423 lines
16 KiB
Python
423 lines
16 KiB
Python
"""
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CMA管理报表中心 — 管理会计OS
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非传统财务报表，聚焦管理决策分析
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报表:
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1. 管理利润表 — 收入→变动成本→边际贡献→固定成本→息税前利润
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2. 预算执行报告 — 各KPI预算vs实际vs差异率
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3. KPI趋势报告 — 选定KPI的历史趋势
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4. 四维度绩效评分卡 — BSC健康度雷达图
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"""
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from fastapi import APIRouter, Depends, Query, HTTPException
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from sqlalchemy.orm import Session
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from sqlalchemy import func
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from typing import Optional
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from datetime import datetime, date
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from app.database import get_db
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from app.auth_middleware import require_role, require_auth
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from app.models import KPIDefinition, KPIValue, BudgetPlan, StrategicMap, KPIAlert, User
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from app.utils.deviation_engine import calc_period_deviation, calc_period_diff
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import logging
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logger = logging.getLogger("cma.reports")
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router = APIRouter(prefix="/api/cma/reports", tags=["管理报表"],
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dependencies=[Depends(require_role("ceo", "finance", "business"))],
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)
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# ============================================================
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# 报表1: 管理利润表
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# ============================================================
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@router.get("/profit-summary")
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def get_profit_summary(
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period: str = Query(None, description="格式 YYYY-MM"),
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db: Session = Depends(get_db),
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):
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"""管理利润表 — 收入→变动成本→边际贡献→固定成本→息税前利润"""
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if period is None:
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period = datetime.now().strftime("%Y-%m")
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# 从KPI数据中获取各利润要素
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def get_val(code: str):
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kpi = db.query(KPIDefinition).filter(KPIDefinition.kpi_code == code).first()
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if not kpi:
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return None
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v = db.query(KPIValue).filter(
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KPIValue.kpi_id == kpi.id, KPIValue.period == period
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).order_by(KPIValue.id.desc()).first()
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return v.actual_value if v else None
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revenue = get_val("F_REVENUE")
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gross_profit_rate = get_val("F_PROFIT_RATE")
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net_profit_rate = get_val("F_NET_PROFIT_RATE")
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cost_ratio = get_val("F_COST_RATIO")
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# 计算利润要素
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# 营收已知，用毛利率算毛利，用成本率算成本
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gross_profit = round(revenue * (gross_profit_rate / 100), 2) if revenue and gross_profit_rate else None
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total_cost = round(revenue * (cost_ratio / 100), 2) if revenue and cost_ratio else None
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net_profit = round(revenue * (net_profit_rate / 100), 2) if revenue and net_profit_rate else None
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# 边际贡献 ≈ 毛利（简化模型）
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contribution_margin = gross_profit
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# 固定成本 ≈ 总成本 - 变动成本（假设变动成本=营收*50%）
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variable_cost = round(revenue * 0.50, 2) if revenue else None
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fixed_cost = round(total_cost - variable_cost, 2) if total_cost and variable_cost else None
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# 找上期做环比
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prev_year, prev_month = period.split("-")
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py, pm = int(prev_year), int(prev_month)
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pm -= 1
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if pm <= 0:
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pm += 12
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py -= 1
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prev_period = f"{py}-{pm:02d}"
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def get_prev_val(code: str):
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kpi = db.query(KPIDefinition).filter(KPIDefinition.kpi_code == code).first()
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if not kpi: return None
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v = db.query(KPIValue).filter(
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KPIValue.kpi_id == kpi.id, KPIValue.period == prev_period
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).order_by(KPIValue.id.desc()).first()
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return v.actual_value if v else None
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prev_revenue = get_prev_val("F_REVENUE")
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prev_gross_profit_rate = get_prev_val("F_PROFIT_RATE")
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prev_net_profit_rate = get_prev_val("F_NET_PROFIT_RATE")
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prev_cost_ratio = get_prev_val("F_COST_RATIO")
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prev_gross_profit = round(prev_revenue * (prev_gross_profit_rate / 100), 2) if prev_revenue and prev_gross_profit_rate else None
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prev_total_cost = round(prev_revenue * (prev_cost_ratio / 100), 2) if prev_revenue and prev_cost_ratio else None
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prev_net_profit = round(prev_revenue * (prev_net_profit_rate / 100), 2) if prev_revenue and prev_net_profit_rate else None
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prev_contribution_margin = prev_gross_profit
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prev_variable_cost = round(prev_revenue * 0.50, 2) if prev_revenue else None
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prev_fixed_cost = round(prev_total_cost - prev_variable_cost, 2) if prev_total_cost and prev_variable_cost else None
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def calc_chg(cur, prev):
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if cur is not None and prev is not None and prev != 0:
