Files
Hermes CI Fix ba8e2f112b fix: P0官方公式对齐(方案A)+反向指标判定Bug修复
1. F_AR_DAYS: 360→365官方口径, 历史值重算(6月75.6/7月116.5), 阈值等比调整(绿76/红91)
2. F_ROI改名: 总资产报酬率(ROA), 说明与官方ROI口径差异
3. 🔴反向指标Bug修复: kpis.py与dashboard.py的REVERSE_INDICATORS不一致
   - 移除错误: F_QUICK_RATIO(速动比率越高越好)/F_INTEREST_COVER/P_QUALITY_RATE
   - 补充缺失: F_AR_DAYS/F_REBATE_RATE/F_FACTORY_REBATE_RATE/F_COST_CONTROL_RATE/F_INV_DAYS
   - 修复前F_AR_DAYS判定反了(116.5天显示绿, 75.6天显示黄)
4. 清理过时预警(id=6/269旧口径)
2026-08-26 21:40:00 +08:00

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"""驾驶舱 API v2 — 支持时间区间"""
from fastapi import APIRouter, Depends, Query, Request, HTTPException
from sqlalchemy.orm import Session
from sqlalchemy import func, or_
from datetime import datetime, timedelta
from typing import Optional
from app.database import get_db
from app.auth_middleware import require_auth, require_role
from app.deps import get_entity_id
from app.models import KPIDefinition, KPIValue, KPIAlert, User
from app.utils.cache import get as cache_get, set as cache_set
import json
import logging
logger = logging.getLogger("cma.dashboard")
router = APIRouter(prefix="/api/cma/dashboard", tags=["驾驶舱"],
dependencies=[Depends(require_role("ceo", "finance", "business", "it"))],
)
def parse_period(period_type: str, start_date: str = None, end_date: str = None):
"""解析时间区间"""
today = datetime.now()
if period_type == "month":
start = today.replace(day=1, hour=0, minute=0, second=0, microsecond=0)
end = today
elif period_type == "quarter":
q = (today.month - 1) // 3
start = today.replace(month=q*3+1, day=1, hour=0, minute=0, second=0, microsecond=0)
end = today
elif period_type == "year":
start = today.replace(month=1, day=1, hour=0, minute=0, second=0, microsecond=0)
end = today
elif period_type == "custom" and start_date and end_date:
start = datetime.strptime(start_date, "%Y-%m-%d")
end = datetime.strptime(end_date, "%Y-%m-%d") + timedelta(days=1)
else:
start = today.replace(day=1, hour=0, minute=0, second=0, microsecond=0)
end = today
return start, end
def period_prefix(period_type: str):
"""生成SQL期间前缀匹配"""
if period_type == "month":
return datetime.now().strftime("%Y-%m")
elif period_type == "quarter":
now = datetime.now()
q = (now.month - 1) // 3
months = [f"{now.year}-{m:02d}" for m in range(q*3+1, q*3+4)]
return months
elif period_type == "year":
return str(datetime.now().year)
return None
def kpi_target_by_frequency(k):
"""按考核频率返回对应周期的目标值(多粒度改造)
monthly/weekly -> target_monthly; quarterly/half_year -> target_quarterly; yearly -> target_yearly
兼容: 对应列无值时回退 target_value
"""
freq = (k.frequency or "monthly").lower()
if freq in ("monthly", "weekly"):
val = getattr(k, "target_monthly", None)
elif freq in ("quarterly", "half_year"):
val = getattr(k, "target_quarterly", None)
elif freq == "yearly":
val = getattr(k, "target_yearly", None)
else:
val = None
if val is None:
val = k.target_value
return val
@router.get("/summary")
def get_dashboard_summary(role: str = Query("ceo"), period: str = Query("month"),
db: Session = Depends(get_db), entity_id: int = Depends(get_entity_id)):
cache_key = f"summary:{role}:{period}:{entity_id}"
cached = cache_get("dashboard", cache_key)
if cached:
return cached
kpi_total = db.query(func.count(KPIDefinition.id)).filter(
KPIDefinition.status == "active", KPIDefinition.entity_id == entity_id).scalar()
alert_count = db.query(func.count(KPIAlert.id)).filter(KPIAlert.status == "pending").scalar()
dims = db.query(KPIDefinition.dimension, func.count(KPIDefinition.id)).filter(
KPIDefinition.status == "active", KPIDefinition.entity_id == entity_id
