modified pppp

client/Reader/MainForm.Designer.cs

@@ -21,7 +21,6 @@ namespace Reader
             Filename = new DataGridViewTextBoxColumn();
             eryi_ID = new DataGridViewTextBoxColumn();
             下载者用户名 = new DataGridViewTextBoxColumn();
-            暗码写入时间 = new DataGridViewTextBoxColumn();
             ((System.ComponentModel.ISupportInitialize)dgv).BeginInit();
             SuspendLayout();
             // 
@@ -58,12 +57,15 @@ namespace Reader
             dgv.AllowUserToDeleteRows = false;
             dgv.AutoSizeColumnsMode = DataGridViewAutoSizeColumnsMode.Fill;
             dgv.ColumnHeadersHeightSizeMode = DataGridViewColumnHeadersHeightSizeMode.AutoSize;
-            dgv.Columns.AddRange(new DataGridViewColumn[] { Filename, eryi_ID, 下载者用户名, 暗码写入时间 });
+            dgv.Columns.AddRange(new DataGridViewColumn[] { Filename, eryi_ID, 下载者用户名 });
             dgv.Location = new Point(12, 59);
             dgv.Name = "dgv";
             dgv.ReadOnly = true;
-            dgv.Size = new Size(748, 332);
+            dgv.RowHeadersWidth = 37;
+            dgv.RowHeadersWidthSizeMode = DataGridViewRowHeadersWidthSizeMode.DisableResizing;
+            dgv.Size = new Size(770, 332);
             dgv.TabIndex = 2;
+            dgv.CellClick += dgv_CellClick;
             // 
             // Filename
             // 
@@ -71,18 +73,18 @@ namespace Reader
             Filename.FillWeight = 300F;
             Filename.Frozen = true;
             Filename.HeaderText = "文件名";
-            Filename.MinimumWidth = 400;
+            Filename.MinimumWidth = 500;
             Filename.Name = "Filename";
             Filename.ReadOnly = true;
-            Filename.Width = 400;
+            Filename.Width = 500;
             // 
             // eryi_ID
             // 
             eryi_ID.AutoSizeMode = DataGridViewAutoSizeColumnMode.ColumnHeader;
-            eryi_ID.HeaderText = "二一资料ID";
+            eryi_ID.HeaderText = "二一暗码(资料ID)";
             eryi_ID.Name = "eryi_ID";
             eryi_ID.ReadOnly = true;
-            eryi_ID.Width = 94;
+            eryi_ID.Width = 100;
             // 
             // 下载者用户名
             // 
@@ -90,16 +92,7 @@ namespace Reader
             下载者用户名.HeaderText = "下载者用户名";
             下载者用户名.Name = "下载者用户名";
             下载者用户名.ReadOnly = true;
-            下载者用户名.Width = 105;
+            下载者用户名.Width = 100;
-            // 
-            // 暗码写入时间
-            // 
-            暗码写入时间.AutoSizeMode = DataGridViewAutoSizeColumnMode.ColumnHeader;
-            暗码写入时间.FillWeight = 300F;
-            暗码写入时间.HeaderText = "暗码写入时间";
-            暗码写入时间.Name = "暗码写入时间";
-            暗码写入时间.ReadOnly = true;
-            暗码写入时间.Width = 105;
             // 
             // MainForm
             // 
@@ -125,6 +118,5 @@ namespace Reader
         private DataGridViewTextBoxColumn Filename;
         private DataGridViewTextBoxColumn eryi_ID;
         private DataGridViewTextBoxColumn 下载者用户名;
-        private DataGridViewTextBoxColumn 暗码写入时间;
     }
 }

client/Reader/MainForm.cs

@@ -1,4 +1,6 @@
 using System;
+using System.Collections.Generic;
+using System.Diagnostics;
 using System.IO;
 using System.Linq;
 using System.Net.Http;
@@ -14,6 +16,11 @@ namespace Reader
     {
         private static readonly HttpClient http = new HttpClient();
         private static readonly string ServerUrl;
+        private static readonly HashSet<string> DocumentExtensions = new(StringComparer.OrdinalIgnoreCase)
+        {
+            ".doc", ".docx", ".pdf", ".ppt", ".pptx"
+        };
+        private MouseButtons lastGridMouseButton = MouseButtons.Left;
 
         static MainForm()
         {
@@ -27,6 +34,8 @@ namespace Reader
         public MainForm()
         {
             InitializeComponent();
+            dgv.CellMouseDown += dgv_CellMouseDown;
+            dgv.CellMouseClick += dgv_CellMouseClick;
         }
 
         private void btnBrowse_Click(object sender, EventArgs e)
@@ -47,25 +56,29 @@ namespace Reader
                 return;
             }
             dgv.Rows.Clear();
-            var files = Directory.GetFiles(folder, "*", SearchOption.AllDirectories);
+            var files = Directory
-            var shaList = new System.Collections.Generic.List<string>();
+                .GetFiles(folder, "*", SearchOption.AllDirectories)
-            var fileMap = new System.Collections.Generic.Dictionary<string, string>();
+                .Where(IsSupportedDocument)
+                .OrderBy(Path.GetFileName, StringComparer.CurrentCultureIgnoreCase)
+                .ToList();
+            var fileEntries = new List<(string FilePath, string Sha)>();
+            var shaList = new List<string>();
             foreach (var f in files)
             {
                 try
                 {
                     var sha = await Task.Run(() => ComputeSha256(f));
+                    fileEntries.Add((f, sha));
                     shaList.Add(sha);
-                    fileMap[sha] = f;
                 }
                 catch { }
             }
-            if (shaList.Count == 0)
+            if (fileEntries.Count == 0)
             {
-                MessageBox.Show("没有找到文件。", "提示", MessageBoxButtons.OK, MessageBoxIcon.Information);
+                MessageBox.Show("没有找到支持的文档文件。", "提示", MessageBoxButtons.OK, MessageBoxIcon.Information);
                 return;
             }
-            var payload = new { shas = shaList };
+            var payload = new { shas = shaList.Distinct().ToList() };
             var content = new StringContent(JsonSerializer.Serialize(payload), Encoding.UTF8, "application/json");
             var resp = await http.PostAsync(ServerUrl + "/read", content);
             if (!resp.IsSuccessStatusCode)
@@ -77,21 +90,25 @@ namespace Reader
             using var doc = JsonDocument.Parse(text);
             var root = doc.RootElement;
             var data = root.GetProperty("data");
-            foreach (var sha in shaList)
+            foreach (var entry in fileEntries)
             {
-                var fileName = Path.GetFileName(fileMap[sha]);
+                var fileName = Path.GetFileName(entry.FilePath);
-                if (data.TryGetProperty(sha, out var item) && item.ValueKind != JsonValueKind.Null)
+                string up = "无";
+                string down = "无";
+                if (data.TryGetProperty(entry.Sha, out var item) && item.ValueKind != JsonValueKind.Null)
                 {
-                    var up = item.GetProperty("upload_code").GetString() ?? "";
+                    up = item.GetProperty("upload_code").GetString() ?? "";
-                    var down = item.GetProperty("download_code").GetString() ?? "";
+                    down = item.GetProperty("download_code").GetString() ?? "";
-                    var created = item.GetProperty("created_at").GetString() ?? "";
-                    dgv.Rows.Add(fileName, up, down, created);
                 }
-                else
+                var rowIndex = dgv.Rows.Add(fileName, up, down);
-                {
+                dgv.Rows[rowIndex].Tag = entry.FilePath;
-                    dgv.Rows.Add(fileName, "无", "无", "无");
+                dgv.Rows[rowIndex].Cells["Filename"].ToolTipText = entry.FilePath;
             }
         }
+
+        private static bool IsSupportedDocument(string filePath)
+        {
+            return DocumentExtensions.Contains(Path.GetExtension(filePath));
         }
 
         private static string ComputeSha256(string filePath)
@@ -106,30 +123,108 @@ namespace Reader
 
         private void MainForm_Load(object sender, EventArgs e)
         {
-            // 1. 去除自动尺寸模式的限制，改用手动指定
             dgv.AutoSizeColumnsMode = DataGridViewAutoSizeColumnsMode.None;
-
+            dgv.ShowCellToolTips = true;
-                // 2. 计算每一列的理想宽度
+            dgv.Columns["Filename"].Width = 500;
-                // 假设您有 N 列，除了最后一列，其余列平分空间
+            dgv.Columns["eryi_ID"].Width = 100;
-                int columnCount = dgv.Columns.Count;
+            dgv.Columns["下载者用户名"].Width = 100;
-                int totalWidth = dgv.ClientSize.Width; // 获取控件当前宽度
-
-                // 3. 遍历每一列
-                for (int i = 0; i < columnCount; i++)
-                {
-                    // 这里做一个简单的平均分配逻辑
-                    double width = totalWidth / columnCount;
-
-                // 设置列宽，注意：不能小于最小宽度
-                dgv.Columns[i].Width = (int)Math.Ceiling(width);
         }
 
