Initial commit: Markdown editor with file management and regex tools
项目特性： - 完整的Markdown编辑器，支持实时预览 - 文件管理功能，支持保存/加载/删除文件 - 正则表达式工具，支持批量文本替换 - 前后端分离架构 - 响应式设计 技术栈： - 前端：React + TypeScript + Vite - 后端：Python Flask - Markdown解析：Python-Markdown 包含组件： - WorkingMarkdownEditor: 基础功能版本 - FullMarkdownEditor: 完整功能版本 - SimpleMarkdownEditor: 简化版本
This commit is contained in:
guo liwei
310
backend/utils/regex_processor.py
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310
backend/utils/regex_processor.py
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"""
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正则表达式处理器模块
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提供基于正则表达式的文本批量操作功能
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"""
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import re
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from typing import Dict, List, Any, Tuple
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class RegexProcessor:
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"""
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正则表达式处理器类
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提供各种基于正则表达式的文本处理功能，包括替换、提取、验证等
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"""
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def __init__(self):
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"""初始化正则表达式处理器"""
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self.compiled_patterns = {}
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def _compile_pattern(self, pattern: str, flags: str = '') -> re.Pattern:
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"""
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编译正则表达式模式，使用缓存提高性能
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Args:
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pattern (str): 正则表达式模式
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flags (str): 正则表达式标志
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Returns:
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re.Pattern: 编译后的正则表达式对象
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"""
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cache_key = f"{pattern}:{flags}"
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if cache_key not in self.compiled_patterns:
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flag_value = 0
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for flag in flags.lower():
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if flag == 'i':
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flag_value |= re.IGNORECASE
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elif flag == 'm':
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flag_value |= re.MULTILINE
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elif flag == 's':
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flag_value |= re.DOTALL
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elif flag == 'x':
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flag_value |= re.VERBOSE
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elif flag == 'u':
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flag_value |= re.UNICODE
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elif flag == 'l':
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flag_value |= re.LOCALE
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self.compiled_patterns[cache_key] = re.compile(pattern, flag_value)
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return self.compiled_patterns[cache_key]
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def replace(self, content: str, pattern: str, replacement: str, flags: str = '') -> Dict[str, Any]:
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"""
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使用正则表达式替换文本
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Args:
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content (str): 原始文本
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pattern (str): 正则表达式模式
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replacement (str): 替换内容
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flags (str): 正则表达式标志
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Returns:
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Dict[str, Any]: 替换结果信息
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{
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'result': str, # 替换后的文本
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'matches': int, # 匹配次数
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'groups': List[str], # 匹配的组
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'replacements': List[Dict[str, str]] # 详细的替换信息
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}
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"""
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regex = self._compile_pattern(pattern, flags)
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# 收集匹配信息
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matches = list(regex.finditer(content))
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replacements = []
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def replace_func(match):
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groups = match.groups()
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replacement_result = match.expand(replacement)
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replacements.append({
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'original': match.group(0),
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'replaced': replacement_result,
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'start': match.start(),
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'end': match.end(),
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'groups': list(groups) if groups else []
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})
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return replacement_result
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# 执行替换
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result = regex.sub(replace_func, content)
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return {
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'result': result,
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'matches': len(matches),
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'groups': [match.groups() for match in matches if match.groups()],
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'replacements': replacements
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}
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def extract(self, content: str, pattern: str, flags: str = '') -> List[Dict[str, Any]]:
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"""
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使用正则表达式提取匹配项
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Args:
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content (str): 文本内容
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pattern (str): 正则表达式模式
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flags (str): 正则表达式标志
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Returns:
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List[Dict[str, Any]]: 匹配项列表
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[
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{
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'match': str, # 完整匹配
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'groups': List[str], # 捕获组
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'start': int, # 开始位置
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'end': int, # 结束位置
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'named_groups': Dict[str, str] # 命名捕获组
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}
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]
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"""
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regex = self._compile_pattern(pattern, flags)
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matches = []
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for match in regex.finditer(content):
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match_info = {
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'match': match.group(0),
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'groups': list(match.groups()) if match.groups() else [],
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'start': match.start(),
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'end': match.end(),
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'named_groups': match.groupdict()
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}
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matches.append(match_info)
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return matches
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def validate(self, content: str, pattern: str, flags: str = '') -> bool:
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"""
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验证文本是否匹配正则表达式
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Args:
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content (str): 文本内容
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pattern (str): 正则表达式模式
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flags (str): 正则表达式标志
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Returns:
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bool: 是否匹配
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"""
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regex = self._compile_pattern(pattern, flags)
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return bool(regex.search(content))
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def split(self, content: str, pattern: str, flags: str = '', maxsplit: int = 0) -> Dict[str, Any]:
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"""
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使用正则表达式分割文本
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Args:
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content (str): 文本内容
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pattern (str): 正则表达式模式
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flags (str): 正则表达式标志
