Hermes CI Fix
778a5d9c79
- my_dashboard的level判断原为actual/target比例法(≥0.9=green) - 反向指标(费用率24.9%/目标20%)被误判为green，实际应red - 新增REVERSE_INDICATORS集合：F_COST_RATIO/C_REBATE_RATE/F_AR_DAYS/F_REBATE_RATE/F_FACTORY_REBATE_RATE/F_COST_CONTROL_RATE - 反向指标逻辑：实际≤目标=绿，≤目标*1.1=黄，否则红
520 lines
20 KiB
Python
520 lines
20 KiB
Python
"""驾驶舱 API v2 — 支持时间区间"""
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from fastapi import APIRouter, Depends, Query, Request, HTTPException
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from sqlalchemy.orm import Session
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from sqlalchemy import func, or_
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from datetime import datetime, timedelta
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from typing import Optional
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from app.database import get_db
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from app.auth_middleware import require_auth, require_role
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from app.deps import get_entity_id
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from app.models import KPIDefinition, KPIValue, KPIAlert, User
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from app.utils.cache import get as cache_get, set as cache_set
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import json
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import logging
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logger = logging.getLogger("cma.dashboard")
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router = APIRouter(prefix="/api/cma/dashboard", tags=["驾驶舱"],
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dependencies=[Depends(require_role("ceo", "finance", "business", "it"))],
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)
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def parse_period(period_type: str, start_date: str = None, end_date: str = None):
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"""解析时间区间"""
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today = datetime.now()
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if period_type == "month":
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start = today.replace(day=1, hour=0, minute=0, second=0, microsecond=0)
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end = today
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elif period_type == "quarter":
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q = (today.month - 1) // 3
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start = today.replace(month=q*3+1, day=1, hour=0, minute=0, second=0, microsecond=0)
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end = today
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elif period_type == "year":
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start = today.replace(month=1, day=1, hour=0, minute=0, second=0, microsecond=0)
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end = today
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elif period_type == "custom" and start_date and end_date:
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start = datetime.strptime(start_date, "%Y-%m-%d")
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end = datetime.strptime(end_date, "%Y-%m-%d") + timedelta(days=1)
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else:
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start = today.replace(day=1, hour=0, minute=0, second=0, microsecond=0)
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end = today
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return start, end
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def period_prefix(period_type: str):
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"""生成SQL期间前缀匹配"""
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if period_type == "month":
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return datetime.now().strftime("%Y-%m")
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elif period_type == "quarter":
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now = datetime.now()
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q = (now.month - 1) // 3
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months = [f"{now.year}-{m:02d}" for m in range(q*3+1, q*3+4)]
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return months
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elif period_type == "year":
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return str(datetime.now().year)
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return None
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@router.get("/summary")
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def get_dashboard_summary(role: str = Query("ceo"), period: str = Query("month"),
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db: Session = Depends(get_db), entity_id: int = Depends(get_entity_id)):
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cache_key = f"summary:{role}:{period}:{entity_id}"
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cached = cache_get("dashboard", cache_key)
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if cached:
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return cached
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kpi_total = db.query(func.count(KPIDefinition.id)).filter(
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KPIDefinition.status == "active", KPIDefinition.entity_id == entity_id).scalar()
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alert_count = db.query(func.count(KPIAlert.id)).filter(KPIAlert.status == "pending").scalar()
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dims = db.query(KPIDefinition.dimension, func.count(KPIDefinition.id)).filter(
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KPIDefinition.status == "active", KPIDefinition.entity_id == entity_id
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).group_by(KPIDefinition.dimension).all()
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# 读取最近一次同步状态（从日志文件最后一行）
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sync_status = {"last_sync": None, "status": "unknown", "detail": ""}
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try:
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with open("/var/log/cma-daily-sync.log", "r") as f:
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lines = f.readlines()
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# 从最后往前找包含 "完成" 或 "失败" 的行
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for line in reversed(lines[-50:]):
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if "全部完成" in line:
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sync_status["status"] = "success"
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sync_status["last_sync"] = line.strip()
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break
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elif "失败" in line or "ERROR" in line:
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sync_status["status"] = "failed"
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sync_status["last_sync"] = line.strip()
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break
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else:
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# 没找到完成/失败标记，取最后一行
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sync_status["last_sync"] = lines[-1].strip() if lines else None
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except Exception as e:
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sync_status["detail"] = str(e)
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result = {
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"kpi_total": kpi_total or 0, "alert_count": alert_count or 0,
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"dimension_stats": [{"dimension": d[0], "count": d[1]} for d in dims],
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"sync_status": sync_status,
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}