-                // 如果最后一列想稍微宽一点，或者确保宽度总和等于控件宽度，可以做微调
+        private void dgv_CellClick(object sender, DataGridViewCellEventArgs e)
-                int remaining = totalWidth - dgv.Columns.Cast<DataGridViewColumn>()
+        {
-                    .Take(columnCount - 1)
+            if (lastGridMouseButton == MouseButtons.Right)
-                    .Sum(col => col.Width);
+            {
+                return;
+            }
+            HandleGridClick(e);
+        }
 
-            dgv.Columns[columnCount - 1].Width = remaining;
+        private void dgv_CellMouseDown(object sender, DataGridViewCellMouseEventArgs e)
+        {
+            lastGridMouseButton = e.Button;
+        }
+
+        private void dgv_CellMouseClick(object sender, DataGridViewCellMouseEventArgs e)
+        {
+            if (e.RowIndex < 0 || e.ColumnIndex < 0 || e.Button != MouseButtons.Right)
+            {
+                return;
+            }
+
+            var columnName = dgv.Columns[e.ColumnIndex].Name;
+            if (columnName != "Filename")
+            {
+                return;
+            }
+
+            var row = dgv.Rows[e.RowIndex];
+            var filePath = row.Tag as string;
+            if (!string.IsNullOrWhiteSpace(filePath) && File.Exists(filePath))
+            {
+                OpenFolderAndSelectFile(filePath);
+            }
+        }
+
+        private void HandleGridClick(DataGridViewCellEventArgs e)
+        {
+            if (e.RowIndex < 0 || e.ColumnIndex < 0)
+            {
+                return;
+            }
+
+            var row = dgv.Rows[e.RowIndex];
+            var columnName = dgv.Columns[e.ColumnIndex].Name;
+            if (columnName == "Filename")
+            {
+                var filePath = row.Tag as string;
+                if (!string.IsNullOrWhiteSpace(filePath) && File.Exists(filePath))
+                {
+                    OpenWithShell(filePath);
+                }
+                return;
+            }
+
+            if (columnName == "eryi_ID")
+            {
+                var code = row.Cells["eryi_ID"].Value?.ToString()?.Trim() ?? "";
+                if (!string.IsNullOrWhiteSpace(code) && code != "无")
+                {
+                    OpenWithShell($"https://www.21cnjy.com/H/3/309824/{code}.shtml?token=mK2x9Pq7Rf4Tz8Wv1Lc3Yh5Nj6Bs0Ad9Eg2Hj3Kl4Mp5Qr6St7Uv8Wx9Yz0Ab1Cd");
+                }
+            }
+        }
+
+        private static void OpenFolderAndSelectFile(string filePath)
+        {
+            try
+            {
+                Process.Start(new ProcessStartInfo
+                {
+                    FileName = "explorer.exe",
+                    Arguments = $"/select,\"{filePath}\"",
+                    UseShellExecute = true
+                });
+            }
+            catch (Exception ex)
+            {
+                MessageBox.Show("打开文件所在位置失败: " + ex.Message, "错误", MessageBoxButtons.OK, MessageBoxIcon.Error);
+            }
+        }
+
+        private static void OpenWithShell(string target)
+        {
+            try
+            {
+                Process.Start(new ProcessStartInfo
+                {
+                    FileName = target,
+                    UseShellExecute = true
+                });
+            }
+            catch (Exception ex)
+            {
+                MessageBox.Show("打开失败: " + ex.Message, "错误", MessageBoxButtons.OK, MessageBoxIcon.Error);
+            }
         }
     }
 }

server/association_detail.py

@@ -0,0 +1,825 @@
+# -*- 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-embed-text:latest')
+
+
+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))
+            break
+
+    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"在 {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 has_audio_video_files(files_list: List[Dict[str, Union[str, float]]]) -> 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'}
+    for file_entry in files_list:
+        name = file_entry.get('name', '')
+        if any(name.lower().endswith(ext) for ext in audio_video_exts):
+            return True
+    return False
+
+
+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]]]:
+            def format_datetime(mtime: float) -> str:
+                """将时间戳格式化为可读的日期时间字符串"""
+                return datetime.fromtimestamp(mtime).strftime("%Y-%m-%d %H:%M:%S")
+
+            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, "datetime": format_datetime(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, "datetime": format_datetime(mtime)})
+            else:
+                mtime = file_path.stat().st_mtime
+                files.append({"name": file_path.name, "mtime": mtime, "datetime": format_datetime(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
+            ]
+            if not extracted_times:
+                return None
+
+            # 找出压缩文件本身的时间
+            archive_mtime = None
+            for entry in file_entries:
+                if entry.get("name") == archive_name and "mtime" in entry:
+                    archive_mtime = entry["mtime"]
+                    break
+
+            latest_extracted = max(extracted_times)
+
+            # 如果压缩文件时间和解压文件最晚时间差小于 8000 秒，返回 None
+            if archive_mtime is not None and abs(latest_extracted - archive_mtime) < 18000:
+                return None
+
+            return latest_extracted
+
+        # 初始化条目
+        entry = {}
+        group1_files = []
+        group2_files = []
+        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（时间差超过阈值），则记录到问题列表
+        # 或者如果解压出来的文件中包含音视频文件，也记录到问题列表
+        TIME_DIFF_THRESHOLD = 30  # 时间差阈值（秒），避免将 zip 文件和解压文件时间相近的误判为问题组
+        time_diff_condition = (
+            group1_latest is not None
+            and group2_latest is not None
+            and group1_latest < group2_latest
+            and (group2_latest - group1_latest) > TIME_DIFF_THRESHOLD
+        )
+        if time_diff_condition:
+            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"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
+        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}")
+        print(len(all_problem_groups))
+
+        # 将所有涉及的原始文件夹从 cc 目录复制到 ff 目录
+        script_dir = Path(__file__).parent
+        cc_dir = script_dir / "cc"
+        ff_dir = script_dir / "ff"
+        ff_dir.mkdir(exist_ok=True)
+
+        # 收集所有需要复制的文件夹（去重）
+        folders_to_copy = set()
+        for group in all_problem_groups:
+            source_folder = group.get("source_folder")
+            if source_folder:
+                folders_to_copy.add(source_folder)
+
+        print(f"\n准备复制 {len(folders_to_copy)} 个文件夹到 ff 目录...")
+        for folder_name in folders_to_copy:
+            src_folder = cc_dir / folder_name
+            if src_folder.exists() and src_folder.is_dir():
+                dest_folder = ff_dir / folder_name
+                if not dest_folder.exists():
+                    print(f"  复制：{folder_name}")
+                    shutil.copytree(str(src_folder), str(dest_folder))
+                else:
+                    print(f"  已存在，跳过：{folder_name}")
+            else:
+                print(f"  未找到源文件夹：{folder_name} (cc/{folder_name})")
+
+        return
+
+if __name__ == "__main__":
+    main()

