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hiddencode_project/server/association_detail_smart.py

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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
import hashlib
import sqlite3
from pathlib import Path
from typing import Optional, List, Dict, Tuple
from datetime import datetime
import re
import shutil
import requests
import math
from urllib.parse import urlparse
OLLAMA_EMBED_URL = os.environ.get('OLLAMA_EMBED_URL', 'http://localhost:11434/api/embeddings')
OLLAMA_EMBED_MODEL = os.environ.get('OLLAMA_EMBED_MODEL', 'qwen3-embedding')
BASE_DIR = Path(__file__).resolve().parent
ARCHIVE_EXTENSIONS = {'.zip', '.rar', '.7z'}
TARGET_DOCUMENT_EXTENSIONS = {'.doc', '.docx', '.pdf', '.ppt', '.pptx'}
DEFAULT_DB_PATH = Path(os.environ.get('HIDDENCODE_DB_PATH', str(BASE_DIR / 'hiddencode.db')))
MATCH_KEYWORDS = [
'语文', '数学', '英语', '物理', '化学', '生物', '历史', '地理', '政治', '科学',
'中考', '高考', '会考', '学考', '一模', '二模', '三模', '模拟', '月考', '期中',
'期末', '联考', '调研', '测试', '试卷', '试题', '课件', '导学案', '教案'
]
def format_datetime(ts: float) -> str:
return datetime.fromtimestamp(ts).strftime("%Y-%m-%d %H:%M:%S")
def compute_sha256(file_path: Path) -> str:
sha = hashlib.sha256()
with open(file_path, 'rb') as f:
for chunk in iter(lambda: f.read(1024 * 1024), b''):
sha.update(chunk)
return sha.hexdigest()
def get_url_site(url: str) -> Optional[str]:
normalized_url = (url or '').lower()
if '21cnjy.com' in normalized_url:
return 'twole'
if 'zxxk.com' in normalized_url:
return 'zxxk'
return None
def extract_twole_id(url: str) -> Optional[str]:
if get_url_site(url) != 'twole':
return None
parsed = urlparse(url)
path_parts = [part for part in parsed.path.split('/') if part]
for part in reversed(path_parts):
match = re.search(r'(\d+)', part)
if match:
return match.group(1)
return None
def is_target_document(file_name: str) -> bool:
return Path(file_name).suffix.lower() in TARGET_DOCUMENT_EXTENSIONS
def list_source_items(source_dir: Path) -> List[Path]:
items = [item for item in source_dir.iterdir() if item.is_dir() or item.suffix.lower() in ARCHIVE_EXTENSIONS]
return sorted(items, key=lambda item: item.name.lower())
def sanitize_for_json(data):
"""去掉仅供脚本内部使用的路径字段。"""
if isinstance(data, dict):
cleaned = {k: sanitize_for_json(v) for k, v in data.items() if k not in {'path', 'source_path'}}
return cleaned
if isinstance(data, list):
return [sanitize_for_json(item) for item in data]
return data
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 tokenize_for_match(text: str) -> Dict[str, float]:
"""为中文匹配生成更细粒度的 token 权重。"""
normalized = normalize_for_match(text)
compact = re.sub(r'[^0-9a-z\u4e00-\u9fff]+', '', normalized)
tokens: Dict[str, float] = {}
def add_token(token: str, weight: float) -> None:
token = re.sub(r'^[年上下前后新旧本]+', '', token)
if token:
tokens[token] = max(tokens.get(token, 0.0), weight)
for keyword in MATCH_KEYWORDS:
if keyword in compact:
add_token(keyword, 1.8)
for number in re.findall(r'\d{4}|\d+', normalized):
add_token(number, 0.6 if len(number) == 4 else 0.3)
for alpha in re.findall(r'[a-z]+', normalized):
add_token(alpha, 0.2)
for chunk in re.findall(r'[\u4e00-\u9fff]+', compact):
for n, weight in ((2, 0.25), (3, 0.7), (4, 1.1)):
if len(chunk) < n:
continue
for index in range(len(chunk) - n + 1):
add_token(chunk[index:index + n], weight)
return tokens
def token_overlap_score(a: str, b: str) -> float:
tokens_a = tokenize_for_match(a)
tokens_b = tokenize_for_match(b)
if not tokens_a or not tokens_b:
return 0.0
overlap_weight = sum(min(weight, tokens_b.get(token, 0.0)) for token, weight in tokens_a.items() if token in tokens_b)
total_weight = sum(tokens_a.values())
return overlap_weight / total_weight if total_weight else 0.0
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:
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: str = "cc", output_dir: str = "data", delete_original: bool = True) -> List[Path]:
"""解压指定目录中的所有 zip 文件"""
