# !/usr/bin/env python
# -*- coding:utf-8 -*-
"""
Date: 2026/1/13 15:00
Desc: 雪球-行情中心-个股
https://xueqiu.com/S/SH513520
"""

import re
from datetime import datetime

import pandas as pd
import requests


def _convert_timestamp(timestamp_ms: int) -> str:
    """
    时间戳转换为字符串时间
    :param timestamp_ms: 时间戳
    :type timestamp_ms: int
    :return: 字符串
    :rtype: str
    """
    timestamp_s = timestamp_ms / 1000
    datetime_obj = datetime.fromtimestamp(timestamp_s)
    return datetime_obj.strftime("%Y-%m-%d %H:%M:%S")


def stock_individual_spot_xq(
    symbol: str = "SH600000",
    token: str = None,
    timeout: float = None,
) -> pd.DataFrame:
    """
    雪球-行情中心-个股
    https://xueqiu.com/S/SH600000
    :param symbol: 证券代码，可以是 A 股代码，A 股场内基金代码，A 股指数，美股代码, 美股指数
    :type symbol: str
    :param token: set xueqiu token
    :type token: str
    :param timeout: choice of None or a positive float number
    :type timeout: float
    :return: 证券最新行情
    :rtype: pandas.DataFrame
    """
    from akshare.stock.cons import xq_a_token
    session = requests.Session()
    xq_a_token = token or xq_a_token
    headers = {
        "cookie": f"xq_a_token={xq_a_token};",
        "User-Agent": "Mozilla/5.0 (iPhone; CPU iPhone OS 16_6 like Mac OS X) AppleWebKit/605.1.15 "
        "(KHTML, like Gecko) Version/16.6 Mobile/15E148 Safari/604.1",
    }
    session.get(url="https://xueqiu.com", headers=headers)
    url = f"https://stock.xueqiu.com/v5/stock/quote.json?symbol={symbol}&extend=detail"
    r = session.get(url, headers=headers, timeout=timeout)
    column_name_map = {
        "acc_unit_nav": "累计净值",
        "amount": "成交额",
        "amplitude": "振幅",
        "avg_price": "均价",
        "chg": "涨跌",
        "currency": "货币",
        "current": "现价",
        "current_year_percent": "今年以来涨幅",
        "dividend": "股息(TTM)",
        "dividend_yield": "股息率(TTM)",
        "eps": "每股收益",
        "exchange": "交易所",
        "float_market_capital": "流通值",
        "float_shares": "流通股",
        "found_date": "成立日期",
        "goodwill_in_net_assets": "净资产中的商誉",
        "high": "最高",
        "high52w": "52周最高",
        "iopv": "参考净值",
        "issue_date": "发行日期",
        "last_close": "昨收",
        "limit_down": "跌停",
        "limit_up": "涨停",
        "lot_size": "最小交易单位",
        "low": "最低",
        "low52w": "52周最低",
        "market_capital": "资产净值/总市值",
        "name": "名称",
        "nav_date": "净值日期",
        "navps": "每股净资产",
        "open": "今开",
        "pb": "市净率",
        "pe_forecast": "市盈率(动)",
        "pe_lyr": "市盈率(静)",
        "pe_ttm": "市盈率(TTM)",
        "percent": "涨幅",
        "premium_rate": "溢价率",
        "psr": "市销率",
        "symbol": "代码",
        "total_shares": "基金份额/总股本",
        "turnover_rate": "周转率",
        "unit_nav": "单位净值",
        "volume": "成交量",
        "time": "时间",
    }
    json_data = r.json()
    temp_df = pd.json_normalize(json_data["data"]["quote"])
    temp_df.columns = [
        *map(
            lambda x: column_name_map[x] if x in column_name_map.keys() else x,
            temp_df.columns,
        )  # 由于传入的 symbol 可能是个股，可能是指数，也可能是基金，所以这里取列的最大公约数，没有数据的列内容为 None
    ]
    temp_df = temp_df[
        list(
            filter(
                lambda x: re.search(pattern="[\u4e00-\u9fa5]", string=x),
                temp_df.columns,
            )  # 过滤 temp_df，留下包含汉字的列
        )
    ]
    temp_df = temp_df.T.reset_index()
    temp_df.columns = ["item", "value"]
    temp_df.loc[temp_df["item"] == "时间", "value"] = temp_df.loc[
        temp_df["item"] == "时间", "value"
    ].apply(lambda x: _convert_timestamp(int(x)) if x and not pd.isna(x) else None)
    temp_df.loc[temp_df["item"] == "发行日期", "value"] = temp_df.loc[
        temp_df["item"] == "发行日期", "value"
    ].apply(lambda x: _convert_timestamp(int(x)) if x and not pd.isna(x) else None)
    return temp_df


if __name__ == "__main__":
    stock_individual_spot_xq_df = stock_individual_spot_xq(symbol="BJ430139")
    print(stock_individual_spot_xq_df)

    stock_individual_spot_xq_df = stock_individual_spot_xq(symbol="SH600000")
    print(stock_individual_spot_xq_df)

    stock_individual_spot_xq_df = stock_individual_spot_xq(symbol="SPY")
    print(stock_individual_spot_xq_df)

    stock_individual_spot_xq_df = stock_individual_spot_xq(symbol=".INX")
    print(stock_individual_spot_xq_df)