server/association_detail2.py

@@ -0,0 +1,863 @@
+# -*- 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-embed-text:latest')
+
+
+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"在 {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"""
+    def is_date_time(line: str) -> bool:
+        """判断一行是否是日期时间格式"""
+        import re
+        # 匹配 YYYY-MM-DD, YYYY/MM/DD, YYYY-MM-DD HH:MM:SS, YYYY/MM/DD H:MM 等格式
+        pattern = r'^\d{4}[-/]\d{1,2}[-/]\d{1,2}( \d{1,2}:\d{1,2}(:\d{1,2})?)?$'
+        return bool(re.match(pattern, line.strip()))
+    
+    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)
+
+            # 删除超链接格式：HYPERLINK "url" url -> 只保留 url 部分
+            def clean_hyperlink(line):
+                """清理超链接格式"""
+                # 匹配 HYPERLINK &quot;url&quot; url 格式（HTML 实体编码）
+                # 也兼容普通引号的情况
+                hl_pattern = r'HYPERLINK\s+&quot;([^&]+)&quot;\s+(\S+)'
+                match = re.match(hl_pattern, line)
+                if match:
+                    return match.group(2)  # 返回第二个 url
+                return line
+
+            processed = [clean_hyperlink(line) for line in processed]
+
+            # 按行处理
+            lines = [line.strip() for line in processed if line.strip()]
+
+            # 检测是否每行都是单字段（没有\t）
+            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:
+                # 新格式：按网站分组，然后将对应位置的资料配对
+
+                # 收集 21 世纪教育的资料
+                twole_titles = []
+                twole_urls = []
+                twole_dates = []
+                in_twole = False
+
+                # 收集学科网的资料
+                zxxk_titles = []
+                zxxk_urls = []
+                zxxk_dates = []
+                in_zxxk = False
+
+                i = 0
+                while i < len(lines):
+                    line = lines[i]
+
+                    # 判断是否为题目标记
+                    if line == '21世纪教育':
+                        in_twole = True
+                        in_zxxk = False
+                        i += 1
+                    elif line == '学科网':
+                        in_twole = False
+                        in_zxxk = True
+                        i += 1
+                    elif line.strip() == '......':
+                        # 分隔符，根据当前位置决定归属
+                        i += 1
+                    elif in_twole:
+                        # 21 世纪教育的数据行：标题在一行，url 在下一行，可选日期在第三行
+                        title = line
+                        if i + 1 < len(lines) and lines[i + 1].startswith('https://www.21cnjy.com/'):
+                            url = lines[i + 1]
+                            if i + 2 < len(lines) and is_date_time(lines[i + 2]):
+                                date = lines[i + 2]
+                                twole_titles.append(title)
+                                twole_urls.append(url)
+                                twole_dates.append(date)
+                                i += 3
+                            else:
+                                twole_titles.append(title)
+                                twole_urls.append(url)
+                                twole_dates.append('1970-1-1')
+                                i += 2
+                        else:
+                            twole_titles.append(title)
+                            twole_urls.append('')
+                            twole_dates.append('1970-1-1')
+                            i += 1
+                    elif in_zxxk:
+                        # 学科网的数据行：标题在一行，url 在下一行，可选日期在第三行
+                        title = line
+                        if i + 1 < len(lines) and lines[i + 1].startswith('https://www.zxxk.com/'):
+                            url = lines[i + 1]
+                            if i + 2 < len(lines) and is_date_time(lines[i + 2]):
+                                date = lines[i + 2]
+                                zxxk_titles.append(title)
+                                zxxk_urls.append(url)
+                                zxxk_dates.append(date)
+                                i += 3
+                            else:
+                                zxxk_titles.append(title)
+                                zxxk_urls.append(url)
+                                zxxk_dates.append('1970-1-1')
+                                i += 2
+                        else:
+                            zxxk_titles.append(title)
+                            zxxk_urls.append('')
+                            zxxk_dates.append('1970-1-1')
+                            i += 1
+                    else:
+                        i += 1
+
+                # 配对生成结果：每对包含 6 个元素（标题 1, url1, 日期 1, 标题 2, url2, 日期 2）
+                result = []
+                # 取两者中较小长度，避免索引越界
+                count = min(len(twole_titles), len(zxxk_titles))
+                for j in range(count):
+                    # 构造 6 个字段
+                    parts = [
+                        twole_titles[j],          # 21 世纪教育标题
+                        twole_urls[j],            # 21 世纪教育 url
+                        twole_dates[j],           # 21 世纪教育日期
+                        zxxk_titles[j],           # 学科网标题
+                        zxxk_urls[j],             # 学科网 url
+                        zxxk_dates[j]             # 学科网日期
+                    ]
+                    result.append('\t'.join(parts))
+
+                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 has_audio_video_files(files_list: List[Dict[str, Union[str, float]]]) -> 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'}
+    for file_entry in files_list:
+        name = file_entry.get('name', '')
+        if any(name.lower().endswith(ext) for ext in audio_video_exts):
+            return True
+    return False
+
+
+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]]]:
+            def format_datetime(mtime: float) -> str:
+                """将时间戳格式化为可读的日期时间字符串"""
+                return datetime.fromtimestamp(mtime).strftime("%Y-%m-%d %H:%M:%S")
+
+            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, "datetime": format_datetime(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, "datetime": format_datetime(mtime)})
+            else:
+                mtime = file_path.stat().st_mtime
+                files.append({"name": file_path.name, "mtime": mtime, "datetime": format_datetime(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
+            ]
+            if not extracted_times:
+                return None
+
+            # 找出压缩文件本身的时间
+            archive_mtime = None
+            for entry in file_entries:
+                if entry.get("name") == archive_name and "mtime" in entry:
+                    archive_mtime = entry["mtime"]
+                    break
+
+            latest_extracted = max(extracted_times)
+
+            # 如果压缩文件时间和解压文件最晚时间差小于 30 秒，返回 None
+            if archive_mtime is not None and abs(latest_extracted - archive_mtime) < 300:
+                return None
+
+            return latest_extracted
+
+        # 初始化条目
+        entry = {}
+        group1_files = []
+        group2_files = []
+        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（时间差超过阈值），则记录到问题列表
+        # 或者如果解压出来的文件中包含音视频文件，也记录到问题列表
+        TIME_DIFF_THRESHOLD = 30  # 时间差阈值（秒），避免将 zip 文件和解压文件时间相近的误判为问题组
+        time_diff_condition = (
+            group1_latest is not None
+            and group2_latest is not None
+            and group1_latest < group2_latest
+            and (group2_latest - group1_latest) > TIME_DIFF_THRESHOLD
+        )
+        if time_diff_condition:
+            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"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
+        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}")
+        print(len(all_problem_groups))
+
+        # 将所有涉及的原始文件夹从 cc 目录复制到 ff 目录
+        script_dir = Path(__file__).parent
+        cc_dir = script_dir / "cc"
+        ff_dir = script_dir / "ff"
+        ff_dir.mkdir(exist_ok=True)
+
+        # 收集所有需要复制的文件夹（去重）
+        folders_to_copy = set()
+        for group in all_problem_groups:
+            source_folder = group.get("source_folder")
+            if source_folder:
+                folders_to_copy.add(source_folder)
+
+        print(f"\n准备复制 {len(folders_to_copy)} 个文件夹到 ff 目录...")
+        for folder_name in folders_to_copy:
+            src_folder = cc_dir / folder_name
+            if src_folder.exists() and src_folder.is_dir():
+                dest_folder = ff_dir / folder_name
+                if not dest_folder.exists():
+                    print(f"  复制：{folder_name}")
+                    shutil.copytree(str(src_folder), str(dest_folder))
+                else:
+                    print(f"  已存在，跳过：{folder_name}")
+            else:
+                print(f"  未找到源文件夹：{folder_name} (cc/{folder_name})")
+
+        return
+
+if __name__ == "__main__":
+    main()

