量化自动化交易python学习笔记之(一)BaoStock使用A股K线数据股票代码sh.60000，四年历史数据,用于后期追溯测试和策略可行性

import baostock as bs
import pandas as pd
 
#### 登陆系统 ####
lg = bs.login()
 
stockCode = "sh.600000"  #股票代码
start_date = '2017-06-01' #开始时间
end_date = '2021-12-31' #结束时间
frequency="d" #frequency="d"取日k线，
adjustflag="3"#adjustflag="3"默认不复权
 
# 显示登陆返回信息
print('login respond error_code:'+lg.error_code)
print('login respond  error_msg:'+lg.error_msg)
 
#### 获取历史K线数据 ####
# 详细指标参数，参见“历史行情指标参数”章节
rs = bs.query_history_k_data_plus(stockCode,
                                  "date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,peTTM,pbMRQ,psTTM,pcfNcfTTM,isST",
                                  start_date , end_date,
                                  frequency , adjustflag)
print('query_history_k_data_plus respond error_code:'+rs.error_code)
print('query_history_k_data_plus respond  error_msg:'+rs.error_msg)
 
#### 打印结果集 ####
data_list = []
while (rs.error_code == '0') & rs.next():
    # 获取一条记录，将记录合并在一起
    data_list.append(rs.get_row_data())
result = pd.DataFrame(data_list, columns=rs.fields)
#### 结果集输出到csv文件 ####
 
result.to_csv("F:/"+stockCode+"history_k_data"+end_date+"-"+end_date+".csv",encoding="gbk" ,index=False )
print(result)
 
#### 登出系统 ####
bs.logout()