feat: 数据治理 — 入库约束+元数据卡片+编码清洗+审计看板

backend/app/api/alert_rules.py

@@ -260,7 +260,7 @@ def run_all_alert_checks(db: Session = Depends(get_db)):
             
             value = latest_value.actual_value
             period = latest_value.period
-            params = rule.params or {}
+            import json; params = json.loads(rule.params) if isinstance(rule.params, str) else (rule.params or {})
             
             alert_level = None
             alert_message = None
@@ -534,7 +534,7 @@ def _check_forecast_alerts(db: Session) -> int:
                 continue
 
             # 检查预测值是否超限
-            params = rule.params or {}
+            import json; params = json.loads(rule.params) if isinstance(rule.params, str) else (rule.params or {})
             params["kpi"] = kpi
             for forecast in latest_forecasts:
                 value = forecast.predicted_cash

backend/app/api/data_quality.py

@@ -253,10 +253,72 @@ def quality_stats(db: Session = Depends(get_db)):
         if cnt:
             type_counts[t] = cnt
 
+    # ── 数据审计看板统计 ──
+    # KPI完整度评分
+    all_kpis = db.query(KPIDefinition).filter(KPIDefinition.status == "active").all()
+    total = len(all_kpis)
+    complete_kpis = 0
+    missing_metadata_count = 0
+    missing_data_count = 0
+    stale_data_count = 0
+
+    from datetime import datetime, timedelta
+    six_months_ago = datetime.now() - timedelta(days=180)
+
+    for kpi in all_kpis:
+        # 元数据完整度检查
+        has_meta = all([
+            kpi.formula and kpi.formula.strip(),
+            kpi.data_source and kpi.data_source.strip(),
+            kpi.data_owner and kpi.data_owner.strip(),
+            kpi.unit and kpi.unit.strip(),
+            kpi.target_value is not None,
+        ])
+        if has_meta:
+            complete_kpis += 1
+        else:
+            missing_metadata_count += 1
+
+        # 数据缺失检查（是否有实际值）
+        val = db.query(KPIValue).filter(
+            KPIValue.kpi_id == kpi.id,
+            KPIValue.actual_value.isnot(None),
+        ).first()
+        if not val:
+            missing_data_count += 1
+
+        # 超30天未更新预警
+        latest_val = db.query(KPIValue).filter(
+            KPIValue.kpi_id == kpi.id,
+            KPIValue.actual_value.isnot(None),
+        ).order_by(KPIValue.period.desc()).first()
+        if latest_val and latest_val.calculated_at:
+            if latest_val.calculated_at < six_months_ago:
+                stale_data_count += 1
+
+    completeness_score = round(complete_kpis / total * 100, 1) if total > 0 else 0
+    missing_rate = round(missing_data_count / total * 100, 1) if total > 0 else 0
+
     return {
         "total_kpis": total_kpis,
         "total_logs": total_logs,
         "open_logs": open_logs,
         "severity_counts": severity_counts,
         "type_counts": type_counts,
+        # 数据审计看板
+        "completeness": {
+            "score": completeness_score,
+            "complete": complete_kpis,
+            "total": total,
+            "missing_metadata": missing_metadata_count,
+        },
+        "data_missing": {
+            "count": missing_data_count,
+            "rate": missing_rate,
+            "total": total,
+        },
+        "stale_data": {
+            "count": stale_data_count,
+            "threshold_days": 180,
+        },
     }

backend/app/api/kpis.py

@@ -406,12 +406,43 @@ def get_kpi(kpi_id: int, db: Session = Depends(get_db)):
     return kpi_to_dict(kpi)
 
 
+def _validate_kpi_data(data: dict, is_update: bool = False):
+    """数据治理：入库必检 + 元数据校验"""
+    errors = []
+
+    # 规则1: target_value 必填
+    tv = data.get("target_value")
+    if tv is None or (isinstance(tv, (int, float)) and tv < 0 and not is_update):
+        if not is_update or "target_value" in data:
+            if tv is None:
+                errors.append("目标值(target_value)不能为空")
+
+    # 规则1: unit 必填
+    unit = data.get("unit")
+    if not unit or (isinstance(unit, str) and unit.strip() == ""):
+        if not is_update or "unit" in data:
+            errors.append("单位(unit)不能为空")
+
+    # 规则2: 元数据必填 — formula/data_source/data_owner
+    for field, label in [("formula", "计算公式"), ("data_source", "数据来源"), ("data_owner", "数据责任人")]:
+        val = data.get(field)
+        if not val or (isinstance(val, str) and val.strip() == ""):
+            if not is_update or field in data:
+                errors.append(f"元数据字段'{label}'({field})不能为空")
+
+    return errors
+
+
 @router.post("")
 def create_kpi(data: dict, db: Session = Depends(get_db), user=WRITE_ROLES):
     # 检查编码唯一性
     existing = db.query(KPIDefinition).filter(KPIDefinition.kpi_code == data.get("kpi_code", "")).first()
     if existing:
         raise HTTPException(400, f"KPI编码 {data['kpi_code']} 已存在")
+    # 数据治理校验
+    errs = _validate_kpi_data(data, is_update=False)
+    if errs:
+        raise HTTPException(422, detail={"message": "数据校验不通过", "errors": errs})
     kpi = KPIDefinition(**data)
     db.add(kpi)
     db.commit()
@@ -425,6 +456,10 @@ def update_kpi(kpi_id: int, data: dict, db: Session = Depends(get_db), user=WRIT
     kpi = db.query(KPIDefinition).filter(KPIDefinition.id == kpi_id).first()
     if not kpi:
         raise HTTPException(404, "KPI不存在")
+    # 数据治理校验（更新时只检查传了但为空的字段）
+    errs = _validate_kpi_data(data, is_update=True)
+    if errs:
+        raise HTTPException(422, detail={"message": "数据校验不通过", "errors": errs})
     for k, v in data.items():
         if hasattr(kpi, k) and v is not None:
             setattr(kpi, k, v)