feat: 全景扫描推荐列表分页改为5只/页，支持收起/展开

原先DB用 trade_date >= now-120天（自然日）过滤，只返回~82个交易日；
API用 limit=120 返回120个交易日。K线条数不一致导致指标计算结果
不同，进而导致信号判定不同。

改为 ORDER BY trade_date DESC LIMIT min(days,300) + reversed，
与API的limit参数行为完全一致。

stock-html/db.py

@@ -552,7 +552,7 @@ def db_save_fundamental(code, data):
 
 # ========== 资金流向历史数据操作（数据库版） ==========
 
-def db_get_fund_flow_history(code):
+def db_get_fund_flow_history(code, limit=60):
     """获取股票的资金流向历史数据"""
     conn = get_db()
     if not conn:
@@ -564,11 +564,14 @@ def db_get_fund_flow_history(code):
             SELECT code, trade_date::text, close_price, change_pct,
                    main_net_inflow, main_net_inflow_pct,
                    super_net_inflow, super_net_inflow_pct,
-                   big_net_inflow, big_net_inflow_pct
+                   big_net_inflow, big_net_inflow_pct,
+                   mid_net_inflow, mid_net_inflow_pct,
+                   small_net_inflow, small_net_inflow_pct
             FROM stock_fund_flow_history 
             WHERE code = %s
             ORDER BY trade_date DESC
-        """, (code,))
+            LIMIT %s
+        """, (code, limit))
         rows = cur.fetchall()
         
         # 获取最新日期

stock-html/docs/算法分析.md

@@ -14,7 +14,7 @@
 信号检测层（signal_detector.py）                ← 第三章
         ↓ 基于7个信号检测买卖点
 外部因素模块（fund_flow/sentiment/external/news）← 第四章
-        ↓ 资金面/情绪/北向/美股/商品/公告/政策/汇率 → 各因素评分
+        ↓ 资金面/情绪/南向/美股/商品/公告/政策/汇率 → 各因素评分
 算法决策层（stock_algorithms.py）               ← 第五章
         ↓ 统一推荐逻辑、牛股阶段识别、技术面深度分析（7维度）→ 技术面基础分
 综合评分引擎（score_engine.py）
@@ -25,7 +25,7 @@
 |------|------|------|------|
 | 技术指标层 | `services/technical_indicators.py` | 计算 MACD、SKDJ、KDJ、EMA、MA 等基础指标 | 二 |
 | 信号检测层 | `services/signal_detector.py` | 基于7个信号检测买卖点 | 三 |
-| 外部因素模块 | `fund_flow_analyzer.py` / `market_sentiment.py` / `external_factors.py` / `news_analyzer.py` | 资金面、市场情绪、北向资金、美股、大宗商品、公告/政策、汇率 | 四 |
+| 外部因素模块 | `fund_flow_analyzer.py` / `market_sentiment.py` / `external_factors.py` / `news_analyzer.py` | 资金面、市场情绪、南向资金、美股、大宗商品、公告/政策、汇率 | 四 |
 | 算法决策层 | `services/stock_algorithms.py` | 统一推荐逻辑、牛股阶段识别、技术面深度分析 | 五 |
 | 综合评分引擎 | `services/score_engine.py` | 整合外部因素（P0-P7）与技术面评分，输出最终评分 | 五 |
 
@@ -258,21 +258,21 @@
 - **API端点**：`GET /api/market_sentiment`
 - **评分范围**：±10
 
-### 4.3 北向资金（P2，已实现）
+### 4.3 南向资金（P2，已实现）
 
-**白话解释**：北向资金是从香港流入A股的"外资"，被市场视为"聪明钱"。北向大幅买入通常被视为利好信号。
+**白话解释**：南向资金是内地通过港股通配置港股的资金，反映跨境资金情绪。南向大幅流入说明内地资金积极配置港股，大中华区risk-on，对A股偏正面。注：2024年8月起北向资金实时数据已停止公布，改用南向资金作为替代指标。
 
 | 信号 | 含义 | 可靠度 | 评分 |
 |------|------|--------|------|
-| 北向单日净流入>50亿 | 外资看好，市场偏多 | ★★★★ | +5 |
+| 南向单日净流入>80亿 | 跨境资金情绪偏暖 | ★★★★ | +5 |
-| 北向单日净流出>50亿 | 外资看空，注意风险 | ★★★★ | -5 |
+| 南向单日净流出>80亿 | 跨境资金情绪偏冷 | ★★★★ | -5 |
-| 北向连续3日净流入 | 外资持续看好，中期偏多 | ★★★★★ | +3 |
+| 南向连续3日净流入 | 资金持续流入，中期偏多 | ★★★★★ | +3 |
-| 北向连续3日净流出 | 外资持续撤离，中期偏空 | ★★★★ | -3 |
+| 南向连续3日净流出 | 资金持续流出，中期偏空 | ★★★★ | -3 |
 
 #### 实现模块
 
-- **模块文件**：`services/external_factors.py` → `get_northbound_capital()`
+- **模块文件**：`services/external_factors.py` → `get_southbound_capital()`
-- **数据来源**：AKShare `stock_hsgt_north_net_flow_in_em`（北向资金净流入）
+- **数据来源**：AKShare `stock_hsgt_fund_flow_summary_em`（今日汇总）+ `stock_hsgt_hist_em`（南向资金历史）
 - **评分范围**：±10
 
 ### 4.4 美股隔夜板块变化（P3，已实现）
@@ -413,7 +413,7 @@
   资金流向数据 → 资金信号 ────────────────────────────────┤
   美股隔夜数据 → 外盘情绪 ────────────────────────────────┤→ 综合评分引擎 → 最终评分 → 买卖建议/AI解说
   公告/新闻 → LLM情感分析 ───────────────────────────────┤
-  北向资金 → 外资动向 ────────────────────────────────────┤
+  南向资金 → 跨境资金情绪 ────────────────────────────────┤
   市场情绪指标 → 情绪评分 ────────────────────────────────┤
   大宗商品 → 板块影响 ────────────────────────────────────┤
   汇率 → 进出口影响 ──────────────────────────────────────┘
@@ -426,7 +426,7 @@
 | 技术面基础分 | 0-100 | `compute_deep_analysis` 原始分 |
 | P0 资金面 | ±20 | 连续流入+10，吸筹+8，大单突击+5 |
 | P1 市场情绪 | ±10 | 涨跌停比+5/-5，连板+3，成交额+2/-2 |
-| P2 北向资金 | ±10 | 大幅流入+5，连续流入+3 |
+| P2 南向资金 | ±10 | 大幅流入+5，连续流入+3 |
 | P3 美股外盘 | ±10 | 美股大涨+5，大跌-5 |
 | P4 大宗商品 | ±5 | 单品种涨跌±1 |
 | P5 公告/异动 | ±15 | 并购+10，业绩预增+8，异动±5 |
@@ -445,7 +445,7 @@
 |------|------|------|
 | 资金流向分析 | `services/fund_flow_analyzer.py` | 从DB读取资金流向，计算连续流入/流出、量价背离、大单突击 |
 | 市场情绪指标 | `services/market_sentiment.py` | 从实时行情表计算涨停跌停比、连板高度、换手率中位数、两市成交额 |
-| 外部因素 | `services/external_factors.py` | 北向资金、美股隔夜板块、大宗商品、汇率变化 |
+| 外部因素 | `services/external_factors.py` | 南向资金、美股隔夜板块、大宗商品、汇率变化 |
 | 新闻/公告分析 | `services/news_analyzer.py` | 公告采集+分类、LLM情感分析、异动检测、政策面监控 |
 | 综合评分引擎 | `services/score_engine.py` | 汇总技术面+所有外部因素，输出最终评分 |
 
@@ -454,7 +454,7 @@
 | 端点 | 方法 | 说明 |
 |------|------|------|
 | `/api/market_sentiment` | GET | 市场情绪指标 |
-| `/api/external_factors` | GET | 外部因素综合数据（北向/美股/商品/汇率） |
+| `/api/external_factors` | GET | 外部因素综合数据（南向/美股/商品/汇率） |
 | `/api/fund_flow_analysis/<code>` | GET | 个股资金流向分析 |
 | `/api/news_analysis/<code>` | GET | 个股消息面分析（公告+政策+异动） |
 
@@ -658,7 +658,7 @@ deep_analyze 接口调用流程：
 |------|------|----------|------|
 | P0 资金面 | `fund_flow_analyzer` | ±20 | 主力在买还是在卖？有没有暗中吸筹/出货？ |
 | P1 市场情绪 | `market_sentiment` | ±10 | 今天涨停的股票多还是跌停的多？市场热不热？ |
-| P2 北向资金 | `external_factors` | ±10 | 外资今天是买还是卖？ |
+| P2 南向资金 | `external_factors` | ±10 | 跨境资金今天是流入还是流出？ |
 | P3 美股外盘 | `external_factors` | ±10 | 昨晚美股涨了还是跌了？ |
 | P4 大宗商品 | `external_factors` | ±5 | 原油/黄金/铜的价格变化对相关板块的影响 |
 | P5 公告/异动 | `news_analyzer` | ±15 | 有没有并购/业绩预告等重大消息？股价有没有异动？ |
@@ -681,7 +681,7 @@ deep_analyze 接口调用流程：
 5. 形态识别（发现了什么技术形态）
 6. 综合建议（根据评分给出操作建议）
 7. 空间估算（风险收益比如何）
-8. 外部因素（资金面/市场情绪/北向资金/美股/消息面等综合影响）
+8. 外部因素（资金面/市场情绪/南向资金/美股/消息面等综合影响）
 