source_dir = Path(source_dir)
output_dir = Path(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:
extract_dir = output_dir / zip_file.stem
extract_dir.mkdir(parents=True, exist_ok=True)
with zipfile.ZipFile(zip_file, '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))
inner_dir = extract_dir / zip_file.stem
if inner_dir.is_dir() and len(list(extract_dir.iterdir())) == 1:
for item in inner_dir.iterdir():
item.rename(extract_dir / item.name)
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)
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_old(doc_path)
return []
def parse_word_content_lines(raw_lines: List[str]) -> List[str]:
"""智能兼容 Word 内容中的分组格式和混排格式。"""
def normalize_line(line: str) -> str:
return line.replace('\ufeff', '').strip()
def is_url_line(line: str) -> bool:
return bool(re.match(r'^https?://', normalize_line(line)))
def is_index_line(line: str) -> bool:
return bool(re.match(r'^\d+[\.、]?$', normalize_line(line)))
def is_twole_label(line: str) -> bool:
return bool(re.match(r'^(二一教育|21 世纪教育|21 世纪教育网|二一世纪教育)[:]?$', normalize_line(line)))
def is_zxxk_label(line: str) -> bool:
return bool(re.match(r'^学科网 [:]?$', normalize_line(line)))
def is_date_time(line: str) -> bool:
pattern = r'^\d{4}[-/]\d{1,2}[-/]\d{1,2}(\s+\d{1,2}:\d{1,2}(:\d{1,2})?(\s*(AM|PM|上午 | 下午))?)?$'
return bool(re.match(pattern, normalize_line(line)))
def is_skip_line(line: str) -> bool:
return is_index_line(line) or is_twole_label(line) or is_zxxk_label(line) or not normalize_line(line)
def is_url_fragment(line: str) -> bool:
return bool(re.match(r"^[A-Za-z0-9._~:/?#\[\]@!$&'()*+,;=%-]+$", normalize_line(line)))
def consume_url(lines: List[str], start: int) -> Optional[Tuple[str, int]]:
i = start
while i < len(lines) and is_skip_line(lines[i]):
i += 1
if i >= len(lines):
return None
first_part = normalize_line(lines[i])
if not first_part.startswith('http'):
return None
url_parts = [first_part]
i += 1
while i < len(lines):
line = normalize_line(lines[i])
if is_date_time(line):
break
if is_skip_line(line):
i += 1
continue
if not is_url_fragment(line):
break
url_parts.append(line)
i += 1
return ''.join(url_parts), i
def parse_content_item(lines: List[str], start: int) -> Optional[Tuple[str, str, str, int]]:
i = start
while i < len(lines) and is_skip_line(lines[i]):
i += 1
title_parts = []
while i < len(lines) and len(title_parts) < 8:
line = normalize_line(lines[i])
if is_url_line(line):
break
if is_date_time(line):
return None
if is_skip_line(line):
i += 1
continue
title_parts.append(line)
i += 1
while i < len(lines) and is_skip_line(lines[i]):
i += 1
url_result = consume_url(lines, i)
if not title_parts or not url_result:
return None
title = ''.join(title_parts)
url, i = url_result
date = '1970-1-1'
if i < len(lines) and is_date_time(lines[i]):
date = normalize_line(lines[i])
i += 1
return title, url, date, i
def get_site_from_url(url: str) -> Optional[str]:
normalized_url = normalize_line(url).lower()
if '21cnjy.com' in normalized_url:
return 'twole'
if 'zxxk.com' in normalized_url:
return 'zxxk'
return None
def extract_content_items(lines: List[str]) -> List[Tuple[str, str, str, str]]:
items = []
i = 0
while i < len(lines):
item = parse_content_item(lines, i)
if not item:
i += 1
continue
title, url, date, next_i = item
site = get_site_from_url(url)
if site in ('twole', 'zxxk'):
items.append((title, url, date, site))
i = next_i
return items
def build_grouped_rows(items: List[Tuple[str, str, str, str]]) -> List[str]:
twole_items = [(title, url, date) for title, url, date, site in items if site == 'twole']
zxxk_items = [(title, url, date) for title, url, date, site in items if site == 'zxxk']
count = min(len(twole_items), len(zxxk_items))
return ['\t'.join([twole_items[index][0], twole_items[index][1], twole_items[index][2],
zxxk_items[index][0], zxxk_items[index][1], zxxk_items[index][2]]) for index in range(count)]
def build_mixed_rows(items: List[Tuple[str, str, str, str]]) -> List[str]:
