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한국투자증권(API)/examples_llm/domestic_stock/overtime_volume/overtime_volume.py Normal file
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# [국내주식] 순위분석 - 국내주식 시간외거래량순위
# Generated by KIS API Generator (Single API Mode)
# -*- coding: utf-8 -*-
"""
Created on 2025-06-17
"""
import logging
import sys
import time
from typing import Optional, Tuple
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] 국내주식 > 국내주식 시간외거래량순위[국내주식-139]
##############################################################################################
# 상수 정의
API_URL = "/uapi/domestic-stock/v1/ranking/overtime-volume"
def overtime_volume(
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_rank_sort_cls_code: str, # 순위 정렬 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
fid_trgt_exls_cls_code: str, # 대상 제외 구분 코드
dataframe1: Optional[pd.DataFrame] = None, # 누적 데이터프레임 (output1)
dataframe2: Optional[pd.DataFrame] = None, # 누적 데이터프레임 (output2)
tr_cont: str = "",
depth: int = 0,
max_depth: int = 10
) -> Tuple[pd.DataFrame, pd.DataFrame]:
"""
[국내주식] 순위분석
국내주식 시간외거래량순위[국내주식-139]
국내주식 시간외거래량순위 API를 호출하여 DataFrame으로 반환합니다.
Args:
fid_cond_mrkt_div_code (str): 시장구분코드 (J: 주식)
fid_cond_scr_div_code (str): Unique key(20235)
fid_input_iscd (str): 0000(전체), 0001(코스피), 1001(코스닥)
fid_rank_sort_cls_code (str): 0(매수잔량), 1(매도잔량), 2(거래량)
fid_input_price_1 (str): 가격 ~
fid_input_price_2 (str): ~ 가격
fid_vol_cnt (str): 거래량 ~
fid_trgt_cls_code (str): 공백
fid_trgt_exls_cls_code (str): 공백
dataframe1 (Optional[pd.DataFrame]): 누적 데이터프레임 (output1)
dataframe2 (Optional[pd.DataFrame]): 누적 데이터프레임 (output2)
tr_cont (str): 연속 거래 여부
depth (int): 현재 재귀 깊이
max_depth (int): 최대 재귀 깊이 (기본값: 10)
Returns:
Tuple[pd.DataFrame, pd.DataFrame]: 국내주식 시간외거래량순위 데이터
Example:
>>> df1, df2 = overtime_volume(
fid_cond_mrkt_div_code='J',
fid_cond_scr_div_code='20235',
fid_input_iscd='0000',
fid_rank_sort_cls_code='2',
fid_input_price_1='',
fid_input_price_2='',
fid_vol_cnt='',
fid_trgt_cls_code='',
fid_trgt_exls_cls_code=''
)
>>> print(df1)
>>> print(df2)
"""
# 필수 파라미터 검증
if not fid_cond_mrkt_div_code:
logger.error("fid_cond_mrkt_div_code is required. (e.g. 'J')")
raise ValueError("fid_cond_mrkt_div_code is required. (e.g. 'J')")
if not fid_cond_scr_div_code:
logger.error("fid_cond_scr_div_code is required. (e.g. '20235')")
raise ValueError("fid_cond_scr_div_code is required. (e.g. '20235')")
if not fid_input_iscd:
logger.error("fid_input_iscd is required. (e.g. '0000')")
raise ValueError("fid_input_iscd is required. (e.g. '0000')")
if not fid_rank_sort_cls_code:
logger.error("fid_rank_sort_cls_code is required. (e.g. '2')")
raise ValueError("fid_rank_sort_cls_code is required. (e.g. '2')")
# 최대 재귀 깊이 체크
if depth >= max_depth:
logger.warning("Maximum recursion depth (%d) reached. Stopping further requests.", max_depth)
return dataframe1 if dataframe1 is not None else pd.DataFrame(), dataframe2 if dataframe2 is not None else pd.DataFrame()
tr_id = "FHPST02350000"
params = {
"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_RANK_SORT_CLS_CODE": fid_rank_sort_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,
"FID_TRGT_EXLS_CLS_CODE": fid_trgt_exls_cls_code,
}
res = ka._url_fetch(API_URL, tr_id, tr_cont, params)
if res.isOK():
# output1 처리
if hasattr(res.getBody(), 'output1'):
output_data = res.getBody().output1
if output_data:
current_data1 = pd.DataFrame(output_data if isinstance(output_data, list) else [output_data])
dataframe1 = pd.concat([dataframe1, current_data1],
ignore_index=True) if dataframe1 is not None else current_data1
else:
dataframe1 = dataframe1 if dataframe1 is not None else pd.DataFrame()
else:
dataframe1 = dataframe1 if dataframe1 is not None else pd.DataFrame()
# output2 처리
if hasattr(res.getBody(), 'output2'):
output_data = res.getBody().output2
if output_data:
current_data2 = pd.DataFrame(output_data if isinstance(output_data, list) else [output_data])
dataframe2 = pd.concat([dataframe2, current_data2],
ignore_index=True) if dataframe2 is not None else current_data2
else:
dataframe2 = dataframe2 if dataframe2 is not None else pd.DataFrame()
else:
dataframe2 = dataframe2 if dataframe2 is not None else pd.DataFrame()
tr_cont = res.getHeader().tr_cont
if tr_cont in ["M", "F"]:
logger.info("Calling next page...")
ka.smart_sleep()
return overtime_volume(
fid_cond_mrkt_div_code,
fid_cond_scr_div_code,
fid_input_iscd,
fid_rank_sort_cls_code,
fid_input_price_1,
fid_input_price_2,
fid_vol_cnt,
fid_trgt_cls_code,
fid_trgt_exls_cls_code,
"N", dataframe1, dataframe2, depth + 1, max_depth
)
else:
logger.info("Data fetch complete.")
return dataframe1, dataframe2
else:
logger.error("API call failed: %s - %s", res.getErrorCode(), res.getErrorMessage())
res.printError(API_URL)
return pd.DataFrame(), pd.DataFrame()