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432 lines
16 KiB
432 lines
16 KiB
# -*- coding: utf-8 -*-
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# zq
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import os
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import sys
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import time
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import json
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import threading
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import multiprocessing
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from pprint import pprint
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from datetime import datetime, timedelta
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BASE_DIR = os.path.abspath('/tz_crypto')
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print(BASE_DIR)
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sys.path.append(BASE_DIR)
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from tz_ctastrategy import (
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ArrayManager,
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BarData,
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BarGenerator,
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OrderData,
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StopOrder,
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TickData,
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TradeData,
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)
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from tz_ctastrategy.backtesting_mul import BacktestingEngine
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from tz_ctastrategy.base import EngineType, BacktestingMode
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from tz_ctastrategy.template import CtaTemplate
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from tzquant.market import zmq_client
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from tzquant.market.log_model import write_file_by_line, log_on_init
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from tzquant.trader.object import *
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from tzquant.market.keep_alive import ping
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from tz_riskmanager.risk_engine import save_setting
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from tzquant.market.market_engine import get_account, private_run
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from tzquant.market.dingtalker import dingmessage
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class AtrRsiStrategy(CtaTemplate):
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""""""
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parameters = {}
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def __init__(
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self, cta_engine, strategy_name, vt_symbol, setting, rolling_info=None
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):
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""""""
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super().__init__(cta_engine, strategy_name, vt_symbol, setting, rolling_info)
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if self.cta_engine.engine_type == EngineType.BACKTESTING:
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self.bg = BarGenerator(self.on_bar)
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else:
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self.bg = BarGenerator(self.on_bar, 60, interval=Interval.SECOND)
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self.bg10s = BarGenerator(self.on_bar, 10, self.on_10s_bar, interval=Interval.SECOND)
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self.am = ArrayManager(size=2000)
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# 初始化变量
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self.atr_value = 0
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self.rsi_value = 0
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self.ma_value = 0
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self.martingale_level = 0 # 马丁策略层级
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self.max_cash = 0.0
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self.max_down = 0.0
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self.max_pos = 0.0
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if self.cta_engine.engine_type == EngineType.BACKTESTING:
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self.place_order_flag = True
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else:
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self.place_order_flag = False
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# ----------------------- log ----------------------------
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self.log = None
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self.log_time = datetime.now().day - 1
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self.zmq = zmq_client.ZMQClient('XX.XXX.XXX.XX') # 实例化zmq客户端
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self.log_message_id = 0
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self.s_file_name = f"{self.strategy_name}"
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self.sub_id: str = "0"
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self.last_tradeid = 0
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def on_init(self):
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"""
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Callback when strategy is inited.
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"""
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self.write_log("策略初始化")
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# 这个是日志输出的函数
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def logger(self):
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d_now = datetime.now()
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# 每天做一次日志名称更改
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if self.log is None or d_now.day != self.log_time:
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self.log = log_on_init(
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log_dir_name="/tzquant_logs",
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log_name=f"{self.strategy_name}-{self.sub_id}_{d_now.year}-{d_now.month:02d}-{d_now.day:02d}.log",
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log_out_name=self.strategy_name,
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write_mode="a",
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line=True,
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)
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self.log_time = d_now.day
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else:
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while self.cta_engine.logs:
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msg = self.cta_engine.logs.pop()
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self.log.info(msg)
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result = {
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"id": self.log_message_id,
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"datetime": d_now.strftime('%Y-%m-%d %H:%M:%S.%f')[:-4],
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"timestamp_ms": int(d_now.timestamp() * 1000),
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"strategy_id": self.strategy_name,
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"level": 'info',
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"log": msg
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}
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self.zmq.send_message(result)
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self.log_message_id += 1
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def on_start(self):
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"""
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Callback when strategy is started.
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"""
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self.write_log("策略启动")
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def on_stop(self):
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"""
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Callback when strategy is stopped.
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"""
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self.write_log("策略停止")
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def on_tick(self, tick: TickData):
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"""
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Callback of new tick data update.
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"""
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if tick.name == 'trade':
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self.bg.tick_to_bar(tick=tick)
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if self.last_tradeid:
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if tick.id - self.last_tradeid != 1:
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print(f'成交数据有缺失: last:{self.last_tick} now:{tick}')
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self.last_tradeid = tick.id
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self.last_tick = tick
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elif tick.name == 'depth':
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pass
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def on_bar(self, bar: BarData):
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"""
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Callback of new bar data update.
