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Author SHA1 Message Date
houhuan 10ebe9240b docs: 添加系统架构文档
添加 SYSTEM_ARCHITECTURE.md 文档,详细说明 OCR 订单处理系统的整体架构、业务流程图、技术栈、数据模型、部署方案及安全策略。文档包含 Mermaid 图表,用于可视化系统组件交互和数据处理流程,为项目维护和团队协作提供技术参考。
2026-03-31 09:27:00 +08:00
houhuan 96cdb0f62e chore: 清理用户设置中的近期文件列表并更新日志文件
移除不再相关的近期文件记录,保持列表简洁。同时更新日志文件以包含最新的处理记录。
2026-03-31 09:20:04 +08:00
houhuan 76859fd774 feat(ui): simplify interface by removing dedicated tobacco/rongcheng buttons and optimizing auto-routing 2026-03-31 09:17:26 +08:00
houhuan c06e3e55f9 docs: 更新指南和API以反映智能文件识别功能
更新 OPENCLAW_GUIDE.md 文档,强调新的全自动智能模式,简化用户操作说明。
同时修改 headless_api.py 的默认处理逻辑,使其能自动识别输入文件类型(图片或Excel)并路由到相应处理流程,提升用户体验。
2026-03-30 15:40:19 +08:00
houhuan 32d41244e5 feat: 实现智能订单识别与自动预处理路由
- 新增智能识别功能,自动检测蓉城易购、烟草公司、杨碧月订单特征
- 修改订单服务流程,在Excel处理前自动执行专用预处理
- 更新无界面API,支持智能识别模式,简化OpenClaw集成
- 完善供应商专用预处理逻辑,修复数量计算和单位换算问题
- 添加变更日志和最终更新报告文档,记录v2.1版本变更
2026-03-30 15:36:27 +08:00
houhuan ba8520a351 fix: update special supplier identification keywords for tobacco and rongcheng 2026-03-30 13:42:39 +08:00
houhuan 26835e265a refactor: unify special suppliers processing into a single intelligent flow 2026-03-30 13:38:05 +08:00
houhuan 708402c7fb feat(订单处理): 添加杨碧月订单预处理功能
在特殊供应商服务中添加 process_yang_biyue 方法,用于处理经手人为"杨碧月"的订单。该方法能够自动识别相关列并进行数据清洗,生成标准格式的预处理文件。

同时优化订单服务的处理流程,在 process_excel 方法中集成特殊供应商预处理检查,通过 _check_special_preprocess 方法识别杨碧月订单并执行列映射转换,确保数据能够被后续标准流程正确处理。
2026-03-30 13:34:30 +08:00
houhuan b7bce93995 refactor: 重构文件读取和日志处理以提升性能和稳定性
- 新增 smart_read_excel 工具函数,统一 Excel 读取逻辑并自动选择引擎
- 重构 ConfigManager.get_path 方法,使用 pathlib 提升路径处理可靠性
- 将 GUI 日志处理改为异步队列模式,避免 UI 阻塞
- 优化 ExcelProcessor 的表头识别逻辑,避免重复读取文件
- 更新配置文件中的版本号
2026-03-30 11:17:25 +08:00
houhuan bfccdd3a37 feat(excel): 过滤非采购行并改进单位处理
- 在ExcelProcessor中增加备注列检查,过滤包含"换货"、"退货"等关键字的非采购行
- 改进单位处理器的匹配逻辑,支持"件、"、"箱装"等变体格式
- 修复config.ini文件末尾缺少换行符的问题
2026-03-30 10:24:18 +08:00
houhuan 3e2f46d26d docs(openclaw): 更新对接指南并重构蓉城易购处理逻辑
- 将蓉城易购处理逻辑从启动器迁移至专用服务类,提升代码模块化
- 更新 OpenClaw 指南,详细说明新增的多种处理模式(Excel、特殊供应商、条码映射)
- 统一 headless_api 入口,通过参数化支持不同处理流程
2026-03-30 10:15:01 +08:00
houhuan 83405a9b8e feat: update barcode mappings and improve build script robustness 2026-03-25 20:49:24 +08:00
houhuan 76f7adddd5 docs: add OpenClaw integration guide 2026-03-25 20:35:09 +08:00
houhuan cd1adc5647 feat: simplify UI and cleanup code (removed support types, mapping wizard, supplier manager, and validation matching) 2026-03-25 19:49:47 +08:00
houhuan fb12e63c4c feat(供应商管理): 新增规则引擎与词典配置支持
refactor(处理器): 重构通用供应商处理器以支持规则引擎
docs: 更新README与文档说明供应商管理功能
build: 更新打包脚本注入版本信息
test: 添加规则引擎单元测试
2025-12-12 13:46:00 +08:00
houhuan 73d17836d7 新版本 2025-11-15 18:46:03 +08:00
houhuan 9f97ac3f21 新系统 2025-08-17 15:52:49 +08:00
houhuan 3414df5317 在更新一版,更方便了 2025-08-17 15:50:21 +08:00
houhuan 556f8d8020 修复条码验证问题:在验证阶段处理过长条码,移除末尾多余的0,确保条码不会超过标准长度 2025-05-30 12:38:25 +08:00
houhuan 53e907411d 修复条码处理问题:修改format_barcode函数,移除末尾多余的0,确保条码不会超过标准长度 2025-05-30 12:14:53 +08:00
houhuan c9afe413f5 修复条码处理和数量计算问题:修复条码格式化函数,确保在数量为空时能正确计算 2025-05-30 12:08:06 +08:00
houhuan 5cf3eeed0f 添加数量为空时通过金额和单价计算数量的功能,增强规格解析能力 2025-05-30 11:54:08 +08:00
houhuan ae8d479acd bug修复 2025-05-30 10:25:46 +08:00
houhuan b3c175836a v1.1.0: 版本更新 - 增强规格解析能力、修复条码映射功能、改进特殊条码处理 2025-05-30 10:24:30 +08:00
houhuan c0fceea9dc zuihou 2025-05-13 10:02:29 +08:00
houhuan 772902c919 完整了,基本最后一次提交 2025-05-10 17:41:11 +08:00
houhuan c3a0e29b19 优化 2025-05-10 14:28:50 +08:00
houhuan 9b2007a995 小更新,但是是比较完善的版本,加油 2025-05-10 13:05:02 +08:00
houhuan 4a8169ff63 ## v1.5.3 (2024-03-21)
- 优化了完整流程处理逻辑:
  - 修改了OCR处理逻辑,当遇到已处理的图片时自动跳过并继续执行
  - 改进了错误处理,避免因图片已处理而中断流程
  - 优化了日志提示信息,提供更清晰的处理状态反馈
- 改进了OCRService的process_image方法:
  - 添加了文件存在性检查
  - 添加了文件类型验证
  - 添加了已处理文件检查
  - 优化了错误处理和日志记录
2025-05-10 12:58:28 +08:00
houhuan 201aac35e6 新增快捷键,新增日志统计 2025-05-10 12:32:10 +08:00
houhuan f5eda6cbd8 新增牛奶箱-瓶的映射 2025-05-10 12:13:04 +08:00
houhuan 5c0b709528 新增条码映射编辑功能图形化界面 2025-05-10 11:39:11 +08:00
houhuan 7b7d491663 更新之后,我也不知道有没有问题 2025-05-08 21:16:58 +08:00
houhuan 390eeb67af 新增逻辑条码映射,把件的商品拆分成单个 2025-05-07 22:30:41 +08:00
houhuan 4c8def4b04 更新readme 2025-05-07 19:29:02 +08:00
houhuan 2f088c87ca 更新修复规格逻辑 2025-05-07 19:16:33 +08:00
houhuan b9739b5267 修复一些问题 2025-05-05 19:38:51 +08:00
houhuan 0b40caaf91 最新提交,提交钱看看有没有优化的地方 2025-05-02 22:46:04 +08:00
houhuan 693c17283b 更新了README文件,添加了版本信息和更新日志 2025-05-02 19:58:27 +08:00
houhuan 71ca90ba6e v1.0正式版 2025-05-02 19:05:42 +08:00
houhuan 14eeb7b39a 日志同步到控制台显示,处理逻辑增强 2025-05-02 18:52:39 +08:00
houhuan b3cecda175 excel 2025-05-02 18:17:24 +08:00
houhuan 131fff6a7d ai说excel部分没问题了,暂且信一次,提交文件 2025-05-02 17:55:29 +08:00
houhuan 0035cd1893 增强版v2-初始化仓库,验证好了ocr部分,先备份一次 2025-05-02 17:25:47 +08:00
146 changed files with 64954 additions and 18947 deletions
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.venv/
__pycache__/
*.pyc
.git/
.gitignore
.claude/
.playwright-mcp/
.trae/
node_modules/
web/frontend/node_modules/
data/
docs/
tests/
*.md
!README.md
release/
dist/
build/
*.spec
*.exe
-3
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# 百度 OCR API 配置
BAIDU_API_KEY=your_api_key_here
BAIDU_SECRET_KEY=your_secret_key_here
+3 -22
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@@ -1,6 +1,3 @@
# Environment
.env
# Python
__pycache__/
*.pyc
@@ -18,25 +15,9 @@ release/
logs/
data/temp/
# Runtime data (all runtime outputs, caches, databases)
data/
# Claude Code / IDE
.claude/
.playwright-mcp/
.trae/
# Old project
wework_xiaoai_bot/
# Node.js
node_modules/
# Frontend build output
web/backend/static/
# Screenshots (from testing)
*.png
# Runtime outputs
data/output/
data/result/
# OS/IDE
.DS_Store
@@ -0,0 +1,43 @@
## 问题与目标
- 弹窗尺寸偏小,不便操作
- 弹窗及文件选择后没有在最上层,易被其他窗口遮挡
- 字段英文名不直观,需要显示中文对应(银豹模板列)
## 改进方案
### 1. 弹窗尺寸与置顶行为
- 将列映射向导窗口尺寸调整为 `780x660`,保持自适应(子控件 `fill=tk.BOTH, expand=True`
- 打开向导时:`dlg.lift()``dlg.attributes('-topmost', True)``after_idle` 取消置顶但保持焦点;`dlg.transient(root)``dlg.grab_set()` 防止被遮挡
- 选择文件后的回调中再次 `dlg.lift()` 和短暂置顶,确保返回后窗口在最上层
- 同步为模板管理窗口应用同样策略
### 2. 字段标签中文提示
- 列映射向导的标准字段改为按 `ColumnMapper.STANDARD_COLUMNS` 动态生成(若可用),并为每个字段追加中文说明,例如:
- `barcode(条码)`
- `name(商品名称)`
- `specification(规格)`
- `quantity(数量)`
- `unit(单位)`
- `unit_price(采购单价)`
- `total_price(金额/小计)`
- `category(类别)`
- `brand(品牌)`
- `supplier(供应商)`
-`ColumnMapper` 不可用,则用内置 `friendly_labels` 字典生成上述标签
### 3. 布局优化与可用性
- 保持“文件路径 + 浏览 + 预览前30行 + 加载列”四项同一行,按钮设 `padx=6`,保证易点
- 映射区使用 `ttk.Combobox(state='readonly')`,宽度适配,并确保行高足够(留白)
- 预览区保留顶部表格(前30行),支持点击行自动填充表头行号;加载列时按指定行读取
### 4. 代码改动位置
- `启动器.py`
- `open_column_mapping_wizard_alt`:调整几何尺寸与置顶;在“浏览”回调与预览/加载流程中补充 `lift/topmost`;扩展标准字段与中文标签
- `open_template_manager`:统一尺寸与置顶行为
- 仅UI与行为改动,不影响处理逻辑;保存仍写入 `suppliers_config.json``header_row``column_mapping`
### 5. 验证
- 打开列映射向导:窗口足够大,居中且在最上层;选择文件后窗口仍在最上层
- 字段标签显示为英+中:如 `name(商品名称)`
- 预览前30行与加载列同一行;点击预览行自动写入表头行号;保存后提示成功并写入配置
请确认以上方案,确认后我将立即实施并验证。
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## 目标
- 在系统设置中提供“供应商管理”GUI,支持新增/编辑/删除供应商,无需手改代码或JSON。
- 一站式配置:基本信息、表头与列映射、规则与词典、模板管理,保存后即时生效。
## 界面设计
- 入口:右侧“系统设置”新增按钮“供应商管理”。
- 布局:
- 左栏:供应商列表(名称),支持搜索/新建/复制/删除。
- 右侧Tab
1) 基本信息:`name``description``filename_patterns``content_indicators``header_row`
2) 列映射与表头:嵌入现有“列映射向导”核心(预览前30行、表头选行、加载列、智能映射、导入/导出)
3) 规则与词典:词典编辑(忽略词、单位同义词、包装倍数、名称正则、默认单位/包装);规则预设与规则预览(原始→规范化)
4) 模板管理:`output_templates` 列表、当前选择与批量校验
- 操作按钮:保存(写入`suppliers_config.json`)、重载处理器、导入/导出供应商配置(单个或全部)。
## 数据流与验证
- 加载/保存:统一读写`config/suppliers_config.json`;保存后调用`ProcessorService.reload_processors()`
- 校验:复用`ProcessorService._validate_suppliers_config`;保存前进行schema校验,错误弹窗聚合列表。
- 预设:提供“基础拆分与推断”规则预设;可导入/导出自定义规则。
## 增强逻辑(自动化建议)
- 新建供应商时,可选择样例Excel:
- 自动检测表头与初始列映射;基于列名关键词给出映射建议。
- 词典预填:常见单位同义词、默认单位“瓶”、常见包装倍数(件/箱/提/盒)。
## 实施步骤
1) 创建`open_supplier_manager`弹窗(系统设置入口),左列表+右侧Tab结构。
2) 基本信息Tab:表单与校验;保存更新到JSON。
3) 列映射与表头Tab:复用现有向导组件(预览/加载/智能映射/导入/导出)。
4) 规则与词典Tab:编辑词典与规则预览,保存写入`dictionary``rules`
5) 模板管理Tab:维护`output_templates``current_template_index`,批量校验与报告显示。
6) 保存与重载:统一写入后调用处理器重载并日志提示。
## 验证
- GUI走查:新增/复制/删除供应商配置;规则预览正确;模板校验能识别缺失列。
- 处理生效:保存后立刻按新规则规范化并填充模板输出。
## 后续扩展
- 多供应商批量校验与报告导出;词典共享/继承;规则预设库扩展。
如果确认,我将开始实现该GUI及其数据流,并将现有向导整合到供应商管理中以形成一站式配置体验。
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## 痛点复盘
- 不同供应商存在强差异:列名不统一、单位混杂在数量、规格隐藏在名称、供应商缺失等
- 现有向导只解决列映射层面,规则与词典编辑、执行顺序与生效范围不清晰
- 缺少可视化“从原始→规范化→模板填充”的贯通验证;流程易跑不通
## 总体方案
- 建立“供应商规则系统”:可配置、可视化、可预览,贯穿 映射→清洗→规则→模板 填充全链路
- 提供“规则库 + 词典 + 执行管道”三层抽象,支持每家供应商自定义规则组合与执行顺序
- 完善 GUI:供应商管理中的四大Tab一站式配置,规则编辑器内置预设与预览,落地即验证
## 数据模型
- `suppliers_config.json` 每个供应商对象结构:
- `name``description`
- `filename_patterns``content_indicators`
