mirror of
https://github.com/dupenf/stock-vit.git
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121 lines
3.7 KiB
Python
121 lines
3.7 KiB
Python
import baostock as bs
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import pandas as pd
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#### 登陆系统 ####
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# lg = bs.login()
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# 显示登陆返回信息
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# print("login respond error_code:" + lg.error_code)
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# print("login respond error_msg:" + lg.error_msg)
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def get_all_codes(save_path="./datasets"):
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# s = bs.query_all_stock()
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# s_df = s.get_data()
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# s_df.to_csv("./datasets/all_codes.csv", encoding="utf-8", index=False)
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#### 登陆系统 ####
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lg = bs.login()
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# 显示登陆返回信息
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print("login respond error_code:" + lg.error_code)
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print("login respond error_msg:" + lg.error_msg)
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#### 获取证券信息 ####
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rs = bs.query_all_stock(day="2024-06-20")
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print("query_all_stock respond error_code:" + rs.error_code)
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print("query_all_stock respond error_msg:" + rs.error_msg)
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#### 打印结果集 ####
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data_list = []
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while (rs.error_code == "0") & rs.next():
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# 获取一条记录，将记录合并在一起
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data_list.append(rs.get_row_data())
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result = pd.DataFrame(data_list, columns=rs.fields)
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#### 结果集输出到csv文件 ####
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result.to_csv(save_path+"/all_codes.csv", encoding="utf-8", index=False)
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print(result)
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#### 登出系统 ####
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bs.logout()
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def download_code_hist(
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save_path="./datasets/origins",
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code="sh.600000",
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start_date="1999-09-01",
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end_date="2024-06-30",
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freq="d",
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adjustflag="1"
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):
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#### 获取沪深A股历史K线数据 ####
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# 详细指标参数，参见“历史行情指标参数”章节；“分钟线”参数与“日线”参数不同。“分钟线”不包含指数。
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# 分钟线指标：date,time,code,open,high,low,close,volume,amount,adjustflag
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# 周月线指标：date,code,open,high,low,close,volume,amount,adjustflag,turn,pctChg
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fields = "date,time,code,open,high,low,close,volume,adjustflag",
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if freq == "d":
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fields = "date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,isST"
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rs = bs.query_history_k_data_plus(
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code,
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# "date,time,code,open,high,low,close,volume,adjustflag",
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# "date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,isST",
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fields=fields,
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start_date=start_date,
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end_date=end_date,
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frequency=freq,
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adjustflag=adjustflag, # hfq
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)
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#### 打印结果集 ####
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data_list = []
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while (rs.error_code == "0") & rs.next():
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# 获取一条记录，将记录合并在一起
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data_list.append(rs.get_row_data())
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result = pd.DataFrame(data_list, columns=rs.fields)
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# print(result)
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#### 结果集输出到csv文件 ####
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filename = save_path + "/" + code + ".csv"
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result.to_csv(filename, index=True)
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# print(result)
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def download_codes(save_path="./datasets/origins", filters=[],freq="d",adjustflag="1"):
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codes = pd.read_csv("./datasets/all_codes.csv")
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codes = codes["code"].tolist()
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lg = bs.login()
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# 显示登陆返回信息
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print("login respond error_code:" + lg.error_code)
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print("login respond error_msg:" + lg.error_msg)
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for code in codes:
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ignore = True
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for f in filters:
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if code.startswith(f):
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ignore = False
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if ignore:
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continue
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print(code)
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# if code < "sz.300138":
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# continue
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download_code_hist(save_path=save_path ,code=code,freq=freq,adjustflag=adjustflag)
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### 登出系统 ####
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bs.logout()
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# get_all_codes(save_path="./datasets")
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download_codes(
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save_path="./datasets/cyday",
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filters=["sh.68","sz.3"],
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# filters=["sz.301"]
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freq="d",
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adjustflag="1" # hfq
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)
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