chore: release v1.3.0 - 京东账单支持

This commit is contained in:
CHE LIANG ZHAO
2026-01-26 15:36:05 +08:00
parent b654265d96
commit f537b53ebd
5 changed files with 192 additions and 1 deletions

View File

@@ -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

View File

@@ -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]}")

116
analyzer/test_jd_cleaner.py Normal file
View File

@@ -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()

View File

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