gm_utils.py

# -*- coding: utf-8 -*-
"""
author: zengbin93
email: zeng_bin8888@163.com
create_dt: 2021/11/17 22:11
describe: 配合 CzscAdvancedTrader 进行使用的掘金工具
"""
import os
import dill
import inspect
import czsc
import traceback
import pandas as pd
from gm.api import *
from datetime import datetime, timedelta, timezone
from collections import OrderedDict
from typing import List, Callable
from czsc.traders import CzscAdvancedTrader
from czsc.utils import qywx as wx
from czsc.utils.bar_generator import BarGenerator
from czsc.utils.log import create_logger
from czsc.objects import RawBar, Event, Freq, Operate, PositionLong, PositionShort
from czsc.signals.signals import get_default_signals

dt_fmt = "%Y-%m-%d %H:%M:%S"
date_fmt = "%Y-%m-%d"

assert czsc.__version__ >= "0.8.13"


def set_gm_token(token):
    with open(os.path.join(os.path.expanduser("~"), "gm_token.txt"), 'w', encoding='utf-8') as f:
        f.write(token)


file_token = os.path.join(os.path.expanduser("~"), "gm_token.txt")
if not os.path.exists(file_token):
    print("{} 文件不存在，请单独启动一个 python 终端，调用 set_gm_token 方法创建该文件，再重新执行。".format(file_token))
else:
    gm_token = open(file_token, encoding="utf-8").read()
    set_token(gm_token)

freq_gm2cn = {"60s": "1分钟", "300s": "5分钟", "900s": "15分钟",
              "1800s": "30分钟", "3600s": "60分钟", "1d": "日线"}
freq_cn2gm = {v: k for k, v in freq_gm2cn.items()}


indices = {
    "上证指数": 'SHSE.000001',
    "上证50": 'SHSE.000016',
    "沪深300": "SHSE.000300",
    "中证1000": "SHSE.000852",

    "深证成指": "SZSE.399001",
    "创业板指数": 'SZSE.399006',
    "深次新股": "SZSE.399678",
    "中小板指": "SZSE.399005",
    "中证500": "SZSE.399905",
    "国证2000": "SZSE.399303",
    "小盘成长": "SZSE.399376",
    "小盘价值": "SZSE.399377",
}


def is_trade_date(dt):
    """判断 dt 时刻是不是交易日期"""
    dt = pd.to_datetime(dt)
    date_ = dt.strftime("%Y-%m-%d")
    trade_dates = get_trading_dates(exchange='SZSE', start_date=date_, end_date=date_)
    if trade_dates:
        return True
    else:
        return False


def is_trade_time(dt):
    """判断 dt 时刻是不是交易时间"""
    dt = pd.to_datetime(dt)
    date_ = dt.strftime("%Y-%m-%d")
    trade_dates = get_trading_dates(exchange='SZSE', start_date=date_, end_date=date_)
    if trade_dates and "15:00" > dt.strftime("%H:%M") > "09:30":
        return True
    else:
        return False


def get_stocks():
    """获取股票市场标的列表，包括股票、指数等"""
    df = get_instruments(exchanges='SZSE,SHSE', fields="symbol,sec_name", df=True)
    shares = {row['symbol']: row['sec_name'] for _, row in df.iterrows()}
    return shares


def get_index_shares(name, end_date=None):
    """获取某一交易日的指数成分股列表

    symbols = get_index_shares("上证50", "2019-01-01 09:30:00")
    """
    if not end_date:
        end_date = datetime.now().strftime(date_fmt)
    else:
        end_date = pd.to_datetime(end_date).strftime(date_fmt)
    constituents = get_history_constituents(indices[name], end_date, end_date)[0]
    symbol_list = [k for k, v in constituents['constituents'].items()]
    return list(set(symbol_list))


def format_kline(df, freq: Freq):
    bars = []
    for i, row in df.iterrows():
        bar = RawBar(symbol=row['symbol'], id=i, freq=freq, dt=row['eob'], open=round(row['open'], 2),
                     close=round(row['close'], 2), high=round(row['high'], 2),
                     low=round(row['low'], 2), vol=row['volume'], amount=row['amount'])
        bars.append(bar)
    return bars


def get_kline(symbol, end_time, freq='60s', count=33000, adjust=ADJUST_PREV):
    """获取K线数据

