feat: 添加每日数据报告定时推送功能

- 新增 daily_report_sender.py 定时任务程序
- 北京时间每天 8 点推送昨天 24 小时预测统计
- 包含各模型准确率、逐小时预测详情
- 失败交易订单汇总
- start_system.py 集成启动报告推送服务

daily_report_sender.py

@@ -0,0 +1,379 @@
+#!/usr/bin/env python3
+"""
+每日数据报告定时推送程序
+- 每天北京时间 8 点推送昨天的 24 小时预测统计
+- 包含各模型准确率、逐小时预测结果详情
+"""
+
+import schedule
+import time
+import logging
+from datetime import datetime, timedelta
+from zoneinfo import ZoneInfo
+from typing import Dict, List
+
+from utils.send_msg import lark_notifier
+from api.models import PredictionModel, convert_to_cst, get_db_connection, TZ_CST, TZ_UTC
+
+# 配置日志
+logging.basicConfig(
+    level=logging.INFO,
+    format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+    handlers=[
+        logging.FileHandler('logs/daily_report.log'),
+        logging.StreamHandler()
+    ]
+)
+logger = logging.getLogger(__name__)
+
+
+class DailyReportSender:
+    """每日数据报告发送器"""
+    
+    def __init__(self):
+        self.model = PredictionModel()
+        self.lark = lark_notifier
+    
+    def get_yesterday_failed_trades(self) -> List[Dict]:
+        """
+        获取昨天的失败交易订单
+        
+        Returns:
+            [
+                {
+                    'timestamp': '2026-02-27 10:30:00',
+                    'market_title': 'BTC 价格',
+                    'action': 'BUY',
+                    'status': 'failed',
+                    'error_message': '余额不足'
+                },
+                ...
+            ]
+        """
+        try:
+            # 获取昨天的日期（CST）
+            now_cst = datetime.now(TZ_CST)
+            yesterday_cst = now_cst - timedelta(days=1)
+            yesterday_date = yesterday_cst.strftime('%Y-%m-%d')
+            
+            # 计算 CST 时间范围
+            start_cst = datetime.strptime(f"{yesterday_date} 00:00:00", '%Y-%m-%d %H:%M:%S').replace(tzinfo=TZ_CST)
+            end_cst = start_cst + timedelta(days=1)
+            
+            start_str = start_cst.strftime('%Y-%m-%d %H:%M:%S')
+            end_str = end_cst.strftime('%Y-%m-%d %H:%M:%S')
+            
+            # 从 trades 表查询失败订单
+            with get_db_connection() as conn:
+                cursor = conn.cursor()
+                sql = """
+                    SELECT 
+                        timestamp,
+                        market_title,
+                        action,
+                        status,
+                        error_message
+                    FROM trades
+                    WHERE timestamp >= %s AND timestamp < %s
+                      AND status != 'MATCHED'
+                    ORDER BY timestamp DESC
+                """
+                cursor.execute(sql, (start_str, end_str))
+                rows = cursor.fetchall()
+            
+            return rows if rows else []
+            
+        except Exception as e:
+            logger.error(f"获取昨天失败交易失败: {e}", exc_info=True)
+            return []
+    
+    def get_yesterday_statistics(self) -> Dict:
+        """
+        获取昨天的 24 小时预测统计和详细数据
+        
+        Returns:
+            {
+                'date': 'YYYY-MM-DD',
+                'models': {
+                    'DLinear': {'total': 24, 'correct': 14, 'accuracy': 58.3},
+                    'N-BEATS': {...},
+                    'TTM-R2': {...},
+                    'Ensemble': {...}
+                },
+                'hourly_details': [
+                    {
+                        'hour': '00:00-01:00',
+                        'actual': '涨',
+                        'dlinear': {'pred': '涨', 'correct': True},
+                        'nbeats': {...},
+                        'ttm': {...},
+                        'ensemble': {...}
+                    },
+                    ...
+                ]
+            }
+        """
+        try:
+            # 获取昨天的日期（CST）
+            now_cst = datetime.now(TZ_CST)
+            yesterday_cst = now_cst - timedelta(days=1)
+            yesterday_date = yesterday_cst.strftime('%Y-%m-%d')
+            
+            # 计算 UTC 时间范围
+            start_cst = datetime.strptime(f"{yesterday_date} 00:00:00", '%Y-%m-%d %H:%M:%S').replace(tzinfo=TZ_CST)
+            end_cst = start_cst + timedelta(days=1)
+            
+            start_utc = start_cst.astimezone(TZ_UTC)
+            end_utc = end_cst.astimezone(TZ_UTC)
+            
+            start_str = start_utc.strftime('%Y-%m-%d %H:%M:%S')
+            end_str = end_utc.strftime('%Y-%m-%d %H:%M:%S')
+            
+            # 查询数据库
+            with get_db_connection() as conn:
+                cursor = conn.cursor()
+                sql = """
+                    SELECT 
+                        timestamp,
+                        actual_result,
+                        dlinear_prediction, dlinear_correct,
+                        nbeats_prediction, nbeats_correct,
+                        ttm_prediction, ttm_correct,
+                        ensemble_prediction, ensemble_correct
+                    FROM hourly_model_predictions
+                    WHERE timestamp >= %s AND timestamp < %s
+                    ORDER BY timestamp ASC
+                """
+                cursor.execute(sql, (start_str, end_str))
+                rows = cursor.fetchall()
+            
+            # 整理统计数据
+            models = ['dlinear', 'nbeats', 'ttm', 'ensemble']
+            model_names = {
+                'dlinear': 'DLinear',
+                'nbeats': 'N-BEATS',
+                'ttm': 'TTM-R2',
+                'ensemble': 'Ensemble'
+            }
+            
+            # 初始化统计
+            stats = {
+                'date': yesterday_date,
+                'models': {},
+                'hourly_details': []
+            }
+            
+            for model in models:
+                stats['models'][model_names[model]] = {
+                    'total': 0,
+                    'correct': 0,
+                    'accuracy': 0.0
+                }
+            
+            # 处理每行数据
+            for idx, row in enumerate(rows):
+                if row.get('actual_result') is None:
+                    continue
+                
+                # 获取时间戳（转为 CST 显示）
+                ts_utc = row['timestamp']
+                if isinstance(ts_utc, str):
+                    ts_utc = datetime.fromisoformat(str(ts_utc).replace('Z', '+00:00'))
+                if ts_utc.tzinfo is None:
+                    ts_utc = ts_utc.replace(tzinfo=TZ_UTC)
+                
+                ts_cst = ts_utc.astimezone(TZ_CST)
+                hour_start = ts_cst.strftime('%H:%M')
+                hour_end = (ts_cst + timedelta(hours=1)).strftime('%H:%M')
