继续优化

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2026-04-16 13:39:44 +08:00
parent d1cd550c1e
commit 1d3895ed97
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# -*- coding: utf-8 -*-
"""
数据文件关联处理程序
功能:解压压缩文件,读取 Word 文档,将文件与 Word 内容关联
"""
import os
import sys
import zipfile
import json
import argparse
from pathlib import Path
from typing import Optional, List, Dict, Tuple, Union
from datetime import datetime
import time
import re
import shutil
import requests
import math
OLLAMA_EMBED_URL = os.environ.get('OLLAMA_EMBED_URL', 'http://localhost:11434/api/embeddings')
OLLAMA_EMBED_MODEL = os.environ.get('OLLAMA_EMBED_MODEL', 'nomic/text-embedding-3-large')
def clear_directory(dir_path: Path) -> None:
"""清空目录中的所有文件和子目录"""
if dir_path.exists():
for item in dir_path.iterdir():
if item.is_file():
item.unlink()
elif item.is_dir():
shutil.rmtree(item)
def get_embedding(text: str) -> List[float]:
"""使用 Ollama 获取文本的 embedding"""
try:
response = requests.post(
OLLAMA_EMBED_URL,
json={
'model': OLLAMA_EMBED_MODEL,
'input': text,
},
timeout=10,
)
response.raise_for_status()
data = response.json()
if isinstance(data, dict):
if 'embedding' in data:
return data['embedding']
if 'data' in data and isinstance(data['data'], list) and data['data']:
return data['data'][0].get('embedding', []) or []
return []
except Exception as e:
print(f"获取 embedding 失败: {e}")
return []
def cosine_similarity(vec1: List[float], vec2: List[float]) -> float:
"""计算两个向量的余弦相似度"""
if not vec1 or not vec2:
return 0.0
dot = sum(a * b for a, b in zip(vec1, vec2))
norm1 = math.sqrt(sum(a * a for a in vec1))
norm2 = math.sqrt(sum(b * b for b in vec2))
return dot / (norm1 * norm2) if norm1 and norm2 else 0.0
def normalize_for_match(text: str) -> str:
"""规范化文本,去掉路径和扩展名后的匹配用字符串"""
text = str(text).lower()
text = re.sub(r'[\u0020-\u002f\u003a-\u0040\u005b-\u0060\u007b-\u007e]+', ' ', text)
text = re.sub(r'\s+', ' ', text).strip()
return text
def token_overlap_score(a: str, b: str) -> float:
tokens_a = set(re.findall(r'[\u4e00-\u9fff]+|\d+|[a-z]+', a))
tokens_b = set(re.findall(r'[\u4e00-\u9fff]+|\d+|[a-z]+', b))
if not tokens_a or not tokens_b:
return 0.0
return len(tokens_a & tokens_b) / max(1, len(tokens_b))
def find_best_match(title: str, candidates: List[Tuple[Path, datetime]]) -> Tuple[Path, datetime]:
"""从候选文件中找到与 title 最相似的文件"""
if not candidates:
return None
title_norm = normalize_for_match(title)
exact_candidates = []
for file_path, ctime in candidates:
stem_norm = normalize_for_match(file_path.stem)
if stem_norm and (stem_norm == title_norm or stem_norm in title_norm or title_norm in stem_norm):
exact_candidates.append((file_path, ctime, stem_norm))
if exact_candidates:
# 直接返回最精确的“包含匹配”候选项
return max(exact_candidates, key=lambda item: len(item[2]))[:2]
title_emb = get_embedding(title)
best_match = None
best_score = -1.0
for file_path, ctime in candidates:
stem_norm = normalize_for_match(file_path.stem)
overlap = token_overlap_score(title_norm, stem_norm)
score = overlap * 0.3
if title_emb:
stem_emb = get_embedding(file_path.stem)
if stem_emb:
score += cosine_similarity(title_emb, stem_emb) * 0.7
if score > best_score:
best_score = score
best_match = (file_path, ctime)
return best_match or candidates[0]
def extract_all_zips(
source_dir: Union[str, Path] = "cc",
output_dir: Union[str, Path] = "data",
delete_original: bool = True
) -> List[Path]:
"""
解压指定目录中的所有 zip 文件
Args:
source_dir: 包含压缩文件的目录
output_dir: 输出目录
delete_original: 解压后删除原文件
Returns:
所有解压后的目录路径列表
"""
source_dir = Path(source_dir)
output_dir = Path(output_dir)
# 清空 output_dir
clear_directory(output_dir)
zip_files = list(source_dir.glob("*.zip"))
if not zip_files:
print(f"{source_dir} 中未发现 zip 文件")
return []
print(f"找到 {len(zip_files)} 个压缩文件,开始解压到 {output_dir}...")
