Files
KisStock/한국투자증권(API)/examples_user/elw/elw_functions.py
2026-01-31 22:34:57 +09:00

3022 lines
115 KiB
Python

import logging
import time
import sys
from typing import Optional, Tuple
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 비교대상종목조회[국내주식-183]
##############################################################################################
def compare_stocks(
fid_cond_scr_div_code: str, # 조건화면분류코드
fid_input_iscd: str, # 입력종목코드
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 비교대상종목조회[국내주식-183]
ELW 비교대상종목조회 API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_scr_div_code (str): 조건화면분류코드 (예: '11517')
fid_input_iscd (str): 입력종목코드 (예: '005930')
tr_cont (str): 연속 거래 여부 (기본값: "")
dataframe (Optional[pd.DataFrame]): 누적 데이터프레임 (기본값: None)
depth (int): 현재 재귀 깊이 (기본값: 0)
max_depth (int): 최대 재귀 깊이 (기본값: 10)
Returns:
Optional[pd.DataFrame]: ELW 비교대상종목조회 데이터
Example:
>>> df = compare_stocks('11517', '005930')
>>> print(df)
"""
# 필수 파라미터 검증
if not fid_cond_scr_div_code:
logger.error("fid_cond_scr_div_code is required. (e.g. '11517')")
raise ValueError("fid_cond_scr_div_code is required. (e.g. '11517')")
if not fid_input_iscd:
logger.error("fid_input_iscd is required. (e.g. '005930')")
raise ValueError("fid_input_iscd is required. (e.g. '005930')")
# 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 = "FHKEW151701C0"
api_url = "/uapi/elw/v1/quotations/compare-stocks"
params = {
"FID_COND_SCR_DIV_CODE": fid_cond_scr_div_code,
"FID_INPUT_ISCD": fid_input_iscd,
}
# 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()
# 데이터프레임 병합
if dataframe is not None:
dataframe = pd.concat([dataframe, current_data], ignore_index=True)
else:
dataframe = current_data
# 연속 거래 여부 확인
tr_cont = res.getHeader().tr_cont
if tr_cont == "M":
logger.info("Calling next page...")
ka.smart_sleep()
return compare_stocks(
fid_cond_scr_div_code,
fid_input_iscd,
"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()
##############################################################################################
# [국내주식] ELW시세 - ELW 종목검색[국내주식-166]
##############################################################################################
def cond_search(
fid_cond_mrkt_div_code: str, # 조건시장분류코드 (필수)
fid_cond_scr_div_code: str, # 조건화면분류코드 (필수)
fid_rank_sort_cls_code: str, # 순위정렬구분코드 (필수)
fid_input_cnt_1: str, # 입력수1 (필수)
fid_rank_sort_cls_code_2: Optional[str] = "", # 순위정렬구분코드2 (선택)
fid_input_cnt_2: Optional[str] = "", # 입력수2 (선택)
fid_rank_sort_cls_code_3: Optional[str] = "", # 순위정렬구분코드3 (선택)
fid_input_cnt_3: Optional[str] = "", # 입력수3 (선택)
fid_trgt_cls_code: Optional[str] = "", # 대상구분코드 (선택)
fid_input_iscd: Optional[str] = "", # 입력종목코드 (선택 - 전체 허용)
fid_unas_input_iscd: Optional[str] = "", # 기초자산입력종목코드 (선택)
fid_mrkt_cls_code: Optional[str] = "", # 시장구분코드 (선택 - 전체 허용)
fid_input_date_1: Optional[str] = "", # 입력날짜1 (선택 - 전체 허용)
fid_input_date_2: Optional[str] = "", # 입력날짜2 (선택 - 전체 허용)
fid_input_iscd_2: Optional[str] = "", # 입력종목코드2 (선택)
fid_etc_cls_code: Optional[str] = "", # 기타구분코드 (선택 - 전체 허용)
fid_input_rmnn_dynu_1: Optional[str] = "", # 입력잔존일수1 (선택 - 이상값)
fid_input_rmnn_dynu_2: Optional[str] = "", # 입력잔존일수2 (선택 - 이하값)
fid_prpr_cnt1: Optional[str] = "", # 현재가수1 (선택 - 이상값)
fid_prpr_cnt2: Optional[str] = "", # 현재가수2 (선택 - 이하값)
fid_rsfl_rate1: Optional[str] = "", # 등락비율1 (선택 - 이상값)
fid_rsfl_rate2: Optional[str] = "", # 등락비율2 (선택 - 이하값)
fid_vol1: Optional[str] = "", # 거래량1 (선택 - 이상값)
fid_vol2: Optional[str] = "", # 거래량2 (선택 - 이하값)
fid_aply_rang_prc_1: Optional[str] = "", # 적용범위가격1 (선택)
fid_aply_rang_prc_2: Optional[str] = "", # 적용범위가격2 (선택)
fid_lvrg_val1: Optional[str] = "", # 레버리지값1 (선택)
fid_lvrg_val2: Optional[str] = "", # 레버리지값2 (선택)
fid_vol3: Optional[str] = "", # 거래량3 (선택)
fid_vol4: Optional[str] = "", # 거래량4 (선택)
fid_ints_vltl1: Optional[str] = "", # 내재변동성1 (선택 - 이상값)
fid_ints_vltl2: Optional[str] = "", # 내재변동성2 (선택 - 이하값)
fid_prmm_val1: Optional[str] = "", # 프리미엄값1 (선택 - 이상값)
fid_prmm_val2: Optional[str] = "", # 프리미엄값2 (선택 - 이하값)
fid_gear1: Optional[str] = "", # 기어링1 (선택 - 이상값)
fid_gear2: Optional[str] = "", # 기어링2 (선택 - 이하값)
fid_prls_qryr_rate1: Optional[str] = "", # 손익분기비율1 (선택 - 이상값)
fid_prls_qryr_rate2: Optional[str] = "", # 손익분기비율2 (선택 - 이하값)
fid_delta1: Optional[str] = "", # 델타1 (선택 - 이상값)
fid_delta2: Optional[str] = "", # 델타2 (선택 - 이하값)
fid_acpr1: Optional[str] = "", # 행사가1 (선택)
fid_acpr2: Optional[str] = "", # 행사가2 (선택)
fid_stck_cnvr_rate1: Optional[str] = "", # 주식전환비율1 (선택 - 이상값)
fid_stck_cnvr_rate2: Optional[str] = "", # 주식전환비율2 (선택 - 이하값)
fid_div_cls_code: Optional[str] = "", # 분류구분코드 (선택)
fid_prit1: Optional[str] = "", # 패리티1 (선택 - 이상값)
fid_prit2: Optional[str] = "", # 패리티2 (선택 - 이하값)
fid_cfp1: Optional[str] = "", # 자본지지점1 (선택 - 이상값)
fid_cfp2: Optional[str] = "", # 자본지지점2 (선택 - 이하값)
fid_input_nmix_price_1: Optional[str] = "", # 지수가격1 (선택 - 이상값)
fid_input_nmix_price_2: Optional[str] = "", # 지수가격2 (선택 - 이하값)
fid_egea_val1: Optional[str] = "", # E기어링값1 (선택 - 이상값)
fid_egea_val2: Optional[str] = "", # E기어링값2 (선택 - 이하값)
fid_input_dvdn_ert: Optional[str] = "", # 배당수익율 (선택 - 이상값)
fid_input_hist_vltl: Optional[str] = "", # 역사적변동성 (선택 - 이하값)
fid_theta1: Optional[str] = "", # 세타1 (선택 - 이상값)
fid_theta2: Optional[str] = "", # 세타2 (선택 - 이하값)
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
) -> pd.DataFrame:
"""
ELW 종목검색 API를 호출하여 조건에 맞는 ELW 종목 정보를 조회합니다.
