chore: release v1.3.0 - 京东账单支持

CHANGELOG.md

@@ -5,6 +5,41 @@
 格式基于 [Keep a Changelog](https://keepachangelog.com/zh-CN/1.0.0/)，
 版本号遵循 [语义化版本](https://semver.org/lang/zh-CN/)。
 
+## [1.3.0] - 2026-01-26
+
+### 新增
+- **京东账单支持** - 支持京东白条账单上传和清洗
+  - 自动识别京东账单类型（交易流水 ZIP）
+  - 解析京东白条账单 CSV 格式（含还款日期信息）
+  - 京东专属分类映射配置（`config/category_jd.yaml`）
+  - 支持京东外卖、京东平台商户等商户识别
+  - 上传页面和账单列表页面添加"京东"选项
+  - 账单来源 Badge 添加紫色京东标识
+
+### 优化
+- **京东订单智能去重** - 上传京东账单时自动软删除其他来源中的京东订单
+  - 识别描述中包含"京东-订单编号"的支付宝/微信账单
+  - 软删除冲突记录，避免重复计入支出
+  - 上传响应返回被删除的记录数
+- **分类推断复核等级优化** - 京东账单引入 LOW 复核等级
+  - 商户映射成功（如"京东外卖"）：无需复核
+  - 原分类映射成功（如"食品酒饮"→餐饮美食）：无需复核
+  - 通用关键词匹配成功：**LOW 复核**（需确认推断准确性）
+  - 未知分类或匹配失败：HIGH 复核
+- **京东平台商户关键词扩展** - 在通用分类配置中添加京东平台常见关键词
+  - 宠物用品：小佩、米家宠物、猫砂、猫粮等
+  - 数码电器：小米、延长保修、家电等
+
+### 技术改进
+- 新增 `analyzer/cleaners/jd.py` 京东账单清理器
+- 新增 `analyzer/config/category_jd.yaml` 京东专属配置
+- 后端新增 `SoftDeleteJDRelatedBills()` 接口和实现
+- 前端 API 类型添加 `'jd'` 支持
+- 新增单元测试 `analyzer/test_jd_cleaner.py`（11 个测试用例）
+
+### 文档
+- 更新 `TODO.md` 添加 Gitea Webhook 自动部署计划
+
 ## [1.2.0] - 2026-01-25
 
 ### 新增

analyzer/analyze_jd_bills.py

@@ -0,0 +1,40 @@
+"""分析京东账单数据"""
+import json
+import sys
+
+sys.stdout.reconfigure(encoding='utf-8')
+
+with open('../jd_bills.json', 'r', encoding='utf-8') as f:
+    d = json.load(f)
+
+bills = [b for b in d['data']['bills'] if b['bill_type'] == 'jd']
+print(f'Total JD bills: {len(bills)}')
+print()
+
+# Review level distribution
+review_levels = {}
+for b in bills:
+    lvl = b['review_level'] or 'NONE'
+    review_levels[lvl] = review_levels.get(lvl, 0) + 1
+print('Review level distribution:')
+for lvl, cnt in sorted(review_levels.items()):
+    print(f'  {lvl}: {cnt}')
+print()
+
+# Category distribution
+categories = {}
+for b in bills:
+    cat = b['category']
+    categories[cat] = categories.get(cat, 0) + 1
+print('Category distribution:')
+for cat, cnt in sorted(categories.items(), key=lambda x: -x[1]):
+    print(f'  {cat}: {cnt}')
+print()
+
+# Show bills that need review
+print('Bills needing review:')
+print(f"{'Level':<5} | {'Category':<12} | {'Merchant':<20} | Description")
+print('-' * 70)
+for b in bills:
+    if b['review_level']:
+        print(f"{b['review_level']:<5} | {b['category']:<12} | {b['merchant'][:20]:<20} | {b['description'][:30]}")

