heropanel修改

app.py

@@ -11154,37 +11154,115 @@ def get_events_effectiveness_stats():
                 RelatedStock.event_id.in_(event_ids)
             ).all()
 
-            # 构建事件 ID 到事件的映射，用于获取涨跌幅
-            event_map = {e.id: e for e in events_query}
-
-            # 统计股票数量（去重），并关联事件涨跌幅
+            # 去重统计股票
             unique_stocks = {}
             for rs in related_stocks:
                 stock_key = rs.stock_code
-                # 获取关联事件的最大涨幅作为该股票的涨幅参考
-                event = event_map.get(rs.event_id)
-                event_max_chg = event.related_max_chg if event else 0
-
-                if stock_key not in unique_stocks:
+                if stock_key and stock_key not in unique_stocks:
                     unique_stocks[stock_key] = {
                         'stockCode': rs.stock_code,
                         'stockName': rs.stock_name,
-                        'maxChg': event_max_chg or 0,
                         'eventId': rs.event_id,
-                        'correlation': rs.correlation or 0,
                     }
-                else:
-                    # 保留最大涨幅的记录
-                    if (event_max_chg or 0) > unique_stocks[stock_key]['maxChg']:
-                        unique_stocks[stock_key]['maxChg'] = event_max_chg or 0
-                        unique_stocks[stock_key]['eventId'] = rs.event_id
 
             total_stocks = len(unique_stocks)
 
+            # 批量查询股票的实时涨跌幅（从 ClickHouse）
+            if unique_stocks:
+                try:
+                    client = get_clickhouse_client()
+
+                    # 标准化股票代码为 ClickHouse 格式
+                    def normalize_code(code):
+                        if not code:
+                            return None
+                        base = code.split('.')[0]
+                        if base.startswith('6'):
+                            return f"{base}.SH"
+                        elif base.startswith(('0', '3')):
+                            return f"{base}.SZ"
+                        return code
+
+                    normalized_codes = [normalize_code(c) for c in unique_stocks.keys() if c]
+                    normalized_codes = [c for c in normalized_codes if c]  # 过滤 None
+
+                    # 构建代码映射
+                    code_mapping = {}
+                    for orig_code in unique_stocks.keys():
+                        norm_code = normalize_code(orig_code)
+                        if norm_code:
+                            code_mapping[orig_code] = norm_code
+
+                    # 获取当前交易日的时间范围
+                    if hasattr(current_trading_day, 'strftime'):
+                        target_date = current_trading_day
+                    else:
+                        target_date = datetime.strptime(str(current_trading_day), '%Y-%m-%d').date()
+
+                    start_datetime = datetime.combine(target_date, dt_time(9, 30))
+                    end_datetime = datetime.combine(target_date, dt_time(15, 0))
+
+                    # 1. 从 ClickHouse 批量查询最新价格
+                    batch_price_query = """
+                        SELECT
+                            code,
+                            argMax(close, timestamp) as last_price
+                        FROM stock_minute
+                        WHERE code IN %(codes)s
+                          AND timestamp >= %(start)s
+                          AND timestamp <= %(end)s
+                        GROUP BY code
+                    """
+                    batch_data = client.execute(batch_price_query, {
+                        'codes': normalized_codes,
+                        'start': start_datetime,
+                        'end': end_datetime
+                    })
+
+                    # 构建价格映射
+                    price_map = {row[0]: float(row[1]) if row[1] else None for row in batch_data}
+
+                    # 2. 批量获取前收盘价（使用 Redis 缓存）
+                    prev_date_str = None
+                    try:
+                        target_idx = trading_days.index(target_date)
+                        if target_idx > 0:
+                            prev_trading_day = trading_days[target_idx - 1]
+                            prev_date_str = prev_trading_day.strftime('%Y%m%d')
+                    except (ValueError, IndexError):
+                        pass
+
+                    prev_close_map = {}
+                    if prev_date_str:
+                        base_codes = list(set([code.split('.')[0] for code in unique_stocks.keys() if code]))
+                        prev_close_map = get_cached_prev_close(base_codes, prev_date_str)
+
+                    # 3. 计算涨跌幅并更新
+                    for orig_code, stock_info in unique_stocks.items():
+                        norm_code = code_mapping.get(orig_code)
+                        base_code = orig_code.split('.')[0] if orig_code else ''
+
+                        last_price = price_map.get(norm_code) if norm_code else None
+                        prev_close = prev_close_map.get(base_code)
+
+                        if last_price is not None and prev_close is not None and prev_close > 0:
+                            change_pct = (last_price - prev_close) / prev_close * 100
+                            stock_info['maxChg'] = round(change_pct, 2)
+                        else:
+                            stock_info['maxChg'] = 0
+
+                except Exception as e:
+                    import traceback
+                    print(f'[effectiveness-stats] 查询股票涨跌幅失败: {e}')
+                    traceback.print_exc()
+                    # 失败时设置默认值
+                    for stock_info in unique_stocks.values():
+                        stock_info['maxChg'] = 0
+
             # 按涨幅排序，取 TOP10
             stock_stats = sorted(
                 unique_stocks.values(),
-                key=lambda x: x['maxChg'],
+                key=lambda x: x.get('maxChg', 0),
                 reverse=True
             )[:10]