feat(cma): 口径裁定 2026-09-17 落地(现金流投资=0 二维判定 / 预警单位+期间口径)
ci/woodpecker/push/main Pipeline failed

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:
Hermes CI Fix
2026-09-18 00:34:04 +08:00
parent e567d1b94f
commit 3bb55189b1
8 changed files with 923 additions and 79 deletions
+164 -47
View File
@@ -6,8 +6,10 @@
import sys
import os
import re
import json
import logging
from typing import Optional
from datetime import datetime, timedelta
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
@@ -15,9 +17,36 @@ sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from app.database import get_session_local
from app.models import KPIDefinition, KPIValue, KPIAlert, ActionPlan
from app.utils.threshold_parser import eval_threshold, LEVEL_PRIORITY
# 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),
# 未核对/疑似单位错配的项降级待核(不落预警、不推送)
from app.utils.caliber_units import resolve_caliber
logger = logging.getLogger("cma.alert_gen")
#: 月期间正则 —— 只认 YYYY-MM(排除 2026-H1/H2、2025-FY 等伪期间;裁定2b)
PERIOD_REGEX = r"^[0-9]{4}-[0-9]{2}$"
_PERIOD_RE = re.compile(PERIOD_REGEX)
def resolve_latest_period(db_session, kpi_id=None):
"""「最近可用期间」(裁定2b):kpi_values 内最新 YYYY-MM,排除 H1/H2 伪期间。
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,
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
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。
实现说明:伪期间过滤在 **Python 侧**做(`SELECT DISTINCT period` 只有十几行),
不依赖 MySQL 的 `REGEXP` —— SQLite 测试库不注册 REGEXP,用 SQL 侧正则会让
单测与生产走两套语义。
"""
q = db_session.query(KPIValue.period).filter(KPIValue.actual_value.isnot(None))
if kpi_id is not None:
q = q.filter(KPIValue.kpi_id == kpi_id)
for (p,) in q.distinct().order_by(KPIValue.period.desc()).all():
if _PERIOD_RE.fullmatch(str(p or "")):
return p
return None
def _parse_threshold(expr: str) -> tuple:
"""[兼容保留] 统一委托 app.utils.threshold_parser.parse_threshold"""
@@ -56,10 +85,23 @@ def _check_threshold(actual: float, threshold_expr: str, level: str) -> tuple:
return True, msg
def run_alert_check(db_session, period: str = None) -> int:
"""检查所有KPI的实际值是否触发预警,返回新生成的预警数"""
if period is None:
period = datetime.now().strftime("%Y-%m")
def run_alert_check(db_session, period: Optional[str] = None, dry_run: bool = False,
stats: Optional[dict] = None) -> int:
"""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
2026-09-17 财务口径裁定 2a/2b:
· **期间(2b)**:period=None → 每个 KPI 回落「最近可用期间」(自己的最新 YYYY-MM,
排除 H1/H2 伪期间),不再硬编码当月(当月无值 → 永久 0 新预警);
· **单位(2a)**:判定前经 resolve_caliber() 归一到「百分比(%)」口径(取数×100,
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;
· dry_run=True → 只计算不写库(抽查复核与放行前证据用)。
"""
st = stats if stats is not None else {}
for k, v in (("period_source", "fixed" if period else "per_kpi_latest"), ("period_fixed", period),
("periods_used", {}), ("normalized", 0), ("normalized_kpis", []),
("dimension_suspect", 0), ("suspect_kpis", []), ("no_period", 0),
("no_value", 0), ("planned", []), ("skipped_existing", 0)):
st.setdefault(k, v)
kpis = db_session.query(KPIDefinition).filter(
KPIDefinition.status == "active"
@@ -76,16 +118,39 @@ def run_alert_check(db_session, period: str = None) -> int:
if not any(thr.values()):
continue
# 获取该KPI当前期间的最新值
# 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
p = period or resolve_latest_period(db_session, kpi.id)
if not p:
st["no_period"] += 1
logger.warning(f" 跳过(无可用期间): {kpi.kpi_name} 无任何 YYYY-MM 实测值")
continue
# 获取该KPI该期间的最新值
latest = db_session.query(KPIValue).filter(
KPIValue.kpi_id == kpi.id,
KPIValue.period == period,
KPIValue.period == p,
).order_by(KPIValue.calculated_at.desc()).first()
if not latest or latest.actual_value is None:
st["no_value"] += 1
continue
actual = latest.actual_value
# 单位口径(裁定2a):取数归一 + 疑似错配降级门
cal = resolve_caliber(latest.actual_value, kpi)
if cal["status"] == "dimension_suspect":
st["dimension_suspect"] += 1
st["suspect_kpis"].append("%s[%s] actual=%s unit=%s" % (
kpi.kpi_code, p, latest.actual_value, kpi.unit))
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" % (
kpi.kpi_name, p, latest.actual_value, kpi.unit, cal["reason"]))
continue
actual = cal["value"]
if cal["status"] == "normalized":
st["normalized"] += 1
st["normalized_kpis"].append("%s[%s] %s → %s(×%s)" % (
kpi.kpi_code, p, latest.actual_value, actual, cal["factor"]))
st["periods_used"][p] = st["periods_used"].get(p, 0) + 1
# 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)
# 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')
@@ -101,6 +166,8 @@ def run_alert_check(db_session, period: str = None) -> int:
if level == "green":
# 正常状态:不生成待处理预警(如有旧的red/yellow预警自动解除)
break
if cal.get("note"):
msg = "%s|%s" % (msg, cal["note"])
# 检查是否已有该期间该KPI同级别的预警
existing = db_session.query(KPIAlert).filter(
KPIAlert.kpi_id == kpi.id,