analyzer/test_jd_cleaner.py

@@ -0,0 +1,116 @@
+"""
+测试京东账单清洗器
+"""
+import zipfile
+import tempfile
+import os
+import csv
+import sys
+
+# 确保输出使用 UTF-8
+sys.stdout.reconfigure(encoding='utf-8')
+
+def test_jd_cleaner():
+    zip_path = r'D:\Projects\BillAI\mock_data\京东交易流水(申请时间2026年01月26日13时29分47秒)(密码683263)_209.zip'
+    
+    with zipfile.ZipFile(zip_path, 'r') as zf:
+        with tempfile.TemporaryDirectory() as tmpdir:
+            zf.extractall(tmpdir, pwd=b'683263')
+            
+            # Find CSV file
+            for f in os.listdir(tmpdir):
+                if f.endswith('.csv'):
+                    input_file = os.path.join(tmpdir, f)
+                    output_file = os.path.join(tmpdir, 'output.csv')
+                    
+                    print(f"Input file: {f}")
+                    print("-" * 60)
+                    
+                    # Run cleaner
+                    from cleaners.jd import JDCleaner
+                    cleaner = JDCleaner(input_file, output_file)
+                    cleaner.clean()
+                    
+                    # Read output and show review levels
+                    print("\n" + "=" * 60)
+                    print("OUTPUT REVIEW LEVELS")
+                    print("=" * 60)
+                    
+                    with open(output_file, 'r', encoding='utf-8') as of:
+                        reader = csv.reader(of)
+                        header = next(reader)
+                        review_idx = header.index('复核等级') if '复核等级' in header else -1
+                        cat_idx = header.index('交易分类') if '交易分类' in header else -1
+                        merchant_idx = header.index('交易对方') if '交易对方' in header else -1
+                        desc_idx = header.index('商品说明') if '商品说明' in header else -1
+                        
+                        stats = {'': 0, 'LOW': 0, 'HIGH': 0}
+                        rows_needing_review = []
+                        
+                        for row in reader:
+                            review = row[review_idx] if review_idx >= 0 else ''
+                            stats[review] = stats.get(review, 0) + 1
+                            if review:  # Collect rows that need review
+                                cat = row[cat_idx] if cat_idx >= 0 else ''
+                                merchant = row[merchant_idx][:20] if merchant_idx >= 0 else ''
+                                desc = row[desc_idx][:25] if desc_idx >= 0 else ''
+                                rows_needing_review.append((review, cat, merchant, desc))
+                        
+                        # Print rows needing review
+                        print(f"{'Level':<5} | {'Category':<12} | {'Merchant':<20} | Description")
+                        print("-" * 70)
+                        for review, cat, merchant, desc in rows_needing_review:
+                            print(f"{review:<5} | {cat:<12} | {merchant:<20} | {desc}")
+                        
+                        print("\n" + "=" * 60)
+                        print("STATISTICS")
+                        print("=" * 60)
+                        print(f"No review (confident): {stats['']}")
+                        print(f"LOW (keyword match):   {stats['LOW']}")
+                        print(f"HIGH (needs manual):   {stats['HIGH']}")
+                        print(f"Total:                 {sum(stats.values())}")
+
+
+def test_infer_jd_category():
+    """测试分类推断逻辑"""
+    from cleaners.jd import infer_jd_category
+    
+    print("\n" + "=" * 60)
+    print("INFER_JD_CATEGORY TESTS")
+    print("=" * 60)
+    
+    tests = [
+        # (商户, 商品, 原分类, 预期等级, 说明)
+        ('京东外卖', '火鸡面', '', 0, '商户映射'),
+        ('京东平台商户', 'xxx', '食品酒饮', 0, '原分类映射'),
+        ('京东平台商户', 'xxx', '数码电器', 0, '原分类映射'),
+        ('京东平台商户', 'xxx', '日用百货', 0, '原分类映射'),
+        ('京东平台商户', 'xxx', '图书文娱', 0, '原分类映射'),
+        ('京东平台商户', '猫粮', '其他', 1, '空映射+关键词成功'),
+        ('京东平台商户', '咖啡', '其他网购', 1, '空映射+关键词成功'),
+        ('京东平台商户', 'xxx', '其他', 2, '空映射+关键词失败'),
+        ('京东平台商户', 'xxx', '家居用品', 2, '未知分类'),
+        ('京东平台商户', 'xxx', '母婴', 2, '未知分类'),
+        ('京东平台商户', 'xxx', '', 2, '无原分类+关键词失败'),
+    ]
+    
+    level_map = {0: 'NONE', 1: 'LOW', 2: 'HIGH'}
+    
+    print(f"{'Merchant':<15} | {'Product':<8} | {'OrigCat':<10} | {'Result':<12} | {'Level':<5} | {'Expected':<5} | Note")
+    print("-" * 90)
+    
+    all_pass = True
+    for merchant, product, orig_cat, expected_level, note in tests:
+        cat, certain, level = infer_jd_category(merchant, product, orig_cat)
+        status = "✓" if level == expected_level else "✗"
+        if level != expected_level:
+            all_pass = False
+        print(f"{merchant:<15} | {product:<8} | {orig_cat or '(empty)':<10} | {cat:<12} | {level_map[level]:<5} | {level_map[expected_level]:<5} | {note} {status}")
+    
+    print("\n" + ("All tests passed!" if all_pass else "Some tests FAILED!"))
+
+
+if __name__ == '__main__':
+    test_infer_jd_category()
+    print("\n")
+    test_jd_cleaner()

web/package.json

@@ -1,7 +1,7 @@
 {
 	"name": "web",
 	"private": true,
-	"version": "1.2.1",
+	"version": "1.3.0",
 	"type": "module",
 	"scripts": {
 		"dev": "vite dev",