同花顺SuperMind 股票策略编写必知必会

2023-10-23 | 0 评论 | 0 浏览

同花顺SuperMind 股票策略编写必知必会

1.策略框架

1.策略框架

In [1]:

source_code = """
def init(context):
    g.is_fired = True
    log.info("初始化,仅在策略第一次运行时执行")

def before_trading(context):
    date = get_datetime().strftime('%Y-%m-%d %H:%M:%S')
    log.info('{} 盘前运行'.format(date))

def open_auction(context,bar_dict):
    date = get_datetime().strftime('%Y-%m-%d %H:%M:%S')
    log.info('{} 集合竞价后运行'.format(date))

def handle_bar(context,bar_dict):
    date = get_datetime().strftime('%Y-%m-%d %H:%M:%S')
    log.info('{} 盘中运行'.format(date))
    if g.is_fired:
        odr_id = order('000001.SZ',100)
        g.is_fired = False

def on_order(context,odr):
    log.info('委托状态更新推送')
    log.info(odr)

def on_trade(context,trade):
    log.info('成交推送')
    log.info(trade)

def after_trading(context):
    date = get_datetime().strftime('%Y-%m-%d %H:%M:%S')
    log.info('{} 盘后运行'.format(date))  
"""

In [2]:

btest = research_strategy(
    source_code=source_code,start_date='20230801',end_date='20230801',
    capital_base=float(1000000),frequency='MINUTE',stock_market='STOCK',
    benchmark='000300.SH',plot=True
)