한국투자 HTS(eFriend Plus) > [0291] ELW 종목검색 화면의 기능을 API로 구현한 함수입니다.
다양한 조건을 설정하여 ELW 종목을 검색하고, 한 번의 호출에 최대 100건까지 조회 가능합니다.
연속 조회를 통해 전체 데이터를 수집할 수 있습니다.
Args:
fid_cond_mrkt_div_code (str): 조건시장분류코드 (ELW의 경우 "W" 입력)
fid_cond_scr_div_code (str): 조건화면분류코드 (화면번호 "11510" 입력)
fid_rank_sort_cls_code (str): 순위정렬구분코드
- 0: 정렬안함, 1: 종목코드, 2: 현재가, 3: 대비율, 4: 거래량
- 5: 행사가격, 6: 전환비율, 7: 상장일, 8: 만기일, 9: 잔존일수, 10: 레버리지
fid_input_cnt_1 (str): 정렬1기준 (1: 상위, 2: 하위)
나머지 파라미터들: 대부분 선택사항으로 빈 문자열("")로 설정 가능
tr_cont (str): 연속 거래 여부 (초기 조회시 공백, 연속 조회시 "N")
dataframe (Optional[pd.DataFrame]): 누적 데이터프레임 (재귀 호출용)
depth (int): 현재 재귀 깊이 (재귀 호출 횟수 추적)
max_depth (int): 최대 재귀 깊이 (무한 재귀 방지, 기본값: 10)
Returns:
Optional[pd.DataFrame]: ELW 종목검색 결과 데이터프레임
- 성공시: ELW 종목 정보가 포함된 DataFrame 반환
- 실패시: 빈 DataFrame 반환
- API 오류시: None 반환
Raises:
ValueError: 필수 파라미터가 누락되거나 잘못된 값이 입력된 경우
Example:
>>> # 기본 ELW 검색 (전체 종목)
>>> df = cond_search(
... fid_cond_mrkt_div_code="W",
... fid_cond_scr_div_code="11510",
... fid_rank_sort_cls_code="0",
... fid_input_cnt_1="1",
... fid_rank_sort_cls_code_2="",
... fid_input_cnt_2="",
... fid_rank_sort_cls_code_3="",
... fid_input_cnt_3="",
... fid_trgt_cls_code="",
... fid_input_iscd="",
... fid_unas_input_iscd="",
... fid_mrkt_cls_code="",
... fid_input_date_1="",
... fid_input_date_2="",
... fid_input_iscd_2="",
... fid_etc_cls_code="",
... # 나머지 모든 파라미터는 빈 문자열
... **{param: "" for param in [
... "fid_input_rmnn_dynu_1", "fid_input_rmnn_dynu_2",
... "fid_prpr_cnt1", "fid_prpr_cnt2", "fid_rsfl_rate1", "fid_rsfl_rate2",
... "fid_vol1", "fid_vol2", "fid_aply_rang_prc_1", "fid_aply_rang_prc_2",
... "fid_lvrg_val1", "fid_lvrg_val2", "fid_vol3", "fid_vol4",
... "fid_ints_vltl1", "fid_ints_vltl2", "fid_prmm_val1", "fid_prmm_val2",
... "fid_gear1", "fid_gear2", "fid_prls_qryr_rate1", "fid_prls_qryr_rate2",
... "fid_delta1", "fid_delta2", "fid_acpr1", "fid_acpr2",
... "fid_stck_cnvr_rate1", "fid_stck_cnvr_rate2", "fid_div_cls_code",
... "fid_prit1", "fid_prit2", "fid_cfp1", "fid_cfp2",
... "fid_input_nmix_price_1", "fid_input_nmix_price_2",
... "fid_egea_val1", "fid_egea_val2", "fid_input_dvdn_ert",
... "fid_input_hist_vltl", "fid_theta1", "fid_theta2"
... ]}
... )
>>> print(df.head())
"""
# 필수 파라미터 검증 (최소한으로 축소)
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. '11510')")
raise ValueError("fid_cond_scr_div_code is required. (e.g. '11510')")
if fid_rank_sort_cls_code is None:
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_input_cnt_1:
logger.error("fid_input_cnt_1 is required. (e.g. '1')")
raise ValueError("fid_input_cnt_1 is required. (e.g. '1')")
# 최대 재귀 깊이 체크 (무한 재귀 방지)
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()
# API 호출 정보 설정
# 요청 파라미터 설정
tr_id = "FHKEW15100000"
api_url = "/uapi/elw/v1/quotations/cond-search"
params = {
"FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
"FID_COND_SCR_DIV_CODE": fid_cond_scr_div_code,
"FID_RANK_SORT_CLS_CODE": fid_rank_sort_cls_code,
"FID_INPUT_CNT_1": fid_input_cnt_1,
"FID_RANK_SORT_CLS_CODE_2": fid_rank_sort_cls_code_2,
"FID_INPUT_CNT_2": fid_input_cnt_2,
"FID_RANK_SORT_CLS_CODE_3": fid_rank_sort_cls_code_3,
"FID_INPUT_CNT_3": fid_input_cnt_3,
"FID_TRGT_CLS_CODE": fid_trgt_cls_code,
"FID_INPUT_ISCD": fid_input_iscd,
"FID_UNAS_INPUT_ISCD": fid_unas_input_iscd,
"FID_MRKT_CLS_CODE": fid_mrkt_cls_code,
"FID_INPUT_DATE_1": fid_input_date_1,
"FID_INPUT_DATE_2": fid_input_date_2,
"FID_INPUT_ISCD_2": fid_input_iscd_2,
"FID_ETC_CLS_CODE": fid_etc_cls_code,
"FID_INPUT_RMNN_DYNU_1": fid_input_rmnn_dynu_1,
"FID_INPUT_RMNN_DYNU_2": fid_input_rmnn_dynu_2,
"FID_PRPR_CNT1": fid_prpr_cnt1,
"FID_PRPR_CNT2": fid_prpr_cnt2,
"FID_RSFL_RATE1": fid_rsfl_rate1,
"FID_RSFL_RATE2": fid_rsfl_rate2,
"FID_VOL1": fid_vol1,
"FID_VOL2": fid_vol2,
"FID_APLY_RANG_PRC_1": fid_aply_rang_prc_1,
"FID_APLY_RANG_PRC_2": fid_aply_rang_prc_2,
"FID_LVRG_VAL1": fid_lvrg_val1,
"FID_LVRG_VAL2": fid_lvrg_val2,
"FID_VOL3": fid_vol3,
"FID_VOL4": fid_vol4,
"FID_INTS_VLTL1": fid_ints_vltl1,
"FID_INTS_VLTL2": fid_ints_vltl2,
"FID_PRMM_VAL1": fid_prmm_val1,
"FID_PRMM_VAL2": fid_prmm_val2,
"FID_GEAR1": fid_gear1,
"FID_GEAR2": fid_gear2,
"FID_PRLS_QRYR_RATE1": fid_prls_qryr_rate1,
"FID_PRLS_QRYR_RATE2": fid_prls_qryr_rate2,
"FID_DELTA1": fid_delta1,
"FID_DELTA2": fid_delta2,
"FID_ACPR1": fid_acpr1,
"FID_ACPR2": fid_acpr2,
"FID_STCK_CNVR_RATE1": fid_stck_cnvr_rate1,
"FID_STCK_CNVR_RATE2": fid_stck_cnvr_rate2,
"FID_DIV_CLS_CODE": fid_div_cls_code,
"FID_PRIT1": fid_prit1,
"FID_PRIT2": fid_prit2,
"FID_CFP1": fid_cfp1,
"FID_CFP2": fid_cfp2,
"FID_INPUT_NMIX_PRICE_1": fid_input_nmix_price_1,
"FID_INPUT_NMIX_PRICE_2": fid_input_nmix_price_2,
"FID_EGEA_VAL1": fid_egea_val1,
"FID_EGEA_VAL2": fid_egea_val2,
"FID_INPUT_DVDN_ERT": fid_input_dvdn_ert,
"FID_INPUT_HIST_VLTL": fid_input_hist_vltl,
"FID_THETA1": fid_theta1,
"FID_THETA2": fid_theta2,
}
# API 호출 정보 로그
logger.info("ELW 종목검색 API 호출 시작 (depth: %d)", depth)
# API 호출 실행
res = ka._url_fetch(api_url, tr_id, tr_cont, params)
# API 응답 처리
if res.isOK():
# 응답 데이터 처리
if hasattr(res.getBody(), 'output'):
output_data = res.getBody().output
# 단일 객체인 경우 리스트로 변환
if not isinstance(output_data, list):
output_data = [output_data]
current_data = pd.DataFrame(output_data)
logger.info("API 호출 성공: %d건의 데이터를 수신했습니다.", len(current_data))
else:
current_data = pd.DataFrame()
logger.warning("API 응답에서 output 데이터를 찾을 수 없습니다.")
