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()
|
||||
|
||||
|
||||
@@ -15,8 +15,9 @@
|
||||
- **NA(无发生额)标注(本版本新增,裁定 finance-20260916-cma-caliber-ruling §2.1)**:
|
||||
某活动**无任何项目行**时净额记 0.00(三净额列为 NOT NULL,表本身表达不了 NA),
|
||||
同时在 `remark` 写入**固定短语**「<活动>活动本期无发生额(无项目行)」,
|
||||
供判定层用 `parse_na_activities(remark)` 取回 → 判定时该维度**不参与**(降维),
|
||||
避免把「无发生额」与「收付相抵的 0」混为一谈(后者才参与判定)。
|
||||
供判定层用 `parse_na_activities(remark)` 取回 → **仅作标注与机读入口**;
|
||||
口径裁定(2026-09-17)已定:该维按 **0 如实参与判定**(八类判定的**二维映射**,
|
||||
经营(±)×筹资(±) 出 2 个候选类型),**不再**因 NA/0 整体判「未判定」。
|
||||
- source='official'(官方报表口径);期初/期末现金 留空(主表采集缺陷,见报告 §项1-②)
|
||||
- 同 (entity_id, period) 重复执行 = 覆盖更新(幂等)
|
||||
|
||||
@@ -52,8 +53,10 @@ _NA_RE = re.compile(r"(经营活动|投资活动|筹资活动)本期无发生额
|
||||
def parse_na_activities(remark):
|
||||
"""从 cashflow_statements.remark 取回 NA(无发生额)活动集合。
|
||||
|
||||
判定层入口:NA 维度**不参与**八类判定(降维),其 0.00 是"表表达不了 NA"的占位,
|
||||
不是"收付相抵的 0"。同时提供 `na_flags(remark)` 返回 {活动: True/False} 供逐维判断。
|
||||
判定层入口(**只作标注/机读**):NA 维度的 0.00 是"表表达不了 NA"的占位,
|
||||
不等于"收付相抵的 0";但按 2026-09-17 口径裁定,两者**都按 0 参与判定**
|
||||
(投资活动=0 → 二维映射出 2 个候选类型),NA 短语仅用于页面/报告显式标注。
|
||||
`na_flags(remark)` 返回 {活动: True/False} 供逐维判断与文案生成。
|
||||
"""
|
||||
if not remark:
|
||||
return set()
|
||||
@@ -117,7 +120,7 @@ def collect(period_filter=None):
|
||||
na_phrases = [NA_PHRASE_TMPL.format(cls=c) for c in missing]
|
||||
head = "源: 智享通现金流量统计表 %s(单位元→万元 /10000);项目行 %d 条" % (
|
||||
os.path.basename(src), len(rows))
|
||||
remark = (head + ";NA(无发生额,不参与判定): " + "、".join(na_phrases)) if na_phrases \
|
||||
remark = (head + ";NA(无发生额,按0参与判定): " + "、".join(na_phrases)) if na_phrases \
|
||||
else (head + ";三类活动均有项目行(无 NA)")
|
||||
payloads.append({
|
||||
"period": period,
|
||||
@@ -145,7 +148,7 @@ def _self_test():
|
||||
([], {"经营活动": False, "投资活动": False, "筹资活动": False}),
|
||||
):
|
||||
phrases = [NA_PHRASE_TMPL.format(cls=c) for c in missing]
|
||||
remark = ("源: X;项目行 3 条;NA(无发生额,不参与判定): " + "、".join(phrases)) if phrases \
|
||||
remark = ("源: X;项目行 3 条;NA(无发生额,按0参与判定): " + "、".join(phrases)) if phrases \
|
||||
else "源: X;项目行 3 条;三类活动均有项目行(无 NA)"
|
||||
assert na_flags(remark) == expect, (missing, remark)
|
||||
assert parse_na_activities(remark) == set(missing)
|
||||
@@ -198,12 +201,23 @@ def main():
|
||||
continue
|
||||
n = p["nets_wan"]
|
||||
cls = classify_enterprise(n["经营活动"], n["投资活动"], n["筹资活动"])
|
||||
# 裁定1(2026-09-17):投资活动=0 → dimension="2D"(type_no=None,候选 2 个)
|
||||
# ⇒ 打印层不得假定 classified ⇒ type_no 非空(原实现此处 TypeError 崩掉整轮 dry-run)
|
||||
if cls.get("classified"):
|
||||
if cls.get("dimension") == "2D":
|
||||
verdict = "二维判定(%s) → 候选 %s" % (
|
||||
cls.get("dimension_label") or "投资活动=0",
|
||||
" / ".join("类型%d %s" % (c["type_no"], c["name"])
|
||||
for c in cls.get("candidates") or []))
