351 lines
16 KiB
Python
351 lines
16 KiB
Python
"""保本点(盈亏平衡)派生KPI执行器 — 管理会计OS (cma-bep-kpi 2026-09-08)
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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：
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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)
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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)
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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)
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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)
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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)
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口径（与财务Bot报告一致）：
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- 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
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- 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
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- 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)
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- 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%)
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- 边际贡献率 = 1 - 渠补率 = 15.39%
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- 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）
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- 单位: voucher 金额为元，聚合后 /10000 → 万元
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- 幂等: 同 kpi_id+period+source_type='derived' 存在则更新，可安全重跑
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- 只写 source_type='derived' 行；不触碰 auto_collect/manual/excel/ledger 行；不改 collector 逻辑
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用法:
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venv/bin/python3 scripts/kpi_bep_deriver.py # 自动选目标月
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venv/bin/python3 scripts/kpi_bep_deriver.py --period 2026-07 # 指定期间(实跑验证用)
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venv/bin/python3 scripts/kpi_bep_deriver.py --entity 1 --rebate-rate 84.61
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venv/bin/python3 scripts/kpi_bep_deriver.py --dry-run # 只计算不落库
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"""
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import argparse
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import logging
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import os
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import sys
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from datetime import datetime, date
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sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
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import re
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from sqlalchemy import func
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from app.database import get_session_local
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from app.models import KPIValue, KPIDefinition, VoucherDetail, KPIAlert
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logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s")
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logger = logging.getLogger("cma.bep_deriver")
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# 厂家政策渠补率（定死不可谈判，财务Bot报告权威值 2026-09-08）
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POLICY_REBATE_RATE_PCT = 84.61
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# 派生KPI 编码 → (kpi_code, 名称)
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TARGET_KPIS = [
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("F_BEP_REVENUE", "保本销售额"),
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("F_BEP_COVER", "保本覆盖率"),
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("F_BEP_GAP", "保本缺口"),
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("F_BEP_REVENUE_CASH", "现金口径保本销售额"),
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("F_BEP_COVER_CASH", "现金口径保本覆盖率"),
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]
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# 现金口径 KPI 编码（计算路径独立于账面，remark 文案用现金口径）
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CASH_CODES = {"F_BEP_REVENUE_CASH", "F_BEP_COVER_CASH"}
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SALES_CODE = "5001" # 主营业务收入
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ADMIN_PREFIX = "5602" # 管理费用（含折旧叶子560213）
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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）
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REBATE_CODE = "571103" # 渠补/捐赠支出（校验用，不直接进公式）
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def _month_range(period: str):
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"""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）"""
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y = int(period[:4])
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m = int(period[5:7])
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start = date(y, 1, 1)
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# 月末
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if m == 12:
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end = date(y, 12, 31)
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else:
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end = date(y, m + 1, 1).replace(day=1) # 次月1日
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from datetime import timedelta
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end = end - timedelta(days=1)
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return start, end
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def _sum_field(db, entity_id: int, period_from: str, period_to: str,
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field: str, subject_filter=None) -> float:
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"""聚合 voucher_details 金额（元）。subject_filter: ('eq', code) / ('like', prefix)"""
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q = db.query(func.sum(getattr(VoucherDetail, field))).filter(
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VoucherDetail.entity_id == entity_id,
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VoucherDetail.carry_forward == 0,
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VoucherDetail.period >= period_from,
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VoucherDetail.period <= period_to,
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)
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if subject_filter:
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kind, code = subject_filter
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if kind == "eq":
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q = q.filter(VoucherDetail.subject_code == code)
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elif kind == "like":
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q = q.filter(VoucherDetail.subject_code.like(code + "%"))
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val = q.scalar()
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return float(val or 0.0)
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def _month_sales(db, entity_id: int, period: str) -> float:
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"""单月销售收入（万元）——用于目标月完整度判断"""
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return _sum_field(db, entity_id, period, period, "credit_amount",
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("eq", SALES_CODE)) / 10000.0
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def _pick_target_period(db, entity_id: int, now: date) -> str:
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"""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"""
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# 收集已有数据月份（5001 贷方）
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rows = db.query(VoucherDetail.period).filter(
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VoucherDetail.entity_id == entity_id,
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VoucherDetail.period.like("%-__"),
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).distinct().order_by(VoucherDetail.period.desc()).all()
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periods = [r[0] for r in rows if r[0] and len(r[0]) == 7]
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if not periods:
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logger.warning("voucher_details 无 period 数据，无法自动选月")
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return now.strftime("%Y-%m")
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# 过滤掉未来/当月（当月未结束数据不全）
