fix(alerts): enforce caliber rulings R1-R4 for alert generation
R1: exclude status=demo entities from alert traversal (alert_generator / deviation_engine / kpi_bep_deriver / alert_rules / cash engine) R2: only generate alerts within the last 6 calendar months (incl. current) R3: only regular month periods (YYYY-MM) participate R4: decouple generation from push - empty notification_channels never blocks Single source of truth: app/utils/alert_entity_scope.py
This commit is contained in:
Hermes CI Fix
@@ -14,6 +14,8 @@ from app.database import get_db, Base
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from app.deps import get_entity_id
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from app.auth_middleware import require_auth, require_role
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from app.models import KPIDefinition, KPIValue, KPIAlert, OperationLog
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# 裁定 R1（2026-09-19 财务口径）：demo 账套不参与预警生成/遍历（单一事实源）
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from app.utils.alert_entity_scope import is_excluded_entity
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logger = logging.getLogger("alert_rules")
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@@ -257,7 +259,14 @@ def generate_default_rules(db: Session = Depends(get_db), entity_id: int = Depen
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@router.post("/check-all")
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def run_all_alert_checks(db: Session = Depends(get_db), entity_id: int = Depends(get_entity_id)):
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"""执行当前企业所有KPI的预警检查 — 生成新的预警记录（账套隔离 2026-08-31）"""
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"""执行当前企业所有KPI的预警检查 — 生成新的预警记录（账套隔离 2026-08-31）
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R1（裁定 2026-09-19）：demo 演示账套不参与预警生成 → 直接返回 skipped。
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"""
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if is_excluded_entity(db, entity_id):
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logger.info("预警检查跳过（demo 账套 R1）: entity_id=%s", entity_id)
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return {"message": f"账套 {entity_id} 为 demo 演示账套，按 R1 不参与预警生成", "generated": 0,
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"skipped": True, "reason": "R1_demo_entity_excluded"}
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rules = db.query(AlertRule).filter(
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AlertRule.enabled == 1, AlertRule.entity_id == entity_id).all()
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kpi_cache = {}
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@@ -642,7 +651,14 @@ def _check_forecast_alerts(db: Session, entity_id: int = 1) -> int:
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@router.post("/check-forecast")
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def run_forecast_alert_check(db: Session = Depends(get_db), entity_id: int = Depends(get_entity_id)):
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"""执行预测值预警检查 — 检查未来7天预测值是否超限（账套隔离 2026-08-31）"""
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"""执行预测值预警检查 — 检查未来7天预测值是否超限（账套隔离 2026-08-31）
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R1（裁定 2026-09-19）：demo 演示账套不参与预警生成。
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"""
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if is_excluded_entity(db, entity_id):
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logger.info("预测值预警检查跳过（demo 账套 R1）: entity_id=%s", entity_id)
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return {"message": f"账套 {entity_id} 为 demo 演示账套，按 R1 不参与预警生成",
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"generated": 0, "skipped": True, "reason": "R1_demo_entity_excluded"}
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generated = _check_forecast_alerts(db, entity_id=entity_id)
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return {"message": f"预测值预警检查完成: 生成{generated}条", "generated": generated}
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@@ -690,7 +706,14 @@ def run_forecast_deviation_check(
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):
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"""预测偏差检查（升级2b, 2026-08-25）— alert_rules type=forecast_deviation
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对每条偏差规则: 取最新预测log(kpi_forecast_log) vs 该期实际值(kpi_values)，
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偏差 > threshold_pct → 生成/更新 pending 预警（去重）"""
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偏差 > threshold_pct → 生成/更新 pending 预警（去重）
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R1（裁定 2026-09-19）：demo 演示账套不参与预警生成。
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"""
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if is_excluded_entity(db, entity_id):
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logger.info("预测偏差检查跳过（demo 账套 R1）: entity_id=%s", entity_id)
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return {"message": f"账套 {entity_id} 为 demo 演示账套，按 R1 不参与预警生成",
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"generated": 0, "skipped": True, "reason": "R1_demo_entity_excluded"}
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from app.models import KpiForecastLog
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rules = db.query(AlertRule).filter(
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AlertRule.entity_id == entity_id,
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@@ -861,7 +884,14 @@ def run_customer_concentration_check(
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entity_id: int = Depends(get_entity_id),
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):
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"""客户集中度检查（P2 2026-09-10）— 遍历本企业 customer_concentration 规则，
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计算客户收入占比，超阈值生成/更新 pending 预警（去重）。"""
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计算客户收入占比，超阈值生成/更新 pending 预警（去重）。