 还可以调用豆包 LLM 对规则文本进行润色，让表达更自然生动。
 

stock-html/docs/算法分析_v2.md

@@ -15,7 +15,7 @@
 信号检测层（signal_detector.py）                ← 第三章
         ↓ 基于7个信号检测买卖点
 外部因素模块（fund_flow/sentiment/external/news）← 第四章
-        ↓ 资金面/情绪/北向/美股/商品/公告/政策/汇率 → 各因素评分
+        ↓ 资金面/情绪/南向/美股/商品/公告/政策/汇率 → 各因素评分
 算法决策层（stock_algorithms.py）               ← 第五章
         ↓ 统一推荐逻辑、牛股阶段识别、技术面深度分析（7维度）→ 技术面基础分
 综合评分引擎（score_engine.py）                  ← 第五章
@@ -26,7 +26,7 @@
 |------|------|------|------|
 | 技术指标层 | `services/technical_indicators.py` | 计算 MACD、SKDJ、KDJ、EMA、MA 等基础指标 | 二 |
 | 信号检测层 | `services/signal_detector.py` | 基于7个信号检测买卖点 | 三 |
-| 外部因素模块 | `fund_flow_analyzer.py` / `market_sentiment.py` / `external_factors.py` / `news_analyzer.py` | 资金面、市场情绪、北向资金、美股、大宗商品、公告/政策、汇率 | 四 |
+| 外部因素模块 | `fund_flow_analyzer.py` / `market_sentiment.py` / `external_factors.py` / `news_analyzer.py` | 资金面、市场情绪、南向资金、美股、大宗商品、公告/政策、汇率 | 四 |
 | 算法决策层 | `services/stock_algorithms.py` | 统一推荐逻辑、牛股阶段识别、技术面深度分析 | 五 |
 | 综合评分引擎 | `services/score_engine.py` | 整合外部因素（P0-P7）与技术面评分，输出最终评分 | 五 |
 
@@ -259,21 +259,21 @@
 - **API端点**：`GET /api/market_sentiment`
 - **评分范围**：±10
 
-### 4.3 北向资金（P2，已实现）
+### 4.3 南向资金（P2，已实现）
 
-**白话解释**：北向资金是从香港流入A股的"外资"，被市场视为"聪明钱"。北向大幅买入通常被视为利好信号。
+**白话解释**：南向资金是内地通过港股通配置港股的资金，反映跨境资金情绪。南向大幅流入说明内地资金积极配置港股，大中华区risk-on，对A股偏正面。注：2024年8月起北向资金实时数据已停止公布，改用南向资金作为替代指标。
 
 | 信号 | 含义 | 可靠度 | 评分 |
 |------|------|--------|------|
-| 北向单日净流入>50亿 | 外资看好，市场偏多 | ★★★★ | +5 |
+| 南向单日净流入>80亿 | 跨境资金情绪偏暖 | ★★★★ | +5 |
-| 北向单日净流出>50亿 | 外资看空，注意风险 | ★★★★ | -5 |
+| 南向单日净流出>80亿 | 跨境资金情绪偏冷 | ★★★★ | -5 |
-| 北向连续3日净流入 | 外资持续看好，中期偏多 | ★★★★★ | +3 |
+| 南向连续3日净流入 | 资金持续流入，中期偏多 | ★★★★★ | +3 |
-| 北向连续3日净流出 | 外资持续撤离，中期偏空 | ★★★★ | -3 |
+| 南向连续3日净流出 | 资金持续流出，中期偏空 | ★★★★ | -3 |
 
 #### 实现模块
 
-- **模块文件**：`services/external_factors.py` → `get_northbound_capital()`
+- **模块文件**：`services/external_factors.py` → `get_southbound_capital()`
-- **数据来源**：AKShare `stock_hsgt_north_net_flow_in_em`（北向资金净流入）
+- **数据来源**：AKShare `stock_hsgt_fund_flow_summary_em`（今日汇总）+ `stock_hsgt_hist_em`（南向资金历史）
 - **评分范围**：±10
 
 ### 4.4 美股隔夜板块变化（P3，已实现）
@@ -414,7 +414,7 @@
   资金流向数据 → 资金信号 ────────────────────────────────┤
   美股隔夜数据 → 外盘情绪 ────────────────────────────────┤→ 综合评分引擎 → 最终评分 → 买卖建议/AI解说
   公告/新闻 → LLM情感分析 ───────────────────────────────┤
-  北向资金 → 外资动向 ────────────────────────────────────┤
+  南向资金 → 跨境资金情绪 ────────────────────────────────┤
   市场情绪指标 → 情绪评分 ────────────────────────────────┤
   大宗商品 → 板块影响 ────────────────────────────────────┤
   汇率 → 进出口影响 ──────────────────────────────────────┘
@@ -427,7 +427,7 @@
 | 技术面基础分 | 0-100 | `compute_deep_analysis` 原始分 |
 | P0 资金面 | ±20 | 连续流入+10，吸筹+8，大单突击+5 |
 | P1 市场情绪 | ±10 | 涨跌停比+5/-5，连板+3，成交额+2/-2 |
-| P2 北向资金 | ±10 | 大幅流入+5，连续流入+3 |
+| P2 南向资金 | ±10 | 大幅流入+5，连续流入+3 |
 | P3 美股外盘 | ±10 | 美股大涨+5，大跌-5 |
 | P4 大宗商品 | ±5 | 单品种涨跌±1 |
 | P5 公告/异动 | ±15 | 并购+10，业绩预增+8，异动±5 |
@@ -446,7 +446,7 @@
 |------|------|------|
 | 资金流向分析 | `services/fund_flow_analyzer.py` | 从DB读取资金流向，计算连续流入/流出、量价背离、大单突击 |
 | 市场情绪指标 | `services/market_sentiment.py` | 从实时行情表计算涨停跌停比、连板高度、换手率中位数、两市成交额 |
-| 外部因素 | `services/external_factors.py` | 北向资金、美股隔夜板块、大宗商品、汇率变化 |
+| 外部因素 | `services/external_factors.py` | 南向资金、美股隔夜板块、大宗商品、汇率变化 |
 | 新闻/公告分析 | `services/news_analyzer.py` | 公告采集+分类、LLM情感分析、异动检测、政策面监控 |
 | 综合评分引擎 | `services/score_engine.py` | 汇总技术面+所有外部因素，输出最终评分 |
 
@@ -455,7 +455,7 @@
 | 端点 | 方法 | 说明 |
 |------|------|------|
 | `/api/market_sentiment` | GET | 市场情绪指标 |
-| `/api/external_factors` | GET | 外部因素综合数据（北向/美股/商品/汇率） |
+| `/api/external_factors` | GET | 外部因素综合数据（南向/美股/商品/汇率） |
 | `/api/fund_flow_analysis/<code>` | GET | 个股资金流向分析 |
 | `/api/news_analysis/<code>` | GET | 个股消息面分析（公告+政策+异动） |
 
@@ -670,7 +670,7 @@ deep_analyze 接口调用流程：
 |------|------|----------|------|
 | P0 资金面 | `fund_flow_analyzer` | ±20 | 主力在买还是在卖？有没有暗中吸筹/出货？ |
 | P1 市场情绪 | `market_sentiment` | ±10 | 今天涨停的股票多还是跌停的多？市场热不热？ |
-| P2 北向资金 | `external_factors` | ±10 | 外资今天是买还是卖？ |
+| P2 南向资金 | `external_factors` | ±10 | 跨境资金今天是流入还是流出？ |
 | P3 美股外盘 | `external_factors` | ±10 | 昨晚美股涨了还是跌了？ |
 | P4 大宗商品 | `external_factors` | ±5 | 原油/黄金/铜的价格变化对相关板块的影响 |
 | P5 公告/异动 | `news_analyzer` | ±15 | 有没有并购/业绩预告等重大消息？股价有没有异动？ |
@@ -772,7 +772,7 @@ deep_analyze 接口调用流程：
 5. 形态识别（发现了什么技术形态）
 6. 综合建议（根据**综合得分**给出操作建议）
 7. 空间估算（风险收益比如何）
-8. 外部因素（资金面/市场情绪/北向资金/美股/消息面等综合影响）
+8. 外部因素（资金面/市场情绪/南向资金/美股/消息面等综合影响）
 9. **三项得分汇总**（技术得分、外部得分、综合得分）
 
 还可以调用豆包 LLM 对规则文本进行润色，让表达更自然生动。

stock-html/full_signal_scan.py

@@ -62,6 +62,7 @@ def get_all_stock_codes(conn):
             SELECT code, name FROM stock_realtime_price
             WHERE volume > 0 AND price > 0
               AND name NOT LIKE '%%退%%'
+              AND name NOT LIKE '%%ST%%'
               AND name NOT LIKE 'PT%%'
             ORDER BY code
         """)

stock-html/requirements.txt

@@ -1,5 +1,6 @@
 flask>=2.0.0
 flask-cors>=3.0.0
+requests>=2.25.0
 akshare>=1.10.0
 pandas>=1.5.0
 numpy>=1.20.0

stock-html/routes/admin.py

@@ -2,7 +2,7 @@
 管理后台 API 路由
 """
 from flask import Blueprint, request, jsonify, session, render_template
-from db import get_db
+from db import get_db, put_db
 from psycopg2.extras import RealDictCursor
 from werkzeug.security import generate_password_hash
 import functools
@@ -182,7 +182,7 @@ def admin_required(f):
             if not row or not row[0]:
                 return jsonify({'success': False, 'error': '无管理员权限'}), 403
         finally:
-            conn.close()
+            put_db(conn)
         return f(*args, **kwargs)
     return decorated
 