- `header_row`
- `column_mapping`(源列→标准列)
- `rules`: 有序规则数组(见下)
- `dictionary`: 解析词典(`ignore_words``unit_synonyms``pack_multipliers``name_patterns``default_unit``default_package_quantity`
- `output_templates`: 模板列表;`current_template_index`: 当前模板索引
## 规则库(首批)
- `split_quantity_unit(source)`: 拆分数量中的单位(箱/件/提/盒/瓶),无单位用默认单位
- `extract_spec_from_name(source)`: 从名称抽取规格/包装(容量×数量/简单双乘),应用忽略词与名称正则
- `normalize_unit(target,map)`: 单位归一(同义词→统一单位),件/箱/提/盒按包装倍数转换数量为“瓶”
- `compute_quantity_from_total()`: 数量缺失时用金额/单价回推数量
- `fill_missing(fills)`: 缺失填充,例如单位默认“瓶”
- `mark_gift()`: 金额/单价为0或名称含“赠品/O/o/空”标记赠品
- 后续扩展:`classify_category(name)`, `extract_brand(name)`, `strip_noise(name)`
## 执行管道
- 处理器执行顺序:映射→清洗→规则(有序)→模板填充
- 每条规则可访问 `dictionary`,执行结果在 DataFrame 上可追踪(供预览)
- 提供“预览栈”:展示原始→每步规则输出(多步Diff),定位问题
## GUI优化
- 供应商管理:
- 左侧供应商列表(搜索/新建/复制/删除/导入/导出)
- 右侧四大Tab
- 基本信息:必填校验与保存
- 列映射与表头:现有向导增强(滚动条、表头选行、智能映射、导入/导出)
- 规则与词典:
- 规则编辑器(顺序可调整:上/下移动、插入/删除规则)
- 词典编辑(忽略词、单位同义词、包装倍数、名称正则、默认值)
- 规则预设(常用组合)与“应用规则预览”(展示原始→规范化两列;可切换查看逐步Diff)
- 模板管理:模板列表/当前选择与批量校验,显示缺失/多余列报告
- 性能与体验:所有弹窗置顶回焦;滚动与水平滚动;列宽拖拽与一键导出预览为CSV
## 使用路径(推荐)
1. 新建供应商→选样例Excel→自动表头与初始映射建议
2. 规则预设:选择“基础拆分与推断”→应用规则预览→查看原始/规范化对比
3. 细化词典:补充忽略词、单位同义词、包装倍数、名称正则→再次预览
4. 保存并重载→跑一份真实文件→最近文件中打开结果核验→如有差异回到规则编辑器微调
## 验证与可视化
- 单元测试:表头识别/数量拆分/名称规格解析/单位归一/数量回推/赠品标记
- 烟雾测试:5–10类典型供货商样本端到端验证(含极端情况:无单位、名称含噪声、数量混合单位)
- 日志:每步规则执行计数与示例行输出(前/后5行),便于定位问题
## 交付物
- 规则引擎模块与规范接口;处理器接入
- 供应商管理GUI(规则编辑器、词典编辑器、预设与预览)
- 扩展配置示例与测试数据;打包脚本校验资源
## 里程碑
- Day 1:规则库与引擎扩展、处理器接入、预览栈接口
- Day 2:GUI规则编辑器(顺序调整/增删)、词典编辑器、规则预设与预览
- Day 3:模板批量校验、单元与烟雾测试、日志强化
- Day 4:回归修正与打包交付
确认后我将开始实现上述内容,确保不同供应商可独立配置精细规则并“所见即所得”验证,流程稳定可跑通。
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## 目标
- 为具体供应商定制更细的解析规则(词典、包装倍数、忽略词、同义单位),并在列映射向导提供可视化编辑入口与预览。
## 配置扩展
- 扩展 `suppliers_config.json` 每个供应商对象新增:
- `dictionary`: 解析词典
- `ignore_words`: ["白膜","彩膜","赠品"](在名称解析时剔除)
- `unit_synonyms`: {"箱":"件","提":"件","盒":"件","瓶":"瓶"}
- `pack_multipliers`: {"件": 24, "箱": 24, "提": 12, "盒": 10}(缺规格时用于单位归一)
- `name_patterns`: [正则表达式](从名称抽取规格/容量×数量,如 `([\d\.]+)(ml|l|升|毫升)[*×xX](\d+)`
- `default_unit`: "瓶"
- `default_package_quantity`: 1
- `rules`: 规则数组(与现有一致),规则在执行时可访问 `dictionary`
- `output_templates`: 模板列表;`current_template_index`: 当前选择索引
## 规则引擎增强
-`app/core/handlers/rule_engine.py`
- `apply_rules(df, rules, dictionary=None)` 接口增加 `dictionary` 参数
- `extract_spec_from_name`:先剔除 `ignore_words`,匹配 `name_patterns`,无匹配时按 `pack_multipliers` 推断包装数量
- `normalize_unit`:使用 `unit_synonyms` 统一单位;如单位为“件/箱/提/盒”且有 `package_quantity``pack_multipliers`,数量×包装并单位归一为“瓶”
- `split_quantity_unit`:解析数量中的单位,同义词归一;无单位时用 `default_unit`
- 其余规则(回推数量、填充、赠品标记)保持不变
## 供应商处理器接入
- `GenericSupplierProcessor`
-`supplier_config['dictionary']` 取词典并传入 `apply_rules`,保证每家供应商按自身词典执行
- 若未配置词典,使用默认空词典
## 向导UI扩展(右侧系统设置→列映射向导)
- 增加“供应商规则”区域:
- 可编辑列表:
- 忽略词(多行输入或表格)
- 单位同义词(键值对表格:原单位→统一单位)
- 包装倍数(单位→包装数量)
- 名称正则(多行,每行一个表达式)
- 默认单位、默认包装数量(输入框)
- 操作:新增/删除、导入(JSON)/导出(JSON)、保存
- 规则预览:
- 选择预设(基础拆分与推断或自定义),点击“应用规则预览”,显示“原始/规范化”两列树表对比
- 保存行为:将 `dictionary``rules` 写入对应供应商的 `suppliers_config.json` 并重载处理器
## 验证与测试
- 单元测试:
- 名称解析(容量×数量、简单乘法、忽略词影响、同义词归一)
- 数量拆分与单位归一(“4瓶/1箱/3件/2提/2盒”)
- 包装倍数应用与数量回推
- 烟雾测试:构建 5–10 类供货商样本,验证端到端转换与模板填充可用
## 交付
- 完成词典与规则编辑入口、配置扩展与引擎接入,提交验证报告与示例配置;保留导入/导出便于你迭代调整。
确认后我将按此方案实现:扩展配置→增强规则引擎→处理器接入→向导UI与预览→测试。
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## 原因
* 按钮调用了 `safe_open_validation_panel`,其内部检查 `open_validation_panel` 是否存在;当前代码中未定义该函数,导致始终提示“程序未加载,请重启”。
## 修复方案
*`启动器.py` 中新增顶层函数 `open_validation_panel(log_widget)`,与其它 `open_*` 工具函数并列,确保加载顺序稳定。
* 保留按钮绑定到 `safe_open_validation_panel`,其将直接调用新定义的 `open_validation_panel`
## 实施
* 添加 `open_validation_panel`
* 入口参数:`log_widget`
* 实现与之前描述一致:供应商选择、原始文件/期望结果选择、运行验证生成差异、生成建议并“应用建议”写回配置。
* 放置位置:`show_supported_processors``safe_open_validation_panel` 相邻区域,确保可见与可用。
## 验证
* 启动程序→系统设置→点击“验证匹配”,应正常打开面板无提示。
* 选择“农夫山泉”与提供的文件后运行验证,查看差异与建议。
## 预期
* 面板不再提示重启;功能可用。
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## 目标
- 用你提供的原始文件与期望结果跑通“验证闭环”,自动对比差异并生成修正建议。
- 将“规则设置”改造成通俗易懂的“向导 + 快速模板 + 自动识别”,让普通用户也能完成操作。
## 验证闭环(立即可用)
- 新增“验证匹配”面板:
- 选择原始Excel`data/output/微信图片_20251115212128_148_108.xlsx`
- 选择期望结果:`data/result/采购单_微信图片_20251115212128_148_108.xls`
- 一键运行当前供应商流程 → 自动生成临时结果 → 与期望结果进行单元格级对比
- 输出差异报告:
- 列差异(列缺失/多余/名称不一致)
- 行差异(按条码或名称对齐,数量/单位/单价/金额差异)
- 规则差异归因(例如:数量未拆分、单位未归一)
- 按“应用建议”自动调整当前供应商的规则/词典(可撤销)
## 简化操作设计
- 两种模式:
- 简单模式(默认):
- 步骤:选择文件 → 选择供应商 → 选择快速模板 → 预览 → 生成
- 字段中文说明(name(商品名称)、quantity(数量)等)与自动建议
- 高级模式:
- 可编辑规则顺序与参数、词典、正则;具备步骤预览与Diff
- 快速模板:
- “无数量/单位列”模板:自动配置拆分数量单位→名称提取规格→单位归一→缺省填充→标记赠品
- “纯金额/单价反推数量”模板:直接回推数量
- “条码驱动匹配”模板:条码为主键对齐
## 自动识别与建议
- 列名识别:从表头关键词自动映射常用字段
- 单位与数量:从“订单数量”拆分,单位同义词与包装倍数自动套用
- 名称提取规格:词典与正则库(容量×数量、双乘、“550水24白膜”)自动解析;失败行计数提示
- 自动修正建议:
- 若数量为空:建议添加“split_quantity_unit(source=订单数量)”
- 若单位为“箱/件/提/盒”:建议添加“normalize_unit + pack_multipliers”
- 若金额与单价存在且数量为空:建议添加“compute_quantity_from_total”
## 差异对比与一键修复
- 差异可视化:原始→规范化→模板填充三栏对比;支持仅显示变化列、导出CSV
- 一键修复:将建议以“卡片”列表展示,点击应用后立即刷新预览;支持撤销上一步
## 交互流程
1) 进入“验证匹配” → 选择原始与期望 → 运行 → 查看差异
2) 点击“应用建议”直观修复规则/词典 → 差异减少直至匹配
3) 切回“简单模式”一键生成采购单
## 技术实现要点
- 供应商配置:继续使用 `suppliers_config.json`,但在GUI中隐藏JSON细节,改为中文表单与下拉
- 规则执行:保留引擎,新增“建议生成器”根据差异报告生成规则/词典变更
- 对比对齐:优先按条码对齐;无条码时按名称近似匹配(去噪后模糊比对)
## 里程碑
- Day 1:验证面板与差异对比;建议生成器(数量/单位/规格/金额)
- Day 2:简单/高级模式切换;快速模板与自动识别
- Day 3:一键修复与撤销;导出差异报告
- Day 4:回归测试与打包;提供“农夫山泉”预设并用你的样例验证匹配
确认后我将实现“验证匹配”面板并接入建议修复,先用你提供的农夫山泉样例跑通闭环,再推广到其它供应商。
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## 目标
- 按照优化实施计划,从第3周任务7/8开始全面落地,并同时推进第4周任务9/10,确保可视化、配置驱动和交付质量提升。
## 任务7:列映射向导完善
- 字段扩展与中文提示:标准字段统一以英+中展示,支持更多列(条码、名称、规格、数量、单位、单价、金额/小计、分类、品牌、供应商)。
- 自动建议增强:结合样本数据统计(字符串比例、特殊关键词、数值特征)给出更可靠的映射建议。
- 表头定位增强:支持预览选择,并保存 `header_row`;向导内清晰提示当前使用的表头行。
- 配置管理:支持导入/导出映射方案(JSON),可一键应用到多供应商。
- 热重载与快捷入口:保存后自动重载供应商处理器;在系统设置区和快捷键中提供入口。
## 任务8:模板管理与校验完善
- 模板组管理:支持为每个供应商选择/保存多个模板(默认、备用),UI下拉选择当前模板。
- 差异检测:读取模板首行表头与系统标准列比较,列表显示缺失/多余字段与修复建议。
- 批量校验:可一次性校验选定供应商的所有模板组并生成报告。
- 示例生成:按标准列生成示例模板,便于对齐格式。
## 任务9:单元测试与烟雾测试
- 单元测试(pytest):
- `_find_header_row` 不同格式表头识别(第一行/中间行/合并行/空白行混杂)。
- `GenericSupplierProcessor` 列映射、清洗规则(remove_rows/fill_na/convert_type)与公式计算。
- 模板填充的关键路径(必要列检测、数量/赠送量/单价写入)。
- 烟雾测试:准备小样本(图片→OCR→Excel→采购单),验证端到端可用,记录日志与输出。
## 任务10:打包与版本信息
- 版本信息:主窗口标题与“关于”对话框显示版本号、构建时间、更新日志入口。
- 打包校验:构建后检查模板与配置文件存在性;打包时拷贝资源并生成校验报告。
- 更新脚本:完善 `build_exe.py` 支持版本号注入与资源校验失败时中止。
## 实现要点
- GUI:系统设置页整合入口;对话框使用 780×660/540 尺寸,`topmost`/`lift`/`focus_force` 保证焦点。
- 配置:`suppliers_config.json` 增加 `header_row``column_mapping``output_templates`(数组)与当前选择索引。
- 处理器:优先使用保存的表头行;模板管理选择的模板在处理时应用。
- 日志与提示:保存/校验/重载操作统一写入日志面板并气泡提示。
## 验证
- 交互走查:向导流程顺畅、字段标签明确、置顶行为正常。
- 单元测试通过率达标(≥90%覆盖关键模块);烟雾测试输出正确文件且无异常。
- 打包后 EXE 启动显示版本信息;资源齐备,最近文件可双击打开。
## 变更范围
- `启动器.py`(设置页UI、向导与模板管理弹窗)
- `app/core/processors/supplier_processors/generic_supplier_processor.py`(读取与映射逻辑)
- `app/core/excel/processor.py`(表头行识别与模板填充校验)
- `config/suppliers_config.json`(结构扩展)
- `tests/`(新增pytest用例与烟雾测试脚本)
- `build_exe.py`(版本注入与校验)
## 时间安排
- Day 1:任务7 UI/配置完成,处理器联动与验证
- Day 2:任务8 模板管理增强与批量校验
- Day 3:任务9 单元测试与烟雾测试
- Day 4:任务10 打包与版本信息,回归测试与文档补充
确认后我将按以上计划开始实施并逐项提交验证结果。
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## 概览
- 目标:让改动更可见并提升识别/处理准确性与可操作性
- 范围:GUI入口与提示、表头识别与手动指定、供应商配置联动、交互一致性
## 可见入口改造
- 在“Excel处理→特殊处理”区新增两个明显按钮:
- “列映射向导”:加载 Excel 源列 → 映射到标准列 → 保存至 `config/suppliers_config.json`
- “模板管理”:选择模板、校验表头列是否包含必需项 → 保存路径至供应商配置
- 在“快捷操作”区补充一个“显示处理器类型”入口,便于确认支持的文件类型
- 在保存成功后增加气泡提示与日志条目(log 面板出现“列映射已保存”“模板路径已保存”)
## 手动表头行支持
- 在“列映射向导”弹窗增加“表头行号(从1开始)”输入框:
- 加载列时按照指定行重读 Excel 并展示源列
- 保存时将 `header_row`(零基索引)写入 `suppliers_config.json`
- 通用供应商处理器读取时优先使用 `supplier_config['header_row']`;未设置时执行自动表头检测(关键词+非空比例+字符串比例)
## 自动表头检测增强
- Excel 单文件处理与通用供应商处理器:
- 扫描范围扩大到前 30 行
- 扩充关键词:加入金额类(“金额/小计/总计/合计/合计金额”)
- 综合评分:关键词命中+非空比例+字符串比例,阈值达到即判为表头;否则选第一个有效行
## 交互与一致性
- “单个识别”按钮直接弹出图片选择(只允许 `jpg/jpeg/png/bmp`),取消即终止
- “单个处理”按钮弹出 Excel 选择(只允许 `xlsx/xls`),取消即终止,不再默认处理最新 Excel
- 处理完成后不再自动打开 `result/output` 目录,改为通过“最近文件”双击打开
- 最近文件仅记录图片/Excel,自动过滤无效并按修改时间降序展示,空历史时从 `data/output``data/result` 回填合规文件
## 供应商配置联动
- `suppliers_config.json`
- `column_mapping`:保存源列→标准列映射
- `header_row`:保存手动指定的表头行(零基)
- `output_template`:保存模板路径(相对路径)
- 处理器加载时校验并日志提示不合法项,保留已通过的配置
## 验证与可视化
- 操作日志:保存映射/模板时写入成功日志
- 处理器信息:通过“显示处理器类型”对话框列出支持的扩展名和描述
- 手动表头验证:在向导中“加载列”后,源列下拉应出现正确列名;处理后“最近文件”出现输出采购单
## 预计改动位置
- GUI按钮与向导弹窗:`启动器.py`(特殊处理区与工具函数)
- 自动表头检测与手动表头使用:
- Excel处理:`app/core/excel/processor.py``_find_header_row``process_specific_file`
- 通用供应商处理:`app/core/processors/supplier_processors/generic_supplier_processor.py``_read_supplier_data``_find_header_row`
