"""东方财富 CHOICE API 所属指数抓取工具。
- 输入: 股票代码列表 (如 ['603233.SH'])
- 输出: pandas DataFrame (指数分类 / 纳入指数统计 / 指数成分权重)
- 不需要登录, 不需要 cookie, 无文件落盘
"""
from __future__ import annotations

import pandas as pd

from utils._emchoice import fetch_report


def _fetch_one(secucode: str, params: dict[str, str]) -> pd.DataFrame:
    """按给定参数拉一只股票的数据."""
    rows = fetch_report(params)
    df = pd.DataFrame(rows)
    if not df.empty:
        df["SECUCODE"] = secucode
    return df


def _concat(frames: list[pd.DataFrame]) -> pd.DataFrame:
    if not frames:
        return pd.DataFrame()
    return pd.concat(frames, ignore_index=True)


# ---------------------------------------------------------------- 指数分类

def _build_classif_params(secucode: str) -> dict[str, str]:
    """构造 RPT_HSF9_BELONGINDEX_CLASSIF 查询参数 (股票所属的指数分类)."""
    return {
        "reportName": "RPT_HSF9_BELONGINDEX_CLASSIF",
        "columns": "INDEX_CLASSIF_CODE,INDEX_CLASSIF",
        "quoteColumns": "",
        "filter": f'(SECUCODE="{secucode}")(STR_TYPE="1")',
        "distinct": "INDEX_CLASSIF_CODE,INDEX_CLASSIF",
        "pageNumber": "",
        "pageSize": "",
        "source": "CHOICE",
        "client": "SW",
    }


def get_index_classif(secucodes: list[str]) -> pd.DataFrame:
    """抓取指定股票所属的指数分类列表."""
    codes = [code.strip() for code in secucodes if code.strip()]
    if not codes:
        return pd.DataFrame()

    frames = [_fetch_one(code, _build_classif_params(code)) for code in codes]
    return _concat([df for df in frames if not df.empty])


# ---------------------------------------------------------------- 纳入指数统计

def _build_belong_index_params(secucode: str) -> dict[str, str]:
    """构造 RPT_CUSTOM_HSF9_BELONG_INDEX 查询参数 (纳入指数数量统计)."""
    return {
        "reportName": "RPT_CUSTOM_HSF9_BELONG_INDEX",
        "filter": f'(SECUCODE="{secucode}")',
        "source": "CHOICE",
        "client": "SW",
    }


def get_belong_index(secucodes: list[str]) -> pd.DataFrame:
    """抓取指定股票纳入指数的统计 (指数/基金数量)."""
    codes = [code.strip() for code in secucodes if code.strip()]
    if not codes:
        return pd.DataFrame()

    frames = [_fetch_one(code, _build_belong_index_params(code)) for code in codes]
    return _concat([df for df in frames if not df.empty])


# ---------------------------------------------------------------- 指数成分权重

# 只保留主要指数分类 (剔除行业/风格类), 沿用 docs/api_docs.md 抓包值
_INDEX_CLASSIF_LIKE = (
    '(INDEX_CLASSIF_CODE like "%001001%")(|INDEX_CLASSIF_CODE like "%001002%")'
    '(|INDEX_CLASSIF_CODE like "%001003%")(|INDEX_CLASSIF_CODE like "%001004%")'
    '(|INDEX_CLASSIF_CODE like "%001005%")(|INDEX_CLASSIF_CODE like "%001007%")'
    '(|INDEX_CLASSIF_CODE like "%001009%")(|INDEX_CLASSIF_CODE like "%001010%")'
    '(|INDEX_CLASSIF_CODE like "%001011%")(|INDEX_CLASSIF_CODE like "%001017%")'
    '(|INDEX_CLASSIF_CODE like "%001020%")(|INDEX_CLASSIF_CODE like "%001022%")'
    '(|INDEX_CLASSIF_CODE like "%001025%")(|INDEX_CLASSIF_CODE like "%001030%")'
    '(|INDEX_CLASSIF_CODE like "%001006%")(|INDEX_CLASSIF_CODE like "%001024%")'
    '(|INDEX_CLASSIF_CODE like "%013003%")(|INDEX_CLASSIF_CODE like "%014%")'
)


def _build_membership_params(secucode: str) -> dict[str, str]:
    """构造 RPT_HSF9_BELONG_INDEX 查询参数 (指数成分及权重)."""
    return {
        "reportName": "RPT_HSF9_BELONG_INDEX",
        "columns": (
            "INDEX_CODE,INDEX_INNER_CODE,TRADE_DATE,SECUCODE,SECURITY_CODE,"
            "SECURITY_NAME_ABBR,INCLUDE_DATE,MAKER_NAME,INDEX_NAME_ABBR,"
            "SECURITY_INNER_CODE,INDEX_CLASSIF_CODE,INDEX_CLASSIF,WEIGHT,NUM,"
            "TOTAL_SCALE,WEIGHT_DATE,CURRENCY"
        ),
        "filter": f'(SECUCODE="{secucode}")({_INDEX_CLASSIF_LIKE})',
        "sortColumns": "NUM,INDEX_CODE",
        "sortTypes": "-1,1",
        "pageNumber": "1",
        "pageSize": "50",
        "source": "CHOICE",
        "client": "SW",
    }


def get_index_membership(secucodes: list[str]) -> pd.DataFrame:
    """抓取指定股票所属的指数成分及权重."""
    codes = [code.strip() for code in secucodes if code.strip()]
    if not codes:
        return pd.DataFrame()

    frames = [_fetch_one(code, _build_membership_params(code)) for code in codes]
    return _concat([df for df in frames if not df.empty])