2023-08-01 00:00:00.000000 - INFO - 初始化,仅在策略第一次运行时执行
2023-08-01 09:00:00.000000 - INFO - 2023-08-01 09:00:00 盘前运行
2023-08-01 09:26:00.000000 - INFO - 2023-08-01 09:26:00 集合竞价后运行
2023-08-01 09:31:00.000000 - INFO - 2023-08-01 09:31:00 盘中运行
2023-08-01 09:31:00.000000 - INFO - 委托状态更新推送
2023-08-01 09:31:00.000000 - INFO - Order({'id': 'b2e33d44a4874dd59286ef9b04c98b9c', 'symbol': '000001.SZ', 'created': datetime.datetime(2023, 8, 1, 9, 31), 'order_type': 'LONG', 'limit_price': 0, 'amount': 100, 'filled_amount': 0, 'type': ORDER_TYPE.MARKET, 'transaction_cost': 0, 'avg_price': 0, 'status': ORDER_STATUS.PENDING_NEW, 'datetime': datetime.datetime(2023, 8, 1, 9, 31), 'offset_flag': None})
2023-08-01 09:31:00.000000 - INFO - 委托状态更新推送
2023-08-01 09:31:00.000000 - INFO - Order({'id': 'b2e33d44a4874dd59286ef9b04c98b9c', 'symbol': '000001.SZ', 'created': datetime.datetime(2023, 8, 1, 9, 31), 'order_type': 'LONG', 'limit_price': 0, 'amount': 100, 'filled_amount': 0, 'type': ORDER_TYPE.MARKET, 'transaction_cost': 0, 'avg_price': 0, 'status': ORDER_STATUS.ACTIVE, 'datetime': datetime.datetime(2023, 8, 1, 9, 31), 'offset_flag': None})
2023-08-01 09:31:00.000000 - INFO - 委托状态更新推送
2023-08-01 09:31:00.000000 - INFO - Order({'id': 'b2e33d44a4874dd59286ef9b04c98b9c', 'symbol': '000001.SZ', 'created': datetime.datetime(2023, 8, 1, 9, 31), 'order_type': 'LONG', 'limit_price': 0, 'amount': 100, 'filled_amount': 100, 'type': ORDER_TYPE.MARKET, 'transaction_cost': 5, 'avg_price': 12.22221, 'status': ORDER_STATUS.FILLED, 'datetime': datetime.datetime(2023, 8, 1, 9, 31), 'offset_flag': None})
2023-08-01 09:31:00.000000 - INFO - 成交推送
2023-08-01 09:31:00.000000 - INFO - Trade({'order_book_id': '000001.SZ', 'trading_datetime': datetime.datetime(2023, 8, 1, 9, 31), 'datetime': datetime.datetime(2023, 8, 1, 9, 31), 'order_id': 'b2e33d44a4874dd59286ef9b04c98b9c', 'last_price': 12.22221, 'last_quantity': 100, 'commission': 5, 'tax': 0, 'transaction_cost': 5, 'side': SIDE.BUY, 'position_effect': None, 'exec_id': 'a8081b2bddb74ce9af2867b525d61c7d', 'frozen_price': 12.2, 'close_today_amount': 0})
2023-08-01 09:32:00.000000 - INFO - 2023-08-01 09:32:00 盘中运行
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2023-08-01 14:06:00.000000 - INFO - 2023-08-01 14:06:00 盘中运行
2023-08-01 14:07:00.000000 - INFO - 2023-08-01 14:07:00 盘中运行
2023-08-01 14:08:00.000000 - INFO - 2023-08-01 14:08:00 盘中运行
2023-08-01 14:09:00.000000 - INFO - 2023-08-01 14:09:00 盘中运行
2023-08-01 14:10:00.000000 - INFO - 2023-08-01 14:10:00 盘中运行
2023-08-01 14:11:00.000000 - INFO - 2023-08-01 14:11:00 盘中运行
2023-08-01 14:12:00.000000 - INFO - 2023-08-01 14:12:00 盘中运行
2023-08-01 14:13:00.000000 - INFO - 2023-08-01 14:13:00 盘中运行
2023-08-01 14:14:00.000000 - INFO - 2023-08-01 14:14:00 盘中运行
2023-08-01 14:15:00.000000 - INFO - 2023-08-01 14:15:00 盘中运行
2023-08-01 14:16:00.000000 - INFO - 2023-08-01 14:16:00 盘中运行
2023-08-01 14:17:00.000000 - INFO - 2023-08-01 14:17:00 盘中运行
2023-08-01 14:18:00.000000 - INFO - 2023-08-01 14:18:00 盘中运行
2023-08-01 14:19:00.000000 - INFO - 2023-08-01 14:19:00 盘中运行
2023-08-01 14:20:00.000000 - INFO - 2023-08-01 14:20:00 盘中运行
2023-08-01 14:21:00.000000 - INFO - 2023-08-01 14:21:00 盘中运行
2023-08-01 14:22:00.000000 - INFO - 2023-08-01 14:22:00 盘中运行
2023-08-01 14:23:00.000000 - INFO - 2023-08-01 14:23:00 盘中运行
2023-08-01 14:24:00.000000 - INFO - 2023-08-01 14:24:00 盘中运行
2023-08-01 14:25:00.000000 - INFO - 2023-08-01 14:25:00 盘中运行
2023-08-01 14:26:00.000000 - INFO - 2023-08-01 14:26:00 盘中运行
2023-08-01 14:27:00.000000 - INFO - 2023-08-01 14:27:00 盘中运行
2023-08-01 14:28:00.000000 - INFO - 2023-08-01 14:28:00 盘中运行
2023-08-01 14:29:00.000000 - INFO - 2023-08-01 14:29:00 盘中运行
2023-08-01 14:30:00.000000 - INFO - 2023-08-01 14:30:00 盘中运行
2023-08-01 14:31:00.000000 - INFO - 2023-08-01 14:31:00 盘中运行
2023-08-01 14:32:00.000000 - INFO - 2023-08-01 14:32:00 盘中运行
2023-08-01 14:33:00.000000 - INFO - 2023-08-01 14:33:00 盘中运行
2023-08-01 14:34:00.000000 - INFO - 2023-08-01 14:34:00 盘中运行
2023-08-01 14:35:00.000000 - INFO - 2023-08-01 14:35:00 盘中运行
2023-08-01 14:36:00.000000 - INFO - 2023-08-01 14:36:00 盘中运行
2023-08-01 14:37:00.000000 - INFO - 2023-08-01 14:37:00 盘中运行
2023-08-01 14:38:00.000000 - INFO - 2023-08-01 14:38:00 盘中运行
2023-08-01 14:39:00.000000 - INFO - 2023-08-01 14:39:00 盘中运行
2023-08-01 14:40:00.000000 - INFO - 2023-08-01 14:40:00 盘中运行
2023-08-01 14:41:00.000000 - INFO - 2023-08-01 14:41:00 盘中运行
2023-08-01 14:42:00.000000 - INFO - 2023-08-01 14:42:00 盘中运行
2023-08-01 14:43:00.000000 - INFO - 2023-08-01 14:43:00 盘中运行
2023-08-01 14:44:00.000000 - INFO - 2023-08-01 14:44:00 盘中运行
2023-08-01 14:45:00.000000 - INFO - 2023-08-01 14:45:00 盘中运行
2023-08-01 14:46:00.000000 - INFO - 2023-08-01 14:46:00 盘中运行
2023-08-01 14:47:00.000000 - INFO - 2023-08-01 14:47:00 盘中运行
2023-08-01 14:48:00.000000 - INFO - 2023-08-01 14:48:00 盘中运行
2023-08-01 14:49:00.000000 - INFO - 2023-08-01 14:49:00 盘中运行
2023-08-01 14:50:00.000000 - INFO - 2023-08-01 14:50:00 盘中运行
2023-08-01 14:51:00.000000 - INFO - 2023-08-01 14:51:00 盘中运行
2023-08-01 14:52:00.000000 - INFO - 2023-08-01 14:52:00 盘中运行
2023-08-01 14:53:00.000000 - INFO - 2023-08-01 14:53:00 盘中运行
2023-08-01 14:54:00.000000 - INFO - 2023-08-01 14:54:00 盘中运行
2023-08-01 14:55:00.000000 - INFO - 2023-08-01 14:55:00 盘中运行
2023-08-01 14:56:00.000000 - INFO - 2023-08-01 14:56:00 盘中运行
2023-08-01 14:57:00.000000 - INFO - 2023-08-01 14:57:00 盘中运行
2023-08-01 14:58:00.000000 - INFO - 2023-08-01 14:58:00 盘中运行
2023-08-01 14:59:00.000000 - INFO - 2023-08-01 14:59:00 盘中运行
2023-08-01 15:00:00.000000 - INFO - 2023-08-01 15:00:00 盘中运行
2023-08-01 15:30:00.000000 - INFO - 2023-08-01 15:30:00 盘后运行

