import time import threading import schedule from datetime import datetime, timedelta from typing import Dict, List import streamlit as st from monitor_db import monitor_db from stock_data import StockDataFetcher from miniqmt_interface import miniqmt, get_miniqmt_status from notification_service import notification_service class StockMonitorService: """股票监测服务""" def __init__(self): self.fetcher = StockDataFetcher() self.running = False self.thread = None def start_monitoring(self): """启动监测服务""" if self.running: return self.running = True self.thread = threading.Thread(target=self._monitor_loop, daemon=True) self.thread.start() st.success("✅ 监测服务已启动") def stop_monitoring(self): """停止监测服务""" self.running = False if self.thread: self.thread.join(timeout=5) st.info("⏹️ 监测服务已停止") def _monitor_loop(self): """监测循环""" print("监测服务已启动") while self.running: try: self._check_all_stocks() # 根据最小监测间隔决定循环间隔，最少5分钟检查一次 time.sleep(300) # 每5分钟检查一次 except Exception as e: print(f"监测服务错误: {e}") time.sleep(60) # 错误后等待1分钟再重试 def _check_all_stocks(self): """检查所有监测股票""" stocks = monitor_db.get_monitored_stocks() current_time = datetime.now() updated_count = 0 for stock in stocks: # 检查是否需要更新价格 last_checked = stock.get('last_checked') check_interval = stock.get('check_interval', 30) if last_checked: last_checked_dt = datetime.fromisoformat(last_checked) next_check = last_checked_dt + timedelta(minutes=check_interval) if current_time < next_check: # 显示距离下次检查的时间 time_left = (next_check - current_time).total_seconds() / 60 print(f"股票 {stock['symbol']} 距离下次检查还有 {time_left:.1f} 分钟") continue try: print(f"正在更新股票 {stock['symbol']} 的价格...") self._update_stock_price(stock) updated_count += 1 # 在每个股票请求之间增加延迟，避免API限流 if updated_count < len(stocks): time.sleep(3) # 每个股票之间等待3秒 except Exception as e: print(f"❌ 更新股票 {stock['symbol']} 价格失败: {e}") time.sleep(3) # 失败后也等待3秒再继续 if updated_count > 0: print(f"✅ 本轮共更新了 {updated_count} 只股票") def _update_stock_price(self, stock: Dict): """更新股票价格并检查条件""" symbol = stock['symbol'] # 获取最新价格 try: # 使用get_stock_info获取当前价格 stock_info = self.fetcher.get_stock_info(symbol) current_price = stock_info.get('current_price') if current_price and current_price != 'N/A': try: current_price = float(current_price) # 更新数据库（包括更新last_checked时间） monitor_db.update_stock_price(stock['id'], current_price) print(f"✅ {symbol} 当前价格: ¥{current_price}") # 检查触发条件 self._check_trigger_conditions(stock, current_price) except (ValueError, TypeError) as e: print(f"❌ 股票 {symbol} 价格格式错误: {current_price}") # 即使失败也更新last_checked，避免持续重试 monitor_db.update_last_checked(stock['id']) else: print(f"⚠️ 无法获取股票 {symbol} 的当前价格") # 更新last_checked，避免持续重试 monitor_db.update_last_checked(stock['id']) except Exception as e: print(f"❌ 获取股票 {symbol} 数据失败: {e}") # 即使失败也更新last_checked，避免持续重试 try: monitor_db.update_last_checked(stock['id']) except: pass def _check_trigger_conditions(self, stock: Dict, current_price: float): """检查触发条件""" if not stock.get('notification_enabled', True): return entry_range = stock.get('entry_range', {}) take_profit = stock.get('take_profit') stop_loss = stock.get('stop_loss') # 检查进场区间 if entry_range and entry_range.get('min') and entry_range.get('max'): if current_price >= entry_range['min'] and current_price <= entry_range['max']: # 检查是否在最近60分钟内已发送过相同通知，避免重复 if not monitor_db.has_recent_notification(stock['id'], 'entry', minutes=60): message = f"股票 {stock['symbol']} ({stock['name']}) 价格 {current_price} 进入进场区间 [{entry_range['min']}-{entry_range['max']}]" monitor_db.add_notification(stock['id'], 'entry', message) # 立即发送通知（包括邮件） notification_service.send_notifications() # 如果启用量化交易，执行自动交易 if stock.get('quant_enabled', False): self._execute_quant_trade(stock, 'entry', current_price) # 检查止盈 if take_profit and current_price >= take_profit: # 检查是否在最近60分钟内已发送过相同通知，避免重复 if not monitor_db.has_recent_notification(stock['id'], 'take_profit', minutes=60): message = f"股票 {stock['symbol']} ({stock['name']}) 价格 {current_price} 达到止盈位 {take_profit}" monitor_db.add_notification(stock['id'], 'take_profit', message) # 立即发送通知（包括邮件） notification_service.send_notifications() # 如果启用量化交易，执行自动交易 if stock.get('quant_enabled', False): self._execute_quant_trade(stock, 'take_profit', current_price) # 检查止损 if stop_loss and current_price <= stop_loss: # 检查是否在最近60分钟内已发送过相同通知，避免重复 if not monitor_db.has_recent_notification(stock['id'], 'stop_loss', minutes=60): message = f"股票 {stock['symbol']} ({stock['name']}) 价格 {current_price} 达到止损位 {stop_loss}" monitor_db.add_notification(stock['id'], 'stop_loss', message) # 立即发送通知（包括邮件） notification_service.send_notifications() # 如果启用量化交易，执行自动交易 if stock.get('quant_enabled', False): self._execute_quant_trade(stock, 'stop_loss', current_price) def _execute_quant_trade(self, stock: Dict, signal_type: str, current_price: float): """执行量化交易""" try: # 检查MiniQMT是否连接 if not miniqmt.is_connected(): print(f"MiniQMT未连接，无法执行 {stock['symbol']} 的量化交易") return # 获取量化配置 quant_config = stock.get('quant_config', {}) if not quant_config: print(f"股票 {stock['symbol']} 未配置量化参数") return # 执行策略信号 signal = { 'type': signal_type, 'price': current_price, 'message': f"{signal_type} signal triggered" } position_size = quant_config.get('max_position_pct', 0.2) success, msg = miniqmt.execute_strategy_signal( stock['id'], stock['symbol'], signal, position_size ) if success: print(f"✅ 量化交易成功: {stock['symbol']} - {msg}") # 记录交易通知（量化交易通知不检查重复，因为每次交易都应该通知） monitor_db.add_notification( stock['id'], 'quant_trade', f"量化交易执行: {msg}" ) # 立即发送通知（包括邮件） notification_service.send_notifications() else: print(f"❌ 量化交易失败: {stock['symbol']} - {msg}") except Exception as e: print(f"执行量化交易异常: {stock['symbol']} - {str(e)}") def get_stocks_needing_update(self) -> List[Dict]: """获取需要更新价格的股票""" stocks = monitor_db.get_monitored_stocks() current_time = datetime.now() need_update = [] for stock in stocks: last_checked = stock.get('last_checked') check_interval = stock.get('check_interval', 30) if not last_checked: need_update.append(stock) continue last_checked_dt = datetime.fromisoformat(last_checked) next_check = last_checked_dt + timedelta(minutes=check_interval) if current_time >= next_check: need_update.append(stock) return need_update def manual_update_stock(self, stock_id: int): """手动更新股票价格""" stock = monitor_db.get_stock_by_id(stock_id) if stock: self._update_stock_price(stock) return True return False def get_scheduler(self): """获取调度器实例""" from monitor_scheduler import get_scheduler return get_scheduler(self) # 全局监测服务实例 monitor_service = StockMonitorService()