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# -*- coding: utf-8 -*-
"""
Created on 2025-06-18
"""
import sys
import logging
import pandas as pd
sys.path.extend(['../..', '.']) # kis_auth 파일 경로 추가
import kis_auth as ka
from indicator import indicator
# 로깅 설정
logging.basicConfig(level=logging.INFO, format='%(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
##############################################################################################
# [국내주식] ELW시세 - ELW 지표순위[국내주식-169]
##############################################################################################
COLUMN_MAPPING = {
'elw_shrn_iscd': 'ELW단축종목코드',
'elw_kor_isnm': 'ELW한글종목명',
'elw_prpr': 'ELW현재가',
'prdy_vrss': '전일대비',
'prdy_vrss_sign': '전일대비부호',
'prdy_ctrt': '전일대비율',
'acml_vol': '누적거래량',
'stck_cnvr_rate': '주식전환비율',
'lvrg_val': '레버리지값',
'acpr': '행사가',
'tmvl_val': '시간가치값',
'invl_val': '내재가치값',
'elw_ko_barrier': '조기종료발생기준가격'
}
NUMERIC_COLUMNS = [
'ELW현재가', '전일대비', '전일대비율', '누적거래량', '주식전환비율',
'레버리지값', '행사가', '시간가치값', '내재가치값', '조기종료발생기준가격'
]
def main():
"""
[국내주식] ELW시세
ELW 지표순위[국내주식-169]
ELW 지표순위 테스트 함수
Parameters:
- fid_cond_mrkt_div_code (str): 조건시장분류코드 (시장구분코드 (W))
- fid_cond_scr_div_code (str): 조건화면분류코드 (Unique key(20279))
- fid_unas_input_iscd (str): 기초자산입력종목코드 ('000000(전체), 2001(코스피200) , 3003(코스닥150), 005930(삼성전자) ')
- fid_input_iscd (str): 발행사 ('00000(전체), 00003(한국투자증권) , 00017(KB증권), 00005(미래에셋주식회사)')
- fid_div_cls_code (str): 콜풋구분코드 (0(전체), 1(콜), 2(풋))
- 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_rank_sort_cls_code (str): 순위정렬구분코드 (0(전환비율), 1(레버리지), 2(행사가 ), 3(내재가치), 4(시간가치))
- fid_blng_cls_code (str): 결재방법 (0(전체), 1(일반), 2(조기종료))
Returns:
- DataFrame: ELW 지표순위 결과
Example:
>>> df = indicator(fid_cond_mrkt_div_code="W", fid_cond_scr_div_code="20279", fid_unas_input_iscd="000000", fid_input_iscd="00000", fid_div_cls_code="0", fid_input_price_1="", fid_input_price_2="", fid_input_vol_1="", fid_input_vol_2="", fid_rank_sort_cls_code="0", fid_blng_cls_code="0")
"""
try:
# pandas 출력 옵션 설정
pd.set_option('display.max_columns', None) # 모든 컬럼 표시
pd.set_option('display.width', None) # 출력 너비 제한 해제
pd.set_option('display.max_rows', None) # 모든 행 표시
# 토큰 발급
logger.info("토큰 발급 중...")
ka.auth()
logger.info("토큰 발급 완료")
# API 호출
logger.info("API 호출")
result = indicator(
fid_cond_mrkt_div_code="W", # 조건시장분류코드
fid_cond_scr_div_code="20279", # 조건화면분류코드
fid_unas_input_iscd="000000", # 기초자산입력종목코드
fid_input_iscd="00000", # 발행사
fid_div_cls_code="0", # 콜풋구분코드
fid_input_price_1="", # 가격(이상)
fid_input_price_2="", # 가격(이하)
fid_input_vol_1="", # 거래량(이상)
fid_input_vol_2="", # 거래량(이하)
fid_rank_sort_cls_code="0", # 순위정렬구분코드
fid_blng_cls_code="0", # 결재방법
)
if result is None or result.empty:
logger.warning("조회된 데이터가 없습니다.")
return
# 컬럼명 출력
logger.info("사용 가능한 컬럼 목록:")
logger.info(result.columns.tolist())
# 한글 컬럼명으로 변환
result = result.rename(columns=COLUMN_MAPPING)
# 숫자형 컬럼 소수점 둘째자리까지 표시
for col in NUMERIC_COLUMNS:
if col in result.columns:
result[col] = pd.to_numeric(result[col], errors='coerce').round(2)
# 결과 출력
logger.info("=== ELW 지표순위 결과 ===")
logger.info("조회된 데이터 건수: %d", len(result))
print(result)
except Exception as e:
logger.error("에러 발생: %s", str(e))
raise
if __name__ == "__main__":
main()

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"""
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 지표순위[국내주식-169]
##############################################################################################
# 상수 정의
API_URL = "/uapi/elw/v1/ranking/indicator"
def indicator(
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_div_cls_code: str, # 콜풋구분코드
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_rank_sort_cls_code: str, # 순위정렬구분코드
fid_blng_cls_code: str, # 결재방법
tr_cont: str = "", # 연속 거래 여부
dataframe: Optional[pd.DataFrame] = None, # 누적 데이터프레임
depth: int = 0, # 현재 재귀 깊이
max_depth: int = 10 # 최대 재귀 깊이
) -> Optional[pd.DataFrame]:
"""
[국내주식] ELW시세
ELW 지표순위[국내주식-169]
ELW 지표순위 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_div_cls_code (str): 콜풋구분코드 (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_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 지표순위 데이터
Example:
>>> df = indicator(
... fid_cond_mrkt_div_code='W',
... fid_cond_scr_div_code='20279',
... fid_unas_input_iscd='000000',
... fid_input_iscd='00000',
... fid_div_cls_code='0',
... fid_input_price_1='1000',
... fid_input_price_2='5000',
... fid_input_vol_1='100',
... fid_input_vol_2='1000',
... fid_rank_sort_cls_code='0',
... 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. '20279')")
raise ValueError("fid_cond_scr_div_code is required. (e.g. '20279')")
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_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 = "FHPEW02790000"
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_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_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 indicator(
fid_cond_mrkt_div_code,
fid_cond_scr_div_code,
fid_unas_input_iscd,
fid_input_iscd,
fid_div_cls_code,
fid_input_price_1,
fid_input_price_2,
fid_input_vol_1,
fid_input_vol_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()