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cur = now.strftime("%Y-%m")
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candidates = [p for p in periods if p < cur]
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if not candidates:
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candidates = [p for p in periods if p <= cur]
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if not candidates:
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candidates = periods
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# 参考月均：候选月中最近 6 个不同月的月销售
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ref_months = []
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for p in periods:
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if p >= cur:
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continue
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s = _month_sales(db, entity_id, p)
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ref_months.append((p, s))
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if len(ref_months) >= 6:
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break
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ref_avg = (sum(s for _, s in ref_months) / len(ref_months)) if ref_months else None
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for p in candidates:
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s = _month_sales(db, entity_id, p)
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if s <= 0:
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continue # 该月无销售，往前找
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if ref_avg and s < ref_avg * 0.3:
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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)
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continue
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return p
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return candidates[0]
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def _eval_static_threshold(value: float, kpi) -> tuple:
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"""按 KPI 定义 threshold_green/yellow/red 判定级别（绿→黄→红，命中即止）。
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与 alert_generator._check_threshold 语义一致。green=正常不落预警。"""
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for level, field in (("green", "threshold_green"), ("yellow", "threshold_yellow"),
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("red", "threshold_red")):
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expr = getattr(kpi, field, None)
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if not expr:
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continue
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m = re.match(r"(>=|<=|>|<|=|!=)\s*([\d.]+)", str(expr).strip())
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if not m:
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continue
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op, val = m.group(1), float(m.group(2))
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hit = {
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">=": value >= val, "<=": value <= val,
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">": value > val, "<": value < val,
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"=": value == val, "!=": value != val,
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}[op]
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if hit:
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level_names = {"green": "正常", "yellow": "预警", "red": "紧急"}
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msg = (f"KPI当前值 {value:.2f}，触发{level_names[level]}阈值 ({expr})")
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return level, msg
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return None, None
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def run_derive(db, entity_id: int, period: str, rebate_rate_pct: float,
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write_kpi: bool = True) -> dict:
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"""计算并落库五个派生KPI（账面3条+现金2条）。返回结果摘要。"""
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kpis = {k.kpi_code: k for k in db.query(KPIDefinition).filter(
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KPIDefinition.entity_id == entity_id,
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KPIDefinition.kpi_code.in_([c for c, _ in TARGET_KPIS]),
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KPIDefinition.status == "active",
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).all()}
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missing = [c for c, _ in TARGET_KPIS if c not in kpis]
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if missing:
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raise RuntimeError(f"entity={entity_id} 缺少派生KPI定义: {missing}")
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year = period[:4]
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period_from = f"{year}-01"
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period_to = period
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months = int(period[5:7]) # YTD 月数（1月=1 ... 7月=7）
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# 1. 取数（元 → 万元）
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sales_sum_w = _sum_field(db, entity_id, period_from, period_to, "credit_amount", ("eq", SALES_CODE)) / 10000.0
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admin_sum_w = _sum_field(db, entity_id, period_from, period_to, "debit_amount", ("like", ADMIN_PREFIX)) / 10000.0
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rebate_sum_w = _sum_field(db, entity_id, period_from, period_to, "debit_amount", ("eq", REBATE_CODE)) / 10000.0
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dep_sum_w = _sum_field(db, entity_id, period_from, period_to, "debit_amount", ("eq", DEP_SUBJECT)) / 10000.0
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sales_avg = sales_sum_w / months
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admin_avg = admin_sum_w / months
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dep_avg = dep_sum_w / months
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cash_admin_avg = admin_avg - dep_avg # 现金口径固定成本（剔除折旧纸面费用）
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# 2. 渠补率：厂家政策值优先，日志附凭证累计校验
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calc_rebate = (rebate_sum_w / sales_sum_w * 100.0) if sales_sum_w > 0 else 0.0
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if rebate_rate_pct is None:
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rebate_rate_pct = POLICY_REBATE_RATE_PCT
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cm_pct = 100.0 - rebate_rate_pct # 边际贡献率(%)
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# 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
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bep = admin_avg / (cm_pct / 100.0) if cm_pct > 0 else 0.0
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cover = (sales_avg / bep * 100.0) if bep > 0 else 0.0
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gap = ((bep - sales_avg) / bep * 100.0) if bep > 0 else 0.0
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cash_bep = cash_admin_avg / (cm_pct / 100.0) if cm_pct > 0 else 0.0
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cash_cover = (sales_avg / cash_bep * 100.0) if cash_bep > 0 else 0.0
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values = {
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"F_BEP_REVENUE": round(bep, 1),
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"F_BEP_COVER": round(cover, 1),
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"F_BEP_GAP": round(gap, 1),
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"F_BEP_REVENUE_CASH": round(cash_bep, 1),
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"F_BEP_COVER_CASH": round(cash_cover, 1),
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}
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# 4. upsert kpi_values (source_type='derived'，幂等)
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batch = f"bep-{datetime.now().strftime('%Y%m%d%H%M%S')}"
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written = {}
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value_rows = {}
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for code, _ in TARGET_KPIS:
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kpi = kpis[code]
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if code in CASH_CODES:
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remark = (f"现金口径: 管理费月均{admin_avg:.2f}万-折旧月均{dep_avg:.2f}万"
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f"=固定现金{cash_admin_avg:.2f}万 ÷ 边际贡献率{cm_pct:.2f}% → 保本{cash_bep:.2f}万")
