InterfaceDocument/counter_demo.py

# -*- coding: utf-8 -*-
# zq

import os
import sys
import time
import json
import threading
import multiprocessing
from pprint import pprint

from datetime import datetime, timedelta

BASE_DIR = os.path.abspath('/tz_crypto')
print(BASE_DIR)
sys.path.append(BASE_DIR)
from tz_ctastrategy import (
    ArrayManager,
    BarData,
    BarGenerator,
    OrderData,
    StopOrder,
    TickData,
    TradeData,
)
from tz_ctastrategy.backtesting_mul import BacktestingEngine
from tz_ctastrategy.base import EngineType, BacktestingMode
from tz_ctastrategy.template import CtaTemplate
from tzquant.market import zmq_client

from tzquant.market.log_model import write_file_by_line, log_on_init
from tzquant.trader.object import *
from tzquant.market.keep_alive import ping
from tz_riskmanager.risk_engine import save_setting
from tzquant.market.market_engine import get_account, private_run
from tzquant.market.dingtalker import dingmessage


class AtrRsiStrategy(CtaTemplate):
    """"""
    parameters = {}

    def __init__(
            self, cta_engine, strategy_name, vt_symbol, setting, rolling_info=None
    ):
        """"""
        super().__init__(cta_engine, strategy_name, vt_symbol, setting, rolling_info)
        if self.cta_engine.engine_type == EngineType.BACKTESTING:
            self.bg = BarGenerator(self.on_bar)
        else:
            self.bg = BarGenerator(self.on_bar, 60, interval=Interval.SECOND)
            self.bg10s = BarGenerator(self.on_bar, 10, self.on_10s_bar, interval=Interval.SECOND)

        self.am = ArrayManager(size=200)

        # 初始化变量
        self.atr_value = 0
        self.rsi_value = 0
        self.ma_value = 0
        self.martingale_level = 0  # 马丁策略层级
        self.max_cash = 0.0
        self.max_down = 0.0
        self.max_pos = 0.0

        if self.cta_engine.engine_type == EngineType.BACKTESTING:
            self.place_order_flag = True
        else:
            self.place_order_flag = False

        # ----------------------- log ----------------------------
        self.log = None
        self.log_time = datetime.now().day - 1
        self.zmq = zmq_client.ZMQClient('XX.XXX.XXX.XX')  # 实例化zmq客户端
        self.log_message_id = 0
        self.s_file_name = f"{self.strategy_name}"
        self.sub_id: str = "0"

        self.last_tradeid = 0

    def on_init(self):
        """
        Callback when strategy is inited.
        """
        self.write_log("策略初始化")

    # 这个是日志输出的函数
    def logger(self):
        d_now = datetime.now()
        # 每天做一次日志名称更改
        if self.log is None or d_now.day != self.log_time:
            self.log = log_on_init(
                log_dir_name="/tzquant_logs",
                log_name=f"{self.strategy_name}-{self.sub_id}_{d_now.year}-{d_now.month:02d}-{d_now.day:02d}.log",
                log_out_name=self.strategy_name,
                write_mode="a",
                line=True,
            )
            self.log_time = d_now.day
        else:
            while self.cta_engine.logs:
                msg = self.cta_engine.logs.pop()
                self.log.info(msg)

                result = {
                    "id": self.log_message_id,
                    "datetime": d_now.strftime('%Y-%m-%d %H:%M:%S.%f')[:-4],
                    "timestamp_ms": int(d_now.timestamp() * 1000),
                    "strategy_id": self.strategy_name,
                    "level": 'info',
                    "log": msg
                }
                self.zmq.send_message(result)
                self.log_message_id += 1

    def on_start(self):
        """
        Callback when strategy is started.
        """
        self.write_log("策略启动")

    def on_stop(self):
        """
        Callback when strategy is stopped.
        """
        self.write_log("策略停止")

