依据:wecom-finance/reports/CMA_口径裁定_20260917.md(任总 2026-09-17 23:14「按建议执行」) 裁定1(现金流「投资活动净额=0」参与判定) - classify_enterprise():0 为合法输入;投资恒为 0 → 经营(±)×筹资(±) 二维映射出 2 个 候选类型(candidate_type_nos/candidates),不再整体判「未判定」;投资栏 investing_note 标注「本期无投资活动」;经营/筹资亦为 0 → 回退「未判定(无投资活动)」,不报错不静默 - /analysis 增 classification_dimension / investing_note / nets.investing.note;前端出 二维横幅 + 候选行高亮 + 投资栏「本期无投资活动」(不给单一类型名) - import_cashflow_statements.py:打印层修 2D(type_no=None)TypeError 崩溃;NA 措辞改为 「按 0 参与判定」(机读短语 NA_PHRASE_TMPL/parse_na_activities 未动) 裁定2a(比率类单位统一「百分比(%)」口径,先做) - 新增 app/utils/caliber_units.py:逐 KPI 对照表 RATIO_CALIBER_TABLE(唯一事实源)+ 判定侧 唯一入口 resolve_caliber();3 项需归一 ×100(流动/速动/毛利率),12 项取数已百分数不归一; 表外且命中「疑似错配」窄形态(阈值子句量级≥100 且 0<|实测|<10 且单位属比率类)→ dimension_suspect:不落预警、不推送(唯一规则,防 586/587 假红灯复发) - alert_generator:判定前归一,文案写「口径归一 ×100(原值 1.29 → 129%)」留审计线索 - 新增 scripts/kpi_unit_crosscheck.py(只读对照表产出器) 裁定2b(期间由「当月硬编码」→「最近可用期间」,后做) - resolve_latest_period():取该 KPI 自己的最新 YYYY-MM(禁全局 MAX,防演示账套劫持); 伪期间(2026-H1/H2、2025-FY)在 Python 侧过滤(保「单测=生产」语义) - 过渡期覆盖度自检扩展:记录回落后的期间分布 + 当月 0 条归因提示 - --dry-run(零写入零推送)作放行前抽查证据;generate_and_push/run_alert_check 支持 dry_run 测试:backend/tests/test_caliber_rulings_20260917.py 17 项;全量 1158 passed/1 xfailed
This commit is contained in:
@@ -6,8 +6,10 @@
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import sys
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import os
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import re
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import json
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import logging
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from typing import Optional
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from datetime import datetime, timedelta
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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@@ -15,9 +17,36 @@ sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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from app.database import get_session_local
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from app.models import KPIDefinition, KPIValue, KPIAlert, ActionPlan
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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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logger = logging.getLogger("cma.alert_gen")
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#: 月期间正则 —— 只认 YYYY-MM(排除 2026-H1/H2、2025-FY 等伪期间;裁定2b)
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PERIOD_REGEX = r"^[0-9]{4}-[0-9]{2}$"
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_PERIOD_RE = re.compile(PERIOD_REGEX)
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def resolve_latest_period(db_session, kpi_id=None):
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"""「最近可用期间」(裁定2b):kpi_values 内最新 YYYY-MM,排除 H1/H2 伪期间。
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给定 kpi_id → 返回**该 KPI 自己**的最近可用期间:期间口径不硬编码当月,
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也不被别人(他账套/演示账套)更新的新期间带偏——实证:全局 MAX(period)=2026-09
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但那是演示账套 e6 的 8 条数据,酣客(e1) 的最新可用期间是 2026-08。
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实现说明:伪期间过滤在 **Python 侧**做(`SELECT DISTINCT period` 只有十几行),
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不依赖 MySQL 的 `REGEXP` —— SQLite 测试库不注册 REGEXP,用 SQL 侧正则会让
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单测与生产走两套语义。
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"""
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q = db_session.query(KPIValue.period).filter(KPIValue.actual_value.isnot(None))
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if kpi_id is not None:
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q = q.filter(KPIValue.kpi_id == kpi_id)
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for (p,) in q.distinct().order_by(KPIValue.period.desc()).all():
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if _PERIOD_RE.fullmatch(str(p or "")):
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return p
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return None
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def _parse_threshold(expr: str) -> tuple:
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"""[兼容保留] 统一委托 app.utils.threshold_parser.parse_threshold"""
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@@ -56,10 +85,23 @@ def _check_threshold(actual: float, threshold_expr: str, level: str) -> tuple:
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return True, msg
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def run_alert_check(db_session, period: str = None) -> int:
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"""检查所有KPI的实际值是否触发预警,返回新生成的预警数"""
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if period is None:
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period = datetime.now().strftime("%Y-%m")
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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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"""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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· **期间(2b)**:period=None → 每个 KPI 回落「最近可用期间」(自己的最新 YYYY-MM,
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排除 H1/H2 伪期间),不再硬编码当月(当月无值 → 永久 0 新预警);
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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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"""
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st = stats if stats is not None else {}
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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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st.setdefault(k, v)
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kpis = db_session.query(KPIDefinition).filter(
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KPIDefinition.status == "active"
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@@ -76,16 +118,39 @@ def run_alert_check(db_session, period: str = None) -> int:
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if not any(thr.values()):
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continue
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# 获取该KPI当前期间的最新值
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# 期间口径(裁定2b):显式指定 → 固定期间;缺省 → 该 KPI 的最近可用期间
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p = period or resolve_latest_period(db_session, kpi.id)
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if not p:
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st["no_period"] += 1
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logger.warning(f" 跳过(无可用期间): {kpi.kpi_name} 无任何 YYYY-MM 实测值")
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continue
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# 获取该KPI该期间的最新值
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latest = db_session.query(KPIValue).filter(
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KPIValue.kpi_id == kpi.id,
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KPIValue.period == period,
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KPIValue.period == p,
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).order_by(KPIValue.calculated_at.desc()).first()
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if not latest or latest.actual_value is None:
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st["no_value"] += 1
