHAR(500) NULL COMMENT '未落值列的原因（fail-closed 留痕，禁静默 0）',
|
||||
`created_at` DATETIME DEFAULT CURRENT_TIMESTAMP,
|
||||
`updated_at` DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
|
||||
PRIMARY KEY (`id`),
|
||||
UNIQUE KEY `uq_cpa_snap_entity_period_unit` (`entity_id`, `period`, `unit_id`),
|
||||
KEY `ix_cpa_snap_entity_period_rank` (`entity_id`, `period`, `rank_no`)
|
||||
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='客户获利性明细快照（CPA P0-a；每客户每期一行，幂等 upsert）'
|
||||
"""
|
||||
|
||||
SQLITE_DDL = f"""
|
||||
CREATE TABLE IF NOT EXISTS {TABLE} (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
entity_id INTEGER NOT NULL,
|
||||
period TEXT NOT NULL,
|
||||
unit_id INTEGER NOT NULL,
|
||||
revenue NUMERIC NOT NULL DEFAULT 0,
|
||||
cogs_alloc NUMERIC,
|
||||
chan_sub NUMERIC,
|
||||
contrib NUMERIC,
|
||||
contrib_rate NUMERIC,
|
||||
rank_no INTEGER,
|
||||
calib_status TEXT NOT NULL DEFAULT 'revenue_only',
|
||||
fail_closed_reason TEXT,
|
||||
created_at TEXT DEFAULT CURRENT_TIMESTAMP,
|
||||
updated_at TEXT DEFAULT CURRENT_TIMESTAMP,
|
||||
CONSTRAINT uq_cpa_snap_entity_period_unit UNIQUE (entity_id, period, unit_id)
|
||||
)
|
||||
"""
|
||||
|
||||
|
||||
def _now():
|
||||
return _dt.datetime.now().strftime("%Y%m%d-%H%M%S")
|
||||
|
||||
|
||||
def _journal_dir(arg):
|
||||
if arg:
|
||||
return arg
|
||||
env = os.environ.get("CPA_MIGRATE_JOURNAL_DIR")
|
||||
if env:
|
||||
return env
|
||||
here = os.path.dirname(os.path.abspath(__file__))
|
||||
d = os.path.join(here, "backups", "db-migrate-journal")
|
||||
os.makedirs(d, exist_ok=True)
|
||||
return d
|
||||
|
||||
|
||||
def _resolve_url(args):
|
||||
if args.db_url:
|
||||
return args.db_url
|
||||
if os.environ.get("CMA_MIGRATE_DB_URL"):
|
||||
return os.environ["CMA_MIGRATE_DB_URL"]
|
||||
user = os.environ.get("CMA_MIGRATE_DB_USER")
|
||||
pwd = os.environ.get("CMA_MIGRATE_DB_PASS", "")
|
||||
if user:
|
||||
host = os.environ.get("CMA_MIGRATE_DB_HOST", "127.0.0.1")
|
||||
port = os.environ.get("CMA_MIGRATE_DB_PORT", "3306")
|
||||
name = args.db_name or os.environ.get("CMA_MIGRATE_DB_NAME") or os.environ.get("CMA_DB_NAME") or "cma"
|
||||
from urllib.parse import quote_plus
|
||||
return f"mysql+pymysql://{user}:{quote_plus(pwd)}@{host}:{port}/{name}?charset=utf8mb4"
|
||||
name = args.db_name or os.environ.get("CMA_DB_NAME") or "cma"
|
||||
return f"mysql+pymysql://root@localhost/{name}?unix_socket=/var/run/mysqld/mysqld.sock&charset=utf8mb4"
|
||||
|
||||
|
||||
def _engine(args):
|
||||
from sqlalchemy import create_engine
|
||||
url = _resolve_url(args)
|
||||
kw = {}
|
||||
if url.startswith("sqlite"):
|
||||
kw["connect_args"] = {"check_same_thread": False}
|
||||
return create_engine(url, **kw), url
|
||||
|
||||
|
||||
def _table_exists(conn, url):
