1

backend/app/analysis/intraday.py

@@ -61,8 +61,8 @@ async def intraday_market_temperature(prev_temp: MarketTemperature) -> MarketTem
 
     # ── 用东方财富 clist API 统计涨停跌停（比腾讯涨停价字段更可靠） ──
     try:
-        limit_up_count = 0
+        realtime_limit_up_count = 0
-        limit_down_count = 0
+        realtime_limit_down_count = 0
 
         for fs, threshold in [
             ("m:0+t:6,m:0+t:80,m:0+t:81+s:2048", 9.9),  # 主板 10%
@@ -84,7 +84,7 @@ async def intraday_market_temperature(prev_temp: MarketTemperature) -> MarketTem
                     if pct == "-" or pct is None:
                         continue
                     if float(pct) >= threshold:
-                        limit_up_count += 1
+                        realtime_limit_up_count += 1
 
                 # 跌停：按涨幅升序取 top 200
                 params_down = {
@@ -102,8 +102,10 @@ async def intraday_market_temperature(prev_temp: MarketTemperature) -> MarketTem
                     if pct == "-" or pct is None:
                         continue
                     if float(pct) <= neg_threshold:
-                        limit_down_count += 1
+                        realtime_limit_down_count += 1
 
+        limit_up_count = realtime_limit_up_count
+        limit_down_count = realtime_limit_down_count
         logger.info(f"东方财富盘中涨跌停: 涨停={limit_up_count} 跌停={limit_down_count}")
     except Exception as e:
         logger.warning(f"东方财富涨跌停统计失败，使用基线数据: {e}")

backend/app/analysis/market_temp.py

@@ -26,6 +26,23 @@ def calculate_market_temperature(trade_date: str = None) -> MarketTemperature:
     # 1. 涨跌家数
     daily_df = tushare_client.get_daily_all(trade_date)
     if daily_df.empty:
+        original_trade_date = trade_date
+        trade_dates = tushare_client.get_trade_dates()
+        fallback_dates = [d for d in trade_dates if d < trade_date][-5:]
+        for fallback_date in reversed(fallback_dates):
+            fallback_df = tushare_client.get_daily_all(fallback_date)
+            if not fallback_df.empty:
+                daily_df = fallback_df
+                trade_date = fallback_date
+                logger.warning(
+                    "市场温度 %s 日线数据为空，回退到最近有效交易日 %s",
+                    original_trade_date,
+                    fallback_date,
+                )
+                break
+
+    if daily_df.empty:
+        logger.warning("市场温度 %s 无有效日线数据，返回占位温度", trade_date)
         return MarketTemperature(trade_date=trade_date, temperature=50)
 
     up_count = len(daily_df[daily_df["pct_chg"] > 0])

backend/app/engine/recommender.py

@@ -21,6 +21,12 @@ _scan_lock = asyncio.Lock()
 _scan_running = False
 
 
+def _has_valid_market_breadth(market_temp: MarketTemperature | None) -> bool:
+    if not market_temp:
+        return False
+    return (market_temp.up_count or 0) + (market_temp.down_count or 0) > 0
+
+
 async def refresh_recommendations(trade_date: str = None, scan_session: str = "manual") -> dict:
     """刷新推荐列表（带扫描锁防止并发）"""
     global _scan_running
@@ -633,23 +639,32 @@ async def _save_to_db(result: dict):
             # 保存市场温度
             mt = result.get("market_temp")
             if mt:
-                # 使用 INSERT OR REPLACE 确保重复扫描能更新数据
+                if _has_valid_market_breadth(mt):
-                stmt = text(
+                    # 使用 INSERT OR REPLACE 确保重复扫描能更新数据
-                    "INSERT OR REPLACE INTO market_temperature "
+                    stmt = text(
-                    "(trade_date, up_count, down_count, limit_up_count, limit_down_count, "
+                        "INSERT OR REPLACE INTO market_temperature "
-                    "max_streak, broken_rate, temperature) "
+                        "(trade_date, up_count, down_count, limit_up_count, limit_down_count, "
-                    "VALUES (:td, :up, :down, :lu, :ld, :ms, :br, :temp)"
+                        "max_streak, broken_rate, temperature) "
-                )
+                        "VALUES (:td, :up, :down, :lu, :ld, :ms, :br, :temp)"
-                await db.execute(stmt, {
+                    )
-                    "td": mt.trade_date,
+                    await db.execute(stmt, {
-                    "up": mt.up_count,
+                        "td": mt.trade_date,
-                    "down": mt.down_count,
+                        "up": mt.up_count,
-                    "lu": mt.limit_up_count,
+                        "down": mt.down_count,
-                    "ld": mt.limit_down_count,
+                        "lu": mt.limit_up_count,
-                    "ms": mt.max_streak,
+                        "ld": mt.limit_down_count,
-                    "br": mt.broken_rate,
+                        "ms": mt.max_streak,
-                    "temp": mt.temperature,
+                        "br": mt.broken_rate,
-                })
+                        "temp": mt.temperature,
+                    })
+                else:
+                    logger.warning(
+                        "跳过无效市场温度快照: trade_date=%s temperature=%s up=%s down=%s",
+                        mt.trade_date,
+                        mt.temperature,
+                        mt.up_count,
+                        mt.down_count,
+                    )
 
             # 保存板块热度（先清除同一 trade_date 的旧数据，再批量插入）
             trade_date_val = mt.trade_date if mt else ""
@@ -769,7 +784,8 @@ async def _load_today_from_db() -> dict:
             result = await db.execute(
                 text(
                     "SELECT * FROM market_temperature "
-                    "ORDER BY REPLACE(trade_date, '-', '') DESC, id DESC LIMIT 1"
+                    "ORDER BY CASE WHEN COALESCE(up_count, 0) + COALESCE(down_count, 0) > 0 THEN 0 ELSE 1 END, "
+                    "REPLACE(trade_date, '-', '') DESC, id DESC LIMIT 1"
                 )
             )
             mt_row = result.fetchone()