baostock下载所有股票的基础数据

PYTHON 2024年1月31日

股票列表格式

股票列表文件

all_stocks-副本下载

代码

  • 2024-1-31更新
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import baostock as bs
import pandas as pd
 
 
class StockData:
    def __init__(self):
        self.df = pd.read_csv('all_stocks.csv', encoding='gbk', index_col='serial')
        self.code_list = self.df['code'].tolist()
        self.cols = ['name', 'code', 'close', 'peTTM', 'pbMRQ', 'psTTM', 'pcfNcfTTM', 'roeAvg', 'npMargin', 'gpMargin', 'netProfit', 'epsTTM',
                     'MBRevenue', 'totalShare', 'liqaShare', 'NRTurnRatio', 'NRTurnDays', 'INVTurnRatio', 'INVTurnDays', 'CATurnRatio', 'AssetTurnRatio',
                     'YOYEquity', 'YOYAsset', 'YOYNI', 'YOYEPSBasic', 'YOYPNI', 'currentRatio', 'quickRatio', 'cashRatio', 'YOYLiability', 'liabilityToAsset', 'assetToEquity',
                     'CAToAsset','NCAToAsset', 'tangibleAssetToAsset', 'ebitToInterest', 'CFOToOR', 'CFOToNP', 'CFOToGr','dupontROE', 'dupontAssetStoEquity',
                     'dupontAssetTurn', 'dupontPnitoni']
 
    def down_data(self):
        '''下载数据'''
        valuation_df = pd.DataFrame(columns=['code', 'close', 'peTTM', 'pbMRQ', 'psTTM', 'pcfNcfTTM'])
        profit_df = pd.DataFrame(
            columns=['code', 'pubDate', 'statDate', 'roeAvg',
                     'npMargin', 'gpMargin', 'netProfit', 'epsTTM',
                     'MBRevenue', 'totalShare', 'liqaShare']
        )
        operation_df = pd.DataFrame(
            columns=['code', 'pubDate', 'statDate', 'NRTurnRatio', 'NRTurnDays', 'INVTurnRatio', 'INVTurnDays', 'CATurnRatio', 'AssetTurnRatio']
        )
        growth_df = pd.DataFrame(
            columns=['code', 'pubDate', 'statDate', 'YOYEquity', 'YOYAsset', 'YOYNI', 'YOYEPSBasic', 'YOYPNI']
        )
        balance_df = pd.DataFrame(
            columns=['code', 'pubDate', 'statDate', 'currentRatio', 'quickRatio', 'cashRatio', 'YOYLiability', 'liabilityToAsset', 'assetToEquity']
        )
        cash_flow_df = pd.DataFrame(
            columns=['code', 'pubDate', 'statDate', 'CAToAsset','NCAToAsset', 'tangibleAssetToAsset', 'ebitToInterest', 'CFOToOR', 'CFOToNP', 'CFOToGr']
        )
        dupont_df = pd.DataFrame(
            columns=['code', 'pubDate', 'statDate', 'dupontROE', 'dupontAssetStoEquity', 'dupontAssetTurn', 'dupontPnitoni']
        )
        bs.login()
        for code in self.code_list:
            # 下载估值指标
            valuation_df = pd.concat([valuation_df, self.down_valuation(str(code))], ignore_index=True)
            # 下载季频盈利能力
            profit_df = pd.concat([profit_df, self.down_profit(str(code))], ignore_index=True)
            # 下载季频营运能力
            operation_df = pd.concat([operation_df, self.down_operation(str(code))], ignore_index=True)
            # 下载季频成长能力
            growth_df = pd.concat([growth_df, self.down_growth(str(code))], ignore_index=True)
            # 下载季频偿债能力
            balance_df = pd.concat([balance_df, self.down_balance(str(code))], ignore_index=True)
            # 下载季频现金流量
            cash_flow_df = pd.concat([cash_flow_df, self.down_cash_flow(str(code))], ignore_index=True)
            # 下载杜邦指数
            dupont_df = pd.concat([dupont_df, self.down_dupont(str(code))], ignore_index=True)
        bs.logout()
        all_data_list = [valuation_df, profit_df, operation_df, growth_df, balance_df, cash_flow_df, dupont_df]
        for d in all_data_list:
            self.df = self.merge_df(self.df, d)
        return self.df
 