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"""
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if self.cta_engine.engine_type == EngineType.BACKTESTING:
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self.on_10s_bar(bar)
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else:
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self.bg10s.update_bar(bar)
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def on_10s_bar(self, bar: BarData):
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try:
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self.am.update_bar(bar)
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# print(bar)
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if time.time() - bar.closetime / 1000 < 30:
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# 柜台下买单
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res = self.buy(
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price=bar.close * (1 - 0.05),
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volume=10 / bar.close,
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closetime=bar.closetime / 1000,
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order_type=OrderType.POC,
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label=f't-{self.strategy_name}-{self.sub_id}-0'
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)
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print('place order', res)
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# res1 = self.cancel_all(closetime=bar.closetime / 1000)
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# print('cancel all orders', res1)
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if res:
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# 柜台撤销单个订单
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res = self.cancel_order(vt_orderid=res[0],
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closetime=bar.closetime / 1000)
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print('cancel order', res)
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self.sell(
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price=bar.close * (1 + 0.05),
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volume=10 / bar.close,
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closetime=bar.closetime / 1000,
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order_type=OrderType.POC,
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label=f't-{self.strategy_name}-{self.sub_id}-1'
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)
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if self.cta_engine.engine_type == EngineType.BACKTESTING:
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# 持仓均价
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self.price = self.cta_engine.ca_balance_now["price"]
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if not self.am.inited:
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# 初始化未完成之前 撤单到成功为止
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if self.cta_engine.active_limit_orders:
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while True:
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res = self.cancel_all(closetime=datetime.now().timestamp(), mode=1,
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order_id_list=list(self.cta_engine.active_limit_orders.keys()))
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time.sleep(0.3)
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if res:
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break
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return
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if self.cta_engine.active_limit_orders:
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# 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
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while True:
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res = self.cancel_all(closetime=bar.closetime / 1000,
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mode=1,
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order_id_list=list(self.cta_engine.active_limit_orders.keys()))
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if res:
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print('cancel success')
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# for index, order_id in enumerate(self.cta_engine.active_limit_orders):
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# print(order_id, type(order_id))
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# time_diff = time.time() - self.cta_engine.active_limit_orders[order_id].datetime.timestamp()
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# if time_diff > 30:
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# msg = f'-----------挂单更新超时-----------:{time_diff}'
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# dingmessage(webhook_key='',
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# secret_name=f'{self.strategy_name}-{self.sub_id}',
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# sub_id=self.sub_id,
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# symbol=self.cta_engine.symbol,
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# msg=msg,
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# async_req=True
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# )
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# print(self.cta_engine.active_limit_orders[order_id].datetime.timestamp())
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break
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time.sleep(0.5)
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print('cancel failed')
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except (Exception, BaseException) as e:
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self.cta_engine.output(
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"on_10s_bar error:%s-----line:%s" % (repr(e), e.__traceback__.tb_lineno)
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)
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def on_order(self, order: OrderData):
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"""
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Callback of new order data update.
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"""
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pass
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def on_trade(self, trade: TradeData):
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"""
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Callback of new trade data update.
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"""
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# self.cta_engine.output(f'成交记录:{trade}---持有仓位:{self.pos}')
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# self.put_event()
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def on_stop_order(self, stop_order: StopOrder):
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"""
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Callback of stop order update.
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"""
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pass
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def run_single(
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platform: str, symbol: str, capital: int, config: dict, risk_setting: dict, queue
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):
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engine = BacktestingEngine()
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now_datetime = datetime.now().replace(second=0, microsecond=0)
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# ---------------- 实盘 -----------------------
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engine.engine_type = EngineType.REAL
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engine.gateway_name = EngineType.REAL
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start = now_datetime - timedelta(days=334 / 1440)
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# start = now_datetime - timedelta(days=1800 / 1440)
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engine.set_parameters(
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vt_symbol=f"{symbol}.{platform}", # 下单平台
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source_exchanges=[platform], # 接收多源平台list
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start=start, # 形如：datetime(2022,1,1)
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end=now_datetime, # 形如：datetime(2022,1,1)
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maker_fee=-0.5 / 10000, # 挂单手续费
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taker_fee=3 / 10000, # 吃单手续费
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slippage=2 / 10000, # 滑点
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size=1, # 杠杆倍数 默认为1
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pricetick=0.1, # 价格精度
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capital=capital, # 本金
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annual_days=365, # 一年的连续交易天数
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interval=Interval.SECOND,
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mode=BacktestingMode.TICK # tick级别实盘
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)
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# 将策略添加进引擎
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engine.add_strategy(AtrRsiStrategy, {})
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# --------------- 加载json 文件的配置信息 ---------------
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action_config = config[symbol]
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engine.strategy.place_order_flag = action_config["place_order"]
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engine.strategy.strategy_name = risk_setting["secret_name"]
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engine.strategy.parameters = action_config
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engine.strategy.sub_id = risk_setting["sub_id"]
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# engine.strategy.on_init()
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# 实盘私有信息通过这个队列传输