    :param symbol: 标的代码
    :param end_time: 结束时间
    :param freq: K线周期
    :param count: K线数量
    :param adjust: 复权方式
    :return:
    """
    if isinstance(end_time, datetime):
        end_time = end_time.strftime(dt_fmt)

    exchange = symbol.split(".")[0]
    freq_map_ = {'60s': Freq.F1, '300s': Freq.F5, '900s': Freq.F15, '1800s': Freq.F30,
                 '3600s': Freq.F60, '1d': Freq.D}

    if exchange in ["SZSE", "SHSE"]:
        df = history_n(symbol=symbol, frequency=freq, end_time=end_time, adjust=adjust,
                       fields='symbol,eob,open,close,high,low,volume,amount', count=count, df=True)
    else:
        df = history_n(symbol=symbol, frequency=freq, end_time=end_time, adjust=adjust,
                       fields='symbol,eob,open,close,high,low,volume,amount,position', count=count, df=True)
    return format_kline(df, freq_map_[freq])


def get_init_bg(symbol: str,
                end_dt: [str, datetime],
                base_freq: str,
                freqs: List[str],
                max_count=1000,
                adjust=ADJUST_PREV):
    """获取 symbol 的初始化 bar generator"""
    if isinstance(end_dt, str):
        end_dt = pd.to_datetime(end_dt, utc=True)
        end_dt = end_dt.tz_convert('dateutil/PRC')
        # 时区转换之后，要减去8个小时才是设置的时间
        end_dt = end_dt - timedelta(hours=8)
    else:
        assert end_dt.tzinfo._filename == 'PRC'
    last_day = (end_dt - timedelta(days=10)).replace(hour=16, minute=0)

    bg = BarGenerator(base_freq, freqs, max_count)
    if "周线" in freqs or "月线" in freqs:
        d_bars = get_kline(symbol=symbol, end_time=last_day, freq=freq_cn2gm["日线"], count=5000, adjust=adjust)
        bgd = BarGenerator("日线", ['周线', '月线', '季线', '年线'])
        for b in d_bars:
            bgd.update(b)
    else:
        bgd = None

    for freq in bg.bars.keys():
        if freq in ['周线', '月线', '季线', '年线']:
            bars_ = bgd.bars[freq]
        else:
            bars_ = get_kline(symbol=symbol, end_time=last_day, freq=freq_cn2gm[freq], count=max_count, adjust=adjust)
        bg.bars[freq] = bars_
        print(f"{symbol} - {freq} - {len(bg.bars[freq])} - last_dt: {bg.bars[freq][-1].dt} - last_day: {last_day}")

    bars2 = get_kline(symbol=symbol, end_time=end_dt, freq=freq_cn2gm[base_freq],
                      count=int(240 / int(base_freq.strip('分钟'))*10))
    data = [x for x in bars2 if x.dt > last_day]
    assert len(data) > 0
    print(f"{symbol}: bar generator 最新时间 {bg.bars[base_freq][-1].dt.strftime(dt_fmt)}，还有{len(data)}行数据需要update")
    return bg, data


order_side_map = {OrderSide_Unknown: '其他', OrderSide_Buy: '买入', OrderSide_Sell: '卖出'}
order_status_map = {
    OrderStatus_Unknown: "其他",
    OrderStatus_New: "已报",
    OrderStatus_PartiallyFilled: "部成",
    OrderStatus_Filled: "已成",
    OrderStatus_Canceled: "已撤",
    OrderStatus_PendingCancel: "待撤",
    OrderStatus_Rejected: "已拒绝",
    OrderStatus_Suspended: "挂起（无效）",
    OrderStatus_PendingNew: "待报",
    OrderStatus_Expired: "已过期",
}
pos_side_map = {PositionSide_Unknown: '其他', PositionSide_Long: '多头', PositionSide_Short: '空头'}
pos_effect_map = {
    PositionEffect_Unknown: '其他',
    PositionEffect_Open: '开仓',
    PositionEffect_Close: '平仓',
    PositionEffect_CloseToday: '平今仓',
    PositionEffect_CloseYesterday: '平昨仓',
}
exec_type_map = {
    ExecType_Unknown: "其他",
    ExecType_New: "已报",
    ExecType_Canceled: "已撤销",
    ExecType_PendingCancel: "待撤销",
    ExecType_Rejected: "已拒绝",
    ExecType_Suspended: "挂起",
    ExecType_PendingNew: "待报",
    ExecType_Expired: "过期",
    ExecType_Trade: "成交(有效)",
    ExecType_OrderStatus: "委托状态",
    ExecType_CancelRejected: "撤单被拒绝(有效)",
}


def on_order_status(context, order):
    """
    https://www.myquant.cn/docs/python/python_object_trade#007ae8f5c7ec5298

