优化连接不上时创建表

applications/reporter/base_reporter.py

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+"""
+报告生成器基类
+提供数据源接口、AI处理接口等扩展能力
+"""
+from abc import ABC, abstractmethod
+from typing import List, Dict, Any, Optional
+from datetime import datetime, timedelta
+import os
+import sys
+from loguru import logger
+
+# 添加父目录到路径
+current_dir = os.path.dirname(os.path.abspath(__file__))
+parent_dir = os.path.dirname(os.path.dirname(current_dir))
+if parent_dir not in sys.path:
+    sys.path.insert(0, parent_dir)
+
+from utils.mysql_agent import MySQLAgent
+from config import Config
+
+
+class DataSource(ABC):
+    """数据源接口基类，用于后续扩展其他数据源"""
+    
+    @abstractmethod
+    def fetch_data(self, start_time: datetime, end_time: datetime) -> List[Dict[str, Any]]:
+        """
+        获取指定时间范围内的数据
+        
+        Args:
+            start_time: 开始时间
+            end_time: 结束时间
+            
+        Returns:
+            数据列表，每条数据应包含：标题、链接、摘要、发布时间等字段
+        """
+        pass
+    
+    @abstractmethod
+    def get_source_name(self) -> str:
+        """获取数据源名称"""
+        pass
+
+
+class RSSDataSource(DataSource):
+    """RSS数据源实现"""
+    
+    def __init__(self, db_agent: MySQLAgent, table_name: str = "collector_rss_subscriptions"):
+        self.db_agent = db_agent
+        self.table_name = table_name
+        self.logger = logger.bind(module="RSSDataSource")
+    
+    def fetch_data(self, start_time: datetime, end_time: datetime) -> List[Dict[str, Any]]:
+        """从数据库获取RSS数据"""
+        try:
+            sql = f"""
+                SELECT 
+                    `文章标题` as title,
+                    `文章链接` as link,
+                    `文章摘要` as summary,
+                    `发布时间` as publish_time,
+                    `来源URL` as source_url,
+                    `创建时间` as create_time
+                FROM `{self.table_name}`
+                WHERE `发布时间` >= %s AND `发布时间` < %s
+                ORDER BY `发布时间` DESC
+            """
+            
+            params = (
+                start_time.strftime('%Y-%m-%d %H:%M:%S'),
+                end_time.strftime('%Y-%m-%d %H:%M:%S')
+            )
+            
+            df = self.db_agent.query_to_df(sql, params=params, is_print=False)
+            
+            if df.empty:
+                self.logger.info(f"时间范围 {start_time} 到 {end_time} 内没有RSS数据")
+                return []
+            
+            # 转换为字典列表
+            data_list = df.to_dict('records')
+            self.logger.info(f"获取到 {len(data_list)} 条RSS数据")
+            return data_list
+            
+        except Exception as e:
+            self.logger.error(f"获取RSS数据失败: {str(e)}", exc_info=True)
+            return []
+    
+    def get_source_name(self) -> str:
+        return "RSS订阅"
+
+
+class AIAnalysisDataSource(DataSource):
+    """AI分析结果数据源实现 - 从ai_processor_rss_analysis表获取已筛选的相关内容"""
+    
+    def __init__(self, db_agent: MySQLAgent, table_name: str = "ai_processor_rss_analysis"):
+        self.db_agent = db_agent
+        self.table_name = table_name
+        self.logger = logger.bind(module="AIAnalysisDataSource")
+    
+    def fetch_data(self, start_time: datetime, end_time: datetime) -> List[Dict[str, Any]]:
+        """从AI分析结果表获取相关数据（是否相关=1）"""
+        try:
+            sql = f"""
+                SELECT 
+                    `文章标题` as title,
+                    `文章链接` as link,
+                    `文章摘要` as summary,
+                    `发布时间` as publish_time,
+                    `来源URL` as source_url,
+                    `分类` as category,
+                    `标签` as tags,
+                    `相关度评分` as relevance_score,
+                    `分析说明` as analysis_note,
+                    `处理时间` as process_time
+                FROM `{self.table_name}`
+                WHERE `发布时间` >= %s AND `发布时间` < %s
+                  AND `是否相关` = 1
+                ORDER BY `发布时间` DESC, `相关度评分` DESC
+            """
+            
+            params = (
+                start_time.strftime('%Y-%m-%d %H:%M:%S'),
+                end_time.strftime('%Y-%m-%d %H:%M:%S')
+            )
+            
+            df = self.db_agent.query_to_df(sql, params=params, is_print=False)
+            
+            if df.empty:
+                self.logger.info(f"时间范围 {start_time} 到 {end_time} 内没有相关数据（是否相关=1）")
+                return []
+            
+            # 转换为字典列表
+            data_list = df.to_dict('records')
+            self.logger.info(f"获取到 {len(data_list)} 条相关数据（是否相关=1）")
+            return data_list
+            
+        except Exception as e:
+            self.logger.error(f"获取AI分析数据失败: {str(e)}", exc_info=True)
+            return []
+    
+    def get_source_name(self) -> str:
+        return "AI分析结果"
+
+
+class AIProcessor:
+    """AI处理器，用于筛选和分析内容"""
+    
+    def __init__(self, api_key: str = None, model: str = None):
+        from openai import OpenAI
+        
+        self.base_url = 'https://qianfan.baidubce.com/v2'
+        self.api_key = api_key or Config.BAIDU_AI_CONFIG.get('api_key')
+        self.model = model or Config.BAIDU_AI_CONFIG.get('model', 'ernie-x1-turbo-32k')
+        self.client = OpenAI(
+            base_url=self.base_url,
+            api_key=self.api_key
+        )
+        self.logger = logger.bind(module="AIProcessor")
+    
+    def filter_automotive_content(self, articles: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
+        """
+        筛选与汽车后市场相关的内容
+        
+        Args:
+            articles: 文章列表
+            
+        Returns:
+            筛选后的文章列表（包含AI标记信息）
+        """
+        if not articles:
+            return []
+        
+        self.logger.info(f"开始AI筛选 {len(articles)} 篇文章")
+        
+        # 批量处理，避免API限流
+        batch_size = 10
+        filtered_articles = []
+        
+        for i in range(0, len(articles), batch_size):
+            batch = articles[i:i + batch_size]
+            try:
+                # 构建批量分析的prompt
+                articles_text = ""
+                for idx, article in enumerate(batch):
+                    articles_text += f"\n[{idx + i}] 标题: {article.get('title', '')}\n"
+                    articles_text += f"摘要: {article.get('summary', '')}\n"
+                
+                prompt = f"""请分析以下新闻文章，判断哪些与汽车后市场相关。
+
+汽车后市场的定义：汽车销售以后，围绕汽车使用过程中的各种服务，包括：
+- 汽车维修保养
+- 汽车配件
+- 汽车改装
+- 汽车美容
+- 汽车用品
+- 汽车金融
+- 汽车保险
+- 二手车交易
+- 汽车租赁
+- 汽车检测
+- 汽车报废回收
+- 汽车相关法律法规和政策
+
+文章列表：
+{articles_text}
+
+请按以下JSON格式返回结果：
+{{
+    "related_articles": [
+        {{
+            "index": 文章的序号（从0开始）,
+            "is_related": true/false,
+            "reason": "判断理由",
+            "category": "所属类别（如：维修保养、配件、政策等）"
+        }}
+    ]
+}}
+
+只返回JSON，不要其他文字说明。"""
+                
+                response = self.client.chat.completions.create(
+                    model=self.model,
+                    messages=[{
+                        "role": "user",
+                        "content": prompt
+                    }]
+                )
+                
+                result_text = response.choices[0].message.content.strip()
+                
+                # 尝试解析JSON（去除可能的markdown代码块标记）
+                import json
+                import re
+                
+                # 提取JSON部分（尝试多种方式）
+                result_json = None
+                # 方式1：查找markdown代码块中的JSON
+                json_match = re.search(r'```(?:json)?\s*(\{.*?\})\s*```', result_text, re.DOTALL)
+                if json_match:
+                    try:
+                        result_json = json.loads(json_match.group(1))
+                    except:
+                        pass
+                
+                # 方式2：直接查找JSON对象
+                if result_json is None:
+                    json_match = re.search(r'\{.*\}', result_text, re.DOTALL)
+                    if json_match:
+                        try:
+                            result_json = json.loads(json_match.group())
+                        except:
+                            pass
+                
+                # 方式3：尝试直接解析
+                if result_json is None:
+                    try:
+                        result_json = json.loads(result_text)
+                    except:
+                        self.logger.warning(f"无法解析AI返回的JSON: {result_text[:200]}")
+                        result_json = {'related_articles': []}
+                
+                # 处理结果
+                for item in result_json.get('related_articles', []):
+                    idx = item.get('index', -1)
+                    if 0 <= idx < len(batch):
+                        article = batch[idx]
+                        if item.get('is_related', False):
+                            article['ai_marked'] = True
+                            article['ai_category'] = item.get('category', '其他')
+                            article['ai_reason'] = item.get('reason', '')
+                            filtered_articles.append(article)
+                
+                # 避免API限流
+                import time
+                if i + batch_size < len(articles):
+                    time.sleep(1.5)
+                    
+            except Exception as e:
+                self.logger.error(f"AI筛选批处理失败: {str(e)}", exc_info=True)
+                # 如果AI处理失败，保留所有文章但标记为未筛选
+                for article in batch:
+                    article['ai_marked'] = False
+                    article['ai_error'] = str(e)
+        
+        self.logger.info(f"AI筛选完成，找到 {len(filtered_articles)} 篇相关文章")
+        return filtered_articles
+    
+    def generate_news_summary(self, articles: List[Dict[str, Any]]) -> str:
+        """
+        生成新闻摘要
+        
+        Args:
+            articles: 筛选后的文章列表
+            
+        Returns:
+            Markdown格式的新闻摘要
+        """
+        if not articles:
+            return "## 相关新闻\n\n暂无相关新闻。\n"
+        
+        articles_text = ""
+        for idx, article in enumerate(articles, 1):
+            category = article.get('ai_category', '其他')
+            reason = article.get('ai_reason', '')
+            articles_text += f"\n### {idx}. {article.get('title', '无标题')}\n"
+            articles_text += f"- **类别**: {category}\n"
+            articles_text += f"- **摘要**: {article.get('summary', '无摘要')}\n"
+            articles_text += f"- **链接**: [{article.get('link', '')}]({article.get('link', '')})\n"
+            articles_text += f"- **发布时间**: {article.get('publish_time', '')}\n"
+            if reason:
+                articles_text += f"- **相关性说明**: {reason}\n"
+            articles_text += "\n"
+        
+        return f"## 汽车后市场相关新闻\n\n共找到 {len(articles)} 篇相关新闻：\n\n{articles_text}"
+
+
+class BaseReporter:
+    """报告生成器基类"""
+    
+    def __init__(self, data_sources: List[DataSource] = None):
+        self.data_sources = data_sources or []
+        self.ai_processor = AIProcessor()
+        self.logger = logger.bind(module="BaseReporter")
+    
+    def add_data_source(self, data_source: DataSource):
+        """添加数据源"""
+        self.data_sources.append(data_source)
+        self.logger.info(f"添加数据源: {data_source.get_source_name()}")
+    
+    def collect_data(self, start_time: datetime, end_time: datetime) -> List[Dict[str, Any]]:
+        """从所有数据源收集数据"""
+        all_data = []
+        for source in self.data_sources:
+            try:
+                data = source.fetch_data(start_time, end_time)
+                # 标记数据来源
+                for item in data:
+                    item['data_source'] = source.get_source_name()
+                all_data.extend(data)
+            except Exception as e:
+                self.logger.error(f"从 {source.get_source_name()} 收集数据失败: {str(e)}")
+        
+        # 按发布时间排序
+        all_data.sort(key=lambda x: x.get('publish_time', ''), reverse=True)
+        return all_data
+    
+    def generate_report_content(self, articles: List[Dict[str, Any]], report_type: str = "日报") -> str:
+        """
+        生成报告内容（Markdown格式）
+        
+        Args:
+            articles: 文章列表（已从AI分析结果表筛选，是否相关=1）
+            report_type: 报告类型（"日报"或"周报"），用于无数据时的提示
+        """
+        # 数据已经是从AI分析结果表筛选过的（是否相关=1），直接使用
+        related_articles = articles
+        
+        # 生成统计信息
+        related_count = len(related_articles)
+        
+        # 如果没有相关数据，返回提示信息
+        if related_count == 0:
+            if report_type == "日报":
+                message = "昨日无汽车后市场相关的新闻"
+            else:
+                message = "上周无汽车后市场相关的新闻"
+            
+            return f"""
+## 数据统计
+
+- **相关文章数**: 0
+
+## 相关新闻
+
+{message}
+"""
+        
+        # 生成新闻摘要
+        news_summary = self._generate_news_summary_from_analysis(related_articles)
+        
+        stats = f"""
+## 数据统计
+
+- **相关文章数**: {related_count}
+
+"""
+        
+        return stats + news_summary
+    
+    def _generate_news_summary_from_analysis(self, articles: List[Dict[str, Any]]) -> str:
+        """
+        从AI分析结果生成新闻摘要（使用数据库中已有的分类和分析说明）
+        
+        Args:
+            articles: 文章列表（包含category、tags、analysis_note等字段）
+            
+        Returns:
+            Markdown格式的新闻摘要
+        """
+        if not articles:
+            return "## 相关新闻\n\n暂无相关新闻。\n"
+        
+        articles_text = ""
+        for idx, article in enumerate(articles, 1):
+            category = article.get('category', '其他')
+            tags = article.get('tags', '')
+            analysis_note = article.get('analysis_note', '')
+            relevance_score = article.get('relevance_score', '')
+            
+            articles_text += f"\n### {idx}. {article.get('title', '无标题')}\n"
+            articles_text += f"- **分类**: {category}\n"
+            if tags:
+                articles_text += f"- **标签**: {tags}\n"
+            articles_text += f"- **摘要**: {article.get('summary', '无摘要')}\n"
+            articles_text += f"- **链接**: [{article.get('link', '')}]({article.get('link', '')})\n"
+            articles_text += f"- **发布时间**: {article.get('publish_time', '')}\n"
+            if relevance_score:
+                articles_text += f"- **相关度评分**: {relevance_score}\n"
+            if analysis_note:
+                articles_text += f"- **分析说明**: {analysis_note}\n"
+            articles_text += "\n"
+        
+        return f"## 汽车后市场相关新闻\n\n共找到 {len(articles)} 篇相关新闻：\n\n{articles_text}"
+    
+    def generate_html_report(self, markdown_content: str, template_path: str = None) -> str:
+        """生成HTML报告"""
+        # 使用相对导入避免循环依赖
+        from .html_template import HTMLTemplateManager
+        
+        template_manager = HTMLTemplateManager()
+        
+        if template_path and os.path.exists(template_path):
+            # 使用外部模板
+            html_content = template_manager.render_external_template(template_path, markdown_content)
+        else:
+            # 使用内置模板
+            html_content = template_manager.render_builtin_template(markdown_content)
+        
+        return html_content
+    
+    def save_report(self, html_content: str, output_path: str):
+        """保存HTML报告到文件"""
+        os.makedirs(os.path.dirname(output_path) if os.path.dirname(output_path) else '.', exist_ok=True)
+        
+        with open(output_path, 'w', encoding='utf-8') as f:
+            f.write(html_content)
+        
+        self.logger.info(f"HTML报告已保存到: {output_path}")
+    
+    def save_markdown_report(self, markdown_content: str, output_path: str):
+        """保存Markdown报告到文件"""
+        os.makedirs(os.path.dirname(output_path) if os.path.dirname(output_path) else '.', exist_ok=True)
+        
+        with open(output_path, 'w', encoding='utf-8') as f:
+            f.write(markdown_content)
+        
+        self.logger.info(f"Markdown报告已保存到: {output_path}")
+

