170 lines
6.5 KiB
Python
170 lines
6.5 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 이격도 순위 [v1_국내주식-095]
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##############################################################################################
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# 상수 정의
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API_URL = "/uapi/domestic-stock/v1/ranking/disparity"
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def disparity(
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fid_input_price_2: str, # 입력 가격2
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fid_cond_mrkt_div_code: str, # 조건 시장 분류 코드
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fid_cond_scr_div_code: str, # 조건 화면 분류 코드
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fid_div_cls_code: str, # 분류 구분 코드
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fid_rank_sort_cls_code: str, # 순위 정렬 구분 코드
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fid_hour_cls_code: str, # 시간 구분 코드
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fid_input_iscd: str, # 입력 종목코드
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fid_trgt_cls_code: str, # 대상 구분 코드
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fid_trgt_exls_cls_code: str, # 대상 제외 구분 코드
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fid_input_price_1: str, # 입력 가격1
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fid_vol_cnt: str, # 거래량 수
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tr_cont: str = "", # 연속 거래 여부
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dataframe: Optional[pd.DataFrame] = None, # 누적 데이터프레임
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depth: int = 0, # 현재 재귀 깊이
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max_depth: int = 10 # 최대 재귀 깊이
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) -> Optional[pd.DataFrame]:
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"""
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[국내주식] 순위분석
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국내주식 이격도 순위[v1_국내주식-095]
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국내주식 이격도 순위 API를 호출하여 DataFrame으로 반환합니다.
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Args:
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fid_input_price_2 (str): 입력값 없을때 전체 (~ 가격)
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fid_cond_mrkt_div_code (str): 시장구분코드 (J:KRX, NX:NXT)
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fid_cond_scr_div_code (str): Unique key( 20178 )
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fid_div_cls_code (str): 0: 전체, 1:관리종목, 2:투자주의, 3:투자경고, 4:투자위험예고, 5:투자위험, 6:보톧주, 7:우선주
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fid_rank_sort_cls_code (str): 0: 이격도상위순, 1:이격도하위순
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fid_hour_cls_code (str): 5:이격도5, 10:이격도10, 20:이격도20, 60:이격도60, 120:이격도120
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fid_input_iscd (str): 0000:전체, 0001:거래소, 1001:코스닥, 2001:코스피200
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fid_trgt_cls_code (str): 0 : 전체
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fid_trgt_exls_cls_code (str): 0 : 전체
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fid_input_price_1 (str): 입력값 없을때 전체 (가격 ~)
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fid_vol_cnt (str): 입력값 없을때 전체 (거래량 ~)
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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 이격도 순위 데이터
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Example:
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>>> df = disparity(
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... fid_input_price_2="",
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... fid_cond_mrkt_div_code="J",
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... fid_cond_scr_div_code="20178",
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... fid_div_cls_code="0",
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... fid_rank_sort_cls_code="0",
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... fid_hour_cls_code="5",
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... fid_input_iscd="0000",
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... fid_trgt_cls_code="0",
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... fid_trgt_exls_cls_code="0",
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... fid_input_price_1="",
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... fid_vol_cnt=""
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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 fid_cond_mrkt_div_code:
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logger.error("fid_cond_mrkt_div_code is required. (e.g. 'J')")
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raise ValueError("fid_cond_mrkt_div_code is required. (e.g. 'J')")
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if not fid_cond_scr_div_code:
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logger.error("fid_cond_scr_div_code is required. (e.g. '20178')")
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raise ValueError("fid_cond_scr_div_code is required. (e.g. '20178')")
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if not fid_div_cls_code:
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logger.error("fid_div_cls_code is required. (e.g. '0')")
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raise ValueError("fid_div_cls_code is required. (e.g. '0')")
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if not fid_rank_sort_cls_code:
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logger.error("fid_rank_sort_cls_code is required. (e.g. '0')")
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raise ValueError("fid_rank_sort_cls_code is required. (e.g. '0')")
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if not fid_hour_cls_code:
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logger.error("fid_hour_cls_code is required. (e.g. '5')")
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raise ValueError("fid_hour_cls_code is required. (e.g. '5')")
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if not fid_input_iscd:
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logger.error("fid_input_iscd is required. (e.g. '0000')")
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raise ValueError("fid_input_iscd is required. (e.g. '0000')")
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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 = "FHPST01780000"
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params = {
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"fid_input_price_2": fid_input_price_2,
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"fid_cond_mrkt_div_code": fid_cond_mrkt_div_code,
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"fid_cond_scr_div_code": fid_cond_scr_div_code,
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"fid_div_cls_code": fid_div_cls_code,
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"fid_rank_sort_cls_code": fid_rank_sort_cls_code,
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"fid_hour_cls_code": fid_hour_cls_code,
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"fid_input_iscd": fid_input_iscd,
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"fid_trgt_cls_code": fid_trgt_cls_code,
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"fid_trgt_exls_cls_code": fid_trgt_exls_cls_code,
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"fid_input_price_1": fid_input_price_1,
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"fid_vol_cnt": fid_vol_cnt,
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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 disparity(
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fid_input_price_2,
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fid_cond_mrkt_div_code,
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fid_cond_scr_div_code,
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fid_div_cls_code,
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fid_rank_sort_cls_code,
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fid_hour_cls_code,
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fid_input_iscd,
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fid_trgt_cls_code,
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fid_trgt_exls_cls_code,
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fid_input_price_1,
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fid_vol_cnt,
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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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