|
||||
else:
|
||||
verdict = "类型%d %s" % (cls["type_no"], cls["name"])
|
||||
else:
|
||||
verdict = "未判定: " + cls.get("reason", "")[:28]
|
||||
print(" %-8s O=%8.2f I=%8.2f F=%8.2f 万 | 判定=%s | 源=%s"
|
||||
% (p["period"], n["经营活动"], n["投资活动"], n["筹资活动"],
|
||||
("类型%d %s" % (cls["type_no"], cls["name"])) if cls.get("classified")
|
||||
else ("未判定: " + cls.get("reason", "")[:28]),
|
||||
os.path.basename(p["src"])))
|
||||
print(" NA(无发生额,不参与判定)=%s" % ("、".join(p["na_classes"]) or "无"))
|
||||
verdict, os.path.basename(p["src"])))
|
||||
print(" NA(无发生额)=%s;投资栏标注=%s" % (
|
||||
"、".join(p["na_classes"]) or "无", cls.get("investing_note") or "-"))
|
||||
if not args.apply:
|
||||
continue
|
||||
rec = db.query(CashFlowStructureValue).filter(
|
||||
|
||||
@@ -0,0 +1,99 @@
|
||||
#!/usr/bin/env python3
|
||||
# -*- coding: utf-8 -*-
|
||||
"""比率类 KPI 单位对照表(只读)—— 财务口径裁定 裁定2a 的产出器
|
||||
|
||||
用途:逐个比率类 KPI 核对「定义 / 声明单位 / 阈值量纲 / 实测值量纲」,出对照表。
|
||||
判定侧的事实源是 `app/utils/caliber_units.RATIO_CALIBER_TABLE`(本脚本只核对与呈现,
|
||||
不写库、不改阈值)。
|
||||
|
||||
用法:
|
||||
python3 scripts/kpi_unit_crosscheck.py # 全账套
|
||||
python3 scripts/kpi_unit_crosscheck.py --entity-id 1 # 单账套
|
||||
python3 scripts/kpi_unit_crosscheck.py --json # JSON(机读)
|
||||
"""
|
||||
import argparse
|
||||
import json
|
||||
import os
|
||||
import re
|
||||
import sys
|
||||
|
||||
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
|
||||
|
||||
from sqlalchemy import text # noqa: E402
|
||||
from app.database import get_engine # noqa: E402
|
||||
from app.utils.caliber_units import resolve_caliber # noqa: E402
|
||||
|
||||
PERIOD_RE = re.compile(r"^[0-9]{4}-[0-9]{2}$")
|
||||
|
||||
|
||||
def q(sql, **params):
|
||||
with get_engine().connect() as c:
|
||||
return [dict(r._mapping) for r in c.execute(text(sql), params).fetchall()]
|
||||
|
||||
|
||||
class _K(dict):
|
||||
"""把 kpi 行包成 duck type(resolve_caliber 只读属性)"""
|
||||
|
||||
def __getattr__(self, item):
|
||||
return self.get(item)
|
||||
|
||||
|
||||
def latest_value(kpi_id):
|
||||
rows = q("SELECT period, actual_value FROM kpi_values WHERE kpi_id=:k AND actual_value IS NOT NULL "
|
||||
"ORDER BY period DESC, calculated_at DESC LIMIT 20", k=kpi_id)
|
||||
for r in rows:
|
||||
if PERIOD_RE.fullmatch(str(r["period"] or "")):
|
||||
return r["period"], r["actual_value"]
|
||||
return None, None
|
||||
|
||||
|
||||
def main():
|
||||
ap = argparse.ArgumentParser()
|
||||
ap.add_argument("--entity-id", type=int, default=None)
|
||||
ap.add_argument("--json", action="store_true")
|
||||
args = ap.parse_args()
|
||||
|
||||
where = "WHERE d.status='active' AND (d.threshold_red IS NOT NULL OR d.threshold_yellow IS NOT NULL " \
|
||||
"OR d.threshold_green IS NOT NULL)"
|
||||
params = {}
|
||||
if args.entity_id:
|
||||