# 데이터프레임 누적 처리
if dataframe is not None:
dataframe = pd.concat([dataframe, current_data], ignore_index=True)
else:
dataframe = current_data
# 연속 조회 여부 확인
tr_cont = res.getHeader().tr_cont
# 연속 데이터가 있는 경우 재귀 호출
if tr_cont == "M":
logger.info("Calling next page...")
ka.smart_sleep() # API 호출 간격 조절
return cond_search(
fid_cond_mrkt_div_code,
fid_cond_scr_div_code,
fid_rank_sort_cls_code,
fid_input_cnt_1,
fid_rank_sort_cls_code_2,
fid_input_cnt_2,
fid_rank_sort_cls_code_3,
fid_input_cnt_3,
fid_trgt_cls_code,
fid_input_iscd,
fid_unas_input_iscd,
fid_mrkt_cls_code,
fid_input_date_1,
fid_input_date_2,
fid_input_iscd_2,
fid_etc_cls_code,
fid_input_rmnn_dynu_1,
fid_input_rmnn_dynu_2,
fid_prpr_cnt1,
fid_prpr_cnt2,
fid_rsfl_rate1,
fid_rsfl_rate2,
fid_vol1,
fid_vol2,
fid_aply_rang_prc_1,
fid_aply_rang_prc_2,
fid_lvrg_val1,
fid_lvrg_val2,
fid_vol3,
fid_vol4,
fid_ints_vltl1,
fid_ints_vltl2,
fid_prmm_val1,
fid_prmm_val2,
fid_gear1,
fid_gear2,
fid_prls_qryr_rate1,
fid_prls_qryr_rate2,
fid_delta1,
fid_delta2,
fid_acpr1,
fid_acpr2,
fid_stck_cnvr_rate1,
fid_stck_cnvr_rate2,
fid_div_cls_code,
fid_prit1,
fid_prit2,
fid_cfp1,
fid_cfp2,
fid_input_nmix_price_1,
fid_input_nmix_price_2,
fid_egea_val1,
fid_egea_val2,
fid_input_dvdn_ert,
fid_input_hist_vltl,
fid_theta1,
fid_theta2,
"N", dataframe, depth + 1, max_depth
)
else:
# 데이터 수집 완료
logger.info("Data fetch complete.")
total_records = len(dataframe) if dataframe is not None else 0
logger.info("%d건의 ELW 종목 데이터를 수집했습니다.", total_records)
return dataframe
else:
# API 호출 실패 처리
error_code = res.getErrorCode()
error_message = res.getErrorMessage()
logger.error("API call failed: %s - %s", error_code, error_message)
res.printError(api_url)
return pd.DataFrame() # 빈 데이터프레임 반환
##############################################################################################
# [국내주식] ELW시세 - ELW 만기예정/만기종목[국내주식-184]
##############################################################################################
def expiration_stocks(
fid_cond_mrkt_div_code: str, # 조건시장분류코드
fid_cond_scr_div_code: str, # 조건화면분류코드
fid_input_date_1: str, # 입력날짜1
fid_input_date_2: str, # 입력날짜2
fid_div_cls_code: str, # 분류구분코드
fid_etc_cls_code: str, # 기타구분코드
fid_unas_input_iscd: str, # 기초자산입력종목코드
fid_input_iscd_2: str, # 발행회사코드
fid_blng_cls_code: str, # 결제방법
fid_input_option_1: str, # 입력옵션1
tr_cont: str = "",
dataframe: Optional[pd.DataFrame] = None,
depth: int = 0,
max_depth: int = 10
) -> Optional[pd.DataFrame]:
"""
[국내주식] ELW시세
ELW 만기예정_만기종목[국내주식-184]
ELW 만기예정_만기종목 API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): W 입력
fid_cond_scr_div_code (str): 11547 입력
fid_input_date_1 (str): 입력날짜 ~ (ex) 20240402)
fid_input_date_2 (str): ~입력날짜 (ex) 20240408)
fid_div_cls_code (str): 0(콜),1(풋),2(전체)
fid_etc_cls_code (str): 공백 입력
fid_unas_input_iscd (str): 000000(전체), 2001(KOSPI 200), 기초자산코드(종목코드 ex. 삼성전자-005930)
fid_input_iscd_2 (str): 00000(전체), 00003(한국투자증권), 00017(KB증권), 00005(미래에셋증권)
fid_blng_cls_code (str): 0(전체),1(일반),2(조기종료)
fid_input_option_1 (str): 공백 입력
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 만기예정_만기종목 데이터
Example:
>>> df = expiration_stocks(
... fid_cond_mrkt_div_code='W',
... fid_cond_scr_div_code='11547',
... fid_input_date_1='20240402',
... fid_input_date_2='20240408',
... fid_div_cls_code='0',
... fid_etc_cls_code='',
... fid_unas_input_iscd='000000',
... fid_input_iscd_2='00000',
... fid_blng_cls_code='0',
... fid_input_option_1='',
... )
>>> 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. '11547')")
raise ValueError("fid_cond_scr_div_code is required. (e.g. '11547')")
if not fid_input_date_1:
logger.error("fid_input_date_1 is required. (e.g. '20240402')")
raise ValueError("fid_input_date_1 is required. (e.g. '20240402')")
if not fid_input_date_2:
logger.error("fid_input_date_2 is required. (e.g. '20240408')")
raise ValueError("fid_input_date_2 is required. (e.g. '20240408')")
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_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_2:
logger.error("fid_input_iscd_2 is required. (e.g. '00000')")
raise ValueError("fid_input_iscd_2 is required. (e.g. '00000')")
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 = "FHKEW154700C0"
api_url = "/uapi/elw/v1/quotations/expiration-stocks"
params = {
"FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
"FID_COND_SCR_DIV_CODE": fid_cond_scr_div_code,
"FID_INPUT_DATE_1": fid_input_date_1,
"FID_INPUT_DATE_2": fid_input_date_2,
"FID_DIV_CLS_CODE": fid_div_cls_code,
"FID_ETC_CLS_CODE": fid_etc_cls_code,
"FID_UNAS_INPUT_ISCD": fid_unas_input_iscd,
"FID_INPUT_ISCD_2": fid_input_iscd_2,
"FID_BLNG_CLS_CODE": fid_blng_cls_code,
"FID_INPUT_OPTION_1": fid_input_option_1,
}
# 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 expiration_stocks(
fid_cond_mrkt_div_code,
fid_cond_scr_div_code,
fid_input_date_1,
fid_input_date_2,
fid_div_cls_code,
fid_etc_cls_code,
fid_unas_input_iscd,
fid_input_iscd_2,
fid_blng_cls_code,
fid_input_option_1,
"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()
##############################################################################################
# [국내주식] ELW시세 - ELW 지표순위[국내주식-169]
##############################################################################################
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"
api_url = "/uapi/elw/v1/ranking/indicator"
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()
##############################################################################################