2.设置函数

包括设置基准,手续费,滑点,初始持仓,等设置性函数,可参考帮助-股票API-设置函数,这里不在赘述

3.重要对象

3.1. context

用于存储策略信息(context.run_info),账户持仓数据(context.portfolio),自定义全局变量

context.run_info
- start_date:策略起始时间
- end_date:策略结束时间
- frequency:策略运行频率
- stock_starting_cash:股票账户初始资金
- future_starting_cash:期货期权账户初始资金
- benchmark:基准指数
- margin_multiplier:保证金率
context.portfolio
- available_cash:可用资金
- frozen_cash:冻结资金
- returns:收益率
- market_value:持仓市值
- portfolio_value:总资产
- starting_value：初始资金
- pnl:盈亏
- start_date:策略起始时间
- positions：持仓信息
- datetime：当前bar时间
- stock_account: 股票账户数据
- future_account: 期货期权账户数据

In [3]:

source_code = """
def init(context):
    context.fired=True
    log.info(context.run_info)
    log.info(context.portfolio)
    log.info(context.fired)

def handle_bar(context,bar_dict):
    if context.fired:
        odr_id = order('000001.SZ',100)
        context.fired = False
        log.info(context.run_info)
        log.info(context.portfolio)
        log.info(context.fired)

        log.info(context.portfolio.positions) #输出看起来像个列表,实际类似于字典
        log.info(context.portfolio.stock_account.positions)

        log.info(context.portfolio.positions['000001.SZ'])
        log.info(context.portfolio.stock_account.positions['000001.SZ'])
"""

In [4]:

btest = research_strategy(
    source_code=source_code,start_date='20230801',end_date='20230801',
    capital_base=float(1000000),frequency='MINUTE',stock_market='STOCK',
    benchmark='000300.SH',plot=True
)

2023-08-01 00:00:00.000000 - INFO - RunInfo({'start_date': datetime.date(2023, 8, 1), 'end_date': datetime.date(2023, 8, 1), 'frequency': '1m', 'stock_starting_cash': 1000000.0, 'future_starting_cash': 0, 'benchmark': '000300.SH', 'margin_multiplier': 1, 'run_type': RUN_TYPE.BACKTEST})
2023-08-01 00:00:00.000000 - INFO - Portfolio({'available_cash': 1000000.0, 'frozen_cash': 0, 'returns': 0.0, 'market_value': 0, 'portfolio_value': 1000000.0, 'starting_value': 1000000.0, 'pnl': 0.0, 'start_date': datetime.date(2023, 8, 1), 'positions': [], 'datetime': datetime.datetime(2023, 8, 1, 0, 0)})
2023-08-01 00:00:00.000000 - INFO - True
2023-08-01 09:31:00.000000 - INFO - RunInfo({'start_date': datetime.date(2023, 8, 1), 'end_date': datetime.date(2023, 8, 1), 'frequency': '1m', 'stock_starting_cash': 1000000.0, 'future_starting_cash': 0, 'benchmark': '000300.SH', 'margin_multiplier': 1, 'run_type': RUN_TYPE.BACKTEST})
2023-08-01 09:31:00.000000 - INFO - Portfolio({'available_cash': 998772.779, 'frozen_cash': 0.0, 'returns': -7.2210000000572094e-06, 'market_value': 1220.0, 'portfolio_value': 999992.779, 'starting_value': 1000000.0, 'pnl': -7.221000000057209, 'start_date': datetime.date(2023, 8, 1), 'positions': ['000001.SZ'], 'datetime': datetime.datetime(2023, 8, 1, 9, 31)})
2023-08-01 09:31:00.000000 - INFO - False
2023-08-01 09:31:00.000000 - INFO - ['000001.SZ']
2023-08-01 09:31:00.000000 - INFO - {'000001.SZ': StockPosition({'symbol': '000001.SZ', 'amount': 100, 'available_amount': 0, 'pnl': -7.221000000000011, 'market_value': 1220.0, 'cost_basis': 12.27221, 'last_price': 12.2, 'datetime': datetime.datetime(2023, 8, 1, 9, 31), 'position_days': 0, 'profit_rate': -0.00586015008671335, 'draw_down': 0.005860150086713367, 'markup': -0.009740259740259822, 'pre_price': 12.32})}
2023-08-01 09:31:00.000000 - INFO - StockPosition({'symbol': '000001.SZ', 'amount': 100, 'available_amount': 0, 'pnl': -7.221000000000011, 'market_value': 1220.0, 'cost_basis': 12.27221, 'last_price': 12.2, 'datetime': datetime.datetime(2023, 8, 1, 9, 31), 'position_days': 0, 'profit_rate': -0.00586015008671335, 'draw_down': 0.005860150086713367, 'markup': -0.009740259740259822, 'pre_price': 12.32})
2023-08-01 09:31:00.000000 - INFO - StockPosition({'symbol': '000001.SZ', 'amount': 100, 'available_amount': 0, 'pnl': -7.221000000000011, 'market_value': 1220.0, 'cost_basis': 12.27221, 'last_price': 12.2, 'datetime': datetime.datetime(2023, 8, 1, 9, 31), 'position_days': 0, 'profit_rate': -0.00586015008671335, 'draw_down': 0.005860150086713367, 'markup': -0.009740259740259822, 'pre_price': 12.32})