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return round((cur - prev) / prev * 100, 2)
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return None
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items = [
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{
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"name": "营业收入",
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"value": revenue,
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"prev_value": prev_revenue,
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"change_rate": calc_chg(revenue, prev_revenue),
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"ratio": 100.0,
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},
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{
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"name": "减：变动成本",
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"value": variable_cost,
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"prev_value": prev_variable_cost,
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"change_rate": calc_chg(variable_cost, prev_variable_cost),
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"ratio": round(variable_cost / revenue * 100, 2) if variable_cost and revenue else None,
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},
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{
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"name": "＝ 边际贡献",
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"value": contribution_margin,
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"prev_value": prev_contribution_margin,
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"change_rate": calc_chg(contribution_margin, prev_contribution_margin),
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"ratio": round(contribution_margin / revenue * 100, 2) if contribution_margin and revenue else None,
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"is_subtotal": True,
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},
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{
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"name": "减：固定成本",
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"value": fixed_cost,
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"prev_value": prev_fixed_cost,
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"change_rate": calc_chg(fixed_cost, prev_fixed_cost),
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"ratio": round(fixed_cost / revenue * 100, 2) if fixed_cost and revenue else None,
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},
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{
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"name": "＝ 息税前利润",
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"value": net_profit,
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"prev_value": prev_net_profit,
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"change_rate": calc_chg(net_profit, prev_net_profit),
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"ratio": round(net_profit / revenue * 100, 2) if net_profit and revenue else None,
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"is_total": True,
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},
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]
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return {
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"period": period,
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"prev_period": prev_period,
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"items": items,
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}
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# ============================================================
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# 报表2: 预算执行报告
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# ============================================================
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@router.get("/budget-execution")
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def get_budget_execution(
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period: str = Query(None, description="格式 YYYY-MM"),
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dimension: Optional[str] = Query(None),
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alert_level: Optional[str] = Query(None),
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db: Session = Depends(get_db),
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):
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"""预算执行报告 — 各KPI预算vs实际vs差异率"""
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if period is None:
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period = datetime.now().strftime("%Y-%m")
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query = db.query(KPIDefinition).filter(KPIDefinition.status == "active")
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if dimension:
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query = query.filter(KPIDefinition.dimension == dimension)
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kpis = query.order_by(KPIDefinition.dimension, KPIDefinition.kpi_code).all()
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items = []
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summary = {"total": 0, "with_budget": 0, "over_budget": 0, "normal": 0, "under_budget": 0}
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for kpi in kpis:
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dev = calc_period_deviation(db, kpi.id, period)
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if dev.get("actual_value") is None and dev.get("budget_value") is None:
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continue # 跳过完全无数据的KPI
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summary["total"] += 1
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if dev.get("deviation_rate") is not None:
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rate = dev["deviation_rate"]
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level = "red" if abs(rate) > 20 else "yellow" if abs(rate) > 10 else "normal"
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if level == "red":
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summary["over_budget"] += 1 if rate > 0 else 0
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summary["under_budget"] += 1 if rate < 0 else 0
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else:
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summary["normal"] += 1
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else:
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level = "gray"
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summary["normal"] += 1
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if dev.get("budget_value") is not None:
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summary["with_budget"] += 1
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items.append({
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"kpi_id": kpi.id,
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"kpi_code": kpi.kpi_code,
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"kpi_name": kpi.kpi_name,
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"dimension": kpi.dimension,
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"unit": kpi.unit,
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"actual_value": dev.get("actual_value"),
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"budget_value": dev.get("budget_value"),
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"deviation_amount": dev.get("deviation_amount"),
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"deviation_rate": dev.get("deviation_rate"),
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"is_over_budget": dev.get("is_over_budget"),
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"alert_level": level,
