Initial commit: 教务系统在线平台

- 包含4个产业方向的前端项目：智能开发、智能制造、大健康、财经商贸
- 已清理node_modules、.yoyo等大文件，项目大小从2.6GB优化至631MB
- 配置完善的.gitignore文件

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

frontend_财经商贸/deep_clean_modified.py

@@ -0,0 +1,114 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import re
+
+def deep_clean_markdown(content):
+    """深度清理markdown内容中的所有删除线和加粗符号"""
+    if not content:
+        return content
+    
+    # 1. 删除所有类型的删除线及其内容
+    # 标准删除线 ~~text~~
+    content = re.sub(r'~~[^~]*~~', '', content)
+    # 中文删除线 ～～text～～
+    content = re.sub(r'～～[^～]*～～', '', content)
+    
+    # 2. 去除加粗符号但保留内容
+    # **text** -> text
+    content = re.sub(r'\*\*([^*]+)\*\*', r'\1', content)
+    # __text__ -> text  
+    content = re.sub(r'__([^_]+)__', r'\1', content)
+    
+    # 3. 清理因删除产生的多余符号和空格
+    # 清理多余的逗号和顿号
+    content = re.sub(r'，\s*，', '，', content)
+    content = re.sub(r'、\s*、', '、', content)
+    content = re.sub(r'，\s*。', '。', content)
+    content = re.sub(r'、\s*。', '。', content)
+    
+    # 清理行首的逗号或顿号
+    content = re.sub(r'^[，、]\s*', '', content, flags=re.MULTILINE)
+    
+    # 清理多余的空格
+    content = re.sub(r' {2,}', ' ', content)
+    content = re.sub(r'\n{3,}', '\n\n', content)
+    
+    # 清理空的列表项
+    content = re.sub(r'^\d+\.\s*$', '', content, flags=re.MULTILINE)
+    content = re.sub(r'^\d+\.\s*\n', '', content, flags=re.MULTILINE)
+    
+    return content.strip()
+
+# 读取文件
+with open('src/mocks/resumeInterviewMock.js', 'r', encoding='utf-8') as f:
+    content = f.read()
+
+# 需要清理的岗位列表
+positions_to_clean = [
+    "会展策划师",
+    "会展讲解员", 
+    "活动执行",
+    "活动策划师",
+    "漫展策划师",
+    "会展执行助理",
+    "旅游规划师",
+    "旅游计调专员",
+    "景区运营专员",
+    "文旅运营总监助理"
+]
+
+print("开始深度清理修改版简历内容...")
+total_cleaned = 0
+
+for position in positions_to_clean:
+    # 查找该岗位的modified内容
+    # 使用更宽松的正则表达式来匹配
+    pattern = rf'title:\s*["\']({position})["\'][^}}]*?modified:\s*`([^`]+)`'
+    
+    matches = list(re.finditer(pattern, content, re.DOTALL))
+    
+    for match in matches:
+        original_modified = match.group(2)
+        
+        # 统计删除线数量
+        strikethrough_count = len(re.findall(r'~~[^~]*~~', original_modified))
+        strikethrough_count += len(re.findall(r'～～[^～]*～～', original_modified))
+        
+        # 统计加粗数量
+        bold_count = len(re.findall(r'\*\*[^*]+\*\*', original_modified))
+        bold_count += len(re.findall(r'__[^_]+__', original_modified))
+        
+        if strikethrough_count > 0 or bold_count > 0:
+            cleaned_modified = deep_clean_markdown(original_modified)
+            
+            # 替换内容
+            old_text = f"modified: `{original_modified}`"
+            new_text = f"modified: `{cleaned_modified}`"
+            content = content.replace(old_text, new_text)
+            
+            print(f"\n✓ {position}")
+            print(f"  - 删除了 {strikethrough_count} 处删除线")
+            print(f"  - 清理了 {bold_count} 处加粗符号")
+            total_cleaned += 1
+
+# 写回文件
+with open('src/mocks/resumeInterviewMock.js', 'w', encoding='utf-8') as f:
+    f.write(content)
+
+print(f"\n✅ 深度清理完成！共处理了 {total_cleaned} 个岗位的修改版内容")
+
+# 验证是否还有遗漏的删除线
+remaining_strikethrough = len(re.findall(r'~~[^~]*~~', content))
+remaining_strikethrough += len(re.findall(r'～～[^～]*～～', content))
+
+if remaining_strikethrough > 0:
+    print(f"\n⚠️ 警告：文件中仍有 {remaining_strikethrough} 处删除线符号")
+    # 查找并显示位置
+    for match in re.finditer(r'(~~[^~]*~~|～～[^～]*～～)', content):
+        start = max(0, match.start() - 50)
+        end = min(len(content), match.end() + 50)
+        context = content[start:end]
+        print(f"  位置: ...{context}...")
+else:
+    print("\n✅ 已确认：所有删除线符号都已清理完毕")