JUKUAN/Lib/future/CandlestickHatchReverseStrategy_v001.py

# 导入函数库
from jqdata import *
from jqdata import finance
import pandas as pd
import numpy as np
from datetime import date, datetime, timedelta
import re

# 烛台影线形态反向交易策略 v001
# 基于烛台形态检测，按照影线相反方向进行交易的策略

# 设置以便完整打印 DataFrame
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.width', None)
pd.set_option('display.max_colwidth', 20)

## 初始化函数，设定基准等等
def initialize(context):
    # 设定沪深300作为基准
    set_benchmark('000300.XSHG')
    # 开启动态复权模式(真实价格)
    set_option('use_real_price', True)
    # 输出内容到日志
    log.info('烛台影线形态反向交易策略初始化开始')

    ### 期货相关设定 ###
    # 设定账户为金融账户
    set_subportfolios([SubPortfolioConfig(cash=context.portfolio.starting_cash, type='index_futures')])
    # 期货类每笔交易时的手续费是: 买入时万分之0.23,卖出时万分之0.23,平今仓为万分之23
    set_order_cost(OrderCost(open_commission=0.000023, close_commission=0.000023, close_today_commission=0.0023), type='index_futures')
    
    # 设置期货交易的滑点
    set_slippage(StepRelatedSlippage(2))
    
    # 初始化全局变量
    g.usage_percentage = 0.8  # 最大资金使用比例
    g.max_margin_per_position = 20000  # 单个标的最大持仓保证金（元）
    
    # 烛台形态检测参数（与研究文件保持一致）
    g.hatch_to_body_ratio = 1.2  # 影线与实体长度比率阈值
    g.opposite_hatch_ratio = 0.5  # 相反方向影线与实体长度比率阈值
    g.historical_days = 365  # 历史数据天数，用于计算平均实体长度阈值（与研究文件保持一致）
    
    # 全局阈值缓存（每月更新一次）
    g.monthly_body_threshold_cache = {}  # 存储每月计算的实体长度阈值
    g.last_threshold_update_month = None  # 记录上次更新阈值的月份
    
    # 止损止盈策略参数
    g.fixed_stop_loss_rate = 0.01  # 固定止损比率（1%）
    g.trailing_stop_thresholds = [0.05, 0.10]  # 动态追踪止损触发条件（5%, 10%）
    g.trailing_stop_rates = [0.02, 0.03, 0.04]  # 动态追踪止损比率（2%, 3%, 4%）
    
    # 开仓方向配置参数
    g.reverse_direction_symbols = ['JD']  # 使用反向逻辑的品种列表（上影线做空，下影线做多）
    # 不在此列表中的品种使用正向逻辑（上影线做多，下影线做空）
    
    # 期货品种完整配置字典
    g.futures_config = {
        # 贵金属
        'AU': {'has_night_session': True, 'margin_rate': {'long': 0.14, 'short': 0.14}, 'multiplier': 1000},
        'AG': {'has_night_session': True, 'margin_rate': {'long': 0.14, 'short': 0.14}, 'multiplier': 15},
        
        # 有色金属
        'CU': {'has_night_session': True, 'margin_rate': {'long': 0.09, 'short': 0.09}, 'multiplier': 5},
        'AL': {'has_night_session': True, 'margin_rate': {'long': 0.09, 'short': 0.09}, 'multiplier': 5},
        'ZN': {'has_night_session': True, 'margin_rate': {'long': 0.09, 'short': 0.09}, 'multiplier': 5},
        'PB': {'has_night_session': True, 'margin_rate': {'long': 0.09, 'short': 0.09}, 'multiplier': 5},
        'NI': {'has_night_session': True, 'margin_rate': {'long': 0.12, 'short': 0.12}, 'multiplier': 1},
        'SN': {'has_night_session': True, 'margin_rate': {'long': 0.12, 'short': 0.12}, 'multiplier': 1},
        'SS': {'has_night_session': True, 'margin_rate': {'long': 0.07, 'short': 0.07}, 'multiplier': 5},
        
        # 黑色系
        'RB': {'has_night_session': True, 'margin_rate': {'long': 0.07, 'short': 0.07}, 'multiplier': 10},
        'HC': {'has_night_session': True, 'margin_rate': {'long': 0.07, 'short': 0.07}, 'multiplier': 10},
        'I': {'has_night_session': True, 'margin_rate': {'long': 0.1, 'short': 0.1}, 'multiplier': 100},
        'JM': {'has_night_session': True, 'margin_rate': {'long': 0.22, 'short': 0.22}, 'multiplier': 100},
        'J': {'has_night_session': True, 'margin_rate': {'long': 0.22, 'short': 0.22}, 'multiplier': 60},
        
        # 能源化工
        'SP': {'has_night_session': True, 'margin_rate': {'long': 0.1, 'short': 0.1}, 'multiplier': 10},
        'FU': {'has_night_session': True, 'margin_rate': {'long': 0.08, 'short': 0.08}, 'multiplier': 10},
        'BU': {'has_night_session': True, 'margin_rate': {'long': 0.04, 'short': 0.04}, 'multiplier': 10},
        'RU': {'has_night_session': True, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 10},
        'BR': {'has_night_session': True, 'margin_rate': {'long': 0.07, 'short': 0.07}, 'multiplier': 5},
        'SC': {'has_night_session': True, 'margin_rate': {'long': 0.12, 'short': 0.12}, 'multiplier': 1000},
        'NR': {'has_night_session': True, 'margin_rate': {'long': 0.13, 'short': 0.13}, 'multiplier': 10},
        'LU': {'has_night_session': True, 'margin_rate': {'long': 0.15, 'short': 0.15}, 'multiplier': 10},
        'LC': {'has_night_session': False, 'margin_rate': {'long': 0.1, 'short': 0.1}, 'multiplier': 1},
        
        # 化工
        'FG': {'has_night_session': True, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 20},
        'TA': {'has_night_session': True, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 5},
        'MA': {'has_night_session': True, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 10},
        'SA': {'has_night_session': True, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 20},
        'L': {'has_night_session': True, 'margin_rate': {'long': 0.07, 'short': 0.07}, 'multiplier': 5},
        'V': {'has_night_session': True, 'margin_rate': {'long': 0.07, 'short': 0.07}, 'multiplier': 5},
        'EG': {'has_night_session': True, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 10},
        'PP': {'has_night_session': True, 'margin_rate': {'long': 0.07, 'short': 0.07}, 'multiplier': 5},
        'EB': {'has_night_session': True, 'margin_rate': {'long': 0.12, 'short': 0.12}, 'multiplier': 5},
        'PG': {'has_night_session': True, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 20},
        