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engine.queue_pri = queue
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print("engine.queue_pri:", engine.queue_pri)
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# 启动风控 实盘不管大资金还是小资金都要启动风控
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engine.strategy.add_risk_manager(
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symbol_list=[symbol_ for symbol_ in config],
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key=risk_setting["key"],
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secret=risk_setting["secret"],
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sub_id=risk_setting["sub_id"]
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)
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# engine.dma_depth_data(platform, int(start.timestamp()))
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threading.Thread(target=engine.dma_depth_data, args=(platform, int(start.timestamp()))).start()
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engine.receive_private_queue_data() # 接收实盘私有信息
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def run():
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# 当前跑的平台
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platform = "gate_swap_u"
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secret_name = "403" # 500_mm_ziying 200
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symbol = "bnbusdt" # btcusdt
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sub_id = "0" # 子账户id str
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settle = 'usdt'
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# platform = "binance_swap_u_uni"
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# secret_name = "200" # 500_mm_ziying 200
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# symbol = "dogeusdt" # btcusdt
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# sub_id = "1" # 子账户id str
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# settle = 'usdt'
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# secret_name = sys.argv[1] # 500_mm_ziying 200
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# symbol = sys.argv[2] # btcusdt
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# platform = sys.argv[3] # binance_spot_uni
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# sub_id = sys.argv[4] # 子账户id str
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# settle = 'usdt' if 'usdt' in symbol else 'fdusd'
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print(secret_name, symbol, settle)
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# 从配置文件中批量读取参数
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file_name = "data.json"
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with open(file_name, "rb") as json_file:
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json_data = json.loads(json_file.read())
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pprint(json_data[secret_name][sub_id][symbol])
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# 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
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config = {
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symbol: json_data[secret_name][sub_id][symbol]
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}
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# ------------------ 修改风控的配置信息 密钥 ---------------------------
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risk_setting = {
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"key": json_data[secret_name]["key"],
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"secret_name": secret_name,
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"sub_id": sub_id,
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"secret": json_data[secret_name]["secret"],
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"sub_key": json_data[secret_name][sub_id]["key"],
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"sub_secret": json_data[secret_name][sub_id]["secret"],
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"active": True, # True 风控启动
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"order_flow_limit_1m": 15, # 根据下单的标签来做1m的下单次数限制
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"net_max_down_level_1": 20, # 实时最大回撤值百分比 超过会提醒
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"net_max_down_level_2": 15,
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"net_max_down_level_3": 10,
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# 单币种的持仓限制
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"position_limit": {symbol_: config[symbol_]["capital"] * config[symbol_]["max_pos_rate"] * 1.04
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for symbol_ in config},
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"position_time_out": 45, # 持仓信息超过45秒没来会提醒
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"webhook_key": json_data[secret_name]["webhook_key"] # 钉钉发送的接收用户
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}
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# 这个是实际的本金
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get_account_ = get_account(risk_setting=risk_setting, platform=platform, settle=settle)
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balance = get_account_.balance + get_account_.unrealised_pnl
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print(get_account_.__dict__, balance)
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# 更新净值风控
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risk_setting["net_level_1"] = (
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balance * (100 - risk_setting["net_max_down_level_1"]) / 100
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)
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risk_setting["net_level_2"] = (
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balance * (100 - risk_setting["net_max_down_level_2"]) / 100
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)
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risk_setting["net_level_3"] = (
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balance * (100 - risk_setting["net_max_down_level_3"]) / 100
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)
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total_capital = sum([config[symbol_]["capital"] for symbol_ in config])
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print("当前实际杠杆倍数：", total_capital / balance)
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print(config)
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print(risk_setting)
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directory_name = "json_hub"
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# 获取当前工作目录
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current_directory = os.getcwd()
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# 构造 json_hub 目录的路径
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json_hub_path = os.path.join(current_directory, directory_name)
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# 检查目录是否存在
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if not os.path.exists(json_hub_path):
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# 如果不存在，则创建目录
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os.makedirs(json_hub_path)
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print(f"Directory '{directory_name}' created.")
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else:
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print(f"Directory '{directory_name}' already exists.")
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save_setting(setting=config, setting_filename=f'/json_hub/{secret_name}_config.json')
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save_setting(setting=risk_setting) # 将risk_setting 的信息写入配置文件
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process = []
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# 创建一个进程间内存共享的队列
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queue_dict = {}
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for index, key in enumerate(config):
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q = multiprocessing.Queue()
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queue_dict[key] = q
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# 先启动私有信息的发送进程 确保初始化有数据
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p = multiprocessing.Process(
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target=private_run, args=(queue_dict, config, risk_setting, platform, settle)
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)
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p.start()
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time.sleep(3)
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# 然后为每个品种启动一个进程来做接收
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for index, key in enumerate(config):
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p1 = multiprocessing.Process(
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target=run_single,
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args=(
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platform,
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key,
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config[key]["capital"],
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config,
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risk_setting,
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queue_dict[key],
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),
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)
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p1.start()
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process.append(p1)
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time.sleep(60)
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process.append(p)
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for p2 in process:
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p2.join()
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if __name__ == "__main__":
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run()
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