#!/usr/bin/env python
# -*- coding:utf-8 -*-
"""
Date: 2026/5/27 17:05
Desc: 乐估乐股-底部研究-巴菲特指标
https://legulegu.com/stockdata/marketcap-gdp
"""

import pandas as pd
import requests

from akshare.stock_feature.stock_a_indicator import get_token_lg, get_cookie_csrf


def stock_buffett_index_lg() -> pd.DataFrame:
    """
    乐估乐股-底部研究-巴菲特指标
    https://legulegu.com/stockdata/marketcap-gdp
    :return: 巴菲特指标
    :rtype: pandas.DataFrame
    """
    token = get_token_lg()
    url = "https://legulegu.com/api/stockdata/marketcap-gdp/get-marketcap-gdp"
    params = {"token": token}
    r = requests.get(
        url,
        params=params,
        **get_cookie_csrf(url="https://legulegu.com/stockdata/marketcap-gdp"),
    )
    data_json = r.json()
    temp_df = pd.DataFrame(data_json["data"])
    rename_map = {
        "marketCap": "总市值",
        "gdp": "GDP",
        "close": "收盘价",
        "date": "日期",
        "quantileInAllHistory": "总历史分位数",
        "quantileInRecent10Years": "近十年分位数",
    }
    existing_rename = {k: v for k, v in rename_map.items() if k in temp_df.columns}
    temp_df.rename(columns=existing_rename, inplace=True)

    base_cols = ["日期", "收盘价", "总市值", "GDP"]
    optional_cols = ["近十年分位数", "总历史分位数"]
    available_cols = base_cols + [c for c in optional_cols if c in temp_df.columns]
    temp_df = temp_df[available_cols]

    temp_df["日期"] = pd.to_datetime(temp_df["日期"], utc=True).dt.date
    temp_df["收盘价"] = pd.to_numeric(temp_df["收盘价"], errors="coerce")
    temp_df["总市值"] = pd.to_numeric(temp_df["总市值"], errors="coerce")
    temp_df["GDP"] = pd.to_numeric(temp_df["GDP"], errors="coerce")

    for col in optional_cols:
        if col in temp_df.columns:
            temp_df[col] = pd.to_numeric(temp_df[col], errors="coerce")

    return temp_df


if __name__ == "__main__":
    stock_buffett_index_lg_df = stock_buffett_index_lg()
    print(stock_buffett_index_lg_df)