diff --git a/mexc/30分钟.py b/mexc/30分钟.py
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+++ b/mexc/30分钟.py
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+"""
+量化交易回测系统 - 30分钟K线策略回测（Weex数据源）
+
+========== 策略规则 ==========
+重要：所有开仓和平仓操作都在下一根K线的开盘价执行
+
+【策略流程】
+1. 开仓条件（信号出现时，下一根K线开盘价开仓）：
+   - 阳包阴（涨包跌）信号 -> 开多
+     * 前一根是跌（阴线），后一根是涨（阳线）
+     * 且：涨的收盘价 > 跌的开盘价
+   
+   - 阴包阳（跌包涨）信号 -> 开空
+     * 前一根是涨（阳线），后一根是跌（阴线）
+     * 且：跌的收盘价 < 涨的开盘价
+
+2. 平仓条件（所有平仓都在下一根K线开盘价执行）：
+   - 持有多单时：遇到两根连续的阴线 -> 下一根K线开盘价平仓
+   - 持有空单时：遇到两根连续的阳线 -> 下一根K线开盘价平仓
+   - 遇到反向信号：下一根K线开盘价平仓并反手开仓
+     * 例如：持有多单时遇到阴包阳信号 -> 平多开空
+
+3. 续持条件：
+   - 遇到同向信号：续持
+   - 未满足平仓条件：续持
+
+【数据处理流程】
+1. 从数据库读取数据
+2. 数据排序（按时间戳升序）
+3. 开始回测
+"""
+
+import datetime
+import calendar
+from dataclasses import dataclass
+from typing import List, Dict, Optional
+from loguru import logger
+
+from models.mexc import Mexc30
+
+
+# ========================= 工具函数 =========================
+
+def is_bullish(c):  # 阳线
+    return float(c['close']) > float(c['open'])
+
+
+def is_bearish(c):  # 阴线
+    return float(c['close']) < float(c['open'])
+
+
+def check_signal(prev, curr):
+    """
+    包住形态信号判定（优化版）：
+    只看两种信号，严格按照收盘价与开盘价的比较：
+    
+    1. 阳包阴（涨包跌，前跌后涨）-> 做多：
+       - 前一根是跌（阴线：close < open）
+       - 后一根是涨（阳线：close > open）
+       - 且：涨的收盘价 > 跌的开盘价（curr['close'] > prev['open']）
+    
+    2. 阴包阳（跌包涨，前涨后跌）-> 做空：
+       - 前一根是涨（阳线：close > open）
+       - 后一根是跌（阴线：close < open）
+       - 且：跌的收盘价 < 涨的开盘价（curr['close'] < prev['open']）
+    """
+    p_open = float(prev['open'])
+    c_close = float(curr['close'])
+
+    # 阳包阴（涨包跌，前跌后涨） -> 做多：涨的收盘价 > 跌的开盘价
+    if is_bearish(prev) and is_bullish(curr) and c_close > p_open:
+        return "long", "bear_bull_engulf"
+
+    # 阴包阳（跌包涨，前涨后跌） -> 做空：跌的收盘价 < 涨的开盘价
+    if is_bullish(prev) and is_bearish(curr) and c_close < p_open:
+        return "short", "bull_bear_engulf"
+
+    return None, None
+
+
+def get_data_by_date(model, date_str: str):
+    """
+    按天获取指定表的数据（30分钟K线）
+    数据格式：时间戳(毫秒级) 开盘价 最高价 最低价 收盘价
+    例如：1767461400000 3106.68 3109.1 3106.22 3107.22
+    
+    注意：返回的数据已按时间戳（id）升序排序
+    """
+    try:
+        target_date = datetime.datetime.strptime(date_str, '%Y-%m-%d')
+    except ValueError:
+        logger.error("日期格式不正确，请使用 YYYY-MM-DD 格式。")
+        return []
+
+    # 将日期转换为毫秒级时间戳进行查询
+    start_ts = int(target_date.timestamp() * 1000)
+    end_ts = int((target_date + datetime.timedelta(days=1)).timestamp() * 1000) - 1
+
+    # 查询时按时间戳升序排序
+    query = model.select().where(model.id.between(start_ts, end_ts)).order_by(model.id.asc())
+    data = [{'id': i.id, 'open': i.open, 'high': i.high, 'low': i.low, 'close': i.close} for i in query]
+    
+    # 确保数据已排序
+    if data:
+        data.sort(key=lambda x: x['id'])
+    
+    return data
+
+
+# ========================= 回测逻辑 =========================
+
+def backtest_15m_trend_optimized(dates: List[str]):
+    """
+    回测策略逻辑：
+    1. 开仓条件（信号出现时，下一根K线开盘价开仓）：
+       - 阳包阴（涨包跌）信号 -> 开多
+       - 阴包阳（跌包涨）信号 -> 开空
+    
+    2. 平仓条件（所有平仓都在下一根K线开盘价执行）：
+       - 持有多单时：遇到两根连续的阴线 -> 下一根K线开盘价平仓
+       - 持有空单时：遇到两根连续的阳线 -> 下一根K线开盘价平仓
+       - 遇到反向信号：下一根K线开盘价平仓并反手开仓
+         （例如：持有多单时遇到阴包阳信号 -> 平多开空）
+    
+    3. 续持条件：
+       - 遇到同向信号：续持
+       - 未满足平仓条件：续持
+    """
+    # ==================== 步骤1：从数据库读取数据 ====================
+    all_data: List[Dict] = []
+    total_queried = 0
+    for d in dates:
+        day_data = get_data_by_date(Mexc30, d)
+        all_data.extend(day_data)
+        if day_data:
+            total_queried += len(day_data)
+    
+    logger.info(f"总共查询了 {len(dates)} 天，获取到 {total_queried} 条K线数据")
+    
+    if not all_data:
