community增加事件详情

app.py

@@ -10541,6 +10541,219 @@ def get_event_counts():
         }), 500
 
 
+@app.route('/api/v1/calendar/combined-data', methods=['GET'])
+def get_calendar_combined_data():
+    """获取日历综合数据（涨停数据 + 事件数量 + 上证涨跌幅）
+    一次性返回日历显示所需的所有数据，避免前端多次请求
+
+    参数:
+        year: 年份（可选，默认当前年份）
+        month: 月份（可选，默认当前月份）
+
+    返回:
+        {
+            success: true,
+            data: [
+                {
+                    date: "20260107",
+                    zt_count: 80,           // 涨停数量
+                    top_sector: "人工智能",  // 最热概念
+                    event_count: 8,         // 事件数量
+                    index_change: 1.38      // 上证涨跌幅(%)
+                },
+                ...
+            ]
+        }
+    """
+    import os
+    import json
+
+    try:
+        year = request.args.get('year', datetime.now().year, type=int)
+        month = request.args.get('month', datetime.now().month, type=int)
+
+        # 计算月份的开始和结束日期
+        start_date = datetime(year, month, 1)
+        if month == 12:
+            end_date = datetime(year + 1, 1, 1)
+        else:
+            end_date = datetime(year, month + 1, 1)
+
+        # 用 Map 存储数据，key 为 YYYYMMDD 格式
+        data_map = {}
+
+        # 1. 从静态文件加载涨停数据
+        zt_dates_path = os.path.join(app.static_folder or 'static', 'data', 'zt', 'dates.json')
+        # 尝试多个可能的路径
+        possible_paths = [
+            zt_dates_path,
+            os.path.join('public', 'data', 'zt', 'dates.json'),
+            os.path.join('data', 'zt', 'dates.json'),
+            '/var/www/vf_react/data/zt/dates.json',  # 服务器路径
+        ]
+
+        zt_dates = []
+        for path in possible_paths:
+            if os.path.exists(path):
+                try:
+                    with open(path, 'r', encoding='utf-8') as f:
+                        zt_data = json.load(f)
+                        zt_dates = zt_data.get('dates', [])
+                        break
+                except Exception as e:
+                    print(f"[calendar] 读取涨停数据失败 {path}: {e}")
+
+        # 处理涨停数据
+        for item in zt_dates:
+            date_str = item.get('date', '')
+            if not date_str:
+                continue
+            # 检查是否在当月范围内
+            try:
+                item_date = datetime.strptime(date_str, '%Y%m%d')
+                if start_date <= item_date < end_date:
+                    data_map[date_str] = {
+                        'date': date_str,
+                        'zt_count': item.get('count', 0),
+                        'top_sector': '',
+                        'event_count': 0,
+                        'index_change': None
+                    }
+            except ValueError:
+                continue
+
+        # 2. 加载涨停详情获取 top_sector（从 daily 文件）
+        zt_daily_dir = None
+        possible_daily_dirs = [
+            os.path.join(app.static_folder or 'static', 'data', 'zt', 'daily'),
+            os.path.join('public', 'data', 'zt', 'daily'),
+            os.path.join('data', 'zt', 'daily'),
+            '/var/www/vf_react/data/zt/daily',
+        ]
+
+        for dir_path in possible_daily_dirs:
+            if os.path.isdir(dir_path):
+                zt_daily_dir = dir_path
+                break
+
+        if zt_daily_dir:
+            for date_str in data_map.keys():
+                daily_file = os.path.join(zt_daily_dir, f'{date_str}.json')
+                if os.path.exists(daily_file):
+                    try:
+                        with open(daily_file, 'r', encoding='utf-8') as f:
+                            daily_data = json.load(f)
+                            # 优先使用词云图最高频词
+                            word_freq = daily_data.get('word_freq_data', [])
+                            if word_freq:
+                                data_map[date_str]['top_sector'] = word_freq[0].get('name', '')
+                            elif daily_data.get('sector_data'):
+                                # 找出涨停数最多的板块
+                                max_sector = ''
+                                max_count = 0
+                                for sector, info in daily_data['sector_data'].items():
+                                    if info.get('count', 0) > max_count:
+                                        max_count = info['count']
+                                        max_sector = sector
+                                data_map[date_str]['top_sector'] = max_sector
+                    except Exception as e:
+                        print(f"[calendar] 读取涨停详情失败 {daily_file}: {e}")
+
+        # 3. 查询事件数量
+        event_query = """
+            SELECT DATE(calendar_time) as date, COUNT(*) as count
+            FROM future_events
+            WHERE calendar_time BETWEEN :start_date AND :end_date
+              AND type = 'event'
+            GROUP BY DATE(calendar_time)
+        """
+
+        event_result = db.session.execute(text(event_query), {
+            'start_date': start_date,
+            'end_date': end_date
+        })
+
+        for row in event_result:
+            event_date = row[0]
+            event_count = row[1]
+            date_str = event_date.strftime('%Y%m%d') if hasattr(event_date, 'strftime') else str(event_date).replace('-', '')
+
+            if date_str in data_map:
+                data_map[date_str]['event_count'] = event_count
+            else:
+                data_map[date_str] = {
+                    'date': date_str,
+                    'zt_count': 0,
+                    'top_sector': '',
+                    'event_count': event_count,
+                    'index_change': None
+                }
+
+        # 4. 查询上证指数涨跌幅（从 MySQL 的 ea_exchangetrade 表）
+        index_query = """
+            SELECT TRADEDATE, F006N, F007N
+            FROM ea_exchangetrade
+            WHERE INDEXCODE = '000001'
+              AND TRADEDATE BETWEEN :start_date AND :end_date
+            ORDER BY TRADEDATE
+        """
+
+        try:
+            with engine.connect() as conn:
+                index_result = conn.execute(text(index_query), {
+                    'start_date': start_date,
+                    'end_date': end_date
+                }).fetchall()
+
+            # 构建前一天收盘价映射，用于计算涨跌幅
+            prev_close = None
+            for row in index_result:
+                trade_date = row[0]
+                close_price = float(row[1]) if row[1] else None
+                db_prev_close = float(row[2]) if row[2] else None
+
+                date_str = trade_date.strftime('%Y%m%d') if hasattr(trade_date, 'strftime') else str(trade_date).replace('-', '')
+
+                # 计算涨跌幅
+                actual_prev = prev_close if prev_close else db_prev_close
+                if close_price and actual_prev:
+                    change_pct = ((close_price - actual_prev) / actual_prev) * 100
+
+                    if date_str in data_map:
+                        data_map[date_str]['index_change'] = round(change_pct, 2)
+                    else:
+                        data_map[date_str] = {
+                            'date': date_str,
+                            'zt_count': 0,
+                            'top_sector': '',
+                            'event_count': 0,
+                            'index_change': round(change_pct, 2)
+                        }
+
+                prev_close = close_price
+
+        except Exception as e:
+            print(f"[calendar] 查询上证指数失败: {e}")
+
+        # 按日期排序返回
+        result = sorted(data_map.values(), key=lambda x: x['date'])
+
+        return jsonify({
+            'success': True,
+            'data': result,
+            'year': year,
+            'month': month
+        })
+
+    except Exception as e:
+        import traceback
+        traceback.print_exc()
+        return jsonify({
+            'success': False,
+            'error': str(e)
+        }), 500
+
+
 @app.route('/api/v1/calendar/events', methods=['GET'])
 def get_calendar_events():
     """获取指定日期的事件列表"""