173 lines
6.9 KiB
Python
173 lines
6.9 KiB
Python
# [국내주식] 순위분석 - 국내주식 시간외거래량순위
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# Generated by KIS API Generator (Single API Mode)
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# -*- coding: utf-8 -*-
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"""
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Created on 2025-06-17
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"""
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import logging
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import sys
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import time
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from typing import Optional, Tuple
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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] 국내주식 > 국내주식 시간외거래량순위[국내주식-139]
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##############################################################################################
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# 상수 정의
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API_URL = "/uapi/domestic-stock/v1/ranking/overtime-volume"
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def overtime_volume(
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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_input_iscd: str, # 입력 종목코드
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fid_rank_sort_cls_code: str, # 순위 정렬 구분 코드
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fid_input_price_1: str, # 입력 가격1
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fid_input_price_2: str, # 입력 가격2
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fid_vol_cnt: str, # 거래량 수
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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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dataframe1: Optional[pd.DataFrame] = None, # 누적 데이터프레임 (output1)
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dataframe2: Optional[pd.DataFrame] = None, # 누적 데이터프레임 (output2)
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tr_cont: str = "",
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depth: int = 0,
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max_depth: int = 10
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) -> Tuple[pd.DataFrame, pd.DataFrame]:
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"""
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[국내주식] 순위분석
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국내주식 시간외거래량순위[국내주식-139]
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국내주식 시간외거래량순위 API를 호출하여 DataFrame으로 반환합니다.
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Args:
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fid_cond_mrkt_div_code (str): 시장구분코드 (J: 주식)
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fid_cond_scr_div_code (str): Unique key(20235)
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fid_input_iscd (str): 0000(전체), 0001(코스피), 1001(코스닥)
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fid_rank_sort_cls_code (str): 0(매수잔량), 1(매도잔량), 2(거래량)
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fid_input_price_1 (str): 가격 ~
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fid_input_price_2 (str): ~ 가격
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fid_vol_cnt (str): 거래량 ~
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fid_trgt_cls_code (str): 공백
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fid_trgt_exls_cls_code (str): 공백
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dataframe1 (Optional[pd.DataFrame]): 누적 데이터프레임 (output1)
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dataframe2 (Optional[pd.DataFrame]): 누적 데이터프레임 (output2)
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tr_cont (str): 연속 거래 여부
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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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Tuple[pd.DataFrame, pd.DataFrame]: 국내주식 시간외거래량순위 데이터
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Example:
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>>> df1, df2 = overtime_volume(
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fid_cond_mrkt_div_code='J',
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fid_cond_scr_div_code='20235',
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fid_input_iscd='0000',
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fid_rank_sort_cls_code='2',
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fid_input_price_1='',
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fid_input_price_2='',
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fid_vol_cnt='',
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fid_trgt_cls_code='',
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fid_trgt_exls_cls_code=''
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)
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>>> print(df1)
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>>> print(df2)
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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. '20235')")
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raise ValueError("fid_cond_scr_div_code is required. (e.g. '20235')")
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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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if not fid_rank_sort_cls_code:
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logger.error("fid_rank_sort_cls_code is required. (e.g. '2')")
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raise ValueError("fid_rank_sort_cls_code is required. (e.g. '2')")
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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 dataframe1 if dataframe1 is not None else pd.DataFrame(), dataframe2 if dataframe2 is not None else pd.DataFrame()
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tr_id = "FHPST02350000"
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params = {
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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_INPUT_ISCD": fid_input_iscd,
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"FID_RANK_SORT_CLS_CODE": fid_rank_sort_cls_code,
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"FID_INPUT_PRICE_1": fid_input_price_1,
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"FID_INPUT_PRICE_2": fid_input_price_2,
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"FID_VOL_CNT": fid_vol_cnt,
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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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}
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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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# output1 처리
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if hasattr(res.getBody(), 'output1'):
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output_data = res.getBody().output1
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if output_data:
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current_data1 = pd.DataFrame(output_data if isinstance(output_data, list) else [output_data])
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dataframe1 = pd.concat([dataframe1, current_data1],
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ignore_index=True) if dataframe1 is not None else current_data1
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else:
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dataframe1 = dataframe1 if dataframe1 is not None else pd.DataFrame()
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else:
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dataframe1 = dataframe1 if dataframe1 is not None else pd.DataFrame()
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# output2 처리
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if hasattr(res.getBody(), 'output2'):
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output_data = res.getBody().output2
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if output_data:
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current_data2 = pd.DataFrame(output_data if isinstance(output_data, list) else [output_data])
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dataframe2 = pd.concat([dataframe2, current_data2],
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ignore_index=True) if dataframe2 is not None else current_data2
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else:
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dataframe2 = dataframe2 if dataframe2 is not None else pd.DataFrame()
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else:
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dataframe2 = dataframe2 if dataframe2 is not None else pd.DataFrame()
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tr_cont = res.getHeader().tr_cont
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if tr_cont in ["M", "F"]:
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logger.info("Calling next page...")
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ka.smart_sleep()
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return overtime_volume(
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fid_cond_mrkt_div_code,
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fid_cond_scr_div_code,
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fid_input_iscd,
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fid_rank_sort_cls_code,
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fid_input_price_1,
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fid_input_price_2,
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fid_vol_cnt,
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fid_trgt_cls_code,
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fid_trgt_exls_cls_code,
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"N", dataframe1, dataframe2, 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 dataframe1, dataframe2
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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(), pd.DataFrame()
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