@@ -201,7 +201,7 @@ def admin_page():
         if not row or not row[0]:
             return '无权访问', 403
     finally:
-        conn.close()
+        put_db(conn)
     return render_template('admin.html')
 
 
@@ -281,7 +281,7 @@ def dashboard():
 
         return jsonify({'success': True, 'data': stats})
     finally:
-        conn.close()
+        put_db(conn)
 
 
 # ========== 用户管理 ==========
@@ -339,7 +339,7 @@ def list_users():
 
         return jsonify({'success': True, 'data': users})
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/api/admin/users/<int:user_id>', methods=['GET'])
@@ -437,7 +437,7 @@ def get_user_detail(user_id):
             }
         })
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/api/admin/users/<int:user_id>/reset_password', methods=['POST'])
@@ -461,7 +461,7 @@ def reset_user_password(user_id):
         conn.rollback()
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/api/admin/users/<int:user_id>/toggle_admin', methods=['POST'])
@@ -483,7 +483,7 @@ def toggle_admin(user_id):
         conn.rollback()
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/api/admin/users/<int:user_id>', methods=['DELETE'])
@@ -509,7 +509,7 @@ def delete_user(user_id):
         conn.rollback()
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 # ========== 用户数据管理 ==========
@@ -526,7 +526,7 @@ def delete_user_watchlist(user_id, code):
         conn.commit()
         return jsonify({'success': True})
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/api/admin/users/<int:user_id>/trades/<int:trade_id>', methods=['DELETE'])
@@ -541,7 +541,7 @@ def delete_user_trade(user_id, trade_id):
         conn.commit()
         return jsonify({'success': True})
     finally:
-        conn.close()
+        put_db(conn)
 
 
 # ========== 系统数据 ==========
@@ -568,7 +568,7 @@ def scan_history():
         """)
         return jsonify({'success': True, 'data': [dict(r) for r in cur.fetchall()]})
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/api/admin/data_stats', methods=['GET'])
@@ -603,7 +603,7 @@ def data_stats():
 
         return jsonify({'success': True, 'data': {'tables': result, 'logs': logs}})
     finally:
-        conn.close()
+        put_db(conn)
 
 
 # ========== 全景扫描管理 ==========
@@ -753,13 +753,9 @@ def trigger_kline_sync():
 def kline_sync_status():
     """管理员查询K线同步状态"""
     try:
-        import psycopg2
+        conn = get_db()
-        from config import Config
+        if not conn:
-
+            return jsonify({'success': False, 'error': '数据库连接失败'}), 500
-        conn = psycopg2.connect(
-            host=Config.DB_HOST, port=Config.DB_PORT,
-            dbname=Config.DB_NAME, user=Config.DB_USER, password=Config.DB_PASSWORD,
-        )
         cur = conn.cursor()
 
         # K线数据统计
@@ -786,7 +782,6 @@ def kline_sync_status():
         total_stocks = cur.fetchone()[0]
 
         cur.close()
-        conn.close()
 
         is_running = _is_kline_sync_running()
 
@@ -862,6 +857,8 @@ def kline_sync_status():
         })
     except Exception as e:
         return jsonify({'success': False, 'error': str(e)}), 500
+    finally:
+        put_db(conn)
 
 
 # ========== 定时任务监控 ==========
@@ -1282,13 +1279,10 @@ def admin_scan_status():
     """管理员查询扫描进度"""
     try:
         from datetime import datetime
-        import psycopg2
-        from config import Config
 
-        conn = psycopg2.connect(
+        conn = get_db()
-            host=Config.DB_HOST, port=Config.DB_PORT,
+        if not conn:
-            dbname=Config.DB_NAME, user=Config.DB_USER, password=Config.DB_PASSWORD,
+            return jsonify({'success': False, 'error': '数据库连接失败'}), 500
-        )
         cur = conn.cursor()
 
         scan_date = datetime.now().strftime('%Y-%m-%d')
@@ -1308,7 +1302,6 @@ def admin_scan_status():
         triggered = cur.fetchone()[0]
 
         cur.close()
-        conn.close()
 
         is_running = _is_scan_running()
 
@@ -1357,3 +1350,5 @@ def admin_scan_status():
         })
     except Exception as e:
         return jsonify({'success': False, 'error': str(e)}), 500
+    finally:
+        put_db(conn)

stock-html/routes/analysis.py

@@ -15,7 +15,8 @@ from services.stock_algorithms import (
 )
 from db import (
     login_required, get_current_user_id,
-    db_get_alerts_cache, db_save_alerts_cache
+    db_get_alerts_cache, db_save_alerts_cache,
+    get_db, put_db
 )
 
 bp = Blueprint('analysis', __name__, url_prefix='/api')
@@ -61,7 +62,7 @@ def analyze():
         # 3. 获取实时价格补充到结果（优先腾讯API，兼容腾讯云）
         try:
             import requests as _req
-            _tcode = ('sh' if stock_code.startswith('6') else 'sz') + stock_code
+            _tcode = ('sh' if stock_code.startswith('6') else 'bj' if stock_code.startswith(('8', '9')) else 'sz') + stock_code
             _r = _req.get(f'http://qt.gtimg.cn/q={_tcode}', timeout=5,
                           headers={'Referer': 'https://finance.qq.com'})
             if _r.status_code == 200 and '\"' in _r.text:
@@ -98,7 +99,7 @@ def deep_analyze():
         if not stock_code:
             return jsonify({'error': '股票代码不能为空'}), 400
 
-        df = algo_get_kline_data(stock_code, days=180)
+        df = algo_get_kline_data(stock_code, days=120)
         if df is None or len(df) < 30:
             return jsonify({'error': 'K线数据不足'}), 400
 
@@ -313,7 +314,7 @@ def ai_analyze_stream(stock_code):
     from flask import Response
     from services.doubao_api import analyze_stock_stream, format_fund_flow, format_market_cap
     from services.mairui_api import get_realtime_price as mairui_price, get_financial_indicators
-    from db import get_db
+    from db import get_db, put_db
     
     def generate():
         # 获取股票数据
@@ -339,6 +340,7 @@ def ai_analyze_stream(stock_code):
         stock_name = get_stock_name(stock_code) or stock_code
         
         # 获取资金流向和技术信号
+        conn = None
         try:
             conn = get_db()
             if conn:
@@ -383,12 +385,14 @@ def ai_analyze_stream(stock_code):
                     stock_data['indicators'] = scan_row['indicators'] or {}
                     stock_data['triggered_count'] = scan_row['triggered_count'] or 0
                 cur2.close()
-
-                conn.close()
         except Exception as e:
             print(f"获取数据失败: {e}")
+        finally:
+            if conn:
+                put_db(conn)
 
         # 记录AI调用日志
+        _conn = None
         try:
             from flask import session as _sess
             _uid = _sess.get('user_id')
@@ -399,9 +403,11 @@ def ai_analyze_stream(stock_code):
                     _cur.execute("INSERT INTO ai_call_log (user_id, stock_code, stock_name) VALUES (%s, %s, %s)",
                                  (_uid, stock_code, stock_name))
                     _conn.commit()
-                    _conn.close()
         except Exception:
             pass
+        finally:
+            if _conn:
+                put_db(_conn)
 
         # 流式调用AI
         for chunk in analyze_stock_stream(stock_code, stock_name, stock_data):
@@ -421,7 +427,7 @@ def ai_analyze(stock_code):
     try:
         from services.doubao_api import analyze_stock
         from services.mairui_api import get_realtime_price as mairui_price, get_financial_indicators
-        from db import get_db
+        from db import get_db, put_db
         
         # 获取股票数据
         stock_data = {}
@@ -446,6 +452,7 @@ def ai_analyze(stock_code):
         stock_name = get_stock_name(stock_code) or stock_code
         
         # 获取近三日资金流向
+        conn = None
         try:
             conn = get_db()
             if conn:
@@ -467,9 +474,11 @@ def ai_analyze(stock_code):
                         'super_pct': float(row[3]) if row[3] else 0,
                     })
                 stock_data['fund_flow_3days'] = fund_flow
-                conn.close()
         except Exception as e:
             print(f"获取资金流向失败: {e}")
+        finally:
+            if conn:
+                put_db(conn)
         
         # 调用AI分析
         result = analyze_stock(stock_code, stock_name, stock_data)
@@ -544,10 +553,8 @@ def batch_technical_signals():
     """批量检测技术交易信号 — 优先从 stock_signal_scan 读取（与提醒一致），无记录时实时计算"""
     try:
         import pandas as pd
-        import psycopg2
         from psycopg2.extras import RealDictCursor
         from services.signal_detector import detect_all_signals
-        from config import Config
 
         data = request.get_json()
         codes = data.get('codes', [])
@@ -566,10 +573,9 @@ def batch_technical_signals():
         change_map = {}
         scan_map = {}
         try:
-            conn = psycopg2.connect(
+            conn = get_db()
-                host=Config.DB_HOST, port=Config.DB_PORT,
+            if not conn:
-                dbname=Config.DB_NAME, user=Config.DB_USER, password=Config.DB_PASSWORD,
+                raise Exception('数据库连接失败')
-            )
             cur = conn.cursor(cursor_factory=RealDictCursor)
             placeholders = ','.join(['%s'] * len(codes))
 
@@ -603,9 +609,10 @@ def batch_technical_signals():
                 scan_map[row['code']] = row
 
             cur.close()
-            conn.close()
         except Exception as e:
             print(f"批量扫描获取数据失败: {e}")
+        finally:
+            put_db(conn)
 
         results = []
         errors = []
@@ -675,9 +682,6 @@ def batch_technical_signals():
 def get_scan_results():
     """查询全量扫描结果"""
     try:
-        import psycopg2
-        from config import Config
-
         scan_date = request.args.get('date', datetime.now().strftime('%Y-%m-%d'))
         min_triggered = int(request.args.get('min_triggered', 0))
         signal_type = request.args.get('signal_type', '')
@@ -689,10 +693,9 @@ def get_scan_results():
         holding_set = set(c.strip() for c in holding_codes_str.split(',') if c.strip())
         recommend_text = (request.args.get('recommend_text') or '').strip()
 
