mirror of
https://github.com/ChuXunYu/OfficeFileHandle.git
synced 2026-01-31 10:11:25 +00:00
103 lines
3.6 KiB
Python
103 lines
3.6 KiB
Python
import subprocess
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import os
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import re
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import json
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from pathlib import Path
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def convert_compact_mode(docx_file):
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path_obj = Path(docx_file)
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base_name = path_obj.stem
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output_md = f"{base_name}_Compact.md"
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media_folder = f"{base_name}_images"
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metadata_file = f"{base_name}_metadata.json"
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images_list_file = f"{base_name}_images.txt"
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# 1. 关键修改：使用 gfm 格式，强制生成紧凑表格
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cmd = ["pandoc", docx_file, "-o", output_md,
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"--to=gfm", # <--- 核心改动：使用 GitHub 风格，拒绝网格表
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"--standalone",
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f"--extract-media={media_folder}",
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"--wrap=none",
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"--markdown-headings=atx"]
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try:
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subprocess.run(cmd, check=True, capture_output=True)
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except Exception as e:
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print(f"❌ 转换出错: {e}")
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return
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with open(output_md, 'r', encoding='utf-8') as f:
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content = f.read()
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# 2. 紧凑版正则清洗
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# 因为 gfm 主要是 pipe table，我们只需要匹配 |...| 结构
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# 并且不仅匹配，还要把里面为了对齐而产生的多余空格给压扁
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# 这一步将 "| 文本 |" 压缩为 "| 文本 |"
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def compress_table_row(match):
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row = match.group(0)
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# 将连续的空格替换为单个空格，但保留结构
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return re.sub(r' +', ' ', row)
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# 匹配标准 Markdown 表格行
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content = re.sub(r'^\|.*\|$', compress_table_row, content, flags=re.MULTILINE)
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# 3. 标记表格 (逻辑简化，因为现在只有一种表格格式了)
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tbl_count = 0
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def tag_table(match):
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nonlocal tbl_count
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tbl_count += 1
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return f"\n\n**[表格 {tbl_count}]**\n{match.group(0)}\n"
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# 匹配连续的表格块
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table_block_regex = r'(\|.*\|[\r\n]+)+(\|[\s\-:|]+\|[\r\n]+)(\|.*\|[\r\n]*)+'
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content = re.sub(table_block_regex, tag_table, content)
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# 4. 图片处理与清单 (保持不变)
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img_count = 0
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img_details = []
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def img_replacer(m):
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nonlocal img_count
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img_count += 1
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path = m.group(2) or m.group(3) or ""
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filename = os.path.basename(path)
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img_details.append(filename)
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return f"\n\n**[图片 {img_count}: {filename}]**\n{m.group(0)}\n"
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content = re.sub(r'(!\[.*?\]\((.*?)\)|\[.*?\]:\s*([^\s]+\.(?:png|jpg|jpeg|gif|bmp))(\s*\{.*?\})?)', img_replacer, content)
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# 5. 深度清洗噪声
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content = re.sub(r'\[(.*?)\]\(\\l\)', r'\1', content)
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content = re.sub(r'\[(.*?)\]\[\d+\]', r'\1', content)
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content = re.sub(r'\{width=.*?\}', '', content)
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content = re.sub(r'\n{3,}', '\n\n', content)
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# 6. 保存元信息与清单
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with open(images_list_file, 'w', encoding='utf-8') as f:
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f.write(f"文档 {base_name} 图片清单：\n" + "="*30 + "\n")
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for i, name in enumerate(img_details, 1):
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f.write(f"{i}. {name}\n")
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stats = {
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"filename": base_name,
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"table_count": tbl_count,
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"image_count": img_count,
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"char_count": len(content),
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# 重新预估 Token，因为去掉了空格，这个值会更准
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"estimated_tokens": int(len(content) * 0.6)
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}
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with open(metadata_file, 'w', encoding='utf-8') as f:
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json.dump(stats, f, indent=4, ensure_ascii=False)
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with open(output_md, 'w', encoding='utf-8') as f:
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f.write(content)
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print(f"\n" + "="*60)
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print(f"✅ 紧凑版转换完成！已去除冗余空格")
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print(f"📁 文档: {output_md}")
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print(f"📊 统计: {img_count} 图片, {tbl_count} 表格")
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print(f"📉 Token 节省: 预估比原版节省 30% 空间")
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print("="*60)
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if __name__ == "__main__":
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convert_compact_mode("1.docx") |