添加分类管理导出导入功能

modules/routes/api_categories.py

@@ -2,10 +2,11 @@
 分类管理 API
 """
 import uuid
+import json
 from datetime import datetime
-from flask import Blueprint, request, jsonify
-from config import CATEGORIES_FILE
-from utils import load_data, save_data
+from flask import Blueprint, request, jsonify, Response
+from config import CATEGORIES_FILE, DATA_DIR
+from utils import load_data, save_data, load_config
 
 cat_bp = Blueprint('api_categories', __name__)
 
@@ -70,3 +71,271 @@ def api_toggle_category_visible(category_id):
     category['visible'] = not category.get('visible', True)
     save_data(CATEGORIES_FILE, categories)
     return jsonify({'success': True, 'visible': category['visible']})
+
+
+# ─── 导出分类相关数据 ───────────────────────────────────────────────────────
+
+@cat_bp.route('/api/categories/export', methods=['GET'])
+def api_export_categories():
+    """导出所有分类及其相关数据（子类别、参数字段、关联数据项）"""
+    try:
+        # 获取所有分类
+        categories = load_data(CATEGORIES_FILE)
+        
+        # 获取各类别下的数据
+        export_data = {
+            'categories': categories,
+            'export_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),
+            'version': '1.0'
+        }
+        
+        # 加载各类别数据文件
+        # 内置分类：AI模型、GPU、CPU
+        models_file = DATA_DIR / 'models.json'
+        gpus_file = DATA_DIR / 'gpus.json'
+        cpus_file = DATA_DIR / 'cpus.json'
+        
+        if models_file.exists():
+            export_data['models'] = load_data(models_file)
+        if gpus_file.exists():
+            export_data['gpus'] = load_data(gpus_file)
+        if cpus_file.exists():
+            export_data['cpus'] = load_data(cpus_file)
+        
+        # 动态分类数据（每个自定义分类有独立的数据文件）
+        for cat in categories:
+            cat_id = cat['id']
+            # 排除内置分类
+            if cat_id in ['ai-models', 'gpus', 'cpus']:
+                continue
+            # 查找该分类的数据文件
+            cat_data_file = DATA_DIR / f'{cat_id}.json'
+            if cat_data_file.exists():
+                export_data[cat_id] = load_data(cat_data_file)
+        
+        # 导出为 JSON 文件
+        json_str = json.dumps(export_data, ensure_ascii=False, indent=2)
+        
+        response = Response(
+            json_str,
+            mimetype='application/json',
+            headers={
+                'Content-Disposition': f'attachment; filename=param-hub-categories-export-{datetime.now().strftime("%Y%m%d%H%M%S")}.json'
+            }
+        )
+        return response
+    except Exception as e:
+        return jsonify({'error': str(e)}), 500
+
+
+@cat_bp.route('/api/categories/export/<category_id>', methods=['GET'])
+def api_export_single_category(category_id):
+    """导出单个分类及其相关数据"""
+    try:
+        categories = load_data(CATEGORIES_FILE)
+        category = next((c for c in categories if c['id'] == category_id), None)
+        if not category:
+            return jsonify({'error': 'Category not found'}), 404
+        
+        export_data = {
+            'category': category,
+            'export_time': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),
+            'version': '1.0'
+        }
+        
+        # 加载该分类的数据
+        if category_id == 'ai-models':
+            models_file = DATA_DIR / 'models.json'
+            if models_file.exists():
+                export_data['items'] = load_data(models_file)
+        elif category_id == 'gpus':
+            gpus_file = DATA_DIR / 'gpus.json'
+            if gpus_file.exists():
+                export_data['items'] = load_data(gpus_file)
+        elif category_id == 'cpus':
+            cpus_file = DATA_DIR / 'cpus.json'
+            if cpus_file.exists():
+                export_data['items'] = load_data(cpus_file)
+        else:
+            # 动态分类
+            cat_data_file = DATA_DIR / f'{category_id}.json'
+            if cat_data_file.exists():
+                export_data['items'] = load_data(cat_data_file)
+        
+        json_str = json.dumps(export_data, ensure_ascii=False, indent=2)
+        
+        response = Response(
+            json_str,
+            mimetype='application/json',
+            headers={
+                'Content-Disposition': f'attachment; filename={category_id}-export-{datetime.now().strftime("%Y%m%d%H%M%S")}.json'
+            }
+        )
+        return response
+    except Exception as e:
+        return jsonify({'error': str(e)}), 500
+
+
+# ─── 导入分类相关数据 ───────────────────────────────────────────────────────
+
+@cat_bp.route('/api/categories/import', methods=['POST'])
+def api_import_categories():
+    """导入分类及其相关数据"""
+    try:
+        import_data = request.get_json()
+        
+        if not import_data:
+            return jsonify({'error': '无导入数据'}), 400
+        
+        # 验证数据结构
+        if 'categories' not in import_data:
+            return jsonify({'error': '缺少 categories 字段'}), 400
+        
+        # 导入模式：merge（合并）或 replace（替换）
+        mode = request.args.get('mode', 'merge')
+        
+        result = {
+            'success': True,
+            'imported_categories': 0,
+            'imported_items': 0,
+            'skipped': [],
+            'updated': []
+        }
