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更新 'counter_demo.py'

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tzquant_zq 11 months ago
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# -*- 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=2000)
# 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:
# 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=334 / 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 = "200" # 500_mm_ziying 200
# symbol = "dogeusdt" # btcusdt
# sub_id = "1" # 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 = {
"key": json_data[secret_name]["key"],
"secret_name": secret_name,
"sub_id": sub_id,
"secret": json_data[secret_name]["secret"],
"sub_key": json_data[secret_name][sub_id]["key"],
"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": json_data[secret_name]["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
# 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)
)
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()
# -*- 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 = {
"key": json_data[secret_name]["key"],
"secret_name": secret_name,
"sub_id": sub_id,
"secret": json_data[secret_name]["secret"],
"sub_key": json_data[secret_name][sub_id]["key"],
"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
# 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()

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