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R1（裁定 2026-09-19）：demo 演示账套不参与预警生成。
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"""
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if is_excluded_entity(db, entity_id):
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logger.info("客户集中度检查跳过（demo 账套 R1）: entity_id=%s", entity_id)
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return {"message": f"账套 {entity_id} 为 demo 演示账套，按 R1 不参与预警生成",
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"generated": 0, "skipped": True, "reason": "R1_demo_entity_excluded"}
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rules = db.query(AlertRule).filter(
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AlertRule.entity_id == entity_id,
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AlertRule.rule_type == "customer_concentration",
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@@ -0,0 +1,96 @@
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# -*- coding: utf-8 -*-
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"""预警「参与范围」口径 —— 单一事实源（财务裁定 R1/R2/R3，2026-09-19）
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依据：`wecom-finance/reports/CMA_预警口径裁定_20260919.md`（任总 2026-09-18「按建议执行」）
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- **R1 账套范围**：`entities.status = 'demo'` 的账套（演示账套）**不参与预警生成/遍历**
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—— demo 仅用于演示展示，不产生业务预警。
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- **R2 期间窗口**：预警遍历期间 = **当月往前 6 个自然月（含当月）**；更早期间**不再新生成**。
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与裁定 2b（各 KPI 最近可用期间）叠加：`max(可用期间下限, 当月-6月)`。
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- **R3 规整月期间**：仅 `YYYY-MM` 参与；`H1/H2/FY`、纯年份等伪期间**一律不参与**。
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约定：所有预警生成入口（alert_generator / deviation_engine / kpi_bep_deriver /
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alert_rules 生成端点 / cash_forecast_engine）**只调本模块的入口函数**，
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禁止在调用点各写一份 `status == 'demo'` / 期间正则 / 窗口算术（避免多处漂移）。
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"""
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import logging
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import re
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from datetime import datetime
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from typing import Optional
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from app.models import Entity, KPIDefinition
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logger = logging.getLogger("cma.alert_scope")
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#: R1：不参与预警的账套状态
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ALERT_EXCLUDED_ENTITY_STATUSES = ("demo",)
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#: R2：期间窗口长度（含当月，6 = 当月 + 往前 5 个月）
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ALERT_WINDOW_MONTHS = 6
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#: R3：规整月期间（严格校验 01–12，`2026-13` 之类非法月同样不参与）
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MONTH_PERIOD_RE = r"^[0-9]{4}-(?:0[1-9]|1[0-2])$"
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_MONTH_PERIOD_RE = re.compile(MONTH_PERIOD_RE)
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def excluded_entity_ids(db_session) -> set:
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"""R1：返回不参与预警遍历的账套 id 集合（当前 status='demo' → entity 3/4/5/6）。
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fail-open：读不到 entities 表（测试库/权限异常）时返回空集并记 WARNING——
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口径缺失不应把预警主流程整条打断（生成链路另有 fail-safe）。
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"""
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try:
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rows = db_session.query(Entity.id).filter(
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Entity.status.in_(ALERT_EXCLUDED_ENTITY_STATUSES)
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).all()
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return {int(r[0]) for r in rows}
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except Exception as e: # pragma: no cover - 防御分支
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logger.warning("读取 entities.status=%s 失败，本次按「不排除任何账套」处理: %s",
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list(ALERT_EXCLUDED_ENTITY_STATUSES), e)
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return set()
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def is_excluded_entity(db_session, entity_id: Optional[int]) -> bool:
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"""R1：单个账套是否被排除（None → 按默认账套 1 处理，与 KPIAlert.entity_id 缺省一致）"""
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return int(entity_id or 1) in excluded_entity_ids(db_session)
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def kpi_excluded(db_session, kpi: KPIDefinition, excluded: Optional[set] = None) -> bool:
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"""R1：KPI 归属账套是否被排除（可传入预取的 excluded 集合，避免循环内重复查询）"""
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eids = excluded if excluded is not None else excluded_entity_ids(db_session)
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return int(getattr(kpi, "entity_id", None) or 1) in eids
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def window_lower_period(now: Optional[datetime] = None) -> str:
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"""R2：期间窗口下限 = 当月往前 6 个自然月（含当月）→ 当月-5 月。
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2026-09 → `2026-04`（窗口 = 2026-04 ~ 2026-09）。
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"""
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now = now or datetime.now()
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months = now.month - (ALERT_WINDOW_MONTHS - 1)
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year = now.year
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while months <= 0:
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months += 12
