fix(rotation): 回测导出JSON序列化NaN/Inf清洗

- simple_rotation.py: 新增 _sanitize_json() 递归替换 NaN/Inf 为 None，
  确保 json.dump 生成合法 JSON（避免前端解析失败）
- .env: 注释掉群2钉钉配置（暂不使用）

.env

@@ -8,8 +8,8 @@ DINGTALK_WEBHOOK_1=https://oapi.dingtalk.com/robot/send?access_token=fb70c1561d8
 DINGTALK_SECRET_1=SEC1ae7cd2f1a6f9da3611af37da3e7d954c1e8533fc073c6c8cc5e5af3b6e5926b
 
 # 钉钉机器人配置 - 群2
-DINGTALK_WEBHOOK_2=https://oapi.dingtalk.com/robot/send?access_token=87c7abfcdd69b699c32da4e4f5981cd2ca6b0445474fc6ffb36f2ed0f6262fbb
+# DINGTALK_WEBHOOK_2=https://oapi.dingtalk.com/robot/send?access_token=87c7abfcdd69b699c32da4e4f5981cd2ca6b0445474fc6ffb36f2ed0f6262fbb
-DINGTALK_SECRET_2=SECf3d6b43f2f8a87ab91feffd052e71ec314fbf57a1842e483fe07af3c0a0e5aa6
+# DINGTALK_SECRET_2=SECf3d6b43f2f8a87ab91feffd052e71ec314fbf57a1842e483fe07af3c0a0e5aa6
 
 
 

datasource/flask_api_source.py

@@ -167,6 +167,15 @@ class FlaskAPIDataSource:
                     standard_cols = ['code'] + standard_cols
                 df = df[standard_cols]
                 
+                # 过滤 yfinance 返回的不完整数据（未收盘日 close=NaN, volume=0）
+                nan_count = df['close'].isna().sum()
+                if nan_count > 0:
+                    df = df.dropna(subset=['close'])
+                    actual_count = len(df)
+                    if actual_count == 0:
+                        print(f"⚠ {code}: 所有数据 close 均为 NaN")
+                        return None
+                
                 # 使用 API 返回的实际数据范围（而非请求参数）
                 actual_start = validated.date_range.start if validated.date_range else start_date
                 actual_end = validated.date_range.end if validated.date_range else end_date

datasource/yfinance_source.py

@@ -44,6 +44,25 @@ class YFinanceSource:
         self.use_ssh_tunnel = use_ssh_tunnel
         self._delay = 0.5  # 请求延迟（避免限流）
 
+    @staticmethod
+    def _normalize_index(index: pd.DatetimeIndex) -> pd.DatetimeIndex:
+        """
+        标准化日期索引，保留交易所本地日期
+        
+        yfinance 返回的时间戳带有交易所本地时区：
+        - 美股: 00:00-04:00 (US/Eastern)  → 剥 tz 后 00:00，日期不变
+        - 日本: 00:00+09:00 (Asia/Tokyo) → 剥 tz 后 00:00，日期不变
+        - 欧洲: 00:00+02:00 (CET)        → 剥 tz 后 00:00，日期不变
+        
+        关键：直接 tz_localize(None) 剥除时区，不做 UTC 转换。
+        错误示范：pd.to_datetime(idx, utc=True) 会先把日本 00:00+09:00 转成
+        前一天 15:00 UTC，导致日期回退一天。
+        """
+        if index.tz is not None:
+            # tz_localize(None) 直接剥除时区，保留本地时间部分
+            index = index.tz_localize(None)
+        return index.normalize()
+
     def fetch(self, code: str, start_date: str, end_date: str, adj: str = 'raw') -> Optional[pd.DataFrame]:
         """
         获取数据（支持 adj 参数）
@@ -108,10 +127,17 @@ class YFinanceSource:
                 "Volume": "volume",
             })
             
-            # 确保索引是日期格式
+            # 确保索引是日期格式（保留交易所本地日期，避免 UTC 转换导致跨日偏移）
-            df.index = pd.to_datetime(df.index, utc=True).tz_localize(None).normalize()
+            df.index = self._normalize_index(df.index)
             df.index.name = "date"
             
+            # 过滤 yfinance 返回的不完整数据（未收盘日 close=NaN, volume=0）
+            nan_mask = df['close'].isna()
+            if nan_mask.any():
+                df = df[~nan_mask]
+                if len(df) == 0:
+                    return None
+            
             # 添加代码列
             df["code"] = code
             
@@ -189,8 +215,8 @@ class YFinanceSource:
                 "Volume": "volume",
             })
             
-            # 确保索引是日期格式
+            # 确保索引是日期格式（保留交易所本地日期，避免 UTC 转换导致跨日偏移）
-            df.index = pd.to_datetime(df.index, utc=True).tz_localize(None).normalize()
+            df.index = self._normalize_index(df.index)
             df.index.name = "date"
             
             # 添加代码列和标记

rotation/simple_rotation.py

@@ -40,6 +40,22 @@ def _http_get(url: str, params: dict = None, timeout: int = 120) -> requests.Res
     return _session.get(url, params=params, timeout=timeout)
 
 
+def _sanitize_json(obj):
+    """Recursively replace NaN/Inf with None in-place so json.dump produces valid JSON"""
+    if isinstance(obj, dict):
+        for k, v in obj.items():
+            if isinstance(v, float) and (math.isnan(v) or math.isinf(v)):
+                obj[k] = None
+            elif isinstance(v, (dict, list)):
+                _sanitize_json(v)
+    elif isinstance(obj, list):
+        for i, v in enumerate(obj):
+            if isinstance(v, float) and (math.isnan(v) or math.isinf(v)):
+                obj[i] = None
+            elif isinstance(v, (dict, list)):
+                _sanitize_json(v)
+
+
 # ============================================================
 # Pure functions: momentum
 # ============================================================
@@ -888,6 +904,7 @@ class SimpleRotationStrategy:
             },
             'days': days_out,
         }
+        _sanitize_json(detail)
         with open(detail_path, 'w', encoding='utf-8') as f:
             json.dump(detail, f, ensure_ascii=False, indent=2)
         print(f"  + Detail: {detail_path} ({len(days_out)} days)")
@@ -895,6 +912,7 @@ class SimpleRotationStrategy:
         # Metrics JSON
         metrics = self._compute_metrics(sum(1 for r in self.daily_records if r['is_rebalance']))
         metrics_path = output_dir / 'simple_rotation_metrics.json'
+        _sanitize_json(metrics)
         with open(metrics_path, 'w', encoding='utf-8') as f:
             json.dump(metrics, f, ensure_ascii=False, indent=2)
         print(f"  + Metrics: {metrics_path}")