        # 农产品
        'RM': {'has_night_session': True, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 10},
        'OI': {'has_night_session': True, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 10},
        'CF': {'has_night_session': True, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 5},
        'SR': {'has_night_session': True, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 10},
        'PF': {'has_night_session': True, 'margin_rate': {'long': 0.1, 'short': 0.1}, 'multiplier': 5},
        'C': {'has_night_session': True, 'margin_rate': {'long': 0.07, 'short': 0.07}, 'multiplier': 10},
        'CS': {'has_night_session': True, 'margin_rate': {'long': 0.07, 'short': 0.07}, 'multiplier': 10},
        'CY': {'has_night_session': True, 'margin_rate': {'long': 0.15, 'short': 0.15}, 'multiplier': 5},
        'A': {'has_night_session': True, 'margin_rate': {'long': 0.07, 'short': 0.07}, 'multiplier': 10},
        'B': {'has_night_session': True, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 10},
        'M': {'has_night_session': True, 'margin_rate': {'long': 0.07, 'short': 0.07}, 'multiplier': 10},
        'Y': {'has_night_session': True, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 10},
        'P': {'has_night_session': True, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 10},
        
        # 无夜盘品种
        'IF': {'has_night_session': False, 'margin_rate': {'long': 0.08, 'short': 0.08}, 'multiplier': 300},
        'IH': {'has_night_session': False, 'margin_rate': {'long': 0.08, 'short': 0.08}, 'multiplier': 300},
        'IC': {'has_night_session': False, 'margin_rate': {'long': 0.08, 'short': 0.08}, 'multiplier': 200},
        'IM': {'has_night_session': False, 'margin_rate': {'long': 0.08, 'short': 0.08}, 'multiplier': 200},
        'AP': {'has_night_session': False, 'margin_rate': {'long': 0.08, 'short': 0.08}, 'multiplier': 10},
        'CJ': {'has_night_session': False, 'margin_rate': {'long': 0.09, 'short': 0.09}, 'multiplier': 5},
        'PK': {'has_night_session': False, 'margin_rate': {'long': 0.05, 'short': 0.05}, 'multiplier': 5},
        'JD': {'has_night_session': False, 'margin_rate': {'long': 0.07, 'short': 0.07}, 'multiplier': 10},
        'LH': {'has_night_session': False, 'margin_rate': {'long': 0.1, 'short': 0.1}, 'multiplier': 16}
    }
    
    # 策略品种选择策略配置
    # 方案1：全品种策略 - 考虑所有配置的期货品种
    # g.strategy_focus_symbols = []  # 空列表表示考虑所有品种
    
    # 方案2：精选品种策略 - 只交易流动性较好的特定品种（如需使用请取消下行注释）
    g.strategy_focus_symbols = ['RM', 'CJ', 'CY', 'JD', 'L', 'LC', 'SF', 'SI']
    
    log.info(f"品种选择策略: {'全品种策略（覆盖所有配置品种）' if not g.strategy_focus_symbols else '精选品种策略（' + str(len(g.strategy_focus_symbols)) + '个品种）'}")
    
    # 输出开仓方向配置信息
    log.info("=" * 50)
    log.info("开仓方向配置:")
    log.info(f"反向逻辑品种: {g.reverse_direction_symbols} (上影线做空，下影线做多)")
    log.info("正向逻辑品种: 所有其他品种 (上影线做多，下影线做空)")
    log.info("=" * 50)
    
    # 交易记录和数据存储
    g.trade_history = {}
    g.candlestick_signals = {}  # 存储烛台形态信号
    g.daily_data_cache = {}  # 存储历史日线数据缓存
    g.minute_data_cache = {}  # 存储今日分钟数据缓存
    g.body_threshold_cache = {}  # 存储实体长度阈值缓存
    
    # 保证金比例管理
    g.margin_rate_history = {}  # 保证金比例变化历史记录
    g.today_trades = []  # 当日交易记录
    
    # 定时任务设置
    # 每月第1个交易日更新阈值
    run_monthly(monthly_update_thresholds, 1, 'before_open', reference_security='IF1808.CCFX')
    
    # 夜盘开始 - 仅止损止盈检查
    run_daily(main_trading_stop_only, time='21:05:00', reference_security='IF1808.CCFX')
    run_daily(main_trading_stop_only, time='21:35:00', reference_security='IF1808.CCFX')
    run_daily(main_trading_stop_only, time='22:05:00', reference_security='IF1808.CCFX')
    run_daily(main_trading_stop_only, time='22:35:00', reference_security='IF1808.CCFX')
    
    # 日盘开始 - 仅止损止盈检查
    run_daily(main_trading_stop_only, time='09:05:00', reference_security='IF1808.CCFX')
    run_daily(main_trading_stop_only, time='09:35:00', reference_security='IF1808.CCFX')
    run_daily(main_trading_stop_only, time='10:05:00', reference_security='IF1808.CCFX')
    run_daily(main_trading_stop_only, time='10:35:00', reference_security='IF1808.CCFX')
    run_daily(main_trading_stop_only, time='11:05:00', reference_security='IF1808.CCFX')
    run_daily(main_trading_stop_only, time='11:25:00', reference_security='IF1808.CCFX')
    run_daily(main_trading_stop_only, time='13:35:00', reference_security='IF1808.CCFX')
    run_daily(main_trading_stop_only, time='14:05:00', reference_security='IF1808.CCFX')
    
    # 收盘前 - 14:55进行完整交易检查，14:35仅止损止盈
    run_daily(main_trading_stop_only, time='14:35:00', reference_security='IF1808.CCFX')
    
    # 完整交易检查 - 仅在14:55执行（任务1, 2, 3, 4, 5, 6, 7）
    run_daily(main_trading_complete, time='14:55:00', reference_security='IF1808.CCFX')
    
    # 收盘后
    run_daily(after_market_close, time='15:30:00', reference_security='IF1808.CCFX')

############################ 主程序执行函数 ###################################

def monthly_update_thresholds(context):
    """每月更新实体长度阈值"""
    log.info("=" * 60)
    log.info("每月阈值更新开始")
    log.info("=" * 60)
    
    current_month = context.current_dt.strftime('%Y-%m')
    
    # 检查是否需要更新
    if g.last_threshold_update_month == current_month:
        log.info(f"本月阈值已更新，跳过更新")
        return
    
    # 获取所有需要计算阈值的品种
    focus_symbols = g.strategy_focus_symbols if g.strategy_focus_symbols else list(g.futures_config.keys())
    
    updated_count = 0
    for symbol in focus_symbols:
        try:
            # 获取主力合约
            dominant_future = get_dominant_future(symbol)
            if not dominant_future:
                continue
            
            # 获取365天历史数据
            data = attribute_history(dominant_future, g.historical_days, '1d', 
                                   ['open', 'close', 'high', 'low', 'volume'], 
                                   df=True)
            
            if data is not None and len(data) > 30:  # 确保有足够数据
                # 计算实体长度阈值
                data['body_length'] = abs(data['close'] - data['open'])
                body_threshold = data['body_length'].mean()
                
                # 存储到全局阈值缓存
                g.monthly_body_threshold_cache[dominant_future] = body_threshold
                updated_count += 1
                
                log.info(f"更新 {symbol}({dominant_future}) 实体长度阈值: {body_threshold:.4f}")
            
        except Exception as e:
            log.warning(f"更新{symbol}阈值时出错: {str(e)}")
            continue
    