applications/reporter/daily.py

@@ -0,0 +1,139 @@
+"""
+日报生成器 - 生成24小时内的汽车后市场情报报告
+"""
+import os
+import sys
+from datetime import datetime, timedelta
+from loguru import logger
+
+# 添加父目录到路径
+current_dir = os.path.dirname(os.path.abspath(__file__))
+parent_dir = os.path.dirname(os.path.dirname(current_dir))
+if parent_dir not in sys.path:
+    sys.path.insert(0, parent_dir)
+
+from applications.reporter.base_reporter import BaseReporter, AIAnalysisDataSource
+from applications.reporter.dingtalk_webhook import DingTalkWebhook
+from utils.mysql_agent import MySQLAgent
+from config import Config
+
+
+class DailyReporter(BaseReporter):
+    """日报生成器"""
+    
+    def __init__(self, dingtalk_webhook: str = None):
+        """
+        初始化日报生成器
+        
+        Args:
+            dingtalk_webhook: 钉钉Webhook地址（可选）
+        """
+        super().__init__()
+        # 初始化数据库连接
+        db_agent = MySQLAgent(Config.MYSQL_CONFIG)
+        # 添加AI分析结果数据源（已筛选是否相关=1）
+        self.add_data_source(AIAnalysisDataSource(db_agent))
+        self.logger = logger.bind(module="DailyReporter")
+        
+        # 初始化钉钉推送（如果提供了webhook）
+        self.dingtalk_webhook = dingtalk_webhook or getattr(Config, 'DINGTALK_WEBHOOK', None)
+        self.dingtalk_client = None
+        if self.dingtalk_webhook:
+            self.dingtalk_client = DingTalkWebhook(self.dingtalk_webhook)
+            self.logger.info("已启用钉钉推送功能")
+    
+    def generate(self, output_dir: str = "output/reports/daily", 
+                 template_path: str = None, 
+                 save_markdown: bool = True,
+                 send_dingtalk: bool = True) -> dict:
+        """
+        生成日报
+        
+        Args:
+            output_dir: 输出目录
+            template_path: 可选的外部HTML模板路径
+            save_markdown: 是否保存Markdown文件
+            send_dingtalk: 是否发送到钉钉
+            
+        Returns:
+            包含生成文件路径的字典
+        """
+        self.logger.info("开始生成日报")
+        
+        # 计算时间范围：24小时内
+        end_time = datetime.now()
+        start_time = end_time - timedelta(hours=24)
+        
+        self.logger.info(f"时间范围: {start_time.strftime('%Y-%m-%d %H:%M:%S')} 至 {end_time.strftime('%Y-%m-%d %H:%M:%S')}")
+        
+        # 收集数据
+        articles = self.collect_data(start_time, end_time)
+        
+        # 生成报告内容（generate_report_content会自动处理空数据情况）
+        markdown_content = f"""# 汽车后市场情报日报
+
+## 报告时间
+**生成时间**: {end_time.strftime('%Y-%m-%d %H:%M:%S')}
+**时间范围**: {start_time.strftime('%Y-%m-%d %H:%M:%S')} 至 {end_time.strftime('%Y-%m-%d %H:%M:%S')}
+
+{self.generate_report_content(articles, report_type="日报")}
+"""
+        
+        # 生成HTML报告
+        html_content = self.generate_html_report(markdown_content, template_path=template_path)
+        
+        # 保存报告
+        os.makedirs(output_dir, exist_ok=True)
+        timestamp = end_time.strftime('%Y%m%d_%H%M%S')
+        
+        result = {}
+        
+        # 保存HTML报告
+        html_filename = f"daily_report_{timestamp}.html"
+        html_path = os.path.join(output_dir, html_filename)
+        self.save_report(html_content, html_path)
+        result['html_path'] = html_path
+        self.logger.info(f"HTML报告已保存: {html_path}")
+        
+        # 保存Markdown报告
+        markdown_path = None
+        if save_markdown:
+            markdown_filename = f"daily_report_{timestamp}.md"
+            markdown_path = os.path.join(output_dir, markdown_filename)
+            self.save_markdown_report(markdown_content, markdown_path)
+            result['markdown_path'] = markdown_path
+            self.logger.info(f"Markdown报告已保存: {markdown_path}")
+        
+        # 发送到钉钉
+        if send_dingtalk and self.dingtalk_client:
+            title = f"汽车后市场情报日报 - {end_time.strftime('%Y-%m-%d')}"
+            success = self.dingtalk_client.send_report(title, markdown_content, markdown_path)
+            result['dingtalk_sent'] = success
+            if success:
+                self.logger.info("报告已推送到钉钉群")
+            else:
+                self.logger.warning("报告推送到钉钉群失败")
+        
+        self.logger.info(f"日报生成完成")
+        return result
+
+
+def main():
+    """主函数"""
+    try:
+        reporter = DailyReporter()
+        result = reporter.generate()
+        print(f"日报已生成:")
+        print(f"  HTML: {result.get('html_path')}")
+        if 'markdown_path' in result:
+            print(f"  Markdown: {result.get('markdown_path')}")
+        if 'dingtalk_sent' in result:
+            print(f"  钉钉推送: {'成功' if result.get('dingtalk_sent') else '失败'}")
+    except Exception as e:
+        logger.error(f"生成日报失败: {str(e)}", exc_info=True)
+        raise
+
+
+if __name__ == "__main__":
+    main()
+

applications/reporter/html_template.py

@@ -0,0 +1,399 @@
+"""
+HTML模板管理器
+支持内置模板和外部HTML模板
+"""
+import os
+import markdown
+from bs4 import BeautifulSoup
+import re
+from typing import Optional
+from loguru import logger
+
+
+class HTMLTemplateManager:
+    """HTML模板管理器"""
+    
+    def __init__(self):
+        self.logger = logger.bind(module="HTMLTemplateManager")
+    
+    def markdown_to_html(self, markdown_content: str) -> str:
+        """将Markdown转换为HTML"""
+        html = markdown.markdown(
+            markdown_content,
+            extensions=['tables', 'fenced_code', 'codehilite']
+        )
+        return html
+    
+    def render_builtin_template(self, markdown_content: str) -> str:
+        """使用内置模板渲染HTML"""
+        html_body = self.markdown_to_html(markdown_content)
+        
+        # 增强HTML结构
+        soup = BeautifulSoup(html_body, 'html.parser')
+        self._enhance_html_structure(soup)
+        
+        # 生成完整HTML
+        html_template = f"""<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>汽车后市场情报报告</title>
+    <link href="https://fonts.googleapis.com/css2?family=Noto+Sans+SC:wght@300;400;500;700&display=swap" rel="stylesheet">
+    <style>
+        :root {{
+            --primary: #3498db;
+            --secondary: #2ecc71;
+            --accent: #e74c3c;
+            --dark: #2c3e50;
+            --light: #f8f9fa;
+            --border: #e0e0e0;
+        }}
+
+        * {{
+            margin: 0;
+            padding: 0;
+            box-sizing: border-box;
+        }}
+
+        body {{
+            font-family: 'Noto Sans SC', -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
+            line-height: 1.8;
+            color: #333;
+            background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
+            padding: 20px;
+        }}
+
+        .report-container {{
+            max-width: 1200px;
+            margin: 0 auto;
+            padding: 40px;
+            background: white;
+            box-shadow: 0 10px 40px rgba(0,0,0,0.1);
+            border-radius: 12px;
+        }}
+
+        .report-header {{
+            text-align: center;
+            padding-bottom: 30px;
+            border-bottom: 3px solid var(--primary);
+            margin-bottom: 40px;
+        }}
+
+        .report-header h1 {{
+            color: var(--dark);
+            font-size: 2.5em;
+            margin-bottom: 10px;
+        }}
+
+        .report-header .report-date {{
+            color: #666;
+            font-size: 1.1em;
+        }}
+
+        h1 {{
+            color: var(--dark);
+            font-size: 2em;
+            margin: 30px 0 20px 0;
+            padding-bottom: 10px;
+            border-bottom: 2px solid var(--primary);
+        }}
+
+        h2 {{
+            color: var(--dark);
+            font-size: 1.6em;
+            margin: 25px 0 15px 0;
+            padding-left: 10px;
+            border-left: 4px solid var(--primary);
+        }}
+
+        h3 {{
+            color: var(--dark);
+            font-size: 1.3em;
+            margin: 20px 0 10px 0;
+        }}
+
+        h4 {{
+            color: #555;
+            font-size: 1.1em;
+            margin: 15px 0 8px 0;
+        }}
+
+        p {{
+            margin: 12px 0;
+            text-align: justify;
+        }}
+
+        ul, ol {{
+            margin: 15px 0;
+            padding-left: 30px;
+        }}
+
+        li {{
+            margin: 8px 0;
+        }}
+
+        /* 表格样式 */
+        table {{
+            width: 100%;
+            border-collapse: collapse;
+            margin: 25px 0;
+            box-shadow: 0 2px 15px rgba(0,0,0,0.1);
+            border-radius: 8px;
+            overflow: hidden;
+        }}
+
+        table thead {{
+            background: linear-gradient(135deg, var(--primary) 0%, #2980b9 100%);
+            color: white;
+        }}
+
+        table th {{
+            padding: 15px;
+            text-align: left;
+            font-weight: 600;
+        }}
+
+        table td {{
+            padding: 12px 15px;
+            border-bottom: 1px solid var(--border);
+        }}
+
+        table tbody tr:hover {{
+            background-color: #f5f5f5;
+        }}
+
+        table tbody tr:last-child td {{
+            border-bottom: none;
+        }}
+
+        /* 代码块样式 */
+        pre {{
+            background: #f4f4f4;
+            border: 1px solid var(--border);
+            border-radius: 6px;
+            padding: 15px;
+            overflow-x: auto;
+            margin: 20px 0;
+        }}
+
+        code {{
+            background: #f4f4f4;
+            padding: 2px 6px;
+            border-radius: 3px;
+            font-family: 'Courier New', monospace;
+            font-size: 0.9em;
+        }}
+
+        pre code {{
+            background: none;
+            padding: 0;
+        }}
+
+        /* 链接样式 */
+        a {{
+            color: var(--primary);
+            text-decoration: none;
+            border-bottom: 1px dotted var(--primary);
+            transition: all 0.3s;
+        }}
+
+        a:hover {{
+            color: var(--accent);
+            border-bottom-color: var(--accent);
+        }}
+
+        /* 新闻列表样式 */
+        .news-item {{
+            background: #f9f9f9;
+            border-left: 4px solid var(--secondary);
+            padding: 15px 20px;
+            margin: 15px 0;
+            border-radius: 6px;
+            transition: all 0.3s;
+        }}
+
+        .news-item:hover {{
+            background: #f0f0f0;
+            box-shadow: 0 2px 8px rgba(0,0,0,0.1);
+        }}
+
+        .news-item h3 {{
+            margin-top: 0;
+            color: var(--dark);
+        }}
+
+        .news-item .news-meta {{
+            color: #666;
+            font-size: 0.9em;
+            margin-top: 10px;
+        }}
+
+        .news-item .news-category {{
+            display: inline-block;
+            background: var(--secondary);
+            color: white;
+            padding: 3px 10px;
+            border-radius: 12px;
+            font-size: 0.85em;
+            margin-right: 10px;
+        }}
+
+        /* 统计信息样式 */
+        .stats-box {{
+            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+            color: white;
+            padding: 25px;
+            border-radius: 10px;
+            margin: 25px 0;
+        }}
+
+        .stats-box h2 {{
+            color: white;
+            border: none;
+            padding: 0;
+            margin: 0 0 15px 0;
+        }}
+
+        .stats-grid {{
+            display: grid;
+            grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
+            gap: 20px;
+            margin-top: 20px;
+        }}
+
+        .stat-item {{
+            text-align: center;
+        }}
+
+        .stat-number {{
+            font-size: 2.5em;
+            font-weight: bold;
+            margin-bottom: 5px;
+        }}
+
+        .stat-label {{
+            font-size: 0.9em;
+            opacity: 0.9;
+        }}
+
+        /* 响应式设计 */
+        @media (max-width: 768px) {{
+            .report-container {{
+                padding: 20px;
+            }}
+
+            .report-header h1 {{
+                font-size: 1.8em;
+            }}
+
+            h1 {{
+                font-size: 1.6em;
+            }}
+
+            h2 {{
+                font-size: 1.3em;
+            }}
+
+            table {{
+                font-size: 0.9em;
+            }}
+
+            table th,
+            table td {{
+                padding: 8px;
+            }}
+        }}
+
+        /* 打印样式 */
+        @media print {{
+            body {{
+                background: white;
+                padding: 0;
+            }}
+
+            .report-container {{
+                box-shadow: none;
+                padding: 0;
+            }}
+        }}
+    </style>
+</head>
+<body>
+    <div class="report-container">
+        {str(soup)}
+    </div>
+</body>
+</html>"""
+        
+        return html_template
+    
+    def render_external_template(self, template_path: str, markdown_content: str) -> str:
+        """
+        使用外部HTML模板渲染
+        
+        Args:
+            template_path: 外部模板文件路径
+            markdown_content: Markdown内容
+            
+        Returns:
+            渲染后的HTML内容
+        """
+        try:
+            with open(template_path, 'r', encoding='utf-8') as f:
+                template = f.read()
+            
+            html_body = self.markdown_to_html(markdown_content)
+            
+            # 查找模板中的占位符并替换
+            # 支持 {{content}} 或 {content} 等格式
+            patterns = [
+                r'\{\{content\}\}',
+                r'\{content\}',
+                r'<!--\s*content\s*-->',
+            ]
+            
+            replaced = False
+            for pattern in patterns:
+                if re.search(pattern, template, re.IGNORECASE):
+                    template = re.sub(pattern, html_body, template, flags=re.IGNORECASE)
+                    replaced = True
+                    break
+            
+            if not replaced:
+                # 如果没有找到占位符，在body标签内追加内容
+                soup = BeautifulSoup(template, 'html.parser')
+                body = soup.find('body')
+                if body:
+                    body.append(BeautifulSoup(html_body, 'html.parser'))
+                else:
+                    # 如果没有body标签，在html末尾追加
+                    template += html_body
+                template = str(soup) if soup else template
+            
+            self.logger.info(f"使用外部模板渲染: {template_path}")
+            return template
+            
+        except Exception as e:
+            self.logger.error(f"使用外部模板失败: {str(e)}，回退到内置模板", exc_info=True)
+            return self.render_builtin_template(markdown_content)
+    
+    def _enhance_html_structure(self, soup: BeautifulSoup):
+        """增强HTML结构"""
+        # 增强表格
+        for table in soup.find_all('table'):
+            if not table.get('class'):
+                table['class'] = 'data-table'
+        
+        # 增强列表项
+        for ul in soup.find_all('ul'):
+            # 检查是否是新闻列表
+            if any('新闻' in str(item) for item in ul.find_all('li')):
+                ul['class'] = 'news-list'
+        
+        # 增强链接
+        for a in soup.find_all('a'):
+            if not a.get('target'):
+                a['target'] = '_blank'
+                a['rel'] = 'noopener noreferrer'
+

applications/reporter/templates/custom_template_example.html

@@ -0,0 +1,50 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>自定义报告模板示例</title>
+    <style>
+        /* 自定义样式示例 */
+        body {
+            font-family: 'Microsoft YaHei', Arial, sans-serif;
+            background: #f0f2f5;
+            padding: 20px;
+            margin: 0;
+        }
+        
+        .container {
+            max-width: 1200px;
+            margin: 0 auto;
+            background: white;
+            padding: 30px;
+            border-radius: 8px;
+            box-shadow: 0 2px 8px rgba(0,0,0,0.1);
+        }
+        
+        /* 内容区域样式 */
+        #content {
+            line-height: 1.8;
+        }
+        
+        h1 {
+            color: #1890ff;
+            border-bottom: 2px solid #1890ff;
+            padding-bottom: 10px;
+        }
+        
+        h2 {
+            color: #333;
+            margin-top: 30px;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <!-- 占位符：内容将在这里插入 -->
+        <!-- 支持以下格式之一：{{content}} 或 {content} 或 <!-- content --> -->
+        {{content}}
+    </div>
+</body>
+</html>
+

applications/reporter/weekly.py

@@ -0,0 +1,139 @@
+"""
+周报生成器 - 生成7天内的汽车后市场情报报告
+"""
+import os
+import sys
+from datetime import datetime, timedelta
+from loguru import logger
+
+# 添加父目录到路径
+current_dir = os.path.dirname(os.path.abspath(__file__))
+parent_dir = os.path.dirname(os.path.dirname(current_dir))
+if parent_dir not in sys.path:
+    sys.path.insert(0, parent_dir)
+
+from applications.reporter.base_reporter import BaseReporter, AIAnalysisDataSource
+from applications.reporter.dingtalk_webhook import DingTalkWebhook
+from utils.mysql_agent import MySQLAgent
+from config import Config
+
+
+class WeeklyReporter(BaseReporter):
+    """周报生成器"""
+    
+    def __init__(self, dingtalk_webhook: str = None):
+        """
+        初始化周报生成器
+        
+        Args:
+            dingtalk_webhook: 钉钉Webhook地址（可选）
+        """
+        super().__init__()
+        # 初始化数据库连接
+        db_agent = MySQLAgent(Config.MYSQL_CONFIG)
+        # 添加AI分析结果数据源（已筛选是否相关=1）
+        self.add_data_source(AIAnalysisDataSource(db_agent))
+        self.logger = logger.bind(module="WeeklyReporter")
+        
+        # 初始化钉钉推送（如果提供了webhook）
+        self.dingtalk_webhook = dingtalk_webhook or getattr(Config, 'DINGTALK_WEBHOOK', None)
+        self.dingtalk_client = None
+        if self.dingtalk_webhook:
+            self.dingtalk_client = DingTalkWebhook(self.dingtalk_webhook)
+            self.logger.info("已启用钉钉推送功能")
+    
+    def generate(self, output_dir: str = "output/reports/weekly", 
+                 template_path: str = None,
+                 save_markdown: bool = True,
+                 send_dingtalk: bool = True) -> dict:
+        """
+        生成周报
+        
+        Args:
+            output_dir: 输出目录
+            template_path: 可选的外部HTML模板路径
+            save_markdown: 是否保存Markdown文件
+            send_dingtalk: 是否发送到钉钉
+            
+        Returns:
+            包含生成文件路径的字典
+        """
+        self.logger.info("开始生成周报")
+        
+        # 计算时间范围：7天内
+        end_time = datetime.now()
+        start_time = end_time - timedelta(days=7)
+        
+        self.logger.info(f"时间范围: {start_time.strftime('%Y-%m-%d %H:%M:%S')} 至 {end_time.strftime('%Y-%m-%d %H:%M:%S')}")
+        
+        # 收集数据
+        articles = self.collect_data(start_time, end_time)
+        
+        # 生成报告内容（generate_report_content会自动处理空数据情况）
+        markdown_content = f"""# 汽车后市场情报周报
+
+## 报告时间
+**生成时间**: {end_time.strftime('%Y-%m-%d %H:%M:%S')}
+**时间范围**: {start_time.strftime('%Y-%m-%d %H:%M:%S')} 至 {end_time.strftime('%Y-%m-%d %H:%M:%S')}
+
+{self.generate_report_content(articles, report_type="周报")}
+"""
+        
+        # 生成HTML报告
+        html_content = self.generate_html_report(markdown_content, template_path=template_path)
+        
+        # 保存报告
+        os.makedirs(output_dir, exist_ok=True)
+        timestamp = end_time.strftime('%Y%m%d_%H%M%S')
+        
+        result = {}
+        
+        # 保存HTML报告
+        html_filename = f"weekly_report_{timestamp}.html"
+        html_path = os.path.join(output_dir, html_filename)
+        self.save_report(html_content, html_path)
+        result['html_path'] = html_path
+        self.logger.info(f"HTML报告已保存: {html_path}")
+        
+        # 保存Markdown报告
+        markdown_path = None
+        if save_markdown:
+            markdown_filename = f"weekly_report_{timestamp}.md"
+            markdown_path = os.path.join(output_dir, markdown_filename)
+            self.save_markdown_report(markdown_content, markdown_path)
+            result['markdown_path'] = markdown_path
+            self.logger.info(f"Markdown报告已保存: {markdown_path}")
+        
+        # 发送到钉钉
+        if send_dingtalk and self.dingtalk_client:
+            title = f"汽车后市场情报周报 - {start_time.strftime('%Y-%m-%d')} 至 {end_time.strftime('%Y-%m-%d')}"
+            success = self.dingtalk_client.send_report(title, markdown_content, markdown_path)
+            result['dingtalk_sent'] = success
+            if success:
+                self.logger.info("报告已推送到钉钉群")
+            else:
+                self.logger.warning("报告推送到钉钉群失败")
+        
+        self.logger.info(f"周报生成完成")
+        return result
+
+
+def main():
+    """主函数"""
+    try:
+        reporter = WeeklyReporter()
+        result = reporter.generate()
+        print(f"周报已生成:")
+        print(f"  HTML: {result.get('html_path')}")
+        if 'markdown_path' in result:
+            print(f"  Markdown: {result.get('markdown_path')}")
+        if 'dingtalk_sent' in result:
+            print(f"  钉钉推送: {'成功' if result.get('dingtalk_sent') else '失败'}")
+    except Exception as e:
+        logger.error(f"生成周报失败: {str(e)}", exc_info=True)
+        raise
+
+
+if __name__ == "__main__":
+    main()
+