# [국내주식] ELW시세 - ELW 투자지표추이(체결)[국내주식-172]
##############################################################################################
def indicator_trend_ccnl(
fid_cond_mrkt_div_code: str, # 조건시장분류코드
fid_input_iscd: str, # 입력종목코드
tr_cont: str = "",
dataframe: Optional[pd.DataFrame] = None,
depth: int = 0,
max_depth: int = 10
) -> Optional[pd.DataFrame]:
"""
[국내주식] ELW시세
ELW 투자지표추이(체결)[국내주식-172]
ELW 투자지표추이(체결) API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 조건시장분류코드 (필수)
fid_input_iscd (str): 입력종목코드 (필수)
tr_cont (str): 연속 거래 여부 (기본값: "")
dataframe (Optional[pd.DataFrame]): 누적 데이터프레임 (기본값: None)
depth (int): 현재 재귀 깊이 (기본값: 0)
max_depth (int): 최대 재귀 깊이 (기본값: 10)
Returns:
Optional[pd.DataFrame]: ELW 투자지표추이(체결) 데이터
Example:
>>> df = indicator_trend_ccnl("W", "58J297")
>>> print(df)
"""
# 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_input_iscd:
logger.error("fid_input_iscd is required. (e.g. '58J297')")
raise ValueError("fid_input_iscd is required. (e.g. '58J297')")
# 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 = "FHPEW02740100"
api_url = "/uapi/elw/v1/quotations/indicator-trend-ccnl"
params = {
"FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
"FID_INPUT_ISCD": fid_input_iscd,
}
# API 호출
res = ka._url_fetch(api_url, tr_id, tr_cont, params)
if res.isOK():
# 응답 데이터 처리
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()
# 데이터프레임 병합
if dataframe is not None:
dataframe = pd.concat([dataframe, current_data], ignore_index=True)
else:
dataframe = current_data
# 연속 거래 여부 확인
tr_cont = res.getHeader().tr_cont
if tr_cont == "M":
logger.info("Calling next page...")
ka.smart_sleep()
return indicator_trend_ccnl(
fid_cond_mrkt_div_code,
fid_input_iscd,
"N", dataframe, depth + 1, max_depth
)
else:
logger.info("Data fetch complete.")
return dataframe
else:
# API 에러 처리
logger.error("API call failed: %s - %s", res.getErrorCode(), res.getErrorMessage())
res.printError(api_url)
return pd.DataFrame()
##############################################################################################
# [국내주식] ELW시세 - ELW 투자지표추이(일별)[국내주식-173]
##############################################################################################
def indicator_trend_daily(
fid_cond_mrkt_div_code: str, # 시장 분류 코드 (예: 'W')
fid_input_iscd: str, # 종목코드 (6자리)
tr_cont: str = "",
dataframe: Optional[pd.DataFrame] = None,
depth: int = 0,
max_depth: int = 10
) -> Optional[pd.DataFrame]:
"""
[국내주식] ELW시세
ELW 투자지표추이(일별)[국내주식-173]
ELW 투자지표추이(일별) API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 시장 분류 코드 (예: 'W')
fid_input_iscd (str): 종목코드 (6자리, 예: '57K281')
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 투자지표추이(일별) 데이터
Example:
>>> df = indicator_trend_daily('W', '57K281')
"""
# 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_input_iscd:
logger.error("fid_input_iscd is required. (e.g. '57K281')")
raise ValueError("fid_input_iscd is required. (e.g. '57K281')")
# 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 = "FHPEW02740200"
api_url = "/uapi/elw/v1/quotations/indicator-trend-daily"
params = {
"FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
"FID_INPUT_ISCD": fid_input_iscd,
}
# 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_trend_daily(
fid_cond_mrkt_div_code,
fid_input_iscd,
"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()
##############################################################################################
# [국내주식] ELW시세 - ELW 투자지표추이(분별)[국내주식-174]
##############################################################################################
def indicator_trend_minute(
fid_cond_mrkt_div_code: str, # 조건시장분류코드
fid_input_iscd: str, # 입력종목코드
fid_hour_cls_code: str, # 시간구분코드
fid_pw_data_incu_yn: str, # 과거데이터 포함 여부
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 투자지표추이(분별)[국내주식-174]
ELW 투자지표추이(분별) API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 시장구분코드 (W)
fid_input_iscd (str): 입력종목코드 예시: 58J297(KBJ297삼성전자콜)
fid_hour_cls_code (str): 시간구분코드 예시: '60(1분), 180(3분), 300(5분), 600(10분), 1800(30분), 3600(60분), 7200(60분)'
fid_pw_data_incu_yn (str): 과거데이터 포함 여부 예시: N(과거데이터포함X), Y(과거데이터포함O)
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 투자지표추이(분별) 데이터
Example:
>>> df = indicator_trend_minute(
... fid_cond_mrkt_div_code='W',
... fid_input_iscd='58J297',
... fid_hour_cls_code='60',
... fid_pw_data_incu_yn='N'
... )
>>> 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_input_iscd:
logger.error("fid_input_iscd is required. (e.g. '58J297')")
raise ValueError("fid_input_iscd is required. (e.g. '58J297')")
if not fid_hour_cls_code:
logger.error("fid_hour_cls_code is required. (e.g. '60')")
raise ValueError("fid_hour_cls_code is required. (e.g. '60')")
if not fid_pw_data_incu_yn:
logger.error("fid_pw_data_incu_yn is required. (e.g. 'N')")
raise ValueError("fid_pw_data_incu_yn is required. (e.g. 'N')")
# 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()
# API 호출 URL 및 거래 ID 설정
# 요청 파라미터 설정
tr_id = "FHPEW02740300"
api_url = "/uapi/elw/v1/quotations/indicator-trend-minute"
params = {
"FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
"FID_INPUT_ISCD": fid_input_iscd,
"FID_HOUR_CLS_CODE": fid_hour_cls_code,
"FID_PW_DATA_INCU_YN": fid_pw_data_incu_yn,
}
# API 호출
res = ka._url_fetch(api_url, tr_id, tr_cont, params)
# API 호출 성공 여부 확인
if res.isOK():
# 응답 데이터 처리
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()
# 데이터프레임 병합
if dataframe is not None:
dataframe = pd.concat([dataframe, current_data], ignore_index=True)
else:
dataframe = current_data
# 연속 거래 여부 확인
tr_cont = res.getHeader().tr_cont
if tr_cont == "M":
logger.info("Calling next page...")
