oficcejo
437 lines
16 KiB
Python
437 lines
16 KiB
Python
"""
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智策定时分析服务
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支持定时运行板块策略分析并发送邮件通知
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"""
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import schedule
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import threading
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import time
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from datetime import datetime
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from sector_strategy_data import SectorStrategyDataFetcher
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from sector_strategy_engine import SectorStrategyEngine
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from notification_service import notification_service
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import json
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class SectorStrategyScheduler:
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"""智策定时分析调度器"""
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def __init__(self):
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self.running = False
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self.thread = None
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self.schedule_time = "09:00" # 默认上午9点
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self.enabled = False
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self.last_run_time = None
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self.last_result = None
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print("[智策定时] 调度器初始化完成")
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def start(self, schedule_time="09:00"):
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"""
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启动定时任务
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Args:
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schedule_time: 定时时间，格式 "HH:MM"
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"""
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if self.running:
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print("[智策定时] 调度器已在运行中")
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return False
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self.schedule_time = schedule_time
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self.enabled = True
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self.running = True
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# 清除之前的任务
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schedule.clear('sector_strategy')
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# 设置定时任务
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schedule.every().day.at(schedule_time).do(self._run_analysis).tag('sector_strategy')
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# 启动后台线程
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self.thread = threading.Thread(target=self._schedule_loop, daemon=True)
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self.thread.start()
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print(f"[智策定时] ✓ 定时任务已启动，每天 {schedule_time} 运行")
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return True
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def stop(self):
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"""停止定时任务"""
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if not self.running:
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print("[智策定时] 调度器未运行")
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return False
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self.running = False
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self.enabled = False
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schedule.clear('sector_strategy')
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print("[智策定时] ✓ 定时任务已停止")
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return True
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def _schedule_loop(self):
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"""定时任务循环"""
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print("[智策定时] 后台线程已启动")
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while self.running:
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try:
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schedule.run_pending()
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time.sleep(60) # 每分钟检查一次
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except Exception as e:
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print(f"[智策定时] ✗ 调度循环出错: {e}")
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time.sleep(60)
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def _run_analysis(self):
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"""运行智策分析"""
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print("\n" + "="*60)
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print(f"[智策定时] 开始定时分析 - {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
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print("="*60)
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try:
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# 1. 获取数据
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print("[智策定时] [1/3] 获取市场数据...")
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fetcher = SectorStrategyDataFetcher()
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data = fetcher.get_all_sector_data()
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if not data.get("success"):
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print("[智策定时] ✗ 数据获取失败")
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self._send_error_notification("数据获取失败")
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return
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print("[智策定时] ✓ 数据获取成功")
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# 2. 运行AI分析
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print("[智策定时] [2/3] AI智能体分析中...")
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engine = SectorStrategyEngine(model="deepseek-chat")
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result = engine.run_comprehensive_analysis(data)
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if not result.get("success"):
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print("[智策定时] ✗ 分析失败")
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self._send_error_notification("AI分析失败")
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return
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print("[智策定时] ✓ 分析完成")
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# 3. 发送邮件通知
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print("[智策定时] [3/3] 发送邮件通知...")
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self._send_analysis_notification(result)
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# 保存最后运行结果
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self.last_run_time = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
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self.last_result = result
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print("="*60)
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print("[智策定时] ✓ 定时分析完成！")
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print("="*60 + "\n")
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except Exception as e:
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print(f"[智策定时] ✗ 分析过程出错: {e}")
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import traceback
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traceback.print_exc()
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self._send_error_notification(f"分析异常: {str(e)}")
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def _send_analysis_notification(self, result):
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"""发送分析结果邮件"""
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try:
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# 检查邮件配置
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config = notification_service.config
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if not config.get('email_enabled') or not all([
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config.get('smtp_server'),
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config.get('email_from'),
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config.get('email_password'),
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config.get('email_to')
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]):
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print("[智策定时] ⚠️ 邮件配置不完整，跳过发送")
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return
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predictions = result.get("final_predictions", {})
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timestamp = result.get("timestamp", datetime.now().strftime('%Y-%m-%d %H:%M:%S'))
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# 构建邮件内容
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subject = f"智策板块分析报告 - {timestamp}"
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body = self._format_email_body(predictions, timestamp)
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# 直接发送邮件
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success = self._send_email_direct(subject, body)
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if success:
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print("[智策定时] ✓ 邮件发送成功")
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else:
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print("[智策定时] ✗ 邮件发送失败")
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except Exception as e:
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print(f"[智策定时] ✗ 邮件发送异常: {e}")
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import traceback
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traceback.print_exc()
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def _send_error_notification(self, error_msg):
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"""发送错误通知邮件"""
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try:
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subject = f"智策定时分析失败 - {datetime.now().strftime('%Y-%m-%d %H:%M')}"
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body = f"""
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智策定时分析任务失败
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时间: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}
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错误: {error_msg}
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请检查系统日志获取详细信息。
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"""
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self._send_email_direct(subject, body)
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except:
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pass
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def _send_email_direct(self, subject, body):
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"""直接发送邮件（参考notification_service的实现）"""
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try:
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import smtplib
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from email.mime.text import MIMEText
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from email.mime.multipart import MIMEMultipart
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config = notification_service.config
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# 创建邮件
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msg = MIMEMultipart()
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msg['From'] = config['email_from']
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msg['To'] = config['email_to']
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msg['Subject'] = subject
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# 添加正文（纯文本）
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msg.attach(MIMEText(body, 'plain', 'utf-8'))
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print(f"[智策定时] 📧 正在发送邮件...")