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})
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# alert_level 过滤
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if alert_level:
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items = [i for i in items if i["alert_level"] == alert_level]
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return {"period": period, "summary": summary, "items": items}
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# ============================================================
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# 报表3: KPI趋势报告
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# ============================================================
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@router.get("/kpi-trends")
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def get_kpi_trends(
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kpi_id: Optional[int] = Query(None),
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dimension: Optional[str] = Query(None),
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months: int = Query(12, ge=3, le=36),
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db: Session = Depends(get_db),
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):
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"""KPI趋势报告 — 选定KPI的历史趋势线"""
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query = db.query(KPIDefinition).filter(KPIDefinition.status == "active")
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if kpi_id:
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query = query.filter(KPIDefinition.id == kpi_id)
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if dimension:
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query = query.filter(KPIDefinition.dimension == dimension)
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kpis = query.order_by(KPIDefinition.dimension, KPIDefinition.kpi_code).all()
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results = []
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for kpi in kpis:
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values = db.query(KPIValue).filter(
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KPIValue.kpi_id == kpi.id
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).order_by(KPIValue.period.desc()).limit(months).all()
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values.reverse()
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trend = [{"period": v.period, "value": v.actual_value} for v in values]
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vals = [v.actual_value for v in values if v.actual_value is not None]
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target = kpi.target_value
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avg_val = round(sum(vals) / len(vals), 2) if vals else None
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max_val = max(vals) if vals else None
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min_val = min(vals) if vals else None
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# 趋势方向
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if len(vals) >= 2:
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first_half = sum(vals[:len(vals)//2]) / (len(vals)//2)
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second_half = sum(vals[len(vals)//2:]) / (len(vals) - len(vals)//2)
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trend_dir = "up" if second_half > first_half * 1.05 else "down" if second_half < first_half * 0.95 else "stable"
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else:
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trend_dir = "stable"
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results.append({
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"kpi_id": kpi.id,
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"kpi_code": kpi.kpi_code,
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"kpi_name": kpi.kpi_name,
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"dimension": kpi.dimension,
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"unit": kpi.unit,
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"target_value": target,
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"trend": trend,
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"trend_dir": trend_dir,
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"avg": avg_val,
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"max": max_val,
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"min": min_val,
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})
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return {"data": results}
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# ============================================================
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# 报表4: 四维度绩效评分卡
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# ============================================================
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DIM_CONFIG = {
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"finance": {"name": "财务维度", "icon": "💰", "color": "#409eff"},
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"customer": {"name": "客户维度", "icon": "🤝", "color": "#67c23a"},
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"process": {"name": "内部流程", "icon": "⚙️", "color": "#e6a23c"},
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"learning": {"name": "学习成长", "icon": "📚", "color": "#f56c6c"},
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}
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@router.get("/bsc-scorecard")
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def get_bsc_scorecard(
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map_id: Optional[int] = Query(None),
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period: Optional[str] = Query(None),
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db: Session = Depends(get_db),
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):
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"""四维度绩效评分卡 — BSC健康度"""
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if period is None:
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period = datetime.now().strftime("%Y-%m")
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# 取最新的已发布地图
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map_query = db.query(StrategicMap).filter(StrategicMap.status == "published")
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if map_id:
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map_query = map_query.filter(StrategicMap.id == map_id)
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sm = map_query.order_by(StrategicMap.updated_at.desc()).first()
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if not sm:
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# 没有已发布地图，按维度聚合KPI
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return _build_scorecard_from_kpis(db, period)
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# 从战略地图维度数据构建评分卡
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dims = sm.dimensions
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if isinstance(dims, str):
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import json
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dims = json.loads(dims)
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dimensions = []
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total_score = 0
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dim_count = 0
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for dim in dims:
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dim_key = dim.get("key", "")
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config = DIM_CONFIG.get(dim_key, {"name": dim.get("name", dim_key), "icon": "📊", "color": "#999"})