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cache_set("dashboard", cache_key, result, ttl_seconds=30)
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return result
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@router.get("/kpis")
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def get_dashboard_kpis(role: str = Query("ceo"), period: str = Query("month"),
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start_date: str = Query(None), end_date: str = Query(None),
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db: Session = Depends(get_db), entity_id: int = Depends(get_entity_id)):
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start, end = parse_period(period, start_date, end_date)
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period_str = start.strftime("%Y-%m")
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kpis = db.query(KPIDefinition).filter(
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KPIDefinition.status == "active",
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KPIDefinition.entity_id == entity_id
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).all()
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result = []
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for k in kpis:
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base_query = db.query(KPIValue).filter(KPIValue.kpi_id == k.id)
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if period == "month":
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latest = base_query.filter(KPIValue.period == period_str).order_by(KPIValue.id.desc()).first()
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elif period == "quarter":
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months = period_prefix("quarter")
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values = base_query.filter(KPIValue.period.in_(months)).all()
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latest_val = sum(v.actual_value for v in values if v.actual_value) if values else None
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latest = type('obj', (object,), {"actual_value": latest_val, "period": f"{months[0]}~{months[-1]}"})() if latest_val else None
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elif period == "year":
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values = base_query.filter(KPIValue.period.like(f"{period_str[:4]}%")).all()
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latest_val = sum(v.actual_value for v in values if v.actual_value) if values else None
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latest = type('obj', (object,), {"actual_value": latest_val, "period": period_str[:4]})() if latest_val else None
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elif period == "custom" and start_date and end_date:
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periods = []
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d = start
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while d <= end:
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periods.append(d.strftime("%Y-%m"))
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d += timedelta(days=32)
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d = d.replace(day=1)
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values = base_query.filter(KPIValue.period.in_(set(periods))).all()
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latest_val = sum(v.actual_value for v in values if v.actual_value) if values else None
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latest = type('obj', (object,), {"actual_value": latest_val, "period": f"{start_date}~{end_date}"})() if latest_val else None
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else:
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latest = base_query.order_by(KPIValue.period.desc()).first()
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alert = db.query(KPIAlert).filter(
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KPIAlert.kpi_id == k.id,
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KPIAlert.status == "pending",
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).order_by(KPIAlert.id.desc()).first()
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result.append({
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"id": k.id, "kpi_code": k.kpi_code, "kpi_name": k.kpi_name,
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"dimension": k.dimension, "unit": k.unit, "target_value": k.target_value,
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"actual_value": latest.actual_value if latest else None,
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"period": latest.period if latest else None,
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"alert_level": alert.alert_level if alert else "none",
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"alert_message": alert.alert_message if alert else None,
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"frequency": k.frequency,
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"responsible_dept": k.responsible_dept,
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})
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return {"data": result, "period": period, "range": {"start": start.strftime("%Y-%m-%d"), "end": end.strftime("%Y-%m-%d")}}
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@router.get("/my-kpis")
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def get_my_kpis(
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current_user: User = Depends(require_auth),
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period: str = Query("month"),
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db: Session = Depends(get_db),
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):
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"""获取当前用户负责的KPI
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- business角色：只看自己负责的KPI
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- 其他角色：看所有有预警的KPI
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"""
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role = current_user.role
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username = current_user.username
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name = current_user.name
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period_str = datetime.now().strftime("%Y-%m")
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kpis = db.query(KPIDefinition).filter(KPIDefinition.status == "active").all()
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result = []
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for k in kpis:
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# business角色筛选
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if role == "business":
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responsible = (k.responsible_user or "").strip()
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if responsible and responsible != username and responsible != name:
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continue
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latest = db.query(KPIValue).filter(
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KPIValue.kpi_id == k.id,
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KPIValue.period == period_str,
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).order_by(KPIValue.id.desc()).first()
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alert = db.query(KPIAlert).filter(
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KPIAlert.kpi_id == k.id,
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KPIAlert.status == "pending",
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).order_by(KPIAlert.id.desc()).first()
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trend_values = db.query(KPIValue).filter(
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KPIValue.kpi_id == k.id,
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).order_by(KPIValue.period.desc()).limit(6).all()
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trend = [{"period": v.period, "value": v.actual_value} for v in reversed(trend_values)]