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else:
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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}%"
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existing = db.query(KPIValue).filter(
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KPIValue.kpi_id == kpi.id,
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KPIValue.period == period,
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KPIValue.source_type == "derived",
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).first()
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if write_kpi:
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is_new = existing is None
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if existing:
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existing.actual_value = values[code]
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existing.source_batch = batch
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existing.remark = remark
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existing.data_status = "pending"
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else:
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existing = KPIValue(
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entity_id=entity_id,
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kpi_id=kpi.id,
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period=period,
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actual_value=values[code],
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source_type="derived",
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source_batch=batch,
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data_status="pending",
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remark=remark,
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)
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db.add(existing)
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db.flush()
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value_rows[kpi.id] = existing
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written[code] = "insert" if is_new else "upsert"
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else:
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written[code] = "dry-run"
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if write_kpi:
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# 5. 同步预警: 仅对本派生KPI评估 threshold（green=正常不落 pending，yellow/red 落 pending）。
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# 幂等规则：同一 KPIValue 已有同级别 pending → 保持不动（值未变不重建）；
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# 其它/旧级别 pending → resolve；最新派生行永远只留一条当前级别。
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for code, _ in TARGET_KPIS:
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kpi = kpis[code]
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kpi_value = value_rows.get(kpi.id)
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if not kpi_value:
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continue
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level, msg = _eval_static_threshold(kpi_value.actual_value, kpi)
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all_pending = db.query(KPIAlert).filter(
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KPIAlert.kpi_id == kpi.id,
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KPIAlert.status == "pending",
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).all()
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same_value = [a for a in all_pending if a.kpi_value_id == kpi_value.id]
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if level in ("yellow", "red") and any(a.alert_level == level for a in same_value):
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# 当前值级别未变 → 只清其它旧值预警，不重建
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for a in all_pending:
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if a.kpi_value_id != kpi_value.id:
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a.status = "resolved"
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a.resolution = "保本派生器: 派生值更新，旧预警自动解除"
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a.resolved_at = datetime.now()
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continue
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for a in all_pending:
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a.status = "resolved"
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a.resolution = "保本派生器: 派生值更新/级别变更，旧预警自动解除"
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a.resolved_at = datetime.now()
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if level in ("yellow", "red"):
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db.add(KPIAlert(
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entity_id=entity_id,
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kpi_id=kpi.id,
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kpi_value_id=kpi_value.id,
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alert_level=level,
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alert_message=f"{kpi.kpi_name}[{period}] {msg}",
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status="pending",
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))
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db.commit()
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return {
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"entity_id": entity_id,
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"period": period,
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"months": months,
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"sales_sum_w": round(sales_sum_w, 2),
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"sales_avg": round(sales_avg, 2),
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"admin_sum_w": round(admin_sum_w, 2),
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"admin_avg": round(admin_avg, 2),
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"dep_sum_w": round(dep_sum_w, 2),
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"dep_avg": round(dep_avg, 2),
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"cash_admin_avg": round(cash_admin_avg, 2),
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"rebate_sum_w": round(rebate_sum_w, 2),
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"rebate_policy_pct": rebate_rate_pct,
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"rebate_calc_pct": round(calc_rebate, 2),
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"cm_pct": round(cm_pct, 2),
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"values": values,
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"written": written,
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}
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def main():
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ap = argparse.ArgumentParser(description="保本点派生KPI执行器")
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ap.add_argument("--period", default=None, help="目标期间 YYYY-MM（默认自动选最近完整月）")
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ap.add_argument("--entity", type=int, default=1, help="entity_id（默认1=陕西酣客）")
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ap.add_argument("--rebate-rate", type=float, default=None,
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help="渠补率%覆盖（默认厂家政策84.61）")
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ap.add_argument("--dry-run", action="store_true", help="只计算不落库")
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args = ap.parse_args()
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db = get_session_local()()
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try:
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period = args.period or _pick_target_period(db, args.entity, date.today())
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r = run_derive(db, args.entity, period, args.rebate_rate,
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write_kpi=not args.dry_run)
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print(f"保本点派生计算完成 entity={r['entity_id']} period={r['period']} "
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f"(YTD {r['months']}个月) mode={'dry-run' if args.dry_run else 'write'}")
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print(f" 销售收入累计 {r['sales_sum_w']:.2f}万 月均 {r['sales_avg']:.2f}万")
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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)")
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print(f" 折旧累计 {r['dep_sum_w']:.2f}万 月均 {r['dep_avg']:.2f}万 (560213) | "
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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()
|