-        conn = psycopg2.connect(
+        conn = get_db()
-            host=Config.DB_HOST, port=Config.DB_PORT,
+        if not conn:
-            dbname=Config.DB_NAME, user=Config.DB_USER, password=Config.DB_PASSWORD,
+            return jsonify({'success': False, 'error': '数据库连接失败'}), 500
-        )
         cur = conn.cursor()
 
         # 检查请求日期是否有数据，如果没有则自动回退到最近可用的扫描日期
@@ -714,7 +717,8 @@ def get_scan_results():
                 )
                 total_scanned = cur.fetchone()[0]
 
-        cur.execute("SELECT count(*) FROM stock_realtime_price")
+        cur.execute("""SELECT count(*) FROM stock_realtime_price
+            WHERE name NOT LIKE '%%退%%' AND name NOT LIKE '%%ST%%' AND name NOT LIKE 'PT%%'""")
         total_stocks = cur.fetchone()[0]
 
         where_clauses = ["scan_date = %s"]
@@ -890,6 +894,7 @@ def get_scan_results():
                 count(*) as cnt
             FROM stock_signal_scan, jsonb_array_elements(signal_status) s
             WHERE scan_date = %s AND (s.value->>'triggered')::boolean = true
+              AND name NOT LIKE '%%退%%' AND name NOT LIKE '%%ST%%'
             GROUP BY s.value->>'name', s.value->>'type'
             ORDER BY cnt DESC
         """, (scan_date,))
@@ -901,6 +906,7 @@ def get_scan_results():
         cur.execute("""
             SELECT count(*) FROM stock_signal_scan
             WHERE scan_date = %s AND triggered_count > 0
+              AND name NOT LIKE '%%退%%' AND name NOT LIKE '%%ST%%'
         """, (scan_date,))
         triggered_stocks = cur.fetchone()[0]
 
@@ -916,6 +922,7 @@ def get_scan_results():
             cur.execute("""
                 SELECT code, signal_status, indicators, triggered_count
                 FROM stock_signal_scan WHERE scan_date = %s
+                AND name NOT LIKE '%%退%%' AND name NOT LIKE '%%ST%%'
             """, (scan_date,))
             recommend_counts = {}
             for r in cur.fetchall():
@@ -925,7 +932,6 @@ def get_scan_results():
                 recommend_counts[disp] = recommend_counts.get(disp, 0) + 1
 
         cur.close()
-        conn.close()
 
         return jsonify({
             'success': True,
@@ -945,6 +951,8 @@ def get_scan_results():
         })
     except Exception as e:
         return jsonify({'success': False, 'error': str(e)}), 500
+    finally:
+        put_db(conn)
 
 
 def _compute_recommend(signal_status, indicators, triggered_count, is_holding):
@@ -955,9 +963,7 @@ def _compute_recommend(signal_status, indicators, triggered_count, is_holding):
 @bp.route('/signal_alerts', methods=['POST'])
 def signal_alerts():
     """基于信号扫描结果生成买入/卖出/观望提醒（与扫描结果共用 _compute_recommend）"""
-    import psycopg2
     from psycopg2.extras import RealDictCursor
-    from config import Config
 
     try:
         data = request.get_json() or {}
@@ -968,10 +974,9 @@ def signal_alerts():
         if not stock_codes:
             return jsonify({'success': True, 'results': []})
 
-        conn = psycopg2.connect(
+        conn = get_db()
-            host=Config.DB_HOST, port=Config.DB_PORT,
+        if not conn:
-            dbname=Config.DB_NAME, user=Config.DB_USER, password=Config.DB_PASSWORD,
+            return jsonify({'success': False, 'error': '数据库连接失败'}), 500
-        )
         cur = conn.cursor(cursor_factory=RealDictCursor)
 
         # 优先今天的扫描数据，无则回退到最近可用日期
@@ -1003,7 +1008,6 @@ def signal_alerts():
             WHERE code IN ({placeholders})
         """, stock_codes)
         price_rows = cur.fetchall()
-        conn.close()
 
         price_map = {}
         change_map = {}
@@ -1085,6 +1089,8 @@ def signal_alerts():
         import traceback
         traceback.print_exc()
         return jsonify({'success': False, 'error': str(e)}), 500
+    finally:
+        put_db(conn)
 
 
 def _is_scan_running():
@@ -1127,13 +1133,9 @@ def get_stock_score_detail(code):
 def get_scan_status():
     """查询扫描进度"""
     try:
-        import psycopg2
+        conn = get_db()
-        from config import Config
+        if not conn:
-
+            return jsonify({'success': False, 'error': '数据库连接失败'}), 500
-        conn = psycopg2.connect(
-            host=Config.DB_HOST, port=Config.DB_PORT,
-            dbname=Config.DB_NAME, user=Config.DB_USER, password=Config.DB_PASSWORD,
-        )
         cur = conn.cursor()
 
         scan_date = datetime.now().strftime('%Y-%m-%d')
@@ -1143,7 +1145,8 @@ def get_scan_status():
         )
         scanned = cur.fetchone()[0]
 
-        cur.execute("SELECT count(*) FROM stock_realtime_price")
+        cur.execute("""SELECT count(*) FROM stock_realtime_price
+            WHERE name NOT LIKE '%%退%%' AND name NOT LIKE '%%ST%%' AND name NOT LIKE 'PT%%'""")
         total = cur.fetchone()[0]
 
         cur.execute(
@@ -1153,7 +1156,6 @@ def get_scan_status():
         triggered = cur.fetchone()[0]
 
         cur.close()
-        conn.close()
 
         return jsonify({
             'success': True,
@@ -1167,6 +1169,8 @@ def get_scan_status():
         })
     except Exception as e:
         return jsonify({'success': False, 'error': str(e)}), 500
+    finally:
+        put_db(conn)
 
 
 @bp.route('/start_full_scan', methods=['POST'])
@@ -1210,18 +1214,15 @@ def start_full_scan():
 def get_scan_strategy():
     """基于体系最强战法，给出分梯队买卖建议。与全景扫描推荐共用 _compute_recommend，算法一致。"""
     try:
-        import psycopg2
         from psycopg2.extras import RealDictCursor
-        from config import Config
 
         scan_date = request.args.get('date', datetime.now().strftime('%Y-%m-%d'))
         holding_codes_str = request.args.get('holding_codes', '')
         holding_set = set(c.strip() for c in holding_codes_str.split(',') if c.strip())
 
-        conn = psycopg2.connect(
+        conn = get_db()
-            host=Config.DB_HOST, port=Config.DB_PORT,
+        if not conn:
-            dbname=Config.DB_NAME, user=Config.DB_USER, password=Config.DB_PASSWORD,
+            return jsonify({'success': False, 'error': '数据库连接失败'}), 500
-        )
         cur = conn.cursor(cursor_factory=RealDictCursor)
 
         # 如果前端未指定日期，且当天无数据，自动回退到最近扫描日期
@@ -1241,7 +1242,6 @@ def get_scan_strategy():
         """, (scan_date,))
         rows = cur.fetchall()
         cur.close()
-        conn.close()
 
         tier1, tier2, tier3, tier4 = [], [], [], []
         for r in rows:
@@ -1322,10 +1322,12 @@ def get_scan_strategy():
         })
     except Exception as e:
         return jsonify({'success': False, 'error': str(e)}), 500
+    finally:
+        put_db(conn)
 
 
 def _get_kline_data(stock_code, days=120):
-    """获取K线数据 — 委托给 services.stock_algorithms.get_kline_data（实时分析不用本地DB缓存）"""
+    """获取K线数据 — 实时检测使用外部API获取最新数据，与扫描结果（本地DB快照）形成互补"""
     return algo_get_kline_data(stock_code, days=days, use_local_db=False)
 
 
@@ -1345,19 +1347,16 @@ def get_bull_stocks():
         stage: 可选，筛选特定阶段(1-5)
         holdingStocks: 可选，持仓代码逗号分隔
     """
-    import psycopg2
     from psycopg2.extras import RealDictCursor
-    from config import Config
 
     try:
         stage_filter = request.args.get('stage', type=int, default=0)
         holding_str = request.args.get('holdingStocks', '')
         holding_codes = set(holding_str.split(',')) if holding_str else set()
 
-        conn = psycopg2.connect(
+        conn = get_db()
-            host=Config.DB_HOST, port=Config.DB_PORT,
+        if not conn:
-            dbname=Config.DB_NAME, user=Config.DB_USER, password=Config.DB_PASSWORD,
+            return jsonify({'success': False, 'error': '数据库连接失败'}), 500
-        )
         cur = conn.cursor(cursor_factory=RealDictCursor)
 
         # 获取最近一次扫描数据（过滤退市/ST）
@@ -1376,8 +1375,6 @@ def get_bull_stocks():
         for p in cur.fetchall():
             price_map[p['code']] = {'price': float(p['price']), 'change_pct': float(p.get('change_pct') or 0)}
 