result = []
i = 0
while i + 1 < len(items):
title1, url1, time1, site1 = items[i]
title2, url2, time2, site2 = items[i + 1]
if site1 == site2:
i += 1
continue
if site1 == 'twole':
twole_item, zxxk_item = (title1, url1, time1), (title2, url2, time2)
else:
twole_item, zxxk_item = (title2, url2, time2), (title1, url1, time1)
result.append('\t'.join([twole_item[0], twole_item[1], twole_item[2], zxxk_item[0], zxxk_item[1], zxxk_item[2]]))
i += 2
return result
def parse_site_items(lines: List[str]) -> List[str]:
items = extract_content_items(lines)
sites = [site for _, _, _, site in items]
if len(sites) < 2 or len(set(sites)) < 2:
return []
switches = sum(1 for current, next_site in zip(sites, sites[1:]) if current != next_site)
if switches <= 1:
return build_grouped_rows(items)
return build_mixed_rows(items)
def parse_grouped_site_rows(lines: List[str]) -> List[str]:
twole_items = []
zxxk_items = []
current_site = None
i = 0
while i < len(lines):
line = normalize_line(lines[i])
if is_twole_label(line):
current_site = 'twole'
i += 1
continue
if is_zxxk_label(line):
current_site = 'zxxk'
i += 1
continue
if not line or line in ('......', '……') or line.startswith('其它内容') or line.startswith('其他内容'):
i += 1
continue
if current_site not in ('twole', 'zxxk'):
i += 1
continue
title = line
url = ''
date = '1970-1-1'
url_result = consume_url(lines, i + 1)
if url_result:
url, i = url_result
if i < len(lines) and is_date_time(lines[i]):
date = normalize_line(lines[i])
i += 1
else:
i += 1
if current_site == 'twole':
twole_items.append((title, url, date))
else:
zxxk_items.append((title, url, date))
count = min(len(twole_items), len(zxxk_items))
return ['\t'.join([twole_items[index][0], twole_items[index][1], twole_items[index][2],
zxxk_items[index][0], zxxk_items[index][1], zxxk_items[index][2]]) for index in range(count)]
def parse_labeled_mixed_rows(lines: List[str]) -> List[str]:
result = []
i = 0
while i < len(lines):
if i + 3 >= len(lines):
break
start = i
item1 = parse_content_item(lines, i)
if not item1:
i += 1
continue
title1, url1, time1, next_i = item1
item2 = parse_content_item(lines, next_i)
if not item2:
i = start + 1
continue
title2, url2, time2, i = item2
result.append('\t'.join([title1, url1, time1, title2, url2, time2]))
return result
def parse_mixed_rows(lines: List[str]) -> List[str]:
result = []
i = 0
while i + 4 <= len(lines):
if i + 5 < len(lines) and is_url_line(lines[i + 1]) and is_date_time(lines[i + 2]) \
and is_url_line(lines[i + 4]) and is_date_time(lines[i + 5]):
result.append('\t'.join(lines[i:i + 6]))
i += 6
elif is_url_line(lines[i + 1]) and is_date_time(lines[i + 2]) and is_url_line(lines[i + 4]):
result.append('\t'.join(lines[i:i + 5] + ['1970-1-1']))
i += 5
else:
i += 1
return result
lines = [normalize_line(line) for line in raw_lines if normalize_line(line)]
has_tab_in_first_rows = any('\t' in line for line in lines[:6])
split_lines = []
for line in lines:
split_lines.extend(normalize_line(part) for part in line.split('\t') if normalize_line(part))
site_result = parse_site_items(split_lines)
if site_result:
return site_result
has_site_labels = any(is_twole_label(line) or is_zxxk_label(line) for line in split_lines)
if has_site_labels:
grouped_result = parse_grouped_site_rows(split_lines)
if grouped_result:
return grouped_result
labeled_mixed_result = parse_labeled_mixed_rows(split_lines)
if labeled_mixed_result:
return labeled_mixed_result
if has_tab_in_first_rows or len(split_lines) < 6:
return lines
mixed_result = parse_mixed_rows(split_lines)
if mixed_result:
return mixed_result
return lines
def read_docx_content(doc_path: Path) -> List[str]:
"""读取 .docx 格式 Word 文档内容,并智能兼容分组格式和混排格式。"""
def clean_hyperlink(line: str) -> str:
patterns = [r'HYPERLINK\s+&quot;([^&]+)&quot;\s+(\S+)', r'HYPERLINK\s+"([^"]+)"\s+(\S+)']
for pattern in patterns:
match = re.match(pattern, line)
if match:
return match.group(2)
return line
try:
with zipfile.ZipFile(doc_path, 'r') as z:
content = z.read('word/document.xml').decode('utf-8')
texts = re.findall(r'<w:t[^>]*>(.*?)</w:t>', content, re.DOTALL)
processed = []
for text in texts:
text = re.sub(r'<[^>]+>', '', text).strip()
if text:
processed.append(clean_hyperlink(text))
return parse_word_content_lines(processed)
except Exception as e:
print(f"读取 .docx 失败 ({doc_path.name}): {e}")
return []
def read_doc_content_old(doc_path: Path) -> List[str]:
"""读取 .doc 格式 Word 文档内容(使用 LibreOffice"""
import subprocess
import tempfile
for soffice_cmd in ['/Applications/LibreOffice.app/Contents/MacOS/soffice',
'/Applications/LibreOffice.app/Contents/MacOS/libreoffice', 'soffice']:
if os.path.isfile(soffice_cmd) and subprocess.run([soffice_cmd, '--version'], capture_output=True).returncode == 0:
break
else:
return []
try:
with tempfile.TemporaryDirectory() as tmpdir:
result = subprocess.run(
[soffice_cmd, '--headless', '--convert-to', 'txt', '--outdir', tmpdir, str(doc_path)],
capture_output=True, timeout=60
)
if result.returncode != 0:
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()]
return parse_word_content_lines(lines)
except Exception:
pass
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"""
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')]
if len(word_files) == 1 and len(subdirs) >= 2:
return word_files[0]
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()
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"""
if clear_dir:
for item in extract_dir.iterdir():
if item.is_file():
item.unlink()
elif item.is_dir():
shutil.rmtree(item)
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))
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()
new_zips = list(extract_dir.glob("*.zip"))
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
return collect_all_files(extract_dir)
def has_audio_video_files(files_list: List[Dict]) -> bool:
"""检查文件列表中是否包含音视频文件"""
audio_video_exts = {'.mp3', '.mp4', '.avi', '.mkv', '.wav', '.flac', '.aac', '.ogg', '.wma', '.mov', '.wmv'}
return any(file_entry.get('name', '').lower().endswith(ext) for file_entry in files_list for ext in audio_video_exts)
def build_file_associations(word_content: List[str], twole_folder: Path, zxxk_folder: Path) -> Dict:
"""构建文件关联关系"""
def process_file(file_path: Path) -> List[Dict]:
files = []
mtime = file_path.stat().st_mtime
files.append({"name": file_path.name, "mtime": mtime, "datetime": format_datetime(mtime), "path": str(file_path)})
if file_path.suffix.lower() in ARCHIVE_EXTENSIONS:
tmp_dir = BASE_DIR / "tmp"
tmp_dir.mkdir(exist_ok=True)
archive_key = hashlib.sha1(str(file_path.resolve()).encode('utf-8')).hexdigest()[:12]
extract_target = tmp_dir / f"{file_path.stem}_{archive_key}"
if extract_target.exists():
clear_directory(extract_target)
extract_target.mkdir(parents=True, exist_ok=True)
if file_path.suffix.lower() == '.zip':
extracted = extract_zip_recursive(file_path, extract_target)
else:
import subprocess
subprocess.run(['unzip', '-o', str(file_path), '-d', str(extract_target)], capture_output=True)
extracted = list(extract_target.iterdir())
for f in extracted:
if f.is_file():
mtime = f.stat().st_mtime
files.append({"name": f.name, "mtime": mtime, "datetime": format_datetime(mtime), "path": str(f)})
return files
def get_latest_extracted_mtime(file_entries: List[Dict], archive_name: str) -> Optional[float]:
extracted_times = [e["mtime"] for e in file_entries if e.get("name") != archive_name and "mtime" in e]
if not extracted_times:
return None
archive_mtime = next((e["mtime"] for e in file_entries if e.get("name") == archive_name), None)
latest_extracted = max(extracted_times)
return None if archive_mtime and abs(latest_extracted - archive_mtime) < 300 else latest_extracted
def match_group(title: str, url: str, time_val: str, group_name: str, twole_files: List, zxxk_files: List) -> Tuple[Dict, Optional[float]]:
if 'www.21cnjy.com' in url and twole_files:
candidates = twole_files