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year -= 1
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return "%04d-%02d" % (year, months)
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def is_month_period(period) -> bool:
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"""R3：是否规整月期间（YYYY-MM）"""
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return bool(_MONTH_PERIOD_RE.fullmatch(str(period or "")))
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def period_in_window(period, now: Optional[datetime] = None) -> bool:
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"""R3 + R2：期间是否可参与预警生成（规整月 + 落在窗口内）"""
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if not is_month_period(period):
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return False
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return str(period) >= window_lower_period(now)
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def scope_summary(db_session, now: Optional[datetime] = None) -> dict:
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"""口径证据（写日志/报告用）：被排除账套 + 窗口下限"""
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return {
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"excluded_entities": sorted(excluded_entity_ids(db_session)),
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"window_lower_period": window_lower_period(now),
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"window_months": ALERT_WINDOW_MONTHS,
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}
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@@ -806,9 +806,17 @@ def check_cash_alerts(db: Session, entity_id: int = 1) -> dict:
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（此前博海走无排序兜底 → 命中 uk_entity_kpi 索引必中 BH_ADM_EXPENSE(437 管理费用)）
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F3 去重命中时刷新文本/等级/逾期天数/归属（此前直接 continue → 金额与天数永久冻结在首版）
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F4 余额快照批次行按开关处理（默认 skip，不再逐户生成伪"到期未收款"）
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R1（裁定 2026-09-19）：demo 演示账套不产生业务预警 → 直接返回 skipped。
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"""
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import json as _json
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from app.models import KPIAlert, CashPlan, KPIDefinition
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from app.utils.alert_entity_scope import is_excluded_entity
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if is_excluded_entity(db, entity_id):
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logger.info("资金预警检查跳过（demo 账套 R1）: entity_id=%s", entity_id)
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return {"entity_id": entity_id, "skipped": True, "reason": "R1_demo_entity_excluded",
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"new_alerts": [], "refreshed": []}
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result = forecast_cash_flow_with_plans(entity_id, db, days=30)
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new_alerts = []
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@@ -14,6 +14,10 @@ from typing import Optional
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from app.database import get_session_local
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from app.models import KPIDefinition, KPIValue, KPIAlert, BudgetPlan, SystemConfig
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# 裁定 R1/R2/R3（2026-09-19 财务口径）：demo 账套排除 / 期间窗口 / 规整月期间
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from app.utils.alert_entity_scope import (
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excluded_entity_ids, kpi_excluded, period_in_window, window_lower_period,
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)
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logger = logging.getLogger("cma.deviation")
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@@ -311,16 +315,31 @@ def build_deviation_alert(db, kpi, period: str, entity_id: int = 1, min_rate: fl
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def run_deviation_check(db_session, period: str = None) -> int:
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"""运行差异预警检查，返回新增预警数（统一走 build_deviation_alert，P2-⑤）"""
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"""运行差异预警检查，返回新增预警数（统一走 build_deviation_alert，P2-⑤）
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2026-09-19 财务口径裁定 R1/R2/R3（`alert_entity_scope`）：
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· R1 —— `status='demo'` 的账套不参与遍历（demo 仅演示，不产生业务预警）；
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· R2/R3 —— 期间须为规整月 `YYYY-MM` 且落在窗口（当月往前 6 个自然月，含当月）内。
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"""
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if period is None:
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period = datetime.now().strftime("%Y-%m")
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if not period_in_window(period):
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logger.warning(" 差异预警跳过（R2/R3）: 期间 %s 非规整月或早于窗口下限 %s",
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period, window_lower_period())
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return 0
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excluded = excluded_entity_ids(db_session)
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kpis = db_session.query(KPIDefinition).filter(
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KPIDefinition.status == "active"
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).all()
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new_count = 0
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skipped_demo = 0
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for kpi in kpis:
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# R1（裁定 2026-09-19）：demo 演示账套不参与预警遍历
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if kpi_excluded(db_session, kpi, excluded):
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skipped_demo += 1
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continue