-        conn.close()
-
         # ---- 批量计算综合评分 ----
         scores_map = None
         try:
@@ -1439,6 +1436,8 @@ def get_bull_stocks():
         import traceback
         traceback.print_exc()
         return jsonify({'success': False, 'error': str(e)}), 500
+    finally:
+        put_db(conn)
 
 
 def _llm_polish_summary(stock_name, stock_code, ai_summary, score, verdict):

stock-html/routes/market.py

@@ -6,7 +6,7 @@ import pandas as pd
 from datetime import datetime, timedelta
 from services.stock_service import get_stock_fund_flow, load_cached_data
 from services.stock_algorithms import get_kline_data as algo_get_kline_data
-from db import get_db
+from db import get_db, put_db
 
 bp = Blueprint('market', __name__, url_prefix='/api')
 
@@ -40,7 +40,7 @@ def db_realtime_price(stock_code):
             'data': dict(row)
         })
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/db/realtime_prices', methods=['POST'])
@@ -71,7 +71,7 @@ def db_realtime_prices():
             'data': [dict(row) for row in rows]
         })
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/db/fund_flow_today/<stock_code>', methods=['GET'])
@@ -102,7 +102,7 @@ def db_fund_flow_today(stock_code):
             'data': dict(row)
         })
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/db/fund_flow_today_batch', methods=['POST'])
@@ -135,7 +135,7 @@ def db_fund_flow_today_batch():
             'data': [dict(row) for row in rows]
         })
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/db/data_status', methods=['GET'])
@@ -171,7 +171,7 @@ def db_data_status():
             'recent_logs': [dict(log) for log in logs]
         })
     finally:
-        conn.close()
+        put_db(conn)
 
 
 # ============ 原有API（兼容） ============
@@ -305,7 +305,7 @@ def get_fund_flow_rank():
                 return jsonify({'success': True, 'data': flow_data, 'total': len(flow_data),
                                 'source': 'cache'})
             finally:
-                _conn.close()
+                put_db(_conn)
         
         return jsonify({'success': True, 'data': [], 'total': 0})
     except Exception as e:
@@ -324,6 +324,7 @@ def get_fundamental(stock_code):
         realtime_data = None
         signal_data = None
         
+        conn = None
         try:
             conn = get_db()
             if conn:
@@ -388,10 +389,10 @@ def get_fundamental(stock_code):
                         'indicators': ind,
                         'triggered_count': sig_row[2] or 0,
                     }
-                
-                conn.close()
         except Exception as e:
             print(f"获取数据失败: {e}")
+        finally:
+            put_db(conn)
         
         # 优先从数据库获取当日缓存
         cached = db_get_fundamental(stock_code)
@@ -484,7 +485,7 @@ def get_fundamental(stock_code):
             # 备用方案：先试腾讯API，再试akshare
             try:
                 import requests as _rq
-                _tc = ('sh' if stock_code.startswith('6') else 'sz') + stock_code
+                _tc = ('sh' if stock_code.startswith('6') else 'bj' if stock_code.startswith(('8', '9')) else 'sz') + stock_code
                 _rr = _rq.get(f'http://qt.gtimg.cn/q={_tc}', timeout=5,
                               headers={'Referer': 'https://finance.qq.com'})
                 if _rr.status_code == 200 and '\"' in _rr.text:

stock-html/routes/sim_trade.py

@@ -4,7 +4,7 @@
 """
 from flask import Blueprint, request, jsonify
 from datetime import datetime, date, time
-from db import get_db, login_required, get_current_user_id
+from db import get_db, put_db, login_required, get_current_user_id
 from psycopg2.extras import RealDictCursor
 
 bp = Blueprint('sim_trade', __name__, url_prefix='/api/sim')
@@ -29,7 +29,7 @@ def init_user_config(user_id):
         cur.execute("SELECT * FROM sim_config WHERE user_id = %s", (user_id,))
         return cur.fetchone()
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/config', methods=['GET'])
@@ -82,7 +82,7 @@ def update_config():
         conn.rollback()
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/trades', methods=['GET'])
@@ -114,7 +114,7 @@ def get_trades():
         trades = cur.fetchall()
         return jsonify({'success': True, 'trades': trades})
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/positions', methods=['GET'])
@@ -140,7 +140,7 @@ def get_positions():
         positions = cur.fetchall()
         return jsonify({'success': True, 'positions': positions})
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/stats', methods=['GET'])
@@ -261,7 +261,7 @@ def get_stats():
             'history': list(reversed(history)) if history else []
         })
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/execute', methods=['POST'])
@@ -381,7 +381,7 @@ def execute_trade():
         traceback.print_exc()
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/auto_execute', methods=['POST'])
@@ -532,7 +532,7 @@ def auto_execute():
         traceback.print_exc()
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/update_prices', methods=['POST'])
@@ -588,7 +588,7 @@ def update_prices():
         conn.rollback()
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/reset', methods=['POST'])
@@ -612,7 +612,7 @@ def reset_simulation():
         conn.rollback()
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/trigger_trade', methods=['POST'])
@@ -623,12 +623,12 @@ def trigger_trade():
     
     try:
         # 优先使用智能引擎
+        smart_conn = None
         try:
             from services.smart_trade_engine import execute_smart_trade
-            conn = get_db()
+            smart_conn = get_db()
-            if conn:
+            if smart_conn:
-                result = execute_smart_trade(conn, user_id, scan_date=None)
+                result = execute_smart_trade(smart_conn, user_id, scan_date=None)
-                conn.close()
                 if result.get('success'):
                     results = result.get('results', [])
                     buy_count = len([r for r in results if r['type'] == 'buy'])
@@ -641,19 +641,29 @@ def trigger_trade():
                     })
         except Exception as e:
             print(f"[trigger_trade] 智能引擎异常，降级: {e}")
+        finally:
+            if smart_conn:
+                put_db(smart_conn)
         
         # 降级: 使用旧引擎
         from services.scheduler import execute_auto_trade_for_user
         
+        conn = None
+        try:
             conn = get_db()
             if conn:
                 cur = conn.cursor(cursor_factory=RealDictCursor)
                 cur.execute("SELECT trade_quantity FROM sim_config WHERE user_id = %s", (user_id,))
                 config = cur.fetchone()
                 trade_quantity = config['trade_quantity'] if config else 1000
-            conn.close()
             else:
                 trade_quantity = 1000
+        except Exception as e:
+            print(f"[trigger_trade] 获取交易配置失败: {e}")
+            trade_quantity = 1000
+        finally:
+            if conn:
+                put_db(conn)
         
         result = execute_auto_trade_for_user(user_id, trade_quantity)
         
@@ -730,4 +740,4 @@ def get_today_trades():
             }
         })
     finally:
-        conn.close()
+        put_db(conn)

stock-html/routes/smart_trade.py

@@ -4,7 +4,7 @@
 """
 from flask import Blueprint, request, jsonify
 from datetime import date
-from db import get_db, login_required, get_current_user_id
+from db import get_db, put_db, login_required, get_current_user_id
 from psycopg2.extras import RealDictCursor
 
 bp = Blueprint('smart_trade', __name__, url_prefix='/api/smart')
@@ -43,7 +43,7 @@ def get_algo_templates():
     except Exception as e:
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 # ═══════════════════════════════════════════════════════
@@ -78,7 +78,7 @@ def get_algo_config():
         traceback.print_exc()
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/config', methods=['POST'])
@@ -111,7 +111,7 @@ def save_algo_config():
         traceback.print_exc()
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 @bp.route('/apply_template', methods=['POST'])
@@ -139,7 +139,7 @@ def apply_template():
         conn.rollback()
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 # ═══════════════════════════════════════════════════════
@@ -164,7 +164,7 @@ def get_status():
         traceback.print_exc()
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 # ═══════════════════════════════════════════════════════
@@ -205,7 +205,7 @@ def trigger_smart_trade():
         traceback.print_exc()
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 # ═══════════════════════════════════════════════════════
@@ -242,7 +242,7 @@ def get_signals():
     except Exception as e:
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)
 
 
 # ═══════════════════════════════════════════════════════
@@ -284,4 +284,4 @@ def get_position_meta():
         traceback.print_exc()
         return jsonify({'success': False, 'error': str(e)}), 500
     finally:
-        conn.close()
+        put_db(conn)

stock-html/routes/trades.py

@@ -130,7 +130,6 @@ def update_trade(trade_id):
         """, (trade_id, user_id))
         old_trade = cur.fetchone()
         if not old_trade:
-            put_db(conn)
             return jsonify({'error': '交易记录不存在'}), 404
 
         cur.execute("""
@@ -152,7 +151,6 @@ def update_trade(trade_id):
         trade = cur.fetchone()
         if not trade:
             conn.rollback()
-            put_db(conn)
             return jsonify({'error': '交易记录不存在'}), 404
 
         old_delta = _calc_cash_delta(old_trade.get('trade_type'), old_trade.get('price'), old_trade.get('quantity'))
@@ -194,7 +192,6 @@ def delete_trade(trade_id):
         """, (trade_id, user_id))
         old_trade = cur.fetchone()
         if not old_trade:
-            put_db(conn)
             return jsonify({'success': False, 'error': '交易记录不存在'}), 404
 
         cur.execute("DELETE FROM trades WHERE id = %s AND user_id = %s", (trade_id, user_id))
@@ -306,7 +303,7 @@ def check_stoploss():
                     current_price = 0
                     try:
                         import requests as _rq
-                        _tc = ('sh' if code.startswith('6') else 'sz') + code
+                        _tc = ('sh' if code.startswith('6') else 'bj' if code.startswith(('8', '9')) else 'sz') + code
                         _rr = _rq.get(f'http://qt.gtimg.cn/q={_tc}', timeout=5,
                                       headers={'Referer': 'https://finance.qq.com'})
                         if _rr.status_code == 200 and '\"' in _rr.text:

stock-html/services/fund_flow_analyzer.py

@@ -155,6 +155,39 @@ def _get_fund_flow_from_mairui(stock_code, days=10):
                 'small_net_inflow_pct': small_net_pct,
             })
 
