"""
量化交易回测系统 - 仅15分钟K线 & 反向K线即时平仓逻辑（完整版）
"""

import datetime
from dataclasses import dataclass
from typing import List, Dict, Optional
from loguru import logger
from models.weex import Weex1Hour  # 替换为你的15分钟K线模型


# ========================= 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：
    - 前跌后涨包住 -> 做多
    - 前涨后跌包住 -> 做空
    """
    p_open, p_close = float(prev['open']), float(prev['close'])
    c_open, c_close = float(curr['open']), float(curr['close'])

    if is_bullish(curr) and is_bearish(prev) and c_open <= p_close and c_close >= p_open:
        return "long", "bear_bull_engulf"
    if is_bearish(curr) and is_bullish(prev) and c_open >= p_close 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（15分钟K线）"""
    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 []

    start_ts = int(target_date.timestamp() * 1000)
    end_ts = int((target_date + datetime.timedelta(days=1)).timestamp() * 1000) - 1

    query = model.select().where(model.id.between(start_ts, end_ts)).order_by(model.id.asc())
    return [{'id': i.id, 'open': i.open, 'high': i.high, 'low': i.low, 'close': i.close} for i in query]


# ========================= 回测逻辑 =========================

def backtest_15m_trend_simplified(dates: List[str]):
    all_data: List[Dict] = []
    for d in dates:
        all_data.extend(get_data_by_date(Weex1Hour, d))
    if not all_data:
        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'},
        }

    all_data.sort(key=lambda x: x['id'])

    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
    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 -> 碰到信号则开仓
        if current_position is None and direction:
            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']
            }
            stats[signal_key]['count'] += 1
            idx += 1
            continue

        if current_position:
            pos_dir = current_position['direction']
            pos_sig_key = current_position['signal_key']

            # 反向信号 -> 平仓 + 反手
            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
                current_position = {
                    'direction': direction,
                    'signal': stats[signal_key]['name'],
                    'signal_key': signal_key,
                    'entry_price': exit_price,
                    'entry_time': next_bar['id']
                }
                stats[signal_key]['count'] += 1
                idx += 1
                continue

            # === 新逻辑：遇到反向K线立即平仓 ===
            if pos_dir == 'long' and is_bearish(curr):
                exit_price = float(curr['close'])
                diff = exit_price - current_position['entry_price']
                trades.append({
                    'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000),
                    'exit_time': datetime.datetime.fromtimestamp(curr['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
                idx += 1
                continue

            if pos_dir == 'short' and is_bullish(curr):
                exit_price = float(curr['close'])
                diff = current_position['entry_price'] - exit_price
                trades.append({
                    'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000),
                    'exit_time': datetime.datetime.fromtimestamp(curr['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
                idx += 1
                continue

        idx += 1

    # 尾仓平仓
    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 =========================
if __name__ == '__main__':
    # dates = [f"2025-06-{i}" for i in range(1, 31)]

    dates = []
    for i in range(1, 11):
        for i1 in range(1, 31):
            dates.append(f"2025-{f'0{i}' if len(str(i)) < 2 else i}-{f'0{i1}' if len(str(i1)) < 2 else i1}")



    trades, stats = backtest_15m_trend_simplified(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 ===
        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

        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("===== 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}")