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continue
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actual = latest.actual_value
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# 单位口径(裁定2a):取数归一 + 疑似错配降级门
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cal = resolve_caliber(latest.actual_value, kpi)
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if cal["status"] == "dimension_suspect":
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st["dimension_suspect"] += 1
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st["suspect_kpis"].append("%s[%s] actual=%s unit=%s" % (
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kpi.kpi_code, p, latest.actual_value, kpi.unit))
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logger.warning(" [降级待核·疑似单位错配→不落预警不推送] %s[%s] 实测=%s 单位=%s ← %s" % (
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kpi.kpi_name, p, latest.actual_value, kpi.unit, cal["reason"]))
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continue
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actual = cal["value"]
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if cal["status"] == "normalized":
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st["normalized"] += 1
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st["normalized_kpis"].append("%s[%s] %s → %s(×%s)" % (
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kpi.kpi_code, p, latest.actual_value, actual, cal["factor"]))
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st["periods_used"][p] = st["periods_used"].get(p, 0) + 1
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# 判定顺序:红灯优先 → 绿灯 → 黄灯(最严重者优先,消除宽黄灯遮蔽红灯)
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# 2026-09-11 修复「黄灯遮蔽红灯」:原顺序 绿→黄→红命中即止,宽黄灯(如 Y='>76')
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@@ -101,6 +166,8 @@ def run_alert_check(db_session, period: str = None) -> int:
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if level == "green":
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# 正常状态:不生成待处理预警(如有旧的red/yellow预警自动解除)
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break
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if cal.get("note"):
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msg = "%s|%s" % (msg, cal["note"])
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# 检查是否已有该期间该KPI同级别的预警
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existing = db_session.query(KPIAlert).filter(
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KPIAlert.kpi_id == kpi.id,
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@@ -110,6 +177,16 @@ def run_alert_check(db_session, period: str = None) -> int:
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if existing:
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# 已有预警,跳过
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st["skipped_existing"] += 1
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break
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st["planned"].append({
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"kpi": "%s/%s" % (kpi.kpi_code, kpi.kpi_name), "period": p,
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"actual": actual, "raw_actual": latest.actual_value, "factor": cal["factor"],
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"level": level, "message": msg,
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})
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if dry_run:
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new_count += 1
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break
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# 创建新预警
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@@ -118,7 +195,7 @@ def run_alert_check(db_session, period: str = None) -> int:
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kpi_id=kpi.id,
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kpi_value_id=latest.id,
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alert_level=level,
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alert_message=f"{kpi.kpi_name}[{period}] {msg}",
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alert_message=f"{kpi.kpi_name}[{p}] {msg}",
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status="pending",
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)
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db_session.add(alert)
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@@ -160,12 +237,15 @@ def run_alert_check(db_session, period: str = None) -> int:
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KPIAlert.alert_level == "red",
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KPIAlert.status.in_(["pending", "processing"]),
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).first()
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if existing_red:
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if existing_red and not dry_run:
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existing_red.status = "resolved"
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existing_red.resolution = "自动解除: 当前值不再触发红色阈值"
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existing_red.resolved_at = datetime.now()
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logger.info(f" 自动解除预警 [red] {kpi.kpi_name}")
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if dry_run:
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db_session.rollback() # 抽查复核/放行前证据:确保零写入
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return new_count
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db_session.commit()
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return new_count
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@@ -205,22 +285,30 @@ def run_rule_engine_checks(db_session) -> dict:
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return stats
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def generate_and_push(db_session) -> dict:
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"""生成预警并推送,返回统计"""
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period = datetime.now().strftime("%Y-%m")
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def generate_and_push(db_session, period: Optional[str] = None, dry_run: bool = False) -> dict:
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"""生成预警并推送,返回统计
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# 0. Bug1修复: 先清理历史green预警
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cleaned = cleanup_green_alerts(db_session)
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2026-09-17 财务口径裁定 2a/2b:
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· **period=None** → 判定期间 = 各 KPI「最近可用期间」(裁定2b,不再硬编码当月);
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显式给出 period → 固定该期间(抽查复核用);
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· **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)。
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"""
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cur_month = datetime.now().strftime("%Y-%m")
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st = {}
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logger.info("开始预警检查(当月=%s;判定期间=%s)..." % (
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cur_month, ("固定 %s" % period) if period else "各 KPI 最近可用期间(裁定2b)"))
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# 1. 生成预警
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logger.info(f"开始预警检查 ({period})...")