+        # 从本地DB补充 close_price 和 change_pct（避免全为0导致量价背离误判）
+        from db import get_db, put_db
+        conn = get_db()
+        if conn:
+            try:
+                cur = conn.cursor()
+                date_list = [r['date'] for r in records if r['date']]
+                if date_list:
+                    cur.execute("""
+                        SELECT k.trade_date::text, k.close,
+                               CASE WHEN prev.close > 0
+                                    THEN ROUND((k.close - prev.close) / prev.close * 100, 2)
+                                    ELSE 0 END AS change_pct
+                        FROM stock_kline_daily k
+                        LEFT JOIN LATERAL (
+                            SELECT close FROM stock_kline_daily
+                            WHERE code = k.code AND trade_date < k.trade_date
+                            ORDER BY trade_date DESC LIMIT 1
+                        ) prev ON true
+                        WHERE k.code = %s AND k.trade_date::text = ANY(%s)
+                    """, (stock_code, date_list))
+                    price_map = {r[0]: {'close': float(r[1] or 0), 'change_pct': float(r[2] or 0)}
+                                 for r in cur.fetchall()}
+                    for r in records:
+                        info = price_map.get(r['date'])
+                        if info:
+                            r['close_price'] = info['close']
+                            r['change_pct'] = info['change_pct']
+            except Exception as e:
+                logger.warning(f"补充K线价格失败({stock_code}): {e}")
+            finally:
+                put_db(conn)
+
         # 按日期升序排列
         records.sort(key=lambda x: x['date'])
         logger.info(f"麦蕊API获取{stock_code}资金流向{len(records)}条")
@@ -245,6 +278,9 @@ def analyze_fund_flow(stock_code, days=5):
     # 出货：主力净流出但价格不跌（跌幅<2%）
     accumulation = False
     distribution = False
+    # 检查是否有有效的价格数据（close_price 全为0说明数据不完整，跳过背离检测）
+    has_valid_price = any(r.get('close_price', 0) > 0 for r in recent)
+    if has_valid_price:
         if total_main_inflow > 0:
             price_changes = [r['change_pct'] for r in recent]
             avg_price_change = sum(price_changes) / len(price_changes) if price_changes else 0

stock-html/services/mairui_api.py

@@ -245,17 +245,21 @@ def get_fund_flow(stock_code, days=3):
         flow_data = []
         for item in data:
             # 计算主力净流入 = 主买大单+主买特大单 - 主卖大单-主卖特大单
-            main_buy = float(item.get('zmbddcje', 0)) + float(item.get('zmbtdcje', 0))
+            main_buy = float(item.get('zmbddcje', 0) or 0) + float(item.get('zmbtdcje', 0) or 0)
-            main_sell = float(item.get('zmsddcje', 0)) + float(item.get('zmstdcje', 0))
+            main_sell = float(item.get('zmsddcje', 0) or 0) + float(item.get('zmstdcje', 0) or 0)
             main_net = main_buy - main_sell
 
+            # 日期解析：与 fund_flow_analyzer.py 保持一致，用字符串截取
+            t_str = str(item.get('t', ''))
+            date_str = t_str[:10] if t_str else ''
+
             flow_data.append({
-                'date': datetime.fromtimestamp(item.get('t', 0)).strftime('%Y-%m-%d') if item.get('t') else '',
+                'date': date_str,
                 'main_net_inflow': main_net,
-                'super_buy': float(item.get('zmbtdcje', 0)),
+                'super_buy': float(item.get('zmbtdcje', 0) or 0),
-                'super_sell': float(item.get('zmstdcje', 0)),
+                'super_sell': float(item.get('zmstdcje', 0) or 0),
-                'big_buy': float(item.get('zmbddcje', 0)),
+                'big_buy': float(item.get('zmbddcje', 0) or 0),
-                'big_sell': float(item.get('zmsddcje', 0)),
+                'big_sell': float(item.get('zmsddcje', 0) or 0),
             })
         return {'success': True, 'data': flow_data}
     

stock-html/services/news_analyzer.py

@@ -456,6 +456,7 @@ def analyze_policy_impact(policy_news):
         affected[category] = impact
 
     # 尝试用LLM深度分析重大政策
+    llm_summary = None
     major_policies = [n for n in policy_news if n['category'] in ['行业扶持', '行业监管', '货币政策']]
     if major_policies and len(major_policies) <= 5:
         try:
@@ -463,14 +464,17 @@ def analyze_policy_impact(policy_news):
             if llm_result:
                 score = llm_result.get('score', score)
                 reasons = llm_result.get('reasons', reasons)
+                llm_summary = llm_result.get('summary')
         except Exception as e:
             logger.warning(f"LLM政策分析失败: {e}")
 
     score = max(-10, min(10, score))
 
-    if positive_count > negative_count:
+    if llm_summary:
+        summary = llm_summary
+    elif score > 0:
         summary = f'近期{len(policy_news)}条政策消息，偏利好（{positive_count}条利好/{negative_count}条利空）'
-    elif negative_count > positive_count:
+    elif score < 0:
         summary = f'近期{len(policy_news)}条政策消息，偏利空（{negative_count}条利空/{positive_count}条利好）'
     else:
         summary = f'近期{len(policy_news)}条政策消息，影响中性'

stock-html/services/scheduler.py

@@ -101,7 +101,7 @@ def is_trading_time():
 
 def get_all_users():
     """获取所有启用自动交易的用户"""
-    from db import get_db
+    from db import get_db, put_db
     from psycopg2.extras import RealDictCursor
     
     conn = get_db()
@@ -121,7 +121,7 @@ def get_all_users():
         print(f"[定时任务] 获取用户列表失败: {e}")
         return []
     finally:
-        conn.close()
+        put_db(conn)
 
 
 # 自定义股票列表（100只精选股票）
@@ -168,7 +168,7 @@ def execute_auto_trade_for_user(user_id, trade_quantity=1000, scan_date=None):
     
     scan_date: 使用哪天的扫描数据, None则自动选择最近可用的
     """
-    from db import get_db
+    from db import get_db, put_db
     from psycopg2.extras import RealDictCursor
 
     print(f"[定时任务] 开始为用户{user_id}执行策略交易（统一推荐算法）...")
@@ -407,7 +407,7 @@ def execute_auto_trade_for_user(user_id, trade_quantity=1000, scan_date=None):
         traceback.print_exc()
         return {'error': str(e)}
     finally:
-        conn.close()
+        put_db(conn)
 
 
 def _get_latest_price(stock_code):
@@ -417,7 +417,7 @@ def _get_latest_price(stock_code):
 
 def update_positions_price_for_user(user_id):
     """更新用户持仓的当前价格（收盘时调用）— 使用腾讯财经API"""
-    from db import get_db
+    from db import get_db, put_db
     from psycopg2.extras import RealDictCursor
     
     conn = get_db()
@@ -443,6 +443,8 @@ def update_positions_price_for_user(user_id):
                 for c in codes:
                     if c.startswith('6'):
                         tencent_codes.append(f'sh{c}')
+                    elif c.startswith('8') or c.startswith('9'):
+                        tencent_codes.append(f'bj{c}')
                     else:
                         tencent_codes.append(f'sz{c}')
                 _r = _req.get(f'http://qt.gtimg.cn/q={",".join(tencent_codes)}',
@@ -492,7 +494,7 @@ def update_positions_price_for_user(user_id):
         conn.rollback()
         print(f"[定时任务] 更新用户{user_id}持仓价格失败: {e}")
     finally:
-        conn.close()
+        put_db(conn)
 
 
 def job_morning_trade():
@@ -512,19 +514,22 @@ def job_morning_trade():
     for user in users:
         user_id = user['user_id']
         # 尝试使用智能引擎
+        smart_conn = None
         try:
             from services.smart_trade_engine import execute_smart_trade
-            from db import get_db
+            from db import get_db, put_db
-            conn = get_db()
+            smart_conn = get_db()
-            if conn:
+            if smart_conn:
-                result = execute_smart_trade(conn, user_id, scan_date=None)
+                result = execute_smart_trade(smart_conn, user_id, scan_date=None)
-                conn.close()
                 if result.get('success'):
                     print(f"[定时任务] 用户{user_id} 智能引擎执行成功 "
                           f"(算法:{result.get('algo','?')}, 信号:{result.get('signals',0)})")
                     continue
         except Exception as e:
             print(f"[定时任务] 用户{user_id} 智能引擎异常，降级到旧引擎: {e}")
+        finally:
+            if smart_conn:
+                put_db(smart_conn)
 
         # 降级：使用旧引擎
         trade_quantity = user.get('trade_quantity') or 1000
@@ -551,18 +556,21 @@ def job_afternoon_trade():
     for user in users:
         user_id = user['user_id']
         # 尝试使用智能引擎
+        smart_conn = None
         try:
             from services.smart_trade_engine import execute_smart_trade
-            from db import get_db
+            from db import get_db, put_db
-            conn = get_db()
+            smart_conn = get_db()
-            if conn:
+            if smart_conn:
-                result = execute_smart_trade(conn, user_id, scan_date=today)
+                result = execute_smart_trade(smart_conn, user_id, scan_date=today)
-                conn.close()
                 if result.get('success'):
                     print(f"[定时任务] 用户{user_id} 午后智能引擎执行成功")
                     continue
         except Exception as e:
             print(f"[定时任务] 用户{user_id} 智能引擎异常，降级: {e}")
+        finally:
+            if smart_conn:
+                put_db(smart_conn)
         trade_quantity = user.get('trade_quantity') or 1000
         execute_auto_trade_for_user(user_id, trade_quantity, scan_date=today)
     