+        logger.warning("未获取到任何数据，请检查数据库连接和日期范围")
+        return [], {
+            'bear_bull_engulf': {'count': 0, 'wins': 0, 'total_profit': 0.0, 'name': '涨包跌'},
+            'bull_bear_engulf': {'count': 0, 'wins': 0, 'total_profit': 0.0, 'name': '跌包涨'},
+        }
+
+    # ==================== 步骤2：数据去重 + 排序（重要！必须先处理再回测） ====================
+    # 以时间戳(id)为唯一键去重，保留最先出现的一条
+    unique_by_id: Dict[int, Dict] = {}
+    for item in all_data:
+        if item['id'] not in unique_by_id:
+            unique_by_id[item['id']] = item
+    all_data = list(unique_by_id.values())
+    all_data.sort(key=lambda x: x['id'])
+    
+    # 验证排序结果
+    if len(all_data) > 1:
+        first_ts = all_data[0]['id']
+        last_ts = all_data[-1]['id']
+        first_time = datetime.datetime.fromtimestamp(first_ts / 1000)
+        last_time = datetime.datetime.fromtimestamp(last_ts / 1000)
+        logger.info(f"数据已按时间排序：{first_time.strftime('%Y-%m-%d %H:%M:%S')} 到 {last_time.strftime('%Y-%m-%d %H:%M:%S')}")
+    
+    # ==================== 步骤3：开始回测 ====================
+
+    stats = {
+        'bear_bull_engulf': {'count': 0, 'wins': 0, 'total_profit': 0.0, 'name': '涨包跌'},
+        'bull_bear_engulf': {'count': 0, 'wins': 0, 'total_profit': 0.0, 'name': '跌包涨'},
+    }
+
+    trades: List[Dict] = []
+    current_position: Optional[Dict] = None  # 开仓信息
+    consecutive_opposite_count = 0  # 连续反色K线计数
+    idx = 1
+
+    while idx < len(all_data) - 1:
+        prev, curr, next_bar = all_data[idx - 1], all_data[idx], all_data[idx + 1]
+        direction, signal_key = check_signal(prev, curr)
+
+        # ==================== 空仓状态：遇到信号则开仓 ====================
+        # 策略：阳包阴信号 -> 开多，阴包阳信号 -> 开空
+        if current_position is None:
+            if direction:
+                # 信号出现（prev和curr形成信号），在下一根K线（next_bar）的开盘价开仓
+                entry_price = float(next_bar['open'])
+                current_position = {
+                    'direction': direction,
+                    'signal': stats[signal_key]['name'],
+                    'signal_key': signal_key,
+                    'entry_price': entry_price,
+                    'entry_time': next_bar['id']
+                }
+                consecutive_opposite_count = 0  # 重置连续反色计数
+                stats[signal_key]['count'] += 1
+                logger.debug(f"开仓: {stats[signal_key]['name']} {'做多' if direction == 'long' else '做空'} @ {entry_price:.2f}")
+            idx += 1
+            continue
+
+        # ==================== 有仓位状态：检查平仓条件 ====================
+        pos_dir = current_position['direction']
+        pos_sig_key = current_position['signal_key']
+
+        # 1. 反向信号 -> 下一根K线开盘价平仓并反手开仓
+        # 策略：遇到反向信号（如持有多单时遇到阴包阳），平仓并反手开仓
+        if direction and direction != pos_dir:
+            exit_price = float(next_bar['open'])
+            diff = (exit_price - current_position['entry_price']) if pos_dir == 'long' else (
+                    current_position['entry_price'] - exit_price)
+            trades.append({
+                'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000),
+                'exit_time': datetime.datetime.fromtimestamp(next_bar['id'] / 1000),
+                'signal': current_position['signal'],
+                'direction': '做多' if pos_dir == 'long' else '做空',
+                'entry': current_position['entry_price'],
+                'exit': exit_price,
+                'diff': diff
+            })
+            stats[pos_sig_key]['total_profit'] += diff
+            if diff > 0: stats[pos_sig_key]['wins'] += 1
+
+            # 反手开仓（下一根K线开盘价）
+            current_position = {
+                'direction': direction,