where += " AND d.entity_id=:e"
|
||||
params["e"] = args.entity_id
|
||||
rows = q("SELECT d.id, d.entity_id, d.kpi_code, d.kpi_name, d.unit, d.threshold_green, "
|
||||
"d.threshold_yellow, d.threshold_red FROM kpi_definitions d %s "
|
||||
"ORDER BY d.entity_id, d.id" % where, **params)
|
||||
|
||||
out = []
|
||||
for r in rows:
|
||||
p, v = latest_value(r["id"])
|
||||
cal = resolve_caliber(v, _K(r))
|
||||
out.append({
|
||||
"kpi_code": r["kpi_code"], "kpi_name": r["kpi_name"], "entity_id": r["entity_id"],
|
||||
"declared_unit": r["unit"],
|
||||
"thresholds": "%s|%s|%s" % (r["threshold_green"], r["threshold_yellow"], r["threshold_red"]),
|
||||
"latest_period": p, "actual": v,
|
||||
"caliber_status": cal["status"], "norm_factor": cal["factor"],
|
||||
"normalized": cal["value"], "note": cal["note"], "reason": cal["reason"],
|
||||
})
|
||||
|
||||
if args.json:
|
||||
print(json.dumps(out, ensure_ascii=False, indent=1, default=str))
|
||||
return 0
|
||||
|
||||
print("=== 比率类 KPI 单位对照表(只读;裁定2a)===")
|
||||
print("%-4s %-8s %-22s %-6s %-10s %-12s %-8s %-6s %s" % (
|
||||
"eid", "code", "name", "unit", "latest", "actual", "status", "factor", "thresholds"))
|
||||
for x in out:
|
||||
print("%-4s %-8s %-22s %-6s %-10s %-12s %-18s %-6s %s" % (
|
||||
x["entity_id"], x["kpi_code"], x["kpi_name"][:20], x["declared_unit"] or "-",
|
||||
x["latest_period"] or "-", x["actual"] if x["actual"] is not None else "-",
|
||||
x["caliber_status"], x["norm_factor"], x["thresholds"]))
|
||||
n_norm = sum(1 for x in out if x["norm_factor"] != 1)
|
||||
n_sus = sum(1 for x in out if x["caliber_status"] == "dimension_suspect")
|
||||
print("=== 合计 %d 项:口径归一 ×100 %d 项 / 同量纲直判 %d 项 / 疑似错配降级待核 %d 项 ===" % (
|
||||
len(out), n_norm, len(out) - n_norm - n_sus, n_sus))
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -2,7 +2,17 @@
|
||||
# -*- coding: utf-8 -*-
|
||||
"""阈值单位口径修正 + 量纲守卫装配(迁移脚本·准备态)
|
||||
|
||||
依据:财务口径裁定 finance-20260916-cma-caliber-ruling.md v1.0 §四(裁定③)+ §3.3/§3.4
|
||||
⚠️ **已被取代,不得执行(2026-09-17)**:
|
||||
本脚本基于 2026-09-16 的口径草案(**把阈值改成「倍」写法** >=2.0/>=1.0/<1.0)。
|
||||
2026-09-17 财务**正式裁定**(`wecom-finance/reports/CMA_口径裁定_20260917.md` 裁定2a)
|
||||
采用**相反方向**:比率类统一「百分比(%)」口径、**阈值保持不变**(150/80),
|
||||
在**取数层** ×100 归一(实现:`app/utils/caliber_units.py` + `scripts/alert_generator.py`)。
|
||||
⇒ 执行本脚本会把口径反向切回「倍」,与现行裁定冲突;假红灯 586/587 在新口径下
|
||||
**是合法红灯**(流动比率 1.29=129% < 150,与「流动性偏紧」一致),**不得作废**。
|
||||
保留本文件仅为审计链(历史草案)——如未来另有阈值单位新裁定,须先改 `PLAN` 与
|
||||
`--resolve-false-reds` 的语义再执行。
|
||||
|
||||
原依据:财务口径裁定 finance-20260916-cma-caliber-ruling.md v1.0 §四(裁定③)+ §3.3/§3.4
|
||||
· 4.1 单位规范:偿债能力比率=**倍**(无量纲);资产负债率等=%;返利率=%
|
||||
· 4.3 具体阈值裁定(贸易型:白酒经销 / IT 经销)
|
||||
· 3.3 09-09 假红灯 586/587 按「口径错误」作废并重算
|
||||
|
||||
Reference in New Issue
Block a user