@@ -645,7 +653,7 @@ def trigger_afternoon_trade():
 
 def trigger_closing_update():
     """手动触发收盘更新（仅更新持仓价格）"""
-    from db import get_db
+    from db import get_db, put_db
     if not is_trading_day():
         print("[定时任务] 今天不是交易日，跳过")
         return

stock-html/services/score_engine.py

@@ -134,10 +134,16 @@ def compute_comprehensive_score(stock_code, stock_name, technical_score, df=None
     external_score = 0
     summaries = []
 
-    # ---- P0: 主力资金进出 ----
+    # ---- P0: 主力资金进出（带30分钟缓存，与批量模式一致）----
     try:
+        now = time.time()
+        cached_ff = _fund_flow_cache.get(stock_code)
+        if cached_ff and (now - cached_ff[1]) < _FUND_FLOW_TTL:
+            fund_result = cached_ff[0]
+        else:
             from services.fund_flow_analyzer import analyze_fund_flow
             fund_result = analyze_fund_flow(stock_code, days=5)
+            _fund_flow_cache[stock_code] = (fund_result, now)
         factors['fund_flow'] = fund_result
         external_score += fund_result.get('score', 0)
         all_reasons.extend(fund_result.get('reasons', []))

stock-html/services/signal_detector.py

@@ -340,6 +340,8 @@ def detect_all_signals(df, lookback=5):
         if not np.issubdtype(df[col].dtype, np.floating):
             df[col] = pd.to_numeric(df[col], errors='coerce').fillna(0).astype(np.float64)
 
+    # 若已有指标列则跳过重复计算（deep_analyze 等场景预计算过）
+    if 'dif' not in df.columns or 'ma5' not in df.columns:
         df = calc_all_indicators(df)
 
     all_signals = []

stock-html/services/smart_trade_engine.py

@@ -501,7 +501,7 @@ def generate_sell_decisions(conn, user_id, config, current_prices, scan_map=None
         if current_shares <= 0:
             continue
 
-        profit_pct_now = (price - buy_price) / buy_price * 100
+        profit_pct_now = (price - buy_price) / buy_price * 100 if buy_price > 0 else 0
         days_held = pos.get('days_held', 0) or 0
         print(f"  {code} 成本{buy_price:.2f} 现价{price:.2f} 盈亏{profit_pct_now:+.1f}% 持仓{days_held}天")
         consec_up = pos.get('consecutive_up_days', 0) or 0
@@ -1003,7 +1003,7 @@ def execute_smart_trade(conn, user_id, scan_date=None):
                 log_signal(conn, user_id, today, code, pos['stock_name'],
                            'partial_sell', dec['reason'], dec['rule'],
                            price, pos['avg_cost'],
-                           (price - pos['avg_cost']) / pos['avg_cost'] * 100,
+                           (price - pos['avg_cost']) / pos['avg_cost'] * 100 if pos['avg_cost'] else 0,
                            True, price, shares)
 
                 results.append({
@@ -1052,7 +1052,7 @@ def execute_smart_trade(conn, user_id, scan_date=None):
                 log_signal(conn, user_id, today, code, pos['stock_name'],
                            'sell', dec['reason'], dec['rule'],
                            price, pos['avg_cost'],
-                           (price - pos['avg_cost']) / pos['avg_cost'] * 100,
+                           (price - pos['avg_cost']) / pos['avg_cost'] * 100 if pos['avg_cost'] else 0,
                            True, price, qty)
 
                 results.append({

stock-html/services/stock_algorithms.py

@@ -165,28 +165,30 @@ def get_kline_data(stock_code, days=120, use_local_db=True):
 
 
 def _get_kline_from_local_db(stock_code, days=120):
-    """从本地数据库读取K线（最快，毫秒级）"""
+    """从本地数据库读取K线（最快，毫秒级）
+    使用 LIMIT 限制交易日条数，与外部 API 的 limit=days 行为一致。
+    """
     import pandas as pd
     try:
         from db import get_db, put_db
         conn = get_db()
         if not conn:
             return None
-        conn.autocommit = True
-        start_date = (datetime.now() - timedelta(days=days)).strftime('%Y-%m-%d')
         try:
             with conn.cursor() as cur:
                 cur.execute("""
                     SELECT trade_date, open, high, low, close, volume
                     FROM stock_kline_daily
-                    WHERE code = %s AND trade_date >= %s
+                    WHERE code = %s
-                    ORDER BY trade_date
+                    ORDER BY trade_date DESC
-                """, (stock_code, start_date))
+                    LIMIT %s
+                """, (stock_code, min(days, 300)))
                 rows = cur.fetchall()
         finally:
             put_db(conn)
 
         if rows and len(rows) >= 30:
+            rows = list(reversed(rows))
             df = pd.DataFrame(rows, columns=['date', 'open', 'high', 'low', 'close', 'volume'])
             df['date'] = df['date'].astype(str)
             for col in ('open', 'high', 'low', 'close', 'volume'):
@@ -202,7 +204,9 @@ _thread_local = threading.local()
 
 
 def get_kline_from_local_db_threaded(stock_code, days=120):
-    """多线程扫描专用：使用线程本地连接从本地DB读取K线"""
+    """多线程扫描专用：使用线程本地连接从本地DB读取K线
+    使用 LIMIT 限制交易日条数，与外部 API 的 limit=days 行为一致。
+    """
     import pandas as pd
     try:
         conn = getattr(_thread_local, 'kline_conn', None)
@@ -215,17 +219,18 @@ def get_kline_from_local_db_threaded(stock_code, days=120):
             conn.autocommit = True
             _thread_local.kline_conn = conn
 
-        start_date = (datetime.now() - timedelta(days=days)).strftime('%Y-%m-%d')
         with conn.cursor() as cur:
             cur.execute("""
                 SELECT trade_date, open, high, low, close, volume
                 FROM stock_kline_daily
-                WHERE code = %s AND trade_date >= %s
+                WHERE code = %s
-                ORDER BY trade_date
+                ORDER BY trade_date DESC
-            """, (stock_code, start_date))
+                LIMIT %s
+            """, (stock_code, min(days, 300)))
             rows = cur.fetchall()
 
         if rows and len(rows) >= 30:
+            rows = list(reversed(rows))
             df = pd.DataFrame(rows, columns=['date', 'open', 'high', 'low', 'close', 'volume'])
             df['date'] = df['date'].astype(str)
             for col in ('open', 'high', 'low', 'close', 'volume'):
@@ -962,8 +967,8 @@ def _generate_plain_summary(price, change_pct, ma_trend, position, supports,
     parts.append(trend_desc + '。')
 
     # 2. 价格位置（用大白话）
-    pos_20 = position.get('20d', {})
+    pos_20 = position.get('d20', {})
-    pct_20 = pos_20.get('pct', 50)
+    pct_20 = pos_20.get('range_pct', 50)
     if pct_20 > 80:
         parts.append(f'当前股价处于近20天的高位区间（{pct_20:.0f}%位置），已经涨了不少，追高要小心。')
     elif pct_20 > 50:

stock-html/services/stock_service.py

@@ -7,11 +7,16 @@ from datetime import datetime, timedelta
 import traceback
 import json
 import os
+import time
+import threading
 from config import Config
 
 
 # ========== 股票名称缓存 ==========
 _stock_name_cache = {}
+_name_cache_dirty = False
+_name_cache_last_save = 0.0
+_name_cache_lock = threading.Lock()
 
 
 def _load_stock_name_cache():
@@ -26,32 +31,61 @@ def _load_stock_name_cache():
         print(f"加载股票名称缓存失败: {e}")
 
 
-def _save_stock_name_cache():
+def _save_stock_name_cache(force=False):
-    """保存股票名称缓存到本地"""
+    """保存股票名称缓存到本地（延迟批量保存，60秒去抖）"""
+    global _name_cache_dirty, _name_cache_last_save
+    if not force and not _name_cache_dirty:
+        return
+    now = time.time()
+    if not force and (now - _name_cache_last_save) < 60:
+        return
+    with _name_cache_lock:
         try:
             with open(Config.STOCK_NAME_CACHE_FILE, 'w', encoding='utf-8') as f:
                 json.dump(_stock_name_cache, f, ensure_ascii=False, indent=2)
+            _name_cache_dirty = False
+            _name_cache_last_save = now
         except Exception as e:
             print(f"保存股票名称缓存失败: {e}")
 
 
 def get_stock_name(stock_code):
-    """获取股票名称 — 使用腾讯财经API"""
+    """获取股票名称 — 优先内存缓存 → DB stock_realtime_price → 腾讯财经API"""
-    global _stock_name_cache
+    global _stock_name_cache, _name_cache_dirty
 
     if stock_code in _stock_name_cache:
         return _stock_name_cache[stock_code]
 
-    # 腾讯财经API获取股票名称
+    # 优先从数据库 stock_realtime_price 表查（毫秒级）
+    try:
+        from db import get_db, put_db
+        conn = get_db()
+        if conn:
+            try:
+                with conn.cursor() as cur:
+                    cur.execute("SELECT name FROM stock_realtime_price WHERE code = %s", (stock_code,))
+                    row = cur.fetchone()
+                    if row and row[0]:
+                        _stock_name_cache[stock_code] = row[0]
+                        _name_cache_dirty = True
+                        _save_stock_name_cache()
+                        return row[0]
+            finally:
+                put_db(conn)
+    except Exception:
+        pass
+
+    # 回退到腾讯财经API
     try:
         import requests as _req
-        tcode = ('sh' if stock_code.startswith('6') else 'sz') + stock_code
+        tcode = ('sh' if stock_code.startswith('6') else 'bj' if stock_code.startswith(('8', '9')) else 'sz') + stock_code
         _r = _req.get(f'http://qt.gtimg.cn/q={tcode}', timeout=5,
                       headers={'Referer': 'https://finance.qq.com'})
         if _r.status_code == 200 and '\"' in _r.text:
             _fields = _r.text.split('\"')[1].split('~')
             if len(_fields) > 2 and _fields[1]:
                 _stock_name_cache[stock_code] = _fields[1]
+                _name_cache_dirty = True
                 _save_stock_name_cache()
                 return _fields[1]
     except Exception as e:
@@ -119,6 +153,8 @@ def get_stock_fund_flow(stock_code, start_date, end_date, force_refresh=False):
             market = 'sh'
         elif stock_code.startswith('0') or stock_code.startswith('3'):
             market = 'sz'
+        elif stock_code.startswith('8') or stock_code.startswith('9'):
+            market = 'bj'
         else:
             return None, None, "无法识别股票代码所属市场"
         