    def on_tick(self, tick: TickData):
        """
        Callback of new tick data update.
        """
        if tick.name == 'trade':
            self.bg.tick_to_bar(tick=tick)
            if self.last_tradeid:
                if tick.id - self.last_tradeid != 1:
                    print(f'成交数据有缺失: last:{self.last_tick} now:{tick}')
            self.last_tradeid = tick.id
            self.last_tick = tick

        elif tick.name == 'depth':
            pass

    def on_bar(self, bar: BarData):
        """
        Callback of new bar data update.
        """
        if self.cta_engine.engine_type == EngineType.BACKTESTING:
            self.on_10s_bar(bar)
        else:
            self.bg10s.update_bar(bar)

    def on_10s_bar(self, bar: BarData):
        try:
            self.am.update_bar(bar)
            # print(bar)
            # if time.time() - bar.closetime / 1000 < 30:
            #     # 柜台下买单
            #     res = self.buy(
            #         price=bar.close * (1 - 0.05),
            #         volume=10 / bar.close,
            #         closetime=bar.closetime / 1000,
            #         order_type=OrderType.POC,
            #         label=f't-{self.strategy_name}-{self.sub_id}-0'
            #     )
            #     print('place order', res)
            #     # res1 = self.cancel_all(closetime=bar.closetime / 1000)
            #     # print('cancel all orders', res1)
            #     if res:
            #         # 柜台撤销单个订单
            #         res = self.cancel_order(vt_orderid=res[0],
            #                                 closetime=bar.closetime / 1000)
            #         print('cancel order', res)
            #
            #     self.sell(
            #         price=bar.close * (1 + 0.05),
            #         volume=10 / bar.close,
            #         closetime=bar.closetime / 1000,
            #         order_type=OrderType.POC,
            #         label=f't-{self.strategy_name}-{self.sub_id}-1'
            #     )

            if self.cta_engine.engine_type == EngineType.BACKTESTING:
                # 持仓均价
                self.price = self.cta_engine.ca_balance_now["price"]

            if not self.am.inited:
                # 初始化未完成之前 撤单到成功为止
                if self.cta_engine.active_limit_orders:
                    while True:
                        res = self.cancel_all(closetime=datetime.now().timestamp(), mode=1,
                                              order_id_list=list(self.cta_engine.active_limit_orders.keys()))
                        time.sleep(0.3)
                        if res:
                            break
            #     return
            if self.cta_engine.active_limit_orders:
                print('active_limit_orders: ', self.cta_engine.active_limit_orders)
            #     # 柜台撤所有订单 mode 要为 1 order_id_list 要传入当前所有的挂单id
            #     while True:
            #         res = self.cancel_all(closetime=bar.closetime / 1000,
            #                               mode=1,
            #                               order_id_list=list(self.cta_engine.active_limit_orders.keys()))
            #         if res:
            #             print('cancel success')
            #             # for index, order_id in enumerate(self.cta_engine.active_limit_orders):
            #             #     print(order_id, type(order_id))
            #             #     time_diff = time.time() - self.cta_engine.active_limit_orders[order_id].datetime.timestamp()
            #             #     if time_diff > 30:
            #             #         msg = f'-----------挂单更新超时-----------:{time_diff}'
            #             #         dingmessage(webhook_key='',
            #             #                     secret_name=f'{self.strategy_name}-{self.sub_id}',
            #             #                     sub_id=self.sub_id,
            #             #                     symbol=self.cta_engine.symbol,
            #             #                     msg=msg,
            #             #                     async_req=True
            #             #                     )
            #             #         print(self.cta_engine.active_limit_orders[order_id].datetime.timestamp())
            #             break
            #         time.sleep(0.5)
            #         print('cancel failed')

        except (Exception, BaseException) as e:
            self.cta_engine.output(
                "on_10s_bar error:%s-----line:%s" % (repr(e), e.__traceback__.tb_lineno)
            )

    def on_order(self, order: OrderData):
        """
        Callback of new order data update.
        """
        pass