|
||||
from sqlalchemy import text
|
||||
if url.startswith("sqlite"):
|
||||
r = conn.execute(text("SELECT name FROM sqlite_master WHERE type='table' AND name=:t"), {"t": TABLE}).fetchall()
|
||||
else:
|
||||
r = conn.execute(text("SELECT TABLE_NAME FROM information_schema.TABLES WHERE TABLE_SCHEMA=DATABASE() AND TABLE_NAME=:t"),
|
||||
{"t": TABLE}).fetchall()
|
||||
return bool(r)
|
||||
|
||||
|
||||
def _rowcount(conn):
|
||||
from sqlalchemy import text
|
||||
try:
|
||||
return int(conn.execute(text(f"SELECT COUNT(*) FROM {TABLE}")).scalar() or 0)
|
||||
except Exception:
|
||||
return None
|
||||
|
||||
|
||||
def main():
|
||||
ap = argparse.ArgumentParser()
|
||||
g = ap.add_mutually_exclusive_group()
|
||||
g.add_argument("--check", action="store_true")
|
||||
g.add_argument("--apply", action="store_true")
|
||||
g.add_argument("--status", action="store_true")
|
||||
g.add_argument("--rollback", nargs="?", const="latest")
|
||||
g.add_argument("--show-create", action="store_true")
|
||||
ap.add_argument("--db-url")
|
||||
ap.add_argument("--db-name")
|
||||
ap.add_argument("--journal-dir")
|
||||
ap.add_argument("--force", action="store_true")
|
||||
ap.add_argument("--json", action="store_true")
|
||||
args = ap.parse_args()
|
||||
|
||||
engine, url = _engine(args)
|
||||
redacted = url.split("//")[0] + "//***"
|
||||
dialect = "sqlite" if url.startswith("sqlite") else "mysql"
|
||||
out = {"dialect": dialect, "table": TABLE, "url": redacted}
|
||||
|
||||
if args.status:
|
||||
d = _journal_dir(args.journal_dir)
|
||||
files = sorted(f for f in os.listdir(d) if f.startswith("cpa-snapshot-"))
|
||||
out["journals"] = files
|
||||
print(json.dumps(out, ensure_ascii=False, indent=2) if args.json else "\n".join(files) or "(no journal)")
|
||||
return 0
|
||||
|
||||
from sqlalchemy import text
|
||||
with engine.connect() as conn:
|
||||
exists = _table_exists(conn, url)
|
||||
rows = _rowcount(conn) if exists else None
|
||||
out.update(existing=exists, rowcount=rows)
|
||||
|
||||
if args.show_create:
|
||||
if not exists:
|
||||
out["show_create"] = None
|
||||
else:
|
||||
if dialect == "sqlite":
|
||||
out["show_create"] = conn.execute(text(
|
||||
"SELECT sql FROM sqlite_master WHERE type='table' AND name=:t"), {"t": TABLE}).scalar()
|
||||
else:
|
||||
out["show_create"] = conn.execute(text(f"SHOW CREATE TABLE `{TABLE}`")).fetchone()[1]
|
||||
print(json.dumps(out, ensure_ascii=False, indent=2))
|
||||
return 0
|
||||
|
||||
if args.rollback is not None:
|
||||
if not exists:
|
||||
out["action"] = "rollback-noop"; print(json.dumps(out, ensure_ascii=False)); return 0
|
||||
if rows and not args.force:
|
||||
out["action"] = "rollback-refused"; out["why"] = f"表内有 {rows} 行，未加 --force"
|
||||