+        
+        # 处理分类
+        existing_categories = load_data(CATEGORIES_FILE)
+        imported_categories = import_data['categories']
+        
+        for cat in imported_categories:
+            existing = next((c for c in existing_categories if c['id'] == cat['id']), None)
+            if existing:
+                if mode == 'replace':
+                    # 替换模式：更新现有分类
+                    existing.update(cat)
+                    result['updated'].append(cat['id'])
+                else:
+                    # 合并模式：跳过已存在的分类
+                    result['skipped'].append(cat['id'])
+            else:
+                # 新分类：添加
+                existing_categories.append(cat)
+                result['imported_categories'] += 1
+        
+        save_data(CATEGORIES_FILE, existing_categories)
+        
+        # 导入各类别数据
+        data_mappings = {
+            'models': 'models.json',
+            'gpus': 'gpus.json',
+            'cpus': 'cpus.json'
+        }
+        
+        for key, filename in data_mappings.items():
+            if key in import_data:
+                data_file = DATA_DIR / filename
+                existing_items = load_data(data_file) if data_file.exists() else []
+                imported_items = import_data[key]
+                
+                for item in imported_items:
+                    existing = next((i for i in existing_items if i['id'] == item['id']), None)
+                    if existing:
+                        if mode == 'replace':
+                            existing.update(item)
+                        else:
+                            continue  # 合并模式跳过
+                    else:
+                        existing_items.append(item)
+                        result['imported_items'] += 1
+                
+                save_data(data_file, existing_items)
+        
+        # 导入动态分类数据
+        for cat in imported_categories:
+            cat_id = cat['id']
+            if cat_id in ['ai-models', 'gpus', 'cpus']:
+                continue
+            if cat_id in import_data:
+                data_file = DATA_DIR / f'{cat_id}.json'
+                existing_items = load_data(data_file) if data_file.exists() else []
+                imported_items = import_data[cat_id]
+                
+                for item in imported_items:
+                    existing = next((i for i in existing_items if i['id'] == item['id']), None)
+                    if existing:
+                        if mode == 'replace':
+                            existing.update(item)
+                        else:
+                            continue
+                    else:
+                        existing_items.append(item)
+                        result['imported_items'] += 1
+                
+                save_data(data_file, existing_items)
+        
+        return jsonify(result)
+    except Exception as e:
+        return jsonify({'error': str(e)}), 500
+
+
+@cat_bp.route('/api/categories/import/<category_id>', methods=['POST'])
+def api_import_single_category(category_id):
+    """导入单个分类数据"""
+    try:
+        import_data = request.get_json()
+        
+        if not import_data:
+            return jsonify({'error': '无导入数据'}), 400
+        
+        if 'category' not in import_data:
+            return jsonify({'error': '缺少 category 字段'}), 400
+        
+        mode = request.args.get('mode', 'merge')
+        
+        result = {
+            'success': True,
+            'imported_items': 0,
+            'updated_items': 0
+        }
+        
+        # 处理分类
+        categories = load_data(CATEGORIES_FILE)
+        imported_cat = import_data['category']
+        
+        existing = next((c for c in categories if c['id'] == category_id), None)
+        if existing:
+            if mode == 'replace':
+                existing.update(imported_cat)
+        else:
+            categories.append(imported_cat)
+        
+        save_data(CATEGORIES_FILE, categories)
+        
+        # 处理数据项
+        if 'items' in import_data:
+            if category_id == 'ai-models':
+                data_file = DATA_DIR / 'models.json'
+            elif category_id == 'gpus':
+                data_file = DATA_DIR / 'gpus.json'
+            elif category_id == 'cpus':
+                data_file = DATA_DIR / 'cpus.json'
+            else:
+                data_file = DATA_DIR / f'{category_id}.json'
+            
+            existing_items = load_data(data_file) if data_file.exists() else []
+            imported_items = import_data['items']
+            
+            for item in imported_items:
+                existing = next((i for i in existing_items if i['id'] == item['id']), None)
+                if existing:
+                    if mode == 'replace':
+                        existing.update(item)
+                        result['updated_items'] += 1
+                else:
+                    existing_items.append(item)
+                    result['imported_items'] += 1
+            
+            save_data(data_file, existing_items)
+        
+        return jsonify(result)
+    except Exception as e:
+        return jsonify({'error': str(e)}), 500