178 lines
8.2 KiB
Python
178 lines
8.2 KiB
Python
#!/usr/bin/env python3
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"""预算偏差告警归因回填 —— yanxue-20260914-budget-p13p14-activation（P1-③ 激活）
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两类动作（都在本进程内组装，不依赖线上服务是否已加载新代码）:
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1) attribution 为空的历史告警 → 现算归因并落库（等价于现成接口
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GET /budget/deviation-alerts/{id}/attribution 的组装逻辑，见 app/api/budget.py）
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2) 已有旧口径归因的告警 → 用修正后的科目口径重算覆盖（旧值备份见
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/root/WB_WS/_backups/p13p14-20260914/）
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另: alert_type 为空 → 按 KPI 特征推断补上；scenario_id 为空且命中
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scenario_suggestions → 补 scenario_id（让告警"能解释、能关"）
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用法:
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/usr/bin/python3 scripts/kpi_alert_attribution_backfill.py # dry-run（只算不写）
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/usr/bin/python3 scripts/kpi_alert_attribution_backfill.py --apply # 落库
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落库前置: cma_api 需对 budget_deviation_alerts 有 UPDATE 权限
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（SHOW GRANTS 现状: 该表未在授权清单内 → 1142 UPDATE command denied）。
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"""
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import json
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import os
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import sys
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from types import SimpleNamespace
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if __name__ == "__main__":
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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 BudgetDeviationAlert, KPIDefinition, KPIValueSource, ScenarioSuggestion
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from app.utils.alert_attribution import build_attribution, match_scenario
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OUT = "/tmp/budget-p13p14/attribution-conclusions.json"
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def mapping_status(db, kpi_id):
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src = db.query(KPIValueSource).filter(
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KPIValueSource.kpi_id == kpi_id,
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KPIValueSource.source_table == "voucher_details",
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).order_by(KPIValueSource.status.asc()).first()
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return src.status if src else None
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def conclusion(alert, kpi, attribution, scenario, map_status):
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dims = attribution.get("dimensions") or []
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subs = attribution.get("subjects") or []
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trend = attribution.get("trend") or {}
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vtype = attribution.get("variance_type")
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hot = [s for s in subs if abs(s.get("amount_diff") or 0) > 0.01][:3]
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if hot:
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sub_txt = "; ".join(
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f"{s['subject_code']} {s.get('subject_name', '')} "
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f"{s['amount_diff']:+.2f}元(x{s.get('weight')})" for s in hot)
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depth = f"科目级({map_status or 'kpi_subject_map原口径'})"
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elif map_status:
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sub_txt = (f"科目明细为空/金额为0（映射={map_status}，当期凭证明细无该科目发生额）")
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depth = f"KPI级(映射={map_status})"
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else:
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sub_txt = "无取数映射（kpi_subject_map 科目未机械桥接到 voucher_details 科目）→ 仅 KPI 级结论"
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depth = "KPI级(无映射)"
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dim_txt = "; ".join(
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f"{d.get('kpi_name')} 偏差{d.get('deviation_value')}" for d in dims
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if d.get("deviation_value") is not None and abs(d["deviation_value"]) > 0.01) or "无下级KPI层级"
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trend_txt = (f"{trend.get('type')}({trend.get('message')})" if trend.get("anomaly")
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else "无连续3期异常")
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view = (
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f"[{alert.id}] {kpi.kpi_code if kpi else alert.kpi_id} {kpi.kpi_name if kpi else ''} {alert.period}: "
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f"实际{alert.actual_value} vs 预算{alert.budget_value}（偏差{alert.deviation_rate}%, {alert.alert_level}）| "
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f"场景={alert.alert_type or '未分类'}{'(建议:' + scenario['title'] + ')' if scenario else ''} | "
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f"深度={depth} | 量价={vtype} | 主科目={sub_txt} | 子KPI={dim_txt} | 趋势={trend_txt}"
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)
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return view, depth
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def main():
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apply = "--apply" in sys.argv
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db = get_session_local()()
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try:
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alerts = db.query(BudgetDeviationAlert).filter(
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BudgetDeviationAlert.entity_id == 1).order_by(BudgetDeviationAlert.id).all()
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print(f"== 告警: {len(alerts)} 条（open {sum(1 for a in alerts if a.status == 'open')}）"
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f" | mode={'APPLY' if apply else 'DRY-RUN'}")
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filled, recomputed, type_filled, scenario_filled = 0, 0, 0, 0
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lines = []
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for a in alerts:
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kpi = db.query(KPIDefinition).filter(KPIDefinition.id == a.kpi_id).first()
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mstat = mapping_status(db, a.kpi_id)
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att, inferred = build_attribution(db, a.kpi_id, a.period, a.alert_type)