    def on_trade(self, trade: TradeData):
        """
        Callback of new trade data update.
        """

        self.cta_engine.output(f'成交记录:{trade}---持有仓位:{self.pos}')
        # self.put_event()

    def on_stop_order(self, stop_order: StopOrder):
        """
        Callback of stop order update.
        """
        pass


def run_single(
        platform: str, symbol: str, capital: int, config: dict, risk_setting: dict, queue
):
    engine = BacktestingEngine()

    now_datetime = datetime.now().replace(second=0, microsecond=0)
    # ---------------- 实盘 -----------------------
    engine.engine_type = EngineType.REAL
    engine.gateway_name = EngineType.REAL

    start = now_datetime - timedelta(days=40 / 1440)
    # start = now_datetime - timedelta(days=1800 / 1440)

    engine.set_parameters(
        vt_symbol=f"{symbol}.{platform}",  # 下单平台
        source_exchanges=[platform],  # 接收多源平台list
        start=start,  # 形如：datetime(2022,1,1)
        end=now_datetime,  # 形如：datetime(2022,1,1)
        maker_fee=-0.5 / 10000,  # 挂单手续费
        taker_fee=3 / 10000,  # 吃单手续费
        slippage=2 / 10000,  # 滑点
        size=1,  # 杠杆倍数 默认为1
        pricetick=0.1,  # 价格精度
        capital=capital,  # 本金
        annual_days=365,  # 一年的连续交易天数
        interval=Interval.SECOND,
        mode=BacktestingMode.TICK  # tick级别实盘
    )
    # 将策略添加进引擎
    engine.add_strategy(AtrRsiStrategy, {})

    # --------------- 加载json 文件的配置信息 ---------------
    action_config = config[symbol]
    engine.strategy.place_order_flag = action_config["place_order"]
    engine.strategy.strategy_name = risk_setting["secret_name"]
    engine.strategy.parameters = action_config
    engine.strategy.sub_id = risk_setting["sub_id"]

    # engine.strategy.on_init()

    # 实盘私有信息通过这个队列传输
    engine.queue_pri = queue
    print("engine.queue_pri:", engine.queue_pri)
    # 启动风控 实盘不管大资金还是小资金都要启动风控
    engine.strategy.add_risk_manager(
        symbol_list=[symbol_ for symbol_ in config],
        key=risk_setting["key"],
        secret=risk_setting["secret"],
        sub_id=risk_setting["sub_id"]
    )
    # engine.dma_depth_data(platform, int(start.timestamp()))
    threading.Thread(target=engine.dma_depth_data, args=(platform, int(start.timestamp()))).start()
    engine.receive_private_queue_data()  # 接收实盘私有信息


def run():
    # 当前跑的平台
    # platform = "gate_swap_u"
    # secret_name = "403"  # 500_mm_ziying 200
    # symbol = "bnbusdt"  # btcusdt
    # sub_id = "0"  # 子账户id str
    # settle = 'usdt'

    platform = "binance_swap_u_uni"
    secret_name = "801"  # 500_mm_ziying 200
    symbol = "dogeusdt"  # btcusdt
    sub_id = "0"  # 子账户id str
    settle = 'usdt'

    # secret_name = sys.argv[1]  # 500_mm_ziying 200
    # symbol = sys.argv[2]  # btcusdt
    # platform = sys.argv[3]  # binance_spot_uni
    # sub_id = sys.argv[4]  # 子账户id str
    # settle = 'usdt' if 'usdt' in symbol else 'fdusd'
    print(secret_name, symbol, settle)

    # 从配置文件中批量读取参数
    file_name = "data.json"

    with open(file_name, "rb") as json_file:
        json_data = json.loads(json_file.read())

    pprint(json_data[secret_name][sub_id][symbol])

    # 当前测试账户虚拟本金1000U place_rate_open 开仓让位 place_rate_close 平仓让位
    config = {
        symbol: json_data[secret_name][sub_id][symbol]
    }

