"""
数据获取模块：使用ccxt库拉取数字货币市场数据
"""

import ccxt
import pandas as pd
import numpy as np
from datetime import datetime, timedelta
import time
from typing import List, Dict, Optional, Tuple
import logging

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)


class DataFetcher:
    """数据获取器：负责从交易所获取K线数据"""
    
    def __init__(self, exchange_name: str = 'binance'):
        """
        初始化数据获取器
        
        Args:
            exchange_name: 交易所名称，默认为binance
        """
        self.exchange_name = exchange_name
        self.exchange = self._init_exchange()
        
    def _init_exchange(self) -> ccxt.Exchange:
        """初始化交易所连接"""
        try:
            exchange_class = getattr(ccxt, self.exchange_name)
            exchange = exchange_class({
                'apiKey': '',  # 对于公开数据不需要API密钥
                'secret': '',
                'timeout': 30000,
                'enableRateLimit': True,
            })
            return exchange
        except Exception as e:
            logger.error(f"初始化交易所失败: {e}")
            raise
            
    def fetch_klines(self, 
                    symbol: str, 
                    timeframe: str = '1h', 
                    limit: int = 1000,
                    since: Optional[int] = None) -> pd.DataFrame:
        """
        获取K线数据
        
        Args:
            symbol: 交易对符号，如'BTC/USDT'
            timeframe: 时间周期，如'1h', '4h', '1d'
            limit: 获取的K线数量
            since: 开始时间戳（毫秒）
            
        Returns:
            包含K线数据的DataFrame
        """
        try:
            logger.info(f"正在获取 {symbol} {timeframe} 数据，数量: {limit}")
            
            # 获取原始数据
            ohlcv = self.exchange.fetch_ohlcv(
                symbol=symbol,
                timeframe=timeframe,
                limit=limit,
                since=since
            )
            
            if not ohlcv:
                raise ValueError("未获取到数据")
                
            # 转换为DataFrame
            df = pd.DataFrame(ohlcv, columns=[
                'timestamp', 'open', 'high', 'low', 'close', 'volume'
            ])
            
            # 转换时间戳为datetime
            df['datetime'] = pd.to_datetime(df['timestamp'], unit='ms')
            df.set_index('datetime', inplace=True)
            
            # 确保数据类型正确
            price_columns = ['open', 'high', 'low', 'close']
            df[price_columns] = df[price_columns].astype(float)
            df['volume'] = df['volume'].astype(float)
            
            logger.info(f"成功获取 {len(df)} 条K线数据")
            return df
            
        except Exception as e:
            logger.error(f"获取K线数据失败: {e}")
            raise
            
    def fetch_multiple_timeframes(self, 
                                 symbol: str, 
                                 timeframes: List[str],
                                 limit: int = 1000) -> Dict[str, pd.DataFrame]:
        """
        获取多个时间周期的数据
        
        Args:
            symbol: 交易对符号
            timeframes: 时间周期列表
            limit: 每个周期获取的数量
            
        Returns:
            字典，键为时间周期，值为对应的DataFrame
        """
        result = {}
        
        for timeframe in timeframes:
            try:
                df = self.fetch_klines(symbol, timeframe, limit)
                result[timeframe] = df
                
                # 避免请求过于频繁
                time.sleep(self.exchange.rateLimit / 1000)
                
            except Exception as e:
                logger.error(f"获取 {timeframe} 数据失败: {e}")
                continue
                
        return result
        
    def get_latest_price(self, symbol: str) -> float:
        """
        获取最新价格
        
        Args:
            symbol: 交易对符号
            
        Returns:
            最新价格
        """
        try:
            ticker = self.exchange.fetch_ticker(symbol)
            return float(ticker['last'])
        except Exception as e:
            logger.error(f"获取最新价格失败: {e}")
            raise
            
    def validate_symbol(self, symbol: str) -> bool:
        """
        验证交易对是否有效
        
        Args:
            symbol: 交易对符号
            
        Returns:
            是否有效
        """
        try:
            markets = self.exchange.load_markets()
            return symbol in markets
        except Exception as e:
            logger.error(f"验证交易对失败: {e}")
            return False