3.2. g

和context的功能类似,存储全局变量,自定义的全局变量推荐存在g里,避免将系统全局变量覆盖

In [5]:

source_code = """
def init(context):
    g.abc=123

def handle_bar(context,bar_dict):
    print(g.abc)
"""

In [6]:

btest = research_strategy(
    source_code=source_code,start_date='20230801',end_date='20230801',
    capital_base=float(1000000),frequency='MINUTE',stock_market='STOCK',
    benchmark='000300.SH',plot=True
)

2023-08-01 09:31:00.000000 - INFO - 123
2023-08-01 09:32:00.000000 - INFO - 123
2023-08-01 09:33:00.000000 - INFO - 123
2023-08-01 09:34:00.000000 - INFO - 123
2023-08-01 09:35:00.000000 - INFO - 123
2023-08-01 09:36:00.000000 - INFO - 123
2023-08-01 09:37:00.000000 - INFO - 123
2023-08-01 09:38:00.000000 - INFO - 123
2023-08-01 09:39:00.000000 - INFO - 123
2023-08-01 09:40:00.000000 - INFO - 123
2023-08-01 09:41:00.000000 - INFO - 123
2023-08-01 09:42:00.000000 - INFO - 123
2023-08-01 09:43:00.000000 - INFO - 123
2023-08-01 09:44:00.000000 - INFO - 123
2023-08-01 09:45:00.000000 - INFO - 123
2023-08-01 09:46:00.000000 - INFO - 123
2023-08-01 09:47:00.000000 - INFO - 123
2023-08-01 09:48:00.000000 - INFO - 123
2023-08-01 09:49:00.000000 - INFO - 123
2023-08-01 09:50:00.000000 - INFO - 123
2023-08-01 09:51:00.000000 - INFO - 123
2023-08-01 09:52:00.000000 - INFO - 123
2023-08-01 09:53:00.000000 - INFO - 123
2023-08-01 09:54:00.000000 - INFO - 123
2023-08-01 09:55:00.000000 - INFO - 123
2023-08-01 09:56:00.000000 - INFO - 123
2023-08-01 09:57:00.000000 - INFO - 123
2023-08-01 09:58:00.000000 - INFO - 123
2023-08-01 09:59:00.000000 - INFO - 123
2023-08-01 10:00:00.000000 - INFO - 123
2023-08-01 10:01:00.000000 - INFO - 123
2023-08-01 10:02:00.000000 - INFO - 123
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2023-08-01 10:04:00.000000 - INFO - 123
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2023-08-01 10:11:00.000000 - INFO - 123
2023-08-01 10:12:00.000000 - INFO - 123
2023-08-01 10:13:00.000000 - INFO - 123
2023-08-01 10:14:00.000000 - INFO - 123
2023-08-01 10:15:00.000000 - INFO - 123
2023-08-01 10:16:00.000000 - INFO - 123
2023-08-01 10:17:00.000000 - INFO - 123
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2023-08-01 10:19:00.000000 - INFO - 123
2023-08-01 10:20:00.000000 - INFO - 123
2023-08-01 10:21:00.000000 - INFO - 123
2023-08-01 10:22:00.000000 - INFO - 123
2023-08-01 10:23:00.000000 - INFO - 123
2023-08-01 10:24:00.000000 - INFO - 123
2023-08-01 10:25:00.000000 - INFO - 123
2023-08-01 10:26:00.000000 - INFO - 123
2023-08-01 10:27:00.000000 - INFO - 123
2023-08-01 10:28:00.000000 - INFO - 123
2023-08-01 10:29:00.000000 - INFO - 123
2023-08-01 10:30:00.000000 - INFO - 123
2023-08-01 10:31:00.000000 - INFO - 123
2023-08-01 10:32:00.000000 - INFO - 123
2023-08-01 10:33:00.000000 - INFO - 123
2023-08-01 10:34:00.000000 - INFO - 123
2023-08-01 10:35:00.000000 - INFO - 123
2023-08-01 10:36:00.000000 - INFO - 123
2023-08-01 10:37:00.000000 - INFO - 123
2023-08-01 10:38:00.000000 - INFO - 123
2023-08-01 10:39:00.000000 - INFO - 123
2023-08-01 10:40:00.000000 - INFO - 123
2023-08-01 10:41:00.000000 - INFO - 123
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2023-08-01 10:43:00.000000 - INFO - 123
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2023-08-01 10:48:00.000000 - INFO - 123
2023-08-01 10:49:00.000000 - INFO - 123
2023-08-01 10:50:00.000000 - INFO - 123
2023-08-01 10:51:00.000000 - INFO - 123
2023-08-01 10:52:00.000000 - INFO - 123
2023-08-01 10:53:00.000000 - INFO - 123
2023-08-01 10:54:00.000000 - INFO - 123
2023-08-01 10:55:00.000000 - INFO - 123
2023-08-01 10:56:00.000000 - INFO - 123
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2023-08-01 11:00:00.000000 - INFO - 123
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2023-08-01 11:27:00.000000 - INFO - 123
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2023-08-01 14:35:00.000000 - INFO - 123
2023-08-01 14:36:00.000000 - INFO - 123
2023-08-01 14:37:00.000000 - INFO - 123
2023-08-01 14:38:00.000000 - INFO - 123
2023-08-01 14:39:00.000000 - INFO - 123
2023-08-01 14:40:00.000000 - INFO - 123
2023-08-01 14:41:00.000000 - INFO - 123
2023-08-01 14:42:00.000000 - INFO - 123
2023-08-01 14:43:00.000000 - INFO - 123
2023-08-01 14:44:00.000000 - INFO - 123
2023-08-01 14:45:00.000000 - INFO - 123
2023-08-01 14:46:00.000000 - INFO - 123
2023-08-01 14:47:00.000000 - INFO - 123
2023-08-01 14:48:00.000000 - INFO - 123
2023-08-01 14:49:00.000000 - INFO - 123
2023-08-01 14:50:00.000000 - INFO - 123
2023-08-01 14:51:00.000000 - INFO - 123
2023-08-01 14:52:00.000000 - INFO - 123
2023-08-01 14:53:00.000000 - INFO - 123
2023-08-01 14:54:00.000000 - INFO - 123
2023-08-01 14:55:00.000000 - INFO - 123
2023-08-01 14:56:00.000000 - INFO - 123
2023-08-01 14:57:00.000000 - INFO - 123
2023-08-01 14:58:00.000000 - INFO - 123
2023-08-01 14:59:00.000000 - INFO - 123
2023-08-01 15:00:00.000000 - INFO - 123