    :param context:
    :param order:
    :return:
    """
    if not is_trade_time(context.now):
        return

    symbol = order.symbol
    latest_dt = context.now.strftime("%Y-%m-%d %H:%M:%S")
    logger = context.logger

    if symbol not in context.symbols_info.keys():
        msg = f"订单状态更新通知：\n{'*' * 31}\n" \
              f"更新时间：{latest_dt}\n" \
              f"标的名称：{symbol} {context.stocks.get(symbol, '无名')}\n" \
              f"操作类型：{order_side_map[order.side]}{pos_effect_map[order.position_effect]}\n" \
              f"操作描述：非机器交易标的\n" \
              f"下单价格：{round(order.price, 2)}\n" \
              f"最新状态：{order_status_map[order.status]}\n" \
              f"委托（股）：{int(order.volume)}\n" \
              f"已成（股）：{int(order.filled_volume)}\n" \
              f"均价（元）：{round(order.filled_vwap, 2)}"

    else:
        trader: GmCzscTrader = context.symbols_info[symbol]['trader']
        if trader.long_pos.operates:
            last_op_desc = trader.long_pos.operates[-1]['op_desc']
        else:
            last_op_desc = ""

        msg = f"订单状态更新通知：\n{'*' * 31}\n" \
              f"更新时间：{latest_dt}\n" \
              f"标的名称：{symbol} {context.stocks.get(symbol, '无名')}\n" \
              f"操作类型：{order_side_map[order.side]}{pos_effect_map[order.position_effect]}\n" \
              f"操作描述：{last_op_desc}\n" \
              f"下单价格：{round(order.price, 2)}\n" \
              f"最新状态：{order_status_map[order.status]}\n" \
              f"委托（股）：{int(order.volume)}\n" \
              f"已成（股）：{int(order.filled_volume)}\n" \
              f"均价（元）：{round(order.filled_vwap, 2)}"

    logger.info(msg.replace("\n", " - ").replace('*', ""))
    if context.mode != MODE_BACKTEST and order.status in [1, 3, 5, 8, 9, 12]:
        wx.push_text(content=str(msg), key=context.wx_key)


def on_execution_report(context, execrpt):
    """响应委托被执行事件，委托成交或者撤单拒绝后被触发。

    https://www.myquant.cn/docs/python/python_trade_event#on_execution_report%20-%20%E5%A7%94%E6%89%98%E6%89%A7%E8%A1%8C%E5%9B%9E%E6%8A%A5%E4%BA%8B%E4%BB%B6
    https://www.myquant.cn/docs/python/python_object_trade#ExecRpt%20-%20%E5%9B%9E%E6%8A%A5%E5%AF%B9%E8%B1%A1

    :param context:
    :param execrpt:
    :return:
    """
    if not is_trade_time(context.now):
        return

    latest_dt = context.now.strftime(dt_fmt)
    logger = context.logger
    msg = f"委托订单被执行通知：\n{'*' * 31}\n" \
          f"时间：{latest_dt}\n" \
          f"标的：{execrpt.symbol}\n" \
          f"名称：{context.stocks.get(execrpt.symbol, '无名')}\n" \
          f"方向：{order_side_map[execrpt.side]}{pos_effect_map[execrpt.position_effect]}\n" \
          f"成交量：{int(execrpt.volume)}\n" \
          f"成交价：{round(execrpt.price, 2)}\n" \
          f"执行回报类型：{exec_type_map[execrpt.exec_type]}"

    logger.info(msg.replace("\n", " - ").replace('*', ""))
    if context.mode != MODE_BACKTEST and execrpt.exec_type in [1, 5, 6, 8, 12, 19]:
        wx.push_text(content=str(msg), key=context.wx_key)


def on_backtest_finished(context, indicator):
    """回测结束回调函数

    :param context:
    :param indicator:
        https://www.myquant.cn/docs/python/python_object_trade#bd7f5adf22081af5
    :return:
    """
    wx_key = context.wx_key
    symbols = context.symbols
    data_path = context.data_path
    logger = context.logger

    logger.info(str(indicator))
    logger.info("回测结束 ... ")
    cash = context.account().cash

    for k, v in indicator.items():
        if isinstance(v, float):
            indicator[k] = round(v, 4)