config.py

@@ -41,4 +41,10 @@ class Config:
         'delay': 1.5,  # 每条记录之间的延迟（秒），避免API限流
         'source_table': 'processed_rss_data',  # 源数据表
         'result_table': 'ai_processor_rss_analysis',  # AI分析结果表
-    }
+    }
+    
+    # 钉钉Webhook配置
+    # 优先从环境变量读取，如果没有则使用下面的默认值（需要用户自行配置）
+    # 请将下面的空字符串替换为你的钉钉Webhook地址，格式：https://oapi.dingtalk.com/robot/send?access_token=xxx
+    DINGTALK_WEBHOOK = os.getenv('DINGTALK_WEBHOOK', '')  # 钉钉机器人Webhook地址
+    # 例如：DINGTALK_WEBHOOK = os.getenv('DINGTALK_WEBHOOK', 'https://oapi.dingtalk.com/robot/send?access_token=your_token_here')

deploy/start.bat

@@ -0,0 +1,135 @@
+@echo off
+REM 情报数据处理系统 - 简化启动脚本
+REM 功能: Python环境检测 + 系统启动
+REM 作者: AI Assistant
+REM 版本: 1.0
+REM 日期: 2025-10-29
+chcp 65001 >nul
+
+setlocal enabledelayedexpansion
+
+REM 设置颜色
+for /f %%a in ('echo prompt $E ^| cmd') do set "ESC=%%a"
+set "GREEN=%ESC%[32m"
+set "RED=%ESC%[31m"
+set "YELLOW=%ESC%[33m"
+set "CYAN=%ESC%[36m"
+set "RESET=%ESC%[0m"
+
+REM 配置变量
+set "CONDA_ENV_NAME=intelligence_env"
+set "PROJECT_PATH=%~dp0.."
+set "PYTHON_VERSION=3.13"
+
+echo %CYAN%===============================================%RESET%
+echo %CYAN%    情报数据处理系统启动器%RESET%
+echo %CYAN%===============================================%RESET%
+echo.
+
+REM 检查项目路径
+if not exist "%PROJECT_PATH%\main.py" (
+    echo %RED%错误: 项目路径不存在或main.py文件未找到%RESET%
+    echo %YELLOW%当前路径: %PROJECT_PATH%%RESET%
+    pause
+    exit /b 1
+)
+
+echo %GREEN%✓ 项目路径检查通过%RESET%
+
+REM 检查Python是否安装
+echo %CYAN%检查Python环境...%RESET%
+python --version >nul 2>&1
+if %errorLevel% neq 0 (
+    echo %RED%Python未安装或未添加到PATH%RESET%
+    echo %YELLOW%正在尝试检测Anaconda...%RESET%
+    
+    REM 检查Anaconda
+    where conda >nul 2>&1
+    if %errorLevel% neq 0 (
+        echo %RED%Anaconda未安装%RESET%
+        echo %YELLOW%请安装Python或Anaconda后重试%RESET%
+        echo %CYAN%下载地址: https://www.python.org/downloads/%RESET%
+        echo %CYAN%或: https://www.anaconda.com/products/distribution%RESET%
+        pause
+        exit /b 1
+    ) else (
+        echo %GREEN%✓ 检测到Anaconda%RESET%
+        conda --version
+    )
+) else (
+    echo %GREEN%✓ Python已安装%RESET%
+    python --version
+)
+
+REM 检查Conda环境
+echo %CYAN%检查Conda环境: %CONDA_ENV_NAME%%RESET%
+conda env list | findstr /i "%CONDA_ENV_NAME%" >nul 2>&1
+if %errorLevel% neq 0 (
+    echo %YELLOW%环境不存在，正在创建...%RESET%
+    conda create -n %CONDA_ENV_NAME% python=%PYTHON_VERSION% -y
+    if %errorLevel% neq 0 (
+        echo %RED%环境创建失败%RESET%
+        pause
+        exit /b 1
+    )
+    echo %GREEN%✓ 环境创建成功%RESET%
+) else (
+    echo %GREEN%✓ 环境已存在%RESET%
+)
+
+REM 激活环境
+echo %CYAN%激活Conda环境...%RESET%
+call conda activate %CONDA_ENV_NAME%
+if %errorLevel% neq 0 (
+    echo %RED%环境激活失败%RESET%
+    pause
+    exit /b 1
+)
+echo %GREEN%✓ 环境激活成功%RESET%
+
+REM 检查依赖
+echo %CYAN%检查Python依赖...%RESET%
+if exist "%PROJECT_PATH%\requirements.txt" (
+    echo %YELLOW%安装/更新依赖包...%RESET%
+    pip install -r "%PROJECT_PATH%\requirements.txt" --quiet
+    if %errorLevel% neq 0 (
+        echo %YELLOW%依赖安装失败，尝试继续运行...%RESET%
+    ) else (
+        echo %GREEN%✓ 依赖安装完成%RESET%
+    )
+) else (
+    echo %YELLOW%未找到requirements.txt，跳过依赖安装%RESET%
+)
+
+REM 切换到项目目录
+echo %CYAN%切换到项目目录: %PROJECT_PATH%%RESET%
+cd /d "%PROJECT_PATH%"
+
+REM 检查配置文件
+if not exist "config.py" (
+    echo %YELLOW%警告: 未找到config.py配置文件%RESET%
+    echo %CYAN%将使用默认配置运行%RESET%
+)
+
+REM 显示启动信息
+echo.
+echo %GREEN%===============================================%RESET%
+echo %GREEN%    启动情报数据处理系统%RESET%
+echo %GREEN%===============================================%RESET%
+echo.
+echo %CYAN%环境信息:%RESET%
+echo   Conda环境: %CONDA_ENV_NAME%
+echo   项目路径: %PROJECT_PATH%
+echo   Python版本: 
+python --version
+echo.
+echo %YELLOW%按 Ctrl+C 停止系统%RESET%
+echo.
+
+REM 启动系统
+echo %CYAN%启动情报数据处理系统主程序...%RESET%
+python main.py
+
+echo.
+echo %CYAN%情报数据处理系统已停止%RESET%
+pause

logs/application.log

@@ -133927,3 +133927,112 @@
     → module: 'RSSDataAIProcessor'
 2025-10-29 10:30:40.130 | DEBUG    | ai_processor_rss_data:112 - 处理记录 182 (2/3)
     → module: 'RSSDataAIProcessor'
+2025-10-29 17:34:56.620 | INFO     | base_reporter:329 - 添加数据源: AI分析结果
+    → module: 'BaseReporter'
+2025-10-29 17:34:56.621 | INFO     | daily:42 - 开始生成日报
+    → module: 'DailyReporter'
+2025-10-29 17:34:56.621 | INFO     | daily:48 - 时间范围: 2025-10-28 17:34:56 至 2025-10-29 17:34:56
+    → module: 'DailyReporter'
+2025-10-29 17:34:56.621 | DEBUG    | mysql_agent:116 - 执行SQL查询
+    → module: 'MySQLAgent(Windows)'
+    → sql: '\n                SELECT \n                    `文章标题` as title,\n                    `文章链接` as link,\n                    `文章摘要` as summary,\n                    `发布时间` as publish_time,\n                    `来源URL` as source_url,\n                    `分类` as category,\n                    `标签` as tags,\n                    `相关度评分` as relevance_score,\n                    `分析说明` as analysis_note,\n                    `处理时间` as process_time\n                FROM `ai_processor_rss_analysis`\n  ...
+2025-10-29 17:34:57.326 | INFO     | base_reporter:130 - 时间范围 2025-10-28 17:34:56.621364 到 2025-10-29 17:34:56.621364 内没有相关数据（是否相关=1）
+    → module: 'AIAnalysisDataSource'
+2025-10-29 17:34:57.329 | ERROR    | daily:83 - 生成日报失败: No module named 'markdown'
+    → exc_info: True
+2025-10-29 17:35:46.546 | INFO     | base_reporter:329 - 添加数据源: AI分析结果
+    → module: 'BaseReporter'
+2025-10-29 17:35:46.547 | INFO     | daily:42 - 开始生成日报
+    → module: 'DailyReporter'
+2025-10-29 17:35:46.547 | INFO     | daily:48 - 时间范围: 2025-10-28 17:35:46 至 2025-10-29 17:35:46
+    → module: 'DailyReporter'
+2025-10-29 17:35:46.547 | DEBUG    | mysql_agent:116 - 执行SQL查询
+    → module: 'MySQLAgent(Windows)'
+    → sql: '\n                SELECT \n                    `文章标题` as title,\n                    `文章链接` as link,\n                    `文章摘要` as summary,\n                    `发布时间` as publish_time,\n                    `来源URL` as source_url,\n                    `分类` as category,\n                    `标签` as tags,\n                    `相关度评分` as relevance_score,\n                    `分析说明` as analysis_note,\n                    `处理时间` as process_time\n                FROM `ai_processor_rss_analysis`\n  ...
+2025-10-29 17:35:47.054 | INFO     | base_reporter:130 - 时间范围 2025-10-28 17:35:46.547444 到 2025-10-29 17:35:46.547444 内没有相关数据（是否相关=1）
+    → module: 'AIAnalysisDataSource'
+2025-10-29 17:35:47.358 | INFO     | base_reporter:449 - 报告已保存到: output/reports/daily\daily_report_20251029_173546.html
+    → module: 'DailyReporter'
+2025-10-29 17:35:47.360 | INFO     | daily:72 - 日报生成完成: output/reports/daily\daily_report_20251029_173546.html
+    → module: 'DailyReporter'
+2025-10-29 17:36:37.665 | INFO     | base_reporter:329 - 添加数据源: AI分析结果
+    → module: 'BaseReporter'
+2025-10-29 17:36:37.666 | INFO     | weekly:42 - 开始生成周报
+    → module: 'WeeklyReporter'
+2025-10-29 17:36:37.666 | INFO     | weekly:48 - 时间范围: 2025-10-22 17:36:37 至 2025-10-29 17:36:37
+    → module: 'WeeklyReporter'
+2025-10-29 17:36:37.667 | DEBUG    | mysql_agent:116 - 执行SQL查询
+    → module: 'MySQLAgent(Windows)'
+    → sql: '\n                SELECT \n                    `文章标题` as title,\n                    `文章链接` as link,\n                    `文章摘要` as summary,\n                    `发布时间` as publish_time,\n                    `来源URL` as source_url,\n                    `分类` as category,\n                    `标签` as tags,\n                    `相关度评分` as relevance_score,\n                    `分析说明` as analysis_note,\n                    `处理时间` as process_time\n                FROM `ai_processor_rss_analysis`\n  ...
+2025-10-29 17:36:38.112 | INFO     | base_reporter:135 - 获取到 1 条相关数据（是否相关=1）
+    → module: 'AIAnalysisDataSource'
+2025-10-29 17:36:38.234 | INFO     | base_reporter:449 - 报告已保存到: output/reports/weekly\weekly_report_20251029_173637.html
+    → module: 'WeeklyReporter'
+2025-10-29 17:36:38.235 | INFO     | weekly:72 - 周报生成完成: output/reports/weekly\weekly_report_20251029_173637.html
+    → module: 'WeeklyReporter'
+2025-10-30 13:47:56.057 | INFO     | task_scheduler:27 - 任务调度器已初始化，最大工作线程数: 5
+    → module: 'TaskScheduler'
+2025-10-30 13:48:20.079 | DEBUG    | mysql_agent:116 - 执行SQL查询
+    → module: 'MySQLAgent(Windows)'
+    → sql: 'SELECT * FROM main_task WHERE task_id = %s'
+2025-10-30 13:48:20.346 | INFO     | mysql_agent:134 - 查询执行成功
+    → module: 'MySQLAgent(Windows)'
+    → 行数: 1
+2025-10-30 13:48:20.349 | ERROR    | 1757831752:141 - 任务执行失败: RSS基于规则数据处理
+    → module: 'TaskNotebook'
+2025-10-30 13:56:55.700 | DEBUG    | mysql_agent:116 - 执行SQL查询
+    → module: 'MySQLAgent(Windows)'
+    → sql: 'SELECT * FROM main_task WHERE task_id = %s'
+2025-10-30 13:56:55.939 | INFO     | mysql_agent:134 - 查询执行成功
+    → module: 'MySQLAgent(Windows)'
+    → 行数: 1
+2025-10-30 13:56:55.941 | ERROR    | 1757831752:141 - 任务执行失败: RSS基于规则数据处理
+    → module: 'TaskNotebook'
+2025-10-30 13:57:07.496 | INFO     | task_scheduler:27 - 任务调度器已初始化，最大工作线程数: 5
+    → module: 'TaskScheduler'
+2025-10-30 13:57:10.827 | DEBUG    | mysql_agent:116 - 执行SQL查询
+    → module: 'MySQLAgent(Windows)'
+    → sql: 'SELECT * FROM main_task WHERE task_id = %s'
+2025-10-30 13:57:11.121 | INFO     | mysql_agent:134 - 查询执行成功
+    → module: 'MySQLAgent(Windows)'
+    → 行数: 1
+2025-10-30 13:57:11.125 | ERROR    | 1757831752:141 - 任务执行失败: RSS基于规则数据处理
+    → module: 'TaskNotebook'
+2025-10-30 13:57:49.005 | DEBUG    | mysql_agent:116 - 执行SQL查询
+    → module: 'MySQLAgent(Windows)'
+    → sql: 'SELECT * FROM main_task WHERE task_id = %s'
+2025-10-30 13:57:49.286 | INFO     | mysql_agent:134 - 查询执行成功
+    → module: 'MySQLAgent(Windows)'
+    → 行数: 1
+2025-10-30 13:57:49.737 | INFO     | processor_rss_data:65 - RSS数据处理器初始化完成
+    → module: 'RSSDataProcessor'
+2025-10-30 13:57:49.738 | INFO     | processor_rss_data:335 - 开始处理RSS数据...
+    → module: 'RSSDataProcessor'
+2025-10-30 13:57:49.740 | DEBUG    | mysql_agent:116 - 执行SQL查询
+    → module: 'MySQLAgent(Windows)'
+    → sql: '\n            SELECT id, 文章标题, 文章摘要, 发布时间, 来源URL, 文章链接\n            FROM collector_rss_subscriptions\n            WHERE 是否已处理 = 0\n            ORDER BY 发布时间 DESC\n            LIMIT %s\n            '
+2025-10-30 13:57:50.013 | INFO     | processor_rss_data:107 - 成功加载 6 条未处理的RSS数据
+    → module: 'RSSDataProcessor'
+2025-10-30 13:57:50.014 | INFO     | processor_rss_data:146 - 成功加载停用词表，共 98 个词
+    → module: 'RSSDataProcessor'
+2025-10-30 13:57:50.015 | INFO     | processor_rss_data:82 - 成功加载汽车后市场关键词，共 37 个
+    → module: 'RSSDataProcessor'
+2025-10-30 13:57:50.899 | INFO     | processor_rss_data:235 - 数据处理完成，共处理 6 条记录
+    → module: 'RSSDataProcessor'
+2025-10-30 13:57:50.905 | INFO     | processor_rss_data:246 - 过滤出 0 条汽车后市场相关新闻
+    → module: 'RSSDataProcessor'
+2025-10-30 13:57:51.015 | DEBUG    | mysql_agent:614 - 更新执行完成
+    → module: 'MySQLAgent(Windows)'
+    → 受影响行数: 6
+2025-10-30 13:57:51.015 | INFO     | processor_rss_data:129 - 成功标记 6 条数据为已处理
+    → module: 'RSSDataProcessor'
+2025-10-30 13:57:51.016 | INFO     | processor_rss_data:372 - RSS数据处理完成
+    → module: 'RSSDataProcessor'
+    → total_articles: 6
+    → filtered_articles: 0
+    → filter_rate: 0.0
+    → processing_time: '2025-10-30 13:57:50'
+    → mark_success: True
+2025-10-30 13:57:53.702 | DEBUG    | mysql_agent:614 - 更新执行完成
+    → module: 'MySQLAgent(Windows)'
+    → 受影响行数: 1

logs/errors.log

@@ -71071,3 +71071,747 @@ Traceback (most recent call last):
                               └ 'RSSDataProcessor'
 