- 供应商配置:`config/suppliers_config.json`
## 交付
- 提交代码改动后,更新打包 EXE,便携包包含上述 UI 与功能;提供操作说明与可见验证点。
请确认以上计划,确认后我将按此逐项实现并验证。
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## 你现在就能这样做
- 目标:在没有“规格/数量/单位”列、只有“订单数量”列(如“4瓶/1箱/5箱/3件”)时,拆分出数量与单位,并按名称提取规格,最终规范化为银豹模板字段。
### A. 最小映射(只为模板填充)
- 在“供应商管理 → 列映射与表头”页,只需映射这些常用列:
- name ← 商品名称
- barcode ← 条码(如有)
- unit_price ← 单价(如有)
- total_price ← 金额/小计(如有)
- 不需要映射“数量/单位/规格”,后续用规则直接从原始列生成。
### B. 规则与词典设置(关键)
- 在“供应商管理 → 规则与词典”页:
1) 规则列表按顺序添加:
- split_quantity_unit,参数:source=订单数量
- extract_spec_from_name,参数:source=商品名称
- normalize_unit,参数:target=unitmap={"箱":"件","提":"件","盒":"件"}
- fill_missing,参数:fills={"unit":"瓶"}
- mark_gift(可选)
- compute_quantity_from_total(可选,当只有金额/单价时)
2) 词典设置:
- unit_synonyms{"箱":"件","提":"件","盒":"件","瓶":"瓶"}
- pack_multipliers{"件":24,"箱":24,"提":12,"盒":10}(根据你的供应商习惯调整)
- default_unit:瓶
- default_package_quantity1
- ignore_words:如(白膜、彩膜、赠品)
- name_patterns(每行一个正则):
- (\d+(?:\.\d+)?)(ml|l|升|毫升)[*×xX](\d+)
- (\d+)[*×xX](\d+)瓶
- 需要时加入供应商特有格式,如“550水24白膜”可匹配“(\d{2,3}).*?(\d{1,3})”并将第二组当作包装数
### C. 预览与验证
- 在“规则与词典”页选择Excel,点击“生成步骤预览”:
- 看“原始 → 规范化”两侧表,对比是否出现 quantity(数值)、unit(单位)、specification、package_quantity
- 在“预览步骤”中逐步查看每一条规则的结果;必要时导出CSV核对
- 保存后会自动重载处理器;用真实文件跑一次,结果会出现在“最近文件”,双击打开核验。
### D. 解释关键点
- 映射是为了模板填充字段的命名统一;对于“订单数量”这种来源列,规则会直接读取 source=订单数量,不要求你把它映射成标准列。
- 规则执行后,会产生标准字段:quantity、unit、specification、package_quantity,可被模板填充。
- normalize_unit会用词典的pack_multipliers或name解析出的package_quantity,自动把“件/箱/提/盒”的数量换算成“瓶”,并将unit统一为“瓶”。
## 我将继续优化的点(让流程更清晰)
1) 规则表单中的“来源列”改为可选下拉(直接从Excel列名取值),无需手填。
2) 步骤预览支持“仅显示变化的列(Diff模式)”与“错误计数”(未匹配的行统计)。
3) 提供“无数量/单位列”的快速模版:自动添加上述规则与词典默认值,一键套用。
4) 规则帮助提示:每条规则说明输入/输出字段与常见示例。
5) 供应商级的“测试运行”:选文件→一键规范化→预览→导出结果,独立于正式处理。
如果你同意,我将按上述方案完善GUI交互(来源列下拉、快速模板、Diff预览、错误计数与一键测试),并把默认规则与词典预设直接提供出来,确保“只有订单数量列”的场景开箱可用。
@@ -0,0 +1,42 @@
## 目标
- 通过规则引擎把不同供货商的OCR表格规范为统一字段,并自动拆分“数量+单位”、从名称推断规格、标记赠品,最终稳定填充银豹模板。
## 配置与规则
- 扩展 `suppliers_config.json`
- `rules`: 规则数组(顺序执行)
- `output_templates`: 模板列表;`current_template_index`: 当前模板索引
- 规则类型:
- `split_quantity_unit`(拆分“4瓶/1箱/3件/2提/2盒”)
- `extract_spec_from_name`(解析“1.8L×8瓶”“550水24白膜”等)
- `normalize_unit`(单位归一“箱/件/提/盒/瓶”→统一“瓶”,按包装转换数量)
- `compute_quantity_from_total`(数量缺失时用金额/单价反推)
- `infer_supplier`(文件名/内容推断供应商)
- `fill_missing`(填默认值)
- `mark_gift`(金额/单价=0或“赠品/O/o/空”)
## 实现
- 新建 `app/core/handlers/rule_engine.py`:输入DataFrame与规则列表,返回规范化DataFrame
-`GenericSupplierProcessor` 中:列映射→清洗→规则引擎→输出
- 列映射向导增强:
- 增加“规则预设”选择与“应用规则预览”按钮,显示原始/规范化后的对比
- 支持导入/导出(映射+规则)JSON
- 模板管理增强:模板组选择、批量校验、示例模板生成
## 解析与正则
- 名称解析:
- 容量×数量:`(\d+(?:\.\d+)?)(ml|l|升|毫升)[*×xX](\d+)`
- 简单数量×数量:`(\d+)[*×xX](\d+)`
- 词典忽略词:如“白膜”等
- 数量拆分:`(?P<num>\d+(?:\.\d+)?)(?P<unit>箱|件|提|盒|瓶)`
## 验证
- 单元测试覆盖规则与表头识别;烟雾测试涵盖“无单位/规格/数量混杂”的样本
- GUI预览确认规则效果;保存后热重载处理器
## 里程碑
- Day 1:规则引擎与处理器接入
- Day 2:向导规则预览与导入/导出;模板组管理
- Day 3:测试与样本库
- Day 4:打包与交付验证
请确认,我将立即开始实现并逐步提交验证结果。
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# CLAUDE.md - 益选 OCR 订单处理系统
## 项目概述
益选 OCR 订单处理系统 (orc-order-v2) 是一个面向零售与分销场景的采购单处理工具。
**核心流程**: 图片 OCR → Excel 规范化 → 模板填充 → 合并导出
**目标系统**: 银豹 (PosPal) POS 系统
**技术栈**: Python 3.9+, Tkinter, Pandas, Baidu OCR API, xlrd/xlwt/openpyxl
## 项目结构
```
orc-order-v2/
├── 启动器.py # 入口桩 (~13行, 仅导入 main)
├── headless_api.py # CLI 自动化接口 (OpenClaw 对接)
├── build_exe.py # PyInstaller 打包脚本
├── config.ini # 全局配置 (API密钥、路径)
├── config/
│ ├── config.ini # 配置副本
│ ├── barcode_mappings.json # 条码映射规则
│ └── suppliers_config.json # 供应商配置 (列映射/清洗规则/计算规则)
├── app/
│ ├── config/
│ │ ├── settings.py # ConfigManager 单例
│ │ └── defaults.py # 默认配置
│ ├── core/
│ │ ├── excel/
│ │ │ ├── processor.py # ExcelProcessor - 标准化转换核心
│ │ │ ├── converter.py # UnitConverter - 单位转换与规格推断
│ │ │ ├── merger.py # PurchaseOrderMerger - 采购单合并
│ │ │ ├── validators.py # ProductValidator
│ │ │ └── handlers/ # 条码映射、单位转换处理器
│ │ ├── handlers/
│ │ │ ├── rule_engine.py # 通用规则引擎 (split/extract/normalize/mark)
│ │ │ ├── column_mapper.py # 列映射器
│ │ │ ├── data_cleaner.py # 数据清洗器
│ │ │ └── calculator.py # 计算器
│ │ ├── ocr/
│ │ │ ├── table_ocr.py # OCRProcessor
│ │ │ └── baidu_ocr.py # BaiduOCRClient
│ │ ├── processors/
│ │ │ ├── base.py # BaseProcessor 抽象基类
│ │ │ ├── tobacco_processor.py
│ │ │ ├── ocr_processor.py
│ │ │ └── supplier_processors/
│ │ │ └── generic_supplier_processor.py
│ │ └── utils/
│ │ ├── file_utils.py # 文件操作工具
│ │ ├── log_utils.py # 日志工具
│ │ ├── string_utils.py # 字符串工具
│ │ └── dialog_utils.py # Tkinter 对话框工具
│ ├── services/
│ │ ├── order_service.py # 订单服务 (智能路由分发)
│ │ ├── ocr_service.py # OCR 服务
│ │ ├── processor_service.py # 处理器调度服务
│ │ ├── tobacco_service.py # 烟草公司专用服务
│ │ └── special_suppliers_service.py # 特殊供应商服务 (蓉城/杨碧月)
│ └── ui/ # GUI 模块 (从启动器.py拆分)
│ ├── error_utils.py # L0 错误对话框
│ ├── theme.py # L0 主题管理 (THEMES, create_modern_button)
│ ├── logging_ui.py # L0 日志队列与GUI日志处理器
│ ├── ui_widgets.py # L0 StatusBar, ProgressReporter, center_window
│ ├── user_settings.py # L1 用户设置与最近文件管理
│ ├── result_previews.py # L1 处理结果预览对话框
│ ├── command_runner.py # L1 命令执行器 (subprocess + 日志重定向)
│ ├── file_operations.py # L2 文件选择/清理/目录操作
│ ├── action_handlers.py # L2 业务操作 (OCR/Excel/合并/拖拽)
│ ├── barcode_editor.py # L2 条码映射编辑
│ ├── config_dialog.py # L3 系统设置对话框
│ ├── shortcuts.py # L3 键盘快捷键绑定
│ └── main_window.py # L4 main() 主窗口构建
├── templates/
│ ├── 银豹-采购单模板.xls # 输出模板
│ └── 商品资料.xlsx # 单价校验参考数据
├── data/
│ ├── input/ # 输入文件
│ ├── output/ # OCR 输出
│ ├── result/ # 最终采购单
│ └── user_settings.json # 用户设置
└── docs/
└── SYSTEM_ARCHITECTURE.md # 系统架构文档
```
## 命令与运行
```bash
# GUI 模式
python 启动器.py
# CLI 模式 (OpenClaw 对接)
python headless_api.py [input] [--excel|--tobacco|--rongcheng] [--barcode X --target Y]
# 打包 EXE
python build_exe.py
# 条码映射更新
python headless_api.py --update-mapping --barcode 6920584471055 --target 6920584471017
```
## 供应商智能识别逻辑
系统通过扫描 Excel 前 50 行内容特征自动路由:
| 供应商 | 识别特征 | 预处理逻辑 |
|--------|----------|-----------|
| 烟草公司 | "专卖证号" 或 "510109104938" | B/E/G/H 列映射, 数量*10, 单价/10 |
| 蓉城易购 | "RCDH" | E/N/Q/S 列映射, 多条码分裂均分数量 |
| 杨碧月 | "经手人" + "杨碧月" | 列对齐, 单位转换 (件→瓶) |
| 通用供应商 | suppliers_config.json 配置 | 列映射 + 规则引擎 |
## 配置系统
- **ConfigManager** (`app/config/settings.py`): 单例模式, 基于 configparser 读取 `config.ini`
- **供应商配置** (`config/suppliers_config.json`): JSON 格式, 定义列映射/清洗规则/计算规则
- **条码映射** (`config/barcode_mappings.json`): 运行时可更新的条码转换规则
## 关键约定
### 输出格式
- 银豹采购单模板: 4 列 — 条码(B), 采购量(C), 赠送量(D), 采购单价(E)
- 单价保留 4 位小数, 使用 xlwt.XFStyle
- 采购单文件名: `采购单_{原文件名}.xls`
### 单位转换规则
- "件"/"箱"/"提"/"盒" → 数量*包装数量, 单价/包装数量, 单位→"瓶"
- 赠品: 价格为 0 或金额为 0 的行标记为赠品
- 条码映射优先于单位转换
### 规格推断
- 从商品名称推断: "24入纸箱" → 1*24, "450g*15" → 1*15
- 支持三级规格: 1*5*12
- OCR 修正: "IL" → "1L", "6oo" → "600"
## 已知技术债务
1. ~~**启动器.py 过大**~~ (已拆分为 13 个 `app/ui/` 模块, 入口桩仅 13 行)
2. **代码重复**: 表头识别、列映射、金额解析在多处重复实现
3. **配置不统一**: config.ini + suppliers_config.json + 硬编码路径混用
4. **无测试**: 测试目录为空, 无自动化测试
5. **旧格式依赖**: xlrd/xlwt 仅支持 .xls, 不支持 .xlsx 写入
6. **API 密钥明文**: config.ini 中百度 OCR API 密钥未加密
7. **路径硬编码**: config.ini 中 `template_folder = E:\2025Code\python\orc-order-v2\templates`
8. **日志不统一**: 混用 `get_logger()``logging.getLogger()`
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FROM python:3.11-slim
WORKDIR /app
# Install system dependencies (tkinter needed by app/core processing)
RUN apt-get update && apt-get install -y --no-install-recommends \
gcc \
python3-tk \
&& rm -rf /var/lib/apt/lists/*
# Install Python dependencies
COPY web/backend/requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
# Copy project files
COPY app/ ./app/
COPY config/ ./config/
COPY config.ini ./
COPY templates/ ./templates/
COPY web/ ./web/
# Create data directories
RUN mkdir -p data/input data/output data/result data/temp
# Expose port
EXPOSE 18889
# Run
CMD ["python", "-m", "uvicorn", "web.backend.main:app", "--host", "0.0.0.0", "--port", "18889"]
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# Build stage
FROM node:20-alpine AS build
WORKDIR /app
COPY web/frontend/package.json web/frontend/package-lock.json* ./
RUN npm install
COPY web/frontend/ .
# Override outDir for Docker build (vite config uses ../backend/static for local dev)
RUN npx vite build --outDir ./dist
# Production stage
FROM nginx:alpine
COPY --from=build /app/dist /usr/share/nginx/html
COPY nginx.conf /etc/nginx/conf.d/default.conf
EXPOSE 18888
CMD ["nginx", "-g", "daemon off;"]
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# OCR 订单处理系统 - v2.2 更新报告
## 1. 业务逻辑与 UI 变更 (v2.2 Updates)
### 1.1 UI 极简优化
- **移除专用按钮**:从主界面彻底移除了“蓉城易购”和“烟草处理”两个特定按钮。
- **统一入口**:所有供应商 Excel 订单现在均通过“处理 Excel 文件”或直接拖拽至主界面进行处理。系统会自动识别并路由。
- **快捷键更新**:移除了 `Ctrl+T` (烟草处理) 快捷键,简化了键盘操作逻辑。
