746 lines
29 KiB
Python
746 lines
29 KiB
Python
# -*- coding: utf-8 -*-
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"""
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数据文件关联处理程序
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功能：解压压缩文件，读取 Word 文档，将文件与 Word 内容关联
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"""
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import os
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import sys
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import zipfile
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import json
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import argparse
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from pathlib import Path
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from typing import Optional, List, Dict, Tuple, Union
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from datetime import datetime
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import time
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import re
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import shutil
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import requests
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import math
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OLLAMA_EMBED_URL = os.environ.get('OLLAMA_EMBED_URL', 'http://localhost:11434/api/embeddings')
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OLLAMA_EMBED_MODEL = os.environ.get('OLLAMA_EMBED_MODEL', 'nomic/text-embedding-3-large')
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def clear_directory(dir_path: Path) -> None:
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"""清空目录中的所有文件和子目录"""
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if dir_path.exists():
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for item in dir_path.iterdir():
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if item.is_file():
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item.unlink()
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elif item.is_dir():
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shutil.rmtree(item)
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def get_embedding(text: str) -> List[float]:
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"""使用 Ollama 获取文本的 embedding"""
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try:
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response = requests.post(
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OLLAMA_EMBED_URL,
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json={
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'model': OLLAMA_EMBED_MODEL,
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'input': text,
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},
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timeout=10,
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)
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response.raise_for_status()
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data = response.json()
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if isinstance(data, dict):
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if 'embedding' in data:
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return data['embedding']
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if 'data' in data and isinstance(data['data'], list) and data['data']:
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return data['data'][0].get('embedding', []) or []
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return []
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except Exception as e:
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print(f"获取 embedding 失败: {e}")
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return []
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def cosine_similarity(vec1: List[float], vec2: List[float]) -> float:
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"""计算两个向量的余弦相似度"""
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if not vec1 or not vec2:
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return 0.0
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dot = sum(a * b for a, b in zip(vec1, vec2))
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norm1 = math.sqrt(sum(a * a for a in vec1))
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norm2 = math.sqrt(sum(b * b for b in vec2))
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return dot / (norm1 * norm2) if norm1 and norm2 else 0.0
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def normalize_for_match(text: str) -> str:
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"""规范化文本，去掉路径和扩展名后的匹配用字符串"""
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text = str(text).lower()
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text = re.sub(r'[\u0020-\u002f\u003a-\u0040\u005b-\u0060\u007b-\u007e]+', ' ', text)
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text = re.sub(r'\s+', ' ', text).strip()
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return text
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def token_overlap_score(a: str, b: str) -> float:
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tokens_a = set(re.findall(r'[\u4e00-\u9fff]+|\d+|[a-z]+', a))
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tokens_b = set(re.findall(r'[\u4e00-\u9fff]+|\d+|[a-z]+', b))
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if not tokens_a or not tokens_b:
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return 0.0
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return len(tokens_a & tokens_b) / max(1, len(tokens_b))
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def find_best_match(title: str, candidates: List[Tuple[Path, datetime]]) -> Tuple[Path, datetime]:
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"""从候选文件中找到与 title 最相似的文件"""
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if not candidates:
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return None
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title_norm = normalize_for_match(title)
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exact_candidates = []
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for file_path, ctime in candidates:
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stem_norm = normalize_for_match(file_path.stem)
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if stem_norm and (stem_norm == title_norm or stem_norm in title_norm or title_norm in stem_norm):
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exact_candidates.append((file_path, ctime, stem_norm))
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if exact_candidates:
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# 直接返回最精确的“包含匹配”候选项
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return max(exact_candidates, key=lambda item: len(item[2]))[:2]
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title_emb = get_embedding(title)
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best_match = None
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best_score = -1.0
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for file_path, ctime in candidates:
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stem_norm = normalize_for_match(file_path.stem)
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overlap = token_overlap_score(title_norm, stem_norm)
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score = overlap * 0.3
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if title_emb:
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stem_emb = get_embedding(file_path.stem)
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if stem_emb:
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score += cosine_similarity(title_emb, stem_emb) * 0.7
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if score > best_score:
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best_score = score
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best_match = (file_path, ctime)
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return best_match or candidates[0]
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def extract_all_zips(
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source_dir: Union[str, Path] = "cc",
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output_dir: Union[str, Path] = "data",
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delete_original: bool = True
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) -> List[Path]:
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"""
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解压指定目录中的所有 zip 文件
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Args:
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source_dir: 包含压缩文件的目录
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output_dir: 输出目录
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delete_original: 解压后删除原文件
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Returns:
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所有解压后的目录路径列表
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"""
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source_dir = Path(source_dir)
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output_dir = Path(output_dir)
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# 清空 output_dir
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clear_directory(output_dir)
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zip_files = list(source_dir.glob("*.zip"))
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if not zip_files:
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print(f"在 {source_dir} 中未发现 zip 文件")
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return []
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print(f"找到 {len(zip_files)} 个压缩文件，开始解压到 {output_dir}...")