+                hour_label = f"{hour_start}-{hour_end}"
+                
+                # 实际结果
+                actual_result = row['actual_result']
+                actual_label = '涨' if actual_result == 1 else '跌'
+                
+                # 每小时预测详情
+                hourly_item = {
+                    'hour': hour_label,
+                    'actual': actual_label
+                }
+                
+                # 逐模型处理预测结果
+                for model in models:
+                    pred = row[f"{model}_prediction"]
+                    correct = row[f"{model}_correct"]
+                    
+                    # 更新统计
+                    if pred is not None:
+                        stats['models'][model_names[model]]['total'] += 1
+                        if correct == 1:
+                            stats['models'][model_names[model]]['correct'] += 1
+                    
+                    # 添加到小时详情
+                    pred_label = '涨' if pred == 1 else ('跌' if pred == 0 else '无')
+                    correct_flag = correct == 1 if correct is not None else None
+                    
+                    hourly_item[model] = {
+                        'pred': pred_label,
+                        'correct': '✓' if correct_flag else ('✗' if correct_flag is False else '-')
+                    }
+                
+                stats['hourly_details'].append(hourly_item)
+            
+            # 计算准确率百分比
+            for model_name in stats['models']:
+                total = stats['models'][model_name]['total']
+                correct = stats['models'][model_name]['correct']
+                if total > 0:
+                    stats['models'][model_name]['accuracy'] = round(correct / total * 100, 2)
+            
+            return stats
+            
+        except Exception as e:
+            logger.error(f"获取昨天统计数据失败: {e}", exc_info=True)
+            return None
+    
+    def format_report(self, stats: Dict, failed_trades: List[Dict] = None) -> str:
+        """
+        格式化报告为飞书 Markdown 格式
+        
+        Args:
+            stats: get_yesterday_statistics 返回的数据字典
+            failed_trades: 失败订单列表
+        
+        Returns:
+            Markdown 格式的报告文本
+        """
+        if not stats:
+            return "❌ 无法获取昨天的统计数据，请检查数据库连接"
+        
+        date = stats['date']
+        models = stats['models']
+        
+        # 构建报告头
+        report = f"**【BTC 日报 - {date}】**\n\n"
+        
+        # 模型准确率统计部分
+        report += "**📊 模型准确率统计（24小时）**\n"
+        for model_name in ['DLinear', 'N-BEATS', 'TTM-R2', 'Ensemble']:
+            data = models.get(model_name, {})
+            total = data.get('total', 0)
+            correct = data.get('correct', 0)
+            accuracy = data.get('accuracy', 0)
+            
+            # 进度条可视化
+            bar_length = 10
+            filled = int(accuracy / 100 * bar_length)
+            bar = '█' * filled + '░' * (bar_length - filled)
+            
+            report += f"• **{model_name}**: {correct}/{total} {bar} {accuracy}%\n"
+        
+        report += "\n"
+        
+        # 交易失败订单详情
+        report += "**⚠️ 交易失败订单**\n"
+        if failed_trades and len(failed_trades) > 0:
+            report += f"昨天共有 {len(failed_trades)} 个失败订单\n"
+            for idx, trade in enumerate(failed_trades[:10], 1):  # 仅显示前10个
+                timestamp = trade.get('timestamp', '未知')
+                market_title = trade.get('market_title', '未知市场')
+                action = trade.get('action', '未知')
+                status = trade.get('status', '未知')
+                error_msg = trade.get('error_message', '无详细信息')
+                
+                # 简化错误信息 - 仅取第一行
+                if error_msg:
+                    error_msg = error_msg.split('\n')[0][:50]  # 仅取前50字
+                else:
+                    error_msg = '无错误信息'
+                
+                report += f"{idx}. [{timestamp}] {market_title} ({action}) → {error_msg}\n"
+            if len(failed_trades) > 10:
+                report += f"... 还有 {len(failed_trades) - 10} 个失败订单\n"
+        else:
+            report += "昨日无失败订单，运营正常 ✓\n"
+        
+        report += "\n生成时间: " + datetime.now(TZ_CST).strftime('%Y-%m-%d %H:%M:%S CST')
+        
+        return report
+    
+    def send_daily_report(self):
+        """获取昨天统计并推送"""
+        try:
+            logger.info("开始推送每日报告...")
+            
+            stats = self.get_yesterday_statistics()
+            if not stats:
+                logger.warning("无法获取昨天统计数据")
+                self.lark.send_alert(
+                    title="⚠️ 每日报告生成失败",
+                    content="无法获取昨天的统计数据，请检查数据库连接"
+                )
+                return
+            
+            # 获取失败订单
+            failed_trades = self.get_yesterday_failed_trades()
+            
+            # 格式化报告
+            report = self.format_report(stats, failed_trades)
+            
+            # 推送到飞书
+            self.lark.send_alert(
+                title="📊 BTC 每日数据报告",
+                content=report
+            )
+            
+            logger.info(f"每日报告已送出: {stats['date']}")
+            
+        except Exception as e:
+            logger.error(f"推送每日报告异常: {e}", exc_info=True)
+            self.lark.send_alert(
+                title="❌ 每日报告推送异常",
+                content=f"错误详情: {str(e)}"
+            )
+
+
+def schedule_daily_report():
+    """
+    启动每日报告定时任务
+    北京时间每天 8 点执行
+    """
+    sender = DailyReportSender()
+    sender.send_daily_report()  # 启动时立即发送一次（可选）
+    # 使用 schedule 库在北京时间 8 点触发
+    # 由于 schedule 库基于本地时间，当前环境如果是 macOS 默认时间，
+    # 我们使用一个包装器来处理 CST 时间转换
+    def cst_8am_job():
+        """北京时间 8 点执行的任务"""
+        now_cst = datetime.now(TZ_CST)
+        if now_cst.hour == 8 and now_cst.minute < 1:
+            # 确保只在 08:00-08:01 间隔执行一次（避免重复）
+            sender.send_daily_report()
+    
+    # 每分钟检查一次是否需要执行 (确保能在 8 点执行)
+    schedule.every(1).minutes.do(cst_8am_job)
+    
+    logger.info("每日报告定时任务已启动（北京时间每天 8 点执行）")
+    
+    # 启动调度循环
+    while True:
+        schedule.run_pending()
+        time.sleep(1)
+
+
+def run_scheduler_background():
+    """
+    在后台线程中运行调度器（供 start_system.py 调用）
+    """
+    import threading
+    
+    scheduler_thread = threading.Thread(target=schedule_daily_report, daemon=True)
+    scheduler_thread.start()
+    
+    logger.info("每日报告调度器已在后台启动")
+    return scheduler_thread
+
+
+if __name__ == '__main__':
+    # 支持单独运行以及从其他模块导入
+    logger.info("启动每日报告系统...")
+    schedule_daily_report()

