mirror of
https://github.com/B-Wear/QuantumEdge.git
synced 2026-08-15 16:08:06 +00:00
B-Wear
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import os
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import sys
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import logging
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import json
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import time
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from datetime import datetime
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from typing import Dict, List
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import pandas as pd
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import ccxt
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from concurrent.futures import ThreadPoolExecutor
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import schedule
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import threading
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import signal
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import queue
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from .trading_strategy import TradingStrategy
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from .config import load_config
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# Configure logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
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handlers=[
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logging.FileHandler('trading_bot.log'),
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logging.StreamHandler(sys.stdout)
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]
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)
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logger = logging.getLogger(__name__)
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class TradingBot:
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def __init__(self, config_path: str):
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# Load configuration
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self.config = load_config(config_path)
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# Initialize exchange
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self.exchange = self._initialize_exchange()
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# Initialize trading strategy
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self.strategy = TradingStrategy(self.config)
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# Initialize state
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self.is_running = False
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self.symbols = self.config['trading']['symbols']
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self.timeframes = self.config['trading']['timeframes']
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self.data_queue = queue.Queue()
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self.signal_queue = queue.Queue()
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# Load previous state if exists
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self._load_state()
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def _initialize_exchange(self) -> ccxt.Exchange:
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"""
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Initialize the cryptocurrency exchange
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"""
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try:
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exchange_class = getattr(ccxt, self.config['exchange']['name'])
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exchange = exchange_class({
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'apiKey': self.config['exchange']['api_key'],
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'secret': self.config['exchange']['api_secret'],
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'enableRateLimit': True
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})
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# Test connection
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exchange.load_markets()
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logger.info(f"Successfully connected to {self.config['exchange']['name']}")
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return exchange
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except Exception as e:
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logger.error(f"Error initializing exchange: {str(e)}")
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raise
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def _load_state(self):
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"""
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Load previous trading state
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"""
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state_file = self.config['trading']['state_file']
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if os.path.exists(state_file):
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try:
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self.strategy.load_state(state_file)
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logger.info("Successfully loaded previous trading state")
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except Exception as e:
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logger.error(f"Error loading state: {str(e)}")
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def _save_state(self):
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"""
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Save current trading state
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"""
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try:
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self.strategy.save_state(self.config['trading']['state_file'])
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logger.info("Successfully saved trading state")
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except Exception as e:
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logger.error(f"Error saving state: {str(e)}")
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def fetch_market_data(self, symbol: str, timeframe: str) -> pd.DataFrame:
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"""
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Fetch market data from exchange
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"""
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try:
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# Get OHLCV data
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ohlcv = self.exchange.fetch_ohlcv(
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symbol,
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timeframe=timeframe,
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limit=self.config['trading']['lookback_periods']
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)
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# Convert to DataFrame
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df = pd.DataFrame(
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ohlcv,
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columns=['timestamp', 'open', 'high', 'low', 'close', 'volume']
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)
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# Convert timestamp to datetime
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df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
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df.set_index('timestamp', inplace=True)
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return df
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except Exception as e:
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logger.error(f"Error fetching market data for {symbol}: {str(e)}")
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return None
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def process_market_data(self):
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"""
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Process market data from queue
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"""
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while self.is_running:
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try:
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# Get data from queue
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data = self.data_queue.get(timeout=1)
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symbol, timeframe, df = data
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# Generate trading signals
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signal = self.strategy.analyze_market(symbol, df)
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if signal:
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# Add signal to queue
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self.signal_queue.put(signal)
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except queue.Empty:
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continue
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except Exception as e:
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logger.error(f"Error processing market data: {str(e)}")
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def execute_signals(self):
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"""
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Execute trading signals from queue
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"""
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while self.is_running:
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try:
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# Get signal from queue
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signal = self.signal_queue.get(timeout=1)
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# Execute trade
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if self.strategy.execute_trade(signal):
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logger.info(f"Executed {signal.action} trade for {signal.symbol}")
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# Update positions with current prices
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current_prices = {
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symbol: self.exchange.fetch_ticker(symbol)['last']
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for symbol in self.symbols
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}
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self.strategy.update_positions(current_prices)
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# Save state after trade
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self._save_state()
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except queue.Empty:
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continue
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except Exception as e:
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logger.error(f"Error executing signals: {str(e)}")
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def update_market_data(self):
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"""
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Update market data for all symbols
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"""
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with ThreadPoolExecutor(max_workers=len(self.symbols)) as executor:
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futures = []
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for symbol in self.symbols:
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for timeframe in self.timeframes:
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future = executor.submit(self.fetch_market_data, symbol, timeframe)
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futures.append((symbol, timeframe, future))
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for symbol, timeframe, future in futures:
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try:
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df = future.result()
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if df is not None:
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self.data_queue.put((symbol, timeframe, df))
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except Exception as e:
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logger.error(f"Error updating market data for {symbol}: {str(e)}")
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def schedule_tasks(self):
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"""
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Schedule periodic tasks
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"""
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# Schedule market data updates
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for timeframe in self.timeframes:
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schedule.every().minute.at(":00").do(self.update_market_data)
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# Schedule state saving
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schedule.every().hour.at(":00").do(self._save_state)
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# Run the scheduler
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while self.is_running:
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schedule.run_pending()
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time.sleep(1)
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def start(self):
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"""
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Start the trading bot
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"""
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try:
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self.is_running = True
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# Start threads
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threads = [
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threading.Thread(target=self.process_market_data),
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threading.Thread(target=self.execute_signals),
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threading.Thread(target=self.schedule_tasks)
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]
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for thread in threads:
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thread.daemon = True
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thread.start()
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# Initial market data update
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self.update_market_data()
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logger.info("Trading bot started successfully")
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# Wait for shutdown signal
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while self.is_running:
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time.sleep(1)
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except Exception as e:
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logger.error(f"Error starting trading bot: {str(e)}")
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self.stop()
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def stop(self):
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"""
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Stop the trading bot
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"""
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try:
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self.is_running = False
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self._save_state()
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logger.info("Trading bot stopped successfully")
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except Exception as e:
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logger.error(f"Error stopping trading bot: {str(e)}")
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def main():
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# Load configuration
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config_path = os.path.join(os.path.dirname(__file__), '..', 'config', 'config.json')
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# Create trading bot
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bot = TradingBot(config_path)
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# Handle shutdown signals
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def signal_handler(signum, frame):
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logger.info("Received shutdown signal")
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bot.stop()
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sys.exit(0)
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signal.signal(signal.SIGINT, signal_handler)
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signal.signal(signal.SIGTERM, signal_handler)
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# Start trading bot
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bot.start()
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if __name__ == "__main__":
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main()
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