elif 'www.zxxk.com' in url and zxxk_files:
candidates = zxxk_files
else:
return {}, None
best_match = find_best_match(title, candidates)
if not best_match:
return {}, None
candidates.remove(best_match)
file_path, _ = best_match
files = process_file(file_path)
entry = {"files": files, "title": title, "url": url, "time": time_val, "source_path": str(file_path)}
latest = get_latest_extracted_mtime(files, file_path.name) if file_path.suffix.lower() in ('.zip', '.rar', '.7z') else None
return entry, latest
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):
parts = content.split('\t')
if len(parts) < 6:
continue
title1, url1, time1 = parts[0].strip(), parts[1].strip(), parts[2].strip()
title2, url2, time2 = parts[3].strip(), parts[4].strip(), parts[5].strip()
entry = {}
group1_entry, group1_latest = match_group(title1, url1, time1, "group1", twole_files, zxxk_files)
group2_entry, group2_latest = match_group(title2, url2, time2, "group2", twole_files, zxxk_files)
if group1_entry:
entry["group1"] = group1_entry
if group2_entry:
entry["group2"] = group2_entry
if entry:
pair_sites = {get_url_site(entry.get("group1", {}).get("url", "")), get_url_site(entry.get("group2", {}).get("url", ""))}
if (pair_sites == {'twole', 'zxxk'} and group1_latest is not None and group2_latest is not None and
group1_latest < group2_latest and (group2_latest - group1_latest) > 30):
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")
})
result.append(entry)
return {"items": result, "problematic_groups": problematic_groups}
def prepare_processing_folder(source_item: Path, data_dir: Path) -> Path:
"""准备单个来源目录:目录直接复制,压缩包则解压到工作目录。"""
if data_dir.exists():
clear_directory(data_dir)
data_dir.mkdir(parents=True, exist_ok=True)
work_dir = data_dir / (source_item.stem if source_item.is_file() else source_item.name)
if work_dir.exists():
shutil.rmtree(work_dir)
if source_item.is_dir():
shutil.copytree(str(source_item), str(work_dir))
return work_dir
work_dir.mkdir(parents=True, exist_ok=True)
if source_item.suffix.lower() == '.zip':
extract_zip_recursive(source_item, work_dir)
return work_dir
import subprocess
commands = []
if shutil.which('7z'):
commands.append(['7z', 'x', '-y', f'-o{work_dir}', str(source_item)])
if shutil.which('unar'):
commands.append(['unar', '-force-overwrite', '-output-directory', str(work_dir), str(source_item)])
for command in commands:
result = subprocess.run(command, capture_output=True, text=True)
if result.returncode == 0:
return work_dir
raise RuntimeError(f"暂不支持解压 {source_item.suffix},请安装 7z/unar 或改用 zip")
def resolve_site_folders(base_dir: Path) -> Tuple[Optional[Path], Optional[Path]]:
zxxk_folder = base_dir / "学科网"
twole_candidates = [base_dir / "21 世纪教育网", base_dir / "二一教育", base_dir / "21 世纪教育", base_dir / "二一世纪教育"]
twole_folder = next((folder for folder in twole_candidates if folder.exists()), None)
return twole_folder, zxxk_folder if zxxk_folder.exists() else None
def collect_targets_to_write(associations: Dict, source_folder: str, word_doc_name: str) -> List[Dict[str, str]]:
targets: List[Dict[str, str]] = []
seen_paths = set()
for item_index, item in enumerate(associations.get("items", []), start=1):
groups = [item.get("group1"), item.get("group2")]
twole_group = next((group for group in groups if group and get_url_site(group.get("url", "")) == 'twole'), None)
if not twole_group:
continue
twole_id = extract_twole_id(twole_group.get("url", ""))
if not twole_id:
continue
for group_name in ("group1", "group2"):
group = item.get(group_name) or {}
site = get_url_site(group.get("url", ""))
for file_entry in group.get("files", []):
file_path = file_entry.get("path")
if not file_path or not is_target_document(file_path):
continue
normalized_path = str(Path(file_path).resolve())
if normalized_path in seen_paths:
continue
seen_paths.add(normalized_path)
targets.append({
"path": normalized_path,
"code": twole_id,
"site": site or "",
"group": group_name,
"file_name": file_entry.get("name", Path(file_path).name),