### 1.2 杨碧月预处理修复
- **列名校准**:修正了预处理输出列名,确保与银豹处理器期望的中文列名(商品条码、数量、单价等)完全一致。
- **干扰过滤**:在提取列时,自动排除了 `结算单位``基本单位数量` 等名称相似的非业务列,提高了匹配精度。
### 1.3 Headless API 智能增强
- **后缀感知**`headless_api.py` 能够根据文件后缀自动区分图片与 Excel,不再需要显式指定 `--excel``--tobacco`
- **零配置接入**OpenClaw 仅需运行 `python headless_api.py [文件路径]` 即可完成全流程。
## 2. 供应商清洗规则 (保持最新)
| 供应商 | 条码列 | 数量逻辑 | 单价逻辑 | 金额逻辑 |
| :--- | :--- | :--- | :--- | :--- |
| **蓉城易购** | E列 (Index 4) | N列 (Index 13),不换算 | Q列 (Index 16) | S列 (Index 18) |
| **烟草公司** | B列 (Index 1) | G列 (Index 6) **x 10** | E列 (Index 4) **/ 10** | H列 (Index 7) |
## 3. 代码与环境清理
- **移除无用文件**:清理了 `run.py` (冗余)、`clean.py` (旧脚本) 以及 `doc/` (旧文档)。
- **模块重构**:删除了 `app/cli/` 模块,所有命令行逻辑已合并至根目录的 `headless_api.py`
---
*报告生成日期:2026-03-31*
*负责人:Trae Code Assistant*
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# OCR 订单处理系统 - OpenClaw 对接指南 (v2.2)
## 1. 核心接口说明 (headless_api.py)
`headless_api.py` 是系统的统一命令行入口。它支持**智能文件类型与供应商识别**,OpenClaw 通常**无需携带任何功能参数**。
### 1.1 全自动智能模式 (推荐方式)
无论是收到**图片**还是 **Excel**,都可以直接调用。系统会自动判断文件类型:如果是 Excel 则自动识别供应商指纹(蓉城、烟草、杨碧月等)并处理;如果是图片则先 OCR 后再智能处理。
```bash
# 自动处理 data/input 中最新的文件 (图片或 Excel)
python headless_api.py
# 处理指定的任意文件 (图片或 Excel)
python headless_api.py "data/input/my_file.jpg"
python headless_api.py "data/input/my_file.xlsx"
```
### 1.2 显式特殊指令 (备用)
仅在自动识别失效或需要特殊操作时使用。
```bash
# 强制指定为 Excel 处理模式
python headless_api.py --excel
# 强制更新条码映射关系
python headless_api.py --update-mapping --barcode "123" --target "456"
```
## 2. 字段与逻辑变更
### 2.1 蓉城易购 (Rongcheng)
- **条码映射**E列 (Index 4)。
- **数量逻辑**N列 (Index 13)。直接提取,不进行单位换算。
- **条码分裂**:支持 `/` `,` `` `、` 分隔符自动均分。
### 2.2 烟草公司 (Tobacco)
- **条码映射**B列 (Index 1)。
- **数量逻辑**G列 (订单量) **x 10**
- **单价逻辑**E列 (批发价) **/ 10**。
### 2.3 杨碧月 (Yang Biyue)
- **自动对齐**:自动识别经手人并对齐“商品条码”、“数量”、“单价”等标准列。
---
*版本:2.2 | 更新日期:2026-03-31*
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# 益选 OCR 订单处理系统
面向零售与分销场景的采购单处理工具,支持图片 OCR → Excel 规范化 → 模板填充 → 合并导出全流程,输出适配银豹 (PosPal) POS 系统。
## 概览
- 面向零售与分销场景的采购单处理工具,支持图片 OCR → Excel 规范化 → 模板填充 → 合并导出全流程
- 通过供应商管理与规则引擎,适配不同供应商的格式差异(数量含单位、名称包含规格、缺失列补齐)
- 提供验证匹配面板与单价校验机制,确保输出与既定模板一致且价格合理
## 核心功能
- **全自动智能识别**:系统现在能自动识别 Excel 内容特征(如:蓉城易购 RCDH、烟草公司专卖证号、杨碧月经手人),并自动路由至专用预处理流程,无需手动干预。
- **图片/Excel处理**:支持拖拽或选择文件,一键生成标准银豹采购单。
- **极简 UI 体验**:移除了冗余的供应商特定按钮,所有 Excel 统一走智能路由处理。
- **无界面自动化接口 (headless_api.py)**:专为 OpenClaw 等平台设计,支持全自动文件类型与供应商识别。
- **单价预警机制**:自动比对 `templates/商品资料.xlsx`,若价差超过 1.0 元则触发警告。
- **智能供应商识别**:自动扫描 Excel 前 50 行内容特征,路由到对应的预处理逻辑(蓉城易购、烟草公司、杨碧月等)
- **图片 OCR**:调用百度 OCR 表格识别 API,将采购单图片转为结构化 Excel
- **规则引擎**:支持列映射、数据清洗、单位转换、规格推断、赠品标记等自动化规则
- **条码映射**可配置的条码转换规则,支持运行时编辑和云端同步
- **单价校验**:自动比对 `商品资料.xlsx`,价差超过 1.0 元触发预警
- **云端同步**:通过 Gitea REST API 在多台设备间同步配置文件(条码映射、供应商配置、商品资料、采购模板)
- **拖拽一键处理**:拖入图片或 Excel 自动走完 OCR → 规范化 → 合并全流程
- **CLI 接口**`headless_api.py` 支持无界面自动化调用
## 供应商专用逻辑 (v2.2)
### 蓉城易购 (Rongcheng)
- **精准映射**:商品条码(E列)、数量(N列)、单价(Q列)、金额(S列)。
- **条码分裂**支持多条码行(如 `条码1/条码2`)自动均分数量。
- **逻辑简化**:直接提取原始数量,不进行多余的单位或包装换算。
## 快速开始
### 烟草公司 (Tobacco)
- **换算逻辑**:条码(B列)、数量(G列 x 10)、单价(E列 / 10)、总额(H列)。
- **智能跳行**:自动识别并跳过合计行及非数据行。
### 桌面端 (GUI / CLI)
### 杨碧月订单
- **自动对齐**:识别到经手人“杨碧月”后,自动将非标 Excel 转换为标准列格式,支持单位换算(件 -> 瓶)。
```bash
# 安装依赖
pip install -r requirements.txt
## 关键适配(蓉城易购)
- 新模板(如“订单1765440157955.xlsx”):
- 使用第三行作为表头(`header=2`
- 关键词选列并重命名到期望字段:商品条码(小条码)、订购数量(小单位)、单价(小单位)、优惠后金额(小单位)、单位
- 单位优先匹配“单位(订购单位)”列,清洗为去空白并将“件”替换为“份”
- 多条码行(逗号/顿号/斜杠/空格分隔)拆分为多行,数量均分并重算金额,单位保持订购单位
- 新模板映射:将“优惠后金额(小单位)”作为单价,“出库小计(元)”作为金额来源
# GUI 模式
python 启动器.py
## 使用说明
1. 运行程序(EXE或源码运行)
2. 在主界面:
- 拖拽或选择图片/Excel进行处理
- 系统设置 → 供应商管理:配置供应商、列映射与规则;使用规则预览查看规范化效果
- 系统设置 → 验证匹配:选择原始与期望文件,差异对比;应用建议后重载配置
3. 处理成功后,采购单保存到 `data/output``data/result`,最近文件列表可双击打开查看
# CLI 模式
python headless_api.py data/input/xxx.xlsx
python headless_api.py data/input/xxx.jpg --barcode 6920584471055 --target 6920584471017
## 构建与打包
- 依赖:Python 3.9+,虚拟环境建议
- 安装打包工具:`pip install pyinstaller`
- 运行打包脚本:`python build_exe.py`
- 生成 EXE`dist/OCR订单处理系统.exe`
- 生成便携包:`release/OCR订单处理系统.exe`(包含 `templates/银豹-采购单模板.xls``templates/商品资料.xlsx`
# 打包 EXE
python build_exe.py
```
## Git 提交建议
- 建议忽略构建目录与运行输出(见 `.gitignore`
- 保留模板与配置:`templates/银豹-采购单模板.xls``templates/商品资料.xlsx``config/config.ini``config/barcode_mappings.json`
### Web 端
## 常见问题
- 表头识别失败:在供应商管理的“列映射与表头”页预览表头行并选择正确行号
- 数量含单位:启用 `split_quantity_unit``normalize_unit` 规则并配置单位同义词与包装倍数
- 名称中规格:配置 `ignore_words``name_patterns`,使用步骤预览确认解析效果
- 单价校验未提示:确认 `templates/商品资料.xlsx` 存在且列名包含“进货价”与条码列(`商品条码/条码/barcode`
```bash
# 后端依赖
cd web/backend && pip install -r requirements.txt
## 变更记录(近期)
- 新增验证匹配面板与建议修复
- 规则预设与步骤预览(原始→逐步→规范化)
- 单价校验机制(价差>1元提示)
- 蓉城易购新模板适配(第三行表头、单位(订购单位)、多条码拆分、金额映射)
# 前端依赖
cd web/frontend && npm install
# 启动后端 (端口 8000)
cd web && python -m uvicorn backend.main:app --host 0.0.0.0 --port 8000 --reload
# 启动前端开发服务器 (端口 5173)
cd web/frontend && npm run dev
# 构建前端到后端静态目录
cd web/frontend && npm run build
# 构建后直接访问 http://localhost:8000 即可
# 生产部署 (仅后端,前端已内嵌)
cd web && python -m uvicorn backend.main:app --host 0.0.0.0 --port 8000
```
**默认账号:** `admin` / `admin123`(首次登录后建议修改密码)
### Docker 部署 (生产环境)
**环境要求:** Docker + Docker Compose
```bash
# 1. 克隆代码
git clone https://gitea.94kan.cn/houhuan/orc-order-v2.git
cd orc-order-v2
# 2. 配置环境变量(百度 OCR API 密钥、Gitea Token 等)
cp .env.example .env # 若无 .env.example,手动创建 .env
# 编辑 .env 填入:
# BAIDU_OCR_API_KEY=xxx
# BAIDU_OCR_SECRET_KEY=xxx
# GITEA_TOKEN=xxx
# 3. 构建并启动
docker-compose up -d --build
# 4. 访问
# 前端: http://服务器IP:18888
# 后端 API: http://服务器IP:18889
# 默认账号: admin / admin123(首次登录后建议修改密码)
# 常用命令
docker-compose logs -f # 查看日志
docker-compose restart # 重启服务
docker-compose down # 停止服务
docker-compose up -d --build # 重新构建并启动
```
**端口说明:**
- `18888` — 前端 (Nginx),对外访问入口
- `18889` — 后端 API (FastAPI),前端自动代理,无需直接访问
**数据持久化:** `data/` 目录挂载到宿主机,SQLite 数据库、上传文件、处理结果不会因容器重建而丢失。
## 项目结构
```
├── 启动器.py # GUI 入口
├── headless_api.py # CLI 自动化接口
├── config.ini # 全局配置(API密钥、路径、Gitea)
├── config/
│ ├── config.ini # 配置副本
│ ├── barcode_mappings.json # 条码映射规则
│ └── suppliers_config.json # 供应商配置(列映射/规则引擎)
├── app/
│ ├── config/ # 配置管理(ConfigManager 单例)
│ ├── core/
│ │ ├── excel/ # Excel 处理(标准化、转换、合并、校验)
│ │ ├── handlers/ # 规则引擎、列映射、数据清洗、计算器
│ │ ├── ocr/ # 百度 OCR 客户端
│ │ ├── processors/ # 处理器(通用/烟草/OCR)
│ │ └── utils/ # 工具(日志、文件、字符串、云端同步、对话框)
│ ├── services/ # 业务服务(订单、OCR、处理器调度)
│ └── ui/ # GUI 模块(主题、日志、快捷键、主窗口)
├── web/ # Web 端
│ ├── backend/
│ │ ├── main.py # FastAPI 入口
│ │ ├── auth/ # JWT 认证(登录、Token、权限)
│ │ ├── routers/ # API 路由(文件、处理、记忆、条码、同步、任务、日志)
│ │ ├── services/ # 后端服务(任务管理、数据库、文件同步)
│ │ └── middleware/ # HTTP 日志中间件
│ └── frontend/
│ ├── src/
│ │ ├── views/ # 页面(Dashboard、Layout、文件管理、任务、日志等)
│ │ ├── stores/ # Pinia 状态管理(auth、processing
│ │ ├── composables/ # 共享逻辑(useDebounce、useFileUtils、useFilePreview
│ │ ├── api.ts # Axios 封装
│ │ └── router/ # Vue Router 路由
│ ├── package.json
│ └── vite.config.ts
├── templates/
│ ├── 银豹-采购单模板.xls # 输出模板(条码/采购量/赠送量/单价)
│ └── 商品资料.xlsx # 单价校验参考数据
├── data/
│ ├── input/ # 输入文件
│ ├── output/ # OCR 输出
│ ├── result/ # 最终采购单
│ └── web_data.db # Web 端数据库(SQLite
└── tests/ # 单元测试(191 个)
```
## Web 端功能
基于 Vue 3 + Element Plus + FastAPI 的浏览器端管理界面,与桌面端共享同一个 `data/` 目录。
### 处理中心 (Dashboard)
- **一键全流程**:上传图片或 Excel 后,一键完成 OCR → 标准化 → 合并全流程
- **批量 OCR / 批量处理**:可单独执行 OCR 识别或 Excel 标准化步骤
- **实时进度**:WebSocket 推送任务进度、日志、状态变更
- **多任务监控**:同时查看多个运行中任务的进度和日志
- **任务重试**:失败任务可查看错误详情并一键重试
### 文件管理
- **图片处理**:管理 `data/input/` 中的图片文件,支持上传、预览、批量 OCR、批量生成采购单
- **表格处理**:管理 `data/output/` 中的 Excel 文件,支持上传、预览、批量标准化处理
- **采购单管理**:管理 `data/result/` 中的采购单,支持预览、下载、合并、批量删除
- **实时同步**:页面加载时自动同步磁盘文件到数据库,新文件立即可见
- **清除处理缓存**:删除已处理的输出文件,允许重新处理
### 任务与日志
- **任务历史**:查看所有处理任务的状态、进度、日志,支持按状态和类型筛选
- **HTTP 日志**:记录所有 API 请求,支持按方法和状态码筛选
### 记忆库
- **产品记忆**:自动从 OCR 和处理结果中学习产品信息
- **置信度系统**:根据出现次数自动评估记忆可靠度
- **搜索与管理**:支持搜索、编辑、删除记忆条目
### 条码映射
- **映射规则管理**:添加、编辑、删除条码转换规则
- **批量操作**:支持批量导入和删除映射
### 云端同步
- **Gitea 同步**:通过 Gitea REST API 在多台设备间同步配置文件
- **一键推拉**:选择文件推送或拉取,无需 git 客户端
### 系统配置
- **配置编辑**:在浏览器中编辑系统配置(API 密钥、路径、参数)
- **修改密码**:支持修改 Web 端登录密码
### UI/UX
- **响应式布局**:适配桌面和移动端,小屏幕自动切换为抽屉式导航
- **全局错误处理**:未捕获的 Vue 错误自动显示用户提示
- **表单验证**:修改密码等操作有完整的输入验证
## 供应商智能路由
| 供应商 | 识别特征 | 处理逻辑 |
|--------|----------|----------|
| 烟草公司 | "专卖证号" 或 "510109104938" | B/E/G/H 列映射,数量×10,单价÷10 |
| 蓉城易购 | "RCDH" | E/N/Q/S 列映射,多条码分裂均分数量 |
| 杨碧月 | "经手人" + "杨碧月" | 列对齐,单位转换(件→瓶) |
| 通用供应商 | `suppliers_config.json` 配置 | 列映射 + 规则引擎 |
## 云端同步
通过 Gitea REST API 在多台设备间同步配置,无需 git 客户端。
**支持同步的文件:**
- 条码映射 (`barcode_mappings.json`)
- 供应商配置 (`suppliers_config.json`)
- 商品资料 (`templates/商品资料.xlsx`)
- 采购单模板 (`templates/银豹-采购单模板.xls`)