3.3. 委托对象order

on_order函数推送,或使用get_order/get_orders/get_open_orders函数查询

order_id:委托订单id
symbol:标的代码
created:订单创建时间
order_type:订单类型LONG/SHORT
limit_price:限价,市价单为0
amount:委托数量
filled_amount:成交数量
type:委托类型(市价/限价)
transaction_cost:交易成本
avg_price:平均成交价
status:委托状态
- ORDER_STATUS.PENDING_NEW：初始化中
- ORDER_STATUS.ACTIVE：活动中（未成交、部分成交）
- ORDER_STATUS.FILLED：已完成（全部成交）
- ORDER_STATUS.REJECTED：废单
- ORDER_STATUS.CANCELLED：已撤单（全撤、部成部撤）
datetime：当前时间
offset_flag：延迟成交信息

3.4. 成交对象trade

on_trade函数推送,或使用get_tradelogs函数查询

order_id:委托订单id
order_book_id:标的代码
trading_datetime:成交时间
side:订单类型SIDE.BUY/SIDE.SELL
last_price:成交价(包含交易成本在内)
last_quantity:成交数量
transaction_cost:交易成本
commission：手续费
tax:印花税
datetime：当前时间

3.5. bar_dict对象

In [7]:

source_code = """
def init(context):
    g.fired = True

def handle_bar(context,bar_dict):
    if g.fired:
        log.info(bar_dict['000001.SZ'])
        log.info(bar_dict['000001.SZ'].datetime)
        log.info(bar_dict['000001.SZ'].close)
        g.fired=False
"""

In [8]:

btest = research_strategy(
    source_code=source_code,start_date='20230801',end_date='20230801',
    capital_base=float(1000000),frequency='MINUTE',stock_market='STOCK',
    benchmark='000300.SH',plot=True
)

2023-08-01 09:31:00.000000 - INFO - Bar(symbol: '000001.SZ', datetime: datetime.datetime(2023, 8, 1, 9, 31), high_limit: 13.55, low_limit: 11.09, prev_close: 12.32, avg_price: 12.221932316118936, is_st: False, is_paused: False, open: 12.26, close: 12.2, volume: 2556000.0, turnover: 31239259.0, is_paused: False)
2023-08-01 09:31:00.000000 - INFO - 2023-08-01 09:31:00
2023-08-01 09:31:00.000000 - INFO - 12.2

4.常用数据接口

4.1 历史行情数据

调用方式：history(symbol_list, fields, bar_count, fre_step, skip_paused = False, fq = 'pre', is_panel=0)