).group_by(KPIDefinition.dimension).all()
# 读取最近一次同步状态(从日志文件最后一行)
sync_status = {"last_sync": None, "status": "unknown", "detail": ""}
try:
with open("/var/log/cma-daily-sync.log", "r") as f:
lines = f.readlines()
# 从最后往前找包含 "完成" 或 "失败" 的行
for line in reversed(lines[-50:]):
if "全部完成" in line:
sync_status["status"] = "success"
sync_status["last_sync"] = line.strip()
break
elif "失败" in line or "ERROR" in line:
sync_status["status"] = "failed"
sync_status["last_sync"] = line.strip()
break
else:
# 没找到完成/失败标记,取最后一行
sync_status["last_sync"] = lines[-1].strip() if lines else None
except Exception as e:
sync_status["detail"] = str(e)
result = {
"kpi_total": kpi_total or 0, "alert_count": alert_count or 0,
"dimension_stats": [{"dimension": d[0], "count": d[1]} for d in dims],
"sync_status": sync_status,
}
cache_set("dashboard", cache_key, result, ttl_seconds=30)
return result
@router.get("/kpis")
def get_dashboard_kpis(role: str = Query("ceo"), period: str = Query("month"),
start_date: str = Query(None), end_date: str = Query(None),
db: Session = Depends(get_db), entity_id: int = Depends(get_entity_id)):
start, end = parse_period(period, start_date, end_date)
period_str = start.strftime("%Y-%m")
kpis = db.query(KPIDefinition).filter(
KPIDefinition.status == "active",
KPIDefinition.entity_id == entity_id
).all()
result = []
for k in kpis:
base_query = db.query(KPIValue).filter(KPIValue.kpi_id == k.id)
if period == "month":
latest = base_query.filter(KPIValue.period == period_str).order_by(KPIValue.id.desc()).first()
elif period == "quarter":
months = period_prefix("quarter")
values = base_query.filter(KPIValue.period.in_(months)).all()
latest_val = sum(v.actual_value for v in values if v.actual_value) if values else None
latest = type('obj', (object,), {"actual_value": latest_val, "period": f"{months[0]}~{months[-1]}"})() if latest_val else None
elif period == "year":
values = base_query.filter(KPIValue.period.like(f"{period_str[:4]}%")).all()
latest_val = sum(v.actual_value for v in values if v.actual_value) if values else None
latest = type('obj', (object,), {"actual_value": latest_val, "period": period_str[:4]})() if latest_val else None
elif period == "custom" and start_date and end_date:
periods = []
d = start
while d <= end:
periods.append(d.strftime("%Y-%m"))
d += timedelta(days=32)
d = d.replace(day=1)
values = base_query.filter(KPIValue.period.in_(set(periods))).all()
latest_val = sum(v.actual_value for v in values if v.actual_value) if values else None
latest = type('obj', (object,), {"actual_value": latest_val, "period": f"{start_date}~{end_date}"})() if latest_val else None
else:
latest = base_query.order_by(KPIValue.period.desc()).first()
alert = db.query(KPIAlert).filter(
KPIAlert.kpi_id == k.id,
KPIAlert.status == "pending",
).order_by(KPIAlert.id.desc()).first()
result.append({
"id": k.id, "kpi_code": k.kpi_code, "kpi_name": k.kpi_name,
"dimension": k.dimension, "unit": k.unit, "target_value": k.target_value,
"target_monthly": k.target_monthly, "target_quarterly": k.target_quarterly, "target_yearly": k.target_yearly,
"actual_value": latest.actual_value if latest else None,
"period": latest.period if latest else None,
"alert_level": alert.alert_level if alert else "none",
"alert_message": alert.alert_message if alert else None,
"frequency": k.frequency,
"responsible_dept": k.responsible_dept,
})
return {"data": result, "period": period, "range": {"start": start.strftime("%Y-%m-%d"), "end": end.strftime("%Y-%m-%d")}}
@router.get("/my-kpis")
def get_my_kpis(
current_user: User = Depends(require_auth),