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new_count = run_alert_check(db_session, period)
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logger.info(f"预警检查完成: 新增 {new_count} 条")
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# 0. Bug1修复: 先清理历史green预警(dry-run 不写)
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cleaned = 0 if dry_run else cleanup_green_alerts(db_session)
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# 1a. 覆盖度自检(2026-09-16 新增,任务 finance-20260916-cma-health-gaps-3items · 项3):
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# run_alert_check 的期间口径 = 当月(period=current month),若当月尚无任何 KPIValue,
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# 则「0 条新预警」并不代表"确无阈值触发",而是"本次检查未覆盖任何数据"——
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# 该区别原实现不可见(日志与汇总行都只说 0 条),导致连续多日 0 新增无法归因。
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# 1. 生成预警(期间口径 + 单位口径均在此落地)
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new_count = run_alert_check(db_session, period=period, dry_run=dry_run, stats=st)
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logger.info(f"预警检查完成: {'将新增' if dry_run else '新增'} {new_count} 条")
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# 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):
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# 若**当月**无任何 KPIValue,「0 条新预警」并不代表"确无阈值触发",而是"当月无数据";
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# 裁定2b 起改为按各 KPI 最近可用期间判定,故此处显式记录回落后的期间分布。
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coverage = {"current_month": cur_month, "periods_used": st.get("periods_used", {})}
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try:
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kpis_with_values = 0
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active_kpis = db_session.query(KPIDefinition).filter(KPIDefinition.status == "active").all()
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@@ -228,33 +316,30 @@ def generate_and_push(db_session) -> dict:
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if not any((k.threshold_red, k.threshold_yellow, k.threshold_green)):
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continue
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hit = db_session.query(KPIValue).filter(
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KPIValue.kpi_id == k.id, KPIValue.period == period,
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KPIValue.kpi_id == k.id, KPIValue.period == cur_month,
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KPIValue.actual_value.isnot(None),
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).first()
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if hit:
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kpis_with_values += 1
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coverage = {"period": period, "kpis_with_threshold_and_value": kpis_with_values}
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coverage["kpis_with_threshold_and_value"] = kpis_with_values
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coverage["period"] = cur_month
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if kpis_with_values == 0:
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latest_period = db_session.query(KPIValue.period).filter(
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KPIValue.actual_value.isnot(None),
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KPIValue.period.op("REGEXP")("^[0-9]{4}-[0-9]{2}$"), # 只取 YYYY-MM 月期间(排除 2026-H1/H2 伪期间)
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).order_by(KPIValue.period.desc()).first()
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coverage["latest_period_in_db"] = resolve_latest_period(db_session)
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logger.warning(
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f"覆盖度告警: 当月({period})无任何 KPI 实际值 → 本次预警检查未覆盖任何 KPI,"
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f"「0 条新预警」= 无数据可判,非「确无阈值触发」。库内最新期间="
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f"{latest_period[0] if latest_period else 'N/A'}"
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)
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coverage["latest_period_in_db"] = latest_period[0] if latest_period else None
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"覆盖度告警: 当月(%s)无任何 KPI 实际值 → 本次按「最近可用期间」判定(期间分布 %s);"
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"「0 条新预警」= 当月无数据可判,非「确无阈值触发」。库内最新月期间=%s" % (
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cur_month, st.get("periods_used"), coverage["latest_period_in_db"]))
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except Exception as e:
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logger.error(f"覆盖度自检失败: {e}")
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coverage = {"error": str(e)}
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# 1b. 规则引擎检查(预测偏差 / 客户集中度,P2 2026-09-10)