ka.smart_sleep()
return indicator_trend_minute(
fid_cond_mrkt_div_code,
fid_input_iscd,
fid_hour_cls_code,
fid_pw_data_incu_yn,
"N", dataframe, depth + 1, max_depth
)
else:
logger.info("Data fetch complete.")
return dataframe
else:
# API 호출 실패 시 에러 로그 출력
logger.error("API call failed: %s - %s", res.getErrorCode(), res.getErrorMessage())
res.printError(api_url)
return pd.DataFrame()
##############################################################################################
# [국내주식] ELW시세 - ELW LP매매추이[국내주식-182]
##############################################################################################
def lp_trade_trend(
fid_cond_mrkt_div_code: str, # 조건시장분류코드
fid_input_iscd: str, # 입력종목코드
dataframe1: Optional[pd.DataFrame] = None, # 누적 데이터프레임 (output1)
dataframe2: Optional[pd.DataFrame] = None, # 누적 데이터프레임 (output2)
tr_cont: str = "",
depth: int = 0,
max_depth: int = 10
) -> Tuple[Optional[pd.DataFrame], Optional[pd.DataFrame]]:
"""
[국내주식] ELW시세
ELW LP매매추이[국내주식-182]
ELW LP매매추이 API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 시장구분(W)
fid_input_iscd (str): 입력종목코드(ex 52K577(미래 K577KOSDAQ150콜)
dataframe1 (Optional[pd.DataFrame]): 누적 데이터프레임 (output1)
dataframe2 (Optional[pd.DataFrame]): 누적 데이터프레임 (output2)
tr_cont (str): 연속 거래 여부
depth (int): 현재 재귀 깊이
max_depth (int): 최대 재귀 깊이 (기본값: 10)
Returns:
Tuple[pd.DataFrame, pd.DataFrame]: ELW LP매매추이 데이터
Example:
>>> df1, df2 = lp_trade_trend("W", "52K577")
>>> print(df1)
>>> print(df2)
"""
# 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_input_iscd:
logger.error("fid_input_iscd is required. (e.g. '52K577')")
raise ValueError("fid_input_iscd is required. (e.g. '52K577')")
# 최대 재귀 깊이 체크
if depth >= max_depth:
logger.warning("Maximum recursion depth (%d) reached. Stopping further requests.", max_depth)
return dataframe1 if dataframe1 is not None else pd.DataFrame(), dataframe2 if dataframe2 is not None else pd.DataFrame()
tr_id = "FHPEW03760000"
api_url = "/uapi/elw/v1/quotations/lp-trade-trend"
params = {
"FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
"FID_INPUT_ISCD": fid_input_iscd,
}
res = ka._url_fetch(api_url, tr_id, tr_cont, params)
if res.isOK():
# output1 처리
if hasattr(res.getBody(), 'output1'):
output_data = res.getBody().output1
if output_data:
current_data1 = pd.DataFrame(output_data if isinstance(output_data, list) else [output_data])
dataframe1 = pd.concat([dataframe1, current_data1], ignore_index=True) if dataframe1 is not None else current_data1
else:
dataframe1 = dataframe1 if dataframe1 is not None else pd.DataFrame()
else:
dataframe1 = dataframe1 if dataframe1 is not None else pd.DataFrame()
# output2 처리
if hasattr(res.getBody(), 'output2'):
output_data = res.getBody().output2
if output_data:
current_data2 = pd.DataFrame(output_data if isinstance(output_data, list) else [output_data])
dataframe2 = pd.concat([dataframe2, current_data2], ignore_index=True) if dataframe2 is not None else current_data2
else:
dataframe2 = dataframe2 if dataframe2 is not None else pd.DataFrame()
else:
dataframe2 = dataframe2 if dataframe2 is not None else pd.DataFrame()
tr_cont = res.getHeader().tr_cont
if tr_cont in ["M", "F"]:
logger.info("Calling next page...")
ka.smart_sleep()
return lp_trade_trend(
fid_cond_mrkt_div_code,
fid_input_iscd,
"N", dataframe1, dataframe2, depth + 1, max_depth
)
else:
logger.info("Data fetch complete.")
return dataframe1, dataframe2
else:
logger.error("API call failed: %s - %s", res.getErrorCode(), res.getErrorMessage())
res.printError(api_url)
return pd.DataFrame(), pd.DataFrame()
##############################################################################################
# [국내주식] ELW시세 - ELW 신규상장종목[국내주식-181]
##############################################################################################
def newly_listed(
fid_cond_mrkt_div_code: str, # 조건시장분류코드
fid_cond_scr_div_code: str, # 조건화면분류코드
fid_div_cls_code: str, # 분류구분코드
fid_unas_input_iscd: str, # 기초자산입력종목코드
fid_input_iscd_2: str, # 입력종목코드2
fid_input_date_1: str, # 입력날짜1
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 신규상장종목[국내주식-181]
ELW 신규상장종목 API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 시장구분코드 (W)
fid_cond_scr_div_code (str): Unique key(11548)
fid_div_cls_code (str): 전체(02), 콜(00), 풋(01)
fid_unas_input_iscd (str): 'ex) 000000(전체), 2001(코스피200) , 3003(코스닥150), 005930(삼성전자) '
fid_input_iscd_2 (str): '00003(한국투자증권), 00017(KB증권), 00005(미래에셋증권)'
fid_input_date_1 (str): 날짜 (ex) 20240402)
fid_blng_cls_code (str): 0(전체), 1(일반), 2(조기종료)
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 신규상장종목 데이터
Example:
>>> df = newly_listed(
... fid_cond_mrkt_div_code='W',
... fid_cond_scr_div_code='11548',
... fid_div_cls_code='02',
... fid_unas_input_iscd='000000',
... fid_input_iscd_2='00003',
... fid_input_date_1='20240402',
... fid_blng_cls_code='0'
... )
>>> print(df)
"""
# 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. '11548')")
raise ValueError("fid_cond_scr_div_code is required. (e.g. '11548')")
if not fid_div_cls_code:
logger.error("fid_div_cls_code is required. (e.g. '02')")
raise ValueError("fid_div_cls_code is required. (e.g. '02')")
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_2:
logger.error("fid_input_iscd_2 is required. (e.g. '00003')")
raise ValueError("fid_input_iscd_2 is required. (e.g. '00003')")
if not fid_input_date_1:
logger.error("fid_input_date_1 is required. (e.g. '20240402')")
raise ValueError("fid_input_date_1 is required. (e.g. '20240402')")
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 = "FHKEW154800C0"
api_url = "/uapi/elw/v1/quotations/newly-listed"
params = {
"FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
"FID_COND_SCR_DIV_CODE": fid_cond_scr_div_code,
"FID_DIV_CLS_CODE": fid_div_cls_code,
"FID_UNAS_INPUT_ISCD": fid_unas_input_iscd,
"FID_INPUT_ISCD_2": fid_input_iscd_2,
"FID_INPUT_DATE_1": fid_input_date_1,
"FID_BLNG_CLS_CODE": fid_blng_cls_code,
}
# API 호출
res = ka._url_fetch(api_url, tr_id, tr_cont, params)
if res.isOK():
# 응답 데이터 처리
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 newly_listed(
fid_cond_mrkt_div_code,
fid_cond_scr_div_code,
fid_div_cls_code,
fid_unas_input_iscd,
fid_input_iscd_2,
fid_input_date_1,
fid_blng_cls_code,
"N", dataframe, depth + 1, max_depth
)
else:
logger.info("Data fetch complete.")