    row = OrderedDict({
        "研究标的": ", ".join(list(context.symbols_info.keys())),
        "回测开始时间": context.backtest_start_time,
        "回测结束时间": context.backtest_end_time,
        "累计收益率": indicator['pnl_ratio'],
        "最大回撤": indicator['max_drawdown'],
        "年化收益率": indicator['pnl_ratio_annual'],
        "夏普比率": indicator['sharp_ratio'],
        "盈利次数": indicator['win_count'],
        "亏损次数": indicator['lose_count'],
        "交易胜率": indicator['win_ratio'],
        "累计出入金": int(cash['cum_inout']),
        "累计交易额": int(cash['cum_trade']),
        "累计手续费": int(cash['cum_commission']),
        "累计平仓收益": int(cash['cum_pnl']),
        "净收益": int(cash['pnl']),
    })
    sdt = pd.to_datetime(context.backtest_start_time).strftime('%Y%m%d')
    edt = pd.to_datetime(context.backtest_end_time).strftime('%Y%m%d')
    file_xlsx = os.path.join(data_path, f'{context.name}_{sdt}_{edt}.xlsx')
    file = pd.ExcelWriter(file_xlsx, mode='w')

    dfe = pd.DataFrame({"指标": list(row.keys()), "值": list(row.values())})
    dfe.to_excel(file, sheet_name='回测表现', index=False)

    logger.info("回测结果：{}".format(row))
    content = ""
    for k, v in row.items():
        content += "{}: {}\n".format(k, v)
    wx.push_text(content=content, key=wx_key)

    trades = []
    operates = []
    performances = []
    for symbol in symbols:
        trader: GmCzscTrader = context.symbols_info[symbol]['trader']
        trades.extend(trader.long_pos.pairs)
        operates.extend(trader.long_pos.operates)
        performances.append(trader.long_pos.evaluate_operates())

    df = pd.DataFrame(trades)
    df['开仓时间'] = df['开仓时间'].apply(lambda x: x.strftime("%Y-%m-%d %H:%M"))
    df['平仓时间'] = df['平仓时间'].apply(lambda x: x.strftime("%Y-%m-%d %H:%M"))
    df.to_excel(file, sheet_name='交易汇总', index=False)

    dfo = pd.DataFrame(operates)
    dfo['dt'] = dfo['dt'].apply(lambda x: x.strftime("%Y-%m-%d %H:%M"))
    dfo.to_excel(file, sheet_name='操作汇总', index=False)

    dfp = pd.DataFrame(performances)
    dfp.to_excel(file, sheet_name='表现汇总', index=False)
    file.close()

    wx.push_file(file_xlsx, wx_key)


def on_error(context, code, info):
    if not is_trade_time(context.now):
        return

    logger = context.logger
    msg = "{} - {}".format(code, info)
    logger.warn(msg)
    if context.mode != MODE_BACKTEST:
        wx.push_text(content=msg, key=context.wx_key)


def on_account_status(context, account):
    """响应交易账户状态更新事件，交易账户状态变化时被触发
    https://www.myquant.cn/docs/python/python_trade_event#4f07d24fc4314e3c
    """
    status = account['status']
    if status['state'] == 3:
        return

    if not is_trade_time(context.now):
        return

    logger = context.logger
    msg = f"{str(account)}"
    logger.warn(msg)
    if context.mode != MODE_BACKTEST:
        wx.push_text(content=msg, key=context.wx_key)


def on_bar(context, bars):
    """订阅K线回调函数"""
    context.unfinished_orders = get_unfinished_orders()
    cancel_timeout_orders(context, max_m=30)

    for bar in bars:
        symbol = bar['symbol']
        trader: GmCzscTrader = context.symbols_info[symbol]['trader']

        # 确保数据更新到最新时刻
        base_freq = trader.base_freq
        bars = context.data(symbol=symbol, frequency=freq_cn2gm[base_freq], count=100,
                            fields='symbol,eob,open,close,high,low,volume,amount')
        bars = format_kline(bars, freq=trader.bg.freq_map[base_freq])
        bars_new = [x for x in bars if x.dt > trader.bg.bars[base_freq][-1].dt]
        if bars_new:
            for bar_ in bars_new:
                trader.update(bar_)

        trader.sync_long_position(context)

        if context.mode != MODE_BACKTEST and context.now.strftime("%H:%M") == '14:00':
            file_trader = os.path.join(context.data_path, f'traders/{symbol}.cat')
            dill.dump(trader, open(file_trader, 'wb'))


def is_order_exist(context, symbol, side) -> bool:
    """判断同方向订单是否已经存在

    :param context:
    :param symbol: 交易标的
    :param side: 交易方向
    :return: bool
    """
    uo = context.unfinished_orders
    if not uo:
        return False
    else:
        for o in uo:
            if o.symbol == symbol and o.side == side:
                context.logger.info("同类型订单已存在：{} - {}".format(symbol, side))
                return True
    return False