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# 1. 差异预警：实际 vs 预算（统一逻辑）
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result = build_deviation_alert(db_session, kpi, period)
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if result["triggered"]:
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@@ -375,6 +394,8 @@ def run_deviation_check(db_session, period: str = None) -> int:
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new_count += 1
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logger.info(f" 新增趋势预警 [{trend['level']}] {trend_alert_msg}")
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if skipped_demo:
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logger.info(" 差异预警跳过 demo 账套 KPI %s 项（R1，裁定 2026-09-19）", skipped_demo)
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db_session.commit()
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return new_count
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@@ -20,6 +20,11 @@ from app.utils.threshold_parser import eval_threshold, LEVEL_PRIORITY
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# 裁定2a（2026-09-17 财务口径）：比率类指标统一「百分比(%)」口径（取数×100），
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# 未核对/疑似单位错配的项降级待核（不落预警、不推送）
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from app.utils.caliber_units import resolve_caliber
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# 裁定 R1/R2/R3（2026-09-19 财务口径）：账套范围（demo 排除）/ 期间窗口 / 规整月期间
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from app.utils.alert_entity_scope import (
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ALERT_WINDOW_MONTHS, excluded_entity_ids, is_month_period, kpi_excluded,
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period_in_window, window_lower_period,
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)
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logger = logging.getLogger("cma.alert_gen")
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@@ -86,7 +91,7 @@ def _check_threshold(actual: float, threshold_expr: str, level: str) -> tuple:
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def run_alert_check(db_session, period: Optional[str] = None, dry_run: bool = False,
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stats: Optional[dict] = None) -> int:
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stats: Optional[dict] = None, now: Optional[datetime] = None) -> int:
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"""检查所有KPI的实际值是否触发预警，返回（将）新生成的预警数
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2026-09-17 财务口径裁定 2a/2b：
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@@ -95,12 +100,29 @@ def run_alert_check(db_session, period: Optional[str] = None, dry_run: bool = Fa
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· **单位（2a）**：判定前经 resolve_caliber() 归一到「百分比(%)」口径（取数×100，
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与阈值 150/80 同量纲）；**未核对/疑似单位错配**的项降级待核 → 不落预警、不推送；
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· dry_run=True → 只计算不写库（抽查复核与放行前证据用）。
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2026-09-19 财务口径裁定 R1/R2/R3（`alert_entity_scope` 单一事实源）：
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· **R1 账套**：`status='demo'` 的账套（演示账套）不参与遍历 → 跳过并计
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`skipped_demo_kpis`；
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· **R2 期间窗口**：仅生成「当月往前 6 个自然月（含当月）」内的预警；更早期间跳过
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（`out_of_window`），与 2b 叠加 = max(各 KPI 最近可用期间, 当月-6月)；
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· **R3 伪期间**：仅规整月期间 YYYY-MM 参与，H1/H2/FY 跳过（`skipped_pseudo_period`）。
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· now 参数仅用于口径复算/测试（缺省=系统当前时间）。
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"""
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st = stats if stats is not None else {}
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window_lower = window_lower_period(now)
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excluded_eids = excluded_entity_ids(db_session)
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for k, v in (("period_source", "fixed" if period else "per_kpi_latest"), ("period_fixed", period),
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("periods_used", {}), ("normalized", 0), ("normalized_kpis", []),
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("dimension_suspect", 0), ("suspect_kpis", []), ("no_period", 0),
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("no_value", 0), ("planned", []), ("skipped_existing", 0)):
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("no_value", 0), ("planned", []), ("skipped_existing", 0),
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# R1/R2/R3 口径证据
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("excluded_demo_entities", sorted(excluded_eids)),
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("window_lower_period", window_lower),
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("window_months", ALERT_WINDOW_MONTHS),
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("skipped_demo_kpis", 0), ("demo_kpis", []),
|
||||
("skipped_pseudo_period", 0), ("pseudo_period_kpis", []),
|
||||
("out_of_window", 0), ("out_of_window_kpis", [])):
|
||||
st.setdefault(k, v)
|
||||
|
||||
kpis = db_session.query(KPIDefinition).filter(
|
||||
@@ -109,6 +131,12 @@ def run_alert_check(db_session, period: Optional[str] = None, dry_run: bool = Fa
|
||||
|
||||
new_count = 0
|
||||
for kpi in kpis:
|
||||
# R1（裁定 2026-09-19）：demo 演示账套不参与预警遍历
|
||||
if kpi_excluded(db_session, kpi, excluded_eids):
|
||||
st["skipped_demo_kpis"] += 1
|
||||
st["demo_kpis"].append("%s/e%s" % (kpi.kpi_code, kpi.entity_id or 1))
|
||||
continue
|
||||
|
||||
# 跳过无阈值的KPI
|
||||
thr = {
|
||||
"red": kpi.threshold_red,
|
||||
@@ -125,6 +153,21 @@ def run_alert_check(db_session, period: Optional[str] = None, dry_run: bool = Fa
|
||||
logger.warning(f" 跳过（无可用期间）: {kpi.kpi_name} 无任何 YYYY-MM 实测值")
|
||||
continue
|
||||
|
||||
# R3（裁定 2026-09-19）：仅规整月期间 YYYY-MM 参与，伪期间一律不参与
|
||||
if not is_month_period(p):