    # 更新最后更新月份
    g.last_threshold_update_month = current_month
    
    log.info(f"阈值更新完成，共更新 {updated_count} 个品种")
    log.info("=" * 60)

def main_trading_stop_only(context):
    """仅进行止损止盈检查的交易时段"""
    # 只进行止损止盈检查
    task_7_check_stop_loss_profit(context)

def main_trading_complete(context):
    """14:55 完整交易检查 - 执行任务1, 2, 3, 4, 5, 6, 7"""
    log.info("=" * 60)
    log.info("14:55 烛台影线形态反向交易策略 - 完整交易检查")
    log.info("=" * 60)
    
    # 任务1: 获取所有可交易品种
    task_1_get_tradable_futures(context)
    
    # 任务2: 获取历史数据并处理阈值（包括单独计算缺失阈值）
    task_2_load_historical_data_and_thresholds(context)
    
    # 任务3: 获取今日分钟数据
    task_3_update_realtime_data(context)
    
    # 任务4: 检测烛台形态
    task_4_detect_candlestick_patterns(context)
    
    # 任务5: 检查开仓条件（简化版）
    filtered_signals = task_5_check_opening_conditions(context)

    # 任务6: 执行交易
    if filtered_signals:
        task_6_execute_trades(context, filtered_signals)
    
    # 任务7: 检查止损止盈
    task_7_check_stop_loss_profit(context)
    
    # 任务8: 检查换月移仓
    task_8_check_position_switch(context)

############################ 核心任务函数 ###################################

def task_1_get_tradable_futures(context):
    """任务1: 获取所有可交易品种（分白天和晚上）"""
    log.info("执行任务1: 获取可交易品种")
    
    current_time = str(context.current_dt.time())[:2]
    
    # 从策略关注列表中筛选可交易品种
    focus_symbols = g.strategy_focus_symbols if g.strategy_focus_symbols else list(g.futures_config.keys())
    
    potential_icon_list = []
    night_session_symbols = []
    day_only_symbols = []
    
    # 预先分类所有品种
    for symbol in focus_symbols:
        if get_futures_config(symbol, 'has_night_session', False):
            night_session_symbols.append(symbol)
        else:
            day_only_symbols.append(symbol)
    
    if current_time in ('21', '22'):
        # 夜盘时间：只考虑有夜盘的品种
        potential_icon_list = night_session_symbols[:]
        log.info(f"夜盘时间，有夜盘交易的品种: {len(night_session_symbols)}个")
        log.info(f"夜盘可交易品种: {potential_icon_list[:10]}{'...' if len(potential_icon_list) > 10 else ''}")  # 显示前10个，避免日志过长
    else:
        # 日盘时间：所有品种都可以交易（包括有夜盘的和只有日盘的）
        potential_icon_list = focus_symbols[:]
        log.info(f"日盘时间，全部品种: {len(focus_symbols)}个（含夜盘品种: {len(night_session_symbols)}个，日盘专属品种: {len(day_only_symbols)}个）")
        if day_only_symbols:
            log.info(f"日盘专属品种: {day_only_symbols}")
        log.info(f"日盘可交易品种: {potential_icon_list[:10]}{'...' if len(potential_icon_list) > 10 else ''}")  # 显示前10个，避免日志过长
    
    potential_future_list = []
    for symbol in potential_icon_list:
        dominant_future = get_dominant_future(symbol)
        if dominant_future:
            potential_future_list.append(dominant_future)
    
    # 过滤掉已有持仓的品种
    existing_positions = set(g.trade_history.keys())
    potential_future_list = [f for f in potential_future_list if not check_symbol_prefix_match(f, existing_positions)]
    
    # 存储到全局变量
    g.tradable_futures = potential_future_list
    log.info(f"最终可交易期货品种数量: {len(potential_future_list)}")
    
    return potential_future_list

def task_2_load_historical_data_and_thresholds(context):
    """任务2: 获取历史数据并处理阈值（包括单独计算缺失阈值）"""
    log.info("执行任务2: 加载历史数据并处理阈值")
    
    if not hasattr(g, 'tradable_futures'):
        return
    
    for future_code in g.tradable_futures:
        try:
            # 获取30天历史数据（用于分钟数据合并）
            data = attribute_history(future_code, 30, '1d', 
                                   ['open', 'close', 'high', 'low', 'volume'], 
                                   df=True)
            
            if data is not None and len(data) > 0:
                # 排除今天的数据
                today = context.current_dt.date()
                data = data[data.index.date < today]
                g.daily_data_cache[future_code] = data
                
                # 处理阈值：优先使用月度阈值，缺失时单独计算
                if future_code in g.monthly_body_threshold_cache:
                    # 使用月度阈值缓存
                    body_threshold = g.monthly_body_threshold_cache[future_code]
                    g.body_threshold_cache[future_code] = body_threshold
                    # log.info(f"已缓存 {future_code} 历史数据 {len(data)} 条，使用月度阈值: {body_threshold:.4f}")
                else:
                    # 单独计算缺失的阈值
                    log.info(f"{future_code} 未找到月度阈值，开始单独计算")
                    body_threshold = calculate_individual_threshold(context, future_code)
                    if body_threshold is not None:
                        g.body_threshold_cache[future_code] = body_threshold
                        log.info(f"已为 {future_code} 单独计算阈值: {body_threshold:.4f}")
                    else:
                        log.warning(f"{future_code} 无法计算阈值，跳过")
            
        except Exception as e:
            log.warning(f"加载{future_code}历史数据时出错: {str(e)}")
            continue
    
    log.info(f"历史数据缓存完成，共缓存 {len(g.daily_data_cache)} 个品种")

def calculate_individual_threshold(context, future_code):
    """为单个工具计算实体长度阈值并自动缓存到月度阈值中"""
    try:
        log.info(f"为 {future_code} 单独计算365天历史阈值")
        
        # 获取365天历史数据
        data = attribute_history(future_code, g.historical_days, '1d', 
                               ['open', 'close', 'high', 'low', 'volume'], 
                               df=True)
        
        if data is not None and len(data) > 30:  # 确保有足够数据
            # 排除今天的数据
            today = context.current_dt.date()
            data = data[data.index.date < today]
            
            # 计算实体长度阈值
            data['body_length'] = abs(data['close'] - data['open'])
            body_threshold = data['body_length'].mean()
            
            # 🚀 优化1：将计算结果自动添加到月度阈值缓存中
            g.monthly_body_threshold_cache[future_code] = body_threshold
            log.info(f"✅ {future_code} 单独计算完成，阈值: {body_threshold:.4f}，已添加到月度缓存")
            log.info(f"当前月度缓存包含 {len(g.monthly_body_threshold_cache)} 个品种阈值")
            
            return body_threshold
        else:
            log.warning(f"{future_code} 历史数据不足，无法计算阈值")
            return None
            
    except Exception as e:
        log.warning(f"为 {future_code} 单独计算阈值时出错: {str(e)}")
        return None

def task_3_update_realtime_data(context):
    """任务3: 获取今日分钟数据"""
    # log.info("执行任务3: 更新实时数据")
    
