# -*- coding: utf-8 -*- """ Created on 2025-06-18 """ import logging import time from typing import Optional import sys import pandas as pd sys.path.extend(['../..', '.']) import kis_auth as ka # 로깅 설정 logging.basicConfig(level=logging.INFO, format='%(levelname)s - %(message)s') logger = logging.getLogger(__name__) ############################################################################################## # [국내주식] ELW시세 - ELW 상승률순위[국내주식-167] ############################################################################################## # 상수 정의 API_URL = "/uapi/elw/v1/ranking/updown-rate" def updown_rate( fid_cond_mrkt_div_code: str, # 사용자권한정보 fid_cond_scr_div_code: str, # 거래소코드 fid_unas_input_iscd: str, # 상승율/하락율 구분 fid_input_iscd: str, # N일자값 fid_input_rmnn_dynu_1: str, # 거래량조건 fid_div_cls_code: str, # NEXT KEY BUFF fid_input_price_1: str, # 사용자권한정보 fid_input_price_2: str, # 거래소코드 fid_input_vol_1: str, # 상승율/하락율 구분 fid_input_vol_2: str, # N일자값 fid_input_date_1: str, # 거래량조건 fid_rank_sort_cls_code: str, # NEXT KEY BUFF fid_blng_cls_code: str, # 사용자권한정보 fid_input_date_2: str, # 거래소코드 tr_cont: str = "", dataframe: Optional[pd.DataFrame] = None, depth: int = 0, max_depth: int = 10 ) -> Optional[pd.DataFrame]: """ [국내주식] ELW시세 ELW 상승률순위[국내주식-167] ELW 상승률순위 API를 호출하여 DataFrame으로 반환합니다. Args: fid_cond_mrkt_div_code (str): 시장구분코드 (W) fid_cond_scr_div_code (str): Unique key(20277) fid_unas_input_iscd (str): '000000(전체), 2001(코스피200) , 3003(코스닥150), 005930(삼성전자) ' fid_input_iscd (str): '00000(전체), 00003(한국투자증권) , 00017(KB증권), 00005(미래에셋주식회사)' fid_input_rmnn_dynu_1 (str): '0(전체), 1(1개월이하), 2(1개월~2개월), 3(2개월~3개월), 4(3개월~6개월), 5(6개월~9개월),6(9개월~12개월), 7(12개월이상)' fid_div_cls_code (str): 0(전체), 1(콜), 2(풋) fid_input_price_1 (str): fid_input_price_2 (str): fid_input_vol_1 (str): fid_input_vol_2 (str): fid_input_date_1 (str): fid_rank_sort_cls_code (str): '0(상승율), 1(하락율), 2(시가대비상승율) , 3(시가대비하락율), 4(변동율)' fid_blng_cls_code (str): 0(전체) fid_input_date_2 (str): tr_cont (str): 연속 거래 여부 dataframe (Optional[pd.DataFrame]): 누적 데이터프레임 depth (int): 현재 재귀 깊이 max_depth (int): 최대 재귀 깊이 (기본값: 10) Returns: Optional[pd.DataFrame]: ELW 상승률순위 데이터 Example: >>> df = updown_rate( ... fid_cond_mrkt_div_code='W', ... fid_cond_scr_div_code='20277', ... fid_unas_input_iscd='000000', ... fid_input_iscd='00000', ... fid_input_rmnn_dynu_1='0', ... fid_div_cls_code='0', ... fid_input_price_1='', ... fid_input_price_2='', ... fid_input_vol_1='', ... fid_input_vol_2='', ... fid_input_date_1='1', ... fid_rank_sort_cls_code='0', ... fid_blng_cls_code='0', ... fid_input_date_2='' ... ) >>> print(df) """ # 로깅 설정 logger = logging.getLogger(__name__) # 필수 파라미터 검증 if not fid_cond_mrkt_div_code: logger.error("fid_cond_mrkt_div_code is required. (e.g. 'W')") raise ValueError("fid_cond_mrkt_div_code is required. (e.g. 'W')") if not fid_cond_scr_div_code: logger.error("fid_cond_scr_div_code is required. (e.g. '20277')") raise ValueError("fid_cond_scr_div_code is required. (e.g. '20277')") if not fid_unas_input_iscd: logger.error("fid_unas_input_iscd is required. (e.g. '000000')") raise ValueError("fid_unas_input_iscd is required. (e.g. '000000')") if not fid_input_iscd: logger.error("fid_input_iscd is required. (e.g. '00000')") raise ValueError("fid_input_iscd is required. (e.g. '00000')") if not fid_input_rmnn_dynu_1: logger.error("fid_input_rmnn_dynu_1 is required. (e.g. '0')") raise ValueError("fid_input_rmnn_dynu_1 is required. (e.g. '0')") if not fid_div_cls_code: logger.error("fid_div_cls_code is required. (e.g. '0')") raise ValueError("fid_div_cls_code is required. (e.g. '0')") if not fid_rank_sort_cls_code: logger.error("fid_rank_sort_cls_code is required. (e.g. '0')") raise ValueError("fid_rank_sort_cls_code is required. (e.g. '0')") if not fid_blng_cls_code: logger.error("fid_blng_cls_code is required. (e.g. '0')") raise ValueError("fid_blng_cls_code is required. (e.g. '0')") # 최대 재귀 깊이 체크 if depth >= max_depth: logger.warning("Maximum recursion depth (%d) reached. Stopping further requests.", max_depth) return dataframe if dataframe is not None else pd.DataFrame() tr_id = "FHPEW02770000" params = { "FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code, "FID_COND_SCR_DIV_CODE": fid_cond_scr_div_code, "FID_UNAS_INPUT_ISCD": fid_unas_input_iscd, "FID_INPUT_ISCD": fid_input_iscd, "FID_INPUT_RMNN_DYNU_1": fid_input_rmnn_dynu_1, "FID_DIV_CLS_CODE": fid_div_cls_code, "FID_INPUT_PRICE_1": fid_input_price_1, "FID_INPUT_PRICE_2": fid_input_price_2, "FID_INPUT_VOL_1": fid_input_vol_1, "FID_INPUT_VOL_2": fid_input_vol_2, "FID_INPUT_DATE_1": fid_input_date_1, "FID_RANK_SORT_CLS_CODE": fid_rank_sort_cls_code, "FID_BLNG_CLS_CODE": fid_blng_cls_code, "FID_INPUT_DATE_2": fid_input_date_2, } # API 호출 res = ka._url_fetch(API_URL, tr_id, tr_cont, params) if res.isOK(): if hasattr(res.getBody(), 'output'): output_data = res.getBody().output if not isinstance(output_data, list): output_data = [output_data] current_data = pd.DataFrame(output_data) else: current_data = pd.DataFrame() if dataframe is not None: dataframe = pd.concat([dataframe, current_data], ignore_index=True) else: dataframe = current_data tr_cont = res.getHeader().tr_cont if tr_cont == "M": logger.info("Calling next page...") ka.smart_sleep() return updown_rate( fid_cond_mrkt_div_code, fid_cond_scr_div_code, fid_unas_input_iscd, fid_input_iscd, fid_input_rmnn_dynu_1, fid_div_cls_code, fid_input_price_1, fid_input_price_2, fid_input_vol_1, fid_input_vol_2, fid_input_date_1, fid_rank_sort_cls_code, fid_blng_cls_code, fid_input_date_2, "N", dataframe, depth + 1, max_depth ) else: logger.info("Data fetch complete.") return dataframe else: logger.error("API call failed: %s - %s", res.getErrorCode(), res.getErrorMessage()) res.printError(API_URL) return pd.DataFrame()