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

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6.0 KiB
Python

# DOMSTK_RANK - 국내주식 체결강도 상위
# Generated by KIS API Generator (Single API Mode)
import logging
import sys
import time
from typing import Optional
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] 순위분석 > 국내주식 체결강도 상위[v1_국내주식-101]
##############################################################################################
# 상수 정의
API_URL = "/uapi/domestic-stock/v1/ranking/volume-power"
def volume_power(
fid_trgt_exls_cls_code: str, # 대상 제외 구분 코드
fid_cond_mrkt_div_code: str, # 조건 시장 분류 코드
fid_cond_scr_div_code: str, # 조건 화면 분류 코드
fid_input_iscd: str, # 입력 종목코드
fid_div_cls_code: str, # 분류 구분 코드
fid_input_price_1: str, # 입력 가격1
fid_input_price_2: str, # 입력 가격2
fid_vol_cnt: str, # 거래량 수
fid_trgt_cls_code: str, # 대상 구분 코드
tr_cont: str = "",
dataframe: Optional[pd.DataFrame] = None,
depth: int = 0,
max_depth: int = 10
) -> Optional[pd.DataFrame]:
"""
[국내주식] 순위분석
국내주식 체결강도 상위[v1_국내주식-101]
국내주식 체결강도 상위 API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_trgt_exls_cls_code (str): 0 : 전체
fid_cond_mrkt_div_code (str): 시장구분코드 (J:KRX, NX:NXT)
fid_cond_scr_div_code (str): Unique key( 20168 )
fid_input_iscd (str): 0000:전체, 0001:거래소, 1001:코스닥, 2001:코스피200
fid_div_cls_code (str): 0: 전체, 1: 보통주 2: 우선주
fid_input_price_1 (str): 입력값 없을때 전체 (가격 ~)
fid_input_price_2 (str): 입력값 없을때 전체 (~ 가격)
fid_vol_cnt (str): 입력값 없을때 전체 (거래량 ~)
fid_trgt_cls_code (str): 0 : 전체
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]: 국내주식 체결강도 상위 데이터
Example:
>>> df = volume_power(
... fid_trgt_exls_cls_code="0",
... fid_cond_mrkt_div_code="J",
... fid_cond_scr_div_code="20168",
... fid_input_iscd="0000",
... fid_div_cls_code="0",
... fid_input_price_1="",
... fid_input_price_2="",
... fid_vol_cnt="",
... fid_trgt_cls_code="0"
... )
>>> print(df)
"""
# 필수 파라미터 검증
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 fid_cond_mrkt_div_code != "J":
logger.error("fid_cond_mrkt_div_code must be 'J'.")
raise ValueError("fid_cond_mrkt_div_code must be 'J'.")
if fid_cond_scr_div_code != "20168":
logger.error("fid_cond_scr_div_code must be '20168'.")
raise ValueError("fid_cond_scr_div_code must be '20168'.")
if fid_input_iscd not in ["0000", "0001", "1001", "2001"]:
logger.error("fid_input_iscd must be one of ['0000', '0001', '1001', '2001'].")
raise ValueError("fid_input_iscd must be one of ['0000', '0001', '1001', '2001'].")
if fid_div_cls_code not in ["0", "1", "2"]:
logger.error("fid_div_cls_code must be one of ['0', '1', '2'].")
raise ValueError("fid_div_cls_code must be one of ['0', '1', '2'].")
if not fid_trgt_cls_code:
logger.error("fid_trgt_cls_code is required. (e.g. '0')")
raise ValueError("fid_trgt_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 = "FHPST01680000"
params = {
"fid_trgt_exls_cls_code": fid_trgt_exls_cls_code,
"fid_cond_mrkt_div_code": fid_cond_mrkt_div_code,
"fid_cond_scr_div_code": fid_cond_scr_div_code,
"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_vol_cnt": fid_vol_cnt,
"fid_trgt_cls_code": fid_trgt_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'):
current_data = pd.DataFrame(res.getBody().output)
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 volume_power(
fid_trgt_exls_cls_code,
fid_cond_mrkt_div_code,
fid_cond_scr_div_code,
fid_input_iscd,
fid_div_cls_code,
fid_input_price_1,
fid_input_price_2,
fid_vol_cnt,
fid_trgt_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()