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系统已经设置了默认的交易手续费和滑点，要修改手续费可使用如下函数\n context.subscribe(context.instruments[0])\n context.set_universe(context.instruments[0]) # 设置需要处理的合约\n context.bar_series = NumPyDeque(200, dtype='object') # 20个分钟 K线 （包括OHLC）\n context.bar_index = 0 # 分钟K线序号\n context.big_cycle_bar_index = 0 #30分钟大周期K线序号\n context.ma_periods = 26 \n\n \n \n ","type":"Literal","bound_global_parameter":null},{"name":"before_trading_start","value":"# 交易引擎：每个单位时间开盘前调用一次。\ndef bigquant_run(context, data):\n pass","type":"Literal","bound_global_parameter":null},{"name":"handle_tick","value":"# 交易引擎：tick数据处理函数，每个tick执行一次\ndef bigquant_run(context, tick):\n pass\n","type":"Literal","bound_global_parameter":null},{"name":"handle_data","value":"# 回测引擎：每日数据处理函数，每天执行一次\ndef bigquant_run(context, data):\n \n import talib as ta\n context.bar_index += 1\n cur_date = data.current_dt\n cur_hm = cur_date.strftime('%H:%M')\n \n \n if context.bar_index % 30 == 0: # 30m k线\n context.big_cycle_bar_index += 1\n \n sid = context.symbol(context.instruments[0])# 标的为字符串格式\n hist = data.history(sid, [\"open\",\"high\",\"low\",\"close\"], 30, \"1m\")\n big_cycle_bar_data = {'datetime':hist.index[-1],'high':hist.high.max(),'open':hist.open.values[0],'low':hist.low.min(),'close':hist.close.values[-1]}\n context.bar_series.append(big_cycle_bar_data)\n \n if context.big_cycle_bar_index > context.ma_periods : # 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    In [2]:
    # 本代码由可视化策略环境自动生成 2022年12月12日 14:11
# 本代码单元只能在可视化模式下编辑。您也可以拷贝代码，粘贴到新建的代码单元或者策略，然后修改。


# 回测引擎：初始化函数，只执行一次
def m3_initialize_bigquant_run(context):
    # 系统已经设置了默认的交易手续费和滑点，要修改手续费可使用如下函数
    context.subscribe(context.instruments[0])
    context.set_universe(context.instruments[0]) # 设置需要处理的合约
    context.bar_series =  NumPyDeque(200, dtype='object')  # 20个分钟 K线 （包括OHLC）
    context.bar_index = 0 # 分钟K线序号
    context.big_cycle_bar_index = 0 #30分钟大周期K线序号
    context.ma_periods  = 26 

     
 
 
# 交易引擎：每个单位时间开盘前调用一次。
def m3_before_trading_start_bigquant_run(context, data):
    pass
# 交易引擎：tick数据处理函数，每个tick执行一次
def m3_handle_tick_bigquant_run(context, tick):
    pass

# 回测引擎：每日数据处理函数，每天执行一次
def m3_handle_data_bigquant_run(context, data):
    
    import talib as ta
    context.bar_index += 1
    cur_date =  data.current_dt
    cur_hm = cur_date.strftime('%H:%M')
 
    
    if context.bar_index % 30 == 0:   # 30m k线
        context.big_cycle_bar_index += 1
            
        sid = context.symbol(context.instruments[0])# 标的为字符串格式
        hist = data.history(sid, ["open","high","low","close"], 30, "1m")
        big_cycle_bar_data = {'datetime':hist.index[-1],'high':hist.high.max(),'open':hist.open.values[0],'low':hist.low.min(),'close':hist.close.values[-1]}
        context.bar_series.append(big_cycle_bar_data)
       
        if context.big_cycle_bar_index > context.ma_periods :  # 30分钟大周期K线的移动平均26个周期的均值  
            price_data = pd.DataFrame(list(context.bar_series))
            
            sma = talib.SMA(price_data['close'], timeperiod=context.ma_periods ).values[-1]
            cur_price = price_data['close'].values[-1]
            cur_position = context.portfolio.positions[sid].amount # 持仓 
            
            if cur_position==0 and cur_price>sma:
                context.order(sid, 100)
                print('buy'*5, cur_date)
                
            elif  cur_position>0 and cur_price<sma:
                context.order_target_percent(sid, 0)
                print('sell'*5, cur_date)