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results = []
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for zip_file in zip_files:
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# 解压到指定目录
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extract_dir = output_dir / zip_file.stem
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extract_dir.mkdir(parents=True, exist_ok=True)
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with zipfile.ZipFile(zip_file, 'r') as zip_ref:
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# 解压所有文件并保留原始时间戳
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for member in zip_ref.infolist():
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# 解压文件
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zip_ref.extract(member, extract_dir)
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# 获取解压后的文件路径
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member_path = extract_dir / member.filename
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# 如果文件存在，设置时间戳
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if member_path.exists():
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# 将 ZipInfo 的日期时间转换为时间戳
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date_time = datetime(*member.date_time[:5])
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timestamp = date_time.timestamp()
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# 设置访问时间和修改时间
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os.utime(member_path, (timestamp, timestamp))
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# 检查是否多了一层目录（zip 内部只有一个同名文件夹）
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inner_dir = extract_dir / zip_file.stem
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if inner_dir.is_dir() and len(list(extract_dir.iterdir())) == 1:
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# 移动内部文件夹所有内容到外层
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for item in inner_dir.iterdir():
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item.rename(extract_dir / item.name)
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# 删除空的内层文件夹
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inner_dir.rmdir()
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print(f"✓ 已解压：{zip_file.name} (移除了多余目录层)")
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else:
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print(f"✓ 已解压：{zip_file.name}")
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results.append(extract_dir)
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# 删除原压缩包
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if delete_original:
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zip_file.unlink()
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return results
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def read_word_content(doc_path: Path) -> List[str]:
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"""读取 Word 文档内容 (.docx 或 .doc)，提取文本行"""
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if doc_path.suffix.lower() == '.docx':
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return read_docx_content(doc_path)
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elif doc_path.suffix.lower() == '.doc':
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return read_doc_content(doc_path)
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return []
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def read_docx_content(doc_path: Path) -> List[str]:
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"""读取 .docx 格式 Word 文档内容"""
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try:
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with zipfile.ZipFile(doc_path, 'r') as z:
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content = z.read('word/document.xml').decode('utf-8')
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# 提取所有 <w:t>...</w:t> 中的内容，保留原始空白字符
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texts = re.findall(r'<w:t[^>]*>(.*?)</w:t>', content, re.DOTALL)
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# 去除 HTML 标签，不替换内部的空白字符
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processed = []
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for text in texts:
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text = re.sub(r'<[^>]+>', '', text).strip()
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if text:
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processed.append(text)
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# 拼接所有文本，保留 \t 和 \n
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full_text = '\n'.join(processed)
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# 智能检测：判断是使用 \t 分割 6 段，还是每行一个字段
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lines = full_text.split('\n')
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lines = [line.strip() for line in lines if line.strip()]
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# 检测是否每行都是单字段（没有\t）
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# 如果前几行都没有\t，可能是每行一个字段
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has_tab_in_first_rows = any('\t' in line for line in lines[:6])
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if not has_tab_in_first_rows and len(lines) >= 6:
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# 判断是否是 6 行一组的模式：第二行是网址且第三行是日期/时间
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def is_url_line(line: str) -> bool:
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"""判断一行是否是网址"""
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return bool(re.match(r'^https?://', line.strip()))
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def is_datetime_line(line: str) -> bool:
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"""判断一行是否是日期或时间"""
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datetime_pattern = r'^\d{4}[-/]\d{1,2}[-/]\d{1,2}\s+\d{1,2}:\d{2}'
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date_pattern = r'^\d{4}[-/]\d{1,2}[-/]\d{1,2}'
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return bool(re.match(datetime_pattern, line.strip())) or \
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bool(re.match(date_pattern, line.strip()))
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# 检查当前起始位置是否是 6 行一组模式
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def is_six_row_group(lines: list, start_idx: int) -> bool:
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"""检查从 start_idx 开始是否是 6 行一组"""
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if start_idx + 5 < len(lines):
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return is_url_line(lines[start_idx + 1]) and \
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is_datetime_line(lines[start_idx + 2]) and \
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is_url_line(lines[start_idx + 4]) and \
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is_datetime_line(lines[start_idx + 5])
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return False
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# 检查当前起始位置是否是 5 行一组模式
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def is_five_row_group(lines: list, start_idx: int) -> bool:
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"""检查从 start_idx 开始是否是 5 行一组"""
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if start_idx + 4 < len(lines):
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return is_url_line(lines[start_idx + 1]) and \
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is_datetime_line(lines[start_idx + 2]) and \
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is_url_line(lines[start_idx + 4])
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return False
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# 按组处理，每组独立判断 offset
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# 规则：优先检查 6 行一组，如果是则合并 6 行；否则检查 5 行一组，如果是则合并 5 行并补充时间；否则丢弃第一行，继续判断
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result = []
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i = 0
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while i + 4 <= len(lines):
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if i + 5 < len(lines) and is_six_row_group(lines, i):
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# 是 6 行一组，合并这 6 行
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combined = '\t'.join(lines[i:i+6])
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# 检查并补充缺失的时间信息
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parts = combined.split('\t')
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if len(parts) >= 3 and not is_datetime_line(parts[2]):
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parts[2] = '1970-1-1'
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if len(parts) >= 6 and not is_datetime_line(parts[5]):
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parts[5] = '1970-1-1'
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combined = '\t'.join(parts)
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result.append(combined)
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i += 6
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elif is_five_row_group(lines, i):
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# 是 5 行一组，合并这 5 行并补充时间2
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combined = '\t'.join(lines[i:i+5])
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# 检查并补充缺失的时间信息
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parts = combined.split('\t')
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if len(parts) >= 3 and not is_datetime_line(parts[2]):
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parts[2] = '1970-1-1'
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||
# 为第二组补充时间
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if len(parts) >= 5:
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parts.append('1970-1-1')
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combined = '\t'.join(parts)
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result.append(combined)
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i += 5
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else:
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# 不是有效组，丢弃当前行（相当于 offset+1）
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||
i += 1
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# 处理剩余行（不足 6 行的）
|
||
while i < len(lines):
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result.append(lines[i])
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i += 1
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||
return result
|
||
else:
|
||
# 每行已经有\t分割，直接返回
|
||
return lines
|
||
except Exception as e:
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||
print(f"读取 .docx 失败 ({doc_path.name}): {e}")
|
||
return []
|
||
|
||
|
||
def read_doc_content(doc_path: Path) -> List[str]:
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||
"""读取 .doc 格式 Word 文档内容（使用 LibreOffice）"""
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||
import subprocess
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||
import tempfile
|
||
|
||
soffice_paths = [
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||
'/Applications/LibreOffice.app/Contents/MacOS/soffice',
|
||
'/Applications/LibreOffice.app/Contents/MacOS/libreoffice',
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||
'soffice',
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||
]
|
||
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print(f"🔍 正在查找 LibreOffice...")