 AttributeError: 类 RSSDataProcessor 中未找到方法 main
+2025-10-29 17:34:57.329 | ERROR | daily:83 - 生成日报失败: No module named 'markdown'
+    → exc_info: True
+
+2025-10-30 13:48:20.349 | ERROR | 1757831752:141 - 任务执行失败: RSS基于规则数据处理
+    → module: 'TaskNotebook'
+Traceback (most recent call last):
+
+  File "<frozen runpy>", line 198, in _run_module_as_main
+  File "<frozen runpy>", line 88, in _run_code
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel_launcher.py", line 18, in <module>
+    app.launch_new_instance()
+    │   └ <bound method Application.launch_instance of <class 'ipykernel.kernelapp.IPKernelApp'>>
+    └ <module 'ipykernel.kernelapp' from 'd:\\ProgramTools\\anaconda3\\envs\\intelligence_system\\Lib\\site-packages\\ipykernel\\ke...
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\traitlets\config\application.py", line 1075, in launch_instance
+    app.start()
+    │   └ <function IPKernelApp.start at 0x00000241EF7C0D60>
+    └ <ipykernel.kernelapp.IPKernelApp object at 0x00000241EB5B7D10>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelapp.py", line 739, in start
+    self.io_loop.start()
+    │    │       └ <function BaseAsyncIOLoop.start at 0x00000241EF7C1C60>
+    │    └ <tornado.platform.asyncio.AsyncIOMainLoop object at 0x00000241EF7AAD20>
+    └ <ipykernel.kernelapp.IPKernelApp object at 0x00000241EB5B7D10>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\tornado\platform\asyncio.py", line 211, in start
+    self.asyncio_loop.run_forever()
+    │    │            └ <function BaseEventLoop.run_forever at 0x00000241EDB7B920>
+    │    └ <_WindowsSelectorEventLoop running=True closed=False debug=False>
+    └ <tornado.platform.asyncio.AsyncIOMainLoop object at 0x00000241EF7AAD20>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\base_events.py", line 645, in run_forever
+    self._run_once()
+    │    └ <function BaseEventLoop._run_once at 0x00000241EDB7D760>
+    └ <_WindowsSelectorEventLoop running=True closed=False debug=False>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\base_events.py", line 1999, in _run_once
+    handle._run()
+    │      └ <function Handle._run at 0x00000241ED6E9D00>
+    └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\events.py", line 88, in _run
+    self._context.run(self._callback, *self._args)
+    │    │            │    │           │    └ <member '_args' of 'Handle' objects>
+    │    │            │    │           └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+    │    │            │    └ <member '_callback' of 'Handle' objects>
+    │    │            └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+    │    └ <member '_context' of 'Handle' objects>
+    └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 519, in dispatch_queue
+    await self.process_one()
+          │    └ <function Kernel.process_one at 0x00000241EF781D00>
+          └ <ipykernel.ipkernel.IPythonKernel object at 0x00000241EF7AAD80>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 508, in process_one
+    await dispatch(*args)
+          │         └ ([<zmq.Frame(b'be29372e-391'...36B)>, <zmq.Frame(b'<IDS|MSG>')>, <zmq.Frame(b'ddbb9c4d44b6'...64B)>, <zmq.Frame(b'{"date":"20...
+          └ <bound method Kernel.dispatch_shell of <ipykernel.ipkernel.IPythonKernel object at 0x00000241EF7AAD80>>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 400, in dispatch_shell
+    await result
+          └ <coroutine object IPythonKernel.execute_request at 0x00000241F0E71E40>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\ipkernel.py", line 368, in execute_request
+    await super().execute_request(stream, ident, parent)
+                                  │       │      └ {'header': {'date': datetime.datetime(2025, 10, 30, 5, 48, 20, 70000, tzinfo=tzutc()), 'msg_id': '7653bb92-3d92-4584-b5fd-f30...
+                                  │       └ [b'be29372e-3914-4138-ba04-8dcacb3dcfbe']
+                                  └ <zmq.eventloop.zmqstream.ZMQStream object at 0x00000241EF7AB140>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 767, in execute_request
+    reply_content = await reply_content
+                          └ <coroutine object IPythonKernel.do_execute at 0x00000241EF6F5B40>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\ipkernel.py", line 455, in do_execute
+    res = shell.run_cell(
+          │     └ <function ZMQInteractiveShell.run_cell at 0x00000241EF7ADDA0>
+          └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\zmqshell.py", line 577, in run_cell
+    return super().run_cell(*args, **kwargs)
+                             │       └ {'store_history': True, 'silent': False, 'cell_id': 'vscode-notebook-cell:/d%3A/Idea%20Project/intelligence_system/tools/task...
+                             └ ('# 手动执行任务（异步方式，快速返回）\ndef run_task_manually(task_id):\n    display(Markdown(f"### 正在手动执行任务ID {task_id}..."))\n    success = ...
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3098, in run_cell
+    result = self._run_cell(
+             │    └ <function InteractiveShell._run_cell at 0x00000241EEDFA200>
+             └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3153, in _run_cell
+    result = runner(coro)
+             │      └ <coroutine object InteractiveShell.run_cell_async at 0x00000241F0E1B5E0>
+             └ <function _pseudo_sync_runner at 0x00000241EEDD5260>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\async_helpers.py", line 128, in _pseudo_sync_runner
+    coro.send(None)
+    │    └ <method 'send' of 'coroutine' objects>
+    └ <coroutine object InteractiveShell.run_cell_async at 0x00000241F0E1B5E0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3362, in run_cell_async
+    has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
+                       │    │             │        │     └ 'C:\\Users\\zy187\\AppData\\Local\\Temp\\ipykernel_15044\\1819114417.py'
+                       │    │             │        └ [<ast.FunctionDef object at 0x00000241F101DA90>, <ast.FunctionDef object at 0x00000241F101D890>, <ast.Expr object at 0x000002...
+                       │    │             └ <ast.Module object at 0x00000241F101DA50>
+                       │    └ <function InteractiveShell.run_ast_nodes at 0x00000241EEDFA5C0>
+                       └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3607, in run_ast_nodes
+    if await self.run_code(code, result, async_=asy):
+             │    │        │     │              └ False
+             │    │        │     └ <ExecutionResult object at 24191c224e0, execution_count=2 error_before_exec=None error_in_exec=None info=<ExecutionInfo objec...
+             │    │        └ <code object <module> at 0x0000024191C1D610, file "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 1>
+             │    └ <function InteractiveShell.run_code at 0x00000241EEDFA660>
+             └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3667, in run_code
+    exec(code_obj, self.user_global_ns, self.user_ns)
+         │         │    │               │    └ <property object at 0x00000241EEDF4B30>
+         │         │    │               └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+         │         │    └ <property object at 0x00000241EEDF4BD0>
+         │         └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+         └ <code object <module> at 0x0000024191C1D610, file "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 1>
+
+  File "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 45, in <module>
+    run_task_with_details(2)
+    └ <function run_task_with_details at 0x0000024191C38C20>
+
+  File "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 16, in run_task_with_details
+    result = manager.run_task_synchronously(task_id)
+             │       │                      └ 2
+             │       └ <function TaskManager.run_task_synchronously at 0x0000024191C38EA0>
+             └ <__main__.TaskManager object at 0x00000241919D6AB0>
+
+> File "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1757831752.py", line 122, in run_task_synchronously
+    self.scheduler._execute_task_logic(task)
+    │    │         │                   └ {'task_id': 2, 'task_name': 'RSS基于规则数据处理', 'task_type': 'processor', 'module_path': 'processors.processor_rss_data', 'cron_ex...
+    │    │         └ <function TaskScheduler._execute_task_logic at 0x0000024191C3F920>
+    │    └ <system_management.scheduler.task_scheduler.TaskScheduler object at 0x00000241FF4E9700>
+    └ <__main__.TaskManager object at 0x00000241919D6AB0>
+
+  File "d:\Idea Project\intelligence_system\system_management\scheduler\task_scheduler.py", line 278, in _execute_task_logic
+    raise AttributeError(f"模块 {module_name} 中未找到类 {class_name}")
+                               │                   └ 'processor_rss_data'
+                               └ 'processors'
+
+AttributeError: 模块 processors 中未找到类 processor_rss_data
+
+Traceback (most recent call last):
+
+  File "<frozen runpy>", line 198, in _run_module_as_main
+  File "<frozen runpy>", line 88, in _run_code
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel_launcher.py", line 18, in <module>
+    app.launch_new_instance()
+    │   └ <bound method Application.launch_instance of <class 'ipykernel.kernelapp.IPKernelApp'>>
+    └ <module 'ipykernel.kernelapp' from 'd:\\ProgramTools\\anaconda3\\envs\\intelligence_system\\Lib\\site-packages\\ipykernel\\ke...
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\traitlets\config\application.py", line 1075, in launch_instance
+    app.start()
+    │   └ <function IPKernelApp.start at 0x00000241EF7C0D60>
+    └ <ipykernel.kernelapp.IPKernelApp object at 0x00000241EB5B7D10>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelapp.py", line 739, in start
+    self.io_loop.start()
+    │    │       └ <function BaseAsyncIOLoop.start at 0x00000241EF7C1C60>
+    │    └ <tornado.platform.asyncio.AsyncIOMainLoop object at 0x00000241EF7AAD20>
+    └ <ipykernel.kernelapp.IPKernelApp object at 0x00000241EB5B7D10>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\tornado\platform\asyncio.py", line 211, in start
+    self.asyncio_loop.run_forever()
+    │    │            └ <function BaseEventLoop.run_forever at 0x00000241EDB7B920>
+    │    └ <_WindowsSelectorEventLoop running=True closed=False debug=False>
+    └ <tornado.platform.asyncio.AsyncIOMainLoop object at 0x00000241EF7AAD20>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\base_events.py", line 645, in run_forever
+    self._run_once()
+    │    └ <function BaseEventLoop._run_once at 0x00000241EDB7D760>
+    └ <_WindowsSelectorEventLoop running=True closed=False debug=False>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\base_events.py", line 1999, in _run_once
+    handle._run()
+    │      └ <function Handle._run at 0x00000241ED6E9D00>
+    └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\events.py", line 88, in _run
+    self._context.run(self._callback, *self._args)
+    │    │            │    │           │    └ <member '_args' of 'Handle' objects>
+    │    │            │    │           └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+    │    │            │    └ <member '_callback' of 'Handle' objects>
+    │    │            └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+    │    └ <member '_context' of 'Handle' objects>
+    └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 519, in dispatch_queue
+    await self.process_one()
+          │    └ <function Kernel.process_one at 0x00000241EF781D00>
+          └ <ipykernel.ipkernel.IPythonKernel object at 0x00000241EF7AAD80>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 508, in process_one
+    await dispatch(*args)
+          │         └ ([<zmq.Frame(b'be29372e-391'...36B)>, <zmq.Frame(b'<IDS|MSG>')>, <zmq.Frame(b'ddbb9c4d44b6'...64B)>, <zmq.Frame(b'{"date":"20...
+          └ <bound method Kernel.dispatch_shell of <ipykernel.ipkernel.IPythonKernel object at 0x00000241EF7AAD80>>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 400, in dispatch_shell
+    await result
+          └ <coroutine object IPythonKernel.execute_request at 0x00000241F0E71E40>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\ipkernel.py", line 368, in execute_request
+    await super().execute_request(stream, ident, parent)
+                                  │       │      └ {'header': {'date': datetime.datetime(2025, 10, 30, 5, 48, 20, 70000, tzinfo=tzutc()), 'msg_id': '7653bb92-3d92-4584-b5fd-f30...
+                                  │       └ [b'be29372e-3914-4138-ba04-8dcacb3dcfbe']
+                                  └ <zmq.eventloop.zmqstream.ZMQStream object at 0x00000241EF7AB140>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 767, in execute_request
+    reply_content = await reply_content
+                          └ <coroutine object IPythonKernel.do_execute at 0x00000241EF6F5B40>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\ipkernel.py", line 455, in do_execute
+    res = shell.run_cell(
+          │     └ <function ZMQInteractiveShell.run_cell at 0x00000241EF7ADDA0>
+          └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\zmqshell.py", line 577, in run_cell
+    return super().run_cell(*args, **kwargs)
+                             │       └ {'store_history': True, 'silent': False, 'cell_id': 'vscode-notebook-cell:/d%3A/Idea%20Project/intelligence_system/tools/task...
+                             └ ('# 手动执行任务（异步方式，快速返回）\ndef run_task_manually(task_id):\n    display(Markdown(f"### 正在手动执行任务ID {task_id}..."))\n    success = ...
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3098, in run_cell
+    result = self._run_cell(
+             │    └ <function InteractiveShell._run_cell at 0x00000241EEDFA200>
+             └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3153, in _run_cell
+    result = runner(coro)
+             │      └ <coroutine object InteractiveShell.run_cell_async at 0x00000241F0E1B5E0>
+             └ <function _pseudo_sync_runner at 0x00000241EEDD5260>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\async_helpers.py", line 128, in _pseudo_sync_runner
+    coro.send(None)
+    │    └ <method 'send' of 'coroutine' objects>
+    └ <coroutine object InteractiveShell.run_cell_async at 0x00000241F0E1B5E0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3362, in run_cell_async
+    has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
+                       │    │             │        │     └ 'C:\\Users\\zy187\\AppData\\Local\\Temp\\ipykernel_15044\\1819114417.py'
+                       │    │             │        └ [<ast.FunctionDef object at 0x00000241F101DA90>, <ast.FunctionDef object at 0x00000241F101D890>, <ast.Expr object at 0x000002...
+                       │    │             └ <ast.Module object at 0x00000241F101DA50>
+                       │    └ <function InteractiveShell.run_ast_nodes at 0x00000241EEDFA5C0>
+                       └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3607, in run_ast_nodes
+    if await self.run_code(code, result, async_=asy):
+             │    │        │     │              └ False
+             │    │        │     └ <ExecutionResult object at 24191c224e0, execution_count=2 error_before_exec=None error_in_exec=None info=<ExecutionInfo objec...
+             │    │        └ <code object <module> at 0x0000024191C1D610, file "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 1>
+             │    └ <function InteractiveShell.run_code at 0x00000241EEDFA660>
+             └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3667, in run_code
+    exec(code_obj, self.user_global_ns, self.user_ns)
+         │         │    │               │    └ <property object at 0x00000241EEDF4B30>
+         │         │    │               └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+         │         │    └ <property object at 0x00000241EEDF4BD0>
+         │         └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+         └ <code object <module> at 0x0000024191C1D610, file "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 1>
+
+  File "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 45, in <module>
+    run_task_with_details(2)
+    └ <function run_task_with_details at 0x0000024191C38C20>
+
+  File "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 16, in run_task_with_details
+    result = manager.run_task_synchronously(task_id)
+             │       │                      └ 2
+             │       └ <function TaskManager.run_task_synchronously at 0x0000024191C38EA0>
+             └ <__main__.TaskManager object at 0x00000241919D6AB0>
+
+> File "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1757831752.py", line 122, in run_task_synchronously
+    self.scheduler._execute_task_logic(task)
+    │    │         │                   └ {'task_id': 2, 'task_name': 'RSS基于规则数据处理', 'task_type': 'processor', 'module_path': 'processors.processor_rss_data', 'cron_ex...
+    │    │         └ <function TaskScheduler._execute_task_logic at 0x0000024191C3F920>
+    │    └ <system_management.scheduler.task_scheduler.TaskScheduler object at 0x00000241FF4E9700>
+    └ <__main__.TaskManager object at 0x00000241919D6AB0>
+
+  File "d:\Idea Project\intelligence_system\system_management\scheduler\task_scheduler.py", line 278, in _execute_task_logic
+    raise AttributeError(f"模块 {module_name} 中未找到类 {class_name}")
+                               │                   └ 'processor_rss_data'
+                               └ 'processors'
+
+AttributeError: 模块 processors 中未找到类 processor_rss_data
+2025-10-30 13:56:55.941 | ERROR | 1757831752:141 - 任务执行失败: RSS基于规则数据处理
+    → module: 'TaskNotebook'
+Traceback (most recent call last):
+
+  File "<frozen runpy>", line 198, in _run_module_as_main
+  File "<frozen runpy>", line 88, in _run_code
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel_launcher.py", line 18, in <module>
+    app.launch_new_instance()
+    │   └ <bound method Application.launch_instance of <class 'ipykernel.kernelapp.IPKernelApp'>>
+    └ <module 'ipykernel.kernelapp' from 'd:\\ProgramTools\\anaconda3\\envs\\intelligence_system\\Lib\\site-packages\\ipykernel\\ke...
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\traitlets\config\application.py", line 1075, in launch_instance
+    app.start()
+    │   └ <function IPKernelApp.start at 0x00000241EF7C0D60>
+    └ <ipykernel.kernelapp.IPKernelApp object at 0x00000241EB5B7D10>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelapp.py", line 739, in start
+    self.io_loop.start()
+    │    │       └ <function BaseAsyncIOLoop.start at 0x00000241EF7C1C60>
+    │    └ <tornado.platform.asyncio.AsyncIOMainLoop object at 0x00000241EF7AAD20>
+    └ <ipykernel.kernelapp.IPKernelApp object at 0x00000241EB5B7D10>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\tornado\platform\asyncio.py", line 211, in start
+    self.asyncio_loop.run_forever()
+    │    │            └ <function BaseEventLoop.run_forever at 0x00000241EDB7B920>
+    │    └ <_WindowsSelectorEventLoop running=True closed=False debug=False>
+    └ <tornado.platform.asyncio.AsyncIOMainLoop object at 0x00000241EF7AAD20>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\base_events.py", line 645, in run_forever
+    self._run_once()
+    │    └ <function BaseEventLoop._run_once at 0x00000241EDB7D760>
+    └ <_WindowsSelectorEventLoop running=True closed=False debug=False>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\base_events.py", line 1999, in _run_once
+    handle._run()
+    │      └ <function Handle._run at 0x00000241ED6E9D00>
+    └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\events.py", line 88, in _run
+    self._context.run(self._callback, *self._args)
+    │    │            │    │           │    └ <member '_args' of 'Handle' objects>
+    │    │            │    │           └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+    │    │            │    └ <member '_callback' of 'Handle' objects>
+    │    │            └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+    │    └ <member '_context' of 'Handle' objects>
+    └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 519, in dispatch_queue
+    await self.process_one()
+          │    └ <function Kernel.process_one at 0x00000241EF781D00>
+          └ <ipykernel.ipkernel.IPythonKernel object at 0x00000241EF7AAD80>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 508, in process_one
+    await dispatch(*args)
+          │         └ ([<zmq.Frame(b'be29372e-391'...36B)>, <zmq.Frame(b'<IDS|MSG>')>, <zmq.Frame(b'36f03038e4ef'...64B)>, <zmq.Frame(b'{"date":"20...
+          └ <bound method Kernel.dispatch_shell of <ipykernel.ipkernel.IPythonKernel object at 0x00000241EF7AAD80>>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 400, in dispatch_shell
+    await result
+          └ <coroutine object IPythonKernel.execute_request at 0x0000024191C6BC40>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\ipkernel.py", line 368, in execute_request
+    await super().execute_request(stream, ident, parent)
+                                  │       │      └ {'header': {'date': datetime.datetime(2025, 10, 30, 5, 56, 55, 692000, tzinfo=tzutc()), 'msg_id': '788ee0fd-a13f-4e53-98b0-e9...
+                                  │       └ [b'be29372e-3914-4138-ba04-8dcacb3dcfbe']
+                                  └ <zmq.eventloop.zmqstream.ZMQStream object at 0x00000241EF7AB140>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 767, in execute_request
+    reply_content = await reply_content
+                          └ <coroutine object IPythonKernel.do_execute at 0x00000241F0DB22C0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\ipkernel.py", line 455, in do_execute
+    res = shell.run_cell(
+          │     └ <function ZMQInteractiveShell.run_cell at 0x00000241EF7ADDA0>
+          └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\zmqshell.py", line 577, in run_cell
+    return super().run_cell(*args, **kwargs)
+                             │       └ {'store_history': True, 'silent': False, 'cell_id': 'vscode-notebook-cell:/d%3A/Idea%20Project/intelligence_system/tools/task...
+                             └ ('# 手动执行任务（异步方式，快速返回）\ndef run_task_manually(task_id):\n    display(Markdown(f"### 正在手动执行任务ID {task_id}..."))\n    success = ...
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3098, in run_cell
+    result = self._run_cell(
+             │    └ <function InteractiveShell._run_cell at 0x00000241EEDFA200>
+             └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3153, in _run_cell
+    result = runner(coro)
+             │      └ <coroutine object InteractiveShell.run_cell_async at 0x0000024191A23AC0>
+             └ <function _pseudo_sync_runner at 0x00000241EEDD5260>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\async_helpers.py", line 128, in _pseudo_sync_runner
+    coro.send(None)
+    │    └ <method 'send' of 'coroutine' objects>
+    └ <coroutine object InteractiveShell.run_cell_async at 0x0000024191A23AC0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3362, in run_cell_async
+    has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
+                       │    │             │        │     └ 'C:\\Users\\zy187\\AppData\\Local\\Temp\\ipykernel_15044\\1819114417.py'
+                       │    │             │        └ [<ast.FunctionDef object at 0x0000024191E00090>, <ast.FunctionDef object at 0x00000241F1027390>, <ast.Expr object at 0x000002...
+                       │    │             └ <ast.Module object at 0x0000024191E00050>
+                       │    └ <function InteractiveShell.run_ast_nodes at 0x00000241EEDFA5C0>
+                       └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3607, in run_ast_nodes
+    if await self.run_code(code, result, async_=asy):
+             │    │        │     │              └ False
+             │    │        │     └ <ExecutionResult object at 24191c22900, execution_count=3 error_before_exec=None error_in_exec=None info=<ExecutionInfo objec...
+             │    │        └ <code object <module> at 0x0000024191CC1DF0, file "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 1>
+             │    └ <function InteractiveShell.run_code at 0x00000241EEDFA660>
+             └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3667, in run_code
+    exec(code_obj, self.user_global_ns, self.user_ns)
+         │         │    │               │    └ <property object at 0x00000241EEDF4B30>
+         │         │    │               └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+         │         │    └ <property object at 0x00000241EEDF4BD0>
+         │         └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+         └ <code object <module> at 0x0000024191CC1DF0, file "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 1>
+
+  File "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 45, in <module>
+    run_task_with_details(2)
+    └ <function run_task_with_details at 0x0000024191C38CC0>
+
+  File "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 16, in run_task_with_details
+    result = manager.run_task_synchronously(task_id)
+             │       │                      └ 2
+             │       └ <function TaskManager.run_task_synchronously at 0x0000024191C38EA0>
+             └ <__main__.TaskManager object at 0x00000241919D6AB0>
+
+> File "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1757831752.py", line 122, in run_task_synchronously
+    self.scheduler._execute_task_logic(task)
+    │    │         │                   └ {'task_id': 2, 'task_name': 'RSS基于规则数据处理', 'task_type': 'processor', 'module_path': 'processors.processor_rss_data', 'cron_ex...
+    │    │         └ <function TaskScheduler._execute_task_logic at 0x0000024191C3F920>
+    │    └ <system_management.scheduler.task_scheduler.TaskScheduler object at 0x00000241FF4E9700>
+    └ <__main__.TaskManager object at 0x00000241919D6AB0>
+
+  File "d:\Idea Project\intelligence_system\system_management\scheduler\task_scheduler.py", line 278, in _execute_task_logic
+    raise AttributeError(f"模块 {module_name} 中未找到类 {class_name}")
+                               │                   └ 'processor_rss_data'
+                               └ 'processors'
+
+AttributeError: 模块 processors 中未找到类 processor_rss_data
+
+Traceback (most recent call last):
+
+  File "<frozen runpy>", line 198, in _run_module_as_main
+  File "<frozen runpy>", line 88, in _run_code
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel_launcher.py", line 18, in <module>
+    app.launch_new_instance()
+    │   └ <bound method Application.launch_instance of <class 'ipykernel.kernelapp.IPKernelApp'>>