"source_folder": source_folder,
"word_doc": word_doc_name,
"item_index": str(item_index),
"twole_url": twole_group.get("url", ""),
})
return targets
def ensure_codes_table(db_path: Path) -> None:
db_path.parent.mkdir(parents=True, exist_ok=True)
conn = sqlite3.connect(db_path)
try:
conn.execute('''
CREATE TABLE IF NOT EXISTS codes (
id INTEGER PRIMARY KEY AUTOINCREMENT,
sha TEXT UNIQUE,
upload_code TEXT,
download_code TEXT,
created_at TEXT
)
''')
conn.commit()
finally:
conn.close()
def write_hidden_codes(targets: List[Dict[str, str]], db_path: Path, dry_run: bool = False) -> Dict:
report = {"total_targets": len(targets), "written": [], "skipped_duplicates": [], "conflicts": [], "failures": []}
if not targets:
return report
ensure_codes_table(db_path)
sha_to_code: Dict[str, str] = {}
sha_to_path: Dict[str, str] = {}
path_to_sha: Dict[str, str] = {}
rows_to_write = []
now = datetime.now().strftime('%Y-%m-%d %H:%M:%S')
for target in targets:
file_path = Path(target["path"])
if not file_path.exists():
report["failures"].append({**target, "reason": "file_not_found"})
continue
try:
sha = path_to_sha.get(target["path"])
if not sha:
sha = compute_sha256(file_path)
path_to_sha[target["path"]] = sha
except Exception as exc:
report["failures"].append({**target, "reason": f"sha256_failed: {exc}"})
continue
existing_code = sha_to_code.get(sha)
if existing_code is not None:
if existing_code != target["code"]:
report["conflicts"].append({**target, "sha": sha, "existing_code": existing_code, "existing_path": sha_to_path.get(sha, "")})
continue
report["skipped_duplicates"].append({**target, "sha": sha})
continue
sha_to_code[sha] = target["code"]
sha_to_path[sha] = target["path"]
write_record = {**target, "sha": sha, "db_path": str(db_path)}
if dry_run:
write_record["status"] = "dry_run"
report["written"].append(write_record)
continue
rows_to_write.append((sha, target["code"], target["code"], now, write_record))
if dry_run or not rows_to_write:
return report
conn = sqlite3.connect(db_path)
try:
cursor = conn.cursor()
for sha, upload_code, download_code, created_at, write_record in rows_to_write:
try:
cursor.execute(
'''INSERT INTO codes (sha, upload_code, download_code, created_at)
VALUES (?,?,?,?)
ON CONFLICT(sha) DO UPDATE SET
upload_code=excluded.upload_code,
download_code=excluded.download_code,
created_at=excluded.created_at''',
(sha, upload_code, download_code, created_at))
committed_record = dict(write_record)
committed_record["status"] = "ok"
report["written"].append(committed_record)
except Exception as exc:
report["failures"].append({**write_record, "reason": f"db_write_failed: {exc}"})
conn.commit()
finally:
conn.close()
return report
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('--base-dir', type=str, help='基础目录')
parser.add_argument('--data-dir', type=str, help='处理过程使用的临时目录')
parser.add_argument('--json-dir', type=str, help='输出 JSON 目录')
parser.add_argument('--db-path', type=str, help='SQLite 数据库路径,默认写入 server/hiddencode.db')
parser.add_argument('--dry-run', action='store_true', help='只计算待写入文件,不写入数据库')
parser.add_argument('--skip-json', action='store_true', help='不输出关联 JSON')
parser.add_argument('--delete-original', action='store_true', help='解压后删除原文件')
args = parser.parse_args()
source_dir = Path(args.base_dir).expanduser().resolve() if args.base_dir else BASE_DIR / "cc"
data_dir = Path(args.data_dir).expanduser().resolve() if args.data_dir else BASE_DIR / "data"
json_dir = Path(args.json_dir).expanduser().resolve() if args.json_dir else BASE_DIR / "jsons"
db_path = Path(args.db_path).expanduser().resolve() if args.db_path else DEFAULT_DB_PATH
if args.extract:
extract_all_zips(source_dir, data_dir, delete_original=args.delete_original)
return
json_dir.mkdir(parents=True, exist_ok=True)
source_items = list_source_items(source_dir)
if not source_items:
print(f"{source_dir} 中未发现待处理的文件夹或压缩包")
return
print(f"找到 {len(source_items)} 个来源项,开始处理...")
