161 lines
4.9 KiB
Python
161 lines
4.9 KiB
Python
"""
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Created on 2025-06-16
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"""
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import logging
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import time
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from typing import Optional
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import sys
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import pandas as pd
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sys.path.extend(['../..', '.'])
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import kis_auth as ka
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# 로깅 설정
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logging.basicConfig(level=logging.INFO, format='%(levelname)s - %(message)s')
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logger = logging.getLogger(__name__)
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##############################################################################################
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# [국내주식] 순위분석 > 국내주식 배당률 상위[국내주식-106]
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##############################################################################################
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# 상수 정의
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API_URL = "/uapi/domestic-stock/v1/ranking/dividend-rate"
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def dividend_rate(
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cts_area: str, # CTS_AREA
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gb1: str, # KOSPI
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upjong: str, # 업종구분
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gb2: str, # 종목선택
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gb3: str, # 배당구분
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f_dt: str, # 기준일From
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t_dt: str, # 기준일To
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gb4: str, # 결산/중간배당
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tr_cont: str = "",
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dataframe: Optional[pd.DataFrame] = None,
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depth: int = 0,
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max_depth: int = 10
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) -> Optional[pd.DataFrame]:
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"""
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[국내주식] 순위분석
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국내주식 배당률 상위[국내주식-106]
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국내주식 배당률 상위 API를 호출하여 DataFrame으로 반환합니다.
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Args:
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cts_area (str): 공백
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gb1 (str): 0:전체, 1:코스피, 2: 코스피200, 3: 코스닥,
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upjong (str): '코스피(0001:종합, 0002:대형주.…0027:제조업 ), 코스닥(1001:종합, …. 1041:IT부품 코스피200 (2001:KOSPI200, 2007:KOSPI100, 2008:KOSPI50)'
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gb2 (str): 0:전체, 6:보통주, 7:우선주
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gb3 (str): 1:주식배당, 2: 현금배당
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f_dt (str): 기준일 시작
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t_dt (str): 기준일 종료
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gb4 (str): 0:전체, 1:결산배당, 2:중간배당
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tr_cont (str): 연속 거래 여부
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dataframe (Optional[pd.DataFrame]): 누적 데이터프레임
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depth (int): 현재 재귀 깊이
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max_depth (int): 최대 재귀 깊이 (기본값: 10)
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Returns:
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Optional[pd.DataFrame]: 국내주식 배당률 상위 데이터
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Example:
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>>> df = dividend_rate(
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... cts_area=" ",
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... gb1="1",
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... upjong="0001",
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... gb2="0",
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... gb3="1",
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... f_dt="20230101",
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... t_dt="20231231",
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... gb4="0"
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... )
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>>> print(df)
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"""
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# 필수 파라미터 검증
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if not gb1:
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logger.error("gb1 is required. (e.g. '1')")
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raise ValueError("gb1 is required. (e.g. '1')")
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if not upjong:
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logger.error("upjong is required. (e.g. '0001')")
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raise ValueError("upjong is required. (e.g. '0001')")
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if not gb2:
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logger.error("gb2 is required. (e.g. '0')")
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raise ValueError("gb2 is required. (e.g. '0')")
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if not gb3:
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logger.error("gb3 is required. (e.g. '1')")
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raise ValueError("gb3 is required. (e.g. '1')")
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if not f_dt:
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logger.error("f_dt is required. (e.g. '20230101')")
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raise ValueError("f_dt is required. (e.g. '20230101')")
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if not t_dt:
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logger.error("t_dt is required. (e.g. '20231231')")
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raise ValueError("t_dt is required. (e.g. '20231231')")
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if not gb4:
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logger.error("gb4 is required. (e.g. '0')")
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raise ValueError("gb4 is required. (e.g. '0')")
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# 최대 재귀 깊이 체크
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if depth >= max_depth:
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logger.warning("Maximum recursion depth (%d) reached. Stopping further requests.", max_depth)
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return dataframe if dataframe is not None else pd.DataFrame()
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tr_id = "HHKDB13470100"
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params = {
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"CTS_AREA": cts_area,
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"GB1": gb1,
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"UPJONG": upjong,
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"GB2": gb2,
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"GB3": gb3,
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"F_DT": f_dt,
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"T_DT": t_dt,
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"GB4": gb4,
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}
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res = ka._url_fetch(API_URL, tr_id, tr_cont, params)
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if res.isOK():
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if hasattr(res.getBody(), 'output'):
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current_data = pd.DataFrame(res.getBody().output)
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else:
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current_data = pd.DataFrame()
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if dataframe is not None:
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dataframe = pd.concat([dataframe, current_data], ignore_index=True)
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else:
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dataframe = current_data
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tr_cont = res.getHeader().tr_cont
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if tr_cont == "M":
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logger.info("Calling next page...")
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ka.smart_sleep()
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return dividend_rate(
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cts_area,
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gb1,
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upjong,
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gb2,
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gb3,
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f_dt,
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t_dt,
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gb4,
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"N", dataframe, depth + 1, max_depth
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)
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else:
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logger.info("Data fetch complete.")
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return dataframe
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else:
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logger.error("API call failed: %s - %s", res.getErrorCode(), res.getErrorMessage())
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res.printError(API_URL)
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return pd.DataFrame()
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