period: str = Query("month"),
db: Session = Depends(get_db),
):
"""获取当前用户负责的KPI
- business角色:只看自己负责的KPI
- 其他角色:看所有有预警的KPI
"""
role = current_user.role
username = current_user.username
name = current_user.name
period_str = datetime.now().strftime("%Y-%m")
kpis = db.query(KPIDefinition).filter(KPIDefinition.status == "active").all()
result = []
for k in kpis:
# business角色筛选
if role == "business":
responsible = (k.responsible_user or "").strip()
if responsible and responsible != username and responsible != name:
continue
latest = db.query(KPIValue).filter(
KPIValue.kpi_id == k.id,
KPIValue.period == period_str,
).order_by(KPIValue.id.desc()).first()
alert = db.query(KPIAlert).filter(
KPIAlert.kpi_id == k.id,
KPIAlert.status == "pending",
).order_by(KPIAlert.id.desc()).first()
trend_values = db.query(KPIValue).filter(
KPIValue.kpi_id == k.id,
).order_by(KPIValue.period.desc()).limit(6).all()
trend = [{"period": v.period, "value": v.actual_value} for v in reversed(trend_values)]
result.append({
"id": k.id, "kpi_code": k.kpi_code, "kpi_name": k.kpi_name,
"dimension": k.dimension, "unit": k.unit,
"target_value": k.target_value,
"target_monthly": k.target_monthly, "target_quarterly": k.target_quarterly, "target_yearly": k.target_yearly,
"actual_value": latest.actual_value if latest else None,
"period": latest.period if latest else period_str,
"alert_level": alert.alert_level if alert else "none",
"alert_message": alert.alert_message if alert else None,
"alert_id": alert.id if alert else None,
"frequency": k.frequency,
"responsible_dept": k.responsible_dept,
"responsible_user": k.responsible_user,
"trend": trend,
"threshold_green": k.threshold_green,
"threshold_yellow": k.threshold_yellow,
"threshold_red": k.threshold_red,
})
return {"data": result, "user_role": role, "user_name": name, "period": period_str}
@router.get("/finance-analysis")
def get_finance_analysis(
current_user: User = Depends(require_auth),
period: str = Query("month"),
db: Session = Depends(get_db),
entity_id: int = Depends(get_entity_id),
):
"""财务工作台分析数据"""
period_str = datetime.now().strftime("%Y-%m")
finance_kpis = db.query(KPIDefinition).filter(
KPIDefinition.status == "active",
KPIDefinition.dimension == "finance",
KPIDefinition.entity_id == entity_id,
).all()
kpi_data = []
for k in finance_kpis:
latest = db.query(KPIValue).filter(
KPIValue.kpi_id == k.id,
KPIValue.period == period_str,
).order_by(KPIValue.id.desc()).first()
trend_values = db.query(KPIValue).filter(
KPIValue.kpi_id == k.id,
).order_by(KPIValue.period.desc()).limit(6).all()
trend = [{"period": v.period, "value": v.actual_value} for v in reversed(trend_values)]
alert = db.query(KPIAlert).filter(
KPIAlert.kpi_id == k.id,
KPIAlert.status == "pending",
).order_by(KPIAlert.id.desc()).first()
kpi_data.append({
"id": k.id, "kpi_code": k.kpi_code, "kpi_name": k.kpi_name,
"unit": k.unit, "target_value": k.target_value,
"target_monthly": k.target_monthly, "target_quarterly": k.target_quarterly, "target_yearly": k.target_yearly,
"actual_value": latest.actual_value if latest else None,
"threshold_green": k.threshold_green,
"threshold_yellow": k.threshold_yellow,
"threshold_red": k.threshold_red,
"trend": trend,
"alert_level": alert.alert_level if alert else "none",
"frequency": k.frequency,
})
total_sales = next((k for k in kpi_data if k["kpi_code"] == "SALES_TOTAL"), None)
gross_profit = next((k for k in kpi_data if k["kpi_code"] == "SALES_PROFIT_RATE"), None)
cost_control = next((k for k in kpi_data if k["kpi_code"] == "COST_CONTROL_RATE"), None)