results = []
for zip_file in zip_files:
# 解压到指定目录
extract_dir = output_dir / zip_file.stem
extract_dir.mkdir(parents=True, exist_ok=True)
with zipfile.ZipFile(zip_file, 'r') as zip_ref:
# 解压所有文件并保留原始时间戳
for member in zip_ref.infolist():
# 解压文件
zip_ref.extract(member, extract_dir)
# 获取解压后的文件路径
member_path = extract_dir / member.filename
# 如果文件存在,设置时间戳
if member_path.exists():
# 将 ZipInfo 的日期时间转换为时间戳
date_time = datetime(*member.date_time[:5])
timestamp = date_time.timestamp()
# 设置访问时间和修改时间
os.utime(member_path, (timestamp, timestamp))
# 检查是否多了一层目录zip 内部只有一个同名文件夹)
inner_dir = extract_dir / zip_file.stem
if inner_dir.is_dir() and len(list(extract_dir.iterdir())) == 1:
# 移动内部文件夹所有内容到外层
for item in inner_dir.iterdir():
item.rename(extract_dir / item.name)
# 删除空的内层文件夹
inner_dir.rmdir()
print(f"✓ 已解压:{zip_file.name} (移除了多余目录层)")
else:
print(f"✓ 已解压:{zip_file.name}")
results.append(extract_dir)
# 删除原压缩包
if delete_original:
zip_file.unlink()
return results
def read_word_content(doc_path: Path) -> List[str]:
"""读取 Word 文档内容 (.docx 或 .doc),提取文本行"""
if doc_path.suffix.lower() == '.docx':
return read_docx_content(doc_path)
elif doc_path.suffix.lower() == '.doc':
return read_doc_content(doc_path)
return []
def read_docx_content(doc_path: Path) -> List[str]:
"""读取 .docx 格式 Word 文档内容"""
try:
with zipfile.ZipFile(doc_path, 'r') as z:
content = z.read('word/document.xml').decode('utf-8')
# 提取所有 <w:t>...</w:t> 中的内容,保留原始空白字符
texts = re.findall(r'<w:t[^>]*>(.*?)</w:t>', content, re.DOTALL)
# 去除 HTML 标签,不替换内部的空白字符
processed = []
for text in texts:
text = re.sub(r'<[^>]+>', '', text).strip()
if text:
processed.append(text)
# 拼接所有文本,保留 \t 和 \n
full_text = '\n'.join(processed)
# 智能检测:判断是使用 \t 分割 6 段,还是每行一个字段
lines = full_text.split('\n')
lines = [line.strip() for line in lines if line.strip()]
# 检测是否每行都是单字段(没有\t
# 如果前几行都没有\t可能是每行一个字段
has_tab_in_first_rows = any('\t' in line for line in lines[:6])
if not has_tab_in_first_rows and len(lines) >= 6:
# 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
def is_url_line(line: str) -> bool:
"""判断一行是否是网址"""
return bool(re.match(r'^https?://', line.strip()))
def is_datetime_line(line: str) -> bool:
"""判断一行是否是日期或时间"""