    # 收集需要更新数据的品种
    update_symbols = set()
    
    # 添加可交易品种
    if hasattr(g, 'tradable_futures') and g.tradable_futures:
        update_symbols.update(g.tradable_futures)
    
    # 添加持仓品种（用于止损止盈）
    if hasattr(g, 'trade_history') and g.trade_history:
        update_symbols.update(g.trade_history.keys())
    
    if not update_symbols:
        return
    
    for future_code in update_symbols:
        try:
            # 获取今日分钟数据
            minute_data = get_today_minute_data(context, future_code)
            if minute_data is None:
                continue
            
            # 获取历史数据
            historical_data = g.daily_data_cache.get(future_code)
            if historical_data is None:
                # 为持仓品种临时获取历史数据
                try:
                    data = attribute_history(future_code, g.historical_days, '1d', 
                                           ['open', 'close', 'high', 'low', 'volume'], 
                                           df=True)
                    if data is not None and len(data) > 0:
                        today = context.current_dt.date()
                        data = data[data.index.date < today]
                        
                        # 计算实体长度阈值
                        data['body_length'] = abs(data['close'] - data['open'])
                        body_threshold = data['body_length'].mean()
                        
                        g.daily_data_cache[future_code] = data
                        g.body_threshold_cache[future_code] = body_threshold
                        historical_data = data
                        log.info(f"为持仓品种 {future_code} 临时获取历史数据 {len(data)} 条")
                except Exception as e:
                    log.warning(f"获取{future_code}历史数据失败: {str(e)}")
                    continue
            
            if historical_data is None:
                continue
            
            # 将今日数据合并为日线数据
            today_data = aggregate_minute_to_daily(minute_data)
            if today_data is not None:
                # 合并历史数据和今日数据
                combined_data = pd.concat([historical_data, today_data], sort=False)
                g.minute_data_cache[future_code] = combined_data
            
        except Exception as e:
            log.warning(f"更新{future_code}实时数据时出错: {str(e)}")
            continue

def task_4_detect_candlestick_patterns(context):
    """任务4: 检测烛台形态"""
    # log.info("执行任务4: 检测烛台形态")
    
    candlestick_signals = []
    
    # 获取已持仓的品种列表
    existing_positions = set(g.trade_history.keys())
    
    for future_code, data in g.minute_data_cache.items():
        try:
            # 检查是否已有相似持仓，如果有则跳过分析
            if check_symbol_prefix_match(future_code, existing_positions):
                continue
            
            # 获取实体长度阈值
            body_threshold = g.body_threshold_cache.get(future_code)
            if body_threshold is None:
                continue
            
            # 检查最新的烛台形态
            latest_pattern = check_latest_candlestick_pattern(data, future_code, body_threshold)
            if latest_pattern:
                candlestick_signals.append(latest_pattern)
                log.info(f"{future_code} 发现烛台形态: {latest_pattern['hatch_direction']}影线")
                
        except Exception as e:
            log.warning(f"检测{future_code}烛台形态时出错: {str(e)}")
            continue
    
    # 存储到全局变量
    g.candlestick_signals = candlestick_signals
    if len(candlestick_signals) > 0:
        log.info(f"烛台形态检测完成，发现信号 {len(candlestick_signals)} 个")
    
    return candlestick_signals

def task_5_check_opening_conditions(context):
    """任务5: 检查开仓条件（简化版）"""
    log.info("执行任务5: 检查开仓条件（简化版）")
    
    if not hasattr(g, 'candlestick_signals') or not g.candlestick_signals:
        log.info("没有检测到烛台信号")
        return []
    
    log.info(f"检测到 {len(g.candlestick_signals)} 个烛台信号，开始筛选")
    
    filtered_signals = []
    
    for i, signal in enumerate(g.candlestick_signals):
        log.info(f"处理信号 {i+1}: {signal['symbol']} {signal['hatch_direction']}影线")
        
        # 仅检查是否已有相似持仓（避免重复开仓同一品种）
        if check_symbol_prefix_match(signal['symbol'], set(g.trade_history.keys())):
            log.info(f"{signal['symbol']} 已有相似持仓，跳过")
            continue
        
        # 简化版：只要形态满足条件就接受，无额外验证
        filtered_signals.append(signal)
        log.info(f"{signal['symbol']} 烛台形态满足条件，接受交易信号")
    
    log.info(f"开仓条件检查完成，满足条件 {len(filtered_signals)} 个")
    return filtered_signals

def task_6_execute_trades(context, filtered_signals):
    """任务6: 执行交易（简化版）"""
    log.info("执行任务6: 执行交易（简化版）")
    
    if not filtered_signals:
        log.info("没有满足条件的交易信号")
        return
    
    log.info(f"开始执行 {len(filtered_signals)} 个交易信号")
    
    for i, signal in enumerate(filtered_signals):
        symbol = signal['symbol']
        log.info(f"执行交易 {i+1}: {symbol} {signal['hatch_direction']}影线形态")
        
        # 使用可配置的开仓方向逻辑
        direction, logic_description = determine_trading_direction(symbol, signal['hatch_direction'])
        
        log.info(f"{symbol} 交易方向: {direction} ({logic_description})")
        
        try:
            # 计算目标手数（优化版：直接返回手数）
            target_hands = calculate_target_hands(context, symbol, direction)
            log.info(f"计算目标手数: {symbol} {direction} 目标手数: {target_hands}")
            
            if target_hands > 0:
                # 执行开仓
                log.info(f"开始下单: {symbol} {direction} 目标手数: {target_hands}")
                success = open_position(context, symbol, target_hands, direction, signal)
                
                if success:
                    actual_margin = g.trade_history[symbol]['actual_margin']
                    actual_price = g.trade_history[symbol]['entry_price']
                    log.info(f"✅ 成功开仓 {symbol} {direction}, 成交价格: {actual_price:.2f}, 目标手数: {target_hands}, 实际保证金: {actual_margin:.0f}")
                else:
                    log.warning(f"❌ 开仓失败 {symbol} {direction}")
            else:
                log.warning(f"{symbol} 计算目标手数为0，跳过")
        except Exception as e:
            log.warning(f"{symbol} 交易执行出错: {str(e)}")
            continue
    
    log.info("交易执行完成")

def task_8_check_position_switch(context):
    """任务8: 检查换月移仓"""
    # log.info("执行任务8: 检查换月移仓")
    
    switch_result = position_auto_switch(context)
    if switch_result:
        log.info(f"执行了 {len(switch_result)} 次移仓换月")
        for result in switch_result:
            log.info(f"移仓: {result['before']} -> {result['after']}")

def task_7_check_stop_loss_profit(context):
    """任务7: 检查止损止盈（带交易时间验证）"""
    # log.info("执行任务7: 检查止损止盈")
    