+    └ <module 'ipykernel.kernelapp' from 'd:\\ProgramTools\\anaconda3\\envs\\intelligence_system\\Lib\\site-packages\\ipykernel\\ke...
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\traitlets\config\application.py", line 1075, in launch_instance
+    app.start()
+    │   └ <function IPKernelApp.start at 0x00000241EF7C0D60>
+    └ <ipykernel.kernelapp.IPKernelApp object at 0x00000241EB5B7D10>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelapp.py", line 739, in start
+    self.io_loop.start()
+    │    │       └ <function BaseAsyncIOLoop.start at 0x00000241EF7C1C60>
+    │    └ <tornado.platform.asyncio.AsyncIOMainLoop object at 0x00000241EF7AAD20>
+    └ <ipykernel.kernelapp.IPKernelApp object at 0x00000241EB5B7D10>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\tornado\platform\asyncio.py", line 211, in start
+    self.asyncio_loop.run_forever()
+    │    │            └ <function BaseEventLoop.run_forever at 0x00000241EDB7B920>
+    │    └ <_WindowsSelectorEventLoop running=True closed=False debug=False>
+    └ <tornado.platform.asyncio.AsyncIOMainLoop object at 0x00000241EF7AAD20>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\base_events.py", line 645, in run_forever
+    self._run_once()
+    │    └ <function BaseEventLoop._run_once at 0x00000241EDB7D760>
+    └ <_WindowsSelectorEventLoop running=True closed=False debug=False>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\base_events.py", line 1999, in _run_once
+    handle._run()
+    │      └ <function Handle._run at 0x00000241ED6E9D00>
+    └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\events.py", line 88, in _run
+    self._context.run(self._callback, *self._args)
+    │    │            │    │           │    └ <member '_args' of 'Handle' objects>
+    │    │            │    │           └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+    │    │            │    └ <member '_callback' of 'Handle' objects>
+    │    │            └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+    │    └ <member '_context' of 'Handle' objects>
+    └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 519, in dispatch_queue
+    await self.process_one()
+          │    └ <function Kernel.process_one at 0x00000241EF781D00>
+          └ <ipykernel.ipkernel.IPythonKernel object at 0x00000241EF7AAD80>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 508, in process_one
+    await dispatch(*args)
+          │         └ ([<zmq.Frame(b'be29372e-391'...36B)>, <zmq.Frame(b'<IDS|MSG>')>, <zmq.Frame(b'36f03038e4ef'...64B)>, <zmq.Frame(b'{"date":"20...
+          └ <bound method Kernel.dispatch_shell of <ipykernel.ipkernel.IPythonKernel object at 0x00000241EF7AAD80>>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 400, in dispatch_shell
+    await result
+          └ <coroutine object IPythonKernel.execute_request at 0x0000024191C6BC40>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\ipkernel.py", line 368, in execute_request
+    await super().execute_request(stream, ident, parent)
+                                  │       │      └ {'header': {'date': datetime.datetime(2025, 10, 30, 5, 56, 55, 692000, tzinfo=tzutc()), 'msg_id': '788ee0fd-a13f-4e53-98b0-e9...
+                                  │       └ [b'be29372e-3914-4138-ba04-8dcacb3dcfbe']
+                                  └ <zmq.eventloop.zmqstream.ZMQStream object at 0x00000241EF7AB140>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 767, in execute_request
+    reply_content = await reply_content
+                          └ <coroutine object IPythonKernel.do_execute at 0x00000241F0DB22C0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\ipkernel.py", line 455, in do_execute
+    res = shell.run_cell(
+          │     └ <function ZMQInteractiveShell.run_cell at 0x00000241EF7ADDA0>
+          └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\zmqshell.py", line 577, in run_cell
+    return super().run_cell(*args, **kwargs)
+                             │       └ {'store_history': True, 'silent': False, 'cell_id': 'vscode-notebook-cell:/d%3A/Idea%20Project/intelligence_system/tools/task...
+                             └ ('# 手动执行任务（异步方式，快速返回）\ndef run_task_manually(task_id):\n    display(Markdown(f"### 正在手动执行任务ID {task_id}..."))\n    success = ...
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3098, in run_cell
+    result = self._run_cell(
+             │    └ <function InteractiveShell._run_cell at 0x00000241EEDFA200>
+             └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3153, in _run_cell
+    result = runner(coro)
+             │      └ <coroutine object InteractiveShell.run_cell_async at 0x0000024191A23AC0>
+             └ <function _pseudo_sync_runner at 0x00000241EEDD5260>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\async_helpers.py", line 128, in _pseudo_sync_runner
+    coro.send(None)
+    │    └ <method 'send' of 'coroutine' objects>
+    └ <coroutine object InteractiveShell.run_cell_async at 0x0000024191A23AC0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3362, in run_cell_async
+    has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
+                       │    │             │        │     └ 'C:\\Users\\zy187\\AppData\\Local\\Temp\\ipykernel_15044\\1819114417.py'
+                       │    │             │        └ [<ast.FunctionDef object at 0x0000024191E00090>, <ast.FunctionDef object at 0x00000241F1027390>, <ast.Expr object at 0x000002...
+                       │    │             └ <ast.Module object at 0x0000024191E00050>
+                       │    └ <function InteractiveShell.run_ast_nodes at 0x00000241EEDFA5C0>
+                       └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3607, in run_ast_nodes
+    if await self.run_code(code, result, async_=asy):
+             │    │        │     │              └ False
+             │    │        │     └ <ExecutionResult object at 24191c22900, execution_count=3 error_before_exec=None error_in_exec=None info=<ExecutionInfo objec...
+             │    │        └ <code object <module> at 0x0000024191CC1DF0, file "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 1>
+             │    └ <function InteractiveShell.run_code at 0x00000241EEDFA660>
+             └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3667, in run_code
+    exec(code_obj, self.user_global_ns, self.user_ns)
+         │         │    │               │    └ <property object at 0x00000241EEDF4B30>
+         │         │    │               └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+         │         │    └ <property object at 0x00000241EEDF4BD0>
+         │         └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x00000241F0C50860>
+         └ <code object <module> at 0x0000024191CC1DF0, file "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 1>
+
+  File "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 45, in <module>
+    run_task_with_details(2)
+    └ <function run_task_with_details at 0x0000024191C38CC0>
+
+  File "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1819114417.py", line 16, in run_task_with_details
+    result = manager.run_task_synchronously(task_id)
+             │       │                      └ 2
+             │       └ <function TaskManager.run_task_synchronously at 0x0000024191C38EA0>
+             └ <__main__.TaskManager object at 0x00000241919D6AB0>
+
+> File "C:\Users\zy187\AppData\Local\Temp\ipykernel_15044\1757831752.py", line 122, in run_task_synchronously
+    self.scheduler._execute_task_logic(task)
+    │    │         │                   └ {'task_id': 2, 'task_name': 'RSS基于规则数据处理', 'task_type': 'processor', 'module_path': 'processors.processor_rss_data', 'cron_ex...
+    │    │         └ <function TaskScheduler._execute_task_logic at 0x0000024191C3F920>
+    │    └ <system_management.scheduler.task_scheduler.TaskScheduler object at 0x00000241FF4E9700>
+    └ <__main__.TaskManager object at 0x00000241919D6AB0>
+
+  File "d:\Idea Project\intelligence_system\system_management\scheduler\task_scheduler.py", line 278, in _execute_task_logic
+    raise AttributeError(f"模块 {module_name} 中未找到类 {class_name}")
+                               │                   └ 'processor_rss_data'
+                               └ 'processors'
+
+AttributeError: 模块 processors 中未找到类 processor_rss_data
+2025-10-30 13:57:11.125 | ERROR | 1757831752:141 - 任务执行失败: RSS基于规则数据处理
+    → module: 'TaskNotebook'
+Traceback (most recent call last):
+
+  File "<frozen runpy>", line 198, in _run_module_as_main
+  File "<frozen runpy>", line 88, in _run_code
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel_launcher.py", line 18, in <module>
+    app.launch_new_instance()
+    │   └ <bound method Application.launch_instance of <class 'ipykernel.kernelapp.IPKernelApp'>>
+    └ <module 'ipykernel.kernelapp' from 'd:\\ProgramTools\\anaconda3\\envs\\intelligence_system\\Lib\\site-packages\\ipykernel\\ke...
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\traitlets\config\application.py", line 1075, in launch_instance
+    app.start()
+    │   └ <function IPKernelApp.start at 0x000001E4F28A0D60>
+    └ <ipykernel.kernelapp.IPKernelApp object at 0x000001E4EE687D10>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelapp.py", line 739, in start
+    self.io_loop.start()
+    │    │       └ <function BaseAsyncIOLoop.start at 0x000001E4F28A1C60>
+    │    └ <tornado.platform.asyncio.AsyncIOMainLoop object at 0x000001E4F288ADE0>
+    └ <ipykernel.kernelapp.IPKernelApp object at 0x000001E4EE687D10>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\tornado\platform\asyncio.py", line 211, in start
+    self.asyncio_loop.run_forever()
+    │    │            └ <function BaseEventLoop.run_forever at 0x000001E4F0D2B920>
+    │    └ <_WindowsSelectorEventLoop running=True closed=False debug=False>
+    └ <tornado.platform.asyncio.AsyncIOMainLoop object at 0x000001E4F288ADE0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\base_events.py", line 645, in run_forever
+    self._run_once()
+    │    └ <function BaseEventLoop._run_once at 0x000001E4F0D2D760>
+    └ <_WindowsSelectorEventLoop running=True closed=False debug=False>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\base_events.py", line 1999, in _run_once
+    handle._run()
+    │      └ <function Handle._run at 0x000001E4F08B9D00>
+    └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\events.py", line 88, in _run
+    self._context.run(self._callback, *self._args)
+    │    │            │    │           │    └ <member '_args' of 'Handle' objects>
+    │    │            │    │           └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+    │    │            │    └ <member '_callback' of 'Handle' objects>
+    │    │            └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+    │    └ <member '_context' of 'Handle' objects>
+    └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 519, in dispatch_queue
+    await self.process_one()
+          │    └ <function Kernel.process_one at 0x000001E4F2861D00>
+          └ <ipykernel.ipkernel.IPythonKernel object at 0x000001E4F288A6C0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 508, in process_one
+    await dispatch(*args)
+          │         └ ([<zmq.Frame(b'4c713768-9d1'...36B)>, <zmq.Frame(b'<IDS|MSG>')>, <zmq.Frame(b'1b55c49a4a65'...64B)>, <zmq.Frame(b'{"date":"20...
+          └ <bound method Kernel.dispatch_shell of <ipykernel.ipkernel.IPythonKernel object at 0x000001E4F288A6C0>>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 400, in dispatch_shell
+    await result
+          └ <coroutine object IPythonKernel.execute_request at 0x000001E4F3F51E40>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\ipkernel.py", line 368, in execute_request
+    await super().execute_request(stream, ident, parent)
+                                  │       │      └ {'header': {'date': datetime.datetime(2025, 10, 30, 5, 57, 10, 815000, tzinfo=tzutc()), 'msg_id': '132b59a7-4a02-4a8d-a25c-e2...
+                                  │       └ [b'4c713768-9d1a-49ca-83ed-6814787009a5']
+                                  └ <zmq.eventloop.zmqstream.ZMQStream object at 0x000001E4F288B200>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 767, in execute_request
+    reply_content = await reply_content
+                          └ <coroutine object IPythonKernel.do_execute at 0x000001E4F27D5B40>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\ipkernel.py", line 455, in do_execute
+    res = shell.run_cell(
+          │     └ <function ZMQInteractiveShell.run_cell at 0x000001E4F288DDA0>
+          └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x000001E4F3DED8B0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\zmqshell.py", line 577, in run_cell
+    return super().run_cell(*args, **kwargs)
+                             │       └ {'store_history': True, 'silent': False, 'cell_id': 'vscode-notebook-cell:/d%3A/Idea%20Project/intelligence_system/tools/task...
+                             └ ('# 手动执行任务（异步方式，快速返回）\ndef run_task_manually(task_id):\n    display(Markdown(f"### 正在手动执行任务ID {task_id}..."))\n    success = ...
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3098, in run_cell
+    result = self._run_cell(
+             │    └ <function InteractiveShell._run_cell at 0x000001E4F1EEA200>
+             └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x000001E4F3DED8B0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3153, in _run_cell
+    result = runner(coro)
+             │      └ <coroutine object InteractiveShell.run_cell_async at 0x000001E4F3EFADC0>
+             └ <function _pseudo_sync_runner at 0x000001E4F1ED5260>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\async_helpers.py", line 128, in _pseudo_sync_runner
+    coro.send(None)
+    │    └ <method 'send' of 'coroutine' objects>
+    └ <coroutine object InteractiveShell.run_cell_async at 0x000001E4F3EFADC0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3362, in run_cell_async
+    has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
+                       │    │             │        │     └ 'C:\\Users\\zy187\\AppData\\Local\\Temp\\ipykernel_19964\\1819114417.py'
+                       │    │             │        └ [<ast.FunctionDef object at 0x000001E4F412F450>, <ast.FunctionDef object at 0x000001E4F410FED0>, <ast.Expr object at 0x000001...
+                       │    │             └ <ast.Module object at 0x000001E4F412C190>
+                       │    └ <function InteractiveShell.run_ast_nodes at 0x000001E4F1EEA5C0>
+                       └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x000001E4F3DED8B0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3607, in run_ast_nodes
+    if await self.run_code(code, result, async_=asy):
+             │    │        │     │              └ False
+             │    │        │     └ <ExecutionResult object at 1e4ffcf6240, execution_count=2 error_before_exec=None error_in_exec=None info=<ExecutionInfo objec...
+             │    │        └ <code object <module> at 0x000001E4FFCE9610, file "C:\Users\zy187\AppData\Local\Temp\ipykernel_19964\1819114417.py", line 1>
+             │    └ <function InteractiveShell.run_code at 0x000001E4F1EEA660>
+             └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x000001E4F3DED8B0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3667, in run_code
+    exec(code_obj, self.user_global_ns, self.user_ns)
+         │         │    │               │    └ <property object at 0x000001E4F1EE4B30>
+         │         │    │               └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x000001E4F3DED8B0>
+         │         │    └ <property object at 0x000001E4F1EE4BD0>
+         │         └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x000001E4F3DED8B0>
+         └ <code object <module> at 0x000001E4FFCE9610, file "C:\Users\zy187\AppData\Local\Temp\ipykernel_19964\1819114417.py", line 1>
+
+  File "C:\Users\zy187\AppData\Local\Temp\ipykernel_19964\1819114417.py", line 45, in <module>
+    run_task_with_details(2)
+    └ <function run_task_with_details at 0x000001E4FFD10CC0>
+
+  File "C:\Users\zy187\AppData\Local\Temp\ipykernel_19964\1819114417.py", line 16, in run_task_with_details
+    result = manager.run_task_synchronously(task_id)
+             │       │                      └ 2
+             │       └ <function TaskManager.run_task_synchronously at 0x000001E4FFD10EA0>
+             └ <__main__.TaskManager object at 0x000001E4FEBA31D0>
+
+> File "C:\Users\zy187\AppData\Local\Temp\ipykernel_19964\1757831752.py", line 122, in run_task_synchronously
+    self.scheduler._execute_task_logic(task)
+    │    │         │                   └ {'task_id': 2, 'task_name': 'RSS基于规则数据处理', 'task_type': 'processor', 'module_path': 'processors.processor_rss_data', 'cron_ex...
+    │    │         └ <function TaskScheduler._execute_task_logic at 0x000001E4FFD0F9C0>
+    │    └ <system_management.scheduler.task_scheduler.TaskScheduler object at 0x000001E4FE552A20>
+    └ <__main__.TaskManager object at 0x000001E4FEBA31D0>
+
+  File "d:\Idea Project\intelligence_system\system_management\scheduler\task_scheduler.py", line 278, in _execute_task_logic
+    raise AttributeError(f"模块 {module_name} 中未找到类 {class_name}")
+                               │                   └ 'processor_rss_data'
+                               └ 'processors'
+
+AttributeError: 模块 processors 中未找到类 processor_rss_data
+
+Traceback (most recent call last):
+
+  File "<frozen runpy>", line 198, in _run_module_as_main
+  File "<frozen runpy>", line 88, in _run_code
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel_launcher.py", line 18, in <module>
+    app.launch_new_instance()
+    │   └ <bound method Application.launch_instance of <class 'ipykernel.kernelapp.IPKernelApp'>>
+    └ <module 'ipykernel.kernelapp' from 'd:\\ProgramTools\\anaconda3\\envs\\intelligence_system\\Lib\\site-packages\\ipykernel\\ke...
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\traitlets\config\application.py", line 1075, in launch_instance
+    app.start()
+    │   └ <function IPKernelApp.start at 0x000001E4F28A0D60>
+    └ <ipykernel.kernelapp.IPKernelApp object at 0x000001E4EE687D10>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelapp.py", line 739, in start
+    self.io_loop.start()
+    │    │       └ <function BaseAsyncIOLoop.start at 0x000001E4F28A1C60>
+    │    └ <tornado.platform.asyncio.AsyncIOMainLoop object at 0x000001E4F288ADE0>
+    └ <ipykernel.kernelapp.IPKernelApp object at 0x000001E4EE687D10>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\tornado\platform\asyncio.py", line 211, in start
+    self.asyncio_loop.run_forever()
+    │    │            └ <function BaseEventLoop.run_forever at 0x000001E4F0D2B920>
+    │    └ <_WindowsSelectorEventLoop running=True closed=False debug=False>
+    └ <tornado.platform.asyncio.AsyncIOMainLoop object at 0x000001E4F288ADE0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\base_events.py", line 645, in run_forever
+    self._run_once()
+    │    └ <function BaseEventLoop._run_once at 0x000001E4F0D2D760>
+    └ <_WindowsSelectorEventLoop running=True closed=False debug=False>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\base_events.py", line 1999, in _run_once
+    handle._run()
+    │      └ <function Handle._run at 0x000001E4F08B9D00>
+    └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\asyncio\events.py", line 88, in _run
+    self._context.run(self._callback, *self._args)
+    │    │            │    │           │    └ <member '_args' of 'Handle' objects>
+    │    │            │    │           └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+    │    │            │    └ <member '_callback' of 'Handle' objects>
+    │    │            └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+    │    └ <member '_context' of 'Handle' objects>
+    └ <Handle Task.task_wakeup(<Future finis...7B)>, ...],))>)>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 519, in dispatch_queue
+    await self.process_one()
+          │    └ <function Kernel.process_one at 0x000001E4F2861D00>
+          └ <ipykernel.ipkernel.IPythonKernel object at 0x000001E4F288A6C0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 508, in process_one
+    await dispatch(*args)
+          │         └ ([<zmq.Frame(b'4c713768-9d1'...36B)>, <zmq.Frame(b'<IDS|MSG>')>, <zmq.Frame(b'1b55c49a4a65'...64B)>, <zmq.Frame(b'{"date":"20...
+          └ <bound method Kernel.dispatch_shell of <ipykernel.ipkernel.IPythonKernel object at 0x000001E4F288A6C0>>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 400, in dispatch_shell
+    await result
+          └ <coroutine object IPythonKernel.execute_request at 0x000001E4F3F51E40>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\ipkernel.py", line 368, in execute_request
+    await super().execute_request(stream, ident, parent)
+                                  │       │      └ {'header': {'date': datetime.datetime(2025, 10, 30, 5, 57, 10, 815000, tzinfo=tzutc()), 'msg_id': '132b59a7-4a02-4a8d-a25c-e2...
+                                  │       └ [b'4c713768-9d1a-49ca-83ed-6814787009a5']
+                                  └ <zmq.eventloop.zmqstream.ZMQStream object at 0x000001E4F288B200>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\kernelbase.py", line 767, in execute_request
+    reply_content = await reply_content
+                          └ <coroutine object IPythonKernel.do_execute at 0x000001E4F27D5B40>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\ipkernel.py", line 455, in do_execute
+    res = shell.run_cell(
+          │     └ <function ZMQInteractiveShell.run_cell at 0x000001E4F288DDA0>
+          └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x000001E4F3DED8B0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\ipykernel\zmqshell.py", line 577, in run_cell
+    return super().run_cell(*args, **kwargs)
+                             │       └ {'store_history': True, 'silent': False, 'cell_id': 'vscode-notebook-cell:/d%3A/Idea%20Project/intelligence_system/tools/task...
+                             └ ('# 手动执行任务（异步方式，快速返回）\ndef run_task_manually(task_id):\n    display(Markdown(f"### 正在手动执行任务ID {task_id}..."))\n    success = ...
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3098, in run_cell
+    result = self._run_cell(
+             │    └ <function InteractiveShell._run_cell at 0x000001E4F1EEA200>
+             └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x000001E4F3DED8B0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3153, in _run_cell
+    result = runner(coro)
+             │      └ <coroutine object InteractiveShell.run_cell_async at 0x000001E4F3EFADC0>
+             └ <function _pseudo_sync_runner at 0x000001E4F1ED5260>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\async_helpers.py", line 128, in _pseudo_sync_runner
+    coro.send(None)
+    │    └ <method 'send' of 'coroutine' objects>
+    └ <coroutine object InteractiveShell.run_cell_async at 0x000001E4F3EFADC0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3362, in run_cell_async
+    has_raised = await self.run_ast_nodes(code_ast.body, cell_name,
+                       │    │             │        │     └ 'C:\\Users\\zy187\\AppData\\Local\\Temp\\ipykernel_19964\\1819114417.py'
+                       │    │             │        └ [<ast.FunctionDef object at 0x000001E4F412F450>, <ast.FunctionDef object at 0x000001E4F410FED0>, <ast.Expr object at 0x000001...
+                       │    │             └ <ast.Module object at 0x000001E4F412C190>
+                       │    └ <function InteractiveShell.run_ast_nodes at 0x000001E4F1EEA5C0>
+                       └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x000001E4F3DED8B0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3607, in run_ast_nodes
+    if await self.run_code(code, result, async_=asy):
+             │    │        │     │              └ False
+             │    │        │     └ <ExecutionResult object at 1e4ffcf6240, execution_count=2 error_before_exec=None error_in_exec=None info=<ExecutionInfo objec...
+             │    │        └ <code object <module> at 0x000001E4FFCE9610, file "C:\Users\zy187\AppData\Local\Temp\ipykernel_19964\1819114417.py", line 1>
+             │    └ <function InteractiveShell.run_code at 0x000001E4F1EEA660>
+             └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x000001E4F3DED8B0>
+  File "d:\ProgramTools\anaconda3\envs\intelligence_system\Lib\site-packages\IPython\core\interactiveshell.py", line 3667, in run_code
+    exec(code_obj, self.user_global_ns, self.user_ns)
+         │         │    │               │    └ <property object at 0x000001E4F1EE4B30>
+         │         │    │               └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x000001E4F3DED8B0>
+         │         │    └ <property object at 0x000001E4F1EE4BD0>
+         │         └ <ipykernel.zmqshell.ZMQInteractiveShell object at 0x000001E4F3DED8B0>
+         └ <code object <module> at 0x000001E4FFCE9610, file "C:\Users\zy187\AppData\Local\Temp\ipykernel_19964\1819114417.py", line 1>
+
+  File "C:\Users\zy187\AppData\Local\Temp\ipykernel_19964\1819114417.py", line 45, in <module>
+    run_task_with_details(2)
+    └ <function run_task_with_details at 0x000001E4FFD10CC0>
+
+  File "C:\Users\zy187\AppData\Local\Temp\ipykernel_19964\1819114417.py", line 16, in run_task_with_details
+    result = manager.run_task_synchronously(task_id)
+             │       │                      └ 2
+             │       └ <function TaskManager.run_task_synchronously at 0x000001E4FFD10EA0>
+             └ <__main__.TaskManager object at 0x000001E4FEBA31D0>
+
+> File "C:\Users\zy187\AppData\Local\Temp\ipykernel_19964\1757831752.py", line 122, in run_task_synchronously
+    self.scheduler._execute_task_logic(task)
+    │    │         │                   └ {'task_id': 2, 'task_name': 'RSS基于规则数据处理', 'task_type': 'processor', 'module_path': 'processors.processor_rss_data', 'cron_ex...
+    │    │         └ <function TaskScheduler._execute_task_logic at 0x000001E4FFD0F9C0>
+    │    └ <system_management.scheduler.task_scheduler.TaskScheduler object at 0x000001E4FE552A20>
+    └ <__main__.TaskManager object at 0x000001E4FEBA31D0>
+
+  File "d:\Idea Project\intelligence_system\system_management\scheduler\task_scheduler.py", line 278, in _execute_task_logic
+    raise AttributeError(f"模块 {module_name} 中未找到类 {class_name}")
+                               │                   └ 'processor_rss_data'
+                               └ 'processors'
+
+AttributeError: 模块 processors 中未找到类 processor_rss_data

