"""保本点(盈亏平衡)派生KPI执行器 — 管理会计OS (cma-bep-kpi 2026-09-08) 按财务Bot权威口径（陕西酣客_保本点分析_2026年1-7月.md）自动计算并落库五个派生KPI： F_BEP_REVENUE 保本销售额(万元) = 月均管理费 ÷ 边际贡献率 (账面口径,含折旧) F_BEP_COVER 保本覆盖率(%) = 月均销售 ÷ 保本销售额 × 100 (正向: >=100绿 >=85黄 <85红) F_BEP_GAP 保本缺口(%) = (保本销售额-月均销售) ÷ 保本销售额 × 100 (反向: <=0绿 <=15黄 >15红) F_BEP_REVENUE_CASH 现金保本销售额(万元) = (月均管理费-月均折旧) ÷ 边际贡献率 (现金口径,剔除折旧560213,中性无阈值) F_BEP_COVER_CASH 现金保本覆盖率(%) = 月均销售 ÷ 现金保本销售额 × 100 (正向: >=100绿 >=85黄 <85红) 口径（与财务Bot报告一致）： - 销售收入: voucher_details.subject_code='5001'(主营业务收入) 贷方合计，当年1月至目标月 YTD 月均 - 管理费: subject_code LIKE '5602%'(管理费用，含560213折旧) 借方合计，YTD 月均 → 账面口径 - 折旧: subject_code = '560213'(管理费用-折旧叶子) 借方合计，YTD 月均 → 现金口径剔除项(eq精确匹配,防5602130误含) - 渠补率: 厂家政策定死 84.61% (571103渠补支出/5001销售, 1-7月累计凭证验证≈84.0%~84.6%) - 边际贡献率 = 1 - 渠补率 = 15.39% - 目标月: --period 显式指定；默认自动选最近完整月（当月跳过；最近月销售额<近6月均30%视为未结账回退） - 单位: voucher 金额为元，聚合后 /10000 → 万元 - 幂等: 同 kpi_id+period+source_type='derived' 存在则更新，可安全重跑 - 只写 source_type='derived' 行；不触碰 auto_collect/manual/excel/ledger 行；不改 collector 逻辑 用法: venv/bin/python3 scripts/kpi_bep_deriver.py # 自动选目标月 venv/bin/python3 scripts/kpi_bep_deriver.py --period 2026-07 # 指定期间(实跑验证用) venv/bin/python3 scripts/kpi_bep_deriver.py --entity 1 --rebate-rate 84.61 venv/bin/python3 scripts/kpi_bep_deriver.py --dry-run # 只计算不落库 """ import argparse import logging import os import sys from datetime import datetime, date sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) import re from sqlalchemy import func from app.database import get_session_local from app.models import KPIValue, KPIDefinition, VoucherDetail, KPIAlert logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s") logger = logging.getLogger("cma.bep_deriver") # 厂家政策渠补率（定死不可谈判，财务Bot报告权威值 2026-09-08） POLICY_REBATE_RATE_PCT = 84.61 # 派生KPI 编码 → (kpi_code, 名称) TARGET_KPIS = [ ("F_BEP_REVENUE", "保本销售额"), ("F_BEP_COVER", "保本覆盖率"), ("F_BEP_GAP", "保本缺口"), ("F_BEP_REVENUE_CASH", "现金口径保本销售额"), ("F_BEP_COVER_CASH", "现金口径保本覆盖率"), ] # 现金口径 KPI 编码（计算路径独立于账面，remark 文案用现金口径） CASH_CODES = {"F_BEP_REVENUE_CASH", "F_BEP_COVER_CASH"} SALES_CODE = "5001" # 主营业务收入 ADMIN_PREFIX = "5602" # 管理费用（含折旧叶子560213） DEP_SUBJECT = "560213" # 管理费用-折旧（现金口径剔除项，eq 精确匹配防 5602130 误含） REBATE_CODE = "571103" # 渠补/捐赠支出（校验用，不直接进公式） def _month_range(period: str): """返回该期间当年1月1日到月末的日期边界（用于 voucher_date 过滤兜底）""" y = int(period[:4]) m = int(period[5:7]) start = date(y, 1, 1) # 月末 if m == 12: end = date(y, 12, 31) else: end = date(y, m + 1, 1).replace(day=1) # 次月1日 from datetime import timedelta end = end - timedelta(days=1) return start, end def _sum_field(db, entity_id: int, period_from: str, period_to: str, field: str, subject_filter=None) -> float: """聚合 voucher_details 金额（元）。