    # 估值指标
    def down_valuation(self, code, start='2023-6-2', end='2023-12-31'):
        results = bs.query_history_k_data_plus(code,
                                               'code,close,peTTM,pbMRQ,psTTM,pcfNcfTTM',
                                               start_date=start, end_date=end,
                                               frequency="d", adjustflag="3")
        result_list = []
        while (results.error_code == '0') & results.next():
            result_list.append(results.get_row_data())
        if result_list:
            print('下载{}估值指标成功！'.format(code), result_list)
            results_valuation = pd.DataFrame([result_list[-1]], columns=results.fields)
            return results_valuation
 
    # 季频盈利能力
    def down_profit(self, code):
        profit_list = []
        rs_profit = bs.query_profit_data(code, year=2023, quarter=1)
        while (rs_profit.error_code == '0') & rs_profit.next():
            profit_list.append(rs_profit.get_row_data())
        if profit_list:
            result_profit = pd.DataFrame([profit_list[-1]], columns=rs_profit.fields)
            print('下载{}季频盈利能力成功！'.format(code), profit_list)
            return result_profit
 
    # 季频营运能力
    def down_operation(self, code):
        operation_list = []
        rs_operation = bs.query_operation_data(code, year=2023, quarter=1)
        while (rs_operation.error_code == '0') & rs_operation.next():
            operation_list.append(rs_operation.get_row_data())
        if operation_list:
            result_operation = pd.DataFrame([operation_list[-1]], columns=rs_operation.fields)
            print('下载{}季频营运能力成功！'.format(code), operation_list)
            return result_operation
 
    # 季频成长能力
    def down_growth(self, code):
        growth_list = []
        rs_growth = bs.query_growth_data(code, year=2023, quarter=1)
        while (rs_growth.error_code == '0') & rs_growth.next():
            growth_list.append(rs_growth.get_row_data())
        if growth_list:
            result_growth = pd.DataFrame([growth_list[-1]], columns=rs_growth.fields)
            print('下载{}季频成长能力成功！'.format(code), growth_list)
            return result_growth
 
    # 季频偿债能力
    def down_balance(self, code):
        balance_list = []
        rs_balance = bs.query_balance_data(code, year=2023, quarter=1)
        while (rs_balance.error_code == '0') & rs_balance.next():
            balance_list.append(rs_balance.get_row_data())
        if balance_list:
            result_balance = pd.DataFrame([balance_list[-1]], columns=rs_balance.fields)
            print('下载{}季频偿债能力成功！'.format(code), balance_list)
            return result_balance
 
    # 季频现金流量
    def down_cash_flow(self, code):
        cash_flow_list = []
        rs_cash_flow = bs.query_cash_flow_data(code, year=2023, quarter=1)
        while (rs_cash_flow.error_code == '0') & rs_cash_flow.next():
            cash_flow_list.append(rs_cash_flow.get_row_data())
        if cash_flow_list:
            result_cash_flow = pd.DataFrame([cash_flow_list[-1]], columns=rs_cash_flow.fields)
            print('下载{}季频现金流量成功！'.format(code), cash_flow_list)
            return result_cash_flow
 
    # 杜邦指数
    def down_dupont(self, code):
        dupont_list = []
        rs_dupont = bs.query_dupont_data(code, year=2023, quarter=1)
        while (rs_dupont.error_code == '0') & rs_dupont.next():
            dupont_list.append(rs_dupont.get_row_data())
        if dupont_list:
            result_profit = pd.DataFrame([dupont_list[-1]], columns=rs_dupont.fields)
            print('下载{}杜邦指数成功！'.format(code), dupont_list)
            return result_profit
 
    # 合并表格
    # 合并表格
    # 合并表格
    def merge_df(self, df1, df2):
        # 先删除可能会冲突的列
        df1 = df1.drop(['pubDate', 'statDate'], axis=1, errors='ignore')
        df2 = df2.drop(['pubDate', 'statDate'], axis=1, errors='ignore')
 
        # 合并数据框，指定suffixes参数
        all_df = pd.merge(df1, df2, on='code', suffixes=('_left', '_right'))
        return all_df
 
    # def merge_df(self, df1, df2):
    #     all_df = pd.merge(df1, df2, on='code')
    #     return all_df
 
    def to_file(self, df):
        df.to_csv('allStockData.csv', index=False)
 
if __name__ == '__main__':
        stockdata = StockData()
        daf = stockdata.down_data()
        daf = daf.loc[:, stockdata.cols]
        stockdata.to_file(daf)
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