datetime_pattern = r'^\d{4}[-/]\d{1,2}[-/]\d{1,2}\s+\d{1,2}:\d{2}'
date_pattern = r'^\d{4}[-/]\d{1,2}[-/]\d{1,2}'
return bool(re.match(datetime_pattern, line.strip())) or \
bool(re.match(date_pattern, line.strip()))
# 检查当前起始位置是否是 6 行一组模式
def is_six_row_group(lines: list, start_idx: int) -> bool:
"""检查从 start_idx 开始是否是 6 行一组"""
if start_idx + 5 < len(lines):
return is_url_line(lines[start_idx + 1]) and \
is_datetime_line(lines[start_idx + 2]) and \
is_url_line(lines[start_idx + 4]) and \
is_datetime_line(lines[start_idx + 5])
return False
# 检查当前起始位置是否是 5 行一组模式
def is_five_row_group(lines: list, start_idx: int) -> bool:
"""检查从 start_idx 开始是否是 5 行一组"""
if start_idx + 4 < len(lines):
return is_url_line(lines[start_idx + 1]) and \
is_datetime_line(lines[start_idx + 2]) and \
is_url_line(lines[start_idx + 4])
return False
# 按组处理,每组独立判断 offset
# 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
result = []
i = 0
while i + 4 <= len(lines):
if i + 5 < len(lines) and is_six_row_group(lines, i):
# 是 6 行一组,合并这 6 行
combined = '\t'.join(lines[i:i+6])
# 检查并补充缺失的时间信息
parts = combined.split('\t')
if len(parts) >= 3 and not is_datetime_line(parts[2]):
parts[2] = '1970-1-1'
if len(parts) >= 6 and not is_datetime_line(parts[5]):
parts[5] = '1970-1-1'
combined = '\t'.join(parts)
result.append(combined)
i += 6
elif is_five_row_group(lines, i):
# 是 5 行一组,合并这 5 行并补充时间2
combined = '\t'.join(lines[i:i+5])
# 检查并补充缺失的时间信息
parts = combined.split('\t')
if len(parts) >= 3 and not is_datetime_line(parts[2]):
parts[2] = '1970-1-1'
# 为第二组补充时间
if len(parts) >= 5:
parts.append('1970-1-1')
combined = '\t'.join(parts)
result.append(combined)
i += 5
else:
# 不是有效组,丢弃当前行(相当于 offset+1
i += 1
# 处理剩余行(不足 6 行的)
while i < len(lines):
result.append(lines[i])
i += 1
return result
else:
# 每行已经有\t分割直接返回
return lines
except Exception as e:
print(f"读取 .docx 失败 ({doc_path.name}): {e}")
return []
def read_doc_content(doc_path: Path) -> List[str]:
"""读取 .doc 格式 Word 文档内容(使用 LibreOffice"""
import subprocess
import tempfile
soffice_paths = [
'/Applications/LibreOffice.app/Contents/MacOS/soffice',
'/Applications/LibreOffice.app/Contents/MacOS/libreoffice',
'soffice',
]
print(f"🔍 正在查找 LibreOffice...")