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maxsplit (int): 最大分割次数
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Returns:
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Dict[str, Any]: 分割结果
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{
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'parts': List[str], # 分割后的部分
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'separators': List[str], # 分隔符
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'count': int # 分割次数
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}
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"""
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regex = self._compile_pattern(pattern, flags)
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if maxsplit > 0:
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parts = regex.split(content, maxsplit)
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else:
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parts = regex.split(content)
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# 找出分隔符
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separators = [match.group(0) for match in regex.finditer(content)]
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return {
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'parts': parts,
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'separators': separators,
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'count': len(separators)
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}
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def find_and_replace_batch(self, content: str, operations: List[Dict[str, str]]) -> Dict[str, Any]:
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"""
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批量执行正则表达式替换操作
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Args:
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content (str): 原始文本
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operations (List[Dict[str, str]]): 替换操作列表
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[
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{
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'pattern': str, # 正则表达式
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'replacement': str, # 替换内容
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'flags': str # 正则表达式标志
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}
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]
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Returns:
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Dict[str, Any]: 批量替换结果
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{
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'result': str, # 最终文本
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'operations': List[Dict[str, Any]] # 每个操作的结果
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}
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"""
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result = content
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operation_results = []
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for operation in operations:
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pattern = operation['pattern']
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replacement = operation['replacement']
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flags = operation.get('flags', '')
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replace_result = self.replace(result, pattern, replacement, flags)
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result = replace_result['result']
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operation_results.append({
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'pattern': pattern,
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'replacement': replacement,
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'flags': flags,
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'matches': replace_result['matches'],
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'replacements': replace_result['replacements']
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})
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return {
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'result': result,
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'operations': operation_results
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}
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def get_statistics(self, content: str, pattern: str, flags: str = '') -> Dict[str, Any]:
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"""
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获取正则表达式的匹配统计信息
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Args:
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content (str): 文本内容
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pattern (str): 正则表达式模式
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flags (str): 正则表达式标志
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Returns:
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Dict[str, Any]: 统计信息
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{
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'total_matches': int, # 总匹配数
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'unique_matches': int, # 唯一匹配数
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'average_length': float, # 平均匹配长度
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'longest_match': str, # 最长匹配
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'shortest_match': str, # 最短匹配
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'positions': List[Tuple[int, int]] # 匹配位置列表
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}
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"""
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matches = self.extract(content, pattern, flags)
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if not matches:
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return {
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'total_matches': 0,
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'unique_matches': 0,
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'average_length': 0.0,
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'longest_match': '',
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'shortest_match': '',
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'positions': []
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}
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match_texts = [m['match'] for m in matches]
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lengths = [len(text) for text in match_texts]
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return {
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'total_matches': len(matches),
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'unique_matches': len(set(match_texts)),
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'average_length': sum(lengths) / len(lengths),
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'longest_match': max(match_texts, key=len),
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'shortest_match': min(match_texts, key=len),
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'positions': [(m['start'], m['end']) for m in matches]
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}
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def common_patterns(self) -> Dict[str, str]:
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"""
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返回常用正则表达式模式
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Returns:
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Dict[str, str]: 常用模式字典
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"""
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return {
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'email': r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b',
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'url': r'https?://(?:[-\w.])+(?:[:\d]+)?(?:/(?:[\w/_.])*(?:\?(?:[\w&=%.])*)?(?:#(?:[\w.])*)?)?',
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'phone': r'(\+?\d{1,3}[-.\s]?)?\(?\d{3}\)?[-.\s]?\d{3}[-.\s]?\d{4}',
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'markdown_headers': r'^#{1,6}\s+(.+)$',
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'markdown_links': r'\[([^\]]+)\]\(([^)]+)\)',
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'markdown_images': r'!\[([^\]]*)\]\(([^)]+)\)',
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'markdown_bold': r'\*\*([^*]+)\*\*|__([^_]+)__',
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'markdown_italic': r'\*([^*]+)\*|_([^_]+)_',
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'code_blocks': r'```(\w*)\n(.*?)\n```',
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'inline_code': r'`([^`]+)`',
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'numbers': r'\d+',
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'words': r'\b\w+\b',
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'whitespace': r'\s+',
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'lines': r'.*(?:\n|$)',
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'markdown_tables': r'\|(.+)\|\n\|[-:\| ]+\|\n((?:\|.+\|\n?)*)',
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'markdown_lists': r'^(\s*)[-*+]\s+(.+)$',
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'markdown_quotes': r'^\s*>\s*(.+)',
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'html_tags': r'</?[a-zA-Z][^>]*\u003e',
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'ip_address': r'\b(?:\d{1,3}\.){3}\d{1,3}\b',
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'date_ymd': r'\d{4}-\d{2}-\d{2}',
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'date_dmy': r'\d{2}/\d{2}/\d{4}',
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'time_hms': r'\d{2}:\d{2}:\d{2}',
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'hex_color': r'#(?:[0-9a-fA-F]{3}){1,2}\b',
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'markdown_task_lists': r'^\s*[-*+]\s+\[([ x])\]\s+(.+)$'
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}
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