|
||
soffice_cmd = None
|
||
for path in soffice_paths:
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||
print(f" 检查：{path}")
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||
try:
|
||
import os
|
||
if os.path.isfile(path):
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||
print(f" ✓ 文件存在")
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||
result = subprocess.run([path, '--version'], capture_output=True, timeout=10)
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print(f" ✓ 版本检查返回码：{result.returncode}")
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||
print(f" 输出：{result.stdout.decode()[:100]}")
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||
if result.returncode == 0:
|
||
soffice_cmd = path
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print(f"✓ 使用 LibreOffice: {path}")
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||
break
|
||
except Exception as e:
|
||
print(f" ✗ 错误：{e}")
|
||
continue
|
||
|
||
if not soffice_cmd:
|
||
print("❌ LibreOffice 未安装或无法访问")
|
||
return []
|
||
|
||
print(f"📄 开始转换文件：{doc_path}")
|
||
try:
|
||
with tempfile.TemporaryDirectory() as tmpdir:
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||
print(f"📁 临时目录：{tmpdir}")
|
||
result = subprocess.run(
|
||
[soffice_cmd, '--headless', '--convert-to', 'txt', '--outdir', tmpdir, str(doc_path)],
|
||
capture_output=True,
|
||
timeout=60
|
||
)
|
||
print(f"🔄 转换返回码：{result.returncode}")
|
||
if result.returncode != 0:
|
||
print(f"✗ 转换失败：{result.stderr.decode()[:300]}")
|
||
return []
|
||
txt_file = Path(tmpdir) / (doc_path.stem + '.txt')
|
||
if txt_file.exists():
|
||
with open(txt_file, 'r', encoding='utf-8', errors='ignore') as f:
|
||
lines = [line.strip() for line in f.readlines() if line.strip()]
|
||
print(f"✓ 成功读取 {len(lines)} 行内容")
|
||
return lines
|
||
else:
|
||
print(f"✗ 转换后的文本文件不存在")
|
||
except Exception as e:
|
||
print(f"✗ LibreOffice 读取失败：{e}")
|
||
|
||
print(f"⚠️ 无法读取 .doc 文件 ({doc_path.name})")
|
||
return []
|
||
|
||
try:
|
||
import tempfile
|
||
with tempfile.TemporaryDirectory() as tmpdir:
|
||
result = subprocess.run(
|
||
[soffice_cmd, '--headless', '--convert-to', 'txt', '--outdir', tmpdir, str(doc_path)],
|
||
capture_output=True,
|
||
text=True,
|
||
timeout=60
|
||
)
|
||
if result.returncode != 0:
|
||
print(f"LibreOffice 转换失败：{result.stderr}")
|
||
return None
|
||
txt_file = Path(tmpdir) / (doc_path.stem + '.txt')
|
||
if txt_file.exists():
|
||
with open(txt_file, 'r', encoding='utf-8', errors='ignore') as f:
|
||
lines = [line.strip() for line in f.readlines() if line.strip()]
|
||
return lines
|
||
except Exception as e:
|
||
print(f"LibreOffice 读取失败：{e}")
|
||
|
||
print(f"⚠️ 无法读取 .doc 文件 ({doc_path.name})")
|
||
return []
|
||
|
||
|
||
def find_word_doc_recursive(base_dir: Path) -> Optional[Path]:
|
||
"""递归查找 base_dir 下符合目标的 Word 文档
|
||
|
||
目标目录条件：包含一个 Word 文件 (.docx 或 .doc) 以及两个子目录
|
||
如果当前目录只有一个子目录且无 Word 文件，则继续深入查找
|
||
"""
|
||
def find_target_dir(current_dir: Path) -> Optional[Path]:
|
||
items = list(current_dir.iterdir())
|
||
subdirs = [item for item in items if item.is_dir()]
|
||
word_files = [item for item in items if item.suffix.lower() in ('.docx', '.doc')]
|
||
|
||
# 目标条件：恰好一个 Word 文件且至少两个子目录
|
||
if len(word_files) == 1 and len(subdirs) >= 2:
|
||
return word_files[0]
|
||
|
||
# 只有一个子目录且没有 Word 文件，继续深入
|