success_count = 0
fail_count = 0
total_written = 0
total_failures = 0
total_conflicts = 0
total_duplicates = 0
all_problem_groups = []
all_write_reports = []
for source_item in source_items:
print(f"\n【开始处理】{source_item.name}")
try:
work_dir = prepare_processing_folder(source_item, data_dir)
word_doc = find_word_doc_recursive(work_dir)
if not word_doc:
print(f"⚠️ 在 {source_item.name} 中未找到 Word 文档")
fail_count += 1
continue
word_content = read_word_content(word_doc)
if not word_content:
print(f"⚠️ 无法读取 Word 文档内容:{word_doc.name}")
fail_count += 1
continue
base_dir = word_doc.parent
twole_folder, zxxk_folder = resolve_site_folders(base_dir)
if not zxxk_folder:
print('❌ 缺少"学科网"目录')
fail_count += 1
continue
if not twole_folder:
print('❌ 缺少"21 世纪教育网/二一教育"目录')
fail_count += 1
continue
print(f"✓ 找到 Word 文档:{word_doc}")
print(f" 关联目录:{base_dir}")
associations = build_file_associations(word_content, twole_folder, zxxk_folder)
for group in associations.get("problematic_groups", []):
group["source_folder"] = source_item.name
group["word_doc"] = word_doc.name
all_problem_groups.extend(associations.get("problematic_groups", []))
if not associations.get("items"):
print("⚠️ 未构建出有效关联")
fail_count += 1
continue
targets = collect_targets_to_write(associations, source_item.name, word_doc.name)
write_report = write_hidden_codes(targets, db_path=db_path, dry_run=args.dry_run)
write_report["source_folder"] = source_item.name
write_report["word_doc"] = word_doc.name
all_write_reports.append(write_report)
total_written += len(write_report["written"])
total_failures += len(write_report["failures"])
total_conflicts += len(write_report["conflicts"])
total_duplicates += len(write_report["skipped_duplicates"])
if not args.skip_json:
output_file = json_dir / f"{word_doc.stem}.json"
with open(output_file, 'w', encoding='utf-8') as f:
json.dump(sanitize_for_json(associations), f, ensure_ascii=False, indent=2)
print(f"✓ 关联 JSON 已保存:{output_file}")
status_text = "模拟写入" if args.dry_run else "写入"
print(
f"{status_text}完成:目标文件 {len(targets)} 个,成功 {len(write_report['written'])} 个,"
f"失败 {len(write_report['failures'])} 个,重复跳过 {len(write_report['skipped_duplicates'])} 个,"
f"冲突 {len(write_report['conflicts'])}"
)
if args.delete_original:
if source_item.is_dir():
shutil.rmtree(source_item)
elif source_item.exists():
source_item.unlink()
success_count += 1
except Exception as exc:
print(f"❌ 处理失败:{exc}")
fail_count += 1
issues_file = json_dir / "compressed_group_time_issues.json"
with open(issues_file, 'w', encoding='utf-8') as f:
json.dump(sanitize_for_json(all_problem_groups), f, ensure_ascii=False, indent=2)
write_report_file = json_dir / "hidden_code_write_report.json"
with open(write_report_file, 'w', encoding='utf-8') as f:
json.dump(sanitize_for_json(all_write_reports), f, ensure_ascii=False, indent=2)
print(f"\n===== 处理完成 =====")
print(f"成功处理来源项:{success_count}, 失败:{fail_count}")
print(f"写码成功:{total_written}, 写码失败:{total_failures}, 重复跳过:{total_duplicates}, SHA 冲突:{total_conflicts}")
print(f"问题组报告:{issues_file}")
print(f"写码报告:{write_report_file}")
if __name__ == "__main__":
main()