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print(f"[智策定时] - 收件人: {config['email_to']}")
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print(f"[智策定时] - 主题: {subject}")
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# 根据端口选择连接方式
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if config['smtp_port'] == 465:
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print(f"[智策定时] - 使用 SMTP_SSL 连接 {config['smtp_server']}:{config['smtp_port']}")
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server = smtplib.SMTP_SSL(config['smtp_server'], config['smtp_port'], timeout=15)
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else:
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print(f"[智策定时] - 使用 SMTP+TLS 连接 {config['smtp_server']}:{config['smtp_port']}")
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server = smtplib.SMTP(config['smtp_server'], config['smtp_port'], timeout=15)
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server.starttls()
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print(f"[智策定时] - 正在登录...")
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server.login(config['email_from'], config['email_password'])
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print(f"[智策定时] - 正在发送...")
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server.send_message(msg)
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server.quit()
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print(f"[智策定时] ✓ 邮件发送成功")
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return True
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except Exception as e:
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print(f"[智策定时] ✗ 邮件发送失败: {e}")
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import traceback
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traceback.print_exc()
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return False
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def _format_email_body(self, predictions, timestamp):
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"""格式化邮件正文"""
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if not predictions or predictions.get("prediction_text"):
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# 文本格式
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return f"""
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智策板块策略分析报告
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分析时间: {timestamp}
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{predictions.get('prediction_text', '暂无预测')}
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---
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本邮件由智策系统自动发送
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"""
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# JSON格式预测
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body_parts = []
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# 标题
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body_parts.append("="*60)
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body_parts.append("智策板块策略分析报告")
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body_parts.append("="*60)
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body_parts.append(f"分析时间: {timestamp}")
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body_parts.append(f"AI模型: DeepSeek Multi-Agent System")
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body_parts.append("")
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# 1. 板块多空
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long_short = predictions.get("long_short", {})
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if long_short:
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body_parts.append("="*60)
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body_parts.append("一、板块多空预测")
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body_parts.append("="*60)
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body_parts.append("")
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# 看多板块
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bullish = long_short.get("bullish", [])
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if bullish:
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body_parts.append("【看多板块】")
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body_parts.append("")
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for idx, item in enumerate(bullish, 1):
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body_parts.append(f"{idx}. {item.get('sector', 'N/A')} (信心度: {item.get('confidence', 0)}/10)")
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body_parts.append(f" 理由: {item.get('reason', 'N/A')}")
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body_parts.append(f" 风险: {item.get('risk', 'N/A')}")
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body_parts.append("")
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# 看空板块
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bearish = long_short.get("bearish", [])
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if bearish:
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body_parts.append("【看空板块】")
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body_parts.append("")
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for idx, item in enumerate(bearish, 1):
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body_parts.append(f"{idx}. {item.get('sector', 'N/A')} (信心度: {item.get('confidence', 0)}/10)")
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body_parts.append(f" 理由: {item.get('reason', 'N/A')}")
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body_parts.append(f" 风险: {item.get('risk', 'N/A')}")
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body_parts.append("")
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# 2. 板块轮动
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rotation = predictions.get("rotation", {})
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if rotation:
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body_parts.append("="*60)
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body_parts.append("二、板块轮动预测")
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body_parts.append("="*60)
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body_parts.append("")
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# 当前强势
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current_strong = rotation.get("current_strong", [])
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if current_strong:
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body_parts.append("【当前强势板块】")
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body_parts.append("")
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for item in current_strong:
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body_parts.append(f"• {item.get('sector', 'N/A')}")
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body_parts.append(f" 轮动逻辑: {item.get('logic', 'N/A')[:100]}...")