return dataframe
else:
# API 에러 처리
logger.error("API call failed: %s - %s", res.getErrorCode(), res.getErrorMessage())
res.printError(api_url)
return pd.DataFrame()
##############################################################################################
# [국내주식] ELW시세 - ELW 당일급변종목[국내주식-171]
##############################################################################################
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"
api_url = "/uapi/elw/v1/ranking/quick-change"
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()
##############################################################################################
# [국내주식] ELW시세 - ELW 민감도 순위[국내주식-170]
##############################################################################################
def sensitivity(
fid_cond_mrkt_div_code: str, # 조건시장분류코드
fid_cond_scr_div_code: str, # 조건화면분류코드
fid_unas_input_iscd: str, # 기초자산입력종목코드
fid_input_iscd: str, # 입력종목코드
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_input_rmnn_dynu_1: str, # 잔존일수(이상)
fid_input_date_1: str, # 조회기준일
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 민감도 순위[국내주식-170]
ELW 민감도 순위 API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 조건시장분류코드
fid_cond_scr_div_code (str): 조건화면분류코드
fid_unas_input_iscd (str): 기초자산입력종목코드
fid_input_iscd (str): 입력종목코드
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_input_rmnn_dynu_1 (str): 잔존일수(이상)
fid_input_date_1 (str): 조회기준일
fid_blng_cls_code (str): 결재방법
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 민감도 순위 데이터
Example:
>>> df = sensitivity(
fid_cond_mrkt_div_code='W',
fid_cond_scr_div_code='20285',
fid_unas_input_iscd='000000',
fid_input_iscd='00000',
fid_div_cls_code='0',
fid_input_price_1='0',
fid_input_price_2='100000',
fid_input_vol_1='0',
fid_input_vol_2='1000000',
fid_rank_sort_cls_code='0',
fid_input_rmnn_dynu_1='0',
fid_input_date_1='20230101',
fid_blng_cls_code='0'
)
>>> print(df)
"""
# 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. '20285')")
raise ValueError("fid_cond_scr_div_code is required. (e.g. '20285')")
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 = "FHPEW02850000"
api_url = "/uapi/elw/v1/ranking/sensitivity"
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_INPUT_RMNN_DYNU_1": fid_input_rmnn_dynu_1,
"FID_INPUT_DATE_1": fid_input_date_1,
"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 sensitivity(
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_input_rmnn_dynu_1,
fid_input_date_1,
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()
##############################################################################################
# [국내주식] ELW시세 - ELW 민감도 추이(체결)[국내주식-175]
##############################################################################################
def sensitivity_trend_ccnl(
fid_cond_mrkt_div_code: str, # 조건시장분류코드
fid_input_iscd: str, # 입력종목코드
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 민감도 추이(체결)[국내주식-175]
ELW 민감도 추이(체결) API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 조건시장분류코드 (필수)
fid_input_iscd (str): 입력종목코드 (필수)
tr_cont (str): 연속 거래 여부 (기본값: "")
dataframe (Optional[pd.DataFrame]): 누적 데이터프레임 (기본값: None)
depth (int): 현재 재귀 깊이 (기본값: 0)
max_depth (int): 최대 재귀 깊이 (기본값: 10)
Returns:
Optional[pd.DataFrame]: ELW 민감도 추이(체결) 데이터
Example:
>>> df = sensitivity_trend_ccnl('W', '58J297')
>>> print(df)
"""
# 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_input_iscd:
logger.error("fid_input_iscd is required. (e.g. '58J297')")
raise ValueError("fid_input_iscd is required. (e.g. '58J297')")
# 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 = "FHPEW02830100"
api_url = "/uapi/elw/v1/quotations/sensitivity-trend-ccnl"
params = {
"FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
"FID_INPUT_ISCD": fid_input_iscd,
}
# API 호출
res = ka._url_fetch(api_url, tr_id, tr_cont, params)
if res.isOK():
# 응답 데이터 처리
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()
# 데이터프레임 병합
if dataframe is not None:
dataframe = pd.concat([dataframe, current_data], ignore_index=True)
else:
dataframe = current_data
# 연속 거래 여부 확인
tr_cont = res.getHeader().tr_cont
if tr_cont == "M":
logger.info("Calling next page...")
ka.smart_sleep()
return sensitivity_trend_ccnl(
fid_cond_mrkt_div_code,
fid_input_iscd,
"N", dataframe, depth + 1, max_depth
)
else:
logger.info("Data fetch complete.")
return dataframe
else:
# API 에러 처리
logger.error("API call failed: %s - %s", res.getErrorCode(), res.getErrorMessage())
res.printError(api_url)
return pd.DataFrame()
##############################################################################################
# [국내주식] ELW시세 - ELW 민감도 추이(일별)[국내주식-176]
##############################################################################################
def sensitivity_trend_daily(
fid_cond_mrkt_div_code: str, # 조건시장분류코드
fid_input_iscd: str, # 입력종목코드
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 민감도 추이(일별)[국내주식-176]
ELW 민감도 추이(일별) API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 조건시장분류코드 (필수)
fid_input_iscd (str): 입력종목코드 (필수)
tr_cont (str): 연속 거래 여부 (기본값: "")
dataframe (Optional[pd.DataFrame]): 누적 데이터프레임 (기본값: None)
depth (int): 현재 재귀 깊이 (기본값: 0)
max_depth (int): 최대 재귀 깊이 (기본값: 10)
Returns:
Optional[pd.DataFrame]: ELW 민감도 추이(일별) 데이터
Example:
>>> df = sensitivity_trend_daily("W", "58J438")
>>> 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_input_iscd:
logger.error("fid_input_iscd is required. (e.g. '58J438')")
raise ValueError("fid_input_iscd is required. (e.g. '58J438')")
# 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()
# API 호출 URL 및 거래 ID 설정
# 요청 파라미터 설정
tr_id = "FHPEW02830200"
api_url = "/uapi/elw/v1/quotations/sensitivity-trend-daily"
params = {
"FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
"FID_INPUT_ISCD": fid_input_iscd,
}
# API 호출
res = ka._url_fetch(api_url, tr_id, tr_cont, params)
# API 응답 처리
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()
# 데이터프레임 병합
if dataframe is not None:
dataframe = pd.concat([dataframe, current_data], ignore_index=True)
else:
dataframe = current_data
# 연속 거래 여부 확인
tr_cont = res.getHeader().tr_cont
if tr_cont == "M":
logger.info("Calling next page...")