    # 获取当前时间
    current_time = context.current_dt.strftime('%H:%M')
    current_hour = int(current_time[:2])
    
    # 判断是否为夜盘时间（21:00-23:00 和 00:00-02:30）
    is_night_session = (current_hour >= 21) or (current_hour <= 2)
    
    # 遍历所有持仓进行止损止盈检查
    subportfolio = context.subportfolios[0]
    long_positions = list(subportfolio.long_positions.values())
    short_positions = list(subportfolio.short_positions.values())
    
    closed_count = 0
    skipped_count = 0
    
    for position in long_positions + short_positions:
        security = position.security
        underlying_symbol = security.split('.')[0][:-4]
        
        # 检查交易时间适配性
        has_night_session = get_futures_config(underlying_symbol, 'has_night_session', False)
        
        # 如果是夜盘时间，但品种不支持夜盘交易，则跳过
        if is_night_session and not has_night_session:
            skipped_count += 1
            # log.info(f"跳过夜盘时间的日间品种: {underlying_symbol} ({current_time})")
            continue
        
        # 执行止损止盈检查
        if check_stop_loss_profit(context, position):
            closed_count += 1
    
    if closed_count > 0:
        log.info(f"执行了 {closed_count} 次止损止盈")
    
    if skipped_count > 0:
        log.info(f"夜盘时间跳过 {skipped_count} 个日间品种的止损止盈检查")

############################ 数据处理辅助函数 ###################################

def check_has_night_session(underlying_symbol):
    """检查品种是否有夜盘"""
    return get_futures_config(underlying_symbol, 'has_night_session', False)

def get_today_minute_data(context, future_code):
    """获取今日分钟数据"""
    try:
        # 判断该品种是否有夜盘
        underlying_symbol = future_code.split('.')[0][:-4]
        has_night_session = check_has_night_session(underlying_symbol)
        
        end_time = context.current_dt
        
        # 获取足够的历史分钟数据
        minute_data = attribute_history(future_code, 
                                      count=800,  # 获取足够多的数据
                                      unit='1m',
                                      fields=['open', 'close', 'high', 'low', 'volume'],
                                      df=True)
        
        if minute_data is None or len(minute_data) == 0:
            return None
        
        # 提取所有日期（年月日维度）
        minute_data['date'] = minute_data.index.date
        unique_dates = sorted(minute_data['date'].unique())
        
        if has_night_session:
            # 有夜盘的品种：需要找到前一交易日的21:00作为今日开盘起点
            today_date = end_time.date()
            
            # 找到今天之前的最后一个交易日
            previous_trading_dates = [d for d in unique_dates if d < today_date]
            if not previous_trading_dates:
                return minute_data
            
            previous_trading_date = max(previous_trading_dates)
            
            # 找到前一交易日21:00:00的数据作为开盘起点
            previous_day_data = minute_data[minute_data['date'] == previous_trading_date]
            night_21_data = previous_day_data[previous_day_data.index.hour == 21]
            
            if len(night_21_data) > 0:
                # 从前一交易日21:00开始的所有数据
                start_time = night_21_data.index[0]  # 21:00:00的时间点
                filtered_data = minute_data[minute_data.index >= start_time]
                return filtered_data.drop(columns=['date'])
            else:
                # 备选方案：使用今天9:00开始的数据
                today_data = minute_data[minute_data['date'] == today_date]
                day_9_data = today_data[today_data.index.hour >= 9]
                if len(day_9_data) > 0:
                    return day_9_data.drop(columns=['date'])
                else:
                    return minute_data.drop(columns=['date'])
        else:
            # 没有夜盘的品种：从今天9:00:00开始
            today_date = end_time.date()
            today_data = minute_data[minute_data['date'] == today_date]
            
            # 找到今天9:00:00开始的数据
            day_9_data = today_data[today_data.index.hour >= 9]
            
            if len(day_9_data) > 0:
                return day_9_data.drop(columns=['date'])
            else:
                return today_data.drop(columns=['date']) if len(today_data) > 0 else minute_data.drop(columns=['date'])
        
    except Exception as e:
        log.warning(f"获取{future_code}今日分钟数据时出错: {str(e)}")
    
    return None

def aggregate_minute_to_daily(minute_data):
    """将分钟数据聚合为日数据"""
    try:
        if minute_data is None or len(minute_data) == 0:
            return None
        
        # 获取今日日期（使用最后一条数据的日期作为今日日期）
        today_date = minute_data.index[-1].date()
        
        # 聚合为日数据
        daily_data = pd.DataFrame({
            'open': [minute_data['open'].iloc[0]],  # 今日交易开始时的开盘价
            'close': [minute_data['close'].iloc[-1]],  # 当前收盘价，实时更新
            'high': [minute_data['high'].max()],
            'low': [minute_data['low'].min()],
            'volume': [minute_data['volume'].sum()]
        }, index=[pd.Timestamp(today_date)])
        
        return daily_data
        
    except Exception as e:
        log.warning(f"聚合分钟数据时出错: {str(e)}")
        return None

def check_latest_candlestick_pattern(data, future_code, body_threshold):
    """检查最新的烛台形态"""
    if len(data) < 1:
        return None
        
    # 获取最新一天的数据
    today = data.iloc[-1]
    
    # 检查烛台形态
    pattern_result = check_candlestick_pattern_single_day(today, body_threshold)
    if not pattern_result:
        return None
    
    return {
        'symbol': future_code,
        'date': today.name,
        'hatch_direction': pattern_result['hatch_direction'],
        'open': today['open'],
        'close': today['close'],
        'high': today['high'],
        'low': today['low'],
        'body_length': pattern_result['body_length'],
        'hatch_length': pattern_result['hatch_length']
    }

def check_candlestick_pattern_single_day(row, body_threshold):
    """检查单日烛台形态是否符合影线条件"""
    open_price = row['open']
    close_price = row['close']
    high_price = row['high']
    low_price = row['low']
    
    # 计算实体长度
    body_length = abs(close_price - open_price)
    
    # 检查实体长度是否满足阈值
    if body_length < body_threshold:
        return None
    
    # 计算影线长度
    upper_hatch = high_price - max(open_price, close_price)
    lower_hatch = min(open_price, close_price) - low_price
    
    # 检查影线条件
    hatch_direction = None
    hatch_length = 0
    
    # 检查上影线条件：上影线长度符合要求 且 下影线长度小于实体长度的一半
    if (upper_hatch >= g.hatch_to_body_ratio * body_length and 
        lower_hatch < g.opposite_hatch_ratio * body_length):
        hatch_direction = 'up'
        hatch_length = upper_hatch
    # 检查下影线条件：下影线长度符合要求 且 上影线长度小于实体长度的一半
    elif (lower_hatch >= g.hatch_to_body_ratio * body_length and 
          upper_hatch < g.opposite_hatch_ratio * body_length):
        hatch_direction = 'down'
        hatch_length = lower_hatch
    
    # 如果满足影线条件，返回形态信息
    if hatch_direction is not None:
        return {
            'hatch_direction': hatch_direction,
            'body_length': body_length,
            'hatch_length': hatch_length
        }
    
    return None

############################ 动态保证金率调整函数 ###################################

def detect_and_update_margin_rates(context, symbol, actual_hands, cash_change, direction):
    """
    检测并更新保证金率配置
    