print(json.dumps(out, ensure_ascii=False)); return 3
|
||||
jdir = _journal_dir(args.journal_dir)
|
||||
jf = os.path.join(jdir, f"cpa-snapshot-rollback-{_now()}.json")
|
||||
with open(jf, "w") as fh:
|
||||
json.dump({"table": TABLE, "rows_before": rows, "ts": _now()}, fh, ensure_ascii=False)
|
||||
with engine.begin() as c2:
|
||||
c2.execute(text(f"DROP TABLE {TABLE}" if dialect == "sqlite" else f"DROP TABLE `{TABLE}`"))
|
||||
out["action"] = "rolled-back"; out["journal"] = jf
|
||||
print(json.dumps(out, ensure_ascii=False, indent=2))
|
||||
return 0
|
||||
|
||||
if not args.apply:
|
||||
# --check：只读预检
|
||||
out["action"] = "check"
|
||||
out["would_create"] = not exists
|
||||
if exists:
|
||||
cols = conn.execute(text(
|
||||
"SELECT COLUMN_NAME FROM information_schema.COLUMNS WHERE TABLE_SCHEMA=DATABASE() AND TABLE_NAME=:t ORDER BY ORDINAL_POSITION"
|
||||
), {"t": TABLE}).fetchall() if dialect == "mysql" else conn.execute(
|
||||
text(f"PRAGMA table_info({TABLE})")).fetchall()
|
||||
out["columns"] = [c[0] for c in cols] if dialect == "mysql" else [c[1] for c in cols]
|
||||
print(json.dumps(out, ensure_ascii=False, indent=2) if args.json else
|
||||
f"[check] table={TABLE} existing={exists} rowcount={rows} would_create={not exists}")
|
||||
return 0
|
||||
|
||||
# --apply：幂等建表
|
||||
ddl = SQLITE_DDL if dialect == "sqlite" else MYSQL_DDL
|
||||
jdir = _journal_dir(args.journal_dir)
|
||||
created_new = 0
|
||||
if not exists:
|
||||
with engine.begin() as c2:
|
||||
c2.execute(text(ddl))
|
||||
created_new = 1
|
||||
with engine.connect() as conn3:
|
||||
assert _table_exists(conn3, url), "建表后自检失败"
|
||||
jf = os.path.join(jdir, f"cpa-snapshot-{_now()}{'' if created_new else '-noop'}.json")
|
||||
with open(jf, "w") as fh:
|
||||
json.dump({"table": TABLE, "created": created_new, "ddl": ddl.strip(), "ts": _now()}, fh, ensure_ascii=False, indent=2)
|
||||
out.update(action="applied", created_new=created_new, journal=jf,
|
||||
rowcount_after=_rowcount(conn3))
|
||||
print(json.dumps(out, ensure_ascii=False, indent=2))
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -0,0 +1,123 @@
|
||||
-- CMA 客户获利能力（CPA / Customer Profitability）KPI 定义 — 2026-10-04
|
||||
-- 任务: finance-20261003-cpa-customer-profitability-mvp-fullstack（P0-a；派单方 财务Bot，放行 任总 2026-10-03 18:17 CST DM「立」）
|
||||
-- 主体范围: 陕西酣客 entity_id=1（zxt_masterbill 唯一有数主体）
|
||||
-- 口径裁定与失败原因: 见 backend/app/utils/cpa_caliber.py 与
|
||||
-- backend/scripts/kpi_customer_profitability_deriver.py 头部文档
|
||||
--
|
||||
-- 动作:
|
||||
-- ① 新增 C_CUST_REVENUE 客户收入（万元） status=active ← 派生器当即可供值
|
||||
-- ② 新增 C_CUST_COUNT 客户数（个） status=active ← 派生器当即可供值
|
||||
-- ③ 新增 5 条 P1 定义（fail-closed，**不供值**）status=inactive ← 口径已登记，待数据/裁定
|
||||
-- C_CUST_COGS_ALLOC / C_CUST_CHAN_SUB / C_CUST_CONTRIB / C_CUST_CONTRIB_RATE / C_CUST_AVG_CONTRIB
