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