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한국투자증권(API)/examples_llm/elw/udrl_asset_price/chk_udrl_asset_price.py Normal file
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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 udrl_asset_price import udrl_asset_price
# 로깅 설정
logging.basicConfig(level=logging.INFO, format='%(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
##############################################################################################
# [국내주식] ELW시세 - ELW 기초자산별 종목시세[국내주식-186]
##############################################################################################
COLUMN_MAPPING = {
'elw_shrn_iscd': 'ELW단축종목코드',
'hts_kor_isnm': 'HTS한글종목명',
'elw_prpr': 'ELW현재가',
'prdy_vrss': '전일대비',
'prdy_vrss_sign': '전일대비부호',
'prdy_ctrt': '전일대비율',
'acml_vol': '누적거래량',
'acpr': '행사가',
'prls_qryr_stpr_prc': '손익분기주가가격',
'hts_rmnn_dynu': 'HTS잔존일수',
'hts_ints_vltl': 'HTS내재변동성',
'stck_cnvr_rate': '주식전환비율',
'lp_hvol': 'LP보유량',
'lp_rlim': 'LP비중',
'lvrg_val': '레버리지값',
'gear': '기어링',
'delta_val': '델타값',
'gama': '감마',
'vega': '베가',
'theta': '세타',
'prls_qryr_rate': '손익분기비율',
'cfp': '자본지지점',
'prit': '패리티',
'invl_val': '내재가치값',
'tmvl_val': '시간가치값',
'hts_thpr': 'HTS이론가',
'stck_lstn_date': '주식상장일자',
'stck_last_tr_date': '주식최종거래일자',
'lp_ntby_qty': 'LP순매도량'
}
NUMERIC_COLUMNS = [
'ELW현재가', '전일대비', '전일대비율', '누적거래량', '행사가', '손익분기주가가격',
'HTS잔존일수', 'HTS내재변동성', '주식전환비율', 'LP보유량', 'LP비중', '레버리지값',
'기어링', '델타값', '감마', '베가', '세타', '손익분기비율', '자본지지점', '패리티',
'내재가치값', '시간가치값', 'HTS이론가', 'LP순매도량'
]
def main():
"""
[국내주식] ELW시세
ELW 기초자산별 종목시세[국내주식-186]
ELW 기초자산별 종목시세 테스트 함수
Parameters:
- fid_cond_mrkt_div_code (str): 조건시장분류코드 (시장구분(W))
- fid_cond_scr_div_code (str): 조건화면분류코드 (Uniquekey(11541))
- fid_mrkt_cls_code (str): 시장구분코드 (전체(A),콜(C),풋(P))
- fid_input_iscd (str): 입력종목코드 ('00000(전체), 00003(한국투자증권) , 00017(KB증권), 00005(미래에셋주식회사)')
- fid_unas_input_iscd (str): 기초자산입력종목코드 ()
- fid_vol_cnt (str): 거래량수 (전일거래량(정수량미만))
- fid_trgt_exls_cls_code (str): 대상제외구분코드 (거래불가종목제외(0:미체크,1:체크))
- fid_input_price_1 (str): 입력가격1 (가격~원이상)
- fid_input_price_2 (str): 입력가격2 (가격~월이하)
- fid_input_vol_1 (str): 입력거래량1 (거래량~계약이상)
- fid_input_vol_2 (str): 입력거래량2 (거래량~계약이하)
- fid_input_rmnn_dynu_1 (str): 입력잔존일수1 (잔존일(~일이상))
- fid_input_rmnn_dynu_2 (str): 입력잔존일수2 (잔존일(~일이하))
- fid_option (str): 옵션 (옵션상태(0:없음,1:ATM,2:ITM,3:OTM))
- fid_input_option_1 (str): 입력옵션1 ()
- fid_input_option_2 (str): 입력옵션2 ()
Returns:
- DataFrame: ELW 기초자산별 종목시세 결과
Example:
>>> df = udrl_asset_price(fid_cond_mrkt_div_code="W", fid_cond_scr_div_code="11541", fid_mrkt_cls_code="A", fid_input_iscd="00000", fid_unas_input_iscd="005930", fid_vol_cnt="1000", fid_trgt_exls_cls_code="0", fid_input_price_1="1000", fid_input_price_2="5000", fid_input_vol_1="100", fid_input_vol_2="1000", fid_input_rmnn_dynu_1="30", fid_input_rmnn_dynu_2="90", fid_option="0", fid_input_option_1="", fid_input_option_2="")
"""
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 = udrl_asset_price(
fid_cond_mrkt_div_code="W", # 조건시장분류코드
fid_cond_scr_div_code="11541", # 조건화면분류코드
fid_mrkt_cls_code="A", # 시장구분코드
fid_input_iscd="00000", # 입력종목코드
fid_unas_input_iscd="005930", # 기초자산입력종목코드
fid_vol_cnt="", # 거래량수
fid_trgt_exls_cls_code="0", # 대상제외구분코드
fid_input_price_1="", # 입력가격1
fid_input_price_2="", # 입력가격2
fid_input_vol_1="", # 입력거래량1
fid_input_vol_2="", # 입력거래량2
fid_input_rmnn_dynu_1="", # 입력잔존일수1
fid_input_rmnn_dynu_2="", # 입력잔존일수2
fid_option="0", # 옵션
fid_input_option_1="", # 입력옵션1
fid_input_option_2="", # 입력옵션2
)
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)
# 숫자 컬럼 처리
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 기초자산별 종목시세 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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한국투자증권(API)/examples_llm/elw/udrl_asset_price/udrl_asset_price.py Normal file
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# [국내주식] ELW시세 - ELW 기초자산별 종목시세