+                'signal': stats[signal_key]['name'],
+                'signal_key': signal_key,
+                'entry_price': exit_price,
+                'entry_time': next_bar['id']
+            }
+            consecutive_opposite_count = 0  # 重置连续反色计数
+            stats[signal_key]['count'] += 1
+            logger.debug(f"反向信号反手: 平{'做多' if pos_dir == 'long' else '做空'} @ {exit_price:.2f}, 开{'做多' if direction == 'long' else '做空'}")
+            idx += 1
+            continue
+
+        # 2. 检查连续反色K线平仓条件（下一根K线开盘价平仓）
+        # 策略：持有多单时，遇到两根连续的阴线 -> 平仓
+        # 持有空单时，遇到两根连续的阳线 -> 平仓
+        if pos_dir == 'long' and is_bearish(curr):
+            consecutive_opposite_count += 1
+            # 如果已经连续两根阴线，下一根K线开盘价平仓
+            if consecutive_opposite_count >= 2:
+                logger.debug(f"平仓: 做多遇到连续两根阴线")
+                exit_price = float(next_bar['open'])
+                diff = exit_price - current_position['entry_price']
+                trades.append({
+                    'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000),
+                    'exit_time': datetime.datetime.fromtimestamp(next_bar['id'] / 1000),
+                    'signal': current_position['signal'],
+                    'direction': '做多',
+                    'entry': current_position['entry_price'],
+                    'exit': exit_price,
+                    'diff': diff
+                })
+                stats[pos_sig_key]['total_profit'] += diff
+                if diff > 0: stats[pos_sig_key]['wins'] += 1
+                current_position = None
+                consecutive_opposite_count = 0
+                idx += 1
+                continue
+            else:
+                # 只有一根阴线，续持
+                idx += 1
+                continue
+
+        # 持有空单：检查是否连续两根阳线
+        elif pos_dir == 'short' and is_bullish(curr):
+            consecutive_opposite_count += 1
+            # 如果已经连续两根阳线，下一根K线开盘价平仓
+            if consecutive_opposite_count >= 2:
+                logger.debug(f"平仓: 做空遇到连续两根阳线")
+                exit_price = float(next_bar['open'])
+                diff = current_position['entry_price'] - exit_price
+                trades.append({
+                    'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000),
+                    'exit_time': datetime.datetime.fromtimestamp(next_bar['id'] / 1000),
+                    'signal': current_position['signal'],
+                    'direction': '做空',
+                    'entry': current_position['entry_price'],
+                    'exit': exit_price,
+                    'diff': diff
+                })
+                stats[pos_sig_key]['total_profit'] += diff
+                if diff > 0: stats[pos_sig_key]['wins'] += 1
+                current_position = None
+                consecutive_opposite_count = 0
+                idx += 1
+                continue
+            else:
+                # 只有一根阳线，续持
+                idx += 1
+                continue
+
+        # 3. 同向K线或同向信号 -> 续持，重置连续反色计数
+        if (pos_dir == 'long' and is_bullish(curr)) or (pos_dir == 'short' and is_bearish(curr)):
+            consecutive_opposite_count = 0  # 重置连续反色计数
+
+        # 同向信号 -> 续持
+        if direction and direction == pos_dir:
+            consecutive_opposite_count = 0  # 重置连续反色计数
+            idx += 1
+            continue
+
+        idx += 1
+
+    # 尾仓：最后一根收盘价平仓
+    if current_position:
+        last = all_data[-1]
+        exit_price = float(last['close'])
+        pos_dir = current_position['direction']
+        diff = (exit_price - current_position['entry_price']) if pos_dir == 'long' else (
+                current_position['entry_price'] - exit_price)
