Python做量化,如果是日内策略,需要更实时的行情数据,不然策略滑点太大,容易跑偏结果。
之前用行情网站提供的level1行情接口,实测平均更新延迟达到了6秒,超过10只股票并发请求频率过快很容易封IP。后面又尝试了买代理IP来请求,成本太高而且不稳定。
在Github上看到一个可转债的Golang高频T+0策略,对接的是WebSocket协议,拿来改了改,封装了一个Python版本的包,记录一下:
#!python3
# -*- coding:utf-8 -*-
import time
import datetime
import websocket
import zlib
import requests
import threading
# 行情订阅推送封装
class Construct:
__token = ""
__server_req_url = "http://jvquant.com/query/server?market=ab&type=websocket&token="
__ws_ser_addr = ""
__ws_conn = ""
__lv1_field = ["time", "name", "price", "ratio", "volume", "amount", "b1", "b1p", "b2", "b2p", "b3", "b3p", "b4",
"b4p", "b5", "b5p", "s1", "s1p", "s2", "s2p", "s3", "s3p", "s4", "s4p", "s5", "s5p"]
__lv2_field = ["time", "oid", "price", "vol"]
def __init__(self, logHandle, token, onRevLv1, onRevLv2):
if logHandle == "" or token == "" or onRevLv1 == "" or onRevLv2 == "":
msg = "行情初始化失败:logHandle或token或onRevLv1或onRevLv2必要参数缺失。"
print(msg)
exit(-1)
self.__log = logHandle
self.__token = token
self.__deal_lv1 = onRevLv1
self.__deal_lv2 = onRevLv2
self.__getSerAddr()
self.__conn_event = threading.Event()
self.th_handle = threading.Thread(target=self.__conn)
self.th_handle.start()
self.__conn_event.wait()
def __getSerAddr(self):
url = self.__server_req_url + self.__token
try:
res = requests.get(url=url)
except Exception as e:
self.__log(e)
return
if (res.json()["code"] == "0"):
self.__ws_ser_addr = res.json()["server"]
print("获取行情服务器地址成功:" + self.__ws_ser_addr)
else:
msg = "获取行情服务器地址失败:" + res.text
self.__log(msg)
exit(-1)
def __conn(self):
wsUrl = self.__ws_ser_addr + "?token=" + self.__token
self.__ws_conn = websocket.WebSocketApp(wsUrl,
on_open=self.__on_open,
on_data=self.__on_message,
on_error=self.__on_error,
on_close=self.__on_close)
self.__ws_conn.run_forever()
self.__conn_event.set()
self.__log("ws thread exited")
def addLv1(self, codeArr):
cmd = "add="
lv1Codes = []
for code in codeArr:
lv1Codes.append("lv1_" + code)
cmd = cmd + ",".join(lv1Codes)
self.__log("cmd:" + cmd)
self.__ws_conn.send(cmd)
def addLv2(self, codeArr):
cmd = "add="
lv1Codes = []
for code in codeArr:
lv1Codes.append("lv2_" + code)
cmd = cmd + ",".join(lv1Codes)
self.__log("cmd:" + cmd)
self.__ws_conn.send(cmd)
def dealLv1(self, data):
self.__deal_lv1(data)
def dealLv2(self, data):
self.__deal_lv1(data)
def __on_open(self, ws):
self.__conn_event.set()
self.__log("行情连接已创建")
def __on_error(self, ws, error):
self.__log("行情处理error:", error)
def __on_close(self, ws, code, msg):
self.__log("行情服务未连接")
def close(self):
self.__ws_conn.close()
def __on_message(self, ws, message, type, flag):
# 命令返回文本消息
if type == websocket.ABNF.OPCODE_TEXT:
self.__log("Text响应:" + message)
# 行情推送压缩二进制消息,在此解压缩
if type == websocket.ABNF.OPCODE_BINARY:
now = datetime.datetime.now()
nStamp = time.mktime(now.timetuple())
date = now.strftime('%Y-%m-%d')
rb = zlib.decompress(message, -zlib.MAX_WBITS)
text = rb.decode("utf-8")
# self.__log("Binary响应:" + text)
ex1 = text.split("\n")
for e1 in ex1:
ex2 = e1.split("=")
if len(ex2) != 2:
continue
code = ex2[0]
hqs = ex2[1]
if code.startswith("lv1_"):
code = code.replace("lv1_", "")
hq = hqs.split(",")
if len(hq) == len(self.__lv1_field):
hqMap = dict(zip(self.__lv1_field, hq))
timeStr = hqMap['time']
date_obj = datetime.datetime.strptime(date + ' ' + timeStr, '%Y-%m-%d %H:%M:%S')
tStamp = int(time.mktime(date_obj.timetuple()))
if abs(tStamp - nStamp) <= 2:
self.__deal_lv1(code, hqMap)
if code.startswith("lv2_"):
code = code.replace("lv2_", "")
hqArr = hqs.split("|")
for hq in hqArr:
hqEx = hq.split(",")
if len(hqEx) == len(self.__lv2_field):
hqMap = dict(zip(self.__lv2_field, hqEx))
timeEx = hqMap['time'].split('.')
if len(timeEx) == 2:
timeStr = timeEx[0]
date_obj = datetime.datetime.strptime(date + ' ' + timeStr, '%Y-%m-%d %H:%M:%S')
tStamp = int(time.mktime(date_obj.timetuple()))
if abs(tStamp - nStamp) <= 2:
self.__deal_lv2(code, hqMap)
引用地址:https://github.com/freevolunteer/bondTrader/blob/main/pyscript/jvUtil/HanqQing.py
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