8a75d418c1edf5ffa1eba4db0f01a323182df62f,QUANTAXIS/QAFetch/QATdx.py,,QA_fetch_get_index_min,#Any#Any#Any#Any#Any#Any#,250

Before Change

    with api.connect(ip, port):
        data = pd.concat([api.to_df(api.get_index_bars(
            level, 1 if str(code)[0] in ["0", "8", "9"] else 0, code, (25 - i) * 800, 800)) for i in range(26)], axis=0)
        return data\
            .assign(datetime=pd.to_datetime(data["datetime"]), code=str(code))\
            .drop(["year", "month", "day", "hour", "minute"], axis=1, inplace=False)\
            .assign(date=data["datetime"].apply(lambda x: str(x)[0:10]))\
            .assign(date_stamp=data["datetime"].apply(lambda x: QA_util_date_stamp(x)))\
            .assign(time_stamp=data["datetime"].apply(lambda x: QA_util_time_stamp(x)))\
            .assign(type=type_).set_index("datetime", drop=False, inplace=False)[start:end]


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

After Change

    with api.connect(ip, port):
        data = pd.concat([api.to_df(api.get_index_bars(
            level, 1 if str(code)[0] in ["0", "8", "9"] else 0, code, (25 - i) * 800, 800)) for i in range(26)], axis=0)
        data = data\
            .assign(datetime=pd.to_datetime(data["datetime"]), code=str(code))\
            .drop(["year", "month", "day", "hour", "minute"], axis=1, inplace=False)\
            .assign(date=data["datetime"].apply(lambda x: str(x)[0:10]))\
            .assign(date_stamp=data["datetime"].apply(lambda x: QA_util_date_stamp(x)))\
            .assign(time_stamp=data["datetime"].apply(lambda x: QA_util_time_stamp(x)))\
            .assign(type=type_).set_index("datetime", drop=False, inplace=False)[start:end]
        // data
        return data.assign(datetime=data["datetime"].apply(lambda x: str(x)))


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

Instances