+        trades.append({
+            'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000),
+            'exit_time': datetime.datetime.fromtimestamp(last['id'] / 1000),
+            'signal': current_position['signal'],
+            'direction': '做多' if pos_dir == 'long' else '做空',
+            'entry': current_position['entry_price'],
+            'exit': exit_price,
+            'diff': diff
+        })
+        stats[current_position['signal_key']]['total_profit'] += diff
+        if diff > 0: stats[current_position['signal_key']]['wins'] += 1
+
+    return trades, stats
+
+
+# ========================= 运行示例（优化版盈利计算） =========================
+if __name__ == '__main__':
+    dates = []
+    # 获取当前日期
+    today = datetime.datetime.now()
+    target_year = 2025
+    
+    for month in range(1, 13):
+        # 获取该月的实际天数
+        days_in_month = calendar.monthrange(target_year, month)[1]
+        for day in range(1, days_in_month + 1):
+            # 只添加今天及之前的日期
+            date_str = f"{target_year}-{month:02d}-{day:02d}"
+            date_obj = datetime.datetime.strptime(date_str, '%Y-%m-%d')
+            # 如果日期在今天之后，跳过
+            if date_obj > today:
+                break
+            dates.append(date_str)
+
+    print(dates)
+
+    # dates = [f"2025-09-{i}" for i in range(1, 32)]
+    trades, stats = backtest_15m_trend_optimized(dates)
+
+    logger.info("===== 每笔交易详情 =====")
+
+    # === 参数设定 ===
+    contract_size = 10000  # 合约规模（1手对应多少基础货币）
+    open_fee_fixed = 5  # 固定开仓手续费
+    close_fee_rate = 0.0005  # 按成交额比例的平仓手续费率
+
+    total_points_profit = 0  # 累计点差
+    total_money_profit = 0  # 累计金额盈利
+    total_fee = 0  # 累计手续费
+
+    for t in trades:
+        entry = t['entry']
+        exit = t['exit']
+        direction = t['direction']
+
+        # === 1️⃣ 原始价差（点差） ===
+        point_diff = (exit - entry) if direction == '做多' else (entry - exit)
+
+        # === 2️⃣ 金额盈利（考虑合约规模） ===
+        money_profit = point_diff / entry * contract_size  # 利润以基础货币计（例如USD）
+
+        # === 3️⃣ 手续费计算 ===
+        # 开仓 + 平仓手续费（按比例计算 + 固定）
+        fee = open_fee_fixed + (contract_size / entry * exit * close_fee_rate)
+
+        # === 4️⃣ 净利润 ===
+        net_profit = money_profit - fee
+
+        # 保存计算结果
+        t.update({
+            'point_diff': point_diff,
+            'raw_profit': money_profit,
+            'fee': fee,
+            'net_profit': net_profit
+        })
+
+        total_points_profit += point_diff
+        total_money_profit += money_profit
+        total_fee += fee
+
+        # if net_profit < -400:
+        logger.info(
+            f"{t['entry_time']} {direction}({t['signal']}) "
+            f"入={entry:.2f} 出={exit:.2f} 差价={point_diff:.2f} "
+            f"原始盈利={money_profit:.2f} 手续费={fee:.2f} 净利润={net_profit:.2f} {t['exit_time']}"
+        )
+
+    # === 汇总统计 ===
+    total_net_profit = total_money_profit - total_fee
+    print(f"\n一共交易笔数：{len(trades)}")
+    print(f"总点差：{total_points_profit:.2f}")
+    print(f"总原始盈利（未扣费）：{total_money_profit:.2f}")
+    print(f"总手续费：{total_fee:.2f}")
+    print(f"总净利润：{total_net_profit:.2f}\n")
+
+    print(total_money_profit - total_fee * 0.1)
+
+    print("===== 信号统计 =====")
+    for k, v in stats.items():
+        name, count, wins, total_p = v['name'], v['count'], v['wins'], v['total_profit']
+        win_rate = (wins / count * 100) if count > 0 else 0.0
+        avg_p = (total_p / count) if count > 0 else 0.0
+        print(f"{name}: 次数={count} 胜率={win_rate:.2f}% 总价差={total_p:.2f} 平均价差={avg_p:.2f}")
diff --git a/models/database.db b/models/database.db
index af6a2c2..a35c4a0 100644
Binary files a/models/database.db and b/models/database.db differ