92 lines
2.9 KiB
Python
92 lines
2.9 KiB
Python
"""
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this script can identify xml tags competency within a column of selected Dataframe.
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It will collect the complete and incomplete tags into 2 separate columns.
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"""
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import pandas as pd
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from lxml import etree
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import re
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data = {
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'Response': [
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'<tag1>content1</tag1> some text here',
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'<tag2>content2<tag3>content3</tag3></tag2> more text',
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"<tag4 content=\"attribute\">content4</tag4> additional text",
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'<tag5>incomplete</tag5> extra text',
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'</tag6> miscellaneous text',
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# ... 其他数据
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]
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}
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# df = pd.DataFrame(data)
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# 正则表达式匹配完整的XML标签
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complete_tag_pattern = re.compile(r'<(\w+)[^>]*>.*?</\1>')
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# 正则表达式匹配不完整的XML标签
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incomplete_tag_pattern = re.compile(r'<(\w+)[^>]*>.*?$')
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# 正则表达式匹配所有开放标签和闭合标签
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open_tag_pattern = re.compile(r'<(\w+)[^>]*>')
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close_tag_pattern = re.compile(r'</(\w+)>')
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# 函数：使用正则表达式提取标签，并分类完整和不完整的标签
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def classify_tags(xml_string):
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# 找到所有开放标签和闭合标签
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open_tags = set(open_tag_pattern.findall(xml_string))
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close_tags = set(close_tag_pattern.findall(xml_string))
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# 确定不完整的标签：只有开放标签或只有闭合标签的
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incomplete_tags = list(open_tags - close_tags) + list(close_tags - open_tags)
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# 确定完整的标签：既有开放标签又有闭合标签的
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complete_tags = [f"<{tag}></{tag}>" for tag in open_tags.intersection(close_tags)]
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# 将标签列表转换为字符串
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complete_tags_str = ', '.join(complete_tags) if complete_tags else ''
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incomplete_tags_str = ', '.join(
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[f"<{tag}>" if tag in open_tags else f"</{tag}>" for tag in incomplete_tags]) if incomplete_tags else ''
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return complete_tags_str, incomplete_tags_str
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def check_df_tags(df=pd.DataFrame(data)):
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# 应用函数到DataFrame
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df['CompleteTags'], df['IncompleteTags'] = zip(*df['Response'].apply(classify_tags))
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return df
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# 正则表达式匹配非XML标签的英文字符
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non_tag_english_chars_pattern = re.compile(r'>[^<>]*<|<[^<>]*>')
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# 函数：提取非XML标签的英文字符
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def extract_english_chars(response):
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# 移除XML标签
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non_tags_content = re.sub(non_tag_english_chars_pattern, '', response)
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# 提取英文字符
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english_chars = re.findall(r'[A-Za-z]+', non_tags_content)
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# 将提取的英文字符转换为字符串
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english_chars_str = ' '.join(english_chars) if english_chars else ''
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return english_chars_str
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def check_df_english(df=pd.DataFrame(data)):
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# 应用函数到DataFrame
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df['EnglishChars'] = df['Response'].apply(extract_english_chars)
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return df
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if __name__ == '__main__':
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df = pd.read_excel('prompt_multiple_template0603_2_4steps_100tests.xlsx')
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checked_df = check_df_tags(df)
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checked_df = check_df_english(checked_df)
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# 保存结果到Excel文件
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checked_df.to_excel('output.xlsx', index=False)
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