receivable = next((k for k in kpi_data if k["kpi_code"] == "RECEIVABLE_TURNOVER"), None)
return {
"period": period_str,
"kpis": kpi_data,
"summary": {
"total_sales": total_sales["actual_value"] if total_sales else None,
"gross_profit_rate": gross_profit["actual_value"] if gross_profit else None,
"cost_control_rate": cost_control["actual_value"] if cost_control else None,
"receivable_turnover": receivable["actual_value"] if receivable else None,
}
}
@router.get("/predict")
def predict_kpis(db: Session = Depends(get_db), entity_id: int = Depends(get_entity_id)):
"""基于历史趋势预测下月KPI值(简单线性回归)"""
from datetime import datetime, timedelta
period_str = datetime.now().strftime("%Y-%m")
next_month = int(period_str[5:7]) + 1
next_year = int(period_str[:4])
if next_month > 12:
next_month = 1
next_year += 1
next_period = f"{next_year}-{next_month:02d}"
kpis = db.query(KPIDefinition).filter(
KPIDefinition.status == "active",
KPIDefinition.entity_id == entity_id
).all()
predictions = []
for k in kpis:
values = db.query(KPIValue).filter(
KPIValue.kpi_id == k.id,
).order_by(KPIValue.period.asc()).all()
# 需要至少3个数据点才能做预测
if len(values) < 3:
continue
# 简单线性回归: y = a + bx
points = [(i, v.actual_value) for i, v in enumerate(values) if v.actual_value is not None]
if len(points) < 3:
continue
n = len(points)
sum_x = sum(p[0] for p in points)
sum_y = sum(p[1] for p in points)
sum_xy = sum(p[0] * p[1] for p in points)
sum_xx = sum(p[0] ** 2 for p in points)
# 斜率 b = (n*sum_xy - sum_x*sum_y) / (n*sum_xx - sum_x*sum_x)
denom = n * sum_xx - sum_x * sum_x
if denom == 0:
continue
b = (n * sum_xy - sum_x * sum_y) / denom
a = (sum_y - b * sum_x) / n
# 预测下个月(x = n,因为最后一个索引是 n-1)
predicted_value = a + b * n
# 检查预测值是否触发阈值
alert_level = "none"
if k.threshold_red:
op = k.threshold_red[:2] if k.threshold_red[1] in "=<>" else k.threshold_red[0]
val = float(k.threshold_red.replace(op, "").strip())
if (op in (">=", ">") and predicted_value >= val) or (op in ("<=", "<") and predicted_value <= val):
alert_level = "red"
if alert_level == "none" and k.threshold_yellow:
op = k.threshold_yellow[:2] if k.threshold_yellow[1] in "=<>" else k.threshold_yellow[0]
val = float(k.threshold_yellow.replace(op, "").strip())
if (op in (">=", ">") and predicted_value >= val) or (op in ("<=", "<") and predicted_value <= val):
alert_level = "yellow"
predictions.append({
"kpi_id": k.id,
"kpi_code": k.kpi_code,
"kpi_name": k.kpi_name,
"target_value": k.target_value,
"last_value": points[-1][1] if points else None,
"predicted_value": round(predicted_value, 2),
"predicted_period": next_period,
"alert_level": alert_level,
"trend": "up" if b > 0 else ("down" if b < 0 else "stable"),
"confidence": "high" if len(points) >= 6 else ("medium" if len(points) >= 4 else "low"),
"data_points": len(points),
})
return {
"current_period": period_str,
"next_period": next_period,
"predictions": predictions,
"kpi_count": len(kpis),
"predictable_count": len(predictions),
}
# ── 个人工作台 ──────────────────────────────
@router.get("/my-dashboard")
def my_dashboard(
current_user: User = Depends(require_auth),
db: Session = Depends(get_db),
entity_id: int = Depends(get_entity_id),
):
"""个人工作台:返回我的KPI、改善行动、待办提醒(账套隔离: 按token企业过滤)"""
username = current_user.username
name = current_user.name
role = current_user.role
# 角色预设KPI编码
ROLE_PRESET_KPIS = {
"ceo": ["F_REVENUE", "F_NET_PROFIT", "F_COST_RATIO", "C_REBATE_RATE", "P_DELIVERY", "F_FCF"],
"finance": ["F_REVENUE", "F_NET_PROFIT", "F_COST_RATIO", "F_OP_CFLOW", "F_ROE"],
"business": ["C_REBATE_RATE", "C_NEW_CLIENTS", "F_REVENUE"],
"it": [],
}
preset_codes = ROLE_PRESET_KPIS.get(role, [])