取当前K线之前的{bar_dict}根K线的数据

symbol_list：股票代码,list/str
fields：字段,list,支持字段可参考日频行情,分钟行情
bar_count：向前取多少根K线的数据
fre_step：步长,常用为'1d'(1天),'1m'(1分钟)
skip_paused：是否跳过停牌
fq：
- fq = None：不复权
- fq = 'post'：后复权
- fq = 'pre'：前复权（以当前K线作为基准向前复权）
is_panel：
- False: 返回格式为key为股票代码,value为dataframe的字典
- True: 返回panel格式

In [9]:

source_code = '''
def init(context):
    pass

def before_trading(context):
    ohlcv = history(['000001.SZ','600519.SH'], ['open','high','low','close','volume'], 5, '1d', skip_paused = False, fq = 'pre', is_panel=0)
    log.info(ohlcv)

    ohlcv = history(['000001.SZ','600519.SH'], ['open','high','low','close','volume'], 5, '1d', skip_paused = False, fq = 'pre', is_panel=1)
    log.info(ohlcv)
    log.info(ohlcv.to_frame())
'''

In [10]:

btest = research_strategy(
    source_code=source_code,start_date='20230801',end_date='20230801',
    capital_base=float(1000000),frequency='MINUTE',stock_market='STOCK',
    benchmark='000300.SH',plot=True
)

2023-08-01 09:00:00.000000 - INFO - {'000001.SZ':              open   high    low  close       volume
2023-07-25  11.45  11.73  11.44  11.72  203295819.0
2023-07-26  11.65  11.74  11.56  11.67   75166268.0
2023-07-27  11.68  11.87  11.65  11.75  111519586.0
2023-07-28  11.69  12.30  11.67  12.26  234701346.0
2023-07-31  12.30  12.50  12.23  12.32  185495239.0, '600519.SH':                open     high      low    close     volume
2023-07-25  1800.00  1828.88  1799.99  1828.55  4308646.0
2023-07-26  1828.55  1835.99  1815.08  1828.55  1961145.0
2023-07-27  1836.00  1854.79  1828.70  1838.03  2034043.0
2023-07-28  1832.00  1900.00  1828.01  1897.00  3901792.0
2023-07-31  1908.00  1935.00  1874.00  1880.58  4537861.0}
2023-08-01 09:00:00.000000 - INFO - <class 'pd_Panel'>
Dimensions: 5 (items) x 5 (major_axis) x 2 (minor_axis)
Items axis: open to volume
Major_axis axis: 2023-07-25T00:00:00.000000000 to 2023-07-31T00:00:00.000000000
Minor_axis axis: 000001.SZ to 600519.SH
2023-08-01 09:00:00.000000 - INFO - items                    open     high      low    close       volume
major      minor                                                   
2023-07-25 000001.SZ    11.45    11.73    11.44    11.72  203295819.0
           600519.SH  1800.00  1828.88  1799.99  1828.55    4308646.0
2023-07-26 000001.SZ    11.65    11.74    11.56    11.67   75166268.0
           600519.SH  1828.55  1835.99  1815.08  1828.55    1961145.0
2023-07-27 000001.SZ    11.68    11.87    11.65    11.75  111519586.0
           600519.SH  1836.00  1854.79  1828.70  1838.03    2034043.0
2023-07-28 000001.SZ    11.69    12.30    11.67    12.26  234701346.0
           600519.SH  1832.00  1900.00  1828.01  1897.00    3901792.0
2023-07-31 000001.SZ    12.30    12.50    12.23    12.32  185495239.0
           600519.SH  1908.00  1935.00  1874.00  1880.58    4537861.0

4.2 表数据

4.2.1 query对象

这边只讲简单的使用方法,具体可以参考官方文档继续学习sqlalchemy文档

表与字段

In [11]:

q = query(
    concept_classification#表名
)

In [ ]:

run_query(q) #取整张表太大了，不进行演示

In [12]:

q = query(
    concept_classification.symbol,#表名.字段
    concept_classification.date,
    concept_classification.concept
)

filter设置条件

相当于SQL中的where

In [13]:

run_query(
    q.filter(
        concept_classification.symbol=='300033.SZ',
        concept_classification.date>'20230201'
    )
)

Out[13]:

	concept_classification_symbol	concept_classification_date	concept_classification_concept
0	300033.SZ	20230202	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
1	300033.SZ	20230203	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
2	300033.SZ	20230206	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
3	300033.SZ	20230207	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
4	300033.SZ	20230208	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
...	...	...	...
118	300033.SZ	20230726	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
119	300033.SZ	20230727	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
120	300033.SZ	20230728	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
121	300033.SZ	20230731	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
122	300033.SZ	20230801	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...

123 rows × 3 columns

In [14]:

run_query(
    q.filter(
        concept_classification.symbol.in_(['300033.SZ','600519.SH']),
        concept_classification.date=='20230201'
    )
)

Out[14]:

	concept_classification_symbol	concept_classification_date	concept_classification_concept
0	300033.SZ	20230201	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
1	600519.SH	20230201	同花顺漂亮100,超级品牌,富时罗素概念,融资融券,国企改革,MSCI概念,央视财经50,标...

