"""东方财富 CHOICE API 杜邦分析抓取工具。
- 输入: 股票代码列表 (如 ['603233.SH'])
- 输出: pandas DataFrame (按报告期的杜邦分析指标)
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"""
from __future__ import annotations

import pandas as pd

from utils._emchoice import fetch_report


_REPORT_NAME = "RPT_HSF9_FINA_DUPONT"
# 列清单沿用 docs/api_docs.md 抓包值
_COLUMNS = (
    "SECUCODE,SECURITY_CODE,SECURITY_NAME_ABBR,ORG_CODE,SECURITY_INNER_CODE,"
    "TRADE_MARKET_CODE,TRADE_MARKET,SECURITY_TYPE,SECURITY_TYPE_CODE,"
    "REPORT_DATE,ROE,NETPROFIT,TOTAL_OPERATE_INCOME,PARENT_NETPROFIT_RATIO,"
    "ASSET_TURNOVER_RATIO,TOTAL_ASSETS,EQUITY_MULTIPLIER,ROE_AVERAGE_PRE,"
    "ROE_DIF,NETPROFIT_TOI,NP_TP,TP_EBIT,EBIT_TOI,STR_YEAR,STR_MONTH,"
    "TOTAL_PROFIT,EBIT,PARENT_NETPROFIT,PRE_TOTAL_ASSETS,AVG_TOTAL_ASSETS,"
    "TOTAL_PARENT_EQUITY,PRETOTAL_PARENT_EQUITY,AVGTOTAL_PARENT_EQUITY,"
    "PARENT_EQUITY_NETMARGIN,IS_NEWEST"
)
# 报告期: 1=一季报, 3=三季报, 5=中报, 6=年报
_REPORT_PERIOD_CODES = '"1","5","3","6","7"'


def _build_params(
    secucode: str,
    start_date: str,
    end_date: str,
) -> dict[str, str]:
    """构造 RPT_HSF9_FINA_DUPONT 查询参数."""
    return {
        "reportName": _REPORT_NAME,
        "columns": _COLUMNS,
        "quoteColumns": "",
        "filter": (
            f'(SECUCODE="{secucode}")'
            f"((REPORT_DATE>='{start_date}')(REPORT_DATE<='{end_date}')"
            f"(STR_MONTH in ({_REPORT_PERIOD_CODES}))(|IS_NEWEST=''1''))"
        ),
        "pageNumber": "1",
        "pageSize": "",
        "sortTypes": "-1",
        "sortColumns": "REPORT_DATE",
        "source": "choice",
        "client": "SW",
    }


def _fetch_one(secucode: str, years: int) -> pd.DataFrame:
    """拉一只股票的杜邦分析指标."""
    today = pd.Timestamp.today()
    start = (today - pd.DateOffset(years=years)).strftime("%Y-%m-%d")
    end = today.strftime("%Y-%m-%d")

    rows = fetch_report(_build_params(secucode, start, end))
    df = pd.DataFrame(rows)
    if not df.empty:
        df["SECUCODE"] = secucode
    return df


def get_dupont(secucodes: list[str], years: int = 3) -> pd.DataFrame:
    """抓取指定股票的杜邦分析指标并按股票合并。"""
    codes = [code.strip() for code in secucodes if code.strip()]
    if not codes:
        return pd.DataFrame()

    frames: list[pd.DataFrame] = []
    for code in codes:
        df = _fetch_one(code, years)
        if not df.empty:
            frames.append(df)

    if not frames:
        return pd.DataFrame()
    return pd.concat(frames, ignore_index=True)