||
if len(subdirs) == 1 and len(word_files) == 0:
|
||
return find_target_dir(subdirs[0])
|
||
|
||
return None
|
||
|
||
return find_target_dir(base_dir)
|
||
|
||
|
||
def get_files_with_times(folder: Path) -> List[Tuple[Path, datetime]]:
|
||
"""获取文件夹中所有文件及其创建时间"""
|
||
files = []
|
||
for f in folder.iterdir():
|
||
if f.is_file():
|
||
stat_info = f.stat()
|
||
# macOS 使用 st_birthtime 作为创建时间，其他系统使用 st_ctime
|
||
try:
|
||
ctime = datetime.fromtimestamp(stat_info.st_birthtime)
|
||
except AttributeError:
|
||
ctime = datetime.fromtimestamp(stat_info.st_ctime)
|
||
files.append((f, ctime))
|
||
files.sort(key=lambda x: x[1])
|
||
return files
|
||
|
||
|
||
def extract_zip_recursive(zip_path: Path, extract_dir: Path, clear_dir: bool = True) -> List[Path]:
|
||
"""递归解压 zip 文件，如果解压后的文件还有 zip，继续解压"""
|
||
# 先清空 extract_dir 中的内容
|
||
if clear_dir:
|
||
for item in extract_dir.iterdir():
|
||
if item.is_file():
|
||
item.unlink()
|
||
elif item.is_dir():
|
||
shutil.rmtree(item)
|
||
|
||
# 解压当前层
|
||
with zipfile.ZipFile(zip_path, 'r') as zip_ref:
|
||
zip_ref.extractall(extract_dir)
|
||
|
||
# 查找解压后的所有 zip 文件，递归解压
|
||
new_zips = list(extract_dir.glob("*.zip"))
|
||
while new_zips:
|
||
for z in new_zips:
|
||
with zipfile.ZipFile(z, 'r') as zip_ref:
|
||
zip_ref.extractall(extract_dir)
|
||
z.unlink() # 删除已解压的 zip 文件
|
||
new_zips = list(extract_dir.glob("*.zip"))
|
||
|
||
# 递归收集所有解压后的文件（包括子目录）
|
||
def collect_all_files(dir_path: Path) -> List[Path]:
|
||
files = []
|
||
for item in dir_path.iterdir():
|
||
if item.is_file():
|
||
files.append(item)
|
||
elif item.is_dir():
|
||
files.extend(collect_all_files(item))
|
||
return files
|
||
|
||
extracted_files = collect_all_files(extract_dir)
|
||
return extracted_files
|
||
|
||
|
||
def build_file_associations(
|
||
word_content: List[str],
|
||
twole_folder: Path,
|
||
zxxk_folder: Path,
|
||
) -> Dict:
|
||
"""构建文件关联关系"""
|
||
result = []
|
||
|
||
twole_files = get_files_with_times(twole_folder)
|
||
zxxk_files = get_files_with_times(zxxk_folder)
|
||
|
||
for i, content in enumerate(word_content):
|
||
# 按 \t 分割成段
|
||
parts = content.split('\t')
|
||
if len(parts) < 6:
|
||
continue
|
||
|
||
# 提取两组数据：标题、网址、时间
|
||
title1, url1, time1 = parts[0].strip(), parts[1].strip(), parts[2].strip()
|
||
title2, url2, time2 = parts[3].strip(), parts[4].strip(), parts[5].strip()
|
||
|
||
# 辅助函数：处理文件路径，如果是 zip 则递归解压
|
||
def process_file(file_path: Path) -> List[str]:
|
||
filenames = [file_path.name]
|
||
# 检查是否是压缩文件
|
||
if file_path.suffix.lower() in ('.zip', '.rar', '.7z'):
|
||
tmp_dir = Path(__file__).parent / "tmp"
|
||
tmp_dir.mkdir(exist_ok=True)
|
||
extract_target = tmp_dir / file_path.stem
|
||
# 清空 extract_target 目录
|
||
clear_directory(extract_target)
|
||
extract_target.mkdir(parents=True, exist_ok=True)
|
||
|
||
# 根据压缩格式选择解压方式
|
||
if file_path.suffix.lower() == '.zip':
|
||
extracted = extract_zip_recursive(file_path, extract_target)
|
||
else:
|
||
# 其他压缩格式使用 subprocess
|
||
import subprocess
|
||
subprocess.run(['unzip', '-o', str(file_path), '-d', str(extract_target)],
|
||
capture_output=True)
|
||
extracted = list(extract_target.iterdir())
|
||
|
||
# 将解压后的文件名添加到列表
|
||
filenames.extend([f.name for f in extracted])
|
||
return filenames
|
||
return filenames
|
||
|
||
# 第一组：根据网址匹配文件
|
||
if 'www.21cnjy.com' in url1 and twole_files:
|
||
candidates = twole_files
|
||
best_match = find_best_match(title1, candidates)
|
||
if best_match:
|
||
twole_files.remove(best_match)
|
||
file_path, ctime = best_match
|
||
result.append({
|
||
"filename": process_file(file_path),
|
||
"title": title1,
|
||
"url": url1,
|
||
"time": time1
|
||
})
|
||
elif 'www.zxxk.com' in url1 and zxxk_files:
|
||
candidates = zxxk_files
|
||
best_match = find_best_match(title1, candidates)
|
||
if best_match:
|
||
zxxk_files.remove(best_match)
|
||
file_path, ctime = best_match
|
||
result.append({
|
||
"filename": process_file(file_path),
|
||
"title": title1,
|
||
"url": url1,
|
||
"time": time1
|
||
})
|
||
|
||
# 第二组：根据网址匹配文件
|
||
if 'www.21cnjy.com' in url2 and twole_files:
|
||
candidates = twole_files
|
||
best_match = find_best_match(title2, candidates)
|
||
if best_match:
|
||
twole_files.remove(best_match)
|
||
file_path, ctime = best_match
|
||
result.append({
|
||
"filename": process_file(file_path),
|
||
"title": title2,
|
||
"url": url2,
|
||
"time": time2
|
||
})
|
||
elif 'www.zxxk.com' in url2 and zxxk_files:
|
||
candidates = zxxk_files
|
||
best_match = find_best_match(title2, candidates)
|
||
if best_match:
|
||
zxxk_files.remove(best_match)
|
||
file_path, ctime = best_match
|
||
result.append({
|
||
"filename": process_file(file_path),
|
||
"title": title2,
|
||
"url": url2,
|
||
"time": time2
|
||
})
|
||
|
||
return {"items": result}
|
||
|
||
|
||
def main():
|
||
parser = argparse.ArgumentParser(description='数据文件关联处理程序')
|
||
parser.add_argument('--extract', action='store_true', help='解压压缩文件')
|
||
parser.add_argument('--associate', action='store_true', help='建立文件关联')
|
||
parser.add_argument('--batch', action='store_true', help='批量处理所有 zip 文件')
|
||
parser.add_argument('--base-dir', type=str, help='基础目录')
|
||
parser.add_argument('--delete-original', action='store_true', help='解压后删除原文件')
|
||
|
||
args = parser.parse_args()
|
||
|
||
# 解压压缩文件
|
||
if args.extract:
|
||
source_dir = Path(args.base_dir) if args.base_dir else Path("cc")
|
||
extract_all_zips(source_dir, "data", delete_original=args.delete_original)
|
||
return
|
||
|
||
# 批量处理所有文件夹（已从 cc 目录解压好）
|
||
if True or args.batch:
|
||
source_dir = Path(args.base_dir) if args.base_dir else Path("cc")
|
||
data_dir = Path("data")
|
||
server_jsons_dir = Path("server") / "jsons"
|
||
server_jsons_dir.mkdir(parents=True, exist_ok=True)
|
||
|
||
# 获取 cc 目录下的所有子文件夹（已解压好的文件夹）
|
||
folders = [f for f in source_dir.iterdir() if f.is_dir()]
|
||
|
||
if not folders:
|
||
print(f"在 {source_dir} 中未发现文件夹")
|
||
return
|
||
|
||
print(f"找到 {len(folders)} 个文件夹，开始批量处理...")
|
||
success_count = 0
|
||
fail_count = 0
|
||
|
||
for folder in folders:
|
||
print(f"\n【开始处理】{folder.name}")
|
||
# 清空 data 目录
|
||
clear_directory(data_dir)
|
||
|
||
try:
|
||
# 拷贝文件夹到 data 目录
|
||
extract_dir = data_dir / folder.name
|
||
shutil.copytree(str(folder), str(extract_dir))
|
||
# 更新 folder 变量，避免后续移动时路径不正确
|
||
folder = extract_dir
|
||
|
||
# 查找 Word 文档
|
||
word_doc = find_word_doc_recursive(extract_dir)
|
||
if not word_doc:
|
||
print(f"⚠️ 在 {folder.name} 中未找到 Word 文档")
|
||
fail_count += 1
|
||
continue
|
||
|
||
# 读取 Word 内容
|
||
word_content = read_word_content(word_doc)
|
||
if not word_content:
|
||
print(f"⚠️ 无法读取 Word 文档内容")
|
||
fail_count += 1
|
||
continue
|
||
|
||