|
||||
-- （inactive 而非 active：避免「有定义无值」在看板上伪装成「无数据」，P0-b 三态按「未定义·待建」显示）
|
||||
-- * C_CUST_CONCENTRATION 复用既有 kpi_id=23（formula 前5大客户收入/总收入×100%），本 SQL 不新增/不改名；
|
||||
-- 其 2026-01~09 九期现网值（source_batch finance-20261002-kpi6, verified）**原样保留**，派生器只补缺口期次。
|
||||
--
|
||||
-- 幂等: NOT EXISTS 守卫，可安全重跑（重跑=零副作用）
|
||||
-- 注意: (entity_id, kpi_code) 唯一键 uk_entity_kpi
|
||||
|
||||
-- ① 客户收入（万元）
|
||||
INSERT INTO kpi_definitions
|
||||
(entity_id, kpi_code, kpi_name, dimension, category, formula, formula_desc,
|
||||
data_source_type, data_source, data_owner, frequency, unit, target_calc_type,
|
||||
kpi_level, status, epic, bot_source, data_source_config)
|
||||
SELECT 1, 'C_CUST_REVENUE', '客户收入', 'customer', 'customer_profitability',
|
||||
'Σ 客户销售额（万元）',
|
||||
'期内客户收入合计 = Σ zxt_masterbill.sum_money（entity_id=1, unit_id>0, sum_money>0, bill_date 期内）÷10000；'
|
||||
'口径单一事实源 app/utils/cpa_caliber.py（与客户集中度预警同源）',
|
||||
'erp', '智享通销售单据 zxt_masterbill（unit_id=往来单位/客户）', '财务部', 'monthly', '万元', 'amount',
|
||||
'strategic', 'active', 'Epic2', 'fullstack-bot',
|
||||
'{"source_ids": [], "deriver": "scripts/kpi_customer_profitability_deriver.py", "basis": "zxt_masterbill.sum_money(含税原值)"}'
|
||||
FROM DUAL
|
||||
WHERE NOT EXISTS (SELECT 1 FROM (SELECT id FROM kpi_definitions
|
||||
WHERE entity_id = 1 AND kpi_code = 'C_CUST_REVENUE') AS t);
|
||||
|
||||
-- ② 客户数（个）
|
||||
INSERT INTO kpi_definitions
|
||||
(entity_id, kpi_code, kpi_name, dimension, category, formula, formula_desc,
|
||||
data_source_type, data_source, data_owner, frequency, unit, target_calc_type,
|
||||
kpi_level, status, epic, bot_source, data_source_config)
|
||||
SELECT 1, 'C_CUST_COUNT', '客户数', 'customer', 'customer_profitability',
|
||||
'期内活跃客户数（个）',
|
||||
'期内 zxt_masterbill 活跃往来单位数（unit_id 去重；含极小金额客户，与客户收入聚合同过滤）',
|
||||
'erp', '智享通销售单据 zxt_masterbill', '财务部', 'monthly', '个', 'number',
|
||||
'strategic', 'active', 'Epic2', 'fullstack-bot',
|
||||
'{"source_ids": [], "deriver": "scripts/kpi_customer_profitability_deriver.py"}'
|
||||
FROM DUAL
|
||||
WHERE NOT EXISTS (SELECT 1 FROM (SELECT id FROM kpi_definitions
|
||||
WHERE entity_id = 1 AND kpi_code = 'C_CUST_COUNT') AS t);
|
||||
|
||||
-- ③ P1 fail-closed 定义（口径已登记，供值待裁定/待打标；status=inactive）
|
||||
INSERT INTO kpi_definitions
|
||||
(entity_id, kpi_code, kpi_name, dimension, category, formula, formula_desc,
|
||||
data_source_type, data_source, data_owner, frequency, unit, target_calc_type,
|
||||
kpi_level, status, epic, bot_source, data_source_config)
|
||||
SELECT 1, 'C_CUST_COGS_ALLOC', '客户销货成本(分摊)', 'customer', 'customer_profitability',
|
||||
'客户收入 × 公司整体销货成本率(5401÷5001)',
|
||||
'【P1 fail-closed 未供值】基数口径未决：客户收入基座 zxt_masterbill 含税单据流（2026-01~09=4,883.52万）'
|
||||