    # ------------------ 修改风控的配置信息 密钥 ---------------------------
    risk_setting = {
        # 这个是交易所的 key
        "key": json_data[secret_name]["key"],
        "secret_name": secret_name,
        "sub_id": sub_id,
        # 这个是交易所的 secret
        "secret": json_data[secret_name]["secret"],
        # 这个是天择网站上申请的虚拟子账户的 key
        "sub_key": json_data[secret_name][sub_id]["key"],
        # 这个是天择网站上申请的虚拟子账户的 secret
        "sub_secret": json_data[secret_name][sub_id]["secret"],
        "active": True,  # True 风控启动
        "order_flow_limit_1m": 15,  # 根据下单的标签来做1m的下单次数限制
        "net_max_down_level_1": 20,  # 实时最大回撤值百分比 超过会提醒
        "net_max_down_level_2": 15,
        "net_max_down_level_3": 10,
        # 单币种的持仓限制
        "position_limit": {symbol_: config[symbol_]["capital"] * config[symbol_]["max_pos_rate"] * 1.04
                           for symbol_ in config},
        "position_time_out": 45,  # 持仓信息超过45秒没来会提醒
        "webhook_key": ['', '']   # 钉钉发送的接收用户
    }

    # 这个是实际的本金
    get_account_ = get_account(risk_setting=risk_setting, platform=platform, settle=settle)
    balance = get_account_.balance + get_account_.unrealised_pnl

    print(get_account_.__dict__, balance)

    # 更新净值风控
    risk_setting["net_level_1"] = (
            balance * (100 - risk_setting["net_max_down_level_1"]) / 100
    )
    risk_setting["net_level_2"] = (
            balance * (100 - risk_setting["net_max_down_level_2"]) / 100
    )
    risk_setting["net_level_3"] = (
            balance * (100 - risk_setting["net_max_down_level_3"]) / 100
    )

    total_capital = sum([config[symbol_]["capital"] for symbol_ in config])
    print("当前实际杠杆倍数：", total_capital / balance)
    print(config)
    print(risk_setting)

    directory_name = "json_hub"

    # 获取当前工作目录
    current_directory = os.getcwd()

    # 构造 json_hub 目录的路径
    json_hub_path = os.path.join(current_directory, directory_name)

    # 检查目录是否存在
    if not os.path.exists(json_hub_path):
        # 如果不存在，则创建目录
        os.makedirs(json_hub_path)
        print(f"Directory '{directory_name}' created.")
    else:
        print(f"Directory '{directory_name}' already exists.")

    save_setting(setting=config, setting_filename=f'/json_hub/{secret_name}_config.json')
    save_setting(setting=risk_setting)  # 将risk_setting 的信息写入配置文件

    process = []
    # 创建一个进程间内存共享的队列
    queue_dict = {}
    for index, key in enumerate(config):
        q = multiprocessing.Queue()
        queue_dict[key] = q
    # 限制该币种杠杆倍数 默认3倍
    leverage_limit = 3
    # 这个是调试用的 不调试要注释掉
    # private_run(queue_dict, config, risk_setting, platform, settle, leverage_limit)
    # 先启动私有信息的发送进程 确保初始化有数据
    p = multiprocessing.Process(
        target=private_run,
        args=(queue_dict, config, risk_setting, platform, settle, leverage_limit)
    )
    p.start()
    time.sleep(3)

    # 然后为每个品种启动一个进程来做接收
    for index, key in enumerate(config):
        p1 = multiprocessing.Process(
            target=run_single,
            args=(
                platform,
                key,
                config[key]["capital"],
                config,
                risk_setting,
                queue_dict[key],
            ),
        )
        p1.start()
        process.append(p1)
        time.sleep(60)
    process.append(p)
    for p2 in process:
        p2.join()


if __name__ == "__main__":
    run()