Files
2026-02-04 00:16:34 +09:00

201 lines
7.5 KiB
Python

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