"""
Created on 2025-06-17

"""

import logging
import time
from typing import Optional, Tuple
import sys

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] 업종/기타 > 국내업종 구분별전체시세[v1_국내주식-066]
##############################################################################################

# 상수 정의
API_URL = "/uapi/domestic-stock/v1/quotations/inquire-index-category-price"

def inquire_index_category_price(
        fid_cond_mrkt_div_code: str,  # FID 조건 시장 분류 코드
        fid_input_iscd: str,  # FID 입력 종목코드
        fid_cond_scr_div_code: str,  # FID 조건 화면 분류 코드
        fid_mrkt_cls_code: str,  # FID 시장 구분 코드
        fid_blng_cls_code: str,  # FID 소속 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] 업종/기타 
    국내업종 구분별전체시세[v1_국내주식-066]
    국내업종 구분별전체시세 API를 호출하여 DataFrame으로 반환합니다.
    
    Args:
        fid_cond_mrkt_div_code (str): 시장구분코드 (업종 U)
        fid_input_iscd (str): 코스피(0001), 코스닥(1001), 코스피200(2001) ... 포탈 (FAQ : 종목정보 다운로드(국내) - 업종코드 참조)
        fid_cond_scr_div_code (str): Unique key( 20214 )
        fid_mrkt_cls_code (str): 시장구분코드(K:거래소, Q:코스닥, K2:코스피200)
        fid_blng_cls_code (str): 시장구분코드에 따라 아래와 같이 입력 시장구분코드(K:거래소) 0:전업종, 1:기타구분, 2:자본금구분 3:상업별구분 시장구분코드(Q:코스닥) 0:전업종, 1:기타구분, 2:벤처구분 3:일반구분 시장구분코드(K2:코스닥) 0:전업종
        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]: 국내업종 구분별전체시세 데이터
        
    Example:
        >>> df1, df2 = inquire_index_category_price(
        ...     fid_cond_mrkt_div_code='U',
        ...     fid_input_iscd='0001',
        ...     fid_cond_scr_div_code='20214',
        ...     fid_mrkt_cls_code='K',
        ...     fid_blng_cls_code='0'
        ... )
        >>> print(df1)
        >>> print(df2)
    """
    # 로깅 설정
    logger = logging.getLogger(__name__)

    # 필수 파라미터 검증
    if not fid_cond_mrkt_div_code:
        logger.error("fid_cond_mrkt_div_code is required. (e.g. 'U')")
        raise ValueError("fid_cond_mrkt_div_code is required. (e.g. 'U')")

    if not fid_input_iscd:
        logger.error("fid_input_iscd is required. (e.g. '0001')")
        raise ValueError("fid_input_iscd is required. (e.g. '0001')")

    if not fid_cond_scr_div_code:
        logger.error("fid_cond_scr_div_code is required. (e.g. '20214')")
        raise ValueError("fid_cond_scr_div_code is required. (e.g. '20214')")

    if not fid_mrkt_cls_code:
        logger.error("fid_mrkt_cls_code is required. (e.g. 'K')")
        raise ValueError("fid_mrkt_cls_code is required. (e.g. 'K')")

    if not fid_blng_cls_code:
        logger.error("fid_blng_cls_code is required. (e.g. '0')")
        raise ValueError("fid_blng_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 dataframe1 if dataframe1 is not None else pd.DataFrame(), dataframe2 if dataframe2 is not None else pd.DataFrame()


    tr_id = "FHPUP02140000"

    params = {
        "FID_COND_MRKT_DIV_CODE": fid_cond_mrkt_div_code,
        "FID_INPUT_ISCD": fid_input_iscd,
        "FID_COND_SCR_DIV_CODE": fid_cond_scr_div_code,
        "FID_MRKT_CLS_CODE": fid_mrkt_cls_code,
        "FID_BLNG_CLS_CODE": fid_blng_cls_code,
    }

    # API 호출
    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()

        # 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()

        tr_cont = res.getHeader().tr_cont

        if tr_cont in ["M", "F"]:
            logger.info("Calling next page...")
            ka.smart_sleep()
            return inquire_index_category_price(
                fid_cond_mrkt_div_code,
                fid_input_iscd,
                fid_cond_scr_div_code,
                fid_mrkt_cls_code,
                fid_blng_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()