server/backup_files.py

@@ -0,0 +1,185 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+根据 compressed_group_time_issues.json 的信息，将文件备份到 bak 目录
+"""
+
+import json
+import shutil
+from pathlib import Path
+
+
+# 配置路径
+JSON_FILE_PATH = 'server/jsons/compressed_group_time_issues.json'
+CC_DIR = Path('cc')
+BAK_DIR = Path('bak')
+
+
+def find_subfolder(base_dir: Path, folder_name: str) -> Path | None:
+    """
+    在 base_dir 下查找名为 folder_name 的子文件夹
+    """
+    target = base_dir / folder_name
+    if target.exists() and target.is_dir():
+        return target
+    return None
+
+
+def find_21cnjy_folder(base_dir: Path) -> Path | None:
+    """
+    查找二一教育（21 世纪教育网）文件夹
+    参照 association_detail.py 第 733-738 行的逻辑
+    """
+    candidates = [
+        "21世纪教育网",
+        "二一教育",
+        "21世纪教育",
+        "二一世纪教育"
+    ]
+    for candidate in candidates:
+        folder = base_dir / candidate
+        if folder.exists() and folder.is_dir():
+            return folder
+    return None
+
+
+def find_zxxk_folder(base_dir: Path) -> Path | None:
+    """
+    查找学科网文件夹
+    """
+    return base_dir / "学科网"
+
+
+def copy_file_with_path(src_file: Path, dst_dir: Path) -> None:
+    """
+    复制文件及其 2 级路径（source_folder 和 二一教育/学科网）到目标目录
+    """
+    if not src_file.exists():
+        return
+
+    source_folder_name = src_file.parent.parent.name
+    platform_folder_name = src_file.parent.name
+
+    # 构建目标路径：bak/source_folder/platform_folder/
+    dst_file = dst_dir / source_folder_name / platform_folder_name / src_file.name
+
+    # 创建目标目录
+    dst_file.parent.mkdir(parents=True, exist_ok=True)
+
+    # 复制文件
+    shutil.copy2(str(src_file), str(dst_file))
+
+
+def process_record(record: dict, cc_dir: Path, bak_dir: Path) -> dict:
+    """
+    处理一条记录，返回处理结果
+    """
+    result = {
+        'row_index': record.get('row_index'),
+        'source_folder': record.get('source_folder'),
+        'group1_copied': False,
+        'group2_copied': False,
+        'group1_file': None,
+        'group2_file': None,
+        'error': None
+    }
+
+    source_folder_name = record.get('source_folder')
+    if not source_folder_name:
+        result['error'] = 'Missing source_folder'
+        return result
+
+    # 在 cc 目录下查找 source_folder
+    source_dir = find_subfolder(cc_dir, source_folder_name)
+    if not source_dir:
+        result['error'] = f'Source folder not found: {source_folder_name}'
+        return result
+
+    # 查找二一教育和学科网文件夹
+    group1_folder = find_21cnjy_folder(source_dir)
+    group2_folder = find_zxxk_folder(source_dir)
+
+    if not group2_folder:
+        result['error'] = f'学科网 folder not found in {source_folder_name}'
+        print(f"Warning: 学科网 folder not found in {source_folder_name}, skipping this record.")
+        return result
+
+    if not group1_folder:
+        result['error'] = f'二一教育 folder not found in {source_folder_name}'
+        print(f"Warning: 二一教育 folder not found in {source_folder_name}, skipping this record.")
+        return result
+
+    # 获取 group1 和 group2 的第一个文件（zip 文件）
+    group1_files = record.get('group1', {}).get('files', [])
+    group2_files = record.get('group2', {}).get('files', [])
+
+    if not group1_files or not group2_files:
+        result['error'] = 'Missing files in group1 or group2'
+        return result
+
+    group1_zip_name = group1_files[0].get('name')
+    group2_zip_name = group2_files[0].get('name')
+
+    # 构建源文件路径
+    group1_src_file = group1_folder / group1_zip_name
+    group2_src_file = group2_folder / group2_zip_name
+
+    # 复制 group1 文件（二一教育）
+    if group1_src_file.exists():
+        copy_file_with_path(group1_src_file, bak_dir)
+        result['group1_copied'] = True
+        result['group1_file'] = group1_zip_name
+    else:
+        result['error'] = f'Group1 file not found: {group1_src_file}'
+        return result
+
+    # 复制 group2 文件（学科网）
+    if group2_src_file.exists():
+        copy_file_with_path(group2_src_file, bak_dir)
+        result['group2_copied'] = True
+        result['group2_file'] = group2_zip_name
+    else:
+        result['error'] = f'Group2 file not found: {group2_src_file}'
+        return result
+
+    return result
+
+
+def main():
+    """主函数"""
+    print("=" * 60)
+    print("开始备份文件到 bak 目录")
+    print("=" * 60)
+
+    # 加载 JSON 数据
+    with open(JSON_FILE_PATH, 'r', encoding='utf-8') as f:
+        data = json.load(f)
+
+    print(f"共 {len(data)} 条记录需要处理\n")
+
+    success_count = 0
+    fail_count = 0
+
+    for record in data:
+        row_index = record.get('row_index', 'unknown')
+        source_folder = record.get('source_folder', 'unknown')
+
+        result = process_record(record, CC_DIR, BAK_DIR)
+
+        if result['group1_copied'] and result['group2_copied']:
+            success_count += 1
+            print(f"✓ [{row_index}] {source_folder}")
+            print(f"    二一教育：{result['group1_file']}")
+            print(f"    学科网：{result['group2_file']}")
+        else:
+            fail_count += 1
+            print(f"✗ [{row_index}] {source_folder}")
+            print(f"    错误：{result['error']}")
+
+    print("\n" + "=" * 60)
+    print(f"备份完成！成功：{success_count} 条，失败：{fail_count} 条")
+    print("=" * 60)
+
+
+if __name__ == '__main__':
+    main()

server/file_association.py

@@ -15,6 +15,11 @@ 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:
@@ -27,6 +32,93 @@ def clear_directory(dir_path: Path) -> None:
                 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",
@@ -151,24 +243,54 @@ def read_docx_content(doc_path: Path) -> List[str]:
                 # 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 + 1 < len(lines):
+                    if start_idx + 5 < len(lines):
                         return is_url_line(lines[start_idx + 1]) and \
-                               is_datetime_line(lines[start_idx + 2])
+                               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：如果第二行是网址且第三行是日期/时间，则当前 6 行为一组；否则丢弃第一行，继续判断
+                # 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 + 5 <= len(lines):
+                while i + 4 <= len(lines):
-                    # 检查当前位置开始是否是 6 行一组模式
+                    if i + 5 < len(lines) and is_six_row_group(lines, i):
-                    if 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 6 行一组，丢弃当前行（相当于 offset+1）
+                        # 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):
@@ -395,7 +517,11 @@ def build_file_associations(
 
         # 第一组：根据网址匹配文件
         if 'www.21cnjy.com' in url1 and twole_files:
-            file_path, ctime = twole_files.pop(0)
+            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,
@@ -403,7 +529,11 @@ def build_file_associations(
                     "time": time1
                 })
         elif 'www.zxxk.com' in url1 and zxxk_files:
-            file_path, ctime = zxxk_files.pop(0)
+            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,
@@ -413,7 +543,11 @@ def build_file_associations(
 
         # 第二组：根据网址匹配文件
         if 'www.21cnjy.com' in url2 and twole_files:
-            file_path, ctime = twole_files.pop(0)
+            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,
@@ -421,7 +555,11 @@ def build_file_associations(
                     "time": time2
                 })
         elif 'www.zxxk.com' in url2 and zxxk_files:
-            file_path, ctime = zxxk_files.pop(0)
+            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,
@@ -472,9 +610,9 @@ def main():
             clear_directory(data_dir)
 
             try:
-                # 移动文件夹到 data 目录
+                # 拷贝文件夹到 data 目录
                 extract_dir = data_dir / folder.name
-                shutil.move(str(folder), str(extract_dir))
+                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
 
@@ -515,6 +653,9 @@ def main():
                     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
@@ -530,6 +671,17 @@ def main():
 
                 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:

server/import_json_to_mysql.py

@@ -0,0 +1,391 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+将 jsons/compressed_group_time_issues.json 导入 MySQL。
+
+只导入以下四类，并把同一 row 中二一教育和学科网的数据合并为同一条记录：
+- single_files
+- same_child_archive_time
+- zxxk_child_earlier
+- twole_child_earlier
+"""
+
+import argparse
+import json
+import re
+from datetime import datetime
+from pathlib import Path
+from typing import Dict, Iterable, List, Optional, Tuple
+
+import mysql.connector
+from mysql.connector import Error
+
+
+DB_CONFIG = {
+    'host': '127.0.0.1',
+    'port': 3306,
+    'user': 'root',
+    'password': 'root123456',
+    'database': 'testdb',
+    'charset': 'utf8mb4'
+}
+
+BASE_DIR = Path(__file__).resolve().parent
+DEFAULT_JSON_FILE_PATH = BASE_DIR / "jsons" / "compressed_group_time_issues.json"
+DEFAULT_TABLE_NAME = "compressed_group_time_records"
+SELECTED_CATEGORIES = (
+    "single_files",
+    "same_child_archive_time",
+    "zxxk_child_earlier",
+    "twole_child_earlier",
+)
+
+
+CREATE_TABLE_TEMPLATE = """
+CREATE TABLE IF NOT EXISTS `{table_name}` (
+    id BIGINT AUTO_INCREMENT PRIMARY KEY COMMENT '主键',
+    category VARCHAR(64) NOT NULL COMMENT '分类',
+    source_folder VARCHAR(512) NOT NULL COMMENT '来源文件夹',
+    word_doc VARCHAR(512) NOT NULL COMMENT '关联 Word 文档',
+    row_index INT NOT NULL COMMENT 'Word 内容行索引',
+
+    earlier_site VARCHAR(64) COMMENT '更早的网站中文名',
+    earlier_site_key VARCHAR(32) COMMENT '更早的网站 key: twole/zxxk',
+    child_time_diff_seconds DOUBLE COMMENT '学科网子文件时间 - 二一教育子文件时间',
+
+    twole_title TEXT COMMENT '二一教育标题',
+    twole_url TEXT COMMENT '二一教育 URL',
+    twole_source_time VARCHAR(100) COMMENT 'Word 中二一教育时间',
+    twole_id VARCHAR(100) COMMENT '二一教育 URL ID',
+    twole_file_kind VARCHAR(32) COMMENT '二一教育文件类型',
+    twole_file_name VARCHAR(1024) COMMENT '二一教育文件名',
+    twole_file_mtime DOUBLE COMMENT '二一教育文件 mtime',
+    twole_file_datetime DATETIME COMMENT '二一教育文件时间',
+    twole_archive_mtime DOUBLE COMMENT '二一教育压缩包 mtime',
+    twole_archive_datetime DATETIME COMMENT '二一教育压缩包时间',
+    twole_latest_child_mtime DOUBLE COMMENT '二一教育压缩包内最新子文件 mtime',
+    twole_latest_child_datetime DATETIME COMMENT '二一教育压缩包内最新子文件时间',
+    twole_child_archive_time_relation VARCHAR(32) COMMENT '二一教育子文件与压缩包时间关系',
+    twole_child_archive_time_diff_seconds DOUBLE COMMENT '二一教育子文件与压缩包时间差',
+
+    zxxk_title TEXT COMMENT '学科网标题',
+    zxxk_url TEXT COMMENT '学科网 URL',
+    zxxk_source_time VARCHAR(100) COMMENT 'Word 中学科网时间',
+    zxxk_id VARCHAR(100) COMMENT '学科网 URL ID',
+    zxxk_file_kind VARCHAR(32) COMMENT '学科网文件类型',
+    zxxk_file_name VARCHAR(1024) COMMENT '学科网文件名',
+    zxxk_file_mtime DOUBLE COMMENT '学科网文件 mtime',
+    zxxk_file_datetime DATETIME COMMENT '学科网文件时间',
+    zxxk_archive_mtime DOUBLE COMMENT '学科网压缩包 mtime',
+    zxxk_archive_datetime DATETIME COMMENT '学科网压缩包时间',
+    zxxk_latest_child_mtime DOUBLE COMMENT '学科网压缩包内最新子文件 mtime',
+    zxxk_latest_child_datetime DATETIME COMMENT '学科网压缩包内最新子文件时间',
+    zxxk_child_archive_time_relation VARCHAR(32) COMMENT '学科网子文件与压缩包时间关系',
+    zxxk_child_archive_time_diff_seconds DOUBLE COMMENT '学科网子文件与压缩包时间差',
+
+    twole_json JSON COMMENT '二一教育原始 JSON',
+    zxxk_json JSON COMMENT '学科网原始 JSON',
+    raw_json JSON NOT NULL COMMENT '合并前原始 JSON',
+    imported_at DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP COMMENT '导入时间',
+    updated_at DATETIME NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP COMMENT '更新时间',
+
+    UNIQUE KEY uniq_category_row (category, source_folder(191), word_doc(191), row_index),
+    KEY idx_category (category),
+    KEY idx_earlier_site_key (earlier_site_key),
+    KEY idx_source_row (source_folder(191), word_doc(191), row_index),
+    KEY idx_twole_id (twole_id),
+    KEY idx_zxxk_id (zxxk_id),
+    KEY idx_twole_latest_child_mtime (twole_latest_child_mtime),
+    KEY idx_zxxk_latest_child_mtime (zxxk_latest_child_mtime)
+) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4 COMMENT='压缩包时间分类记录';
+"""
+
+
+INSERT_COLUMNS = (
+    "category", "source_folder", "word_doc", "row_index",
+    "earlier_site", "earlier_site_key", "child_time_diff_seconds",
+    "twole_title", "twole_url", "twole_source_time", "twole_id", "twole_file_kind",
+    "twole_file_name", "twole_file_mtime", "twole_file_datetime",
+    "twole_archive_mtime", "twole_archive_datetime",
+    "twole_latest_child_mtime", "twole_latest_child_datetime",
+    "twole_child_archive_time_relation", "twole_child_archive_time_diff_seconds",
+    "zxxk_title", "zxxk_url", "zxxk_source_time", "zxxk_id", "zxxk_file_kind",
+    "zxxk_file_name", "zxxk_file_mtime", "zxxk_file_datetime",
+    "zxxk_archive_mtime", "zxxk_archive_datetime",
+    "zxxk_latest_child_mtime", "zxxk_latest_child_datetime",
+    "zxxk_child_archive_time_relation", "zxxk_child_archive_time_diff_seconds",
+    "twole_json", "zxxk_json", "raw_json",
+)
+
+
+def mysql_identifier(name: str) -> str:
+    if not re.match(r"^[A-Za-z0-9_]+$", name):
+        raise ValueError(f"非法表名：{name}")
+    return name
+
+
+def epoch_to_datetime(value) -> Optional[str]:
+    if value in (None, ""):
+        return None
+    return datetime.fromtimestamp(float(value)).strftime("%Y-%m-%d %H:%M:%S")
+
+
+def normalize_datetime(value) -> Optional[str]:
+    if not value:
+        return None
+    if isinstance(value, str) and re.match(r"^\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}$", value):
+        return value
+    return None
+
+
+def json_dumps(value) -> str:
+    return json.dumps(value or {}, ensure_ascii=False)
+
+
+def extract_url_id(url: Optional[str], site: str) -> Optional[str]:
+    if not url:
+        return None
+    if site == "twole":
+        match = re.search(r"/(\d+)\.shtml(?:[?#].*)?$", url)
+        if match:
+            return match.group(1)
+    if site == "zxxk":
+        match = re.search(r"/(?:soft/)?(\d+)\.html(?:[?#].*)?$", url)
+        if match:
+            return match.group(1)
+    numbers = re.findall(r"\d+", url)
+    return numbers[-1] if numbers else None
+
+
+def first_file_from_group(group: Dict) -> Dict:
+    files = group.get("files") or []
+    return files[0] if files else {}
+
+
+def build_side_from_individual(record: Dict) -> Dict:
+    file_info = record.get("file") or {}
+    site = record.get("site") or ""
+    return {
+        "title": record.get("title"),
+        "url": record.get("url"),
+        "source_time": record.get("time"),
+        "id": extract_url_id(record.get("url"), site),
+        "file_kind": record.get("file_kind"),
+        "file_name": file_info.get("name"),
+        "file_mtime": file_info.get("mtime"),
+        "file_datetime": normalize_datetime(file_info.get("datetime")) or epoch_to_datetime(file_info.get("mtime")),
+        "archive_mtime": record.get("archive_mtime"),
+        "archive_datetime": normalize_datetime(record.get("archive_datetime")) or epoch_to_datetime(record.get("archive_mtime")),
+        "latest_child_mtime": record.get("latest_child_mtime"),
+        "latest_child_datetime": normalize_datetime(record.get("latest_child_datetime")) or epoch_to_datetime(record.get("latest_child_mtime")),
+        "child_archive_time_relation": record.get("child_archive_time_relation"),
+        "child_archive_time_diff_seconds": record.get("child_archive_time_diff_seconds"),
+        "json": record,
+    }
+
+
+def build_side_from_pair(group: Dict, site: str, pair_record: Dict) -> Dict:
+    file_info = first_file_from_group(group)
+    return {
+        "title": group.get("title"),
+        "url": group.get("url"),
+        "source_time": group.get("time"),
+        "id": extract_url_id(group.get("url"), site),
+        "file_kind": "archive",
+        "file_name": file_info.get("name"),
+        "file_mtime": file_info.get("mtime"),
+        "file_datetime": normalize_datetime(file_info.get("datetime")) or epoch_to_datetime(file_info.get("mtime")),
+        "archive_mtime": file_info.get("mtime"),
+        "archive_datetime": normalize_datetime(file_info.get("datetime")) or epoch_to_datetime(file_info.get("mtime")),
+        "latest_child_mtime": pair_record.get(f"{site}_latest_child_mtime"),
+        "latest_child_datetime": normalize_datetime(pair_record.get(f"{site}_latest_child_datetime")) or epoch_to_datetime(pair_record.get(f"{site}_latest_child_mtime")),
+        "child_archive_time_relation": "different",
+        "child_archive_time_diff_seconds": None,
+        "json": group,
+    }
+
+
+def empty_import_record(category: str, source_folder: str, word_doc: str, row_index: int, raw_json) -> Dict:
+    record = {column: None for column in INSERT_COLUMNS}
+    record.update({
+        "category": category,
+        "source_folder": source_folder,
+        "word_doc": word_doc,
+        "row_index": row_index,
+        "raw_json": json_dumps(raw_json),
+    })
+    return record
+
+
+def apply_side(record: Dict, site: str, side: Dict) -> None:
+    prefix = "twole" if site == "twole" else "zxxk"
+    for key in (
+        "title", "url", "source_time", "id", "file_kind", "file_name", "file_mtime", "file_datetime",
+        "archive_mtime", "archive_datetime", "latest_child_mtime", "latest_child_datetime",
+        "child_archive_time_relation", "child_archive_time_diff_seconds",
+    ):
+        record[f"{prefix}_{key}"] = side.get(key)
+    record[f"{prefix}_json"] = json_dumps(side.get("json"))
+
+
+def row_key(record: Dict) -> Tuple[str, str, int]:
+    return (record.get("source_folder") or "", record.get("word_doc") or "", int(record.get("row_index") or 0))
+
+
+def normalize_individual_category(category: str, records: Iterable[Dict]) -> List[Dict]:
+    grouped: Dict[Tuple[str, str, int], Dict] = {}
+    raw_records: Dict[Tuple[str, str, int], List[Dict]] = {}
+
+    for source_record in records:
+        key = row_key(source_record)
+        raw_records.setdefault(key, []).append(source_record)
+        if key not in grouped:
+            grouped[key] = empty_import_record(category, key[0], key[1], key[2], raw_records[key])
+        grouped[key]["raw_json"] = json_dumps(raw_records[key])
+
+        site = source_record.get("site")
+        if site in ("twole", "zxxk"):
+            apply_side(grouped[key], site, build_side_from_individual(source_record))
+
+    return [grouped[key] for key in sorted(grouped)]
+
+
+def normalize_pair_category(category: str, records: Iterable[Dict]) -> List[Dict]:
+    normalized = []
+    for source_record in records:
+        key = row_key(source_record)
+        record = empty_import_record(category, key[0], key[1], key[2], source_record)
+        record["earlier_site"] = source_record.get("earlier_site")
+        record["earlier_site_key"] = source_record.get("earlier_site_key")
+        record["child_time_diff_seconds"] = source_record.get("child_time_diff_seconds")
+        apply_side(record, "twole", build_side_from_pair(source_record.get("twole") or {}, "twole", source_record))
+        apply_side(record, "zxxk", build_side_from_pair(source_record.get("zxxk") or {}, "zxxk", source_record))
+        normalized.append(record)
+    return normalized
+
+
+def normalize_records_for_import(data: Dict) -> List[Dict]:
+    normalized: List[Dict] = []
+    normalized.extend(normalize_individual_category("single_files", data.get("single_files", [])))
+    normalized.extend(normalize_individual_category("same_child_archive_time", data.get("same_child_archive_time", [])))
+    normalized.extend(normalize_pair_category("zxxk_child_earlier", data.get("zxxk_child_earlier", [])))
+    normalized.extend(normalize_pair_category("twole_child_earlier", data.get("twole_child_earlier", [])))
+    return normalized
+
+
+def load_json_data(file_path: Path) -> Dict:
+    with file_path.open("r", encoding="utf-8") as f:
+        data = json.load(f)
+    if not isinstance(data, dict):
+        raise ValueError("当前导入脚本只支持新版分类字典格式 JSON")
+    return data
+
+
+def create_connection():
+    return mysql.connector.connect(**DB_CONFIG)
+
+
+def create_table(connection, table_name: str) -> None:
+    cursor = connection.cursor()
+    try:
+        cursor.execute(CREATE_TABLE_TEMPLATE.format(table_name=mysql_identifier(table_name)))
+        connection.commit()
+    finally:
+        cursor.close()
+
+
+def truncate_table(connection, table_name: str) -> None:
+    cursor = connection.cursor()
+    try:
+        cursor.execute(f"TRUNCATE TABLE `{mysql_identifier(table_name)}`")
+        connection.commit()
+    finally:
+        cursor.close()
+
+
+def build_insert_sql(table_name: str) -> str:
+    columns = ", ".join(f"`{column}`" for column in INSERT_COLUMNS)
+    placeholders = ", ".join(["%s"] * len(INSERT_COLUMNS))
+    updates = ", ".join(
+        f"`{column}` = VALUES(`{column}`)"
+        for column in INSERT_COLUMNS
+        if column not in {"category", "source_folder", "word_doc", "row_index"}
+    )
+    return f"""
+    INSERT INTO `{mysql_identifier(table_name)}` ({columns})
+    VALUES ({placeholders})
+    ON DUPLICATE KEY UPDATE {updates}
+    """
+
+
+def insert_records(connection, table_name: str, records: List[Dict], batch_size: int = 500) -> int:
+    if not records:
+        return 0
+
+    insert_sql = build_insert_sql(table_name)
+    cursor = connection.cursor()
+    inserted = 0
+    try:
+        for start in range(0, len(records), batch_size):
+            batch = records[start:start + batch_size]
+            values = [tuple(record.get(column) for column in INSERT_COLUMNS) for record in batch]
+            cursor.executemany(insert_sql, values)
+            connection.commit()
+            inserted += len(batch)
+            print(f"已写入/更新 {inserted}/{len(records)} 条记录")
+    finally:
+        cursor.close()
+    return inserted
+
+
+def print_category_summary(records: List[Dict]) -> None:
+    counts = {category: 0 for category in SELECTED_CATEGORIES}
+    for record in records:
+        counts[record["category"]] = counts.get(record["category"], 0) + 1
+    print("待导入分类统计：")
+    for category in SELECTED_CATEGORIES:
+        print(f"  {category}: {counts.get(category, 0)}")
+    print(f"  total: {len(records)}")
+
+
+def parse_args():
+    parser = argparse.ArgumentParser(description="导入 compressed_group_time_issues.json 到 MySQL")
+    parser.add_argument("--json-file", type=Path, default=DEFAULT_JSON_FILE_PATH, help="JSON 文件路径")
+    parser.add_argument("--table", default=DEFAULT_TABLE_NAME, help="MySQL 表名")
+    parser.add_argument("--truncate", action="store_true", help="导入前清空目标表")
+    parser.add_argument("--dry-run", action="store_true", help="只解析和统计，不连接 MySQL")
+    return parser.parse_args()
+
+
+def main():
+    args = parse_args()
+    data = load_json_data(args.json_file)
+    records = normalize_records_for_import(data)
+    print_category_summary(records)
+
+    if args.dry_run:
+        print("dry-run 模式：未连接 MySQL，未写入数据")
+        return
+
+    connection = None
+    try:
+        connection = create_connection()
+        print("成功连接到 MySQL")
+        create_table(connection, args.table)
+        print(f"已确认目标表：{args.table}")
+        if args.truncate:
+            truncate_table(connection, args.table)
+            print(f"已清空目标表：{args.table}")
+        inserted = insert_records(connection, args.table, records)
+        print(f"导入完成：写入/更新 {inserted} 条记录")
+    except Error as exc:
+        print(f"MySQL 操作失败：{exc}")
+        raise
+    finally:
+        if connection and connection.is_connected():
+            connection.close()
+            print("MySQL 连接已关闭")
+
+
+if __name__ == "__main__":
+    main()