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body_parts.append(f" 时间窗口: {item.get('time_window', 'N/A')}")
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body_parts.append(f" 操作建议: {item.get('advice', 'N/A')}")
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body_parts.append("")
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# 潜力接力
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potential = rotation.get("potential", [])
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if potential:
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body_parts.append("【潜力接力板块】⭐ 重点关注")
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body_parts.append("")
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for item in potential:
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body_parts.append(f"• {item.get('sector', 'N/A')}")
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body_parts.append(f" 轮动逻辑: {item.get('logic', 'N/A')[:100]}...")
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body_parts.append(f" 时间窗口: {item.get('time_window', 'N/A')}")
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body_parts.append(f" 操作建议: {item.get('advice', 'N/A')}")
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body_parts.append("")
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# 3. 板块热度
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heat = predictions.get("heat", {})
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if heat:
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body_parts.append("="*60)
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body_parts.append("三、板块热度排行")
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body_parts.append("="*60)
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body_parts.append("")
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# 最热板块
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hottest = heat.get("hottest", [])
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if hottest:
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body_parts.append("【最热板块 TOP5】")
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body_parts.append("")
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for idx, item in enumerate(hottest, 1):
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body_parts.append(f"{idx}. {item.get('sector', 'N/A')} - 热度: {item.get('score', 0)}分 ({item.get('trend', 'N/A')})")
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body_parts.append("")
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# 升温板块
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heating = heat.get("heating", [])
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if heating:
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body_parts.append("【升温板块】")
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body_parts.append("")
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for idx, item in enumerate(heating, 1):
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body_parts.append(f"{idx}. {item.get('sector', 'N/A')} - 热度: {item.get('score', 0)}分 ↗")
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body_parts.append("")
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# 4. 策略总结
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summary = predictions.get("summary", {})
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if summary:
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body_parts.append("="*60)
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body_parts.append("四、策略总结")
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body_parts.append("="*60)
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body_parts.append("")
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if summary.get('market_view'):
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body_parts.append("【市场观点】")
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body_parts.append(summary['market_view'])
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body_parts.append("")
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if summary.get('key_opportunity'):
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body_parts.append("【核心机会】⭐")
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body_parts.append(summary['key_opportunity'])
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body_parts.append("")
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if summary.get('major_risk'):
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body_parts.append("【主要风险】⚠️")
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body_parts.append(summary['major_risk'])
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body_parts.append("")
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if summary.get('strategy'):
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body_parts.append("【整体策略】")
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body_parts.append(summary['strategy'])
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body_parts.append("")
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# 结束语
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body_parts.append("="*60)
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body_parts.append("本报告由智策AI系统自动生成并发送")
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body_parts.append("仅供参考，不构成投资建议")
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body_parts.append("="*60)
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return "\n".join(body_parts)
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def manual_run(self):
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"""手动触发一次分析"""
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print("[智策定时] 手动触发分析...")
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self._run_analysis()
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def get_status(self):
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"""获取调度器状态"""
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return {
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"running": self.running,
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"enabled": self.enabled,
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"schedule_time": self.schedule_time,
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"last_run_time": self.last_run_time,
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"next_run_time": self._get_next_run_time()
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}
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def _get_next_run_time(self):
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"""获取下次运行时间"""
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if not self.running:
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return None
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try:
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jobs = schedule.get_jobs('sector_strategy')
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if jobs:
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next_run = jobs[0].next_run
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if next_run:
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return next_run.strftime('%Y-%m-%d %H:%M:%S')
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except:
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pass
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return None
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# 创建全局实例
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sector_strategy_scheduler = SectorStrategyScheduler()
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# 测试函数
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if __name__ == "__main__":
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print("智策定时分析服务测试")
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print("="*60)
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# 启动定时任务（测试用，设置为当前时间后1分钟）
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from datetime import datetime, timedelta
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test_time = (datetime.now() + timedelta(minutes=1)).strftime("%H:%M")
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print(f"设置测试时间: {test_time}")
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sector_strategy_scheduler.start(test_time)
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# 保持运行
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try:
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while True:
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status = sector_strategy_scheduler.get_status()
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print(f"\n状态: {status}")
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time.sleep(30)
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except KeyboardInterrupt:
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print("\n停止测试...")
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sector_strategy_scheduler.stop()
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