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result.append({
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"id": k.id, "kpi_code": k.kpi_code, "kpi_name": k.kpi_name,
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"dimension": k.dimension, "unit": k.unit,
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"target_value": k.target_value,
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"actual_value": latest.actual_value if latest else None,
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"period": latest.period if latest else period_str,
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"alert_level": alert.alert_level if alert else "none",
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"alert_message": alert.alert_message if alert else None,
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"alert_id": alert.id if alert else None,
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"frequency": k.frequency,
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"responsible_dept": k.responsible_dept,
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"responsible_user": k.responsible_user,
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"trend": trend,
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"threshold_green": k.threshold_green,
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"threshold_yellow": k.threshold_yellow,
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"threshold_red": k.threshold_red,
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})
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return {"data": result, "user_role": role, "user_name": name, "period": period_str}
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@router.get("/finance-analysis")
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def get_finance_analysis(
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current_user: User = Depends(require_auth),
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period: str = Query("month"),
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db: Session = Depends(get_db),
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entity_id: int = Depends(get_entity_id),
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):
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"""财务工作台分析数据"""
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period_str = datetime.now().strftime("%Y-%m")
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finance_kpis = db.query(KPIDefinition).filter(
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KPIDefinition.status == "active",
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KPIDefinition.dimension == "finance",
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KPIDefinition.entity_id == entity_id,
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).all()
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kpi_data = []
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for k in finance_kpis:
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latest = db.query(KPIValue).filter(
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KPIValue.kpi_id == k.id,
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KPIValue.period == period_str,
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).order_by(KPIValue.id.desc()).first()
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trend_values = db.query(KPIValue).filter(
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KPIValue.kpi_id == k.id,
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).order_by(KPIValue.period.desc()).limit(6).all()
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trend = [{"period": v.period, "value": v.actual_value} for v in reversed(trend_values)]
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alert = db.query(KPIAlert).filter(
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KPIAlert.kpi_id == k.id,
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KPIAlert.status == "pending",
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).order_by(KPIAlert.id.desc()).first()
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kpi_data.append({
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"id": k.id, "kpi_code": k.kpi_code, "kpi_name": k.kpi_name,
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"unit": k.unit, "target_value": k.target_value,
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"actual_value": latest.actual_value if latest else None,
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"threshold_green": k.threshold_green,
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"threshold_yellow": k.threshold_yellow,
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"threshold_red": k.threshold_red,
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"trend": trend,
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"alert_level": alert.alert_level if alert else "none",
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"frequency": k.frequency,
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})
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total_sales = next((k for k in kpi_data if k["kpi_code"] == "SALES_TOTAL"), None)
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gross_profit = next((k for k in kpi_data if k["kpi_code"] == "SALES_PROFIT_RATE"), None)
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cost_control = next((k for k in kpi_data if k["kpi_code"] == "COST_CONTROL_RATE"), None)
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receivable = next((k for k in kpi_data if k["kpi_code"] == "RECEIVABLE_TURNOVER"), None)
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return {
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"period": period_str,
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"kpis": kpi_data,
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"summary": {
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"total_sales": total_sales["actual_value"] if total_sales else None,
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"gross_profit_rate": gross_profit["actual_value"] if gross_profit else None,
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"cost_control_rate": cost_control["actual_value"] if cost_control else None,
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"receivable_turnover": receivable["actual_value"] if receivable else None,
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}
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}
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@router.get("/predict")
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def predict_kpis(db: Session = Depends(get_db), entity_id: int = Depends(get_entity_id)):
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"""基于历史趋势预测下月KPI值（简单线性回归）"""
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from datetime import datetime, timedelta
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period_str = datetime.now().strftime("%Y-%m")
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next_month = int(period_str[5:7]) + 1
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next_year = int(period_str[:4])
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if next_month > 12:
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next_month = 1
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next_year += 1
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next_period = f"{next_year}-{next_month:02d}"
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kpis = db.query(KPIDefinition).filter(
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KPIDefinition.status == "active",
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KPIDefinition.entity_id == entity_id
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).all()
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predictions = []
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for k in kpis:
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values = db.query(KPIValue).filter(
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KPIValue.kpi_id == k.id,
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).order_by(KPIValue.period.asc()).all()