|
||||
st["skipped_pseudo_period"] += 1
|
||||
st["pseudo_period_kpis"].append("%s[%s]" % (kpi.kpi_code, p))
|
||||
logger.warning(" 跳过（伪期间 R3）: %s 期间=%s 非 YYYY-MM" % (kpi.kpi_name, p))
|
||||
continue
|
||||
|
||||
# R2（裁定 2026-09-19）：期间窗口 = 当月往前 6 个自然月（含当月），更早不新生成
|
||||
if str(p) < window_lower:
|
||||
st["out_of_window"] += 1
|
||||
st["out_of_window_kpis"].append("%s[%s]" % (kpi.kpi_code, p))
|
||||
logger.info(" 跳过（期间超出窗口 R2，窗口下限 %s）: %s[%s]" % (
|
||||
window_lower, kpi.kpi_name, p))
|
||||
continue
|
||||
|
||||
# 获取该KPI该期间的最新值
|
||||
latest = db_session.query(KPIValue).filter(
|
||||
KPIValue.kpi_id == kpi.id,
|
||||
@@ -261,7 +304,8 @@ def run_rule_engine_checks(db_session) -> dict:
|
||||
AlertRule, run_forecast_deviation_check, run_customer_concentration_check,
|
||||
)
|
||||
|
||||
stats = {"forecast_deviation": 0, "customer_concentration": 0}
|
||||
stats = {"forecast_deviation": 0, "customer_concentration": 0,
|
||||
"skipped_demo_entities": 0, "excluded_entities": sorted(excluded_entity_ids(db_session))}
|
||||
try:
|
||||
rows = db_session.query(AlertRule.entity_id).filter(
|
||||
AlertRule.enabled == 1,
|
||||
@@ -272,6 +316,11 @@ def run_rule_engine_checks(db_session) -> dict:
|
||||
return stats
|
||||
|
||||
for (eid,) in rows:
|
||||
# R1（裁定 2026-09-19）：demo 演示账套不参与预警遍历
|
||||
if int(eid or 1) in set(stats["excluded_entities"]):
|
||||
stats["skipped_demo_entities"] += 1
|
||||
logger.info(f" 规则引擎跳过（demo 账套 R1）: entity={eid}")
|
||||
continue
|
||||
for key, fn in (("forecast_deviation", run_forecast_deviation_check),
|
||||
("customer_concentration", run_customer_concentration_check)):
|
||||
try:
|
||||
@@ -285,24 +334,42 @@ def run_rule_engine_checks(db_session) -> dict:
|
||||
return stats
|
||||
|
||||
|
||||
def generate_and_push(db_session, period: Optional[str] = None, dry_run: bool = False) -> dict:
|
||||
def _enabled_channel_count(db_session) -> int:
|
||||
"""R4（裁定 2026-09-19）：推送出口计数 —— 生成/推送解耦，空通道只记录不报错。"""
|
||||
from app.models import NotificationChannel
|
||||
try:
|
||||
return int(db_session.query(NotificationChannel).filter(
|
||||
NotificationChannel.enabled == True # noqa: E712 - 与其他调用点一致
|
||||
).count())
|
||||
except Exception as e: # pragma: no cover - 防御分支
|
||||
logger.warning(f"读取通知渠道失败（按无渠道处理）: {e}")
|
||||
return 0
|
||||
|
||||
|
||||
def generate_and_push(db_session, period: Optional[str] = None, dry_run: bool = False,
|
||||
now: Optional[datetime] = None) -> dict:
|
||||
"""生成预警并推送，返回统计
|
||||
|
||||
2026-09-17 财务口径裁定 2a/2b：
|
||||
· **period=None** → 判定期间 = 各 KPI「最近可用期间」（裁定2b，不再硬编码当月）；
|
||||
显式给出 period → 固定该期间（抽查复核用）；
|
||||
· **dry_run=True** → 零写入、零推送：返回将生成的预警清单与口径证据（放行前抽查复核）。
|
||||
|
||||
2026-09-19 裁定 R1–R4：
|
||||
· R1/R2/R3 在 run_alert_check 内落地（demo 账套排除 / 期间窗口 / 规整月期间）；
|
||||
· **R4 生成与推送解耦**：`notification_channels` 为空时仅入库、不报错、不阻断；
|
||||
"""
|
||||
cur_month = datetime.now().strftime("%Y-%m")
|
||||
cur_month = (now or datetime.now()).strftime("%Y-%m")
|
||||
st = {}
|
||||
logger.info("开始预警检查（当月=%s；判定期间=%s）..." % (
|
||||
cur_month, ("固定 %s" % period) if period else "各 KPI 最近可用期间（裁定2b）"))
|
||||
logger.info("开始预警检查（当月=%s；判定期间=%s；窗口下限=%s；排除账套=%s）..." % (
|
||||
cur_month, ("固定 %s" % period) if period else "各 KPI 最近可用期间（裁定2b）",
|
||||
window_lower_period(now), sorted(excluded_entity_ids(db_session))))
|
||||
|
||||
# 0. Bug1修复: 先清理历史green预警（dry-run 不写）
|
||||
cleaned = 0 if dry_run else cleanup_green_alerts(db_session)
|
||||
|
||||
# 1. 生成预警（期间口径 + 单位口径均在此落地）
|
||||
new_count = run_alert_check(db_session, period=period, dry_run=dry_run, stats=st)
|
||||
new_count = run_alert_check(db_session, period=period, dry_run=dry_run, stats=st, now=now)
|
||||
logger.info(f"预警检查完成: {'将新增' if dry_run else '新增'} {new_count} 条")
|
||||
|
||||
# 1a. 覆盖度自检（2026-09-16 项3；2026-09-17 裁定2b 过渡期保留并扩展「期间回落」明细）：
|
||||
@@ -338,19 +405,29 @@ def generate_and_push(db_session, period: Optional[str] = None, dry_run: bool =
|
||||
else run_rule_engine_checks(db_session)
|
||||
|
||||
# 2. 推送（dry-run 零推送）
|
||||
# R4（裁定 2026-09-19）：生成与推送解耦 —— notification_channels 为空时
|
||||
# **仅入库、不报错、不阻断**（推送出口缺失只是"未触达"，不等于"未生成"）。
|
||||
channels_enabled = _enabled_channel_count(db_session)
|
||||
push_skipped_no_channel = channels_enabled == 0
|
||||
pushed = 0
|
||||
if new_count > 0 and not dry_run:
|
||||
try:
|
||||
from app.utils.notifier import push_pending_alerts
|
||||
pushed = push_pending_alerts(db_session)
|
||||
logger.info(f"推送完成: {pushed} 条")
|
||||
except Exception as e:
|
||||
logger.error(f"推送失败: {e}")
|
||||
if push_skipped_no_channel:
|
||||
logger.info("推送出口缺失（notification_channels 启用数=0）→ 仅入库、不推送、不阻断（裁定 R4）")
|
||||
else:
|
||||
try:
|
||||
from app.utils.notifier import push_pending_alerts
|
||||
pushed = push_pending_alerts(db_session)
|
||||
logger.info(f"推送完成: {pushed} 条")
|
||||
except Exception as e:
|
||||
logger.error(f"推送失败（不影响已入库预警，生成/推送解耦 R4）: {e}")
|
||||
|
||||
return {"period": cur_month, "dry_run": dry_run,
|
||||
"period_source": st.get("period_source"), "period_fixed": st.get("period_fixed"),
|
||||
"periods_used": st.get("periods_used", {}),
|
||||
"new_alerts": new_count, "pushed": pushed,
|
||||
# R4：推送出口（生成/推送解耦证据）
|
||||
"channels_enabled": channels_enabled,
|
||||
"push_skipped_no_channel": push_skipped_no_channel,
|
||||
"cleaned_green": cleaned, "rule_engine": rule_stats,
|
||||
"coverage": coverage,
|
||||
# 裁定2a 口径证据
|
||||
@@ -358,7 +435,14 @@ def generate_and_push(db_session, period: Optional[str] = None, dry_run: bool =
|
||||
"dimension_suspect": st.get("dimension_suspect", 0), "suspect_kpis": st.get("suspect_kpis", []),
|
||||
# 期间/取值覆盖明细
|
||||
"no_period": st.get("no_period", 0), "no_value": st.get("no_value", 0),
|
||||
"skipped_existing": st.get("skipped_existing", 0), "planned": st.get("planned", [])}
|
||||
"skipped_existing": st.get("skipped_existing", 0), "planned": st.get("planned", []),
|
||||
# 裁定 R1/R2/R3 口径证据
|
||||
"excluded_demo_entities": st.get("excluded_demo_entities", []),
|
||||
"skipped_demo_kpis": st.get("skipped_demo_kpis", 0),
|
||||
"window_lower_period": st.get("window_lower_period"), "window_months": st.get("window_months"),