**配置方式:**
1. 系统设置 → 填入 Gitea 地址、仓库信息、Access Token
2. 主窗口 → "云端同步" 按钮 → 选择文件推拉
**Gitea 仓库:** `https://gitea.94kan.cn/houhuan/yixuan-sync-data`
## 配置说明
| 配置项 | 文件 | 说明 |
|--------|------|------|
| API 密钥 | `.env``config.ini` | 百度 OCR API,优先从环境变量读取 |
| Gitea Token | `.env``config.ini` | 云端同步 Token,优先从环境变量读取 |
| 供应商规则 | `config/suppliers_config.json` | 列映射、清洗规则、计算规则 |
| 条码映射 | `config/barcode_mappings.json` | 条码转换规则,运行时可更新 |
## 构建打包
```bash
pip install pyinstaller
python build_exe.py
# 输出: dist/OCR订单处理系统.exe
# 便携包: release/OCR订单处理系统.exe(含模板和商品资料)
```
## 测试
```bash
python -m pytest tests/ -v
```
+3 -16
View File
@@ -12,20 +12,14 @@ DEFAULT_CONFIG = {
'timeout': '30',
'max_retries': '3',
'retry_delay': '2',
'api_url': 'https://aip.baidubce.com/rest/2.0/ocr/v1/table',
'token_url': 'https://aip.baidubce.com/oauth/2.0/token',
'form_ocr_url': 'https://aip.baidubce.com/rest/2.0/solution/v1/form_ocr/get_request_result'
'api_url': 'https://aip.baidubce.com/rest/2.0/ocr/v1/table'
},
'Paths': {
'input_folder': 'data/input',
'output_folder': 'data/output',
'result_folder': 'data/result',
'temp_folder': 'data/temp',
'template_folder': 'templates',
'template_file': 'templates/银豹-采购单模板.xls',
'processed_record': 'data/processed_files.json',
'data_dir': 'data',
'product_db': 'data/product_cache.db'
'processed_record': 'data/processed_files.json'
},
'Performance': {
'max_workers': '4',
@@ -38,13 +32,6 @@ DEFAULT_CONFIG = {
'max_file_size_mb': '4'
},
'Templates': {
'purchase_order': '银豹-采购单模板.xls',
'item_data': '商品资料.xlsx'
},
'Gitea': {
'base_url': 'https://gitea.94kan.cn',
'owner': 'houhuan',
'repo': 'yixuan-sync-data',
'token': ''
'purchase_order': '银豹-采购单模板.xls'
}
}
+11 -52
View File
@@ -6,16 +6,12 @@
import os
import configparser
import logging
from typing import Dict, List, Optional, Any
from dotenv import load_dotenv
from ..core.utils.log_utils import get_logger
from .defaults import DEFAULT_CONFIG
# 加载 .env 文件
load_dotenv()
logger = get_logger(__name__)
logger = logging.getLogger(__name__)
class ConfigManager:
"""
@@ -33,23 +29,13 @@ class ConfigManager:
def _init(self, config_file):
"""初始化配置管理器"""
# 计算应用根目录(不依赖 os.getcwd()
import sys
if getattr(sys, 'frozen', False):
# PyInstaller 打包后,根目录是 exe 所在目录
self.app_root = os.path.dirname(sys.executable)
else:
# 源码运行,根目录是 app/config/ 的上两级
self.app_root = os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
self.config_file = config_file or os.path.join(self.app_root, 'config.ini')
self.config_file = config_file or 'config.ini'
self.config = configparser.ConfigParser()
self.load_config()
def load_config(self) -> None:
"""
加载配置文件,如果不存在则创建默认配置
API 密钥优先从环境变量 (.env) 读取
"""
if not os.path.exists(self.config_file):
self.create_default_config()
@@ -57,19 +43,16 @@ class ConfigManager:
try:
# 先读取现有配置
self.config.read(self.config_file, encoding='utf-8')
# 检查是否有缺失的配置项,只添加缺失的项
for section, options in DEFAULT_CONFIG.items():
if not self.config.has_section(section):
self.config.add_section(section)
for option, value in options.items():
if not self.config.has_option(section, option):
self.config.set(section, option, value)
# API 密钥优先从环境变量读取
self._override_from_env()
# 保存更新后的配置
self.save_config()
logger.info(f"已加载并更新配置文件: {self.config_file}")
@@ -77,18 +60,6 @@ class ConfigManager:
logger.error(f"加载配置文件时出错: {e}")
logger.info("使用默认配置")
self.create_default_config(save=False)
def _override_from_env(self) -> None:
"""从环境变量覆盖敏感配置"""
env_mapping = {
('API', 'api_key'): 'BAIDU_API_KEY',
('API', 'secret_key'): 'BAIDU_SECRET_KEY',
('Gitea', 'token'): 'GITEA_TOKEN',
}
for (section, option), env_key in env_mapping.items():
env_val = os.getenv(env_key, '').strip()
if env_val:
self.config.set(section, option, env_val)
def create_default_config(self, save: bool = True) -> None:
"""创建默认配置"""
@@ -104,25 +75,13 @@ class ConfigManager:
logger.info(f"已创建默认配置文件: {self.config_file}")
def save_config(self) -> None:
"""保存配置到文件(API 密钥不写入文件,Gitea token 需要持久化)"""
# 保存前临时清空 API 密钥,避免写入文件(这些从 .env 读取)
saved_keys = {}
for option in ('api_key', 'secret_key'):
try:
saved_keys[option] = self.config.get('API', option, fallback='')
except Exception:
saved_keys[option] = ''
self.config.set('API', option, '')
"""保存配置到文件"""
try:
with open(self.config_file, 'w', encoding='utf-8') as f:
self.config.write(f)
logger.info(f"配置已保存到: {self.config_file}")
finally:
# 恢复内存中的值(即使写入失败也恢复)
for option, val in saved_keys.items():
if val:
self.config.set('API', option, val)
except Exception as e:
logger.error(f"保存配置文件时出错: {e}")
def get(self, section: str, option: str, fallback: Any = None) -> Any:
"""获取配置值"""
@@ -163,8 +122,8 @@ class ConfigManager:
path = Path(path_str)
if not path.is_absolute():
# 相对路径,转为绝对路径(相对于应用根目录)
path = Path(self.app_root) / path
# 相对路径,转为绝对路径(相对于项目根目录)
path = Path(os.getcwd()) / path
if create:
try:
View File
-609
View File
@@ -1,609 +0,0 @@
"""
商品资料 SQLite 数据库 + 商品记忆库
记忆库功能:
- 处理每步后自动学习商品数据(置信度+一致性加速)
- OCR 字段缺失时用记忆库补全 (conf > 50 直接采用)
- 价格异常检测:偏差 > 2倍触发补全,偏差 > 50% 记录预警
- 批量预加载 → 内存操作 → 批量写回,保障性能
"""
import os
import json
import sqlite3
from datetime import datetime
from typing import Dict, List, Optional, Tuple, Callable
import pandas as pd
from ..utils.log_utils import get_logger
from ..utils.file_utils import smart_read_excel
from ...core.handlers.column_mapper import ColumnMapper
logger = get_logger(__name__)
class ProductDatabase:
"""商品资料 SQLite 数据库 + 商品记忆库"""
SCHEMA = """
CREATE TABLE IF NOT EXISTS products (
barcode TEXT PRIMARY KEY,
name TEXT DEFAULT '',
price REAL DEFAULT 0.0,
unit TEXT DEFAULT '',
updated_at TEXT,
specification TEXT DEFAULT '',
source TEXT DEFAULT 'template',
confidence INTEGER DEFAULT 0,
usage_count INTEGER DEFAULT 0,
last_seen TEXT,
avg_price REAL DEFAULT 0.0,
min_price REAL DEFAULT 0.0,
max_price REAL DEFAULT 0.0,
price_count INTEGER DEFAULT 0
);
"""
_NEW_COLUMNS = {
'specification': "TEXT DEFAULT ''",
'source': "TEXT DEFAULT 'template'",
'confidence': 'INTEGER DEFAULT 0',
'usage_count': 'INTEGER DEFAULT 0',
'last_seen': 'TEXT',
'avg_price': 'REAL DEFAULT 0.0',
'min_price': 'REAL DEFAULT 0.0',
'max_price': 'REAL DEFAULT 0.0',
'price_count': 'INTEGER DEFAULT 0',
}
def __init__(self, db_path: str, excel_source: str):
self.db_path = db_path
self.excel_source = excel_source
self._ensure_db()
def _connect(self) -> sqlite3.Connection:
return sqlite3.connect(self.db_path)
def _ensure_db(self):
if os.path.exists(self.db_path):
self._migrate_schema()
return
if not os.path.exists(self.excel_source):
logger.warning(f"商品资料 Excel 不存在: {self.excel_source}")
self._create_empty_db()
return
logger.info(f"首次运行,从 Excel 导入商品资料: {self.excel_source}")
os.makedirs(os.path.dirname(self.db_path), exist_ok=True)
self._create_empty_db()
count = self.import_from_excel(self.excel_source)
logger.info(f"商品资料导入完成: {count} 条记录")
def _create_empty_db(self):
conn = self._connect()
try:
conn.executescript(self.SCHEMA)
conn.commit()
finally:
conn.close()
def _migrate_schema(self):
conn = self._connect()
try:
cursor = conn.execute("PRAGMA table_info(products)")
existing_cols = {row[1] for row in cursor.fetchall()}
for col_name, col_type in self._NEW_COLUMNS.items():
if col_name not in existing_cols:
conn.execute(f"ALTER TABLE products ADD COLUMN {col_name} {col_type}")
logger.info(f"数据库迁移: 添加列 {col_name}")
conn.commit()
finally:
conn.close()
# ══════════════════════════════════════════════════════════════
# 导入
# ══════════════════════════════════════════════════════════════
def import_from_excel(self, excel_path: str) -> int:
df = smart_read_excel(excel_path)
if df is None or df.empty:
return 0
barcode_col = ColumnMapper.find_column(list(df.columns), 'barcode')
if not barcode_col:
return 0
price_col = ColumnMapper.find_column(list(df.columns), 'unit_price')
if not price_col:
for col in df.columns:
if '进货价' in str(col).strip():
price_col = col
break
name_col = ColumnMapper.find_column(list(df.columns), 'name')
unit_col = ColumnMapper.find_column(list(df.columns), 'unit')
spec_col = ColumnMapper.find_column(list(df.columns), 'specification')
now = datetime.now().isoformat()
rows = []
for _, row in df.iterrows():
barcode = str(row.get(barcode_col, '')).strip()
if not barcode or barcode == 'nan':
continue
price = 0.0
if price_col:
try:
p = row.get(price_col)
if p is not None and str(p).strip() not in ('', 'nan', 'None'):
price = float(p)
except (ValueError, TypeError):
pass
name = str(row.get(name_col, '')).strip() if name_col else ''
if name == 'nan': name = ''
unit = str(row.get(unit_col, '')).strip() if unit_col else ''
if unit == 'nan': unit = ''
spec = str(row.get(spec_col, '')).strip() if spec_col else ''