output/reports/daily/daily_report_20251029_173546.html

@@ -0,0 +1,301 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>汽车后市场情报报告</title>
+    <link href="https://fonts.googleapis.com/css2?family=Noto+Sans+SC:wght@300;400;500;700&display=swap" rel="stylesheet">
+    <style>
+        :root {
+            --primary: #3498db;
+            --secondary: #2ecc71;
+            --accent: #e74c3c;
+            --dark: #2c3e50;
+            --light: #f8f9fa;
+            --border: #e0e0e0;
+        }
+
+        * {
+            margin: 0;
+            padding: 0;
+            box-sizing: border-box;
+        }
+
+        body {
+            font-family: 'Noto Sans SC', -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
+            line-height: 1.8;
+            color: #333;
+            background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
+            padding: 20px;
+        }
+
+        .report-container {
+            max-width: 1200px;
+            margin: 0 auto;
+            padding: 40px;
+            background: white;
+            box-shadow: 0 10px 40px rgba(0,0,0,0.1);
+            border-radius: 12px;
+        }
+
+        .report-header {
+            text-align: center;
+            padding-bottom: 30px;
+            border-bottom: 3px solid var(--primary);
+            margin-bottom: 40px;
+        }
+
+        .report-header h1 {
+            color: var(--dark);
+            font-size: 2.5em;
+            margin-bottom: 10px;
+        }
+
+        .report-header .report-date {
+            color: #666;
+            font-size: 1.1em;
+        }
+
+        h1 {
+            color: var(--dark);
+            font-size: 2em;
+            margin: 30px 0 20px 0;
+            padding-bottom: 10px;
+            border-bottom: 2px solid var(--primary);
+        }
+
+        h2 {
+            color: var(--dark);
+            font-size: 1.6em;
+            margin: 25px 0 15px 0;
+            padding-left: 10px;
+            border-left: 4px solid var(--primary);
+        }
+
+        h3 {
+            color: var(--dark);
+            font-size: 1.3em;
+            margin: 20px 0 10px 0;
+        }
+
+        h4 {
+            color: #555;
+            font-size: 1.1em;
+            margin: 15px 0 8px 0;
+        }
+
+        p {
+            margin: 12px 0;
+            text-align: justify;
+        }
+
+        ul, ol {
+            margin: 15px 0;
+            padding-left: 30px;
+        }
+
+        li {
+            margin: 8px 0;
+        }
+
+        /* 表格样式 */
+        table {
+            width: 100%;
+            border-collapse: collapse;
+            margin: 25px 0;
+            box-shadow: 0 2px 15px rgba(0,0,0,0.1);
+            border-radius: 8px;
+            overflow: hidden;
+        }
+
+        table thead {
+            background: linear-gradient(135deg, var(--primary) 0%, #2980b9 100%);
+            color: white;
+        }
+
+        table th {
+            padding: 15px;
+            text-align: left;
+            font-weight: 600;
+        }
+
+        table td {
+            padding: 12px 15px;
+            border-bottom: 1px solid var(--border);
+        }
+
+        table tbody tr:hover {
+            background-color: #f5f5f5;
+        }
+
+        table tbody tr:last-child td {
+            border-bottom: none;
+        }
+
+        /* 代码块样式 */
+        pre {
+            background: #f4f4f4;
+            border: 1px solid var(--border);
+            border-radius: 6px;
+            padding: 15px;
+            overflow-x: auto;
+            margin: 20px 0;
+        }
+
+        code {
+            background: #f4f4f4;
+            padding: 2px 6px;
+            border-radius: 3px;
+            font-family: 'Courier New', monospace;
+            font-size: 0.9em;
+        }
+
+        pre code {
+            background: none;
+            padding: 0;
+        }
+
+        /* 链接样式 */
+        a {
+            color: var(--primary);
+            text-decoration: none;
+            border-bottom: 1px dotted var(--primary);
+            transition: all 0.3s;
+        }
+
+        a:hover {
+            color: var(--accent);
+            border-bottom-color: var(--accent);
+        }
+
+        /* 新闻列表样式 */
+        .news-item {
+            background: #f9f9f9;
+            border-left: 4px solid var(--secondary);
+            padding: 15px 20px;
+            margin: 15px 0;
+            border-radius: 6px;
+            transition: all 0.3s;
+        }
+
+        .news-item:hover {
+            background: #f0f0f0;
+            box-shadow: 0 2px 8px rgba(0,0,0,0.1);
+        }
+
+        .news-item h3 {
+            margin-top: 0;
+            color: var(--dark);
+        }
+
+        .news-item .news-meta {
+            color: #666;
+            font-size: 0.9em;
+            margin-top: 10px;
+        }
+
+        .news-item .news-category {
+            display: inline-block;
+            background: var(--secondary);
+            color: white;
+            padding: 3px 10px;
+            border-radius: 12px;
+            font-size: 0.85em;
+            margin-right: 10px;
+        }
+
+        /* 统计信息样式 */
+        .stats-box {
+            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+            color: white;
+            padding: 25px;
+            border-radius: 10px;
+            margin: 25px 0;
+        }
+
+        .stats-box h2 {
+            color: white;
+            border: none;
+            padding: 0;
+            margin: 0 0 15px 0;
+        }
+
+        .stats-grid {
+            display: grid;
+            grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
+            gap: 20px;
+            margin-top: 20px;
+        }
+
+        .stat-item {
+            text-align: center;
+        }
+
+        .stat-number {
+            font-size: 2.5em;
+            font-weight: bold;
+            margin-bottom: 5px;
+        }
+
+        .stat-label {
+            font-size: 0.9em;
+            opacity: 0.9;
+        }
+
+        /* 响应式设计 */
+        @media (max-width: 768px) {
+            .report-container {
+                padding: 20px;
+            }
+
+            .report-header h1 {
+                font-size: 1.8em;
+            }
+
+            h1 {
+                font-size: 1.6em;
+            }
+
+            h2 {
+                font-size: 1.3em;
+            }
+
+            table {
+                font-size: 0.9em;
+            }
+
+            table th,
+            table td {
+                padding: 8px;
+            }
+        }
+
+        /* 打印样式 */
+        @media print {
+            body {
+                background: white;
+                padding: 0;
+            }
+
+            .report-container {
+                box-shadow: none;
+                padding: 0;
+            }
+        }
+    </style>
+</head>
+<body>
+    <div class="report-container">
+        <h1>汽车后市场情报日报</h1>
+<h2>报告时间</h2>
+<p><strong>生成时间</strong>: 2025-10-29 17:35:46
+<strong>时间范围</strong>: 2025-10-28 17:35:46 至 2025-10-29 17:35:46</p>
+<h2>数据统计</h2>
+<ul>
+<li><strong>相关文章数</strong>: 0</li>
+</ul>
+<h2>相关新闻</h2>
+<p>昨日无汽车后市场相关的新闻</p>
+    </div>
+</body>
+</html>