server/pbassociation_detail.py

@@ -0,0 +1,730 @@
+# -*- 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 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]:
+    """解压 zip 文件
+
+    使用 macOS 的 open 命令调用 Archive Utility 解压，
+    先将 zip 文件移动到 extract_dir 里面，然后在 extract_dir 中解压，
+    解压后会生成一个与压缩文件同名的文件夹。
+    不再递归处理解压出来的 zip 文件。
+    """
+    # 使用 open 命令调用 Archive Utility 解压
+    # Archive Utility 会在 zip 文件所在目录生成同名文件夹
+    extract_dir= extract_dir.parent
+    if clear_dir:
+        for item in extract_dir.iterdir():
+            if item.is_file():
+                item.unlink()
+            elif item.is_dir():
+                shutil.rmtree(item)
+
+    # 先将 zip 文件移动到 extract_dir 里面
+    moved_zip_path = extract_dir / zip_path.name
+    shutil.move(str(zip_path), str(moved_zip_path))
+
+    import time
+    os.system(f'open  -W  "{moved_zip_path}"')
+    #time.sleep(0.5)  # 等待 Archive Utility 完成解压
+
+    # 解压后的文件夹名称与 zip 文件名一致（不含扩展名）
+    # 文件夹位于 extract_dir 中（因为 zip 已经移动到这里）
+    extracted_folder = extract_dir / moved_zip_path.stem
+
+    # 递归收集解压文件夹中的所有文件（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
+
+    if extracted_folder.exists():
+        extracted_files = collect_all_files(extracted_folder)
+    else:
+        # 如果文件夹名有差异，查找可能存在的文件夹
+        extracted_files = []
+        for item in extract_dir.iterdir():
+            if item.is_dir() and not item.name.endswith('.app'):
+                extracted_files = collect_all_files(item)
+                break
+
+    # 如果还没有收集到文件，直接收集 extract_dir 中的所有文件（排除 zip 文件本身）
+    if len(extracted_files) == 0:
+        extracted_files = [
+            item for item in extract_dir.iterdir()
+            if item.is_file() and item != moved_zip_path
+        ]
+        if extracted_files:
+            print(f"⚠️  解压完成，未找到解压后的文件夹，但直接从 extract_dir 中收集了 {len(extracted_files)} 个文件。")
+
+    return extracted_files
+
+
+def has_audio_video_files(files_list: List[Dict[str, Union[str, float]]]) -> 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'}
+    for file_entry in files_list:
+        name = file_entry.get('name', '')
+        if any(name.lower().endswith(ext) for ext in audio_video_exts):
+            return True
+    return False
+
+
+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]]]:
+            def format_datetime(mtime: float) -> str:
+                """将时间戳格式化为可读的日期时间字符串"""
+                return datetime.fromtimestamp(mtime).strftime("%Y-%m-%d %H:%M:%S")
+
+            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, "datetime": format_datetime(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, "datetime": format_datetime(mtime)})
+            else:
+                mtime = file_path.stat().st_mtime
+                files.append({"name": file_path.name, "mtime": mtime, "datetime": format_datetime(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
+            ]
+            if not extracted_times:
+                return None
+
+            # 找出压缩文件本身的时间
+            archive_mtime = None
+            for entry in file_entries:
+                if entry.get("name") == archive_name and "mtime" in entry:
+                    archive_mtime = entry["mtime"]
+                    break
+
+            latest_extracted = max(extracted_times)
+
+            # 如果压缩文件时间和解压文件最晚时间差小于 30 秒，返回 None
+            if archive_mtime is not None and abs(latest_extracted - archive_mtime) < 300:
+                return None
+
+            return latest_extracted
+
+        # 初始化条目
+        entry = {}
+        group1_files = []
+        group2_files = []
+        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（时间差超过阈值），则记录到问题列表
+        # 或者如果解压出来的文件中包含音视频文件，也记录到问题列表
+        TIME_DIFF_THRESHOLD = 30  # 时间差阈值（秒），避免将 zip 文件和解压文件时间相近的误判为问题组
+        time_diff_condition = (
+            group1_latest is not None
+            and group2_latest is not None
+            and group1_latest < group2_latest
+            and (group2_latest - group1_latest) > TIME_DIFF_THRESHOLD
+        )
+        if time_diff_condition:
+            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()
+
+
+    # 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
+        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}")
+        print(len(all_problem_groups))
+        return
+
+if __name__ == "__main__":
+    main()

