Add files to chanlun_1

data/data_fetcher.py

@@ -0,0 +1,160 @@
+"""
+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