            
            

        
         

    
    
    
    
    
    
    
    
    
    
    
    

   
# 交易引擎：成交回报处理函数，每个成交发生时执行一次
def m3_handle_trade_bigquant_run(context, trade):
    pass 

# 交易引擎：委托回报处理函数，每个委托变化时执行一次
def m3_handle_order_bigquant_run(context, order):
    pass

# 交易引擎：盘后处理函数，每日盘后执行一次
def m3_after_trading_bigquant_run(context, data):
    pass


m1 = M.instruments.v2(
    start_date='2022-01-01',
    end_date=T.live_run_param('trading_date', '2022-03-11'),
    market='CN_STOCK_A',
    instrument_list='600519.SHA',
    max_count=0,
    m_cached=False
)

m3 = M.hftrade.v2(
    instruments=m1.data,
    start_date='',
    end_date='',
    initialize=m3_initialize_bigquant_run,
    before_trading_start=m3_before_trading_start_bigquant_run,
    handle_tick=m3_handle_tick_bigquant_run,
    handle_data=m3_handle_data_bigquant_run,
    handle_trade=m3_handle_trade_bigquant_run,
    handle_order=m3_handle_order_bigquant_run,
    after_trading=m3_after_trading_bigquant_run,
    capital_base=500000,
    frequency='minute',
    price_type='真实价格',
    product_type='股票',
    before_start_days='0',
    volume_limit=1,
    order_price_field_buy='open',
    order_price_field_sell='open',
    benchmark='000300.HIX',
    plot_charts=True,
    disable_cache=False,
    replay_bdb=True,
    show_debug_info=False,
    backtest_only=False
)

    buybuybuybuybuy 2022-01-12 10:30:00
sellsellsellsellsell 2022-01-13 10:00:00
buybuybuybuybuy 2022-01-18 10:00:00
sellsellsellsellsell 2022-01-24 13:30:00
buybuybuybuybuy 2022-01-26 14:30:00
sellsellsellsellsell 2022-01-28 10:00:00
buybuybuybuybuy 2022-02-09 13:30:00
sellsellsellsellsell 2022-02-11 13:30:00
buybuybuybuybuy 2022-02-14 11:30:00
sellsellsellsellsell 2022-02-14 14:30:00
sellsellsellsellsell 2022-02-17 13:30:00
buybuybuybuybuy 2022-02-18 11:00:00
sellsellsellsellsell 2022-02-21 10:30:00
buybuybuybuybuy 2022-02-25 10:00:00
sellsellsellsellsell 2022-02-25 10:30:00
sellsellsellsellsell 2022-02-25 11:00:00
sellsellsellsellsell 2022-02-25 11:30:00
sellsellsellsellsell 2022-02-25 13:30:00
sellsellsellsellsell 2022-02-28 10:00:00
buybuybuybuybuy 2022-02-28 15:00:00
buybuybuybuybuy 2022-03-01 10:00:00
sellsellsellsellsell 2022-03-03 10:00:00
buybuybuybuybuy 2022-03-08 14:00:00
sellsellsellsellsell 2022-03-08 14:30:00
sellsellsellsellsell 2022-03-08 15:00:00
sellsellsellsellsell 2022-03-09 14:00:00
buybuybuybuybuy 2022-03-09 14:30:00
sellsellsellsellsell 2022-03-11 10:00:00
buybuybuybuybuy 2022-03-11 14:30:00
sellsellsellsellsell 2022-03-11 15:00:00

    ---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-2-2232d4dc55fe> in <module>
     97 )
     98 
---> 99 m3 = M.hftrade.v2(
    100     instruments=m1.data,
    101     start_date='',

AttributeError: 'BigQuantModule' object has no attribute '_basic_info_ds'