# [장내채권] 주문/계좌 - 장내채권 잔고조회
# Generated by KIS API Generator (Single API Mode)
# -*- coding: utf-8 -*-
"""
Created on 2025-06-20

"""

import logging
import time
from typing import Optional
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__)

##############################################################################################
# [장내채권] 주문/계좌 > 장내채권 잔고조회 [국내주식-198]
##############################################################################################

# 상수 정의
API_URL = "/uapi/domestic-bond/v1/trading/inquire-balance"

def inquire_balance(
        cano: str,  # 종합계좌번호
        acnt_prdt_cd: str,  # 계좌상품코드
        inqr_cndt: str,  # 조회조건
        pdno: str,  # 상품번호
        buy_dt: str,  # 매수일자
        FK200: str = "",  # 연속조회검색조건200
        NK200: str = "",  # 연속조회키200
        tr_cont: str = "",  # 연속 거래 여부
        dataframe: Optional[pd.DataFrame] = None,  # 누적 데이터프레임
        depth: int = 0,  # 현재 재귀 깊이
        max_depth: int = 10  # 최대 재귀 깊이
) -> Optional[pd.DataFrame]:
    """
    [장내채권] 주문/계좌 
    장내채권 잔고조회[국내주식-198]
    장내채권 잔고조회 API를 호출하여 DataFrame으로 반환합니다.
    
    Args:
        cano (str): 종합계좌번호
        acnt_prdt_cd (str): 계좌상품코드
        inqr_cndt (str): 조회조건 (00: 전체, 01: 상품번호단위)
        pdno (str): 상품번호 (공백 허용)
        buy_dt (str): 매수일자 (공백 허용)
        FK200 (str): 연속조회검색조건200
        NK200 (str): 연속조회키200
        tr_cont (str): 연속 거래 여부 (기본값: "")
        dataframe (Optional[pd.DataFrame]): 누적 데이터프레임
        depth (int): 현재 재귀 깊이
        max_depth (int): 최대 재귀 깊이 (기본값: 10)
        
    Returns:
        Optional[pd.DataFrame]: 장내채권 잔고조회 데이터
        
    Example:
        >>> df = inquire_balance(
        ...     cano=trenv.my_acct,
        ...     acnt_prdt_cd=trenv.my_prod,
        ...     inqr_cndt='00',
        ...     pdno='',
        ...     buy_dt='',
        ... )
        >>> print(df)
    """
    # 로깅 설정
    logger = logging.getLogger(__name__)

    # 필수 파라미터 검증
    if not cano:
        logger.error("cano is required. (e.g. '12345678')")
        raise ValueError("cano is required. (e.g. '12345678')")

    if not acnt_prdt_cd:
        logger.error("acnt_prdt_cd is required. (e.g. '01')")
        raise ValueError("acnt_prdt_cd is required. (e.g. '01')")

    if not inqr_cndt:
        logger.error("inqr_cndt is required. (e.g. '00')")
        raise ValueError("inqr_cndt is required. (e.g. '00')")

    # 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 = "CTSC8407R"

    params = {
        "CANO": cano,
        "ACNT_PRDT_CD": acnt_prdt_cd,
        "INQR_CNDT": inqr_cndt,
        "PDNO": pdno,
        "BUY_DT": buy_dt,
        "CTX_AREA_FK200": FK200,
        "CTX_AREA_NK200": NK200,
    }

    # API 호출
    res = ka._url_fetch(API_URL, tr_id, tr_cont, params)

    if res.isOK():
        if hasattr(res.getBody(), 'output'):
            output_data = res.getBody().output
            if not isinstance(output_data, list):
                output_data = [output_data]
            current_data = pd.DataFrame(output_data)
        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
        NK200 = res.getBody().ctx_area_nk200
        FK200 = res.getBody().ctx_area_fk200

        if tr_cont == "M":
            logger.info("Calling next page...")
            ka.smart_sleep()
            return inquire_balance(
                cano,
                acnt_prdt_cd,
                inqr_cndt,
                pdno,
                buy_dt,
                FK200,
                NK200,
                "N", dataframe, depth + 1, max_depth
            )
        else:
            logger.info("Data fetch complete.")
            return dataframe
    else:
        logger.error("API call failed: %s - %s", res.getErrorCode(), res.getErrorMessage())
        res.printError(API_URL)
        return pd.DataFrame()