# Generated by KIS API Generator (Single API Mode)
# -*- 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 기초자산별 종목시세[국내주식-186]
##############################################################################################
# 상수 정의
API_URL = "/uapi/elw/v1/quotations/udrl-asset-price"
def udrl_asset_price(
fid_cond_mrkt_div_code: str, # 조건시장분류코드
fid_cond_scr_div_code: str, # 조건화면분류코드
fid_mrkt_cls_code: str, # 시장구분코드
fid_input_iscd: str, # 입력종목코드
fid_unas_input_iscd: str, # 기초자산입력종목코드
fid_vol_cnt: str, # 거래량수
fid_trgt_exls_cls_code: str, # 대상제외구분코드
fid_input_price_1: str, # 입력가격1
fid_input_price_2: str, # 입력가격2
fid_input_vol_1: str, # 입력거래량1
fid_input_vol_2: str, # 입력거래량2
fid_input_rmnn_dynu_1: str, # 입력잔존일수1
fid_input_rmnn_dynu_2: str, # 입력잔존일수2
fid_option: str, # 옵션
fid_input_option_1: str, # 입력옵션1
fid_input_option_2: str, # 입력옵션2
tr_cont: str = "",
dataframe: Optional[pd.DataFrame] = None,
depth: int = 0,
max_depth: int = 10
) -> Optional[pd.DataFrame]:
"""
[국내주식] ELW시세
ELW 기초자산별 종목시세[국내주식-186]
ELW 기초자산별 종목시세 API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 시장구분(W)
fid_cond_scr_div_code (str): Uniquekey(11541)
fid_mrkt_cls_code (str): 전체(A),콜(C),풋(P)
fid_input_iscd (str): '00000(전체), 00003(한국투자증권) , 00017(KB증권), 00005(미래에셋주식회사)'
fid_unas_input_iscd (str): 기초자산입력종목코드
fid_vol_cnt (str): 전일거래량(정수량미만)
fid_trgt_exls_cls_code (str): 거래불가종목제외(0:미체크,1:체크)
fid_input_price_1 (str): 가격~원이상
fid_input_price_2 (str): 가격~월이하
fid_input_vol_1 (str): 거래량~계약이상
fid_input_vol_2 (str): 거래량~계약이하
fid_input_rmnn_dynu_1 (str): 잔존일(~일이상)
fid_input_rmnn_dynu_2 (str): 잔존일(~일이하)
fid_option (str): 옵션상태(0:없음,1:ATM,2:ITM,3:OTM)
fid_input_option_1 (str): 입력옵션1
fid_input_option_2 (str): 입력옵션2
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 기초자산별 종목시세 데이터
Example:
>>> df = udrl_asset_price(
... fid_cond_mrkt_div_code='W',
... fid_cond_scr_div_code='11541',
... fid_mrkt_cls_code='A',
... fid_input_iscd='00000',
... fid_unas_input_iscd='005930',
... fid_vol_cnt='1000',
... fid_trgt_exls_cls_code='0',
... fid_input_price_1='1000',
... fid_input_price_2='5000',
... fid_input_vol_1='100',
... fid_input_vol_2='500',
... fid_input_rmnn_dynu_1='10',
... fid_input_rmnn_dynu_2='20',
... fid_option='0',
... fid_input_option_1='',
... fid_input_option_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. '11541')")
raise ValueError("fid_cond_scr_div_code is required. (e.g. '11541')")
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_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_unas_input_iscd:
logger.error("fid_unas_input_iscd is required. (e.g. '00001')")
raise ValueError("fid_unas_input_iscd is required. (e.g. '00001')")
if not fid_trgt_exls_cls_code:
logger.error("fid_trgt_exls_cls_code is required. (e.g. '0')")
raise ValueError("fid_trgt_exls_cls_code is required. (e.g. '0')")
if not fid_option:
logger.error("fid_option is required. (e.g. '0')")
raise ValueError("fid_option 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 = "FHKEW154101C0"
params = {
"FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
"FID_COND_SCR_DIV_CODE": fid_cond_scr_div_code,
"FID_MRKT_CLS_CODE": fid_mrkt_cls_code,
"FID_INPUT_ISCD": fid_input_iscd,
"FID_UNAS_INPUT_ISCD": fid_unas_input_iscd,
"FID_VOL_CNT": fid_vol_cnt,
"FID_TRGT_EXLS_CLS_CODE": fid_trgt_exls_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_RMNN_DYNU_1": fid_input_rmnn_dynu_1,
"FID_INPUT_RMNN_DYNU_2": fid_input_rmnn_dynu_2,
"FID_OPTION": fid_option,
"FID_INPUT_OPTION_1": fid_input_option_1,
"FID_INPUT_OPTION_2": fid_input_option_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 udrl_asset_price(
fid_cond_mrkt_div_code,
fid_cond_scr_div_code,
fid_mrkt_cls_code,
fid_input_iscd,
fid_unas_input_iscd,
fid_vol_cnt,
fid_trgt_exls_cls_code,
fid_input_price_1,
fid_input_price_2,
fid_input_vol_1,
fid_input_vol_2,
fid_input_rmnn_dynu_1,
fid_input_rmnn_dynu_2,
fid_option,
fid_input_option_1,
fid_input_option_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()