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# 需要至少3个数据点才能做预测
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if len(values) < 3:
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continue
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# 简单线性回归: y = a + bx
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points = [(i, v.actual_value) for i, v in enumerate(values) if v.actual_value is not None]
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if len(points) < 3:
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continue
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n = len(points)
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sum_x = sum(p[0] for p in points)
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sum_y = sum(p[1] for p in points)
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sum_xy = sum(p[0] * p[1] for p in points)
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sum_xx = sum(p[0] ** 2 for p in points)
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# 斜率 b = (n*sum_xy - sum_x*sum_y) / (n*sum_xx - sum_x*sum_x)
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denom = n * sum_xx - sum_x * sum_x
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if denom == 0:
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continue
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b = (n * sum_xy - sum_x * sum_y) / denom
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a = (sum_y - b * sum_x) / n
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# 预测下个月（x = n，因为最后一个索引是 n-1）
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predicted_value = a + b * n
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# 检查预测值是否触发阈值
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alert_level = "none"
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if k.threshold_red:
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op = k.threshold_red[:2] if k.threshold_red[1] in "=<>" else k.threshold_red[0]
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val = float(k.threshold_red.replace(op, "").strip())
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if (op in (">=", ">") and predicted_value >= val) or (op in ("<=", "<") and predicted_value <= val):
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alert_level = "red"
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if alert_level == "none" and k.threshold_yellow:
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op = k.threshold_yellow[:2] if k.threshold_yellow[1] in "=<>" else k.threshold_yellow[0]
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val = float(k.threshold_yellow.replace(op, "").strip())
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if (op in (">=", ">") and predicted_value >= val) or (op in ("<=", "<") and predicted_value <= val):
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alert_level = "yellow"
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predictions.append({
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"kpi_id": k.id,
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"kpi_code": k.kpi_code,
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"kpi_name": k.kpi_name,
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"target_value": k.target_value,
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"last_value": points[-1][1] if points else None,
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"predicted_value": round(predicted_value, 2),
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"predicted_period": next_period,
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"alert_level": alert_level,
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"trend": "up" if b > 0 else ("down" if b < 0 else "stable"),
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"confidence": "high" if len(points) >= 6 else ("medium" if len(points) >= 4 else "low"),
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"data_points": len(points),
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})
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return {
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"current_period": period_str,
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"next_period": next_period,
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"predictions": predictions,
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"kpi_count": len(kpis),
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"predictable_count": len(predictions),
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}
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# ── 个人工作台 ──────────────────────────────
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@router.get("/my-dashboard")
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def my_dashboard(
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current_user: User = Depends(require_auth),
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db: Session = Depends(get_db),
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):
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"""个人工作台：返回我的KPI、改善行动、待办提醒"""
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username = current_user.username
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name = current_user.name
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role = current_user.role
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# 角色预设KPI编码
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ROLE_PRESET_KPIS = {
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"ceo": ["F_REVENUE", "F_NET_PROFIT", "F_COST_RATIO", "C_REBATE_RATE", "P_DELIVERY", "F_FCF"],
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"finance": ["F_REVENUE", "F_NET_PROFIT", "F_COST_RATIO", "F_OP_CFLOW", "F_ROE"],
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"business": ["C_REBATE_RATE", "C_NEW_CLIENTS", "F_REVENUE"],
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"it": [],
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}
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preset_codes = ROLE_PRESET_KPIS.get(role, [])
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# 1. 我的KPI（responsible_user匹配用户名或姓名）+ 角色预设
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assigned_kpis = db.query(KPIDefinition).filter(
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or_(
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KPIDefinition.responsible_user == username,
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KPIDefinition.responsible_user == name,
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),
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KPIDefinition.status == "active",
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).all()
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assigned_ids = {k.id for k in assigned_kpis}
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# 补充角色预设KPI（去重）
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preset_kpis = []
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if preset_codes:
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q = db.query(KPIDefinition).filter(
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KPIDefinition.kpi_code.in_(preset_codes),
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KPIDefinition.status == "active",
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)
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if assigned_ids:
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q = q.filter(~KPIDefinition.id.in_(assigned_ids))
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preset_kpis = q.all()
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|
||
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 = k.target_value
|
||
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
|
||
REVERSE_INDICATORS = {
|
||
"F_COST_RATIO", "C_REBATE_RATE", "F_AR_DAYS",
|
||
"F_REBATE_RATE", "F_FACTORY_REBATE_RATE", "F_COST_CONTROL_RATE",
|
||
}
|
||
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,
|
||
"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）
|
||
from app.models import ActionPlan
|
||
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,
|
||
}
|