    参数:
    symbol: 期货合约代码
    actual_hands: 实际成交手数
    cash_change: 实际资金变化（保证金使用）
    direction: 交易方向
    """
    try:
        underlying_symbol = symbol.split('.')[0][:-4]
        
        if underlying_symbol not in g.futures_config:
            return
        
        current_price = get_current_data()[symbol].last_price
        multiplier = get_multiplier(underlying_symbol)
        
        # 计算实际保证金率
        contract_value = current_price * multiplier * actual_hands
        actual_margin_rate = cash_change / contract_value if contract_value > 0 else 0
        
        # 获取配置中的保证金率
        config_margin_rate = g.futures_config[underlying_symbol]['margin_rate'][direction]
        
        # 计算差异百分比
        rate_diff_percentage = abs(actual_margin_rate - config_margin_rate) / config_margin_rate * 100 if config_margin_rate > 0 else 100
        
        # 如果差异超过10%，更新配置
        if rate_diff_percentage > 10:
            log.info(f"🔍 检测到{underlying_symbol}保证金率差异: 配置={config_margin_rate:.3f}, 实际={actual_margin_rate:.3f}, 差异={rate_diff_percentage:.1f}%")
            
            # 更新配置
            g.futures_config[underlying_symbol]['margin_rate'][direction] = actual_margin_rate
            
            # 如果是双向更新（多空保证金率通常相同）
            if g.futures_config[underlying_symbol]['margin_rate']['long'] == g.futures_config[underlying_symbol]['margin_rate']['short']:
                g.futures_config[underlying_symbol]['margin_rate']['long'] = actual_margin_rate
                g.futures_config[underlying_symbol]['margin_rate']['short'] = actual_margin_rate
                log.info(f"✅ 已更新{underlying_symbol}保证金率为 {actual_margin_rate:.3f} (双向)")
            else:
                log.info(f"✅ 已更新{underlying_symbol} {direction}保证金率为 {actual_margin_rate:.3f}")
                
    except Exception as e:
        log.warning(f"检测保证金率时出错 {symbol}: {str(e)}")

############################ 机会性仓位调整函数 ###################################

def opportunistic_position_increase(context, symbol, direction, signal):
    """
    机会性仓位调整：在保证金使用量低于限制时自动增加仓位
    
    参数:
    symbol: 期货合约代码
    direction: 交易方向
    signal: 交易信号
    """
    try:
        if symbol not in g.trade_history:
            return False
            
        underlying_symbol = symbol.split('.')[0][:-4]
        current_price = get_current_data()[symbol].last_price
        margin_rate = get_margin_rate(underlying_symbol, direction)
        multiplier = get_multiplier(underlying_symbol)
        
        # 获取当前持仓信息
        current_actual_margin = g.trade_history[symbol]['actual_margin']
        current_hands = g.trade_history[symbol]['actual_hands']
        
        # 计算剩余保证金容量
        max_margin = g.max_margin_per_position
        remaining_margin_capacity = max_margin - current_actual_margin
        
        # 检查是否有足够的剩余容量增加至少1手
        single_hand_margin = current_price * multiplier * margin_rate
        
        if remaining_margin_capacity >= single_hand_margin:
            # 计算可以增加的最大手数
            additional_hands = int(remaining_margin_capacity / single_hand_margin)
            
            # 同时考虑可用资金限制
            available_cash = context.portfolio.available_cash * g.usage_percentage
            max_hands_by_cash = int(available_cash / single_hand_margin)
            
            # 取较小值
            additional_hands = min(additional_hands, max_hands_by_cash)
            
            if additional_hands >= 1:
                log.info(f"🚀 机会性增仓机会: {symbol} 当前{current_hands}手(保证金:{current_actual_margin:.0f}), 可增加{additional_hands}手")
                
                # 计算新的目标手数
                new_target_hands = current_hands + additional_hands
                
                # 执行增仓
                order = order_target(symbol, new_target_hands, side=direction)
                
                if order and order.filled > 0:
                    # 计算实际增仓使用的保证金
                    cash_after = context.portfolio.available_cash
                    additional_margin_used = order.filled * single_hand_margin  # 估算使用的保证金
                    
                    # 更新交易记录
                    new_total_hands = current_hands + order.filled
                    new_total_margin = current_actual_margin + additional_margin_used
                    
                    g.trade_history[symbol]['actual_hands'] = new_total_hands
                    g.trade_history[symbol]['target_hands'] = new_target_hands
                    g.trade_history[symbol]['actual_margin'] = new_total_margin
                    
                    log.info(f"✅ 成功增仓 {symbol} {order.filled}手, 总手数: {new_total_hands}手, 总保证金: {new_total_margin:.0f}")
                    
                    # 记录增仓交易
                    g.today_trades.append({
                        'security': symbol,
                        'underlying_symbol': underlying_symbol,
                        'direction': direction,
                        'order_amount': order.filled,
                        'order_price': order.avg_cost if order.avg_cost else order.price,
                        'cash_change': additional_margin_used,
                        'time': context.current_dt,
                        'trade_type': 'increase'  # 标记为增仓
                    })
                    
                    return True
                    
        return False
        
    except Exception as e:
        log.warning(f"机会性增仓时出错 {symbol}: {str(e)}")
        return False

############################ 交易执行函数 ###################################

def open_position(context, security, target_hands, direction, signal):
    """开仓（优化版：使用order_target按手数开仓）"""
    try:
        # 记录交易前的可用资金
        cash_before = context.portfolio.available_cash
        
        # 使用order_target按手数开仓，自动处理持仓差额
        order = order_target(security, target_hands, side=direction)
        
        if order is not None and order.filled > 0:
            # 记录交易后的可用资金
            cash_after = context.portfolio.available_cash
            
            # 计算实际资金变化
            cash_change = cash_before - cash_after
            
            # 获取订单价格和数量
            order_price = order.avg_cost if order.avg_cost else order.price
            order_amount = order.filled
            
            # 记录当日交易
            underlying_symbol = security.split('.')[0][:-4]
            g.today_trades.append({
                'security': security,
                'underlying_symbol': underlying_symbol,
                'direction': direction,
                'order_amount': order_amount,
                'order_price': order_price,
                'cash_change': cash_change,
                'time': context.current_dt
            })
            
            # 记录交易信息，包含止损止盈相关信息
            g.trade_history[security] = {
                'entry_price': order_price,
                'target_hands': target_hands,
                'actual_hands': order_amount,
                'actual_margin': cash_change,
                'direction': direction,
                'entry_time': context.current_dt,
                'signal_info': signal,
                'max_profit': 0.0,  # 初始化最大利润
                'max_profit_price': order_price  # 记录最大利润时的价格
            }
            
            # 🚀 优化2：动态保证金率调整
            detect_and_update_margin_rates(context, security, order_amount, cash_change, direction)
            
            # 🚀 优化3：机会性仓位调整
            opportunistic_position_increase(context, security, direction, signal)
            
            return True
            
    except Exception as e:
        log.warning(f"开仓失败 {security}: {str(e)}")
    
    return False

def close_position(context, security, direction):
    """平仓（优化版：使用order_target平仓到0手）"""
    try:
        # 使用order_target平仓到0手，自动处理持仓清零
        order = order_target(security, 0, side=direction)
        
        if order is not None and order.filled > 0:
            underlying_symbol = security.split('.')[0][:-4]
            
