WINDAPI读取期货交易数据

本文参考进行一些改动和细化主要为了能够读取期货品种的昨结今结

另外安装WIND财经windows终端的情况下，查询相应文档的路径是

“量化-数据接口-API接口（API）”，“量化-数据接口-代码生成器”，WIND本身提供VBA, C#,C++,Python,R和MATLAB这几个接口，视方便可选用WindAPI文档_小黄人的黄的博客-CSDN博客_wind的apipython - WindAPI文档https://blog.csdn.net/Minion_Yellow/article/details/105679716

测试环境：

Windows+Python 3.7

from WindPy import w
import pandas as pd
import numpy as npw.start() # 必须 需要登陆WIND账户
w.isconnected() # 判断WindPy是否已经登录成功

1.简单测试读取

codes = ["PP2203"]
fields = ["CLOSE"]
beginTime='2021-08-01'
endTime='2022-03-02'
w.wsd(codes, fields, beginTime, endTime)

返回数据应该为

.ErrorCode=0
.Codes=[PP2203]
.Fields=[CLOSE]
.Times=[20210802,20210803,20210804,20210805,20210806,20210809,20210810,20210811,20210812,20210813,...]
.Data=[[None,None,None,None,None,None,None,None,None,None,...]]

其中ErrorCode=0代表读取成功，如果读取数据超限，ErrorCode=40XXXXX之类的数字

注意到Data数据全部为None，为什么呢？

2.读取期货多列数据

# 不加交易所的话 无法提取对应的数据
# Y2203.DCE会成功，Y2203会失败
w.wsd("Y2203.DCE", "close,pre_settle,settle,trade_code,windcode,open,high,low", "2022-02-05", "2022-03-03", "")

这样就可以成功返回多列数据了

.ErrorCode=0
.Codes=[Y2203.DCE]
.Fields=[CLOSE,PRE_SETTLE,SETTLE,TRADE_CODE,WINDCODE,OPEN,HIGH,LOW,LASTRADEDAY_S,FIRSTRADEDAY_S,...]
.Times=[20220207,20220208,20220209,20220210,20220211,20220214,20220215,20220216,20220217,20220218,...]
.Data=[[10320.0,10162.0,10088.0,10124.0,10102.0,10256.0,10260.0,10288.0,10354.0,10510.0,...],[9970.0,10432.0,10286.0,10040.0,10148.0,10110.0,10206.0,10200.0,10178.0,10320.0,...],[10432.0,10286.0,10040.0,10148.0,10110.0,10206.0,10200.0,10178.0,10320.0,10426.0,...],[Y2203,Y2203,Y2203,Y2203,Y2203,Y2203,Y2203,Y2203,Y2203,Y2203,...],[Y2203.DCE,Y2203.DCE,Y2203.DCE,Y2203.DCE,Y2203.DCE,Y2203.DCE,Y2203.DCE,Y2203.DCE,Y2203.DCE,Y2203.DCE,...],[10256.0,10320.0,10116.0,10156.0,10148.0,10182.0,10206.0,10192.0,10294.0,10410.0,...],[10648.0,10418.0,10116.0,10202.0,10182.0,10372.0,10260.0,10296.0,10412.0,10518.0,...],[10256.0,10134.0,9920.0,10046.0,10010.0,10150.0,10148.0,10016.0,10244.0,10384.0,...],[2022-02-07 00:00:00,2022-02-08 00:00:00,2022-02-09 00:00:00,2022-02-10 00:00:00,2022-02-11 00:00:00,2022-02-14 00:00:00,2022-02-15 00:00:00,2022-02-16 00:00:00,2022-02-17 00:00:00,2022-02-18 00:00:00,...],[None,None,None,None,None,None,None,None,None,None,...],...]

需要注意的是，使用wsd命令时，多个字段情况下，只能每次查询一个代码，也就是说，Y2203和Y2204要分两次查询，请特别注意

3.将得到的数据转换为 dataframe（供参考）

以股票数据为例

w_data = w.wsd("000002.SZ", "trade_code,sec_name,compindex2,indexweight", "2022-02-02", "2022-05-06", "index=3;unit=1;windCode3=000300.SH")
df = pd.DataFrame(w_data.Data,index=w_data.Fields, columns=w_data.Times).T
print(df)

这样就可以得到对应的dataframe了，然后操作起来就方便很多

4.不同品种对应的交易所，也稍微发一下

 "exchange": {"SHF": ["CU","AL","ZN","PB","AU","AG","RB","WR","FU","RU","BU","HC","NI","SN","SP","SS"], "INE": ["SC","NR","LU","BC"],"DCE": ["C","A","B","M","Y","P","L","V","J","JM","FB","BB","I","JD","PP","CS","EG","RR","EB","PG","LH"],"CZC": ["WH","PM","CF","SR","TA","OI","RI","MA","FG","RS","RM","JR","LR","SF","SM","ZC","CY","AP","CJ","UR","SA","PF","PK"],"CFE": ["IF","IC","IH","T","TS","TF","IO"],"SH": ["510050"]},

以上，完结撒花。

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