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rule_stats = run_rule_engine_checks(db_session)
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# 1b. 规则引擎检查(预测偏差 / 客户集中度,P2 2026-09-10;dry-run 不写)
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rule_stats = {"forecast_deviation": 0, "customer_concentration": 0} if dry_run \
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else run_rule_engine_checks(db_session)
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# 2. 推送
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# 2. 推送(dry-run 零推送)
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pushed = 0
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if new_count > 0:
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if new_count > 0 and not dry_run:
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try:
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from app.utils.notifier import push_pending_alerts
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pushed = push_pending_alerts(db_session)
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@@ -262,24 +347,51 @@ def generate_and_push(db_session) -> dict:
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except Exception as e:
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logger.error(f"推送失败: {e}")
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return {"period": period, "new_alerts": new_count, "pushed": pushed,
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return {"period": cur_month, "dry_run": dry_run,
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"period_source": st.get("period_source"), "period_fixed": st.get("period_fixed"),
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"periods_used": st.get("periods_used", {}),
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"new_alerts": new_count, "pushed": pushed,
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"cleaned_green": cleaned, "rule_engine": rule_stats,
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"coverage": coverage}
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"coverage": coverage,
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# 裁定2a 口径证据
|
||||
"normalized": st.get("normalized", 0), "normalized_kpis": st.get("normalized_kpis", []),
|
||||
"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", [])}
|
||||
|
||||
|
||||
def coverage_note(result: dict) -> str:
|
||||
"""汇总行追加提示:当月无 KPI 值时显式说明「0 条 = 无数据可判」而非「确无触发」
|
||||
"""汇总行追加提示:期间口径回落后显式说明「0 条 = 无数据可判」而非「确无触发」
|
||||
|
||||
2026-09-16 新增(项3)。独立成函数便于回查(无需触发真实写路径即可断言文案)。
|
||||
2026-09-16 新增(项3);2026-09-17 裁定2b 起追加「期间回落」明细。
|
||||
"""
|
||||
cov = result.get("coverage") or {}
|
||||
parts = []
|
||||
used = result.get("periods_used") or cov.get("periods_used") or {}
|
||||
if used and cov.get("current_month") not in used:
|
||||
parts.append(" | 期间回落(裁定2b): 当月(%s)无 KPI 值 → 按各 KPI 最近可用期间判定 %s"
|
||||
% (cov.get("current_month"), used))
|
||||
if cov.get("kpis_with_threshold_and_value") == 0:
|
||||
return (f" | ⚠️ 当月({result['period']})无KPI值: 本次检查未覆盖任何KPI"
|
||||
f"(库内最新月期间 {cov.get('latest_period_in_db')})→ 0 条不等于确无触发")
|
||||
return ""
|
||||
parts.append(" | ⚠️ 当月(%s)无KPI值: 本次检查按最近可用期间判定(库内最新月期间 %s)→ 0 条不等于确无触发"
|
||||
% (cov.get("current_month"), cov.get("latest_period_in_db")))
|
||||
if result.get("dimension_suspect"):
|
||||
parts.append(" | ⛔ 降级待核(疑似单位错配,不推送) %s 项: %s"
|
||||
% (result["dimension_suspect"], (result.get("suspect_kpis") or [])[:3]))
|
||||
if result.get("normalized"):
|
||||
parts.append(" | 口径归一 ×100 %s 项" % result["normalized"])
|
||||
return "".join(parts)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import argparse
|
||||
|
||||
ap = argparse.ArgumentParser(description="预警生成与推送(2026-09-17 口径裁定 2a/2b)")
|
||||
ap.add_argument("--dry-run", action="store_true", help="只计算不写库不推送(抽查复核/放行前证据)")
|
||||
ap.add_argument("--period", default=None, help="固定判定期间 YYYY-MM(缺省=各 KPI 最近可用期间,裁定2b)")
|
||||
ap.add_argument("--json", action="store_true", help="JSON 输出完整证据(含将生成的预警清单)")
|
||||
args = ap.parse_args()
|
||||
|
||||
logging.basicConfig(
|
||||
level=logging.INFO,
|
||||
format="%(asctime)s [%(levelname)s] %(name)s: %(message)s",
|
||||
@@ -287,8 +399,13 @@ if __name__ == "__main__":
|
||||
|
||||
db = get_session_local()()
|
||||
try:
|
||||
result = generate_and_push(db)
|
||||
print(f"预警检查: {result['new_alerts']}条新预警 / {result['pushed']}条已推送"
|
||||
f" / 规则引擎{result['rule_engine']}{coverage_note(result)}")
|
||||
result = generate_and_push(db, period=args.period, dry_run=args.dry_run)
|
||||
if args.json:
|
||||
print(json.dumps(result, ensure_ascii=False, indent=1, default=str))
|
||||
else:
|
||||
print(f"预警检查{'(dry-run 零写入零推送)' if args.dry_run else ''}: "
|
||||
f"{result['new_alerts']}条新预警 / {result['pushed']}条已推送"
|
||||
f" / 规则引擎{result['rule_engine']}{coverage_note(result)}")
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
|
||||
Reference in New Issue
Block a user