|
||||
"out_of_window": st.get("out_of_window", 0), "out_of_window_kpis": st.get("out_of_window_kpis", []),
|
||||
"skipped_pseudo_period": st.get("skipped_pseudo_period", 0),
|
||||
"pseudo_period_kpis": st.get("pseudo_period_kpis", [])}
|
||||
|
||||
|
||||
def coverage_note(result: dict) -> str:
|
||||
@@ -380,6 +464,18 @@ def coverage_note(result: dict) -> str:
|
||||
% (result["dimension_suspect"], (result.get("suspect_kpis") or [])[:3]))
|
||||
if result.get("normalized"):
|
||||
parts.append(" | 口径归一 ×100 %s 项" % result["normalized"])
|
||||
# 裁定 R1/R2/R3/R4（2026-09-19）证据
|
||||
if result.get("skipped_demo_kpis"):
|
||||
parts.append(" | R1 排除 demo 账套 %s（跳过 KPI %s 项）"
|
||||
% (result.get("excluded_demo_entities"), result["skipped_demo_kpis"]))
|
||||
if result.get("out_of_window"):
|
||||
parts.append(" | R2 窗口(下限 %s)外不新生成 %s 项"
|
||||
% (result.get("window_lower_period"), result["out_of_window"]))
|
||||
if result.get("skipped_pseudo_period"):
|
||||
parts.append(" | R3 伪期间跳过 %s 项" % result["skipped_pseudo_period"])
|
||||
if result.get("push_skipped_no_channel"):
|
||||
parts.append(" | R4 推送出口缺失(启用渠道 %s) → 仅入库、不阻断"
|
||||
% result.get("channels_enabled"))
|
||||
return "".join(parts)
|
||||
|
||||
|
||||
|
||||
@@ -38,6 +38,8 @@ import re
|
||||
from sqlalchemy import func
|
||||
from app.database import get_session_local
|
||||
from app.models import KPIValue, KPIDefinition, VoucherDetail, KPIAlert
|
||||
# 裁定 R1（2026-09-19 财务口径）：demo 账套不产生业务预警（派生值仍落库，仅跳过预警同步）
|
||||
from app.utils.alert_entity_scope import is_excluded_entity
|
||||
|
||||
logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
|
||||
logger = logging.getLogger("cma.bep_deriver")
|
||||
@@ -320,7 +322,11 @@ def run_derive(db, entity_id: int, period: str, rebate_rate_pct: float,
|
||||
# 5. 同步预警: 仅对本派生KPI评估 threshold（green=正常不落 pending，yellow/red 落 pending）。
|
||||
# 幂等规则：同一 KPIValue 已有同级别 pending → 保持不动（值未变不重建）；
|
||||
# 其它/旧级别 pending → resolve；最新派生行永远只留一条当前级别。
|
||||
for code, _ in TARGET_KPIS:
|
||||
# R1（裁定 2026-09-19）：demo 账套不产生业务预警 → 整段预警同步跳过（派生值照落库）。
|
||||
target_sync = [] if is_excluded_entity(db, entity_id) else TARGET_KPIS
|
||||
if not target_sync:
|
||||
logger.info("demo 账套（entity=%s）跳过预警同步（R1，裁定 2026-09-19）", entity_id)
|
||||
for code, _ in target_sync:
|
||||
kpi = kpis[code]
|
||||
kpi_value = value_rows.get(kpi.id)
|
||||
if not kpi_value:
|
||||
|
||||
@@ -0,0 +1,363 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""财务预警口径裁定 R1–R4 落地测试（2026-09-19）
|
||||
|
||||
依据：`wecom-finance/reports/CMA_预警口径裁定_20260919.md`（任总 2026-09-18「按建议执行」）
|
||||
· R1 —— `entities.status='demo'` 的账套不参与预警生成/遍历（demo 仅演示展示）；
|
||||
· R2 —— 预警遍历期间 = 当月往前 6 个自然月（含当月），更早期间不再新生成；
|
||||
· R3 —— 仅规整月期间 `YYYY-MM` 参与，`H1/H2/FY` 等伪期间一律不参与；
|
||||
· R4 —— 生成与推送解耦：`notification_channels` 为空时仅入库、不报错、不阻断。
|
||||
|
||||
口径唯一事实源：`app/utils/alert_entity_scope.py`（本套件同时锁该模块的入口函数）。
|
||||
"""
|
||||
from datetime import datetime
|
||||
|
||||
import pytest
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
from tests.conftest import create_test_kpi
|
||||
from app.models import Entity, KPIValue, KPIAlert, NotificationChannel
|
||||
from app.utils.alert_entity_scope import (
|
||||
ALERT_EXCLUDED_ENTITY_STATUSES, ALERT_WINDOW_MONTHS, excluded_entity_ids,
|
||||
is_excluded_entity, is_month_period, kpi_excluded, period_in_window, window_lower_period,
|
||||
)
|
||||
from scripts.alert_generator import generate_and_push, run_alert_check
|
||||
|
||||
#: 固定「当月」= 2026-09 → 窗口 = 2026-04 ~ 2026-09（口径复算不依赖真实时钟）
|
||||
NOW = datetime(2026, 9, 19, 10, 0)
|
||||
|
||||
RED_EXPR = "<58.4" # 0<实测<10 比值形态不触发 dimension_suspect（见裁定2a 降级门）
|
||||
|
||||
|
||||
def _ent(db, eid, status, name=None):
|
||||
db.add(Entity(id=eid, name=name or ("账套%d" % eid), short_name="e%d" % eid, status=status))
|
||||
db.commit()
|
||||
|
||||
|
||||
def _kpi_value(db, kpi, period, value, entity_id=1):
|
||||
db.add(KPIValue(entity_id=entity_id, kpi_id=kpi.id, period=period, actual_value=value))
|
||||
db.commit()
|
||||
|
||||
|
||||
def _demo_and_active(db):
|
||||
_ent(db, 1, "active", "陕西酣客文化传媒")
|
||||
_ent(db, 6, "demo", "演示企业（虚构数据）")
|
||||
|
||||
|
||||
# ───────────────────────── R1：demo 账套排除 ─────────────────────────
|
||||
|
||||
class TestR1DemoEntityExcluded:
|
||||
def test_excluded_ids_only_demo(self, db: Session):
|
||||
_ent(db, 1, "active")
|
||||
_ent(db, 3, "demo")
|
||||
_ent(db, 4, "demo")
|
||||
_ent(db, 5, "demo")
|
||||
_ent(db, 6, "demo")
|
||||
assert excluded_entity_ids(db) == {3, 4, 5, 6}
|
||||
assert is_excluded_entity(db, 6) is True
|
||||
assert is_excluded_entity(db, 1) is False
|
||||
assert is_excluded_entity(db, None) is False, "None → 默认账套 1（不被排除）"
|
||||
assert ALERT_EXCLUDED_ENTITY_STATUSES == ("demo",)
|
||||
|
||||
def test_demo_entity_missing_table_fail_open(self, db: Session, monkeypatch):
|
||||
"""口径读取失败时 fail-open（不阻断预警主流程），返回空集"""
|
||||
import app.utils.alert_entity_scope as scope
|
||||
|
||||
def _boom(*a, **kw):
|
||||
raise RuntimeError("simulated db error")
|
||||
|
||||
monkeypatch.setattr(db, "query", _boom)
|
||||
assert scope.excluded_entity_ids(db) == set()
|
||||
|
||||
def test_demo_kpi_not_traversed_active_kpi_still_is(self, db: Session):
|
||||
"""同一形态两份 KPI：demo 账套(e6) 跳过、active 账套(e1) 正常判定（正对照）"""
|
||||
_demo_and_active(db)
|
||||
k_demo = create_test_kpi(db, kpi_code="DEMO_REVENUE", kpi_name="演示收入",
|
||||
entity_id=6, unit="%", threshold_red=RED_EXPR)
|
||||
k_real = create_test_kpi(db, kpi_code="F_REVENUE", kpi_name="营业收入",
|
||||
entity_id=1, unit="%", threshold_red=RED_EXPR)
|
||||
_kpi_value(db, k_demo, "2026-09", 14.45, entity_id=6)
|
||||
_kpi_value(db, k_real, "2026-09", 14.45, entity_id=1)
|
||||
|
||||
st = {}
|
||||
n = run_alert_check(db, period=None, dry_run=True, stats=st, now=NOW)
|
||||
|
||||
assert n == 1, "只有 active 账套的 KPI 参与判定"
|
||||
assert st["skipped_demo_kpis"] == 1
|
||||
assert st["demo_kpis"] == ["DEMO_REVENUE/e6"]
|
||||
assert st["excluded_demo_entities"] == [6]
|
||||
assert [p["kpi"].split("/")[0] for p in st["planned"]] == ["F_REVENUE"]