base_dir = word_doc.parent
|
||
print(f"✓ 找到 Word 文档：{word_doc}")
|
||
print(f" 关联目录：{base_dir}")
|
||
|
||
# 建立文件关联
|
||
twole_folder = base_dir / "21世纪教育网"
|
||
zxxk_folder = base_dir / "学科网"
|
||
|
||
if not zxxk_folder.exists():
|
||
print("❌ 文件夹不存在，请先解压文件")
|
||
# 将失败的文件移动到本程序所在目录的 ee 子目录
|
||
script_dir = Path(__file__).parent
|
||
ee_dir = script_dir / "ee"
|
||
ee_dir.mkdir(exist_ok=True)
|
||
dest_file = ee_dir / folder.name
|
||
shutil.move(str(folder), str(dest_file))
|
||
print(f" 已移动失败文件到：{dest_file}")
|
||
fail_count += 1
|
||
continue
|
||
if not twole_folder.exists():
|
||
twole_folder = base_dir / "二一教育"
|
||
if not twole_folder.exists():
|
||
twole_folder = base_dir / "21世纪教育"
|
||
if not twole_folder.exists():
|
||
twole_folder = base_dir / "二一世纪教育"
|
||
|
||
if not twole_folder.exists():
|
||
print("❌ 文件夹不存在，请先解压文件")
|
||
# 将失败的文件移动到本程序所在目录的 ee 子目录
|
||
script_dir = Path(__file__).parent
|
||
ee_dir = script_dir / "ee"
|
||
ee_dir.mkdir(exist_ok=True)
|
||
dest_file = ee_dir
|
||
print(str(folder), str(dest_file))
|
||
shutil.move(str(folder), str(dest_file))
|
||
print(f" 已移动失败文件到：{dest_file}")
|
||
fail_count += 1
|
||
continue
|
||
|
||
associations = build_file_associations(word_content, twole_folder, zxxk_folder)
|
||
|
||
if not associations["items"]:
|
||
# 移动到ee目录
|
||
script_dir = Path(__file__).parent
|
||
ee_dir = script_dir / "ee"
|
||
ee_dir.mkdir(exist_ok=True)
|
||
dest_file = ee_dir / folder.name
|
||
shutil.move(str(folder), str(dest_file))
|
||
print(f" 已移动空关联文件夹到：{dest_file}")
|
||
fail_count += 1
|
||
continue
|
||
|
||
# 保存 JSON 文件
|
||
output_file = server_jsons_dir / f"{word_doc.stem}.json"
|
||
with open(output_file, 'w', encoding='utf-8') as f:
|
||
json.dump(associations, f, ensure_ascii=False, indent=2)
|
||
|
||
print(f"✓ JSON 文件已保存到：{output_file}")
|
||
|
||
# 删除原文件夹
|
||
if args.delete_original:
|
||
shutil.rmtree(folder)
|
||
|
||
success_count += 1
|
||
|
||
except Exception as e:
|
||
print(f"❌ 处理失败：{e}")
|
||
fail_count += 1
|
||
|
||
print(f"\n===== 批量处理完成 =====")
|
||
print(f"成功：{success_count}, 失败：{fail_count}")
|
||
return
|
||
|
||
# 建立文件关联
|
||
if args.associate:
|
||
base_dir = Path(args.base_dir) if args.base_dir else Path("data")
|
||
word_doc = find_word_doc_recursive(base_dir)
|
||
if not word_doc:
|
||
print("⚠️ 未找到 Word 文档 (.doc 或 .docx)，请先解压文件")
|
||
return
|
||
|
||
word_content = read_word_content(word_doc)
|
||
if not word_content:
|
||
print("⚠️ 无法读取 Word 文档内容")
|
||
return
|
||
|
||
base_dir = word_doc.parent
|
||
print(f"✓ 找到 Word 文档：{word_doc}")
|
||
print(f" 关联目录：{base_dir}")
|
||
|
||
twole_folder = base_dir / "21世纪教育网"
|
||
zxxk_folder = base_dir / "学科网"
|
||
|
||
if not twole_folder.exists() or not zxxk_folder.exists():
|
||
print("❌ 文件夹不存在，请先解压文件")
|
||
return
|
||
|
||
associations = build_file_associations(word_content, twole_folder, zxxk_folder)
|
||
|
||
# JSON 文件保存到 server 目录下的 jsons 文件夹，文件名与 Word 文档相同
|
||
server_jsons_dir = Path("server") / "jsons"
|
||
server_jsons_dir.mkdir(parents=True, exist_ok=True)
|
||
output_file = server_jsons_dir / f"{word_doc.stem}.json"
|
||
with open(output_file, 'w', encoding='utf-8') as f:
|
||
json.dump(associations, f, ensure_ascii=False, indent=2)
|
||
print(f"\n✓ 关联关系已保存到：{output_file}")
|
||
return
|
||
|
||
parser.print_help()
|
||
|
||
|
||
if __name__ == "__main__":
|
||
main()
|