            # 记录当日交易（平仓）
            g.today_trades.append({
                'security': security,
                'underlying_symbol': underlying_symbol,
                'direction': direction,
                'order_amount': -order.filled,  # 负数表示平仓
                'order_price': order.avg_cost if order.avg_cost else order.price,
                'cash_change': 0,  # 平仓不计算保证金变化
                'time': context.current_dt
            })
            
            log.info(f"平仓成功 - 品种: {underlying_symbol}, 平仓手数: {order.filled}")
            
            # 从交易历史中移除
            if security in g.trade_history:
                del g.trade_history[security]
            return True
            
    except Exception as e:
        log.warning(f"平仓失败 {security}: {str(e)}")
    
    return False

def check_stop_loss_profit(context, position):
    """检查止损止盈"""
    security = position.security
    
    if security not in g.trade_history:
        return False
    
    trade_info = g.trade_history[security]
    direction = trade_info['direction']
    entry_price = trade_info['entry_price']
    current_price = position.price
    
    # 计算当前盈亏比率
    if direction == 'long':
        profit_rate = (current_price - entry_price) / entry_price
    else:
        profit_rate = (entry_price - current_price) / entry_price
    
    # 更新最大利润记录
    if profit_rate > trade_info['max_profit']:
        trade_info['max_profit'] = profit_rate
        trade_info['max_profit_price'] = current_price
        g.trade_history[security] = trade_info
    
    # 检查固定止损
    if profit_rate <= -g.fixed_stop_loss_rate:
        log.info(f"触发固定止损 {security} {direction}, 当前亏损率: {profit_rate:.3%}, 成本价: {entry_price:.2f}, 当前价格: {current_price:.2f}")
        close_position(context, security, direction)
        return True
    
    # 检查动态追踪止盈
    max_profit = trade_info['max_profit']
    if max_profit > 0:
        # 确定追踪止损比率
        if max_profit <= g.trailing_stop_thresholds[0]:  # ≤5%
            trailing_rate = g.trailing_stop_rates[0]  # 1%
        elif max_profit <= g.trailing_stop_thresholds[1]:  # 5%-10%
            trailing_rate = g.trailing_stop_rates[1]  # 2%
        else:  # >10%
            trailing_rate = g.trailing_stop_rates[2]  # 3%
        
        # 检查是否触发追踪止损
        profit_drawdown = max_profit - profit_rate
        if profit_drawdown >= trailing_rate:
            log.info(f"触发动态追踪止损 {security} {direction}")
            log.info(f"最大利润: {max_profit:.3%}, 当前利润: {profit_rate:.3%}, 回撤: {profit_drawdown:.3%}, 触发阈值: {trailing_rate:.3%}")
            close_position(context, security, direction)
            return True
    
    return False

############################ 辅助函数 ###################################

def determine_trading_direction(symbol, hatch_direction):
    """
    确定开仓方向（支持可配置的正向/反向逻辑）
    
    参数:
    symbol: 期货合约代码 (如 'JD2510.XDCE')
    hatch_direction: 影线方向 ('up' 或 'down')
    
    返回:
    (direction, logic_description): 交易方向和逻辑说明的元组
    """
    # 提取基础品种代码
    underlying_symbol = symbol.split('.')[0][:-4]  # 如 'JD2510.XDCE' -> 'JD'
    
    # 检查是否在反向逻辑列表中
    use_reverse_logic = underlying_symbol in g.reverse_direction_symbols
    
    if use_reverse_logic:
        # 反向逻辑：上影线做空，下影线做多（当前逻辑）
        if hatch_direction == 'up':
            direction = 'short'
            logic_description = f"反向逻辑：{underlying_symbol}上影线做空"
        else:
            direction = 'long'
            logic_description = f"反向逻辑：{underlying_symbol}下影线做多"
    else:
        # 正向逻辑：上影线做多，下影线做空（新逻辑）
        if hatch_direction == 'up':
            direction = 'long'
            logic_description = f"正向逻辑：{underlying_symbol}上影线做多"
        else:
            direction = 'short'
            logic_description = f"正向逻辑：{underlying_symbol}下影线做空"
    
    return direction, logic_description

def get_futures_config(underlying_symbol, config_key=None, default_value=None):
    """获取期货品种配置信息的辅助函数"""
    if underlying_symbol not in g.futures_config:
        if config_key and default_value is not None:
            return default_value
        return {}
    
    if config_key is None:
        return g.futures_config[underlying_symbol]
    
    return g.futures_config[underlying_symbol].get(config_key, default_value)

def get_margin_rate(underlying_symbol, direction, default_rate=0.10):
    """获取保证金比例的辅助函数"""
    return g.futures_config.get(underlying_symbol, {}).get('margin_rate', {}).get(direction, default_rate)

def get_multiplier(underlying_symbol, default_multiplier=10):
    """获取合约乘数的辅助函数"""
    return g.futures_config.get(underlying_symbol, {}).get('multiplier', default_multiplier)

def calculate_target_hands(context, security, direction):
    """计算目标开仓手数（优化版：直接返回手数用于order_target）"""
    current_price = get_current_data()[security].last_price
    underlying_symbol = security.split('.')[0][:-4]
    
    # 使用保证金比例
    margin_rate = get_margin_rate(underlying_symbol, direction)
    multiplier = get_multiplier(underlying_symbol)
    
    # 计算单手保证金
    single_hand_margin = current_price * multiplier * margin_rate
    
    # 还要考虑可用资金限制
    available_cash = context.portfolio.available_cash * g.usage_percentage
    
    # 根据单个标的最大持仓保证金限制计算开仓数量
    max_margin = g.max_margin_per_position
    
    if single_hand_margin <= max_margin:
        # 如果单手保证金不超过最大限制，计算最大可开仓手数
        max_hands = int(max_margin / single_hand_margin)
        max_hands_by_cash = int(available_cash / single_hand_margin)
        
        # 取两者较小值
        actual_hands = min(max_hands, max_hands_by_cash)
        
        # 确保至少开1手
        actual_hands = max(1, actual_hands)
        
        # 实际保证金
        actual_margin = single_hand_margin * actual_hands
        
        log.info(f"单手保证金: {single_hand_margin:.0f}, 目标开仓手数: {actual_hands}, 预计保证金: {actual_margin:.0f}")
        
        # 直接返回手数，用于order_target()
        return actual_hands
    else:
        # 如果单手保证金超过最大限制，默认开仓1手
        actual_hands = 1
        actual_margin = single_hand_margin * actual_hands
        
        log.info(f"单手保证金: {single_hand_margin:.0f} 超过最大限制: {max_margin}, 默认开仓1手, 预计保证金: {actual_margin:.0f}")
        