'与凭证账 5401/5001（收入量级~900万）相差约5.4×，直接相乘无经济意义；且须与「统一后的 CVP 变动成本口径」'
|
||||
'（finance-20261003-cvp-fix-and-bohai-coverage 第⑤项）一致 ⇒ 待财务裁定基数后落值。禁写 0/分摊值。',
|
||||
'derived', '待建（scripts/kpi_customer_profitability_deriver.py 已留位）', '财务部', 'monthly', '万元', 'amount',
|
||||
'strategic', 'inactive', 'Epic2', 'fullstack-bot',
|
||||
'{"fail_closed": true, "reason_code": "cogs_base_undecided", "pending_on": "finance-20261003-cvp-fix-and-bohai-coverage#5"}'
|
||||
FROM DUAL
|
||||
WHERE NOT EXISTS (SELECT 1 FROM (SELECT id FROM kpi_definitions
|
||||
WHERE entity_id = 1 AND kpi_code = 'C_CUST_COGS_ALLOC') AS t);
|
||||
|
||||
INSERT INTO kpi_definitions
|
||||
(entity_id, kpi_code, kpi_name, dimension, category, formula, formula_desc,
|
||||
data_source_type, data_source, data_owner, frequency, unit, target_calc_type,
|
||||
kpi_level, status, epic, bot_source, data_source_config)
|
||||
SELECT 1, 'C_CUST_CHAN_SUB', '客户渠道补贴', 'customer', 'customer_profitability',
|
||||
'Σ 客户专属渠道补贴',
|
||||
'【P1 fail-closed 未供值】571103 渠道补贴目前仅有总额、不可按客户/渠道拆分；须先落「渠道补贴台账」'
|
||||
'（人员/渠道/客户 × 期间 × 金额）再取值。禁按收入占比硬摊。',
|
||||
'derived', '待建（渠道补贴打标台账）', '财务部', 'monthly', '万元', 'amount',
|
||||
'strategic', 'inactive', 'Epic2', 'fullstack-bot',
|
||||
'{"fail_closed": true, "reason_code": "channel_subsidy_untagged"}'
|
||||
FROM DUAL
|
||||
WHERE NOT EXISTS (SELECT 1 FROM (SELECT id FROM kpi_definitions
|
||||
WHERE entity_id = 1 AND kpi_code = 'C_CUST_CHAN_SUB') AS t);
|
||||
|
||||
INSERT INTO kpi_definitions
|
||||
(entity_id, kpi_code, kpi_name, dimension, category, formula, formula_desc,
|
||||
data_source_type, data_source, data_owner, frequency, unit, target_calc_type,
|
||||
kpi_level, status, epic, bot_source, data_source_config)
|
||||
SELECT 1, 'C_CUST_CONTRIB', '客户贡献毛利', 'customer', 'customer_profitability',
|
||||
'客户收入 − 客户销货成本(分摊) − 客户专属渠道补贴',
|
||||
'【P1 fail-closed 未供值】依赖 C_CUST_COGS_ALLOC 与 C_CUST_CHAN_SUB，二者皆未落值 ⇒ 不计算、不写 0。',
|
||||
'derived', '待建', '财务部', 'monthly', '万元', 'amount',
|
||||
'strategic', 'inactive', 'Epic2', 'fullstack-bot',
|
||||
'{"fail_closed": true, "reason_code": "depends_on_cogs_alloc_and_chan_sub"}'
|
||||
FROM DUAL
|
||||
WHERE NOT EXISTS (SELECT 1 FROM (SELECT id FROM kpi_definitions
|
||||
WHERE entity_id = 1 AND kpi_code = 'C_CUST_CONTRIB') AS t);
|
||||
|
||||
INSERT INTO kpi_definitions
|
||||
(entity_id, kpi_code, kpi_name, dimension, category, formula, formula_desc,
|
||||
data_source_type, data_source, data_owner, frequency, unit, target_calc_type,
|
||||
kpi_level, status, epic, bot_source, data_source_config)
|
||||
SELECT 1, 'C_CUST_CONTRIB_RATE', '客户贡献毛利率', 'customer', 'customer_profitability',
|
||||
'客户贡献毛利 ÷ 客户收入 × 100%',
|
||||
'【P1 fail-closed 未供值】依赖 C_CUST_CONTRIB ⇒ 不计算。',
|
||||
'derived', '待建', '财务部', 'monthly', '%', 'ratio',
