297 lines
12 KiB
Python
297 lines
12 KiB
Python
from binance.client import Client
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from binance.exceptions import BinanceAPIException, BinanceOrderException
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import pandas as pd
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import time
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import logging
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from datetime import datetime, timedelta
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from typing import List, Dict, Optional
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import requests
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class BinanceDataFetcher:
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def __init__(self, api_key=None, secret=None):
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"""初始化Binance数据获取器"""
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try:
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# 如果没有提供API密钥，使用公共客户端
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if api_key and secret:
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self.client = Client(api_key, secret)
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else:
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self.client = Client() # 公共客户端，只能访问市场数据
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# 测试连接
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self.client.ping()
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print("Binance API连接成功")
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except Exception as e:
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logging.error(f"Binance API初始化失败: {e}")
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print(f"Binance API初始化失败: {e}")
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raise
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def get_top_usdt_pairs(self, limit=100) -> List[str]:
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"""获取交易量最大的USDT交易对，排除稳定币"""
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try:
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print(f"正在获取前{limit}个USDT交易对...")
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# 定义需要排除的稳定币
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stable_coins = {
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'USDCUSDT', 'BUSDUSDT', 'TUSDUSDT', 'PAXUSDT', 'DAIUSDT',
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'FDUSDUSDT', 'USTCUSDT', 'SUSDUSDT', 'GUSDUSDT', 'USDPUSDT'
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}
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# 获取24小时ticker统计
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tickers = self.client.get_ticker()
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print(f"获取到{len(tickers)}个交易对")
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usdt_pairs = []
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for ticker in tickers:
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symbol = ticker['symbol']
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if (symbol.endswith('USDT') and
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float(ticker['quoteVolume']) > 2000 * 10000 and
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symbol not in stable_coins):
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usdt_pairs.append({
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'symbol': symbol,
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'volume': float(ticker['quoteVolume']),
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'price': float(ticker['lastPrice'])
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})
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# 按交易量排序
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usdt_pairs.sort(key=lambda x: x['volume'], reverse=True)
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top_pairs = [pair['symbol'] for pair in usdt_pairs[:limit]]
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logging.info(f"获取到{len(top_pairs)}个USDT交易对(已排除稳定币)")
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print(f"成功获取{len(top_pairs)}个USDT交易对(已排除稳定币)")
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return top_pairs
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except Exception as e:
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logging.error(f"获取交易对失败: {e}")
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print(f"获取交易对失败: {e}")
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return []
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def _convert_timeframe(self, timeframe: str) -> str:
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"""转换时间周期格式"""
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timeframe_mapping = {
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'1m': Client.KLINE_INTERVAL_1MINUTE,
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'5m': Client.KLINE_INTERVAL_5MINUTE,
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'15m': Client.KLINE_INTERVAL_15MINUTE,
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'30m': Client.KLINE_INTERVAL_30MINUTE,
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'1h': Client.KLINE_INTERVAL_1HOUR,
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'4h': Client.KLINE_INTERVAL_4HOUR,
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'1d': Client.KLINE_INTERVAL_1DAY,
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'3d': Client.KLINE_INTERVAL_3DAY,
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'1w': Client.KLINE_INTERVAL_1WEEK
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}
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return timeframe_mapping.get(timeframe, Client.KLINE_INTERVAL_4HOUR)
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def fetch_ohlcv_data(self, symbol: str, timeframe: str, limit: int = 500) -> pd.DataFrame:
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"""获取K线数据"""
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try:
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interval = self._convert_timeframe(timeframe)
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klines = self.client.get_klines(
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symbol=symbol,
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interval=interval,
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limit=limit
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)
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# 转换为DataFrame
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df = pd.DataFrame(klines, columns=[
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'timestamp', 'open', 'high', 'low', 'close', 'volume',
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'close_time', 'quote_asset_volume', 'number_of_trades',
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'taker_buy_base_asset_volume', 'taker_buy_quote_asset_volume', 'ignore'
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])
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# 数据类型转换
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df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
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for col in ['open', 'high', 'low', 'close', 'volume']:
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df[col] = pd.to_numeric(df[col])
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# 设置索引
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df.set_index('timestamp', inplace=True)
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# 只保留需要的列
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df = df[['open', 'high', 'low', 'close', 'volume']]
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return df
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except BinanceAPIException as e:
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logging.error(f"获取{symbol} {timeframe}数据失败: {e}")
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print(f"获取{symbol} {timeframe}数据失败: {e}")
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return pd.DataFrame()
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except Exception as e:
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logging.error(f"获取{symbol} {timeframe}数据时发生未知错误: {e}")
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return pd.DataFrame()
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def get_multi_timeframe_data(self, symbol: str, timeframes: List[str] = None) -> Dict[str, pd.DataFrame]:
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"""获取多时间周期数据"""
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if timeframes is None:
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timeframes = ['4h', '1h', '15m']
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data = {}
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for tf in timeframes:
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df = self.fetch_ohlcv_data(symbol, tf)
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if not df.empty:
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data[tf] = df
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time.sleep(0.1) # 避免频率限制
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return data
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def get_current_price(self, symbol: str) -> Optional[float]:
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"""获取当前价格"""
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try:
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ticker = self.client.get_symbol_ticker(symbol=symbol)
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return float(ticker['price'])
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except Exception as e:
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logging.error(f"获取{symbol}当前价格失败: {e}")
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return None
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def get_24h_stats(self, symbol: str) -> Dict:
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"""获取24小时统计数据"""
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try:
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ticker = self.client.get_ticker(symbol=symbol)
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return {
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'price_change_percent': float(ticker['priceChangePercent']),
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'volume': float(ticker['volume']),
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'quote_volume': float(ticker['quoteVolume']),
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'high_24h': float(ticker['highPrice']),
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'low_24h': float(ticker['lowPrice'])
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}
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except Exception as e:
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logging.error(f"获取{symbol} 24h统计数据失败: {e}")
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return {}
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def batch_fetch_data(self, symbols: List[str], timeframes: List[str] = None) -> Dict[str, Dict]:
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"""批量获取多个币种的多时间周期数据"""
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if timeframes is None:
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timeframes = ['4h', '1h', '15m']
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all_data = {}
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total = len(symbols)
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for i, symbol in enumerate(symbols):
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try:
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logging.info(f"正在获取 {symbol} 数据 ({i+1}/{total})")
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print(f"正在获取 {symbol} 数据 ({i+1}/{total})")
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# 获取多时间周期K线数据
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timeframe_data = self.get_multi_timeframe_data(symbol, timeframes)
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if timeframe_data:
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# 获取24小时统计数据
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stats = self.get_24h_stats(symbol)
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# 组织数据结构以匹配分析器期望
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all_data[symbol] = {
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'timeframes': timeframe_data,
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'volume_24h_usd': stats.get('quote_volume', 0), # 这是24小时USDT交易量
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'stats': stats
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}
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logging.info(f"{symbol} 24小时交易量: ${stats.get('quote_volume', 0):,.0f}")
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# 控制请求频率，避免被限制
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time.sleep(0.2)
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except Exception as e:
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logging.error(f"获取{symbol}数据时出错: {e}")
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print(f"获取{symbol}数据时出错: {e}")
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continue
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logging.info(f"成功获取{len(all_data)}个币种的数据")
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print(f"成功获取{len(all_data)}个币种的数据")
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return all_data
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def get_top_market_cap_usdt_pairs(self, limit=100) -> List[str]:
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"""获取市值排名前N的USDT交易对"""
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try:
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print(f"正在获取市值排名前{limit}个币种...")
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# 从CoinGecko获取市值排名数据
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url = "https://api.coingecko.com/api/v3/coins/markets"
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params = {
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'vs_currency': 'usd',
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'order': 'market_cap_desc',
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'per_page': min(limit * 2, 250), # 获取更多数据以确保有足够的匹配
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'page': 1,
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'sparkline': 'false'
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}
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response = requests.get(url, params=params, timeout=10)
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if response.status_code != 200:
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print(f"CoinGecko API请求失败: {response.status_code}")
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# 回退到按交易量获取
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return self.get_top_usdt_pairs(limit)
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market_data = response.json()
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print(f"从CoinGecko获取到{len(market_data)}个币种的市值数据")
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# 获取Binance支持的所有USDT交易对
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binance_tickers = self.client.get_ticker()
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binance_usdt_symbols = set()
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# 排除稳定币
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stable_coins = {
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'USDCUSDT', 'BUSDUSDT', 'TUSDUSDT', 'PAXUSDT', 'DAIUSDT',
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'FDUSDUSDT', 'USTCUSDT', 'SUSDUSDT', 'GUSDUSDT', 'USDPUSDT'
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}
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for ticker in binance_tickers:
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symbol = ticker['symbol']
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if (symbol.endswith('USDT') and
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float(ticker['quoteVolume']) > 1000000 and # 最低交易量要求
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symbol not in stable_coins):
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binance_usdt_symbols.add(symbol)
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print(f"Binance支持的USDT交易对: {len(binance_usdt_symbols)}个")
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# 匹配市值排名和Binance交易对
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matched_pairs = []
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for coin in market_data:
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# 尝试不同的符号格式匹配
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symbol_variants = [
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f"{coin['symbol'].upper()}USDT",
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f"{coin['id'].upper().replace('-', '')}USDT"
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]
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for variant in symbol_variants:
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if variant in binance_usdt_symbols:
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matched_pairs.append({
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'symbol': variant,
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'market_cap_rank': coin['market_cap_rank'],
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'market_cap': coin['market_cap'],
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'name': coin['name']
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})
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print(f"匹配成功: {coin['name']}({coin['symbol']}) -> {variant} (排名#{coin['market_cap_rank']})")
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break
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if len(matched_pairs) >= limit:
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break
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# 按市值排名排序
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matched_pairs.sort(key=lambda x: x['market_cap_rank'] if x['market_cap_rank'] else 999999)
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top_pairs = [pair['symbol'] for pair in matched_pairs[:limit]]
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print(f"成功匹配{len(top_pairs)}个市值排名前{limit}的USDT交易对")
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# 如果匹配数量不足，用交易量排序的方式补充
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if len(top_pairs) < limit:
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print(f"市值匹配数量不足({len(top_pairs)}/{limit})，用交易量排序补充...")
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volume_pairs = self.get_top_usdt_pairs(limit)
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# 补充未包含的交易对
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for pair in volume_pairs:
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if pair not in top_pairs and len(top_pairs) < limit:
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top_pairs.append(pair)
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return top_pairs[:limit]
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except Exception as e:
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logging.error(f"获取市值排名失败: {e}")
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print(f"获取市值排名失败: {e}，回退到按交易量获取")
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# 出错时回退到原有的交易量排序方式
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return self.get_top_usdt_pairs(limit)
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def get_exchange_info(self):
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"""获取交易所信息"""
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try:
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return self.client.get_exchange_info()
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except Exception as e:
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logging.error(f"获取交易所信息失败: {e}")
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return None |