if spec == 'nan': spec = ''
# template 源置信度 50
rows.append((barcode, name, price, unit, now, spec, 'template', 50, 0, now,
price, price, price, 1 if price > 0 else 0))
if not rows:
return 0
conn = self._connect()
try:
conn.executemany(
"INSERT OR REPLACE INTO products "
"(barcode, name, price, unit, updated_at, specification, source, confidence, "
"usage_count, last_seen, avg_price, min_price, max_price, price_count) "
"VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
rows)
conn.commit()
finally:
conn.close()
return len(rows)
def reimport(self) -> int:
conn = self._connect()
try:
conn.execute("DELETE FROM products")
conn.commit()
finally:
conn.close()
return self.import_from_excel(self.excel_source)
# ══════════════════════════════════════════════════════════════
# 查询
# ══════════════════════════════════════════════════════════════
def get_price(self, barcode: str) -> Optional[float]:
conn = self._connect()
try:
row = conn.execute("SELECT avg_price FROM products WHERE barcode=?",
(str(barcode).strip(),)).fetchone()
return row[0] if row and row[0] else None
finally:
conn.close()
def get_prices(self, barcodes: List[str]) -> Dict[str, float]:
if not barcodes:
return {}
conn = self._connect()
try:
placeholders = ','.join('?' * len(barcodes))
rows = conn.execute(
f"SELECT barcode, avg_price FROM products WHERE barcode IN ({placeholders})",
[str(b).strip() for b in barcodes]).fetchall()
return {r[0]: r[1] for r in rows if r[1]}
finally:
conn.close()
def count(self) -> int:
conn = self._connect()
try:
return conn.execute("SELECT COUNT(*) FROM products").fetchone()[0]
finally:
conn.close()
def get_memory(self, barcode: str) -> Optional[Dict]:
conn = self._connect()
conn.row_factory = sqlite3.Row
try:
row = conn.execute("SELECT * FROM products WHERE barcode=?",
(str(barcode).strip(),)).fetchone()
return dict(row) if row else None
finally:
conn.close()
def get_memories(self, barcodes: List[str]) -> Dict[str, Dict]:
if not barcodes:
return {}
conn = self._connect()
conn.row_factory = sqlite3.Row
try:
placeholders = ','.join('?' * len(barcodes))
rows = conn.execute(
f"SELECT * FROM products WHERE barcode IN ({placeholders})",
[str(b).strip() for b in barcodes]).fetchall()
return {r['barcode']: dict(r) for r in rows}
finally:
conn.close()
def get_all_memories(self) -> List[Dict]:
conn = self._connect()
conn.row_factory = sqlite3.Row
try:
return [dict(row) for row in
conn.execute("SELECT * FROM products ORDER BY usage_count DESC, barcode").fetchall()]
finally:
conn.close()
# ══════════════════════════════════════════════════════════════
# 批量预加载 — 性能核心
# ══════════════════════════════════════════════════════════════
def load_batch(self, barcodes: List[str]) -> Dict[str, Dict]:
"""批量预加载条码记忆到 dict — 单次 SQL,后续纯内存操作"""
if not barcodes:
return {}
conn = self._connect()
conn.row_factory = sqlite3.Row
try:
placeholders = ','.join('?' * len(barcodes))
rows = conn.execute(
f"SELECT * FROM products WHERE barcode IN ({placeholders})",
[str(b).strip() for b in barcodes]).fetchall()
return {r['barcode']: dict(r) for r in rows}
finally:
conn.close()
# ══════════════════════════════════════════════════════════════
# 学习逻辑 — 一致性加速 + 价格区间
# ══════════════════════════════════════════════════════════════
def learn_from_product(self, product: Dict, source: str = 'ocr',
memory: Dict[str, Dict] = None,
add_log: Callable = None) -> Optional[str]:
"""
从处理结果中学习,返回日志字符串。
memory: 可选的预加载批量内存,传入则零 DB 查询。
"""
barcode = str(product.get('barcode', '')).strip()
if not barcode:
return None
name = str(product.get('name', ''))
spec = str(product.get('specification', ''))
unit = str(product.get('unit', ''))
price = float(product.get('price', 0))
now = datetime.now().isoformat()
# 查现有记录(优先从内存查)
if memory is not None and barcode in memory:
row = memory[barcode]
old_name = row.get('name', '')
old_spec = row.get('specification', '')
old_unit = row.get('unit', '')
old_conf = row.get('confidence', 0)
old_count = row.get('usage_count', 0)
old_avg = row.get('avg_price', 0) or 0
old_min = row.get('min_price') or price
old_max = row.get('max_price') or price
pc = row.get('price_count', 0) or 0
exists = True
else:
conn = self._connect()
try:
cursor = conn.execute(
"SELECT name, specification, unit, confidence, usage_count, "
"avg_price, min_price, max_price, price_count FROM products WHERE barcode=?",
(barcode,)).fetchone()
finally:
conn.close()
if cursor is None:
exists = False
else:
old_name, old_spec, old_unit, old_conf, old_count, old_avg, old_min, old_max, pc = cursor
old_avg = old_avg or 0
pc = pc or 0
old_min = old_min if old_min is not None else price
old_max = old_max if old_max is not None else price
exists = True
new_count = old_count + 1 if exists else 1
# ── 置信度 ──
if source == 'user_confirmed':
new_conf = 90
elif source == 'template':
new_conf = 50
elif exists and old_conf < 50:
# 一致性加速
spec_match = bool(spec and old_spec and spec == old_spec)
unit_match = bool(unit and old_unit and unit == old_unit)
if spec_match and unit_match:
boost = 10
elif unit_match:
boost = 5
else:
boost = 3
new_conf = min(50, old_conf + boost)
elif exists:
new_conf = old_conf # > 50 稳定不变
else:
new_conf = 10 # 新 OCR 记录
# ── 价格区间 ──
if price > 0:
new_pc = (pc if exists else 0) + 1
new_avg = ((old_avg * (new_pc - 1)) + price) / new_pc if exists else price
new_min = min(old_min, price) if exists else price
new_max = max(old_max, price) if exists else price
else:
new_avg = old_avg if exists else 0
new_min = old_min if exists else 0
new_max = old_max if exists else 0
new_pc = pc if exists else 0
# ── 写入 ──
conn = self._connect()
try:
if not exists:
conn.execute(
"INSERT INTO products (barcode, name, specification, unit, price, "
"source, confidence, usage_count, last_seen, updated_at, "
"avg_price, min_price, max_price, price_count) "
"VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
(barcode, name, spec, unit, price, source, new_conf, 1, now, now,
new_avg, new_min, new_max, new_pc))
log = f"记忆库新增: {barcode} {name} 源={source} 可信度={new_conf}"
else:
# 高可信度源全字段覆盖;低可信度仅填空
if source in ('template', 'user_confirmed') or new_conf > 50:
conn.execute(
"UPDATE products SET name=?, specification=?, unit=?, price=?, "
"source=?, confidence=?, usage_count=?, last_seen=?, updated_at=?, "
"avg_price=?, min_price=?, max_price=?, price_count=? WHERE barcode=?",
(name or old_name, spec or old_spec, unit or old_unit, price,
source, new_conf, new_count, now, now,
new_avg, new_min, new_max, new_pc, barcode))
else:
conn.execute(
"UPDATE products SET "
"name=CASE WHEN name='' THEN ? ELSE name END, "
"specification=CASE WHEN specification='' THEN ? ELSE specification END, "
"unit=CASE WHEN unit='' THEN ? ELSE unit END, "
"source=?, confidence=?, usage_count=?, last_seen=?, updated_at=?, "
"avg_price=?, min_price=?, max_price=?, price_count=? WHERE barcode=?",
(name, spec, unit, source, new_conf, new_count, now, now,
new_avg, new_min, new_max, new_pc, barcode))
log = f"记忆库更新: {barcode} 可信度{old_conf if exists else 0}{new_conf}"
if price > 0:
log += f" 均价{new_avg:.4f}({new_pc}次)"
conn.commit()
# 更新内存 dict(如果传入了)
if memory is not None and barcode in memory:
memory[barcode].update({
'confidence': new_conf, 'usage_count': new_count,
'avg_price': new_avg, 'min_price': new_min,
'max_price': new_max, 'price_count': new_pc,
'name': name or old_name,
'specification': spec or old_spec,
'unit': unit or old_unit,
})
if add_log:
add_log(log)
return log
finally:
conn.close()
def learn_from_products(self, products: List[Dict], source: str = 'ocr',
add_log: Callable = None) -> int:
"""批量学习 — 先批量预加载,再逐条处理,返回更新条数"""
barcodes = [str(p.get('barcode', '')) for p in products if p.get('barcode')]
memory = self.load_batch(barcodes)
count = 0
for p in products:
try:
result = self.learn_from_product(p, source, memory=memory, add_log=add_log)
if result:
count += 1
except Exception as e:
logger.warning(f"学习商品记忆失败: {e}")
return count
# ══════════════════════════════════════════════════════════════
# 记忆辅助 — OCR 补全
# ══════════════════════════════════════════════════════════════
def _price_anomaly(self, product: Dict, mem: Dict) -> bool:
"""价格异常:> 2倍偏差"""
price = float(product.get('price', 0))
avg = mem.get('avg_price', 0)
if not price or not avg:
return False
return price > avg * 2 or price < avg * 0.5
def fill_from_memory(self, barcode: str, ocr_result: Dict,
memory: Dict[str, Dict] = None) -> Tuple[Dict, str]:
"""用记忆库补全 OCR 缺失字段。返回 (补全后的dict, 日志字符串)"""
if memory:
mem = memory.get(barcode)
else:
mem = self.get_memory(barcode)
if not mem or mem.get('confidence', 0) < 10:
return ocr_result, ""
logs = []
result = dict(ocr_result)
conf = mem.get('confidence', 0)
has_spec = result.get('specification')
has_unit = result.get('unit')
price = float(result.get('price', 0))
if conf > 50 and not has_spec and mem.get('specification'):
result['specification'] = mem['specification']
logs.append(f"规格补全(可信{conf}): {barcode}{mem['specification']}")
elif not has_spec and mem.get('specification') and self._price_anomaly(result, mem):
result['specification'] = mem['specification']
logs.append(f"价格异常→规格补全: {barcode} 本次{price:.2f} vs 均价{mem['avg_price']:.2f}{mem['specification']}")
if conf > 50 and not has_unit and mem.get('unit'):
result['unit'] = mem['unit']
logs.append(f"单位补全(可信{conf}): {barcode}{mem['unit']}")
elif not has_unit and mem.get('unit') and self._price_anomaly(result, mem):
result['unit'] = mem['unit']
logs.append(f"价格异常→单位补全: {barcode}{mem['unit']}")
return result, "; ".join(logs)
def price_warning(self, barcode: str, price: float,
memory: Dict[str, Dict] = None) -> Optional[str]:
"""价格预警。> 50% 偏差告警"""
if memory:
mem = memory.get(barcode)
else:
mem = self.get_memory(barcode)
if not mem or not mem.get('avg_price'):
return None
avg = mem['avg_price']
min_p = mem.get('min_price', avg)
max_p = mem.get('max_price', avg)
pc = mem.get('price_count', 0)
if price > avg * 1.5 or price < avg * 0.5:
return (f"单价预警: {barcode} 本次{price:.4f}元 vs "
f"历史均价{avg:.4f} (范围{min_p:.4f}~{max_p:.4f}, {pc}次)")
return None
# ══════════════════════════════════════════════════════════════
# 手动编辑
# ══════════════════════════════════════════════════════════════
def update_memory(self, barcode: str, fields: Dict) -> bool:
barcode = str(barcode).strip()
if not barcode:
return False
allowed = {'name', 'specification', 'unit', 'price', 'confidence'}
updates = {k: v for k, v in fields.items() if k in allowed}
if not updates:
return False
now = datetime.now().isoformat()
set_clause = ', '.join(f"{k}=?" for k in updates)
values = list(updates.values())
extra_sql = ", source='user_confirmed'"
if 'confidence' not in updates:
extra_sql += ", confidence=90"
conn = self._connect()
try:
conn.execute(
f"UPDATE products SET {set_clause}{extra_sql}, updated_at=? WHERE barcode=?",
values + [now, barcode])
conn.commit()
return conn.total_changes > 0
finally:
conn.close()
def delete_memory(self, barcode: str) -> bool:
conn = self._connect()
try:
conn.execute("DELETE FROM products WHERE barcode=?", (str(barcode).strip(),))
conn.commit()
return conn.total_changes > 0
finally:
conn.close()
# ══════════════════════════════════════════════════════════════
# 云端同步
# ══════════════════════════════════════════════════════════════
def export_for_sync(self) -> Dict:
conn = self._connect()
try:
cursor = conn.execute(
"SELECT barcode, name, specification, unit, price, source, "
"confidence, usage_count, last_seen, avg_price, min_price, max_price, price_count "
"FROM products")
result = {}
for row in cursor.fetchall():
result[row[0]] = {
'name': row[1], 'specification': row[2], 'unit': row[3],
'price': row[4], 'source': row[5], 'confidence': row[6],
'usage_count': row[7], 'last_seen': row[8],
'avg_price': row[9], 'min_price': row[10],
'max_price': row[11], 'price_count': row[12],
}
return result
finally:
conn.close()
def import_from_sync(self, data: Dict) -> int:
now = datetime.now().isoformat()
count = 0
conn = self._connect()
try:
for barcode, info in data.items():
barcode = str(barcode).strip()
if not barcode:
continue
name = str(info.get('name', ''))
spec = str(info.get('specification', ''))
unit = str(info.get('unit', ''))
price = float(info.get('price', 0))
remote_source = str(info.get('source', 'ocr'))
remote_conf = int(info.get('confidence', 50))
remote_count = int(info.get('usage_count', 1))
remote_seen = str(info.get('last_seen', now))
remote_avg = float(info.get('avg_price', price))
remote_min = float(info.get('min_price', price))
remote_max = float(info.get('max_price', price))
remote_pc = int(info.get('price_count', 1))
row = conn.execute("SELECT confidence FROM products WHERE barcode=?",
(barcode,)).fetchone()
if row is None:
conn.execute(
"INSERT INTO products (barcode, name, specification, unit, price, "
"source, confidence, usage_count, last_seen, updated_at, "
"avg_price, min_price, max_price, price_count) "
"VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
(barcode, name, spec, unit, price, remote_source, remote_conf,
remote_count, remote_seen, now,
remote_avg, remote_min, remote_max, remote_pc))
count += 1
else:
local_conf = row[0]
if remote_conf > local_conf:
conn.execute(
"UPDATE products SET name=?, specification=?, unit=?, price=?, "
"source=?, confidence=?, usage_count=?, last_seen=?, updated_at=?, "
"avg_price=?, min_price=?, max_price=?, price_count=? WHERE barcode=?",
(name, spec, unit, price, remote_source, remote_conf,
remote_count, remote_seen, now,
remote_avg, remote_min, remote_max, remote_pc, barcode))
count += 1
elif remote_conf == local_conf:
conn.execute(
"UPDATE products SET "
"name=CASE WHEN name='' THEN ? ELSE name END, "
"specification=CASE WHEN specification='' THEN ? ELSE specification END, "
"unit=CASE WHEN unit='' THEN ? ELSE unit END, "
"usage_count=MAX(usage_count, ?), updated_at=? WHERE barcode=?",
(name, spec, unit, remote_count, now, barcode))
count += 1
conn.commit()
finally:
conn.close()
return count
def _export_memory_json(self, json_path=None):
"""导出记忆库为 JSON(兼容旧代码调用)"""
import os as _os
if json_path is None:
json_path = _os.path.join(_os.path.dirname(self.db_path), 'product_memory.json')
data = self.export_for_sync()
_os.makedirs(_os.path.dirname(json_path), exist_ok=True)
with open(json_path, 'w', encoding='utf-8') as f:
json.dump(data, f, ensure_ascii=False, indent=2)
return json_path
+88 -43
View File
@@ -16,7 +16,6 @@ from datetime import datetime
from ...config.settings import ConfigManager
from ..utils.log_utils import get_logger
from ..handlers.column_mapper import ColumnMapper
from ..utils.file_utils import (
ensure_dir,
get_file_extension,
@@ -49,7 +48,7 @@ class PurchaseOrderMerger:
# 修复ConfigParser对象没有get_path方法的问题
try:
# 获取输出目录
self.output_dir = config.get_path('Paths', 'output_folder', fallback='data/output', create=True) if hasattr(config, 'get_path') else os.path.abspath('data/output')
self.output_dir = config.get('Paths', 'output_folder', fallback='data/output')
# 确保目录存在
os.makedirs(self.output_dir, exist_ok=True)
@@ -96,8 +95,8 @@ class PurchaseOrderMerger:
Returns:
采购单文件路径列表
"""
# 采购单文件保存在result目录
result_dir = self.config.get_path('Paths', 'result_folder', fallback='data/result', create=True) if hasattr(self.config, 'get_path') else os.path.abspath('data/result')
# 采购单文件保存在data/result目录
result_dir = "data/result"
logger.info(f"搜索目录 {result_dir} 中的采购单Excel文件")
# 确保目录存在
@@ -141,46 +140,92 @@ class PurchaseOrderMerger:
logger.debug(f"Excel文件的列名: {df.columns.tolist()}")
# 处理特殊情况:检查是否需要读取指定行作为标题行
header_row_idx = ColumnMapper.detect_header_row(df, max_rows=5, min_matches=3)
if header_row_idx >= 0:
logger.info(f"检测到表头在第 {header_row_idx+1}")
# 使用此行作为列名,数据从下一行开始
header_row = df.iloc[header_row_idx].astype(str)
data_rows = df.iloc[header_row_idx+1:].reset_index(drop=True)
# 为每一列分配名称(避免重复的列名)
new_columns = []
for i, col in enumerate(header_row):
col_str = str(col)
if col_str == 'nan' or col_str == 'None' or pd.isna(col):
new_columns.append(f"Col_{i}")
else:
new_columns.append(col_str)
# 使用新列名创建新的DataFrame
data_rows.columns = new_columns
df = data_rows
logger.debug(f"重新构建的数据帧列名: {df.columns.tolist()}")
# 使用 ColumnMapper 统一查找列名(保留中文键名以兼容下游代码)
for header_row_idx in range(5): # 检查前5行
if len(df) <= header_row_idx:
continue
potential_header = df.iloc[header_row_idx].astype(str)
header_keywords = ['条码', '条形码', '商品条码', '商品名称', '规格', '单价', '数量', '金额', '单位', '必填']
matches = sum(1 for keyword in header_keywords if any(keyword in str(val) for val in potential_header.values))
if matches >= 3: # 如果至少匹配3个关键词,认为是表头
logger.info(f"检测到表头在第 {header_row_idx+1}")
# 使用此行作为列名,数据从下一行开始
header_row = potential_header
data_rows = df.iloc[header_row_idx+1:].reset_index(drop=True)
# 为每一列分配名称(避免重复的列名)
new_columns = []
for i, col in enumerate(header_row):
col_str = str(col)
if col_str == 'nan' or col_str == 'None' or pd.isna(col):
new_columns.append(f"Col_{i}")
else:
new_columns.append(col_str)
# 使用新列名创建新的DataFrame
data_rows.columns = new_columns
df = data_rows
logger.debug(f"重新构建的数据帧列名: {df.columns.tolist()}")
break
# 定义可能的列名映射
column_mapping = {
'条码': ['条码', '条形码', '商品条码', 'barcode', '商品条形码', '条形码', '商品条码', '商品编码', '商品编号', '条形码', '条码(必填)'],
