#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ 低价擒牛策略监控服务 定时扫描股票，检测卖出信号 """ import time import threading import logging from datetime import datetime from typing import Optional import os from low_price_bull_monitor import low_price_bull_monitor from notification_service import notification_service class LowPriceBullService: """低价擒牛策略监控服务""" def __init__(self): self.logger = logging.getLogger(__name__) self.running = False self.thread: Optional[threading.Thread] = None self.scan_interval = 60 # 默认扫描间隔（秒） self.holding_days_limit = 5 # 持股天数限制 # 从环境变量读取配置 self._load_config() def _load_config(self): """从环境变量加载配置""" try: from dotenv import load_dotenv load_dotenv() # 扫描间隔 interval = os.getenv('LOW_PRICE_BULL_SCAN_INTERVAL', '60') self.scan_interval = int(interval) # 持股天数限制 days = os.getenv('LOW_PRICE_BULL_HOLDING_DAYS', '5') self.holding_days_limit = int(days) # TDX API配置 self.tdx_api_url = os.getenv('TDX_BASE_URL', 'http://127.0.0.1:5000') self.logger.info(f"监控配置: 扫描间隔={self.scan_interval}秒, 持股天数限制={self.holding_days_limit}天") self.logger.info(f"TDX API: {self.tdx_api_url}") except Exception as e: self.logger.warning(f"加载配置失败，使用默认值: {e}") def start(self): """启动监控服务""" if self.running: self.logger.warning("监控服务已在运行") return False self.running = True self.thread = threading.Thread(target=self._monitor_loop, daemon=True) self.thread.start() self.logger.info("低价擒牛监控服务已启动") return True def stop(self): """停止监控服务""" if not self.running: return False self.running = False if self.thread: self.thread.join(timeout=5) self.logger.info("低价擒牛监控服务已停止") return True def _monitor_loop(self): """监控循环""" while self.running: try: self._scan_stocks() time.sleep(self.scan_interval) except Exception as e: self.logger.error(f"监控循环错误: {e}") time.sleep(self.scan_interval) def _scan_stocks(self): """扫描所有监控的股票""" try: # 更新持有天数 low_price_bull_monitor.update_holding_days() # 获取监控列表 stocks = low_price_bull_monitor.get_monitored_stocks() if not stocks: return self.logger.info(f"开始扫描 {len(stocks)} 只股票") for stock in stocks: try: self._check_stock(stock) except Exception as e: self.logger.error(f"检查股票 {stock['stock_code']} 失败: {e}") # 处理提醒 self._process_alerts() except Exception as e: self.logger.error(f"扫描股票失败: {e}") def _check_stock(self, stock: dict): """ 检查单只股票的卖出信号 Args: stock: 股票信息字典 """ stock_code = stock['stock_code'] stock_name = stock['stock_name'] holding_days = stock['holding_days'] # 检查1: 持股天数 if holding_days >= self.holding_days_limit: # 添加提醒 low_price_bull_monitor.add_sell_alert( stock_code=stock_code, stock_name=stock_name, alert_type='holding_days', alert_reason=f'持股满{self.holding_days_limit}天，建议卖出', holding_days=holding_days ) self.logger.info(f"{stock_code} 持股满{self.holding_days_limit}天，生成卖出提醒") return # 检查2: MA5下穿MA20 current_price, ma5, ma20 = self._get_stock_data(stock_code) if current_price and ma5 and ma20: if ma5 < ma20: # MA5下穿MA20，添加提醒 low_price_bull_monitor.add_sell_alert( stock_code=stock_code, stock_name=stock_name, alert_type='ma_cross', alert_reason='MA5下穿MA20，技术信号卖出', current_price=current_price, ma5=ma5, ma20=ma20, holding_days=holding_days ) self.logger.info(f"{stock_code} MA5下穿MA20，生成卖出提醒") def _get_stock_data(self, stock_code: str) -> tuple: """ 获取股票数据（价格和均线） Args: stock_code: 股票代码（可能带后缀，如002259.SZ） Returns: (当前价格, MA5, MA20) """ try: import requests import pandas as pd # 处理股票代码格式：去掉后缀，保留纯数字代码 # 例如：002259.SZ -> 002259 clean_code = stock_code.split('.')