|
||||
assert kpi_excluded(db, k_demo) is True and kpi_excluded(db, k_real) is False
|
||||
|
||||
def test_demo_kpi_writes_no_alert(self, db: Session):
|
||||
"""非 dry-run：demo KPI 不落库；active KPI 落库（前后计数差 =1）"""
|
||||
_demo_and_active(db)
|
||||
k_demo = create_test_kpi(db, kpi_code="DEMO_REVENUE", kpi_name="演示收入",
|
||||
entity_id=6, unit="%", threshold_red=RED_EXPR)
|
||||
k_real = create_test_kpi(db, kpi_code="F_REVENUE", kpi_name="营业收入",
|
||||
entity_id=1, unit="%", threshold_red=RED_EXPR)
|
||||
_kpi_value(db, k_demo, "2026-09", 14.45, entity_id=6)
|
||||
_kpi_value(db, k_real, "2026-09", 14.45, entity_id=1)
|
||||
before = db.query(KPIAlert).count()
|
||||
|
||||
st = {}
|
||||
n = run_alert_check(db, dry_run=False, stats=st, now=NOW)
|
||||
db.expire_all()
|
||||
|
||||
rows = db.query(KPIAlert).all()
|
||||
assert n == 1 and len(rows) == before + 1
|
||||
assert [r.entity_id for r in rows] == [1], "demo 账套零预警"
|
||||
|
||||
def test_rule_engine_skips_demo_entity(self, db: Session, monkeypatch):
|
||||
"""规则引擎（按 AlertRule.entity_id 遍历）跳过 demo 账套"""
|
||||
from app.api import alert_rules as ar
|
||||
from scripts import alert_generator as ag
|
||||
|
||||
ar.AlertRule.__table__.create(bind=db.get_bind(), checkfirst=True)
|
||||
_demo_and_active(db)
|
||||
called = []
|
||||
monkeypatch.setattr(ar, "run_forecast_deviation_check",
|
||||
lambda db, entity_id: called.append(("fd", entity_id)) or {"generated": 0})
|
||||
monkeypatch.setattr(ar, "run_customer_concentration_check",
|
||||
lambda db, entity_id: called.append(("cc", entity_id)) or {"generated": 0})
|
||||
for eid in (1, 6):
|
||||
db.add(ar.AlertRule(entity_id=eid, kpi_id=1, rule_type="forecast_deviation", enabled=1))
|
||||
db.commit()
|
||||
|
||||
stats = ag.run_rule_engine_checks(db)
|
||||
|
||||
assert stats["excluded_entities"] == [6]
|
||||
assert stats["skipped_demo_entities"] == 1
|
||||
assert sorted(e for _, e in called) == [1, 1], "demo 账套一条规则都不跑"
|
||||
|
||||
def test_alert_rules_endpoints_skip_demo(self, db: Session):
|
||||
"""生成端点对 demo 账套直接返回 skipped（不起规则遍历）"""
|
||||
from app.api.alert_rules import (
|
||||
AlertRule, run_all_alert_checks, run_forecast_alert_check,
|
||||
run_forecast_deviation_check, run_customer_concentration_check,
|
||||
)
|
||||
|
||||
AlertRule.__table__.create(bind=db.get_bind(), checkfirst=True)
|
||||
_demo_and_active(db)
|
||||
for fn in (run_all_alert_checks, run_forecast_alert_check,
|
||||
run_forecast_deviation_check, run_customer_concentration_check):
|
||||
r = fn(db=db, entity_id=6)
|
||||
assert r.get("skipped") is True, fn.__name__
|
||||
assert r.get("reason") == "R1_demo_entity_excluded"
|
||||
assert r.get("generated") == 0
|
||||
|
||||
def test_cash_alerts_skip_demo(self, db: Session):
|
||||
from app.utils.cash_forecast_engine import check_cash_alerts
|
||||
|
||||
_demo_and_active(db)
|
||||
r = check_cash_alerts(db, entity_id=6)
|
||||
assert r["skipped"] is True and r["reason"] == "R1_demo_entity_excluded"
|
||||
assert db.query(KPIAlert).count() == 0
|
||||
|
||||
def test_deviation_check_excludes_demo_kpi(self, db: Session, monkeypatch):
|
||||
"""差异预警遍历（daily_sync 第4步）同样排除 demo 账套 KPI"""
|
||||
import app.utils.deviation_engine as de
|
||||
|
||||
_demo_and_active(db)
|
||||
create_test_kpi(db, kpi_code="DEMO_REVENUE", kpi_name="演示收入",
|
||||
entity_id=6, unit="%", threshold_red=RED_EXPR)
|
||||
create_test_kpi(db, kpi_code="F_REVENUE", kpi_name="营业收入",
|
||||
entity_id=1, unit="%", threshold_red=RED_EXPR)
|
||||
# 让所有 KPI 都「差异触发」，只观察遍历范围（不依赖预算数据形态）
|
||||
monkeypatch.setattr(de, "build_deviation_alert",
|
||||
lambda db_s, kpi, period, *a, **kw: {
|
||||
"triggered": True, "kpi_alert_level": "red", "alert_type": "budget",
|
||||
"suggestion": None,
|
||||
"deviation": {"actual_value": 14.45, "budget_value": 100.0,
|
||||
"deviation_rate": -85.6}})
|
||||
monkeypatch.setattr(de, "check_trend_anomaly", lambda *a, **kw: {"anomaly": False})
|
||||
|
||||
n = de.run_deviation_check(db, period="2026-08")
|
||||
db.expire_all()
|
||||
|
||||
rows = db.query(KPIAlert).all()
|
||||
assert n == 1 and [r.entity_id for r in rows] == [1]
|
||||
|
||||
|
||||
# ───────────────────────── R2：期间窗口（6 个自然月） ─────────────────────────
|
||||
|
||||
class TestR2Window:
|
||||
def test_window_lower_period_math(self):
|
||||
assert ALERT_WINDOW_MONTHS == 6
|
||||
assert window_lower_period(NOW) == "2026-04" # 2026-09 往前 5 个月
|
||||
assert window_lower_period(datetime(2026, 9, 1)) == "2026-04"
|
||||
assert window_lower_period(datetime(2026, 6, 30)) == "2026-01"
|
||||
assert window_lower_period(datetime(2026, 1, 5)) == "2025-08" # 跨年
|
||||
assert window_lower_period(datetime(2026, 3, 31)) == "2025-10"
|
||||
|
||||
def test_period_in_window(self):
|
||||
assert period_in_window("2026-04", NOW) is True # 窗口下限（含）
|
||||
assert period_in_window("2026-09", NOW) is True # 当月（含）
|
||||
assert period_in_window("2026-03", NOW) is False # 窗口外
|
||||
assert period_in_window("2026-01", NOW) is False
|
||||
assert period_in_window("2026-H1", NOW) is False # R3
|
||||
assert period_in_window(None, NOW) is False
|
||||
|
||||
def test_out_of_window_kpi_not_generated(self, db: Session):
|
||||
"""博海形态：最新可用期间 2026-01/03（窗口外）→ 不再新生成"""
|
||||
_demo_and_active(db)
|
||||
for code, period in (("BH_SALES_1", "2026-03"), ("BH_SALES_5", "2026-01")):
|
||||
k = create_test_kpi(db, kpi_code=code, kpi_name=code, entity_id=2,
|
||||
unit="%", threshold_red=RED_EXPR)
|
||||
_kpi_value(db, k, period, 63070.3, entity_id=2)
|
||||
|
||||
st = {}
|
||||
n = run_alert_check(db, period=None, dry_run=True, stats=st, now=NOW)
|
||||
|
||||
assert n == 0
|
||||
assert st["out_of_window"] == 2
|
||||
assert sorted(st["out_of_window_kpis"]) == ["BH_SALES_1[2026-03]", "BH_SALES_5[2026-01]"]
|
||||
assert st["window_lower_period"] == "2026-04"
|
||||
|
||||
def test_window_boundary_generates_inside_only(self, db: Session):
|
||||
"""边界：窗口下限 2026-04 生成；2026-03 不生成"""
|
||||
_demo_and_active(db)
|
||||
k_in = create_test_kpi(db, kpi_code="F_REVENUE", kpi_name="营业收入", entity_id=1,
|
||||
unit="%", threshold_red=RED_EXPR)
