data_fq.py 文件源码

def QA_data_stock_to_fq(__data, type_='01'):

    def __QA_fetch_stock_xdxr(code, format_='pd', collections=QA_Setting.client.quantaxis.stock_xdxr):
        '????????/???'
        try:
            data = pd.DataFrame([item for item in collections.find(
                {'code': code})]).drop(['_id'], axis=1)
            data['date'] = pd.to_datetime(data['date'])
            return data.set_index(['date', 'code'], drop=False)
        except:
            return pd.DataFrame(columns=['category', 'category_meaning', 'code', 'date', 'fenhong',
                                         'fenshu', 'liquidity_after', 'liquidity_before', 'name', 'peigu', 'peigujia',
                                         'shares_after', 'shares_before', 'songzhuangu', 'suogu', 'xingquanjia'])
    '?? ??/??? ??????'
    if type_ in ['01', 'qfq']:
        #print(QA_data_make_qfq(__data, __QA_fetch_stock_xdxr(__data['code'][0])))
        return QA_data_make_qfq(__data, __QA_fetch_stock_xdxr(__data['code'][0]))
    elif type_ in ['02', 'hfq']:
        return QA_data_make_hfq(__data, __QA_fetch_stock_xdxr(__data['code'][0]))
    else:
        QA_util_log_info('wrong fq type! Using qfq')
        return QA_data_make_qfq(__data, __QA_fetch_stock_xdxr(__data['code'][0]))