zq/check_xkw_codes.py

@@ -0,0 +1,48 @@
+import json
+import re
+import os
+from pathlib import Path
+
+jsons_dir = Path(__file__).parent / "jsons"
+output_file = Path(__file__).parent / "mismatched_codes.json"
+
+mismatches = []
+
+for json_file in sorted(jsons_dir.glob("*.json")):
+    with open(json_file, encoding="utf-8") as f:
+        data = json.load(f)
+
+    for item in data.get("items", []):
+        url = item.get("url", "")
+        xkw_code = item.get("xkw_code", "")
+
+        if "www.zxxk.com" not in url:
+            continue
+
+        # Extract numeric ID from URL (e.g. /soft/38079968.html or ?id=38079968)
+        match = re.search(r"[\\/](\d+)(?:\.\w+)?(?:\?|$)", url)
+        if not match:
+            match = re.search(r"[?&](?:id|soft)=(\d+)", url)
+
+        if not match:
+            continue
+
+        url_id = match.group(1)
+
+        if str(xkw_code) == "0":
+            continue
+
+        if url_id != str(xkw_code):
+            mismatches.append({
+                "source_file": json_file.name,
+                "filename": item.get("filename", []),
+                "title": item.get("title", ""),
+                "url": url,
+                "url_id": url_id,
+                "xkw_code": xkw_code,
+            })
+
+with open(output_file, "w", encoding="utf-8") as f:
+    json.dump(mismatches, f, ensure_ascii=False, indent=2)
+
+print(f"检查完成：共发现 {len(mismatches)} 条不一致记录，已输出到 {output_file}")

zq/match_all.py

@@ -0,0 +1,145 @@
+#!/usr/bin/env python3
+# 遍历 jsons/ 目录下所有 JSON 文件，按 URL 来源匹配 Excel 暗码：
+#   - url 含 www.21cnjy.com → 在 "21世纪资料名" 列精确匹配 filename[0]
+#   - url 含 www.zxxk.com  → 在 "学科网资料名" 列精确匹配 filename[0]
+#       学科网资料名有重复时，从 item 的 url 中提取数字 ID 与各暗码候选值比对消歧
+#   - 匹配成功写入 xkw_code，未匹配写入 "0"
+#   - 未匹配数据汇总写入 问题数据/未匹配填充0.json
+
+import json       # 用于读写 JSON 文件
+import re         # 用于正则表达式提取 URL 中的数字 ID
+import glob       # 用于批量匹配目录下的文件路径
+import openpyxl   # 用于读取 Excel (.xlsx) 文件
+
+EXCEL_PATH = "结果.xlsx"                      # Excel 数据文件路径
+JSON_DIR = "jsons"                             # JSON 文件所在目录
+UNMATCHED_OUT = "问题数据/未匹配填充0.json"    # 未匹配数据输出路径
+
+
+def clean(v):
+    # 将单元格值转为字符串并去除首尾空格
+    if not v:
+        return ""  # 空值直接返回空字符串
+    s = str(v).strip()  # 转字符串并去首尾空白
+    if s.startswith("'"):
+        s = s[1:]  # 去掉 Excel 强制文本时产生的前导单引号（如以 + 开头的单元格）
+    return s
+
+
+def load_excel_indexes(path):
+    # 读取 Excel 文件，构建两个查找字典
+    # 返回：
+    #   map_21:  {21世纪资料名 → 暗码}
+    #   map_xkw: {学科网资料名 → [暗码, ...]}  （同名可能对应多个暗码，全部保留）
+    wb = openpyxl.load_workbook(path)   # 打开 Excel 文件
+    ws = wb.active                       # 取活动工作表
+    headers = [cell.value for cell in ws[1]]  # 读取第一行作为列名
+    col = {h: i for i, h in enumerate(headers)}  # 构建列名到列索引的映射
+
+    idx_21 = col["21世纪资料名"]   # "21世纪资料名" 列的索引
+    idx_xkw = col["学科网资料名"]  # "学科网资料名" 列的索引
+    idx_code = col["暗码"]         # "暗码" 列的索引
+
+    map_21 = {}   # 21世纪资料名 → 暗码（唯一映射，重复则后者覆盖前者）
+    map_xkw = {}  # 学科网资料名 → [暗码列表]（同名保留全部暗码）
+    for row in ws.iter_rows(min_row=2, values_only=True):  # 从第2行开始逐行读取
+        code = clean(row[idx_code])       # 读取并清洗暗码
+        name_21 = clean(row[idx_21])      # 读取并清洗 21世纪资料名
+        name_xkw = clean(row[idx_xkw])    # 读取并清洗学科网资料名
+        if name_21 and code:
+            map_21[name_21] = code        # 写入 21世纪索引
+        if name_xkw and code:
+            map_xkw.setdefault(name_xkw, []).append(code)  # 追加到学科网索引列表
+
+    return map_21, map_xkw  # 返回两个索引字典
+
+
+def extract_url_id(url):
+    # 从学科网 URL 中提取纯数字资源 ID
+    # 例如 https://www.zxxk.com/soft/38079968.html → '38079968'
+    m = re.search(r'/(\d+)(?:\.\w+)?(?:\?|$)', url)  # 匹配路径最后一段的纯数字
+    return m.group(1) if m else None  # 有匹配则返回数字字符串，否则返回 None
+
+
+def resolve_xkw_code(fn0, url, map_xkw):
+    # 学科网资料名匹配逻辑：
+    #   - 无匹配 → 返回 None
+    #   - 只有一个唯一暗码 → 直接返回
+    #   - 多个不同暗码（同名不同资源）→ 用 URL ID 消歧，找到匹配则返回，否则返回 None
+    codes = map_xkw.get(fn0)  # 查找该文件名对应的暗码列表
+    if not codes:
+        return None  # 在学科网索引中找不到该文件名
+    unique_codes = list(dict.fromkeys(codes))  # 去重并保持原顺序
+    if len(unique_codes) == 1:
+        return unique_codes[0]  # 唯一暗码，直接返回
+    url_id = extract_url_id(url)  # 从 URL 中提取数字 ID
+    if url_id and url_id in codes:
+        return url_id  # URL ID 与某个暗码一致，用该值
+    return None  # 无法消歧，返回 None
+
+
+def process_file(json_path, map_21, map_xkw):
+    # 处理单个 JSON 文件：为每个 item 写入 xkw_code
+    with open(json_path, encoding="utf-8") as f:
+        data = json.load(f)  # 读取 JSON 数据
+
+    matched = 0         # 成功匹配的计数
+    unmatched_items = []  # 未匹配的 item 列表，用于汇总输出
+
+    for item in data.get("items", []):  # 遍历每个资源 item
+        fns = item.get("filename", [])  # 读取 filename 列表
+        if not fns:
+            continue  # filename 为空则跳过该 item
+        fn0 = fns[0].strip()        # 只取第一个 filename 并去空格
+        url = item.get("url", "")   # 读取该 item 的 URL
+
+        code = None  # 初始化暗码为空
+        if "www.21cnjy.com" in url:
+            code = map_21.get(fn0)  # 在 21世纪索引中精确查找
+        elif "www.zxxk.com" in url:
+            code = resolve_xkw_code(fn0, url, map_xkw)  # 在学科网索引中查找（含消歧）
+
+        if code:
+            item["xkw_code"] = code  # 匹配成功，写入暗码
+            matched += 1             # 匹配计数加一
+        else:
+            item["xkw_code"] = "0"   # 未匹配，填充 "0"
+            unmatched_items.append({
+                "source_file": json_path,  # 来源 JSON 文件路径
+                "filename": fn0,           # 未匹配的文件名
+                "url": url,                # 对应的 URL
+            })
+
+    with open(json_path, "w", encoding="utf-8") as f:
+        json.dump(data, f, ensure_ascii=False, indent=2)  # 将修改后的数据写回 JSON 文件
+
+    return matched, unmatched_items  # 返回匹配数和未匹配列表
+
+
+def main():
+    print("加载 Excel 索引...")
+    map_21, map_xkw = load_excel_indexes(EXCEL_PATH)  # 构建 Excel 查找索引
+    print(f"Excel 索引：21世纪 {len(map_21)} 条，学科网 {len(map_xkw)} 个不重复名称\n")
+
+    files = sorted(glob.glob(f"{JSON_DIR}/*.json"))  # 获取所有 JSON 文件路径并排序
+    total_files = len(files)    # JSON 文件总数
+    total_matched = 0           # 全局匹配计数
+    all_unmatched = []          # 全局未匹配列表
+
+    for i, path in enumerate(files, 1):  # 逐个处理每个 JSON 文件
+        matched, unmatched_items = process_file(path, map_21, map_xkw)  # 处理单文件
+        total_matched += matched                     # 累加匹配数
+        all_unmatched.extend(unmatched_items)        # 合并未匹配列表
+        print(f"[{i}/{total_files}] {path}  匹配:{matched}  未匹配:{len(unmatched_items)}")
+
+    with open(UNMATCHED_OUT, "w", encoding="utf-8") as f:
+        json.dump(all_unmatched, f, ensure_ascii=False, indent=2)  # 写出所有未匹配数据
+
+    total_unmatched = len(all_unmatched)  # 全局未匹配总数
+    print(f"\n完成：处理 {total_files} 个文件，写入 xkw_code {total_matched + total_unmatched} 条"
+          f"（匹配:{total_matched}，填0:{total_unmatched}）")
+    print(f"未匹配数据已保存至 {UNMATCHED_OUT}")  # 提示未匹配数据保存路径
+
+
+if __name__ == "__main__":
+    main()  # 脚本直接运行时执行 main 函数

