# -*- coding: utf-8 -*-
"""
Created on 2025-07-01

"""

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__)

##############################################################################################
# [해외선물옵션] 기본시세 > 해외옵션 호가 [해외선물-033]
##############################################################################################

# API 정보
API_URL = "/uapi/overseas-futureoption/v1/quotations/opt-asking-price"

def opt_asking_price(
    srs_cd: str,  # 종목명
    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]:
    """
    [해외선물옵션] 기본시세 
    해외옵션 호가[해외선물-033]
    해외옵션 호가 API를 호출하여 DataFrame으로 반환합니다.
    
    Args:
        srs_cd (str): 종목명 (예: 'OTXM24 C22000')
        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]: 해외옵션 호가 데이터
        
    Example:
        >>> df1, df2 = opt_asking_price(srs_cd="OTXM24 C22000")
        >>> print(df1)
        >>> print(df2)
    """
    # [필수 파라미터 검증]
    if not srs_cd:
        logger.error("srs_cd is required. (e.g. 'OTXM24 C22000')")
        raise ValueError("srs_cd is required. (e.g. 'OTXM24 C22000')")

    # 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 = "HHDFO86000000"

    params = {
        "SRS_CD": srs_cd,
    }

    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:
                if isinstance(output_data, list):
                    current_data1 = pd.DataFrame(output_data)
                else:
                    current_data1 = pd.DataFrame([output_data])
                
                if dataframe1 is not None:
                    dataframe1 = pd.concat([dataframe1, current_data1], ignore_index=True)
                else:
                    dataframe1 = current_data1
            else:
                if dataframe1 is None:
                    dataframe1 = pd.DataFrame()
        else:
            if dataframe1 is None:
                dataframe1 = pd.DataFrame()
        
        # output2 처리
        if hasattr(res.getBody(), 'output2'):
            output_data = res.getBody().output2
            if output_data:
                if isinstance(output_data, list):
                    current_data2 = pd.DataFrame(output_data)
                else:
                    current_data2 = pd.DataFrame([output_data])
                
                if dataframe2 is not None:
                    dataframe2 = pd.concat([dataframe2, current_data2], ignore_index=True)
                else:
                    dataframe2 = current_data2
            else:
                if dataframe2 is None:
                    dataframe2 = pd.DataFrame()
        else:
            if dataframe2 is None:
                dataframe2 = pd.DataFrame()
        
        tr_cont = res.getHeader().tr_cont
        
        if tr_cont in ["M", "F"]:
            logger.info("Calling next page...")
            ka.smart_sleep()
            return opt_asking_price(
                srs_cd,
                dataframe1, dataframe2, tr_cont, 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()