output/reports/weekly/weekly_report_20251029_173637.html

@@ -0,0 +1,311 @@
+<!DOCTYPE html>
+<html lang="zh-CN">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>汽车后市场情报报告</title>
+    <link href="https://fonts.googleapis.com/css2?family=Noto+Sans+SC:wght@300;400;500;700&display=swap" rel="stylesheet">
+    <style>
+        :root {
+            --primary: #3498db;
+            --secondary: #2ecc71;
+            --accent: #e74c3c;
+            --dark: #2c3e50;
+            --light: #f8f9fa;
+            --border: #e0e0e0;
+        }
+
+        * {
+            margin: 0;
+            padding: 0;
+            box-sizing: border-box;
+        }
+
+        body {
+            font-family: 'Noto Sans SC', -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
+            line-height: 1.8;
+            color: #333;
+            background: linear-gradient(135deg, #f5f7fa 0%, #c3cfe2 100%);
+            padding: 20px;
+        }
+
+        .report-container {
+            max-width: 1200px;
+            margin: 0 auto;
+            padding: 40px;
+            background: white;
+            box-shadow: 0 10px 40px rgba(0,0,0,0.1);
+            border-radius: 12px;
+        }
+
+        .report-header {
+            text-align: center;
+            padding-bottom: 30px;
+            border-bottom: 3px solid var(--primary);
+            margin-bottom: 40px;
+        }
+
+        .report-header h1 {
+            color: var(--dark);
+            font-size: 2.5em;
+            margin-bottom: 10px;
+        }
+
+        .report-header .report-date {
+            color: #666;
+            font-size: 1.1em;
+        }
+
+        h1 {
+            color: var(--dark);
+            font-size: 2em;
+            margin: 30px 0 20px 0;
+            padding-bottom: 10px;
+            border-bottom: 2px solid var(--primary);
+        }
+
+        h2 {
+            color: var(--dark);
+            font-size: 1.6em;
+            margin: 25px 0 15px 0;
+            padding-left: 10px;
+            border-left: 4px solid var(--primary);
+        }
+
+        h3 {
+            color: var(--dark);
+            font-size: 1.3em;
+            margin: 20px 0 10px 0;
+        }
+
+        h4 {
+            color: #555;
+            font-size: 1.1em;
+            margin: 15px 0 8px 0;
+        }
+
+        p {
+            margin: 12px 0;
+            text-align: justify;
+        }
+
+        ul, ol {
+            margin: 15px 0;
+            padding-left: 30px;
+        }
+
+        li {
+            margin: 8px 0;
+        }
+
+        /* 表格样式 */
+        table {
+            width: 100%;
+            border-collapse: collapse;
+            margin: 25px 0;
+            box-shadow: 0 2px 15px rgba(0,0,0,0.1);
+            border-radius: 8px;
+            overflow: hidden;
+        }
+
+        table thead {
+            background: linear-gradient(135deg, var(--primary) 0%, #2980b9 100%);
+            color: white;
+        }
+
+        table th {
+            padding: 15px;
+            text-align: left;
+            font-weight: 600;
+        }
+
+        table td {
+            padding: 12px 15px;
+            border-bottom: 1px solid var(--border);
+        }
+
+        table tbody tr:hover {
+            background-color: #f5f5f5;
+        }
+
+        table tbody tr:last-child td {
+            border-bottom: none;
+        }
+
+        /* 代码块样式 */
+        pre {
+            background: #f4f4f4;
+            border: 1px solid var(--border);
+            border-radius: 6px;
+            padding: 15px;
+            overflow-x: auto;
+            margin: 20px 0;
+        }
+
+        code {
+            background: #f4f4f4;
+            padding: 2px 6px;
+            border-radius: 3px;
+            font-family: 'Courier New', monospace;
+            font-size: 0.9em;
+        }
+
+        pre code {
+            background: none;
+            padding: 0;
+        }
+
+        /* 链接样式 */
+        a {
+            color: var(--primary);
+            text-decoration: none;
+            border-bottom: 1px dotted var(--primary);
+            transition: all 0.3s;
+        }
+
+        a:hover {
+            color: var(--accent);
+            border-bottom-color: var(--accent);
+        }
+
+        /* 新闻列表样式 */
+        .news-item {
+            background: #f9f9f9;
+            border-left: 4px solid var(--secondary);
+            padding: 15px 20px;
+            margin: 15px 0;
+            border-radius: 6px;
+            transition: all 0.3s;
+        }
+
+        .news-item:hover {
+            background: #f0f0f0;
+            box-shadow: 0 2px 8px rgba(0,0,0,0.1);
+        }
+
+        .news-item h3 {
+            margin-top: 0;
+            color: var(--dark);
+        }
+
+        .news-item .news-meta {
+            color: #666;
+            font-size: 0.9em;
+            margin-top: 10px;
+        }
+
+        .news-item .news-category {
+            display: inline-block;
+            background: var(--secondary);
+            color: white;
+            padding: 3px 10px;
+            border-radius: 12px;
+            font-size: 0.85em;
+            margin-right: 10px;
+        }
+
+        /* 统计信息样式 */
+        .stats-box {
+            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+            color: white;
+            padding: 25px;
+            border-radius: 10px;
+            margin: 25px 0;
+        }
+
+        .stats-box h2 {
+            color: white;
+            border: none;
+            padding: 0;
+            margin: 0 0 15px 0;
+        }
+
+        .stats-grid {
+            display: grid;
+            grid-template-columns: repeat(auto-fit, minmax(200px, 1fr));
+            gap: 20px;
+            margin-top: 20px;
+        }
+
+        .stat-item {
+            text-align: center;
+        }
+
+        .stat-number {
+            font-size: 2.5em;
+            font-weight: bold;
+            margin-bottom: 5px;
+        }
+
+        .stat-label {
+            font-size: 0.9em;
+            opacity: 0.9;
+        }
+
+        /* 响应式设计 */
+        @media (max-width: 768px) {
+            .report-container {
+                padding: 20px;
+            }
+
+            .report-header h1 {
+                font-size: 1.8em;
+            }
+
+            h1 {
+                font-size: 1.6em;
+            }
+
+            h2 {
+                font-size: 1.3em;
+            }
+
+            table {
+                font-size: 0.9em;
+            }
+
+            table th,
+            table td {
+                padding: 8px;
+            }
+        }
+
+        /* 打印样式 */
+        @media print {
+            body {
+                background: white;
+                padding: 0;
+            }
+
+            .report-container {
+                box-shadow: none;
+                padding: 0;
+            }
+        }
+    </style>
+</head>
+<body>
+    <div class="report-container">
+        <h1>汽车后市场情报周报</h1>
+<h2>报告时间</h2>
+<p><strong>生成时间</strong>: 2025-10-29 17:36:37
+<strong>时间范围</strong>: 2025-10-22 17:36:37 至 2025-10-29 17:36:37</p>
+<h2>数据统计</h2>
+<ul>
+<li><strong>相关文章数</strong>: 1</li>
+</ul>
+<h2>汽车后市场相关新闻</h2>
+<p>共找到 1 篇相关新闻：</p>
+<h3>1. 2025年全国汽车以旧换新补贴申请量突破1000万份</h3>
+<ul class="news-list">
+<li><strong>分类</strong>: 二手车</li>
+<li><strong>标签</strong>: ["二手车", "政策补贴"]</li>
+<li><strong>摘要</strong>: 记者从商务部了解到，截至10月22日，2025年汽车以旧换新补贴申请量突破1000万份，其中汽车报废更新超340万份，置换更新超660万份。</li>
+<li><strong>链接</strong>: <a href="http://www.chinanews.com/cj/2025/10-23/10503300.shtml" rel="noopener noreferrer" target="_blank">http://www.chinanews.com/cj/2025/10-23/10503300.shtml</a></li>
+<li><strong>发布时间</strong>: 2025-10-23 08:35:31</li>
+<li><strong>相关度评分</strong>: 70</li>
+<li><strong>分析说明</strong>: 新闻涉及汽车以旧换新补贴申请量，其中包含置换更新超660万份，直接关联二手车流通环节，属于汽车后市场中二手车领域的政策动态。</li>
+</ul>
+    </div>
+</body>
+</html>

processors/ai_processors/ai_processor_rss_data.py

@@ -195,7 +195,7 @@ class RSSDataAIProcessor:
             raise
     
     def create_ai_result_table(self):
-        """创建AI处理结果表"""
+        """创建AI处理结果表（使用安全方法，确保不会删除现有数据）"""
         create_sql = f"""
         CREATE TABLE IF NOT EXISTS {self.ai_table} (
             id INT AUTO_INCREMENT PRIMARY KEY COMMENT '主键ID',
@@ -221,10 +221,13 @@ class RSSDataAIProcessor:
         """
         
         try:
-            self.db_agent.execute_sql(create_sql)
-            self.log.info(f"成功创建AI结果表: {self.ai_table}")
+            # 使用安全方法创建表（如果不存在），确保不会删除现有数据
+            self.db_agent.create_table_if_not_exists(
+                table_name=self.ai_table,
+                create_sql=create_sql
+            )
         except Exception as e:
-            self.log.error(f"创建AI结果表失败: {str(e)}", exc_info=True)
+            self.log.error(f"创建AI结果表失败（可能是数据库连接问题）: {str(e)}", exc_info=True)
             raise
     
     def load_unprocessed_data(self, limit: int = 100) -> pd.DataFrame:

processors/processor_rss_data.py

@@ -270,14 +270,34 @@ class RSSDataProcessor:
             save_df = save_df.drop('segmented_words', axis=1)
             
             # 检查目标表是否存在，不存在则创建
-            if not self.db_agent.table_exists(self.processed_table_name):
-                self.create_processed_table()
+            # 注意：如果连接失败，table_exists可能返回False，需要捕获异常
+            try:
+                table_exists = self.db_agent.table_exists(self.processed_table_name)
+                if not table_exists:
+                    self.log.warning(f"表 {self.processed_table_name} 不存在，正在创建...")
+                    self.create_processed_table()
+                else:
+                    # 表存在时，也确保有唯一索引（安全操作，不会删除数据）
+                    self.create_processed_table()  # 这个方法会检查并添加索引，不会删除数据
+            except Exception as table_check_error:
+                # 如果检查表存在性时连接失败，记录错误但不中断
+                # 因为后续的插入操作会再次尝试连接
+                self.log.warning(f"检查表存在性时出错（可能是连接问题）: {str(table_check_error)}")
+                # 尝试创建表（如果表已存在，CREATE TABLE IF NOT EXISTS不会报错）
+                try:
+                    self.create_processed_table()
+                except Exception as create_error:
+                    # 如果创建表也失败（可能是连接问题），记录错误
+                    self.log.error(f"创建表时出错（可能是连接问题）: {str(create_error)}")
+                    # 继续尝试插入，如果表存在，插入会成功；如果表不存在，插入会失败并抛出异常
             
-            # 插入数据
+            # 插入数据（ignore_duplicates=True 会跳过重复的文章链接）
+            # 注意：INSERT INTO + ignore_duplicates 只会跳过重复记录，不会覆盖或删除现有数据
+            # 如果数据库连接失败，此操作会抛出异常，不会部分成功
             inserted_rows = self.db_agent.insert_from_df(
                 table_name=self.processed_table_name,
                 df=save_df,
-                ignore_duplicates=True
+                ignore_duplicates=True  # 跳过重复的文章链接，不会删除或覆盖现有数据
             )
             
             self.log.info(f"成功保存 {inserted_rows} 条处理结果到数据库")
@@ -288,7 +308,10 @@ class RSSDataProcessor:
             return False
     
     def create_processed_table(self):
-        """创建处理结果表"""
+        """
+        创建处理结果表（带唯一索引保护，防止重复插入）
+        使用 MySQLAgent 的安全方法，确保不会删除现有数据
+        """
         create_sql = f"""
         CREATE TABLE IF NOT EXISTS {self.processed_table_name} (
             id INT AUTO_INCREMENT PRIMARY KEY,
@@ -306,10 +329,27 @@ class RSSDataProcessor:
         """
         
         try:
-            self.db_agent.execute_sql(create_sql)
-            self.log.info(f"成功创建处理结果表: {self.processed_table_name}")
+            # 使用安全方法创建表（如果不存在）
+            self.db_agent.create_table_if_not_exists(
+                table_name=self.processed_table_name,
+                create_sql=create_sql
+            )
+            
+            # 使用安全方法添加唯一索引（如果不存在）
+            # 注意：唯一索引在创建表时不能直接包含，因为如果表已存在会报错
+            # 所以先创建表，再单独添加索引
+            self.db_agent.add_unique_index_if_not_exists(
+                table_name=self.processed_table_name,
+                index_name='uk_article_link',
+                column_name='文章链接',
+                column_length=500,
+                check_duplicates=True
+            )
+            
         except Exception as e:
-            self.log.error(f"创建表失败: {str(e)}", exc_info=True)
+            # 如果创建表或添加索引失败（可能是连接问题），抛出异常
+            # 这样上层调用可以知道操作失败，不会误以为成功
+            self.log.error(f"创建/检查表失败（可能是数据库连接问题）: {str(e)}", exc_info=True)
             raise
     
     def get_processing_statistics(self, df: pd.DataFrame) -> Dict[str, Any]:
@@ -383,27 +423,9 @@ class RSSDataProcessor:
             return {'success': False, 'message': f'处理失败: {str(e)}'}
 
 
-def main():
-    """主函数入口"""
-    try:
-        # 创建处理器实例
-        processor = RSSDataProcessor()
-        
-        # 处理RSS数据
-        result = processor.process_rss_data(
-            limit=5000,  # 处理最近5000条数据
-            save_to_db=True  # 保存到数据库
-        )
-        
-        if result['success']:
-            print("RSS数据处理完成！")
-            print(f"处理统计: {result['statistics']}")
-        else:
-            print(f"处理失败: {result['message']}")
-            
-    except Exception as e:
-        print(f"程序运行出错: {str(e)}")
-
+    def main(self, limit: int = 1000, save_to_db: bool = True) -> Dict[str, Any]:
+        """主函数入口（实例方法），对外统一调用"""
+        return self.process_rss_data(limit=limit, save_to_db=save_to_db)
 
 if __name__ == "__main__":
-    main()
+    RSSDataProcessor().main(limit=5000, save_to_db=True)

system_management/scheduler/task_scheduler.py

@@ -1,6 +1,5 @@
 import importlib
 import threading
-import time
 from datetime import datetime
 from typing import Dict, List, Optional, Any
 import croniter

test/钉钉api测试.ipynb

@@ -0,0 +1,67 @@
+{
+ "cells": [
+  {
+   "metadata": {},
+   "cell_type": "markdown",
+   "source": "## 获取钉钉token",
+   "id": "4a7d18176711daad"
+  },
+  {
+   "cell_type": "code",
+   "id": "initial_id",
+   "metadata": {
+    "collapsed": true,
+    "ExecuteTime": {
+     "end_time": "2025-10-30T02:59:09.458462Z",
+     "start_time": "2025-10-30T02:59:09.015765Z"
+    }
+   },
+   "source": [
+    "from utils.Ding_api import DingAPI\n",
+    "\n",
+    "api_instance = DingAPI()\n",
+    "token = api_instance.get_token()\n",
+    "print(token)"
+   ],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "D:\\ProgramTools\\anaconda3\\envs\\intelligence_system\\Lib\\site-packages\\requests\\__init__.py:86: RequestsDependencyWarning: Unable to find acceptable character detection dependency (chardet or charset_normalizer).\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "2b166a1c8e683ee38f8d2112a7de5e05\n"
+     ]
+    }
+   ],
+   "execution_count": 1
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