zq/问题数据/match_unmatched.py

@@ -0,0 +1,166 @@
+"""
+读取未匹配填充0.json，对每个json对象：
+1. 取filename去掉后缀名，jieba分词后与结果.xlsx中"学科网资料名"进行分词包含匹配
+2. 从url中提取数字ID，写入url_id字段
+3. 在匹配到的行中，用url_id与"暗码"精准匹配：匹配则xkw_code=暗码值，否则xkw_code=0
+4. xkw_code与url_id一致则"一致性"=1，否则=0
+"""
+
+import json
+import re
+import os
+import jieba
+
+import openpyxl
+
+SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
+INPUT_JSON = os.path.join(SCRIPT_DIR, "未匹配填充0.json")
+EXCEL_PATH = os.path.join(SCRIPT_DIR, "..", "结果.xlsx")
+STILL_UNMATCHED_JSON = os.path.join(SCRIPT_DIR, "未匹配填充0_仍未匹配.json")
+
+# 过滤掉太短或无意义的分词token
+MIN_TOKEN_LEN = 2
+
+
+def strip_ext(name: str) -> str:
+    """去掉文件后缀名"""
+    base, _ = os.path.splitext(name)
+    return base
+
+
+def is_meaningful_token(t: str) -> bool:
+    """token中必须包含至少一个汉字或字母数字字符，否则视为纯标点无意义"""
+    return any(c.isalnum() or '\u4e00' <= c <= '\u9fff' for c in t)
+
+
+def tokenize(text: str) -> list[str]:
+    """使用jieba分词，过滤短词和纯标点/符号"""
+    result = []
+    for t in jieba.cut(text, cut_all=False):
+        t = t.strip()
+        if len(t) >= MIN_TOKEN_LEN and is_meaningful_token(t):
+            result.append(t)
+    return result
+
+
+def extract_url_id(url: str) -> str:
+    """从url中提取数字ID，例如 https://www.zxxk.com/soft/33839713.html -> 33839713"""
+    m = re.search(r'/(\d+)(?:\.\w+)?$', url)
+    if m:
+        return m.group(1)
+    # fallback: 取url中最后一段数字
+    nums = re.findall(r'\d+', url)
+    return nums[-1] if nums else ""
+
+
+def build_excel_index(excel_path: str):
+    """
+    读取Excel，返回：
+    - rows: list of dict，每行包含 学科网资料名(无后缀)、暗码
+    - anma_index: dict[暗码str -> 学科网资料名str]，用于url_id精准查找
+    """
+    wb = openpyxl.load_workbook(excel_path, read_only=True, data_only=True)
+    ws = wb.active
+    headers = [cell.value for cell in next(ws.iter_rows(min_row=1, max_row=1))]
+
+    idx_xkw_name = headers.index("学科网资料名")
+    idx_anma = headers.index("暗码")
+
+    rows = []
+    anma_index = {}  # 暗码 -> 学科网资料名（无后缀），学科网资料名为空时存 ""
+    for row in ws.iter_rows(min_row=2, values_only=True):
+        xkw_name = row[idx_xkw_name]
+        anma = row[idx_anma]
+        anma_str = str(anma) if anma is not None else ""
+
+        # anma_index：只要暗码有值就记录，学科网资料名可以为空
+        if anma_str and anma_str not in anma_index:
+            xkw_name_noext = strip_ext(str(xkw_name)) if xkw_name else ""
+            anma_index[anma_str] = xkw_name_noext
+
+        # rows（用于分词匹配）：学科网资料名为空则跳过
+        if not xkw_name:
+            continue
+        xkw_name_noext = strip_ext(str(xkw_name))
+        rows.append({
+            "xkw_name": xkw_name_noext,
+            "anma": anma_str,
+        })
+    wb.close()
+    return rows, anma_index
+
+
+def tokens_match(tokens: list[str], target: str) -> bool:
+    """判断target是否包含所有token"""
+    return all(t in target for t in tokens)
+
+
+def process(input_json: str, excel_path: str, still_unmatched_json: str):
+    print("加载Excel...")
+    excel_rows, anma_index = build_excel_index(excel_path)
+    print(f"Excel共 {len(excel_rows)} 行数据")
+
+    print("加载JSON...")
+    with open(input_json, "r", encoding="utf-8") as f:
+        data = json.load(f)
+    print(f"JSON共 {len(data)} 条记录")
+
+    for i, obj in enumerate(data):
+        filename = obj.get("filename", "")
+        url = obj.get("url", "")
+
+        # 1. 去掉后缀名并分词
+        name_noext = strip_ext(filename)
+        tokens = tokenize(name_noext)
+
+        # 2. 提取url_id
+        url_id = extract_url_id(url)
+        obj["url_id"] = url_id
+
+        # 3. 分词包含匹配，找出所有匹配行
+        matched_rows = [r for r in excel_rows if tokens_match(tokens, r["xkw_name"])]
+
+        # 4. 在匹配行中用url_id与暗码精准匹配
+        xkw_code = "0"
+        if matched_rows:
+            exact = [r for r in matched_rows if r["anma"] == url_id]
+            if exact:
+                xkw_code = exact[0]["anma"]
+
+        obj["xkw_code"] = xkw_code
+        obj.pop("一致性", None)  # 清除旧字段
+
+        # 5. xkw_code不为0但与url_id不一致
+        obj["xwk_code不为0但xkw_code与url_id不一致"] = 1 if xkw_code != "0" and xkw_code != url_id else 0
+
+        # 6. 用url_id去暗码字段精准查找
+        xkw_name_by_id = anma_index.get(url_id)
+        obj["xlsx中的暗码"] = url_id if xkw_name_by_id is not None else "0"
+        obj["学科网资料名"] = xkw_name_by_id if xkw_name_by_id is not None else ""
+
+        # 7. xlsx中的暗码有值但学科网资料名为空
+        xlsx_anma = obj["xlsx中的暗码"]
+        xkw_name_val = obj["学科网资料名"]
+        obj["xlsx中的暗码有值学科网资料名为空"] = 1 if xlsx_anma != "0" and not xkw_name_val else 0
+
+        if (i + 1) % 100 == 0:
+            print(f"  已处理 {i+1}/{len(data)}")
+
+    # 直接写回原文件
+    print(f"写回原文件 {input_json}")
+    with open(input_json, "w", encoding="utf-8") as f:
+        json.dump(data, f, ensure_ascii=False, indent=2)
+
+    # xkw_code为0的输出到新文件
+    still_unmatched = [obj for obj in data if obj["xkw_code"] == "0"]
+    print(f"写出仍未匹配记录到 {still_unmatched_json}")
+    with open(still_unmatched_json, "w", encoding="utf-8") as f:
+        json.dump(still_unmatched, f, ensure_ascii=False, indent=2)
+
+    matched_count = sum(1 for obj in data if obj["xkw_code"] != "0")
+    inconsistent_count = sum(1 for obj in data if obj["xwk_code不为0但xkw_code与url_id不一致"] == 1)
+    print(f"完成：共{len(data)}条，xkw_code非0共{matched_count}条，其中与url_id不一致{inconsistent_count}条，仍未匹配{len(still_unmatched)}条")
+
+
+if __name__ == "__main__":
+    process(INPUT_JSON, EXCEL_PATH, STILL_UNMATCHED_JSON)