[0] if '.' in stock_code else stock_code # 判断市场并添加前缀（TDX API可能需要） # 深圳：0开头、3开头 -> SZ前缀 # 上海：6开头 -> SH前缀 if clean_code.startswith(('0', '3')): api_code = f"SZ{clean_code}" elif clean_code.startswith('6'): api_code = f"SH{clean_code}" else: api_code = clean_code # 调用TDX API获取K线数据 url = f"{self.tdx_api_url}/api/kline" params = { 'code': api_code, 'type': 'day' # 日K线 } self.logger.debug(f"请求TDX API: code={stock_code} -> api_code={api_code}") response = requests.get(url, params=params, timeout=10) if response.status_code != 200: self.logger.warning(f"获取 {stock_code} K线数据失败: HTTP {response.status_code}") self.logger.warning(f"请求URL: {url}?code={api_code}&type=day") # 尝试使用纯数字代码重试 if api_code != clean_code: self.logger.info(f"尝试使用纯数字代码重试: {clean_code}") params['code'] = clean_code response = requests.get(url, params=params, timeout=10) if response.status_code != 200: self.logger.warning(f"重试失败: HTTP {response.status_code}") return None, None, None else: return None, None, None data = response.json() # 检查数据格式 # 支持两种格式： # 1. 直接返回数组: [{date, open, high, low, close, volume}, ...] # 2. 嵌套格式: {code: 0, message: "success", data: {List: [...]}} if isinstance(data, dict) and 'data' in data: # 嵌套格式 if data.get('code') != 0: self.logger.warning(f"{stock_code} API返回错误: {data.get('message')}") return None, None, None data_obj = data.get('data', {}) kline_list = data_obj.get('List', []) if not kline_list or len(kline_list) < 20: self.logger.warning(f"{stock_code} K线数据不足，需要至少20天，当前{len(kline_list)}天") return None, None, None # 转换为DataFrame，字段名需要映射 # API返回：{Time, Open, High, Low, Close, Volume, Amount} # 需要：{date, open, high, low, close, volume} df = pd.DataFrame(kline_list) # 重命名字段（大小写转换） if 'Time' in df.columns: df['date'] = df['Time'] if 'Open' in df.columns: df['open'] = df['Open'] if 'High' in df.columns: df['high'] = df['High'] if 'Low' in df.columns: df['low'] = df['Low'] if 'Close' in df.columns: df['close'] = df['Close'] if 'Volume' in df.columns: df['volume'] = df['Volume'] elif isinstance(data, list): # 直接数组格式 if len(data) < 20: self.logger.warning(f"{stock_code} K线数据不足，需要至少20天") return None, None, None df = pd.DataFrame(data) else: self.logger.warning(f"{stock_code} K线数据格式错误") return None, None, None # 确保有close列 if 'close' not in df.columns: self.logger.warning(f"{stock_code} K线数据缺少close字段") return None, None, None # 转换为浮点数 df['close'] = pd.to_numeric(df['close'], errors='coerce') # 计算MA5和MA20 df['MA5'] = df['close'].rolling(window=5).mean() df['MA20'] = df['close'].rolling(window=20).mean() # 获取最新数据 latest = df.iloc[-1] current_price = latest['close'] ma5 = latest['MA5'] ma20 = latest['MA20'] # 检查是否有效 if pd.isna(current_price) or pd.isna(ma5) or pd.isna(ma20): self.logger.warning(f"{stock_code} 数据包含NaN值") return None, None, None self.logger.info(f"{stock_code} 数据: 价格={current_price:.2f}, MA5={ma5:.2f}, MA20={ma20:.2f}") return current_price, ma5, ma20 except requests.exceptions.RequestException as e: self.logger.error(f"请求TDX