|
||||
k_out = create_test_kpi(db, kpi_code="F_COST_RATIO", kpi_name="费用率", entity_id=1,
|
||||
unit="%", threshold_red=RED_EXPR)
|
||||
_kpi_value(db, k_in, "2026-04", 14.45)
|
||||
_kpi_value(db, k_out, "2026-03", 14.45)
|
||||
|
||||
st = {}
|
||||
n = run_alert_check(db, period=None, dry_run=True, stats=st, now=NOW)
|
||||
|
||||
assert n == 1
|
||||
assert st["periods_used"] == {"2026-04": 1}
|
||||
assert st["out_of_window"] == 1
|
||||
assert st["planned"][0]["kpi"].startswith("F_REVENUE")
|
||||
|
||||
def test_no_new_alert_written_out_of_window(self, db: Session):
|
||||
"""非 dry-run 回查：窗口外 KPI 不落库（前后计数一致）"""
|
||||
_demo_and_active(db)
|
||||
k = create_test_kpi(db, kpi_code="BH_SALES_1", kpi_name="销售-陈艳", entity_id=2,
|
||||
unit="%", threshold_red=RED_EXPR)
|
||||
_kpi_value(db, k, "2026-01", 63070.3, entity_id=2)
|
||||
before = db.query(KPIAlert).count()
|
||||
|
||||
run_alert_check(db, dry_run=False, now=NOW)
|
||||
db.expire_all()
|
||||
|
||||
assert db.query(KPIAlert).count() == before == 0
|
||||
|
||||
|
||||
# ───────────────────────── R3：伪期间不参与 ─────────────────────────
|
||||
|
||||
class TestR3PseudoPeriod:
|
||||
def test_is_month_period(self):
|
||||
assert is_month_period("2026-08") is True and is_month_period("2025-12") is True
|
||||
for bad in ("2026-H1", "2026-H2", "2025-FY", "2025", "2026-13", None, ""):
|
||||
assert is_month_period(bad) is False, bad
|
||||
|
||||
def test_explicit_pseudo_period_skipped(self, db: Session):
|
||||
"""显式传入 2026-H1 → 伪期间跳过（不放行、不落库）"""
|
||||
_demo_and_active(db)
|
||||
k = create_test_kpi(db, kpi_code="F_GROSS_MARGIN", kpi_name="毛利率",
|
||||
entity_id=1, unit="%", threshold_red="<15")
|
||||
_kpi_value(db, k, "2026-08", 5.0)
|
||||
before = db.query(KPIAlert).count()
|
||||
|
||||
st = {}
|
||||
n = run_alert_check(db, period="2026-H1", dry_run=False, stats=st, now=NOW)
|
||||
db.expire_all()
|
||||
|
||||
assert n == 0 and db.query(KPIAlert).count() == before
|
||||
assert st["skipped_pseudo_period"] == 1
|
||||
assert st["pseudo_period_kpis"] == ["F_GROSS_MARGIN[2026-H1]"]
|
||||
|
||||
def test_only_pseudo_period_means_no_period(self, db: Session):
|
||||
"""KPI 只有 2026-H1 数据 → 无可用期间（no_period，不静默）"""
|
||||
_demo_and_active(db)
|
||||
k = create_test_kpi(db, kpi_code="F_GROSS_MARGIN", kpi_name="毛利率",
|
||||
entity_id=1, unit="%", threshold_red="<15")
|
||||
_kpi_value(db, k, "2026-H1", 5.0)
|
||||
|
||||
st = {}
|
||||
n = run_alert_check(db, period=None, dry_run=True, stats=st, now=NOW)
|
||||
|
||||
assert n == 0 and st["no_period"] == 1 and st["skipped_pseudo_period"] == 0
|
||||
|
||||
|
||||
# ───────────────────────── R4：生成与推送解耦 ─────────────────────────
|
||||
|
||||
class TestR4PushDecoupled:
|
||||
def _triggering_kpi(self, db):
|
||||
_demo_and_active(db)
|
||||
k = create_test_kpi(db, kpi_code="F_REVENUE", kpi_name="营业收入", entity_id=1,
|
||||
unit="%", threshold_red=RED_EXPR)
|
||||
_kpi_value(db, k, "2026-09", 14.45)
|
||||
return k
|
||||
|
||||
def test_empty_channels_only_store_no_error(self, db: Session):
|
||||
"""notification_channels=0 → 仅入库、不报错、不阻断（生成结果照常返回）"""
|
||||
self._triggering_kpi(db)
|
||||
assert db.query(NotificationChannel).count() == 0
|
||||
|
||||
r = generate_and_push(db, dry_run=False, now=NOW)
|
||||
db.expire_all()
|
||||
|
||||
assert r["new_alerts"] == 1, "预警照常生成入库"
|
||||
assert r["channels_enabled"] == 0 and r["push_skipped_no_channel"] is True
|
||||
assert r["pushed"] == 0
|
||||
assert db.query(KPIAlert).count() == 1
|
||||
assert db.query(KPIAlert).first().status == "pending"
|
||||
|
||||
def test_push_failure_does_not_block_generation(self, db: Session, monkeypatch):
|
||||
"""有渠道但推送抛异常 → 生成结果不受影响（try/except 解耦）"""
|
||||
import app.utils.notifier as notifier
|
||||
|
||||
self._triggering_kpi(db)
|
||||
db.add(NotificationChannel(name="企微群", channel_type="wecom",
|
||||
config={"webhook_url": "https://example.invalid/hook"},
|
||||
enabled=True))
|
||||
db.commit()
|
||||
|
||||
def _boom(*a, **kw):
|
||||
raise RuntimeError("simulated push failure")
|
||||
|
||||
monkeypatch.setattr(notifier, "push_pending_alerts", _boom)
|
||||
|
||||
r = generate_and_push(db, dry_run=False, now=NOW)
|
||||
assert r["new_alerts"] == 1 and r["pushed"] == 0
|
||||
assert r["channels_enabled"] == 1 and r["push_skipped_no_channel"] is False
|
||||
|
||||
def test_push_called_when_channel_present(self, db: Session, monkeypatch):
|
||||
import app.utils.notifier as notifier
|
||||
|
||||
self._triggering_kpi(db)
|
||||
db.add(NotificationChannel(name="企微群", channel_type="wecom",
|
||||
config={"webhook_url": "https://example.invalid/hook"},
|
||||
enabled=True))
|
||||
db.commit()
|
||||
monkeypatch.setattr(notifier, "push_pending_alerts", lambda db_: 1)
|
||||
|
||||
r = generate_and_push(db, dry_run=False, now=NOW)
|
||||
assert r["new_alerts"] == 1 and r["pushed"] == 1 and r["channels_enabled"] == 1
|
||||
|
||||
def test_dry_run_zero_write_and_zero_push(self, db: Session, monkeypatch):
|
||||
"""dry-run：零写入、零推送，且返回 R1/R2/R3 口径证据"""
|
||||
import app.utils.notifier as notifier
|
||||
|
||||
self._triggering_kpi(db)
|
||||
k_old = create_test_kpi(db, kpi_code="BH_SALES_1", kpi_name="销售-陈艳", entity_id=2,
|
||||
unit="%", threshold_red=RED_EXPR)
|
||||
_kpi_value(db, k_old, "2026-01", 63070.3, entity_id=2)
|
||||
create_test_kpi(db, kpi_code="DEMO_REVENUE", kpi_name="演示收入", entity_id=6,
|
||||
unit="%", threshold_red=RED_EXPR)
|
||||
called = []
|
||||
monkeypatch.setattr(notifier, "push_pending_alerts", lambda db_: called.append(1) or 9)
|
||||
|
||||
before = db.query(KPIAlert).count()
|
||||
r = generate_and_push(db, dry_run=True, now=NOW)
|
||||
db.expire_all()
|
||||
|
||||
assert db.query(KPIAlert).count() == before == 0, "dry-run 零写入"
|
||||
assert called == [], "dry-run 零推送"
|
||||
assert r["new_alerts"] == 1 and r["pushed"] == 0
|
||||
assert r["skipped_demo_kpis"] == 1 and r["out_of_window"] == 1
|
||||
assert r["window_lower_period"] == "2026-04" and r["excluded_demo_entities"] == [6]
|
||||
assert r["push_skipped_no_channel"] is True
|
||||
Reference in New Issue
Block a user