subject_filter: ('eq', code) / ('like', prefix)""" q = db.query(func.sum(getattr(VoucherDetail, field))).filter( VoucherDetail.entity_id == entity_id, VoucherDetail.carry_forward == 0, VoucherDetail.period >= period_from, VoucherDetail.period <= period_to, ) if subject_filter: kind, code = subject_filter if kind == "eq": q = q.filter(VoucherDetail.subject_code == code) elif kind == "like": q = q.filter(VoucherDetail.subject_code.like(code + "%")) val = q.scalar() return float(val or 0.0) def _month_sales(db, entity_id: int, period: str) -> float: """单月销售收入（万元）——用于目标月完整度判断""" return _sum_field(db, entity_id, period, period, "credit_amount", ("eq", SALES_CODE)) / 10000.0 def _pick_target_period(db, entity_id: int, now: date) -> str: """自动选择目标月：跳过当月；最近月销售额<近6月完整月均30%则视为未结账回退""" # 收集已有数据月份（5001 贷方） rows = db.query(VoucherDetail.period).filter( VoucherDetail.entity_id == entity_id, VoucherDetail.period.like("%-__"), ).distinct().order_by(VoucherDetail.period.desc()).all() periods = [r[0] for r in rows if r[0] and len(r[0]) == 7] if not periods: logger.warning("voucher_details 无 period 数据，无法自动选月") return now.strftime("%Y-%m") # 过滤掉未来/当月（当月未结束数据不全） cur = now.strftime("%Y-%m") candidates = [p for p in periods if p < cur] if not candidates: candidates = [p for p in periods if p <= cur] if not candidates: candidates = periods # 参考月均：候选月中最近 6 个不同月的月销售 ref_months = [] for p in periods: if p >= cur: continue s = _month_sales(db, entity_id, p) ref_months.append((p, s)) if len(ref_months) >= 6: break ref_avg = (sum(s for _, s in ref_months) / len(ref_months)) if ref_months else None for p in candidates: s = _month_sales(db, entity_id, p) if s <= 0: continue # 该月无销售，往前找 if ref_avg and s < ref_avg * 0.3: logger.info("目标月 %s 销售 %.1f万 < 参考月均 %.1f万*30%%，视为未结账，回退", p, s, ref_avg) continue return p return candidates[0] def _eval_static_threshold(value: float, kpi) -> tuple: """按 KPI 定义 threshold_green/yellow/red 判定级别（绿→黄→红，命中即止）。 与 alert_generator._check_threshold 语义一致。green=正常不落预警。""" for level, field in (("green", "threshold_green"), ("yellow", "threshold_yellow"), ("red", "threshold_red")): expr = getattr(kpi, field, None) if not expr: continue m = re.match(r"(>=|<=|>|<|=|!=)\s*([\d.]+)", str(expr).strip()) if not m: continue op, val = m.group(1), float(m.group(2)) hit = { ">=": value >= val, "<=": value <= val, ">": value > val, "<": value < val, "=": value == val, "!=": value != val, }[op] if hit: level_names = {"green": "正常", "yellow": "预警", "red": "紧急"} msg = (f"KPI当前值 {value:.2f}，触发{level_names[level]}阈值 ({expr})") return level, msg return None, None def run_derive(db, entity_id: int, period: str, rebate_rate_pct: float, write_kpi: bool = True) -> dict: """计算并落库五个派生KPI（账面3条+现金2条）。返回结果摘要。""" kpis = {k.kpi_code: k for k in db.query(KPIDefinition).filter( KPIDefinition.entity_id == entity_id, KPIDefinition.kpi_code.in_([c for c, _ in TARGET_KPIS]), KPIDefinition.status == "active", ).all()} missing = [c for c, _ in TARGET_KPIS if c not in kpis] if missing: raise RuntimeError(f"entity={entity_id} 缺少派生KPI定义: {missing}") year = period[:4] period_from = f"{year}-01" period_to = period months = int(period[5:7]) # YTD 月数（1月=1 ... 