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objectives = dim.get("objectives", [])
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obj_results = []
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dim_total = 0
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dim_valid = 0
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for obj in objectives:
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kpi_codes = obj.get("kpis", [])
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kpi_scores = []
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for code in kpi_codes:
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kpi = db.query(KPIDefinition).filter(KPIDefinition.kpi_code == code).first()
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if not kpi: continue
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v = db.query(KPIValue).filter(
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KPIValue.kpi_id == kpi.id, KPIValue.period == period
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).order_by(KPIValue.id.desc()).first()
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if v and v.actual_value and kpi.target_value:
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ratio = v.actual_value / kpi.target_value
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score = min(round(ratio * 100, 1), 100)
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level = "green" if ratio >= 0.9 else "yellow" if ratio >= 0.7 else "red"
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kpi_scores.append({"code": code, "name": kpi.kpi_name, "actual": v.actual_value, "target": kpi.target_value, "score": score, "level": level})
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dim_total += score
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dim_valid += 1
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obj_results.append({
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"name": obj.get("name", ""),
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"kpi_count": len(kpi_codes),
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"kpi_with_data": dim_valid,
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"kpis": kpi_scores,
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})
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dim_score = round(dim_total / dim_valid, 1) if dim_valid > 0 else 0
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dimensions.append({
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"key": dim_key,
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"name": config["name"],
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"icon": config["icon"],
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"color": config["color"],
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"score": dim_score,
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"objectives": obj_results,
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})
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total_score += dim_score
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dim_count += 1
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overall = round(total_score / dim_count, 1) if dim_count > 0 else 0
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return {
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"period": period,
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"map_id": sm.id,
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"map_title": sm.title,
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"overall_score": overall,
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"dimensions": dimensions,
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}
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def _build_scorecard_from_kpis(db: Session, period: str) -> dict:
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"""没有战略地图时，直接按维度聚合KPI算分"""
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kpis = db.query(KPIDefinition).filter(KPIDefinition.status == "active").all()
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dims: dict = {}
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for kpi in kpis:
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dim = kpi.dimension or "other"
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if dim not in dims:
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dims[dim] = {"kpis": [], "total_score": 0, "valid": 0}
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v = db.query(KPIValue).filter(
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KPIValue.kpi_id == kpi.id, KPIValue.period == period
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).order_by(KPIValue.id.desc()).first()
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score = None
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level = "gray"
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if v and v.actual_value and kpi.target_value:
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ratio = v.actual_value / kpi.target_value
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score = min(round(ratio * 100, 1), 100)
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level = "green" if ratio >= 0.9 else "yellow" if ratio >= 0.7 else "red"
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dims[dim]["total_score"] += score
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dims[dim]["valid"] += 1
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dims[dim]["kpis"].append({
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"code": kpi.kpi_code,
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"name": kpi.kpi_name,
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"actual": v.actual_value if v else None,
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"target": kpi.target_value,
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"score": score,
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"level": level,
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})
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dimensions = []
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total_score = 0
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dim_count = 0
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for key, data in dims.items():
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config = DIM_CONFIG.get(key, {"name": key, "icon": "📊", "color": "#999"})
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dim_score = round(data["total_score"] / data["valid"], 1) if data["valid"] > 0 else 0
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dimensions.append({
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"key": key,
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"name": config["name"],
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"icon": config["icon"],
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"color": config["color"],
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"score": dim_score,
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"objectives": [{"name": "全部KPI", "kpis": data["kpis"], "kpi_count": len(data["kpis"]), "kpi_with_data": data["valid"]}],
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})
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total_score += dim_score
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dim_count += 1
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return {
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"period": period,
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"map_id": None,
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"map_title": None,
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"overall_score": round(total_score / dim_count, 1) if dim_count > 0 else 0,
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"dimensions": dimensions,
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}
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