指定查前几条数据：limit

In [15]:

run_query(
    q.filter(
        concept_classification.symbol=='300033.SZ',
        concept_classification.date>'20230201'
    ).limit(10)
)

Out[15]:

	concept_classification_symbol	concept_classification_date	concept_classification_concept
0	300033.SZ	20230202	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
1	300033.SZ	20230203	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
2	300033.SZ	20230206	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
3	300033.SZ	20230207	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
4	300033.SZ	20230208	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
5	300033.SZ	20230209	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
6	300033.SZ	20230210	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
7	300033.SZ	20230213	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
8	300033.SZ	20230214	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
9	300033.SZ	20230215	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...

排序：order_by

In [16]:

run_query(
    q.filter(
        concept_classification.symbol=='300033.SZ',
        concept_classification.date>'20230201'
    ).order_by(
        concept_classification.date.desc()
    ).limit(10)
)

Out[16]:

	concept_classification_symbol	concept_classification_date	concept_classification_concept
0	300033.SZ	20230801	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
1	300033.SZ	20230731	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
2	300033.SZ	20230728	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
3	300033.SZ	20230727	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
4	300033.SZ	20230726	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
5	300033.SZ	20230725	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
6	300033.SZ	20230724	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
7	300033.SZ	20230721	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
8	300033.SZ	20230720	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
9	300033.SZ	20230719	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...

In [17]:

run_query(
    q.filter(
        concept_classification.symbol=='300033.SZ',
        concept_classification.date>'20230201'
    ).order_by(
        concept_classification.date.asc()
    ).limit(10)
)

Out[17]:

	concept_classification_symbol	concept_classification_date	concept_classification_concept
0	300033.SZ	20230202	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
1	300033.SZ	20230203	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
2	300033.SZ	20230206	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
3	300033.SZ	20230207	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
4	300033.SZ	20230208	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
5	300033.SZ	20230209	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
6	300033.SZ	20230210	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
7	300033.SZ	20230213	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
8	300033.SZ	20230214	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
9	300033.SZ	20230215	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...

In [18]:

run_query(
    q.filter(
        concept_classification.symbol=='300033.SZ',
        concept_classification.date>'20230201'
    ).order_by(
        concept_classification.date
    ).limit(10)
)

Out[18]:

	concept_classification_symbol	concept_classification_date	concept_classification_concept
0	300033.SZ	20230202	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
1	300033.SZ	20230203	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
2	300033.SZ	20230206	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
3	300033.SZ	20230207	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
4	300033.SZ	20230208	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
5	300033.SZ	20230209	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
6	300033.SZ	20230210	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
7	300033.SZ	20230213	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
8	300033.SZ	20230214	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...
9	300033.SZ	20230215	电子商务,证金持股,融资融券,基金三方销售,机器人概念,ChatGPT概念,金融科技,转融券...

4.2.2 财务数据表

调用方式： get_fundamentals(query_object, date=None, statDate=None, latest=False)

query_object：query对象
date：查询指定日期的财务数据
statDate：查询指定季度或年份的财务数据
latest：是否取最新报告期

In [19]:

#获取全市场2022年报资产负债表中的总资产数据，仅取合并报表
data = get_fundamentals(
    query(
        balance.symbol,
        balance.report_date,
        balance.stat_date,
        balance.total_assets
    ).filter(
        balance.reporttypecode == 'HB'
    ),
    statDate = '2022q4'
)

In [20]:

data

Out[20]:

	balance_stat_symbol	balance_stat_report_date	balance_stat_stat_date	balance_stat_total_assets
0	000001.SZ	2023-03-09	2022-12-31	5.321514e+12
1	000002.SZ	2023-03-31	2022-12-31	1.757124e+12
2	000003.SZ	2023-04-28	2022-12-31	4.733694e+07
3	000004.SZ	2023-04-29	2022-12-31	5.753907e+08
4	000005.SZ	2023-04-29	2022-12-31	2.602190e+09
...	...	...	...	...
5356	873305.BJ	2023-04-26	2022-12-31	3.578005e+08
5357	873339.BJ	2023-04-12	2022-12-31	7.227376e+08
5358	873527.BJ	2023-04-17	2022-12-31	5.867523e+08
5359	873576.BJ	2023-03-02	2022-12-31	6.605258e+08
5360	873593.BJ	2023-02-24	2022-12-31	3.661453e+08

5361 rows × 4 columns

In [21]:

#获取全市场2023年2月1日全市场股票最近一期资产负债表中的总资产数据，取最新报告数据
data = get_fundamentals(
    query(
        balance.symbol,
        balance.date,
        balance.report_date,
        balance.stat_date,
        balance.total_assets
    ),
    date = '20230201',
    latest = True
)

