a3b39f9e6e7e1b33a3eb9919923d939430b60b86,QUANTAXIS/QAFetch/QATdx.py,,QA_fetch_get_stock_min,#Any#Any#Any#Any#Any#Any#,255

Before Change

        for i in range(26):
            data += api.get_security_bars(level,
                                          market_code, code, (25 - i) * 800, 800)
        data = api.to_df(data)
        data["datetime"] = pd.to_datetime(data["datetime"])
        data["code"] = code
        data = data.drop(["year", "month", "day", "hour", "minute"], axis=1,
                         inplace=False).set_index("datetime", drop=False, inplace=False)
        data["datetime"] = data["datetime"].apply(lambda x: str(x)[0:19])
        data["date"] = data["datetime"].apply(lambda x: str(x)[0:10])
        data["date_stamp"] = data["date"].apply(
            lambda x: QA_util_date_stamp(x))
        data["time_stamp"] = data["datetime"].apply(
            lambda x: QA_util_time_stamp(x))
        data["type"] = type_
        print(data)

After Change

    with api.connect(ip, port):

        data = pd.concat([api.to_df(api.get_security_bars(level,
                                                          market_code, code, (25 - i) * 800, 800)) for i in range(26)], axis=0)
        return data\
            .assign(datetime=pd.to_datetime(data["datetime"]), code=code)\
            .drop(["year", "month", "day", "hour", "minute"], axis=1, inplace=False)\
            .set_index("datetime", drop=False, inplace=False)\
            .assign(date=data["datetime"].apply(lambda x: str(x)[0:10]))\
            .assign(date_stamp=QA_util_date_stamp(data["datetime"].apply(lambda x: str(x)[0:10])))\
            .assign(time_stamp=data["datetime"].apply(lambda x: QA_util_time_stamp(x)))\
            .assign(type=type_)[start:end]


def __QA_fetch_get_stock_transaction(code, day, retry, api):
    data_ = pd.concat([api.to_df(api.get_history_transaction_data(

Instances