"""
美股数据源
使用 yfinance 和 finnhub 获取数据
"""
from typing import Dict, List, Any, Optional
from datetime import datetime, timedelta

import yfinance as yf

from app.data_sources.base import BaseDataSource
from app.utils.logger import get_logger
from app.config import APIKeys, YFinanceConfig

logger = get_logger(__name__)


class USStockDataSource(BaseDataSource):
    """美股数据源"""
    
    name = "USStock/yfinance"
    
    # yfinance 时间周期映射
    INTERVAL_MAP = {
        '1m': '1m',
        '5m': '5m',
        '15m': '15m',
        '30m': '30m',
        '1H': '1h',
        '4H': '4h',
        '1D': '1d',
        '1W': '1wk'
    }
    
    # 不同周期获取数据的天数范围
    DAYS_MAP = {
        '1m': lambda limit: min(7, max(1, (limit // 390) + 2)),
        '5m': lambda limit: min(60, max(1, (limit // 78) + 2)),
        '15m': lambda limit: min(60, max(1, (limit // 26) + 2)),
        '30m': lambda limit: min(60, max(1, (limit // 13) + 2)),
        '1H': lambda limit: min(730, max(1, (limit // 24) + 2)),
        '4H': lambda limit: min(730, max(1, (limit // 6) + 2)),
        '1D': lambda limit: min(3650, limit + 1),
        '1W': lambda limit: min(3650, (limit * 7) + 7)
    }
    
    def __init__(self):
        # 初始化 finnhub 作为备选
        self.finnhub_client = None
        try:
            import finnhub
            if APIKeys.is_configured('FINNHUB_API_KEY'):
                self.finnhub_client = finnhub.Client(api_key=APIKeys.FINNHUB_API_KEY)
                logger.info("Finnhub client initialized")
        except Exception as e:
            logger.warning(f"Finnhub init failed: {e}")
    
    def get_kline(
        self,
        symbol: str,
        timeframe: str,
        limit: int,
        before_time: Optional[int] = None
    ) -> List[Dict[str, Any]]:
        """获取美股K线数据"""
        klines = []
        
        try:
            interval = self.INTERVAL_MAP.get(timeframe, '1d')
            days_func = self.DAYS_MAP.get(timeframe, lambda x: x + 1)
            days = days_func(limit)
            
            # 计算日期范围
            if before_time:
                end_date = datetime.fromtimestamp(before_time)
                start_date = end_date - timedelta(days=days)
            else:
                end_date = datetime.now()
                start_date = end_date - timedelta(days=days)
            
            # logger.info(f"使用 yfinance 获取 {symbol}, 周期: {interval}, 日期: {start_date.date()} ~ {end_date.date()}")
            
            # 尝试 yfinance
            df = self._fetch_yfinance(symbol, interval, start_date, end_date)
            
            if df is None or df.empty:
                # 尝试 finnhub
                if self.finnhub_client and timeframe == '1D':
                    klines = self._fetch_finnhub(symbol, start_date, end_date, limit)
                    if klines:
                        return klines
            else:
                klines = self._convert_dataframe(df, limit)
            
            # 过滤和限制
            klines = self.filter_and_limit(klines, limit, before_time)
            
            # 记录结果
            self.log_result(symbol, klines, timeframe)
            
        except Exception as e:
            logger.error(f"Failed to fetch US stock K-lines {symbol}: {str(e)}")
            import traceback
            logger.error(traceback.format_exc())
        
        return klines
    
    def _fetch_yfinance(self, symbol: str, interval: str, start_date: datetime, end_date: datetime):
        """使用 yfinance 获取数据"""
        try:
            ticker = yf.Ticker(symbol)
            df = ticker.history(
                start=start_date.strftime('%Y-%m-%d'),
                end=end_date.strftime('%Y-%m-%d'),
                interval=interval
            )
            # logger.info(f"yfinance 返回 {len(df) if df is not None and not df.empty else 0} 条数据")
            return df
        except Exception as e:
            logger.warning(f"yfinance fetch failed: {e}")
            return None
    
    def _fetch_finnhub(
        self,
        symbol: str,
        start_date: datetime,
        end_date: datetime,
        limit: int
    ) -> List[Dict[str, Any]]:
        """使用 finnhub 获取日线数据"""
        klines = []
        try:
            start_ts = int(start_date.timestamp())
            end_ts = int(end_date.timestamp())
            
            # logger.info(f"使用 Finnhub 获取 {symbol} 日线数据")
            candles = self.finnhub_client.stock_candles(symbol, 'D', start_ts, end_ts)
            
            if candles and candles.get('s') == 'ok':
                for i in range(len(candles['t'])):
                    klines.append(self.format_kline(
                        timestamp=candles['t'][i],
                        open_price=candles['o'][i],
                        high=candles['h'][i],
                        low=candles['l'][i],
                        close=candles['c'][i],
                        volume=candles['v'][i]
                    ))
                # logger.info(f"Finnhub 返回 {len(klines)} 条数据")
        except Exception as e:
            logger.error(f"Finnhub fetch failed: {e}")
        
        return klines
    
    def _convert_dataframe(self, df, limit: int) -> List[Dict[str, Any]]:
        """转换 DataFrame 为K线列表"""
        klines = []
        df = df.tail(limit).reset_index()
        
        # 确定时间列名（日线是 Date，分钟级是 Datetime）
        time_col = None
        if 'Datetime' in df.columns:
            time_col = 'Datetime'
        elif 'Date' in df.columns:
            time_col = 'Date'
        elif 'index' in df.columns:
            time_col = 'index'
        
        if time_col is None:
            logger.warning(f"Unable to determine time column; available columns: {df.columns.tolist()}")
            return klines
        
        for _, row in df.iterrows():
            try:
                # 处理时间戳
                time_value = row[time_col]
                if hasattr(time_value, 'timestamp'):
                    ts = int(time_value.timestamp())
                else:
                    continue
                
                klines.append(self.format_kline(
                    timestamp=ts,
                    open_price=row['Open'],
                    high=row['High'],
                    low=row['Low'],
                    close=row['Close'],
                    volume=row['Volume']
                ))
            except Exception as e:
                logger.debug(f"Failed to parse row data: {e}")
                continue
        
        return klines