In [22]:

data

Out[22]:

	balance_symbol	balance_date	balance_report_date	balance_stat_date	balance_total_assets
0	000001.SZ	2023-02-01	2022-10-25	2022-09-30	5.195133e+12
1	000002.SZ	2023-02-01	2022-10-29	2022-09-30	1.832624e+12
2	000004.SZ	2023-02-01	2022-10-28	2022-09-30	1.053263e+09
3	000005.SZ	2023-02-01	2022-10-31	2022-09-30	2.359511e+09
4	000006.SZ	2023-02-01	2022-10-28	2022-09-30	2.631976e+10
...	...	...	...	...	...
5073	873169.BJ	2023-02-01	2022-10-28	2022-09-30	3.459986e+08
5074	873223.BJ	2023-02-01	2022-10-26	2022-09-30	4.906200e+08
5075	873305.BJ	2023-02-01	2022-10-20	2022-09-30	2.281411e+08
5076	873339.BJ	2023-02-01	2022-10-17	2022-09-30	6.065306e+08
5077	873527.BJ	2023-02-01	2022-10-27	2022-09-30	4.367683e+08

5078 rows × 5 columns

5.下单与撤单

5.1下单

跟据绝对数量下单

order(id_or_ins,amount,price=None) 指定数量下单
order_value(id_or_ins,cash_amount,price=None) 指定金额下单,自动跟据金额与价格计算下单数量,并下单
order_percent(id_or_ins,percent,price=None) 指定总资产占比下单,自动跟据比例、总计产、价格计算下单数量,并下单

跟据目标值下单,可能会下0股,导致日志出现warn

order_target(id_or_ins,amount,price=None) 设定目标数量下单，跟据目标数量和当前实际持有数量计算下单数量
order_target_value(id_or_ins,cash_amount,price=None) 设定目标金额下单，跟据目标金额和当前实际持有市值计算下单数量
order_target_percent(id_or_ins,percent,price=None) 设定目标持仓占比，跟据目标持仓占比和当前持仓占计算下单数量

下单成功,返回订单委托id,失败则返回None

在回测中,以市价单买入涨停股或者卖出跌停股,订单会作为失败处理,而限价单会挂着

5.2 撤单

指定id撤单 cancel_order(order_id)

全撤 cancel_order_all()

In [23]:

source_code = '''
def init(context):
    g.fired = True

def handle_bar(context,bar_dict):
    if g.fired:
        order_id = order('000001.SZ',100,bar_dict['000001.SZ'].close*0.98)
        cancel_order(order_id)
        g.fired = False

def on_order(context,odr):
    print(odr)
'''

In [24]:

btest = research_strategy(
    source_code=source_code,start_date='20230801',end_date='20230801',
    capital_base=float(1000000),frequency='MINUTE',stock_market='STOCK',
    benchmark='000300.SH',plot=True
)

2023-08-01 09:31:00.000000 - INFO - Order({'id': '5d091e5c20174815a3cc840cd5f6c8f9', 'symbol': '000001.SZ', 'created': datetime.datetime(2023, 8, 1, 9, 31), 'order_type': 'LONG', 'limit_price': 11.956, 'amount': 100, 'filled_amount': 0, 'type': ORDER_TYPE.LIMIT, 'transaction_cost': 0, 'avg_price': 0, 'status': ORDER_STATUS.PENDING_NEW, 'datetime': datetime.datetime(2023, 8, 1, 9, 31), 'offset_flag': None})
2023-08-01 09:31:00.000000 - INFO - Order({'id': '5d091e5c20174815a3cc840cd5f6c8f9', 'symbol': '000001.SZ', 'created': datetime.datetime(2023, 8, 1, 9, 31), 'order_type': 'LONG', 'limit_price': 11.956, 'amount': 100, 'filled_amount': 0, 'type': ORDER_TYPE.LIMIT, 'transaction_cost': 0, 'avg_price': 0, 'status': ORDER_STATUS.ACTIVE, 'datetime': datetime.datetime(2023, 8, 1, 9, 31), 'offset_flag': None})
2023-08-01 09:31:00.000000 - INFO - Order({'id': '5d091e5c20174815a3cc840cd5f6c8f9', 'symbol': '000001.SZ', 'created': datetime.datetime(2023, 8, 1, 9, 31), 'order_type': 'LONG', 'limit_price': 11.956, 'amount': 100, 'filled_amount': 0, 'type': ORDER_TYPE.LIMIT, 'transaction_cost': 0, 'avg_price': 0, 'status': ORDER_STATUS.ACTIVE, 'datetime': datetime.datetime(2023, 8, 1, 9, 31), 'offset_flag': None})
2023-08-01 09:31:00.000000 - WARN - 订单 5d091e5c20174815a3cc840cd5f6c8f9 被取消。
2023-08-01 09:31:00.000000 - INFO - Order({'id': '5d091e5c20174815a3cc840cd5f6c8f9', 'symbol': '000001.SZ', 'created': datetime.datetime(2023, 8, 1, 9, 31), 'order_type': 'LONG', 'limit_price': 11.956, 'amount': 100, 'filled_amount': 0, 'type': ORDER_TYPE.LIMIT, 'transaction_cost': 0, 'avg_price': 0, 'status': ORDER_STATUS.CANCELLED, 'datetime': datetime.datetime(2023, 8, 1, 9, 31), 'offset_flag': None})

In [ ]:

标题：同花顺SuperMind 股票策略编写必知必会
作者：michael
地址：https://blog.junxworks.cn/articles/2023/10/23/1698023555540.html