7月=7） # 1. 取数（元 → 万元） sales_sum_w = _sum_field(db, entity_id, period_from, period_to, "credit_amount", ("eq", SALES_CODE)) / 10000.0 admin_sum_w = _sum_field(db, entity_id, period_from, period_to, "debit_amount", ("like", ADMIN_PREFIX)) / 10000.0 rebate_sum_w = _sum_field(db, entity_id, period_from, period_to, "debit_amount", ("eq", REBATE_CODE)) / 10000.0 dep_sum_w = _sum_field(db, entity_id, period_from, period_to, "debit_amount", ("eq", DEP_SUBJECT)) / 10000.0 sales_avg = sales_sum_w / months admin_avg = admin_sum_w / months dep_avg = dep_sum_w / months cash_admin_avg = admin_avg - dep_avg # 现金口径固定成本（剔除折旧纸面费用） # 2. 渠补率：厂家政策值优先，日志附凭证累计校验 calc_rebate = (rebate_sum_w / sales_sum_w * 100.0) if sales_sum_w > 0 else 0.0 if rebate_rate_pct is None: rebate_rate_pct = POLICY_REBATE_RATE_PCT cm_pct = 100.0 - rebate_rate_pct # 边际贡献率(%) # 3. 派生计算（万元 / %）——账面3条路径不变；现金口径在账面基础上剔除折旧 bep = admin_avg / (cm_pct / 100.0) if cm_pct > 0 else 0.0 cover = (sales_avg / bep * 100.0) if bep > 0 else 0.0 gap = ((bep - sales_avg) / bep * 100.0) if bep > 0 else 0.0 cash_bep = cash_admin_avg / (cm_pct / 100.0) if cm_pct > 0 else 0.0 cash_cover = (sales_avg / cash_bep * 100.0) if cash_bep > 0 else 0.0 values = { "F_BEP_REVENUE": round(bep, 1), "F_BEP_COVER": round(cover, 1), "F_BEP_GAP": round(gap, 1), "F_BEP_REVENUE_CASH": round(cash_bep, 1), "F_BEP_COVER_CASH": round(cash_cover, 1), } # 4. upsert kpi_values (source_type='derived'，幂等) batch = f"bep-{datetime.now().strftime('%Y%m%d%H%M%S')}" written = {} value_rows = {} for code, _ in TARGET_KPIS: kpi = kpis[code] if code in CASH_CODES: remark = (f"现金口径: 管理费月均{admin_avg:.2f}万-折旧月均{dep_avg:.2f}万" f"=固定现金{cash_admin_avg:.2f}万 ÷ 边际贡献率{cm_pct:.2f}% → 保本{cash_bep:.2f}万") else: remark = f"保本派生器: 销售月均{sales_avg:.1f}万/管理费月均{admin_avg:.1f}万/渠补率{rebate_rate_pct:.2f}%" existing = db.query(KPIValue).filter( KPIValue.kpi_id == kpi.id, KPIValue.period == period, KPIValue.source_type == "derived", ).first() if write_kpi: is_new = existing is None if existing: existing.actual_value = values[code] existing.source_batch = batch existing.remark = remark existing.data_status = "pending" else: existing = KPIValue( entity_id=entity_id, kpi_id=kpi.id, period=period, actual_value=values[code], source_type="derived", source_batch=batch, data_status="pending", remark=remark, ) db.add(existing) db.flush() value_rows[kpi.id] = existing written[code] = "insert" if is_new else "upsert" else: written[code] = "dry-run" if write_kpi: # 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: kpi = kpis[code] kpi_value = value_rows.get(kpi.id) if not kpi_value: continue level, msg = _eval_static_threshold(kpi_value.actual_value, kpi) all_pending = db.query(KPIAlert).filter( KPIAlert.kpi_id == kpi.id, KPIAlert.status == "pending", ).all() same_value = [a for a in all_pending if a.kpi_value_id == kpi_value.id] if level in ("yellow", "red") and any(a.alert_level == level for a in same_value): # 当前值级别未变 → 只清其它旧值预警，不重建 for a in all_pending: if a.kpi_value_id != kpi_value.id: a.status = "resolved" a.resolution = "保本派生器: 派生值更新，旧预警自动解除" a.resolved_at = datetime.now() continue for a in all_pending: a.status = "resolved" a.resolution = "保本派生器: 派生值更新/级别变更，旧预警自动解除" a.resolved_at = datetime.now() if level in ("yellow", "red"): db.add(KPIAlert( entity_id=entity_id, kpi_id=kpi.id, kpi_value_id=kpi_value.id, alert_level=level, alert_message=f"{kpi.kpi_name}[{period}] {msg}", status="pending", )) db.commit() return { "entity_id": entity_id, "period": period, "months": months, "sales_sum_w": round(sales_sum_w, 2), "sales_avg": round(sales_avg, 2), "admin_sum_w": round(admin_sum_w, 2), "admin_avg": round(admin_avg, 2), "dep_sum_w": round(dep_sum_w, 2), "dep_avg": round(dep_avg, 2), "cash_admin_avg": round(cash_admin_avg, 2), "rebate_sum_w": round(rebate_sum_w, 2), "rebate_policy_pct": rebate_rate_pct, "rebate_calc_pct": round(calc_rebate, 2), "cm_pct": round(cm_pct, 2), "values": values, "written": written, } def main(): ap = argparse.ArgumentParser(description="保本点派生KPI执行器") ap.add_argument("--period", default=None, help="目标期间 YYYY-MM（默认自动选最近完整月）") ap.add_argument("--entity", type=int, default=1, help="entity_id（默认1=陕西酣客）") ap.add_argument("--rebate-rate", type=float, default=None, help="渠补率%覆盖（默认厂家政策84.61）") ap.add_argument("--dry-run", action="store_true", help="只计算不落库") args = ap.parse_args() db = get_session_local()() try: period = args.period or _pick_target_period(db, args.entity, date.today()) r = run_derive(db, args.entity, period, args.rebate_rate, write_kpi=not args.dry_run) print(f"保本点派生计算完成 entity={r['entity_id']} period={r['period']} " f"(YTD {r['months']}个月) mode={'dry-run' if args.dry_run else 'write'}") print(f" 销售收入累计 {r['sales_sum_w']:.2f}万 月均 {r['sales_avg']:.2f}万") print(f" 管理费累计 {r['admin_sum_w']:.2f}万 月均 {r['admin_avg']:.2f}万 (含折旧,账面口径)") print(f" 折旧累计 {r['dep_sum_w']:.2f}万 月均 {r['dep_avg']:.2f}万 (560213) | " f"现金固定成本月均 {r['cash_admin_avg']:.2f}万 (管理费-折旧)") print(f" 渠补支出累计 {r['rebate_sum_w']:.2f}万 | 渠补率: 政策{r['rebate_policy_pct']:.2f}% " f"(凭证累计校验 {r['rebate_calc_pct']:.2f}%) | 边际贡献率 {r['cm_pct']:.2f}%") print(f" F_BEP_REVENUE 保本销售额 = {r['values']['F_BEP_REVENUE']} 万元") print(f" F_BEP_COVER 保本覆盖率 = {r['values']['F_BEP_COVER']} %") print(f" F_BEP_GAP 保本缺口 = {r['values']['F_BEP_GAP']} %") print(f" F_BEP_REVENUE_CASH 现金保本销售额 = {r['values']['F_BEP_REVENUE_CASH']} 万元") print(f" F_BEP_COVER_CASH 现金保本覆盖率 = {r['values']['F_BEP_COVER_CASH']} %") print(f" 落库: {r['written']}") finally: db.close() if __name__ == "__main__": main()