def cancel_timeout_orders(context, max_m=30):
    """实盘仿真，撤销挂单时间超过 max_m 分钟的订单。

    :param context:
    :param max_m: 最大允许挂单分钟数
    :return:
    """
    for u_order in context.unfinished_orders:
        if context.now - u_order.created_at >= timedelta(minutes=max_m):
            order_cancel(u_order)


def report_account_status(context):
    """报告账户持仓状态"""
    if context.now.isoweekday() > 5:
        return

    logger = context.logger
    latest_dt = context.now.strftime(dt_fmt)
    account = context.account(account_id=context.account_id)
    cash = account.cash
    positions = account.positions()

    logger.info("=" * 30 + f" 账户状态【{latest_dt}】 " + "=" * 30)
    cash_report = f"净值：{int(cash.nav)}，可用资金：{int(cash.available)}，" \
                  f"浮动盈亏：{int(cash.fpnl)}，标的数量：{len(positions)}"
    logger.info(cash_report)

    for p in positions:
        p_report = f"标的：{p.symbol}，名称：{context.stocks.get(p.symbol, '无名')}，" \
                   f"数量：{p.volume}，成本：{round(p.vwap, 2)}，方向：{p.side}，" \
                   f"当前价：{round(p.price, 2)}，成本市值：{int(p.volume * p.vwap)}，" \
                   f"建仓时间：{p.created_at.strftime(dt_fmt)}"
        logger.info(p_report)

    # 实盘或仿真，推送账户信息到企业微信
    if context.mode != MODE_BACKTEST:

        msg = f"股票账户状态报告\n{'*' * 31}\n"
        msg += f"账户净值：{int(cash.nav)}\n" \
               f"持仓市值：{int(cash.market_value)}\n" \
               f"可用资金：{int(cash.available)}\n" \
               f"浮动盈亏：{int(cash.fpnl)}\n" \
               f"标的数量：{len(positions)}\n" \
               f"{'*' * 31}\n"

        for p in positions:
            try:
                msg += f'标的代码：{p.symbol}\n' \
                       f"标的名称：{context.stocks.get(p.symbol, '无名')}\n" \
                       f'持仓数量：{p.volume}\n' \
                       f'最新价格：{round(p.price, 2)}\n' \
                       f'持仓成本：{round(p.vwap, 2)}\n' \
                       f'盈亏比例：{int((p.price - p.vwap) / p.vwap * 10000) / 100}%\n' \
                       f'持仓市值：{int(p.volume * p.vwap)}\n' \
                       f'持仓天数：{(context.now - p.created_at).days}\n' \
                       f"{'*' * 31}\n"
            except:
                print(p)

        wx.push_text(msg.strip("\n *"), key=context.wx_key)


class GmCzscTrader(CzscAdvancedTrader):
    def __init__(self,
                 bg: BarGenerator,
                 get_signals: Callable,
                 long_events: List[Event] = None,
                 long_pos: PositionLong = None,
                 short_events: List[Event] = None,
                 short_pos: PositionShort = None,
                 max_bi_count: int = 50,
                 bi_min_len: int = 7,
                 signals_n: int = 0,
                 verbose: bool = False,
                 ):
        super().__init__(
            bg=bg,
            get_signals=get_signals,
            long_events=long_events,
            long_pos=long_pos,
            short_events=short_events,
            short_pos=short_pos,
            max_bi_count=max_bi_count,
            bi_min_len=bi_min_len,
            signals_n=signals_n,
            verbose=verbose,
        )

    def sync_long_position(self, context):
        """同步多头仓位到交易账户"""
        if not self.long_events:
            return

        symbol = self.symbol
        name = context.stocks.get(symbol, "无名标的")
        long_pos = self.long_pos
        max_sym_pos = context.symbols_info[symbol]['max_sym_pos']  # 最大标的仓位
        logger = context.logger
        if context.mode == MODE_BACKTEST:
            account = context.account()
        else:
            account = context.account(account_id=context.account_id)
        cash = account.cash

        price = self.latest_price
        print(f"{self.end_dt}: {name}，多头：{long_pos.pos}，成本：{long_pos.long_cost}，"
              f"现价：{price}，操作次数：{len(long_pos.operates)}")

        algo_name = os.environ.get('algo_name', None)
        if algo_name:
            # 算法名称，TWAP、VWAP、ATS-SMART、ZC-POV
            algo_name = algo_name.upper()
            start_time = self.end_dt.strftime("%H:%M:%S")
            end_time = (self.end_dt + timedelta(minutes=30)).strftime("%H:%M:%S")
            end_time = min(end_time, '14:55:00')