|
||||
'strategic', 'inactive', 'Epic2', 'fullstack-bot',
|
||||
'{"fail_closed": true, "reason_code": "depends_on_contrib"}'
|
||||
FROM DUAL
|
||||
WHERE NOT EXISTS (SELECT 1 FROM (SELECT id FROM kpi_definitions
|
||||
WHERE entity_id = 1 AND kpi_code = 'C_CUST_CONTRIB_RATE') AS t);
|
||||
|
||||
INSERT INTO kpi_definitions
|
||||
(entity_id, kpi_code, kpi_name, dimension, category, formula, formula_desc,
|
||||
data_source_type, data_source, data_owner, frequency, unit, target_calc_type,
|
||||
kpi_level, status, epic, bot_source, data_source_config)
|
||||
SELECT 1, 'C_CUST_AVG_CONTRIB', '客户平均贡献值', 'customer', 'customer_profitability',
|
||||
'期内客户贡献毛利合计 ÷ 期内活跃客户数',
|
||||
'【P1 fail-closed 未供值】依赖 C_CUST_CONTRIB ⇒ 不计算。页面「客户平均贡献值」卡即此码；'
|
||||
'P0 阶段按「未定义·待建」显示（定义已登记但 inactive）。',
|
||||
'derived', '待建', '财务部', 'monthly', '万元', 'amount',
|
||||
'strategic', 'inactive', 'Epic2', 'fullstack-bot',
|
||||
'{"fail_closed": true, "reason_code": "depends_on_contrib"}'
|
||||
FROM DUAL
|
||||
WHERE NOT EXISTS (SELECT 1 FROM (SELECT id FROM kpi_definitions
|
||||
WHERE entity_id = 1 AND kpi_code = 'C_CUST_AVG_CONTRIB') AS t);
|
||||
@@ -3,6 +3,42 @@
|
||||
<div class="page-header">
|
||||
<h3 class="page-title">客户维度KPI看板</h3>
|
||||
</div>
|
||||
|
||||
<!-- 客户标准指标族（9 卡三态：真值 / 无数据 / 未定义·待建）—— CPA P0-b 2026-10-04 -->
|
||||
<el-card shadow="never" class="section-card">
|
||||
<template #header>
|
||||
<div class="card-header-flex">
|
||||
<span>客户标准指标族（9 项）</span>
|
||||
<span class="std-summary">
|
||||
真值 {{ stdSummary.value }} · 无数据 {{ stdSummary.no_data }} · 未定义·待建 {{ stdSummary.undefined }}
|
||||
</span>
|
||||
</div>
|
||||
</template>
|
||||
<div class="std-grid">
|
||||
<div
|
||||
v-for="it in stdItems" :key="it.name"
|
||||
class="std-card" :class="'std-' + it.state"
|
||||
>
|
||||
<div class="std-head">
|
||||
<span class="std-name">{{ it.name }}</span>
|
||||
<span class="std-badge" :class="'badge-' + it.state">{{ it.state_label }}</span>
|
||||
</div>
|
||||
<div class="std-value">
|
||||
<template v-if="it.state === 'value'">
|
||||
<span class="std-num">{{ it.actual_value }}</span>
|
||||
<span class="std-unit">{{ it.unit }}</span>
|
||||
</template>
|
||||
<span v-else-if="it.state === 'no_data'" class="std-ph">定义在库 · 暂无数据</span>
|
||||
<span v-else class="std-ph">未定义 · 待建</span>
|
||||
</div>
|
||||
<div class="std-meta">
|
||||
<span v-if="it.kpi_code">{{ it.kpi_code }}</span>
|
||||
<span v-if="it.period">最近期间 {{ it.period }}</span>
|
||||
<span v-else>目标 {{ it.target_value }}{{ it.unit }}</span>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</el-card>
|
||||
<KPIListView
|
||||
ref="kpiListRef"
|
||||
:dimension="'customer'"
|
||||
@@ -58,6 +94,22 @@ const CUSTOMER_TEMPLATES = [
|
||||