tools/task_manager.ipynb

@@ -10,14 +10,25 @@
   },
   {
    "cell_type": "code",
+   "execution_count": 1,
    "id": "initial_id",
    "metadata": {
-    "collapsed": true,
     "ExecuteTime": {
      "end_time": "2025-10-29T02:25:08.582541Z",
      "start_time": "2025-10-29T02:25:08.473381Z"
-    }
+    },
+    "collapsed": true
    },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "PROJECT_ROOT = d:\\Idea Project\\intelligence_system\n",
+      "\u001b[32m2025-10-30 13:57:07\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mtask_scheduler\u001b[0m - \u001b[1m任务调度器已初始化，最大工作线程数: 5\u001b[0m\n"
+     ]
+    }
+   ],
    "source": [
     "# 使 Notebook 可从项目根导入\n",
     "import sys\n",
@@ -206,18 +217,7 @@
     "        except Exception:\n",
     "            pass\n",
     "        return str(dt)"
-   ],
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "PROJECT_ROOT = D:\\Idea Project\\intelligence_system\n",
-      "\u001B[32m2025-10-29 10:25:08\u001B[0m | \u001B[1mINFO    \u001B[0m | \u001B[36mtask_scheduler\u001B[0m - \u001B[1m任务调度器已初始化，最大工作线程数: 5\u001B[0m\n"
-     ]
-    }
-   ],
-   "execution_count": 8
+   ]
   },
   {
    "cell_type": "markdown",
@@ -242,7 +242,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001B[32m2025-10-29 09:54:09\u001B[0m | \u001B[1mINFO    \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[1m查询执行成功\u001B[0m\n"
+      "\u001b[32m2025-10-29 09:54:09\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mmysql_agent\u001b[0m - \u001b[1m查询执行成功\u001b[0m\n"
      ]
     },
     {
@@ -469,6 +469,7 @@
   },
   {
    "cell_type": "code",
+   "execution_count": 10,
    "id": "eab90de72c35429e",
    "metadata": {
     "ExecuteTime": {
@@ -476,6 +477,62 @@
      "start_time": "2025-10-29T02:26:12.648420Z"
     }
    },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m2025-10-29 10:26:12\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mmysql_agent\u001b[0m - \u001b[1m查询执行成功\u001b[0m\n"
+     ]
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "### 任务详情\n",
+       "**任务ID**: 1\n",
+       "**任务名称**: RSS新闻订阅\n",
+       "**任务类型**: collector\n",
+       "**模块路径**: processors.processor_rss_data.RSSDataProcessor\n",
+       "**Cron表达式**: */5 * * * *\n",
+       "**时区**: Asia/Shanghai\n",
+       "**最后运行时间**: 2025-10-28 13:35:09\n",
+       "**下次运行时间**: 2025-10-29 10:25:00\n",
+       "**运行状态**: success\n",
+       "**是否活跃**: 是\n",
+       "**运行次数**: 496\n",
+       "**创建时间**: 2025-10-16 15:47:34"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'task_id': 1,\n",
+       " 'task_name': 'RSS新闻订阅',\n",
+       " 'task_type': 'collector',\n",
+       " 'module_path': 'processors.processor_rss_data.RSSDataProcessor',\n",
+       " 'cron_expression': '*/5 * * * *',\n",
+       " 'time_zone': 'Asia/Shanghai',\n",
+       " 'next_run_time': Timestamp('2025-10-29 10:25:00'),\n",
+       " 'last_run_time': Timestamp('2025-10-28 13:35:09'),\n",
+       " 'last_run_status': 'success',\n",
+       " 'run_count': 496,\n",
+       " 'is_active': 1,\n",
+       " 'is_running': 0,\n",
+       " 'created_at': Timestamp('2025-10-16 15:47:34'),\n",
+       " 'updated_at': Timestamp('2025-10-29 10:24:49')}"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# 查看指定任务的详情\n",
     "def show_task_details(task_id):\n",
@@ -503,53 +560,7 @@
     "\n",
     "# 执行：查看任务ID为1的详情（替换为实际ID）\n",
     "show_task_details(1)"
-   ],
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\u001B[32m2025-10-29 10:26:12\u001B[0m | \u001B[1mINFO    \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[1m查询执行成功\u001B[0m\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ],
-      "text/markdown": "### 任务详情\n**任务ID**: 1\n**任务名称**: RSS新闻订阅\n**任务类型**: collector\n**模块路径**: processors.processor_rss_data.RSSDataProcessor\n**Cron表达式**: */5 * * * *\n**时区**: Asia/Shanghai\n**最后运行时间**: 2025-10-28 13:35:09\n**下次运行时间**: 2025-10-29 10:25:00\n**运行状态**: success\n**是否活跃**: 是\n**运行次数**: 496\n**创建时间**: 2025-10-16 15:47:34"
-     },
-     "metadata": {},
-     "output_type": "display_data",
-     "jetTransient": {
-      "display_id": null
-     }
-    },
-    {
-     "data": {
-      "text/plain": [
-       "{'task_id': 1,\n",
-       " 'task_name': 'RSS新闻订阅',\n",
-       " 'task_type': 'collector',\n",
-       " 'module_path': 'processors.processor_rss_data.RSSDataProcessor',\n",
-       " 'cron_expression': '*/5 * * * *',\n",
-       " 'time_zone': 'Asia/Shanghai',\n",
-       " 'next_run_time': Timestamp('2025-10-29 10:25:00'),\n",
-       " 'last_run_time': Timestamp('2025-10-28 13:35:09'),\n",
-       " 'last_run_status': 'success',\n",
-       " 'run_count': 496,\n",
-       " 'is_active': 1,\n",
-       " 'is_running': 0,\n",
-       " 'created_at': Timestamp('2025-10-16 15:47:34'),\n",
-       " 'updated_at': Timestamp('2025-10-29 10:24:49')}"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "execution_count": 10
+   ]
   },
   {
    "cell_type": "markdown",
@@ -569,8 +580,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\u001B[32m2025-10-29 09:56:52\u001B[0m | \u001B[1mINFO    \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[1m查询执行成功\u001B[0m\n",
-      "\u001B[32m2025-10-29 09:56:52\u001B[0m | \u001B[1mINFO    \u001B[0m | \u001B[36mtask_scheduler\u001B[0m - \u001B[1m新任务添加成功\u001B[0m\n"
+      "\u001b[32m2025-10-29 09:56:52\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mmysql_agent\u001b[0m - \u001b[1m查询执行成功\u001b[0m\n",
+      "\u001b[32m2025-10-29 09:56:52\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mtask_scheduler\u001b[0m - \u001b[1m新任务添加成功\u001b[0m\n"
      ]
     },
     {
@@ -646,6 +657,7 @@
   },
   {
    "cell_type": "code",
+   "execution_count": 21,
    "id": "c892fd8ad2f0dd9d",
    "metadata": {
     "ExecuteTime": {
@@ -653,6 +665,61 @@
      "start_time": "2025-10-29T02:29:55.754298Z"
     }
    },
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "### 任务ID 2 更新成功"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m2025-10-29 10:29:56\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mmysql_agent\u001b[0m - \u001b[1m查询执行成功\u001b[0m\n"
+     ]
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "### 任务详情\n",
+       "**任务ID**: 2\n",
+       "**任务名称**: RSS基于规则数据处理\n",
+       "**任务类型**: processor\n",
+       "**模块路径**: processors.processor_rss_data\n",
+       "**Cron表达式**: 0 8,20 * * *\n",
+       "**时区**: Asia/Shanghai\n",
+       "**最后运行时间**: 2025-10-28 13:34:49\n",
+       "**下次运行时间**: 2025-10-28 20:00:00\n",
+       "**运行状态**: success\n",
+       "**是否活跃**: 是\n",
+       "**运行次数**: 10\n",
+       "**创建时间**: 2025-10-22 16:06:42"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# 更新任务属性\n",
     "def update_task(task_id, **kwargs):\n",
@@ -685,53 +752,7 @@
     "\n",
     "# 执行：同时更新多个属性（名称和Cron表达式）\n",
     "# update_task(1, name=\"每日早间新闻采集\", cron=\"0 8 * * *\")"
-   ],
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ],
-      "text/markdown": "### 任务ID 2 更新成功"
-     },
-     "metadata": {},
-     "output_type": "display_data",
-     "jetTransient": {
-      "display_id": null
-     }
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\u001B[32m2025-10-29 10:29:56\u001B[0m | \u001B[1mINFO    \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[1m查询执行成功\u001B[0m\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ],
-      "text/markdown": "### 任务详情\n**任务ID**: 2\n**任务名称**: RSS基于规则数据处理\n**任务类型**: processor\n**模块路径**: processors.processor_rss_data\n**Cron表达式**: 0 8,20 * * *\n**时区**: Asia/Shanghai\n**最后运行时间**: 2025-10-28 13:34:49\n**下次运行时间**: 2025-10-28 20:00:00\n**运行状态**: success\n**是否活跃**: 是\n**运行次数**: 10\n**创建时间**: 2025-10-22 16:06:42"
-     },
-     "metadata": {},
-     "output_type": "display_data",
-     "jetTransient": {
-      "display_id": null
-     }
-    },
-    {
-     "data": {
-      "text/plain": [
-       "True"
-      ]
-     },
-     "execution_count": 21,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "execution_count": 21
+   ]
   },
   {
    "cell_type": "markdown",
@@ -800,15 +821,149 @@
   },
   {
    "cell_type": "code",
+   "execution_count": 3,
    "id": "94892f4134316f8e",
    "metadata": {
-    "jupyter": {
-     "is_executing": true
-    },
     "ExecuteTime": {
      "start_time": "2025-10-29T02:30:10.298891Z"
+    },
+    "jupyter": {
+     "is_executing": true
     }
    },
+   "outputs": [
+    {
+     "data": {
+      "text/markdown": [
+       "### 开始执行任务ID 2"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "---"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m2025-10-30 13:57:49\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mmysql_agent\u001b[0m - \u001b[1m查询执行成功\u001b[0m\n",
+      "\u001b[32m2025-10-30 13:57:49\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1mRSS数据处理器初始化完成\u001b[0m\n",
+      "\u001b[32m2025-10-30 13:57:49\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1m开始处理RSS数据...\u001b[0m\n",
+      "\u001b[32m2025-10-30 13:57:50\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1m成功加载 6 条未处理的RSS数据\u001b[0m\n",
+      "\u001b[32m2025-10-30 13:57:50\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1m成功加载停用词表，共 98 个词\u001b[0m\n",
+      "\u001b[32m2025-10-30 13:57:50\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1m成功加载汽车后市场关键词，共 37 个\u001b[0m\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Building prefix dict from the default dictionary ...\n",
+      "Loading model from cache C:\\Users\\zy187\\AppData\\Local\\Temp\\jieba.cache\n",
+      "Loading model cost 0.839 seconds.\n",
+      "Prefix dict has been built successfully.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[32m2025-10-30 13:57:50\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1m数据处理完成，共处理 6 条记录\u001b[0m\n",
+      "\u001b[32m2025-10-30 13:57:50\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1m过滤出 0 条汽车后市场相关新闻\u001b[0m\n",
+      "\u001b[32m2025-10-30 13:57:51\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1m成功标记 6 条数据为已处理\u001b[0m\n",
+      "\u001b[32m2025-10-30 13:57:51\u001b[0m | \u001b[1mINFO    \u001b[0m | \u001b[36mprocessor_rss_data\u001b[0m - \u001b[1mRSS数据处理完成\u001b[0m\n"
+     ]
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "**任务名称**: RSS基于规则数据处理"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "**任务ID**: 2"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "**执行时长**: 4.41 秒"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "---"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/markdown": [
+       "### ✅ 任务执行成功"
+      ],
+      "text/plain": [
+       "<IPython.core.display.Markdown object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'success': True,\n",
+       " 'task_name': 'RSS基于规则数据处理',\n",
+       " 'task_id': 2,\n",
+       " 'execution_time': 4.414557695388794,\n",
+       " 'output': '',\n",
+       " 'error': None}"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "# 手动执行任务（异步方式，快速返回）\n",
     "def run_task_manually(task_id):\n",
@@ -854,47 +1009,8 @@
     "    return result\n",
     "\n",
     "# 执行：手动运行任务ID为2的任务（显示详细执行过程）\n",
-    "run_task_with_details(3)"
-   ],
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ],
-      "text/markdown": "### 开始执行任务ID 3"
-     },
-     "metadata": {},
-     "output_type": "display_data",
-     "jetTransient": {
-      "display_id": null
-     }
-    },
-    {
-     "data": {
-      "text/plain": [
-       "<IPython.core.display.Markdown object>"
-      ],
-      "text/markdown": "---"
-     },
-     "metadata": {},
-     "output_type": "display_data",
-     "jetTransient": {
-      "display_id": null
-     }
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\u001B[32m2025-10-29 10:30:10\u001B[0m | \u001B[1mINFO    \u001B[0m | \u001B[36mmysql_agent\u001B[0m - \u001B[1m查询执行成功\u001B[0m\n",
-      "\u001B[32m2025-10-29 10:30:11\u001B[0m | \u001B[1mINFO    \u001B[0m | \u001B[36mai_processor_rss_data\u001B[0m - \u001B[1mRSS数据AI处理器初始化完成\u001B[0m\n",
-      "\u001B[32m2025-10-29 10:30:11\u001B[0m | \u001B[1mINFO    \u001B[0m | \u001B[36mai_processor_rss_data\u001B[0m - \u001B[1m开始批量处理数据，批次大小: 200, 延迟: 1.5秒\u001B[0m\n",
-      "\u001B[32m2025-10-29 10:30:11\u001B[0m | \u001B[1mINFO    \u001B[0m | \u001B[36mai_processor_rss_data\u001B[0m - \u001B[1m成功加载 3 条未处理的数据\u001B[0m\n"
-     ]
-    }
-   ],
-   "execution_count": null
+    "run_task_with_details(2)"
+   ]
   },
   {
    "cell_type": "markdown",

utils/Ding_api.py

@@ -0,0 +1,52 @@
+import requests
+from typing import Optional
+
+
+class DingAPI():
+    def __init__(self):
+        self.token = None
+        self.url = ''
+
+    def get_token(self) -> Optional:
+        """
+        获取Access Token
+        return: token(str)
+        """
+
+        url = 'https://api.dingtalk.com/v1.0/oauth2/dinga88e3d35525b86ca/token'
+
+        payload = {
+            "client_id": "dingn3de1pyuwkymohhe",
+            "client_secret": "qv__egWJnLVXh14_R1rfD_vBi7M8Gzhnk94EJN6puMzsqqpBCP8U7Ow-zA7SV8Rx",
+            "grant_type": "client_credentials"
+        }
+
+        response = requests.post(url, json=payload)
+        token = response.json().get('access_token')
+
+        return token
+
+
+    def card_create(self, data):
+        """
+        创建并投放卡片
+        return: response(dict)
+        """
+        url = 'https://api.dingtalk.com/v1.0/card/instances/createAndDeliver'
+
+        headers = {
+            'x-acs-dingtalk-access-token': data["token"],
+            'Content-Type': 'application/json'
+        }
+
+        data = {
+            "cardTemplateId": "cee2715f-001d-41cb-8fcd-3be18be9fbf5.schema",
+            "outTrackId": "",
+            "cardData":"",
+            "openSpaceId":"dtv1.card//IM_GROUP.4210192048793363",# 场域id
+        }
+        response = requests.post(url, json=data, headers=headers)
+        return response.json()
+
+    def get_
+

utils/mysql_agent.py

@@ -153,6 +153,12 @@ class MySQLAgent:
         """
         兼容旧接口的通用插入方法：保留replace参数，同时支持新的ignore_duplicates
         自动处理重复数据，对所有数据源通用，插入失败的数据会通过日志记录
+        
+        安全性说明:
+            - 使用 INSERT INTO（不是 REPLACE INTO 或 INSERT ... ON DUPLICATE KEY UPDATE）
+            - 当 ignore_duplicates=True 时，重复记录会被跳过，不会覆盖或删除现有数据
+            - 如果数据库连接失败，操作会抛出异常，不会部分成功
+            - 所有操作都是安全的，不会导致数据丢失或覆盖
         """
         # 【兼容性处理】如果未指定ignore_duplicates，用replace参数推导
         if ignore_duplicates is None:
@@ -592,6 +598,114 @@ class MySQLAgent:
                            exc_info=True)
             return False
 
+    def create_table_if_not_exists(self, table_name: str, create_sql: str) -> bool:
+        """
+        创建表（如果不存在）
+        使用 CREATE TABLE IF NOT EXISTS，不会删除已存在的表和数据
+        
+        参数:
+            table_name: 表名
+            create_sql: 完整的 CREATE TABLE SQL 语句（必须包含 IF NOT EXISTS）
+        
+        返回:
+            bool: 是否成功（表已存在也会返回True）
+        
+        注意:
+            - 此方法使用 CREATE TABLE IF NOT EXISTS，是安全的，不会删除现有数据
+            - 如果连接失败，会抛出异常
+        """
+        if "IF NOT EXISTS" not in create_sql.upper():
+            self.log.warning(f"CREATE TABLE 语句建议使用 IF NOT EXISTS 以保证安全性")
+        
+        try:
+            self.execute_sql(create_sql)
+            self.log.info(f"成功创建/检查表（表已存在时不会删除数据）: {table_name}")
+            return True
+        except Exception as e:
+            self.log.error(f"创建/检查表失败（可能是数据库连接问题）: {str(e)}", 
+                         table=table_name, exc_info=True)
+            raise
+
+    def add_unique_index_if_not_exists(self, table_name: str, index_name: str, 
+                                      column_name: str, column_length: int = 500,
+                                      check_duplicates: bool = True) -> bool:
+        """
+        添加唯一索引（如果不存在）
+        不会删除数据，只添加索引
+        
+        参数:
+            table_name: 表名
+            index_name: 索引名称
+            column_name: 要添加索引的列名
+            column_length: 索引长度（对于VARCHAR/TEXT类型）
+            check_duplicates: 是否在添加索引前检查重复数据
+        
+        返回:
+            bool: 是否成功添加索引（索引已存在也会返回True）
+        
+        注意:
+            - 此方法是安全的，不会删除数据
+            - 如果表中存在重复数据，会跳过添加索引（不会删除数据）
+            - 如果连接失败，会抛出异常
+        """
+        try:
+            # 1. 检查索引是否已存在
+            check_index_sql = f"""
+            SELECT COUNT(*) as cnt
+            FROM INFORMATION_SCHEMA.STATISTICS
+            WHERE TABLE_SCHEMA = %s
+              AND TABLE_NAME = %s
+              AND INDEX_NAME = %s
+            """
+            result = self.query_to_df(
+                check_index_sql, 
+                params=(self.config['database'], table_name, index_name),
+                is_print=False
+            )
+            
+            if not result.empty and result['cnt'].iloc[0] > 0:
+                self.log.debug(f"唯一索引 {index_name} 已存在，跳过添加")
+                return True
+            
+            # 2. 如果启用重复检查，先检查是否有重复数据
+            if check_duplicates:
+                check_duplicates_sql = f"""
+                SELECT {column_name}, COUNT(*) as cnt
+                FROM `{table_name}`
+                WHERE {column_name} IS NOT NULL AND {column_name} != ''
+                GROUP BY {column_name}
+                HAVING cnt > 1
+                LIMIT 1
+                """
+                duplicates = self.query_to_df(check_duplicates_sql, is_print=False)
+                
+                if not duplicates.empty:
+                    self.log.warning(
+                        f"表 {table_name} 中存在重复的 {column_name} 数据，无法添加唯一索引。"
+                        "现有数据不会被删除。",
+                        duplicate_count=len(duplicates)
+                    )
+                    return False
+            
+            # 3. 添加唯一索引
+            add_index_sql = f"""
+            ALTER TABLE `{table_name}`
+            ADD UNIQUE KEY `{index_name}` ({column_name}({column_length}))
+            """
+            self.execute_sql(add_index_sql)
+            self.log.info(f"成功添加唯一索引 {index_name}（现有数据不受影响）")
+            return True
+            
+        except Exception as e:
+            error_msg = str(e)
+            # 如果索引已存在，不报错
+            if "Duplicate key name" in error_msg or "already exists" in error_msg.lower():
+                self.log.debug(f"唯一索引 {index_name} 已存在，跳过添加")
+                return True
+            else:
+                self.log.warning(f"添加唯一索引时出现问题（不影响现有数据）: {error_msg}")
+                raise
+
     def execute_sql(self, sql: str, params: Union[tuple, dict, None] = None,
                     fetch: bool = False) -> Union[int, List[Dict[str, Any]]]:
         """执行SQL语句（原有逻辑完全保留）"""