@@ -110,6 +177,16 @@ def run_alert_check(db_session, period: str = None) -> int:
if existing:
# 已有预警,跳过
st["skipped_existing"] += 1
break
st["planned"].append({
"kpi": "%s/%s" % (kpi.kpi_code, kpi.kpi_name), "period": p,
"actual": actual, "raw_actual": latest.actual_value, "factor": cal["factor"],
"level": level, "message": msg,
})
if dry_run:
new_count += 1
break
# 创建新预警
@@ -118,7 +195,7 @@ def run_alert_check(db_session, period: str = None) -> int:
kpi_id=kpi.id,
kpi_value_id=latest.id,
alert_level=level,
alert_message=f"{kpi.kpi_name}[{period}] {msg}",
alert_message=f"{kpi.kpi_name}[{p}] {msg}",
status="pending",
)
db_session.add(alert)
@@ -160,12 +237,15 @@ def run_alert_check(db_session, period: str = None) -> int:
KPIAlert.alert_level == "red",
KPIAlert.status.in_(["pending", "processing"]),
).first()
if existing_red:
if existing_red and not dry_run:
existing_red.status = "resolved"
existing_red.resolution = "自动解除: 当前值不再触发红色阈值"
existing_red.resolved_at = datetime.now()
logger.info(f" 自动解除预警 [red] {kpi.kpi_name}")
if dry_run:
db_session.rollback() # 抽查复核/放行前证据:确保零写入
return new_count
db_session.commit()
return new_count
@@ -205,22 +285,30 @@ def run_rule_engine_checks(db_session) -> dict:
return stats
def generate_and_push(db_session) -> dict:
"""生成预警并推送,返回统计"""
period = datetime.now().strftime("%Y-%m")
def generate_and_push(db_session, period: Optional[str] = None, dry_run: bool = False) -> dict:
"""生成预警并推送,返回统计
# 0. Bug1修复: 先清理历史green预警
cleaned = cleanup_green_alerts(db_session)
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)。
"""
cur_month = 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)"))
# 1. 生成预警
logger.info(f"开始预警检查 ({period})...")
new_count = run_alert_check(db_session, period)
logger.info(f"预警检查完成: 新增 {new_count} 条")
# 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)
# 1a. 覆盖度自检(2026-09-16 新增,任务 finance-20260916-cma-health-gaps-3items · 项3):
# run_alert_check 的期间口径 = 当月(period=current month),若当月尚无任何 KPIValue,
# 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"——
# 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。
# 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)
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):
# 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";
# 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。
coverage = {"current_month": cur_month, "periods_used": st.get("periods_used", {})}
try:
kpis_with_values = 0
active_kpis = db_session.query(KPIDefinition).filter(KPIDefinition.status == "active").all()
@@ -228,33 +316,30 @@ def generate_and_push(db_session) -> dict:
if not any((k.threshold_red, k.threshold_yellow, k.threshold_green)):
continue
hit = db_session.query(KPIValue).filter(
KPIValue.kpi_id == k.id, KPIValue.period == period,
KPIValue.kpi_id == k.id, KPIValue.period == cur_month,
KPIValue.actual_value.isnot(None),
).first()
if hit:
kpis_with_values += 1
coverage = {"period": period, "kpis_with_threshold_and_value": kpis_with_values}
coverage["kpis_with_threshold_and_value"] = kpis_with_values
coverage["period"] = cur_month
if kpis_with_values == 0:
latest_period = db_session.query(KPIValue.period).filter(
KPIValue.actual_value.isnot(None),
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)
).order_by(KPIValue.period.desc()).first()
coverage["latest_period_in_db"] = resolve_latest_period(db_session)
logger.warning(
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,"
f"「0 条新预警」= 无数据可判,非「确无阈值触发」。库内最新期间="
f"{latest_period[0] if latest_period else 'N/A'}"
)
coverage["latest_period_in_db"] = latest_period[0] if latest_period else None
"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);"
"「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" % (
cur_month, st.get("periods_used"), coverage["latest_period_in_db"]))
except Exception as e:
logger.error(f"覆盖度自检失败: {e}")
coverage = {"error": str(e)}
# 1b. 规则引擎检查(预测偏差 / 客户集中度,P2 2026-09-10)
rule_stats = run_rule_engine_checks(db_session)
# 1b. 规则引擎检查(预测偏差 / 客户集中度,P2 2026-09-10;dry-run 不写)
rule_stats = {"forecast_deviation": 0, "customer_concentration": 0} if dry_run \
else run_rule_engine_checks(db_session)
# 2. 推送
# 2. 推送(dry-run 零推送)
pushed = 0
if new_count > 0:
if new_count > 0 and not dry_run:
try:
from app.utils.notifier import push_pending_alerts
pushed = push_pending_alerts(db_session)
@@ -262,24 +347,51 @@ def generate_and_push(db_session) -> dict:
except Exception as e:
logger.error(f"推送失败: {e}")
return {"period": period, "new_alerts": new_count, "pushed": pushed,
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,
"cleaned_green": cleaned, "rule_engine": rule_stats,
"coverage": coverage}
"coverage": coverage,
# 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()