"""
Tushare数据服务
封装Tushare API调用
"""
import tushare as ts
import pandas as pd
from typing import Optional, List
from datetime import datetime, timedelta
from app.config import get_settings
from app.utils.logger import logger
from app.utils.validators import normalize_stock_code


class TushareService:
    """Tushare数据服务类"""

    def __init__(self):
        """初始化Tushare服务"""
        settings = get_settings()
        if not settings.tushare_token:
            logger.warning("Tushare token未配置")
            self.pro = None
        else:
            ts.set_token(settings.tushare_token)
            self.pro = ts.pro_api()
            logger.info("Tushare服务初始化成功")

    def get_realtime_quote(self, stock_code: str) -> Optional[dict]:
        """
        获取实时行情

        Args:
            stock_code: 股票代码

        Returns:
            行情数据字典
        """
        if not self.pro:
            logger.error("Tushare服务未初始化")
            return None

        try:
            # 标准化股票代码
            ts_code = normalize_stock_code(stock_code)
            if not ts_code:
                logger.error(f"无效的股票代码: {stock_code}")
                return None

            # 获取最新交易日数据
            df = self.pro.daily(ts_code=ts_code, start_date='', end_date='')

            if df.empty:
                logger.warning(f"未找到股票数据: {ts_code}")
                return None

            # 取最新一条
            latest = df.iloc[0]

            # 获取股票名称
            stock_info = self.pro.stock_basic(ts_code=ts_code, fields='ts_code,name')
            name = stock_info.iloc[0]['name'] if not stock_info.empty else None

            return {
                'ts_code': ts_code,
                'name': name,
                'trade_date': latest['trade_date'],
                'open': float(latest['open']),
                'high': float(latest['high']),
                'low': float(latest['low']),
                'close': float(latest['close']),
                'pre_close': float(latest['pre_close']),
                'change': float(latest['change']),
                'pct_chg': float(latest['pct_chg']),
                'vol': float(latest['vol']),
                'amount': float(latest['amount'])
            }

        except Exception as e:
            logger.error(f"获取实时行情失败: {e}")
            return None

    def get_kline_data(
        self,
        stock_code: str,
        start_date: Optional[str] = None,
        end_date: Optional[str] = None,
        period: str = 'D'
    ) -> Optional[List[dict]]:
        """
        获取K线数据

        Args:
            stock_code: 股票代码
            start_date: 开始日期（YYYYMMDD）
            end_date: 结束日期（YYYYMMDD）
            period: 周期（D=日，W=周，M=月）

        Returns:
            K线数据列表
        """
        if not self.pro:
            logger.error("Tushare服务未初始化")
            return None

        try:
            # 标准化股票代码
            ts_code = normalize_stock_code(stock_code)
            if not ts_code:
                logger.error(f"无效的股票代码: {stock_code}")
                return None

            # 默认获取最近180个交易日（约6个月），确保技术指标计算准确
            # MA60需要至少60个交易日，加上缓冲期，180天可以覆盖约120个交易日
            if not start_date:
                start_date = (datetime.now() - timedelta(days=180)).strftime('%Y%m%d')
            if not end_date:
                end_date = datetime.now().strftime('%Y%m%d')

            logger.info(f"获取K线数据: {stock_code}, 时间范围: {start_date} - {end_date}")

            # 获取日线数据
            if period == 'D':
                df = self.pro.daily(
                    ts_code=ts_code,
                    start_date=start_date,
                    end_date=end_date
                )
            elif period == 'W':
                df = self.pro.weekly(
                    ts_code=ts_code,
                    start_date=start_date,
                    end_date=end_date
                )
            elif period == 'M':
                df = self.pro.monthly(
                    ts_code=ts_code,
                    start_date=start_date,
                    end_date=end_date
                )
            else:
                logger.error(f"不支持的周期: {period}")
                return None

            if df.empty:
                logger.warning(f"未找到K线数据: {ts_code}")
                return None

            # 按日期升序排列
            df = df.sort_values('trade_date')

            # 转换为字典列表
            kline_data = []
            for _, row in df.iterrows():
                kline_data.append({
                    'ts_code': ts_code,
                    'trade_date': row['trade_date'],
                    'open': float(row['open']),
                    'high': float(row['high']),
                    'low': float(row['low']),
                    'close': float(row['close']),
                    'vol': float(row['vol']),
                    'amount': float(row['amount']) if pd.notna(row['amount']) else None
                })

            return kline_data

        except Exception as e:
            logger.error(f"获取K线数据失败: {e}")
            return None

    def get_stock_basic(self, stock_code: str) -> Optional[dict]:
        """
        获取股票基本信息

        Args:
            stock_code: 股票代码

        Returns:
            基本信息字典
        """
        if not self.pro:
            logger.error("Tushare服务未初始化")
            return None

        try:
            ts_code = normalize_stock_code(stock_code)
            if not ts_code:
                return None

            df = self.pro.stock_basic(
                ts_code=ts_code,
                fields='ts_code,symbol,name,area,industry,market,list_date'
            )

            if df.empty:
                return None

            info = df.iloc[0]
            return {
                'ts_code': info['ts_code'],
                'symbol': info['symbol'],
                'name': info['name'],
                'area': info['area'],
                'industry': info['industry'],
                'market': info['market'],
                'list_date': info['list_date']
            }

        except Exception as e:
            logger.error(f"获取股票基本信息失败: {e}")
            return None

    def search_stock(self, keyword: str) -> Optional[List[dict]]:
        """
        搜索股票（通过名称或代码）

        Args:
            keyword: 搜索关键词（股票名称或代码）

        Returns:
            匹配的股票列表
        """
        if not self.pro:
            logger.error("Tushare服务未初始化")
            return None

        try:
            # 获取所有股票列表
            df = self.pro.stock_basic(
                fields='ts_code,symbol,name,area,industry,market,list_date'
            )

            if df.empty:
                return None

            # 搜索匹配的股票
            # 1. 精确匹配代码
            exact_match = df[df['symbol'] == keyword]
            if not exact_match.empty:
                return [exact_match.iloc[0].to_dict()]

            # 2. 模糊匹配名称
            name_match = df[df['name'].str.contains(keyword, na=False)]
            if not name_match.empty:
                results = []
                for _, row in name_match.iterrows():
                    results.append(row.to_dict())
                return results[:5]  # 最多返回5个结果

            # 3. 模糊匹配代码
            code_match = df[df['symbol'].str.contains(keyword, na=False)]
            if not code_match.empty:
                results = []
                for _, row in code_match.iterrows():
                    results.append(row.to_dict())
                return results[:5]

            return None

        except Exception as e:
            logger.error(f"搜索股票失败: {e}")
            return None


# 创建全局实例
tushare_service = TushareService()