From 1471bf806aab931329b98d47a071e416ab545b48 Mon Sep 17 00:00:00 2001
From: zzlgreat <zzlgreat@gmail.com>
Date: Sat, 13 Dec 2025 22:36:59 +0800
Subject: [PATCH] update pay ui

---
 app_vx.py | 65 +++++++++++++++++++++++++++----------------------------
 1 file changed, 32 insertions(+), 33 deletions(-)

diff --git a/app_vx.py b/app_vx.py
index d188ed51..c65f100d 100644
--- a/app_vx.py
+++ b/app_vx.py
@@ -4609,42 +4609,41 @@ def api_event_related_stocks(event_id):
         try:
             if stock_codes:
                 print(f"批量查询 {len(stock_codes)} 只股票的价格数据...")
+                print(f"  股票代码: {stock_codes}")
+                print(f"  时间范围: {start_datetime} 至 {end_datetime}")
 
-                # 3.1 批量查询价格和涨跌幅数据（使用子查询方式，避免窗口函数与 GROUP BY 冲突）
+                # 诊断：检查这些股票在 ClickHouse 中是否有数据
+                diag_query = """
+                    SELECT code, MIN(timestamp) as min_ts, MAX(timestamp) as max_ts, COUNT(*) as cnt
+                    FROM stock_minute
+                    WHERE code IN %(codes)s
+                    GROUP BY code
+                """
+                diag_result = client.execute(diag_query, {'codes': tuple(stock_codes)})
+                print(f"  诊断 - 各股票数据情况: {diag_result}")
+
+                # 3.1 批量查询价格和涨跌幅数据（简化版，避免 CTE 兼容性问题）
+                # 使用 argMin/argMax 聚合函数获取第一条和最后一条记录的值
                 batch_price_query = """
-                                    WITH first_prices AS (SELECT code,
-                                        close as first_price \
-                                       , ROW_NUMBER() OVER (PARTITION BY code ORDER BY timestamp ASC) as rn
-                                    FROM stock_minute
-                                    WHERE code IN %(codes)s
-                                      AND timestamp >= %(start)s
-                                      AND timestamp <= %(end)s
-                                        ) \
-                                        , last_prices AS (
-                                    SELECT
-                                        code, close as last_price, open as open_price, high as high_price, low as low_price, volume, amt as amount, ROW_NUMBER() OVER (PARTITION BY code ORDER BY timestamp DESC) as rn
-                                    FROM stock_minute
-                                    WHERE code IN %(codes)s
-                                      AND timestamp >= %(start)s
-                                      AND timestamp <= %(end)s
-                                        )
-                                    SELECT fp.code, \
-                                           fp.first_price, \
-                                           lp.last_price, \
-                                           (lp.last_price - fp.first_price) / fp.first_price * 100 as change_pct, \
-                                           lp.open_price, \
-                                           lp.high_price, \
-                                           lp.low_price, \
-                                           lp.volume, \
-                                           lp.amount
-                                    FROM first_prices fp
-                                             INNER JOIN last_prices lp ON fp.code = lp.code
-                                    WHERE fp.rn = 1 \
-                                      AND lp.rn = 1 \
-                                    """
+                    SELECT
+                        code,
+                        argMin(close, timestamp) as first_price,
+                        argMax(close, timestamp) as last_price,
+                        (argMax(close, timestamp) - argMin(close, timestamp)) / argMin(close, timestamp) * 100 as change_pct,
+                        argMax(open, timestamp) as open_price,
+                        max(high) as high_price,
+                        min(low) as low_price,
+                        sum(volume) as volume,
+                        sum(amt) as amount
+                    FROM stock_minute
+                    WHERE code IN %(codes)s
+                      AND timestamp >= %(start)s
+                      AND timestamp <= %(end)s
+                    GROUP BY code
+                """
 
                 price_data = client.execute(batch_price_query, {
-                    'codes': stock_codes,
+                    'codes': tuple(stock_codes),
                     'start': start_datetime,
                     'end': end_datetime
                 })
@@ -4691,7 +4690,7 @@ def api_event_related_stocks(event_id):
                                      """
 
                 minute_data = client.execute(minute_chart_query, {
-                    'codes': stock_codes,
+                    'codes': tuple(stock_codes),
                     'start': start_datetime,
                     'end': end_datetime
                 })