            if algo_name == 'TWAP' or algo_name == 'VWAP' or algo_name == 'ZC-POV':
                algo_param = {
                    "start_time": start_time,
                    "end_time": end_time,
                    "part_rate": 0.5,
                    "min_amount": 5000,
                }
            elif algo_name == 'ATS-SMART':
                algo_param = {
                    'start_time': start_time,
                    'end_time_referred': end_time,
                    'end_time': end_time,
                    'end_time_valid': 1,
                    'stop_sell_when_dl': 1,
                    'cancel_when_pl': 0,
                    'min_trade_amount': 5000
                }
            else:
                raise ValueError("算法单名称输入错误")
        else:
            algo_param = {}

        sym_position = account.position(symbol, PositionSide_Long)
        if long_pos.pos == 0 and sym_position and sym_position.volume > 0:
            volume = sym_position.volume
            if algo_name:
                assert len(algo_param) > 0, f"error: {algo_name}, {algo_param}"
                _ = algo_order(symbol=symbol, volume=volume, side=OrderSide_Sell,
                               order_type=OrderType_Limit, position_effect=PositionEffect_Close,
                               price=price, algo_name=algo_name, algo_param=algo_param, account=account.id)
            else:
                order_target_volume(symbol=symbol, volume=0, position_side=PositionSide_Long,
                                    order_type=OrderType_Limit, price=price, account=account.id)
            return

        if not long_pos.pos_changed:
            return

        cash_left = cash.available
        if long_pos.operates[-1]['op'] in [Operate.LO, Operate.LA1, Operate.LA2]:
            change_amount = max_sym_pos * long_pos.operates[-1]['pos_change'] * cash.nav
            if cash_left < change_amount:
                logger.info(f"{context.now} {symbol} {name} 可用资金不足，无法开多仓；"
                            f"剩余资金{int(cash_left)}元，所需资金{int(change_amount)}元")
                return

        if is_order_exist(context, symbol, PositionSide_Long):
            logger.info(f"{context.now} {symbol} {name} 同方向订单已存在")
            return

        percent = max_sym_pos * long_pos.pos
        volume = int((cash.nav * percent / price // 100) * 100)
        if algo_name:
            _ = algo_order(symbol=symbol, volume=volume, side=OrderSide_Buy,
                           order_type=OrderType_Limit, position_effect=PositionEffect_Open,
                           price=price, algo_name=algo_name, algo_param=algo_param, account=account.id)
        else:
            order_target_volume(symbol=symbol, volume=volume, position_side=PositionSide_Long,
                                order_type=OrderType_Limit, price=price, account=account.id)

    def sync_short_position(self, context):
        """同步空头仓位到交易账户"""
        if not self.short_events:
            return

        symbol = self.symbol
        name = context.stocks.get(symbol, "无名标的")
        short_pos: PositionShort = self.short_pos
        max_sym_pos = context.symbols_info[symbol]['max_sym_pos']  # 最大标的仓位
        logger = context.logger
        if context.mode == MODE_BACKTEST:
            account = context.account()
        else:
            account = context.account(account_id=context.account_id)
        cash = account.cash

        price = self.latest_price
        print(f"{self.end_dt}: {name}，空头：{short_pos.pos}，成本：{short_pos.short_cost}，"
              f"现价：{price}，操作次数：{len(short_pos.operates)}")

        sym_position = account.position(symbol, PositionSide_Short)
        if short_pos.pos == 0 and sym_position and sym_position.volume > 0:
            order_target_percent(symbol=symbol, percent=0, position_side=PositionSide_Short,
                                 order_type=OrderType_Limit, price=price, account=account.id)
            return

        if not short_pos.pos_changed:
            return

        cash_left = cash.available
        if short_pos.operates[-1]['op'] in [Operate.SO, Operate.SA1, Operate.SA2]:
            change_amount = max_sym_pos * short_pos.operates[-1]['pos_change'] * cash.nav
            if cash_left < change_amount:
                logger.info(f"{context.now} {symbol} {name} 可用资金不足，无法开空仓；"
                            f"剩余资金{int(cash_left)}元，所需资金{int(change_amount)}元")
                return

        if is_order_exist(context, symbol, PositionSide_Long):
            logger.info(f"{context.now} {symbol} {name} 同方向订单已存在")
            return

        percent = max_sym_pos * short_pos.pos
        order_target_percent(symbol=symbol, percent=percent, position_side=PositionSide_Short,
                             order_type=OrderType_Limit, price=price, account=account.id)


def gm_take_snapshot(gm_symbol, end_dt=None, file_html=None,
                     get_signals: Callable = get_default_signals,
                     adjust=ADJUST_PREV, max_count=1000):
    """使用掘金的数据对任意标的、任意时刻的状态进行快照