ka.smart_sleep()
return sensitivity_trend_daily(
fid_cond_mrkt_div_code,
fid_input_iscd,
"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()
##############################################################################################
# [국내주식] ELW시세 - ELW 기초자산 목록조회[국내주식-185]
##############################################################################################
def udrl_asset_list(
fid_cond_scr_div_code: str, # 조건화면분류코드
fid_rank_sort_cls_code: str, # 순위정렬구분코드
fid_input_iscd: str, # 입력종목코드
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 기초자산 목록조회[국내주식-185]
ELW 기초자산 목록조회 API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_scr_div_code (str): 조건화면분류코드, 예: '11541'
fid_rank_sort_cls_code (str): 순위정렬구분코드, 예: '0', '1', '2', '3', '4', '5', '6'
fid_input_iscd (str): 입력종목코드, 예: '00000', '00003', '00017', '00005'
tr_cont (str): 연속 거래 여부, 기본값은 공백
dataframe (Optional[pd.DataFrame]): 누적 데이터프레임
depth (int): 현재 재귀 깊이
max_depth (int): 최대 재귀 깊이 (기본값: 10)
Returns:
Optional[pd.DataFrame]: ELW 기초자산 목록조회 데이터
Example:
>>> df = udrl_asset_list('11541', '0', '00000')
>>> print(df)
"""
# 로깅 설정
logger = logging.getLogger(__name__)
# 필수 파라미터 검증
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_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_input_iscd:
logger.error("fid_input_iscd is required. (e.g. '00000')")
raise ValueError("fid_input_iscd is required. (e.g. '00000')")
# 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 = "FHKEW154100C0"
api_url = "/uapi/elw/v1/quotations/udrl-asset-list"
params = {
"FID_COND_SCR_DIV_CODE": fid_cond_scr_div_code,
"FID_RANK_SORT_CLS_CODE": fid_rank_sort_cls_code,
"FID_INPUT_ISCD": fid_input_iscd,
}
# 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_list(
fid_cond_scr_div_code,
fid_rank_sort_cls_code,
fid_input_iscd,
"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()
##############################################################################################
# [국내주식] ELW시세 - ELW 기초자산별 종목시세[국내주식-186]
##############################################################################################
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"
api_url = "/uapi/elw/v1/quotations/udrl-asset-price"
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()
##############################################################################################
# [국내주식] ELW시세 - ELW 상승률순위[국내주식-167]
##############################################################################################
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"
api_url = "/uapi/elw/v1/ranking/updown-rate"
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()
##############################################################################################
# [국내주식] ELW시세 - ELW 변동성추이(체결)[국내주식-177]
##############################################################################################
def volatility_trend_ccnl(
fid_cond_mrkt_div_code: str, # 조건시장분류코드
fid_input_iscd: str, # 입력종목코드
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 변동성추이(체결)[국내주식-177]
ELW 변동성추이(체결) API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 조건시장분류코드 (필수)
fid_input_iscd (str): 입력종목코드 (필수)
tr_cont (str): 연속 거래 여부 (기본값: "")
dataframe (Optional[pd.DataFrame]): 누적 데이터프레임 (기본값: None)
depth (int): 현재 재귀 깊이 (기본값: 0)
max_depth (int): 최대 재귀 깊이 (기본값: 10)
Returns:
Optional[pd.DataFrame]: ELW 변동성추이(체결) 데이터
Example:
>>> df = volatility_trend_ccnl("W", "58J297")
>>> 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_input_iscd:
logger.error("fid_input_iscd is required. (e.g. '58J297')")
raise ValueError("fid_input_iscd is required. (e.g. '58J297')")
# 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()
# API 호출 URL 및 거래 ID 설정
# 요청 파라미터 설정
tr_id = "FHPEW02840100"
api_url = "/uapi/elw/v1/quotations/volatility-trend-ccnl"
params = {
"FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
"FID_INPUT_ISCD": fid_input_iscd,
}
# API 호출
res = ka._url_fetch(api_url, tr_id, tr_cont, params)
# API 응답 처리
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()
# 데이터프레임 병합
if dataframe is not None:
dataframe = pd.concat([dataframe, current_data], ignore_index=True)
else:
dataframe = current_data
# 연속 거래 여부 확인
tr_cont = res.getHeader().tr_cont
if tr_cont == "M":
logger.info("Calling next page...")
ka.smart_sleep()
return volatility_trend_ccnl(
fid_cond_mrkt_div_code,
fid_input_iscd,
"N", dataframe, depth + 1, max_depth
)
else:
logger.info("Data fetch complete.")
return dataframe
else:
# API 에러 처리
logger.error("API call failed: %s - %s", res.getErrorCode(), res.getErrorMessage())
res.printError(api_url)
return pd.DataFrame()
##############################################################################################
# [국내주식] ELW시세 - ELW 변동성추이(일별)[국내주식-178]
##############################################################################################
def volatility_trend_daily(
fid_cond_mrkt_div_code: str, # 조건시장분류코드
fid_input_iscd: str, # 입력종목코드
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 변동성 추이(일별)[국내주식-178]
ELW 변동성 추이(일별) API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 조건시장분류코드 (예: 'W')
fid_input_iscd (str): 입력종목코드 (예: '58J297')
tr_cont (str): 연속 거래 여부 (기본값: "")
dataframe (Optional[pd.DataFrame]): 누적 데이터프레임 (기본값: None)
depth (int): 현재 재귀 깊이 (기본값: 0)
max_depth (int): 최대 재귀 깊이 (기본값: 10)
Returns:
Optional[pd.DataFrame]: ELW 변동성 추이(일별) 데이터
Example:
>>> df = volatility_trend_daily('W', '58J297')
>>> 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_input_iscd:
logger.error("fid_input_iscd is required. (e.g. '58J297')")
raise ValueError("fid_input_iscd is required. (e.g. '58J297')")
# 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 = "FHPEW02840200"
api_url = "/uapi/elw/v1/quotations/volatility-trend-daily"
params = {
"FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
"FID_INPUT_ISCD": fid_input_iscd,
}
# API 호출
res = ka._url_fetch(api_url, tr_id, tr_cont, params)
if res.isOK():
# 응답 데이터 처리
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()
# 데이터프레임 병합
if dataframe is not None:
dataframe = pd.concat([dataframe, current_data], ignore_index=True)
else:
dataframe = current_data
# 연속 거래 여부 확인
tr_cont = res.getHeader().tr_cont
if tr_cont == "M":
logger.info("Calling next page...")
ka.smart_sleep()
return volatility_trend_daily(
fid_cond_mrkt_div_code,
fid_input_iscd,
"N", dataframe, depth + 1, max_depth
)
else:
logger.info("Data fetch complete.")