@@ -313,7 +349,7 @@ def get_realtime_price(stock_code):
     # 备用方案2：使用腾讯财经API（腾讯云可用）
     try:
         import requests as _req
-        tcode = ('sh' if stock_code.startswith('6') else 'sz') + stock_code
+        tcode = ('sh' if stock_code.startswith('6') else 'bj' if stock_code.startswith(('8', '9')) else 'sz') + stock_code
         _r = _req.get(f'http://qt.gtimg.cn/q={tcode}', timeout=5,
                       headers={'Referer': 'https://finance.qq.com'})
         if _r.status_code == 200 and '\"' in _r.text:

stock-html/static/css/scan.css

@@ -655,6 +655,32 @@
 .scan-pagination button:disabled { opacity: 0.3; cursor: not-allowed; }
 .scan-pagination span { font-size: 13px; color: var(--text-secondary); }
 
+/* 结果列表可收起 header */
+.full-scan-list-section {
+    margin-top: 8px;
+}
+.scan-list-header {
+    display: flex;
+    justify-content: space-between;
+    align-items: center;
+    padding: 8px 12px;
+    cursor: pointer;
+    border-radius: 8px;
+    background: rgba(255,255,255,0.03);
+    transition: background 0.15s;
+}
+.scan-list-header:hover { background: rgba(255,255,255,0.06); }
+.scan-list-title {
+    font-size: 13px;
+    font-weight: 600;
+    color: var(--text-secondary);
+}
+.scan-list-title small {
+    font-weight: 400;
+    color: var(--text-muted);
+    margin-left: 4px;
+}
+
 .admin-link-btn {
     display: block;
     text-align: center;

stock-html/static/js/app.js

@@ -86,10 +86,12 @@
                     fullScanLoading: false,
                     fullScanPage: 1,
                     fullScanTotalPages: 1,
+                    fullScanPerPage: 5,           // 每页显示5只股票
                     fullScanFilter: 'all',
                     fullScanFilterTypes: [],
                     fullScanFilterRecommend: '买入',  // 扫描结果打开时缺省显示买入列表；all|买入|加仓|卖出|持有|关注|观察|观望
                     scanSummaryCollapsed: false,
+                    scanResultsCollapsed: false,   // 结果列表可收起
                     fullScanSignalDist: [],
                     
                     // 找牛股（保留兼容）
@@ -2253,7 +2255,7 @@
                         const resp = await axios.get('/api/scan_results', {
                             params: {
                                 page: this.fullScanPage,
-                                per_page: 50,
+                                per_page: this.fullScanPerPage,
                                 min_triggered: minTriggered,
                                 signal_type: signalTypes,
                                 holding_codes: (this.holdingStocks || []).join(','),

stock-html/sync_kline.py

@@ -60,6 +60,7 @@ def get_all_stock_codes(conn):
             SELECT code, name FROM stock_realtime_price
             WHERE volume > 0 AND price > 0
               AND name NOT LIKE '%%退%%'
+              AND name NOT LIKE '%%ST%%'
               AND name NOT LIKE 'PT%%'
             ORDER BY code
         """)

stock-html/sync_kline_5min.py

@@ -243,8 +243,9 @@ def fetch_5min_kline_sina(code):
                 l = float(row.get('low', 0))
                 c = float(row.get('close', 0))
                 v = int(float(row.get('volume', 0)))
+                amt = float(row.get('amount', 0))
 
-                rows.append((code, dt, o, h, l, c, v, 0.0, 0.0))
+                rows.append((code, dt, o, h, l, c, v, amt, 0.0))
             return rows if rows else None
 
         except (IndexError, KeyError, ValueError):
@@ -366,7 +367,8 @@ def fetch_5min_kline_tencent(code):
                 dt = datetime(today.year, today.month, today.day, h, m, 0)
             except (ValueError, IndexError):
                 continue
-            min_data.append((dt, price, vol))
+            amt = float(parts[3]) if len(parts) > 3 else 0.0
+            min_data.append((dt, price, vol, amt))
 
         if not min_data:
             return None
@@ -375,26 +377,30 @@ def fetch_5min_kline_tencent(code):
         # 5分钟窗口: 09:30-09:35, 09:35-09:40, ...
         from collections import defaultdict
         bars = defaultdict(list)
-        for dt, price, vol in min_data:
+        for dt, price, vol, amt in min_data:
             # 5分钟窗口起始时间
             minute = dt.minute
             bar_min = (minute // 5) * 5
             bar_dt = dt.replace(minute=bar_min, second=0)
-            bars[bar_dt].append((price, vol))
+            bars[bar_dt].append((price, vol, amt))
 
         rows = []
         prev_vol = 0
+        prev_amt = 0
         for bar_dt in sorted(bars.keys()):
             ticks = bars[bar_dt]
             o = ticks[0][0]     # 第一个价格
             c = ticks[-1][0]    # 最后一个价格
-            h = max(p for p, _ in ticks)
+            h = max(p for p, _, _ in ticks)
-            l = min(p for p, _ in ticks)
+            l = min(p for p, _, _ in ticks)
-            # 腾讯的volume是累积值，取窗口最后的 - 窗口最前的之前
+            # 腾讯的volume和amount是累积值，取窗口最后的 - 前一窗口最后的
             last_vol = ticks[-1][1]
             bar_vol = last_vol - prev_vol if prev_vol > 0 else ticks[-1][1]
             prev_vol = last_vol
-            rows.append((code, bar_dt, o, h, l, c, max(0, bar_vol), 0.0, 0.0))
+            last_amt = ticks[-1][2]
+            bar_amt = last_amt - prev_amt if prev_amt > 0 else ticks[-1][2]
+            prev_amt = last_amt
+            rows.append((code, bar_dt, o, h, l, c, max(0, bar_vol), max(0, bar_amt), 0.0))
 
         return rows if rows else None
 

stock-html/templates/index.html

@@ -25,7 +25,7 @@
     <link rel="stylesheet" href="/static/css/components.css?v=20260718v1">
     <link rel="stylesheet" href="/static/css/auth.css?v=20260718v1">
     <link rel="stylesheet" href="/static/css/pages.css?v=20260719v2">
-    <link rel="stylesheet" href="/static/css/scan.css?v=20260719v5">
+    <link rel="stylesheet" href="/static/css/scan.css?v=20260722v1">
     <link rel="stylesheet" href="/static/css/responsive.css?v=20260719v1">
 </head>
 <body>
@@ -883,7 +883,12 @@
                             </div>
                         </div>
                     </div>
-                    <div class="full-scan-list">
+                    <div class="full-scan-list-section">
+                        <div class="scan-list-header" role="button" tabindex="0" :aria-expanded="!scanResultsCollapsed" @click="scanResultsCollapsed = !scanResultsCollapsed" @keyup.enter="scanResultsCollapsed = !scanResultsCollapsed">
+                            <span class="scan-list-title">推荐列表 <small v-if="fullScanTotalPages > 1">{{ fullScanPage }}/{{ fullScanTotalPages }}页</small></span>
+                            <span class="scan-summary-toggle">{{ scanResultsCollapsed ? '▶' : '▼' }}</span>
+                        </div>
+                    <div v-show="!scanResultsCollapsed" class="full-scan-list">
                         <div v-if="fullScanResultsFiltered.length === 0" class="scan-empty-hint">暂无符合条件的股票</div>
                         <div v-for="item in fullScanResultsFiltered" :key="item.code" class="scan-result-card"
                              :class="{ 'has-signal': item.triggered_count > 0, 'is-watched': searchHistory.some(h => h.code === item.code) }">
@@ -915,11 +920,11 @@
                             </div>
                             <div class="scan-holding-note" v-if="item.holding_note">{{ item.holding_note }}</div>
                         </div>
-                    </div>
                     <div v-if="fullScanTotalPages > 1" class="scan-pagination">
-                        <button type="button" @click="fetchFullScanResults(fullScanPage - 1)" :disabled="fullScanPage <= 1">上一页</button>
+                        <button type="button" @click.stop="fetchFullScanResults(fullScanPage - 1)" :disabled="fullScanPage <= 1">上一页</button>
                         <span>{{ fullScanPage }} / {{ fullScanTotalPages }}</span>
-                        <button type="button" @click="fetchFullScanResults(fullScanPage + 1)" :disabled="fullScanPage >= fullScanTotalPages">下一页</button>
+                        <button type="button" @click.stop="fetchFullScanResults(fullScanPage + 1)" :disabled="fullScanPage >= fullScanTotalPages">下一页</button>
+                    </div>
                     </div>
                 </template>
             </div>
@@ -2299,6 +2304,6 @@
     </div>
     
 {% endraw %}
-    <script src="/static/js/app.js?v=20260718v2"></script>
+    <script src="/static/js/app.js?v=20260722v1"></script>
 </body>
 </html>