    :param gm_symbol:
    :param end_dt:
    :param file_html:
    :param get_signals:
    :param adjust:
    :param max_count:
    :return:
    """
    if not end_dt:
        end_dt = datetime.now().strftime(dt_fmt)

    bg, data = get_init_bg(gm_symbol, end_dt, base_freq='1分钟',
                           freqs=['5分钟', '15分钟', '30分钟', '60分钟', '日线', '周线', '月线'],
                           max_count=max_count, adjust=adjust)
    ct = GmCzscTrader(bg, get_signals=get_signals)
    for bar in data:
        ct.update(bar)

    if file_html:
        ct.take_snapshot(file_html)
        print(f'saved into {file_html}')
    else:
        ct.open_in_browser()
    return ct


def check_index_status(qywx_key):
    """查看主要指数状态"""
    from czsc.utils.cache import home_path

    wx.push_text(f"{datetime.now()} 开始获取主要指数行情快照", qywx_key)
    for gm_symbol in indices.values():
        try:
            file_html = os.path.join(home_path, f"{gm_symbol}_{datetime.now().strftime('%Y%m%d')}.html")
            gm_take_snapshot(gm_symbol, file_html=file_html)
            wx.push_file(file_html, qywx_key)
            os.remove(file_html)
        except:
            traceback.print_exc()
    wx.push_text(f"{datetime.now()} 获取主要指数行情快照获取结束，请仔细观察！！！", qywx_key)


def realtime_check_index_status(context):
    """实盘：发送主要指数行情图表"""
    if context.now.isoweekday() > 5:
        print(f"realtime_check_index_status: {context.now} 不是交易时间")
        return

    check_index_status(context.wx_key)


def process_out_of_symbols(context):
    """实盘：处理不在交易列表的持仓股"""
    if context.now.isoweekday() > 5:
        print(f"process_out_of_symbols: {context.now} 不是交易时间")
        return

    account = context.account(account_id=context.account_id)
    positions = account.positions(symbol="", side=PositionSide_Long)

    for p in positions:
        symbol = p.symbol
        if p.volume > 0 and p.symbol not in context.symbols_info.keys():
            order_target_percent(symbol=symbol, percent=0, position_side=PositionSide_Long,
                                 order_type=OrderType_Market, account=account.id)


def init_context_universal(context, name):
    """通用 context 初始化：1、创建文件目录和日志记录

    :param context:
    :param name: 交易策略名称，建议使用英文
    """
    path_gm_logs = os.environ.get('path_gm_logs', None)
    assert os.path.exists(path_gm_logs)
    if context.mode == MODE_BACKTEST:
        data_path = os.path.join(path_gm_logs, f"backtest/{name}_{datetime.now().strftime('%Y%m%d_%H%M%S')}")
    else:
        data_path = os.path.join(path_gm_logs, f"realtime/{name}")
    os.makedirs(data_path, exist_ok=True)
    context.name = name
    context.data_path = data_path
    context.stocks = get_stocks()
    context.logger = create_logger(os.path.join(data_path, "gm_trader.log"), cmd=True, name="gm")

    context.logger.info("运行配置：")
    context.logger.info(f"data_path = {data_path}")

    if context.mode == MODE_BACKTEST:
        context.logger.info("backtest_start_time = " + str(context.backtest_start_time))
        context.logger.info("backtest_end_time = " + str(context.backtest_end_time))


def init_context_env(context):
    """通用 context 初始化：2、读入环境变量

    :param context:
    """
    context.wx_key = os.environ['wx_key']
    context.account_id = os.environ.get('account_id', '')
    if context.mode != MODE_BACKTEST:
        assert len(context.account_id) > 10, "非回测模式，必须设置 account_id "

    # 单个标的仓位控制[0, 1]，按资金百分比控制，1表示满仓，仅在开仓的时候控制
    context.max_sym_pos = float(os.environ['max_sym_pos'])
    assert 0 <= context.max_sym_pos <= 1

    logger = context.logger
    logger.info(f"环境变量读取结果如下：")
    logger.info(f"单标的控制：context.max_sym_pos = {context.max_sym_pos}")


def init_context_traders(context, symbols: List[str], strategy: Callable):
    """通用 context 初始化：3、为每个标的创建 GmCzscTrader 对象