return dataframe
else:
# API 에러 처리
logger.error("API call failed: %s - %s", res.getErrorCode(), res.getErrorMessage())
res.printError(api_url)
return pd.DataFrame()
##############################################################################################
# [국내주식] ELW시세 - ELW 변동성추이(분별)[국내주식-179]
##############################################################################################
def volatility_trend_minute(
fid_cond_mrkt_div_code: str, # 조건시장분류코드
fid_input_iscd: str, # 입력종목코드
fid_hour_cls_code: str, # 시간구분코드
fid_pw_data_incu_yn: str, # 과거데이터 포함 여부
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 변동성 추이(분별)[국내주식-179]
ELW 변동성 추이(분별) API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 조건시장분류코드 (예: 'W')
fid_input_iscd (str): 입력종목코드 (예: '58J297')
fid_hour_cls_code (str): 시간구분코드 (예: '60', '180', '300', '600', '1800', '3600')
fid_pw_data_incu_yn (str): 과거데이터 포함 여부 ('N' 또는 'Y')
tr_cont (str): 연속 거래 여부 (기본값: "")
dataframe (Optional[pd.DataFrame]): 누적 데이터프레임
depth (int): 현재 재귀 깊이
max_depth (int): 최대 재귀 깊이 (기본값: 10)
Returns:
Optional[pd.DataFrame]: ELW 변동성 추이(분별) 데이터
Example:
>>> df = volatility_trend_minute(
... fid_cond_mrkt_div_code='W',
... fid_input_iscd='58J297',
... fid_hour_cls_code='60',
... fid_pw_data_incu_yn='N'
... )
>>> 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_input_iscd:
logger.error("fid_input_iscd is required. (e.g. '58J297')")
raise ValueError("fid_input_iscd is required. (e.g. '58J297')")
if not fid_hour_cls_code:
logger.error("fid_hour_cls_code is required. (e.g. '60')")
raise ValueError("fid_hour_cls_code is required. (e.g. '60')")
if not fid_pw_data_incu_yn:
logger.error("fid_pw_data_incu_yn is required. (e.g. 'N')")
raise ValueError("fid_pw_data_incu_yn is required. (e.g. 'N')")
# 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()
# API 호출 URL 및 거래 ID 설정
# 요청 파라미터 설정
tr_id = "FHPEW02840300"
api_url = "/uapi/elw/v1/quotations/volatility-trend-minute"
params = {
"FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
"FID_INPUT_ISCD": fid_input_iscd,
"FID_HOUR_CLS_CODE": fid_hour_cls_code,
"FID_PW_DATA_INCU_YN": fid_pw_data_incu_yn,
}
# API 호출
res = ka._url_fetch(api_url, tr_id, tr_cont, params)
# API 응답 처리
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()
# 데이터프레임 병합
if dataframe is not None:
dataframe = pd.concat([dataframe, current_data], ignore_index=True)
else:
dataframe = current_data
# 연속 거래 여부 확인
tr_cont = res.getHeader().tr_cont
if tr_cont == "M":
logger.info("Calling next page...")
ka.smart_sleep()
return volatility_trend_minute(
fid_cond_mrkt_div_code,
fid_input_iscd,
fid_hour_cls_code,
fid_pw_data_incu_yn,
"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()
##############################################################################################
# [국내주식] ELW시세 - ELW 변동성추이(틱)[국내주식-180]
##############################################################################################
def volatility_trend_tick(
fid_cond_mrkt_div_code: str, # 조건시장분류코드
fid_input_iscd: str, # 입력종목코드
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 변동성 추이(틱)[국내주식-180]
ELW 변동성 추이(틱) API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 조건시장분류코드 (예: 'W')
fid_input_iscd (str): 입력종목코드 (예: '58J297')
tr_cont (str): 연속 거래 여부 (기본값: "")
dataframe (Optional[pd.DataFrame]): 누적 데이터프레임
depth (int): 현재 재귀 깊이
max_depth (int): 최대 재귀 깊이 (기본값: 10)
Returns:
Optional[pd.DataFrame]: ELW 변동성 추이(틱) 데이터
Example:
>>> df = volatility_trend_tick('W', '58J297')
>>> 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_input_iscd:
logger.error("fid_input_iscd is required. (e.g. '58J297')")
raise ValueError("fid_input_iscd is required. (e.g. '58J297')")
# 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()
# API 호출 URL 및 거래 ID 설정
# 요청 파라미터 설정
tr_id = "FHPEW02840400"
api_url = "/uapi/elw/v1/quotations/volatility-trend-tick"
params = {
"FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
"FID_INPUT_ISCD": fid_input_iscd,
}
# API 호출
res = ka._url_fetch(api_url, tr_id, tr_cont, params)
# API 응답 처리
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()
# 데이터프레임 병합
if dataframe is not None:
dataframe = pd.concat([dataframe, current_data], ignore_index=True)
else:
dataframe = current_data
# 연속 거래 여부 확인
tr_cont = res.getHeader().tr_cont
if tr_cont == "M":
logger.info("Calling next page...")
ka.smart_sleep()
return volatility_trend_tick(
fid_cond_mrkt_div_code,
fid_input_iscd,
"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()
##############################################################################################
# [국내주식] ELW시세 - ELW 거래량순위[국내주식-168]
##############################################################################################
def volume_rank(
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_input_rmnn_dynu_1: str, # 입력잔존일수
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_input_date_1: str, # 조회기준일
fid_rank_sort_cls_code: str, # 순위정렬구분코드
fid_blng_cls_code: str, # 소속구분코드
fid_input_iscd_2: str, # LP발행사
fid_input_date_2: str, # 만기일-최종거래일조회
tr_cont: str = "",
dataframe: Optional[pd.DataFrame] = None,
depth: int = 0,
max_depth: int = 10
) -> Optional[pd.DataFrame]:
"""
[국내주식] ELW시세
ELW 거래량순위[국내주식-168]
ELW 거래량순위 API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 조건시장분류코드 (예: 'W')
fid_cond_scr_div_code (str): 조건화면분류코드 (예: '20278')
fid_unas_input_iscd (str): 기초자산입력종목코드 (예: '000000')
fid_input_iscd (str): 발행사 (예: '00000')
fid_input_rmnn_dynu_1 (str): 입력잔존일수
fid_div_cls_code (str): 콜풋구분코드 (예: '0')
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_input_date_1 (str): 조회기준일
fid_rank_sort_cls_code (str): 순위정렬구분코드 (예: '0')
fid_blng_cls_code (str): 소속구분코드 (예: '0')
fid_input_iscd_2 (str): LP발행사 (예: '0000')
fid_input_date_2 (str): 만기일-최종거래일조회
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 거래량순위 데이터
Example:
>>> df = volume_rank(
... fid_cond_mrkt_div_code='W',
... fid_cond_scr_div_code='20278',
... fid_unas_input_iscd='000000',
... fid_input_iscd='00000',
... fid_input_rmnn_dynu_1='',
... 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_input_date_1='20230101',
... fid_rank_sort_cls_code='0',
... fid_blng_cls_code='0',
... fid_input_iscd_2='0000',
... 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. '20278')")
raise ValueError("fid_cond_scr_div_code is required. (e.g. '20278')")
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')")
if not fid_input_iscd_2:
logger.error("fid_input_iscd_2 is required. (e.g. '0000')")
raise ValueError("fid_input_iscd_2 is required. (e.g. '0000')")
# 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 = "FHPEW02780000"
api_url = "/uapi/elw/v1/ranking/volume-rank"
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_ISCD_2": fid_input_iscd_2,
"FID_INPUT_DATE_2": fid_input_date_2,
}
# API 호출
res = ka._url_fetch(api_url, tr_id, tr_cont, params)
if res.isOK():
# 응답 데이터 처리
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()
# 데이터프레임 병합
if dataframe is not None:
dataframe = pd.concat([dataframe, current_data], ignore_index=True)
else:
dataframe = current_data
# 연속 거래 여부 확인
tr_cont = res.getHeader().tr_cont
if tr_cont == "M":
logger.info("Calling next page...")
ka.smart_sleep()
return volume_rank(
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_iscd_2,
fid_input_date_2,
"N", dataframe, depth + 1, max_depth
)
else:
logger.info("Data fetch complete.")
return dataframe
else:
# API 에러 처리
logger.error("API call failed: %s - %s", res.getErrorCode(), res.getErrorMessage())
res.printError(api_url)
return pd.DataFrame()