API失败 {stock_code}: {e}") self.logger.error(f"请检查.env中的TDX_BASE_URL配置: {self.tdx_api_url}") return None, None, None except Exception as e: self.logger.error(f"获取股票数据失败 {stock_code}: {e}") import traceback traceback.print_exc() return None, None, None def _process_alerts(self): """处理待发送的提醒""" try: alerts = low_price_bull_monitor.get_pending_alerts() if not alerts: return self.logger.info(f"处理 {len(alerts)} 条卖出提醒") for alert in alerts: try: # 发送通知 self._send_alert_notification(alert) # 标记已发送 low_price_bull_monitor.mark_alert_sent(alert['id']) # 自动移除股票 low_price_bull_monitor.remove_stock( alert['stock_code'], reason=alert['alert_reason'] ) self.logger.info(f"已处理提醒并移除股票: {alert['stock_code']}") except Exception as e: self.logger.error(f"处理提醒失败: {e}") except Exception as e: self.logger.error(f"处理提醒失败: {e}") def _send_alert_notification(self, alert: dict): """ 发送卖出提醒通知 Args: alert: 提醒信息字典 """ try: # 构建消息 keyword = notification_service.config.get('webhook_keyword', 'aiagents通知') message_text = f"### {keyword} - 低价擒牛卖出提醒\n\n" message_text += f"**股票代码**: {alert['stock_code']}\n\n" message_text += f"**股票名称**: {alert['stock_name']}\n\n" message_text += f"**提醒类型**: {self._get_alert_type_name(alert['alert_type'])}\n\n" message_text += f"**提醒原因**: {alert['alert_reason']}\n\n" # 添加详细信息（确保数据类型正确） current_price = alert.get('current_price') if current_price is not None: try: price_val = float(current_price) message_text += f"**当前价格**: {price_val:.2f}元\n\n" except (ValueError, TypeError): pass ma5 = alert.get('ma5') ma20 = alert.get('ma20') if ma5 is not None and ma20 is not None: try: ma5_val = float(ma5) ma20_val = float(ma20) message_text += f"**MA5**: {ma5_val:.2f}\n\n" message_text += f"**MA20**: {ma20_val:.2f}\n\n" except (ValueError, TypeError): pass holding_days = alert.get('holding_days') if holding_days is not None: try: days_val = int(holding_days) message_text += f"**持有天数**: {days_val}天\n\n" except (ValueError, TypeError): pass message_text += f"**提醒时间**: {alert['alert_time']}\n\n" message_text += "---\n\n" message_text += "**建议**: 开盘时卖出该股票\n\n" message_text += "_此消息由AI股票分析系统自动发送_" # 发送钉钉通知 if notification_service.config['webhook_enabled']: import requests data = { "msgtype": "markdown", "markdown": { "title": f"{keyword} - 卖出提醒", "text": message_text } } response = requests.post( notification_service.config['webhook_url'], json=data, headers={'Content-Type': 'application/json'}, timeout=10 ) if response.status_code == 200: self.logger.info(f"卖出提醒已发送: {alert['stock_code']}") else: self.logger.error(f"发送提醒失败: HTTP {response.status_code}") except Exception as e: self.logger.error(f"发送通知失败: {e}") def _get_alert_type_name(self, alert_type: str) -> str: """获取提醒类型名称""" type_map = { 'holding_days': '持股到期', 'ma_cross': 'MA均线死叉' } return type_map.get(alert_type, alert_type) def get_status(self) -> dict: """获取服务状态""" stocks = low_price_bull_monitor.get_monitored_stocks() alerts = low_price_bull_monitor.get_pending_alerts() return { 'running': self.running, 'scan_interval': self.scan_interval, 'holding_days_limit': self.holding_days_limit, 'monitored_count': len(stocks), 'pending_alerts': len(alerts) } # 全局服务实例 low_price_bull_service = LowPriceBullService()