# -*- 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 당일급변종목[국내주식-171] ############################################################################################## # 상수 정의 API_URL = "/uapi/elw/v1/ranking/quick-change" def quick_change( fid_cond_mrkt_div_code: str, # 조건시장분류코드 fid_cond_scr_div_code: str, # 조건화면분류코드 fid_unas_input_iscd: str, # 기초자산입력종목코드 fid_input_iscd: str, # 발행사 fid_mrkt_cls_code: str, # 시장구분코드 fid_input_price_1: str, # 가격(이상) fid_input_price_2: str, # 가격(이하) fid_input_vol_1: str, # 거래량(이상) fid_input_vol_2: str, # 거래량(이하) fid_hour_cls_code: str, # 시간구분코드 fid_input_hour_1: str, # 입력 일 또는 분 fid_input_hour_2: str, # 기준시간(분 선택 시) fid_rank_sort_cls_code: str, # 순위정렬구분코드 fid_blng_cls_code: str, # 결재방법 tr_cont: str = "", dataframe: Optional[pd.DataFrame] = None, depth: int = 0, max_depth: int = 10 ) -> Optional[pd.DataFrame]: """ [국내주식] ELW시세 ELW 당일급변종목[국내주식-171] ELW 당일급변종목 API를 호출하여 DataFrame으로 반환합니다. Args: fid_cond_mrkt_div_code (str): 조건시장분류코드 (필수) fid_cond_scr_div_code (str): 조건화면분류코드 (필수) fid_unas_input_iscd (str): 기초자산입력종목코드 (필수) fid_input_iscd (str): 발행사 (필수) fid_mrkt_cls_code (str): 시장구분코드 (필수) fid_input_price_1 (str): 가격(이상) (필수) fid_input_price_2 (str): 가격(이하) (필수) fid_input_vol_1 (str): 거래량(이상) (필수) fid_input_vol_2 (str): 거래량(이하) (필수) fid_hour_cls_code (str): 시간구분코드 (필수) fid_input_hour_1 (str): 입력 일 또는 분 (필수) fid_input_hour_2 (str): 기준시간(분 선택 시) (필수) fid_rank_sort_cls_code (str): 순위정렬구분코드 (필수) fid_blng_cls_code (str): 결재방법 (필수) tr_cont (str): 연속 거래 여부 (옵션) dataframe (Optional[pd.DataFrame]): 누적 데이터프레임 (옵션) depth (int): 현재 재귀 깊이 (옵션) max_depth (int): 최대 재귀 깊이 (기본값: 10) Returns: Optional[pd.DataFrame]: ELW 당일급변종목 데이터 Example: >>> df = quick_change( ... fid_cond_mrkt_div_code='W', ... fid_cond_scr_div_code='20287', ... fid_unas_input_iscd='000000', ... fid_input_iscd='00000', ... fid_mrkt_cls_code='A', ... fid_input_price_1='1000', ... fid_input_price_2='5000', ... fid_input_vol_1='10000', ... fid_input_vol_2='50000', ... fid_hour_cls_code='1', ... fid_input_hour_1='10', ... fid_input_hour_2='30', ... fid_rank_sort_cls_code='1', ... fid_blng_cls_code='0' ... ) >>> 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. '20287')") raise ValueError("fid_cond_scr_div_code is required. (e.g. '20287')") 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_mrkt_cls_code: logger.error("fid_mrkt_cls_code is required. (e.g. 'A')") raise ValueError("fid_mrkt_cls_code is required. (e.g. 'A')") if not fid_hour_cls_code: logger.error("fid_hour_cls_code is required. (e.g. '1')") raise ValueError("fid_hour_cls_code is required. (e.g. '1')") if not fid_rank_sort_cls_code: logger.error("fid_rank_sort_cls_code is required. (e.g. '1')") raise ValueError("fid_rank_sort_cls_code is required. (e.g. '1')") 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 = "FHPEW02870000" 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_MRKT_CLS_CODE": fid_mrkt_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_HOUR_CLS_CODE": fid_hour_cls_code, "FID_INPUT_HOUR_1": fid_input_hour_1, "FID_INPUT_HOUR_2": fid_input_hour_2, "FID_RANK_SORT_CLS_CODE": fid_rank_sort_cls_code, "FID_BLNG_CLS_CODE": fid_blng_cls_code, } # 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 quick_change( fid_cond_mrkt_div_code, fid_cond_scr_div_code, fid_unas_input_iscd, fid_input_iscd, fid_mrkt_cls_code, fid_input_price_1, fid_input_price_2, fid_input_vol_1, fid_input_vol_2, fid_hour_cls_code, fid_input_hour_1, fid_input_hour_2, fid_rank_sort_cls_code, fid_blng_cls_code, "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()