soffice_cmd = None
for path in soffice_paths:
print(f" 检查:{path}")
try:
import os
if os.path.isfile(path):
print(f" ✓ 文件存在")
result = subprocess.run([path, '--version'], capture_output=True, timeout=10)
print(f" ✓ 版本检查返回码:{result.returncode}")
print(f" 输出:{result.stdout.decode()[:100]}")
if result.returncode == 0:
soffice_cmd = path
print(f"✓ 使用 LibreOffice: {path}")
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:
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 []
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)
# 解压当前层并保留原始时间戳
with zipfile.ZipFile(zip_path, 'r') as zip_ref:
for member in zip_ref.infolist():
zip_ref.extract(member, extract_dir)
member_path = extract_dir / member.filename
if member_path.exists():
date_time = datetime(*member.date_time[:5])
timestamp = date_time.timestamp()
os.utime(member_path, (timestamp, timestamp))
# 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:
for member in zip_ref.infolist():
zip_ref.extract(member, extract_dir)
member_path = extract_dir / member.filename
if member_path.exists():
date_time = datetime(*member.date_time[:5])
timestamp = date_time.timestamp()
os.utime(member_path, (timestamp, timestamp))
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 = []
problematic_groups = []
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[Dict[str, Union[str, float]]]:
files = []
# 检查是否是压缩文件
if file_path.suffix.lower() in ('.zip', '.rar', '.7z'):
# 先添加压缩文件本身
mtime = file_path.stat().st_mtime
files.append({"name": file_path.name, "mtime": mtime})
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())
# 将解压后的文件名和修改时间添加到列表
for f in extracted:
if f.is_file():
mtime = f.stat().st_mtime
files.append({"name": f.name, "mtime": mtime})
else:
mtime = file_path.stat().st_mtime
files.append({"name": file_path.name, "mtime": mtime})
return files
def get_latest_extracted_mtime(file_entries: List[Dict[str, Union[str, float]]], archive_name: str) -> Optional[float]:
extracted_times = [
entry["mtime"]
for entry in file_entries
if entry.get("name") != archive_name and "mtime" in entry
]
return max(extracted_times) if extracted_times else None
# 初始化条目
entry = {}
group1_latest = None
group2_latest = None
# 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
group1_files = process_file(file_path)
entry["group1"] = {
"files": group1_files,
"title": title1,
"url": url1,
"time": time1
}
if file_path.suffix.lower() in ('.zip', '.rar', '.7z'):
group1_latest = get_latest_extracted_mtime(group1_files, file_path.name)
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
group1_files = process_file(file_path)
entry["group1"] = {
"files": group1_files,
"title": title1,
"url": url1,
"time": time1
}
if file_path.suffix.lower() in ('.zip', '.rar', '.7z'):
group1_latest = get_latest_extracted_mtime(group1_files, file_path.name)
# 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
group2_files = process_file(file_path)
entry["group2"] = {
"files": group2_files,
"title": title2,
"url": url2,
"time": time2
}
if file_path.suffix.lower() in ('.zip', '.rar', '.7z'):
group2_latest = get_latest_extracted_mtime(group2_files, file_path.name)
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
group2_files = process_file(file_path)
entry["group2"] = {
"files": group2_files,
"title": title2,
"url": url2,
"time": time2
}
if file_path.suffix.lower() in ('.zip', '.rar', '.7z'):
group2_latest = get_latest_extracted_mtime(group2_files, file_path.name)
# 如果 group1 和 group2 都是压缩文件,并且 group1 的解压文件最新时间早于 group2则记录到问题列表
if group1_latest is not None and group2_latest is not None and group1_latest < group2_latest:
problematic_groups.append({
"row_index": i,
"group1_latest_extracted_mtime": group1_latest,
"group2_latest_extracted_mtime": group2_latest,
"group1": entry.get("group1"),
"group2": entry.get("group2")
})
# 如果有匹配的条目,添加到结果列表
if entry:
result.append(entry)
return {"items": result, "problematic_groups": problematic_groups}
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"{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
all_problem_groups = []
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)
for group in associations.get("problematic_groups", []):
group["source_folder"] = folder.name
group["word_doc"] = word_doc.name
all_problem_groups.extend(associations.get("problematic_groups", []))
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
report_file = server_jsons_dir / "compressed_group_time_issues.json"
with open(report_file, 'w', encoding='utf-8') as f:
json.dump(all_problem_groups, f, ensure_ascii=False, indent=2)
print(f"\n===== 批量处理完成 =====")
print(f"成功:{success_count}, 失败:{fail_count}")
print(f"问题组报告已保存到:{report_file}")
return
if __name__ == "__main__":
main()