start_system.py

@@ -4,6 +4,7 @@
 同时启动：
 1. FastAPI 后端服务 (提供前端看板 API)
 2. Polymarket 自动交易程序
+3. 每日数据报告推送程序 (北京时间每天 8 点)
 
 支持平台：macOS, Linux, Windows
 """
@@ -15,6 +16,13 @@ import os
 import platform
 from datetime import datetime
 
+try:
+    from daily_report_sender import run_scheduler_background
+except ImportError:
+    # 如果模块导入失败，定义一个空函数避免启动失败
+    def run_scheduler_background():
+        return None
+
 # 检测操作系统
 IS_WINDOWS = platform.system() == 'Windows'
 
@@ -126,6 +134,18 @@ def main():
     trade_cmd = f"{python_exec} -u trader/auto_trade_polymarket.py"
     trade_process = start_process(trade_cmd, "Polymarket 自动交易程序")
     
+    # 3. 启动每日数据报告推送程序（后台线程）
+    # 北京时间每天 8 点推送昨天的数据统计
+    try:
+        report_thread = run_scheduler_background()
+        if report_thread:
+            log("每日数据报告推送程序已启动", GREEN)
+        else:
+            log("⚠️  每日数据报告推送程序启动失败", YELLOW)
+    except Exception as e:
+        log(f"⚠️  启动每日报告程序异常: {e}", YELLOW)
+        report_thread = None
+    
     log("系统启动完成！", GREEN)
     log("前端访问地址: http://localhost:8000", GREEN)
     log("按 Ctrl+C 停止所有服务...", YELLOW)