    :param context:
    :param symbols:
    :param strategy:
    :return:
    """
    with open(os.path.join(context.data_path, f'{strategy.__name__}.txt'), mode='w') as f:
        f.write(inspect.getsource(strategy))

    tactic = strategy()

    base_freq = tactic['base_freq']
    freqs = tactic['freqs']
    get_signals = tactic['get_signals']

    long_states_pos = tactic.get('long_states_pos', None)
    long_events = tactic.get('long_events', None)
    long_min_interval = tactic.get('long_min_interval', None)

    short_states_pos = tactic.get('short_states_pos', None)
    short_events = tactic.get('short_events', None)
    short_min_interval = tactic.get('short_min_interval', None)

    frequency = freq_cn2gm[base_freq]
    unsubscribe(symbols='*', frequency=frequency)

    data_path = context.data_path
    logger = context.logger
    logger.info(f"输入交易标的数量：{len(symbols)}")
    logger.info(f"交易员的周期列表：base_freq = {base_freq}; freqs = {freqs}")

    if context.mode == MODE_BACKTEST:
        adjust = ADJUST_POST
    else:
        adjust = ADJUST_PREV
    os.makedirs(os.path.join(data_path, 'traders'), exist_ok=True)

    symbols_info = {symbol: dict() for symbol in symbols}
    for symbol in symbols:
        try:
            symbols_info[symbol]['max_sym_pos'] = context.max_sym_pos
            file_trader = os.path.join(data_path, f'traders/{symbol}.cat')

            if os.path.exists(file_trader) and context.mode != MODE_BACKTEST:
                trader: GmCzscTrader = dill.load(open(file_trader, 'rb'))
                logger.info(f"{symbol} Loaded Trader from {file_trader}")

            else:
                if long_states_pos:
                    long_pos = PositionLong(symbol, T0=False,
                                            long_min_interval=long_min_interval,
                                            hold_long_a=long_states_pos['hold_long_a'],
                                            hold_long_b=long_states_pos['hold_long_b'],
                                            hold_long_c=long_states_pos['hold_long_c'])
                else:
                    long_pos = None

                if short_states_pos:
                    short_pos = PositionShort(symbol, T0=False,
                                              short_min_interval=short_min_interval,
                                              hold_short_a=short_states_pos['hold_short_a'],
                                              hold_short_b=short_states_pos['hold_short_b'],
                                              hold_short_c=short_states_pos['hold_short_c'])
                else:
                    short_pos = None

                bg, data = get_init_bg(symbol, context.now, base_freq=base_freq, freqs=freqs, max_count=1000,
                                       adjust=adjust)
                trader = GmCzscTrader(
                    bg=bg, get_signals=get_signals,
                    long_events=long_events, long_pos=long_pos,
                    short_events=short_events, short_pos=short_pos,
                    signals_n=tactic.get('signals_n', 0)
                )
                for bar in data:
                    trader.update(bar)
                dill.dump(trader, open(file_trader, 'wb'))

            symbols_info[symbol]['trader'] = trader
            logger.info("{} Trader 构建成功，最新时间：{}，多仓：{}".format(symbol, trader.end_dt, trader.long_pos.pos))

        except:
            del symbols_info[symbol]
            logger.info(f"{symbol} - {context.stocks[symbol]} 初始化失败，当前时间：{context.now}")
            traceback.print_exc()

    subscribe(",".join(symbols_info.keys()), frequency=frequency, count=300, wait_group=True)
    logger.info(f"订阅成功交易标的数量：{len(symbols_info)}")
    logger.info(f"交易标的配置：{symbols_info}")
    context.symbols_info = symbols_info


def init_context_schedule(context):
    """通用 context 初始化：设置定时任务

    :param context:
    """
    schedule(schedule_func=report_account_status, date_rule='1d', time_rule='09:31:00')
    schedule(schedule_func=report_account_status, date_rule='1d', time_rule='10:01:00')
    schedule(schedule_func=report_account_status, date_rule='1d', time_rule='10:31:00')
    schedule(schedule_func=report_account_status, date_rule='1d', time_rule='11:01:00')
    schedule(schedule_func=report_account_status, date_rule='1d', time_rule='11:31:00')
    schedule(schedule_func=report_account_status, date_rule='1d', time_rule='13:01:00')
    schedule(schedule_func=report_account_status, date_rule='1d', time_rule='13:31:00')
    schedule(schedule_func=report_account_status, date_rule='1d', time_rule='14:01:00')
    schedule(schedule_func=report_account_status, date_rule='1d', time_rule='14:31:00')
    schedule(schedule_func=report_account_status, date_rule='1d', time_rule='15:01:00')

    schedule(schedule_func=process_out_of_symbols, date_rule='1d', time_rule='09:40:00')

    if context.mode != MODE_BACKTEST:
        # 以下是 实盘/仿真 模式下的定时任务
        schedule(schedule_func=realtime_check_index_status, date_rule='1d', time_rule='17:30:00')