# 1. 我的KPIresponsible_user匹配用户名或姓名)+ 角色预设(均按企业隔离)
assigned_kpis = db.query(KPIDefinition).filter(
or_(
KPIDefinition.responsible_user == username,
KPIDefinition.responsible_user == name,
),
KPIDefinition.status == "active",
KPIDefinition.entity_id == entity_id,
).all()
assigned_ids = {k.id for k in assigned_kpis}
# 补充角色预设KPI(去重,按企业隔离)
preset_kpis = []
if preset_codes:
q = db.query(KPIDefinition).filter(
KPIDefinition.kpi_code.in_(preset_codes),
KPIDefinition.status == "active",
KPIDefinition.entity_id == entity_id,
)
if assigned_ids:
q = q.filter(~KPIDefinition.id.in_(assigned_ids))
preset_kpis = q.all()
all_kpis = assigned_kpis + preset_kpis
kpi_list = []
for k in all_kpis:
latest_v = db.query(KPIValue).filter(
KPIValue.kpi_id == k.id
).order_by(KPIValue.calculated_at.desc()).first()
actual = latest_v.actual_value if latest_v else None
target = kpi_target_by_frequency(k)
level = "gray"
if actual is not None and target:
# 反向指标(越低越好):费用率/渠补率/应收天数/返利率/成本率/存货天数
REVERSE_INDICATORS = {
"F_COST_RATIO", "C_REBATE_RATE", "F_AR_DAYS",
"F_REBATE_RATE", "F_FACTORY_REBATE_RATE", "F_COST_CONTROL_RATE",
"F_INV_DAYS", "F_DEBT_RATIO", "P_BUG_RATE", "P_REWORK_PCT",
}
if k.kpi_code in REVERSE_INDICATORS:
# 反向:实际≤目标=绿;实际≤目标*1.1=黄;否则红
level = "green" if actual <= target else (
"yellow" if actual <= target * 1.1 else "red")
else:
ratio = actual / target
level = "green" if ratio >= 0.9 else ("yellow" if ratio >= 0.7 else "red")
kpi_list.append({
"id": k.id,
"kpi_code": k.kpi_code,
"kpi_name": k.kpi_name,
"dimension": k.dimension,
"category": k.category,
"target_value": target,
"target_monthly": k.target_monthly,
"target_quarterly": k.target_quarterly,
"target_yearly": k.target_yearly,
"frequency": k.frequency,
"actual_value": actual,
"unit": k.unit,
"level": level,
"period": latest_v.period if latest_v else None,
})
# 2. 我的改善行动(assignee匹配;CEO/管理员看全部)
from app.models import ActionPlan
if current_user.role == "ceo":
# CEO/管理员查看全部行动方案(2026-08-26修复: 原逻辑只按assignee过滤导致工作台显示空)
my_plans = db.query(ActionPlan).order_by(ActionPlan.updated_at.desc()).all()
else:
my_plans = db.query(ActionPlan).filter(
or_(
ActionPlan.assignee == username,
ActionPlan.assignee == name,
)
).order_by(ActionPlan.updated_at.desc()).all()
plan_list = []
for p in my_plans:
overdue = False
if p.due_date and p.status not in ("completed", "cancelled"):
overdue = p.due_date < datetime.now()
kpi_name = ""
kpi = db.query(KPIDefinition).filter(KPIDefinition.id == p.kpi_id).first()
if kpi:
kpi_name = kpi.kpi_name
plan_list.append({
"id": p.id,
"kpi_id": p.kpi_id,
"kpi_name": kpi_name,
"title": p.title,
"assignee": p.assignee,
"priority": p.priority,
"status": p.status,
"progress": p.progress or 0,
"due_date": p.due_date.isoformat() if p.due_date else None,
"overdue": overdue,
"created_at": p.created_at.isoformat() if p.created_at else None,
})
# 3. 待办提醒
reminders = []
# 逾期行动
for p in plan_list:
if p["overdue"]:
reminders.append({
"type": "overdue_plan",
"severity": "danger",
"message": f"你负责的「{p['title']}」已逾期",
"related_id": p["id"],
"related_type": "action_plan",
})
# 红色预警KPI
for k in kpi_list:
if k["level"] == "red":
reminders.append({
"type": "red_kpi",
"severity": "danger",
"message": f"你负责的KPI「{k['kpi_name']}」处于红色预警",
"related_id": k["id"],
"related_type": "kpi",
})
# 黄色预警KPI
for k in kpi_list:
if k["level"] == "yellow":
reminders.append({
"type": "yellow_kpi",
"severity": "warning",
"message": f"你负责的KPI「{k['kpi_name']}」处于黄色预警",
"related_id": k["id"],
"related_type": "kpi",
})
return {
"kpis": kpi_list,
"action_plans": plan_list,
"reminders": reminders,
}