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had = a.attribution is not None
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if apply:
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if not had:
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a.attribution = att
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filled += 1
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else:
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if (a.attribution or {}) != att:
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a.attribution = att
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recomputed += 1
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if a.alert_type is None and inferred:
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a.alert_type = inferred
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type_filled += 1
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eff_type = a.alert_type or inferred
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scenario = match_scenario(db, eff_type)
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if apply and scenario and a.scenario_id is None:
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a.scenario_id = scenario["scenario_id"]
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scenario_filled += 1
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alert_copy = a
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if not apply:
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# 只读预览：不改 ORM 对象（避免 autoflush 落库）
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alert_copy = SimpleNamespace(
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id=a.id, kpi_id=a.kpi_id, period=a.period, status=a.status,
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alert_level=a.alert_level, budget_value=a.budget_value,
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actual_value=a.actual_value, deviation_rate=a.deviation_rate,
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deviation_value=a.deviation_value, alert_type=eff_type,
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scenario_id=a.scenario_id)
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view, depth = conclusion(alert_copy, kpi, att, scenario, mstat)
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lines.append({
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"id": a.id, "kpi_id": a.kpi_id, "kpi_code": kpi.kpi_code if kpi else None,
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"kpi_name": kpi.kpi_name if kpi else None,
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"period": a.period, "status": a.status, "alert_level": a.alert_level,
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"budget_value": a.budget_value, "actual_value": a.actual_value,
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"deviation_rate": a.deviation_rate, "alert_type": eff_type,
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"scenario_id": a.scenario_id,
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"mapping_status": mstat, "depth": depth,
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"n_subjects": len(att.get("subjects") or []),
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"n_subject_moves": sum(1 for s in (att.get("subjects") or [])
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if abs(s.get("amount_diff") or 0) > 0.01),
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"variance_type": att.get("variance_type"),
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"had_attribution": had,
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"view": view,
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})
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if apply:
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try:
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db.commit()
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except Exception as e:
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db.rollback()
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print(f"!! 落库失败（未写任何行）: {type(e).__name__}: {str(e)[:200]}")
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return 2
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for row in lines:
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print(row["view"])
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os.makedirs(os.path.dirname(OUT), exist_ok=True)
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with open(OUT, "w") as fh:
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json.dump(lines, fh, ensure_ascii=False, indent=1)
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print(f"\n== 结论落盘: {OUT} ({len(lines)} 条)")
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depths = {}
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for row in lines:
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depths[row["depth"]] = depths.get(row["depth"], 0) + 1
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print(f"== 归因深度分布: {json.dumps(depths, ensure_ascii=False)}")
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opens = [r for r in lines if r["status"] == "open"]
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print(f"== open 告警有结论: {len(opens)}/{len(opens)}"
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f" | 其中科目级可解释: {sum(1 for r in opens if r['depth'].startswith('科目级'))}")
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if apply:
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n_attr = db.query(BudgetDeviationAlert).filter(
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BudgetDeviationAlert.entity_id == 1,
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BudgetDeviationAlert.attribution.isnot(None)).count()
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total = db.query(BudgetDeviationAlert).filter(BudgetDeviationAlert.entity_id == 1).count()
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n_scen = db.query(BudgetDeviationAlert).filter(
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BudgetDeviationAlert.entity_id == 1,
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BudgetDeviationAlert.scenario_id.isnot(None)).count()
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print(f"== 落库结果: attribution {n_attr}/{total} | scenario_id {n_scen} | "
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f"新填 {filled} / 重算 {recomputed} / 场景类型补全 {type_filled} / "
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f"场景建议补全 {scenario_filled}")
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else:
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print("== DRY-RUN: 未写库（落库需 --apply，且 cma_api 需 UPDATE 授权）")
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return 0
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finally:
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db.close()
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if __name__ == "__main__":
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sys.exit(main())
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