        # 直接返回手数，用于order_target()
        return actual_hands

def check_sufficient_capital(context, symbol):
    """检查资金是否充足"""
    try:
        current_price = get_current_data()[symbol].last_price
        underlying_symbol = symbol.split('.')[0][:-4]
        
        margin_rate = get_margin_rate(underlying_symbol, 'long')
        multiplier = get_multiplier(underlying_symbol)
        
        # 计算单手保证金
        single_hand_margin = current_price * multiplier * margin_rate
        
        # 使用实际可用资金（考虑资金使用比例）
        available_cash = context.portfolio.available_cash * g.usage_percentage
        
        # 检查是否有足够资金开仓至少1手
        return available_cash >= single_hand_margin
    except:
        return False

def check_price_and_liquidity(signal):
    """检查价格合理性和流动性"""
    try:
        # 简单的合理性检查
        symbol = signal['symbol']
        current_data = get_current_data()[symbol]
        
        log.info(f"{symbol} 价格检查 - 当前价: {current_data.last_price:.2f}, 涨停: {current_data.high_limit:.2f}, 跌停: {current_data.low_limit:.2f}, 成交量: {current_data.volume}")
        
        # 检查是否处于涨跌停
        if current_data.last_price <= current_data.low_limit:
            log.warning(f"{symbol} 价格触及跌停板 ({current_data.last_price:.2f} <= {current_data.low_limit:.2f})，跳过")
            return False
            
        if current_data.last_price >= current_data.high_limit:
            log.warning(f"{symbol} 价格触及涨停板 ({current_data.last_price:.2f} >= {current_data.high_limit:.2f})，跳过")
            return False
        
        # 检查成交量是否充足
        if current_data.volume <= 0:
            log.warning(f"{symbol} 无成交量 ({current_data.volume})，跳过")
            return False
        
        log.info(f"{symbol} 价格和流动性检查通过")
        return True
    except Exception as e:
        log.warning(f"{signal['symbol']} 价格检查时出错: {str(e)}")
        return False

def check_symbol_prefix_match(symbol, hold_symbols):
    """检查是否有相似的持仓品种"""
    symbol_prefix = symbol[:-9]
    
    for hold_symbol in hold_symbols:
        hold_symbol_prefix = hold_symbol[:-9]
        if symbol_prefix == hold_symbol_prefix:
            return True
    return False

def after_market_close(context):
    """收盘后运行函数"""
    log.info(str('函数运行时间(after_market_close):'+str(context.current_dt.time())))
    
    # 只有当天有交易时才打印统计信息
    if g.today_trades:
        print_daily_trading_summary(context)
        
        # 清空当日交易记录
        g.today_trades = []
    
    log.info('##############################################################')

def print_daily_trading_summary(context):
    """打印当日交易汇总"""
    if not g.today_trades:
        return
    
    log.info("\n=== 当日交易汇总 ===")
    total_margin = 0
    
    for trade in g.today_trades:
        if trade['order_amount'] > 0:  # 开仓
            log.info(f"开仓 {trade['underlying_symbol']} {trade['direction']} {trade['order_amount']}手 "
                  f"价格:{trade['order_price']:.2f} 保证金:{trade['cash_change']:.0f}")
            total_margin += trade['cash_change']
        else:  # 平仓
            log.info(f"平仓 {trade['underlying_symbol']} {trade['direction']} {abs(trade['order_amount'])}手 "
                  f"价格:{trade['order_price']:.2f}")
    
    log.info(f"当日保证金占用: {total_margin:.0f}")
    log.info("==================\n")

########################## 自动移仓换月函数 #################################
def position_auto_switch(context, pindex=0, switch_func=None, callback=None):
    """
    期货自动移仓换月。默认使用市价单进行开平仓。
    """
    import re
    subportfolio = context.subportfolios[pindex]
    symbols = set(subportfolio.long_positions.keys()) | set(subportfolio.short_positions.keys())
    switch_result = []
    for symbol in symbols:
        match = re.match(r"(?P<underlying_symbol>[A-Z]{1,})", symbol)
        if not match:
            raise ValueError("未知期货标的: {}".format(symbol))
        else:
            dominant = get_dominant_future(match.groupdict()["underlying_symbol"])
            cur = get_current_data()
            symbol_last_price = cur[symbol].last_price
            dominant_last_price = cur[dominant].last_price
            log.info(f'当前持仓合约: {symbol}, 当前主力合约: {dominant}')
            
            if dominant > symbol:
                for positions_ in (subportfolio.long_positions, subportfolio.short_positions):
                    if symbol not in positions_.keys():
                        continue
                    else :
                        p = positions_[symbol]

                    if switch_func is not None:
                        switch_func(context, pindex, p, dominant)
                    else:
                        amount = p.total_amount
                        # 跌停不能开空和平多，涨停不能开多和平空。
                        if p.side == "long":
                            symbol_low_limit = cur[symbol].low_limit
                            dominant_high_limit = cur[dominant].high_limit
                            if symbol_last_price <= symbol_low_limit:
                                log.warning("标的{}跌停，无法平仓。移仓换月取消。".format(symbol))
                                continue
                            elif dominant_last_price >= dominant_high_limit:
                                log.warning("标的{}涨停，无法开仓。移仓换月取消。".format(dominant))
                                continue
                            else:
                                log.info("进行移仓换月: ({0},long) -> ({1},long)".format(symbol, dominant))
                                order_old = order_target(symbol, 0, side='long')
                                if order_old != None and order_old.filled > 0:
                                    order_new = order_target(dominant, amount, side='long')
                                    if order_new != None and order_new.filled > 0:
                                        switch_result.append({"before": symbol, "after": dominant, "side": "long"})
                                        # 换月中的买卖都成功了，则增加新的记录去掉旧的记录
                                        g.trade_history[dominant] = g.trade_history[symbol]
                                        del g.trade_history[symbol]
                                    else:
                                        log.warning("标的{}交易失败，无法开仓。移仓换月失败。".format(dominant))
                        if p.side == "short":
                            symbol_high_limit = cur[symbol].high_limit
                            dominant_low_limit = cur[dominant].low_limit
                            if symbol_last_price >= symbol_high_limit:
                                log.warning("标的{}涨停，无法平仓。移仓换月取消。".format(symbol))
                                continue
                            elif dominant_last_price <= dominant_low_limit:
                                log.warning("标的{}跌停，无法开仓。移仓换月取消。".format(dominant))
                                continue
                            else:
                                log.info("进行移仓换月: ({0},short) -> ({1},short)".format(symbol, dominant))
                                order_old = order_target(symbol, 0, side='short')
                                if order_old != None and order_old.filled > 0:
                                    order_new = order_target(dominant, amount, side='short')
                                    if order_new != None and order_new.filled > 0:
                                        switch_result.append({"before": symbol, "after": dominant, "side": "short"})
                                        # 换月中的买卖都成功了，则增加新的记录去掉旧的记录
                                        g.trade_history[dominant] = g.trade_history[symbol]
                                        del g.trade_history[symbol]
                                    else:
                                        log.warning("标的{}交易失败，无法开仓。移仓换月失败。".format(dominant))
                        if callback:
                            callback(context, pindex, p, dominant)
    return switch_result