{ name: 'NPS净推荐值', unit: '分', targetValue: 60 },
|
||||
]
|
||||
|
||||
// ── 客户标准指标族三态（CPA P0-b 2026-10-04）──
|
||||
// 数据源 = GET /customer-dashboard/standard-indicators（只读；显式白名单映射，不做名称模糊匹配）
|
||||
// state: value=真值 / no_data=定义在库无值 / undefined=KPI 库无定义（未定义·待建）——禁止显示为 0
|
||||
const stdItems = ref<any[]>([])
|
||||
const stdSummary = ref<any>({ value: 0, no_data: 0, undefined: 0, total: 0 })
|
||||
async function loadStandardIndicators() {
|
||||
const eid = Number(localStorage.getItem('cma_entity_id') || 1)
|
||||
try {
|
||||
const r: any = await api.get('/customer-dashboard/standard-indicators', { params: { entity_id: eid } })
|
||||
stdItems.value = r.items || []
|
||||
stdSummary.value = r.summary || stdSummary.value
|
||||
} catch {
|
||||
stdItems.value = []
|
||||
}
|
||||
}
|
||||
|
||||
// ── 趋势分析 ──
|
||||
const kpiListRef = ref<InstanceType<typeof KPIListView> | null>(null)
|
||||
const trendType = ref('monthly')
|
||||
@@ -116,6 +168,7 @@ function renderChart() {
|
||||
}
|
||||
|
||||
onMounted(() => {
|
||||
loadStandardIndicators()
|
||||
// 等待 KPIListView 加载完成后加载趋势
|
||||
setTimeout(() => loadTrend(), 500)
|
||||
// 尝试加载 ECharts
|
||||
@@ -139,4 +192,21 @@ onUnmounted(() => {
|
||||
.customer-dashboard { padding: 0; }
|
||||
.section-card { margin-bottom: 16px; margin-top: 16px; }
|
||||
.card-header-flex { display: flex; justify-content: space-between; align-items: center; }
|
||||
.std-summary { font-size: 12px; color: #909399; }
|
||||
.std-grid { display: grid; grid-template-columns: repeat(auto-fill, minmax(200px, 1fr)); gap: 12px; }
|
||||
.std-card { border: 1px solid #ebeef5; border-radius: 8px; padding: 12px 14px; background: #fff; }
|
||||
.std-card.std-value { border-left: 3px solid #67c23a; }
|
||||
.std-card.std-no_data { border-left: 3px solid #e6a23c; }
|
||||
.std-card.std-undefined { border-left: 3px solid #dcdfe6; background: #fafafa; }
|
||||
.std-head { display: flex; justify-content: space-between; align-items: center; gap: 6px; }
|
||||
.std-name { font-size: 13px; font-weight: 600; color: #303133; }
|
||||
.std-badge { font-size: 11px; padding: 1px 6px; border-radius: 3px; white-space: nowrap; }
|
||||
.badge-value { background: #f0f9eb; color: #67c23a; }
|
||||
.badge-no_data { background: #fdf6ec; color: #e6a23c; }
|
||||
.badge-undefined { background: #f4f4f5; color: #909399; }
|
||||
.std-value { margin: 8px 0 4px; min-height: 32px; display: flex; align-items: baseline; }
|
||||
.std-num { font-size: 22px; font-weight: 700; color: #303133; }
|
||||
.std-unit { font-size: 12px; color: #909399; margin-left: 4px; }
|
||||
.std-ph { font-size: 13px; color: #a8abb2; }
|
||||
.std-meta { display: flex; gap: 10px; font-size: 11px; color: #c0c4cc; }
|
||||
</style>
|
||||
|
||||
Reference in New Issue
Block a user