'采购量': ['数量', '采购数量', '购买数量', '采购数量', '订单数量', '采购数量', '采购量(必填)', '采购量', '数量(必填)'],
'采购单价': ['单价', '价格', '采购单价', '销售价', '采购单价(必填)', '单价(必填)', '价格(必填)'],
'赠送量': ['赠送量', '赠品数量', '赠送数量', '赠品']
}
# 显示所有列名,用于调试
all_columns = df.columns.tolist()
logger.info(f"列名: {all_columns}")
standard_to_chinese = {
'barcode': '条码',
'quantity': '采购量',
'unit_price': '采购单价',
'gift_quantity': '赠送量',
}
# 映射实际的列名
mapped_columns = {}
for std_name, chinese_name in standard_to_chinese.items():
matched = ColumnMapper.find_column(all_columns, std_name)
if matched:
mapped_columns[chinese_name] = matched
logger.info(f"列名映射: {matched} -> {chinese_name}")
for target_col, possible_names in column_mapping.items():
for col in all_columns:
# 清理列名以进行匹配
col_str = str(col).strip()
# 直接匹配整个列名
if col_str in possible_names:
mapped_columns[target_col] = col
logger.info(f"直接匹配列名: {col_str} -> {target_col}")
break
# 移除列名中的空白字符进行比较
clean_col = re.sub(r'\s+', '', col_str)
for name in possible_names:
clean_name = re.sub(r'\s+', '', name)
# 完全匹配
if clean_col == clean_name:
mapped_columns[target_col] = col
logger.info(f"清理后匹配列名: {col_str} -> {target_col}")
break
# 部分匹配(列名包含关键词)
elif clean_name in clean_col:
mapped_columns[target_col] = col
logger.info(f"部分匹配列名: {col_str} -> {target_col}")
break
if target_col in mapped_columns:
break
# 如果没有找到匹配,尝试模糊匹配
if target_col not in mapped_columns:
for col in all_columns:
col_str = str(col).strip().lower()
for name in possible_names:
name_lower = name.lower()
if name_lower in col_str:
mapped_columns[target_col] = col
logger.info(f"模糊匹配列名: {col} -> {target_col}")
break
if target_col in mapped_columns:
break
# 如果找到了必要的列,重命名列
if mapped_columns:
rename_dict = {mapped_columns[key]: key for key in mapped_columns}
@@ -354,9 +399,9 @@ class PurchaseOrderMerger:
# 采购单价(必填)- E列(4)
output_sheet.write(r, price_col, float(row['采购单价']), price_style)
# 生成输出文件名,保存到result目录
# 生成输出文件名,保存到data/result目录
timestamp = datetime.now().strftime("%Y%m%d%H%M%S")
result_dir = self.config.get_path('Paths', 'result_folder', fallback='data/result', create=True) if hasattr(self.config, 'get_path') else os.path.abspath('data/result')
result_dir = "data/result"
os.makedirs(result_dir, exist_ok=True)
output_file = os.path.join(result_dir, f"合并采购单_{timestamp}.xls")
+208 -124
View File
@@ -25,12 +25,11 @@ from ..utils.file_utils import (
)
from ..utils.string_utils import (
clean_string,
clean_barcode,
extract_number,
format_barcode,
parse_monetary_string
format_barcode
)
from .converter import UnitConverter
from ..handlers.column_mapper import ColumnMapper
logger = get_logger(__name__)
@@ -40,20 +39,19 @@ class ExcelProcessor:
提取条码单价和数量并按照采购单模板的格式填充
"""
def __init__(self, config, product_db=None):
def __init__(self, config):
"""
初始化Excel处理器
Args:
config: 配置信息
product_db: 商品数据库实例可选由外部传入以共享
"""
self.config = config
# 修复ConfigParser对象没有get_path方法的问题
try:
# 获取输入和输出目录
self.output_dir = config.get_path('Paths', 'output_folder', fallback='data/output', create=True) if hasattr(config, 'get_path') else os.path.abspath('data/output')
self.output_dir = config.get('Paths', 'output_folder', fallback='data/output')
self.temp_dir = config.get('Paths', 'temp_folder', fallback='data/temp')
# 获取模板文件路径
@@ -75,18 +73,6 @@ class ExcelProcessor:
# 加载单位转换器和配置
self.unit_converter = UnitConverter()
# 商品记忆库
if product_db is not None:
self.product_db = product_db
else:
from ..db.product_db import ProductDatabase
db_path = config.get_path('Paths', 'product_db', fallback='data/product_cache.db') if hasattr(config, 'get_path') else 'data/product_cache.db'
tpl_folder = config.get('Paths', 'template_folder', fallback='templates')
item_data = config.get('Templates', 'item_data', fallback='商品资料.xlsx')
tpl_path = os.path.join(tpl_folder, item_data)
self.product_db = ProductDatabase(db_path, tpl_path)
logger.info(f"初始化ExcelProcessor完成,模板文件: {self.template_path}")
except Exception as e:
logger.error(f"初始化ExcelProcessor失败: {e}")
@@ -135,6 +121,48 @@ class ExcelProcessor:
logger.info(f"找到最新的Excel文件: {latest_file}")
return latest_file
def validate_barcode(self, barcode: Any) -> bool:
"""
验证条码是否有效
新增功能如果条码是"仓库"则返回False以避免误认为有效条码
Args:
barcode: 条码值
Returns:
条码是否有效
"""
# 处理"仓库"特殊情况
if isinstance(barcode, str) and barcode.strip() in ["仓库", "仓库全名"]:
logger.warning(f"条码为仓库标识: {barcode}")
return False
# 清理条码格式
barcode_clean = clean_barcode(barcode)
# 对特定的错误条码进行修正(开头改6开头)
if len(barcode_clean) > 8 and barcode_clean.startswith('5') and not barcode_clean.startswith('53'):
barcode_clean = '6' + barcode_clean[1:]
logger.info(f"修正条码前缀 5->6: {barcode} -> {barcode_clean}")
# 验证条码长度
if len(barcode_clean) < 8 or len(barcode_clean) > 13:
logger.warning(f"条码长度异常: {barcode_clean}, 长度={len(barcode_clean)}")
return False
# 验证条码是否全为数字
if not barcode_clean.isdigit():
logger.warning(f"条码包含非数字字符: {barcode_clean}")
return False
# 对于序号9的特殊情况,允许其条码格式
if barcode_clean == "5321545613":
logger.info(f"特殊条码验证通过: {barcode_clean}")
return True
logger.debug(f"条码验证通过: {barcode_clean}")
return True
def extract_barcode(self, df: pd.DataFrame) -> List[str]:
"""
从数据帧中提取条码列名
@@ -145,7 +173,12 @@ class ExcelProcessor:
Returns:
可能的条码列名列表
"""
possible_barcode_columns = ColumnMapper.STANDARD_COLUMNS['barcode']
possible_barcode_columns = [
'条码', '条形码', '商品条码', '商品条形码',
'商品编码', '商品编号', '条形码', '条码(必填)',
'barcode', 'Barcode', '编码', '条形码', '电脑条码',
'条码ID', '产品条码', 'BarCode'
]
found_columns = []
@@ -269,11 +302,25 @@ class ExcelProcessor:
if amt is None:
is_amt_gift = True
elif isinstance(amt, str):
parsed = parse_monetary_string(amt)
is_amt_gift = (parsed is None or parsed == 0.0)
s = amt.strip()
if s == '' or s.lower() == 'o' or s == '0' or s == '':
is_amt_gift = True
else:
amt_clean = re.sub(r'[^\d\.,]', '', s)
if ',' in amt_clean and '.' not in amt_clean:
amt_clean = amt_clean.replace(',', '.')
elif ',' in amt_clean and '.' in amt_clean:
amt_clean = amt_clean.replace(',', '')
if amt_clean:
try:
is_amt_gift = float(amt_clean) == 0.0
except ValueError:
pass
else:
parsed = parse_monetary_string(amt)
is_amt_gift = (parsed is not None and parsed == 0.0)
try:
is_amt_gift = float(amt) == 0.0
except (ValueError, TypeError):
pass
if is_amt_gift:
product['is_gift'] = True
except Exception:
@@ -376,78 +423,35 @@ class ExcelProcessor:
# 如果数量为0但单价和金额都存在,计算数量 = 金额/单价
if (product['quantity'] == 0 or product['quantity'] is None) and product['price'] > 0 and product['amount']:
try:
amount = parse_monetary_string(product['amount'])
if amount is not None and amount > 0:
# 确保金额是数字
if isinstance(product['amount'], str):
# 移除货币符号和非数字字符,保留数字、小数点和逗号
amount_str = re.sub(r'[^\d\.,]', '', product['amount'].strip())
# 替换逗号为小数点(如果逗号作为小数分隔符)
if ',' in amount_str and '.' not in amount_str:
amount_str = amount_str.replace(',', '.')
# 处理既有逗号又有小数点的情况(通常逗号是千位分隔符)
elif ',' in amount_str and '.' in amount_str:
amount_str = amount_str.replace(',', '')
amount = float(amount_str)
else:
amount = float(product['amount'])
# 计算数量
if amount > 0:
quantity = amount / product['price']
logger.info(f"数量为空或为0,通过金额({amount})和单价({product['price']})计算得出数量: {quantity}")
product['quantity'] = quantity
except Exception as e:
logger.warning(f"通过金额和单价计算数量失败: {e}")
# 应用记忆库补全
product = self._apply_memory(product)
products.append(product)
except Exception as e:
logger.error(f"提取第{idx+1}行商品信息时出错: {e}", exc_info=True)
continue
logger.info(f"提取到 {len(products)} 个商品信息")
return products
def _apply_memory(self, product: Dict) -> Dict:
"""查记忆库,补全 OCR 缺失/错误的字段"""
barcode = product.get('barcode', '')
if not barcode:
return product
try:
memory = self.product_db.get_memory(barcode)
except Exception:
return product
if memory is None or memory.get('confidence', 0) < 80:
return product
# 补全规格
ocr_spec = product.get('specification', '')
mem_spec = memory.get('specification', '') or ''
if mem_spec and (not ocr_spec or self._is_spec_suspicious(ocr_spec)):
product['specification'] = mem_spec
logger.info(f"记忆修正规格: {barcode} '{ocr_spec}' -> '{mem_spec}'")
# 补全名称
ocr_name = product.get('name', '')
mem_name = memory.get('name', '') or ''
if mem_name and not ocr_name:
product['name'] = mem_name
logger.info(f"记忆修正名称: {barcode} -> '{mem_name}'")
# 补全单位
ocr_unit = product.get('unit', '')
mem_unit = memory.get('unit', '') or ''
if mem_unit and not ocr_unit:
product['unit'] = mem_unit
logger.info(f"记忆修正单位: {barcode} -> '{mem_unit}'")
# 不改数量和单价(每单不同)
return product
def _is_spec_suspicious(self, spec: str) -> bool:
"""检测规格是否像 OCR 垃圾"""
if not spec:
return True
# IL*12I 和 1 混淆)
if re.search(r'^[Ii][Ll*]', spec):
return True
# 4.51*4L 被识别为 1
if re.search(r'\d+\.\d+1\*\d+', spec):
return True
# 包含非常规字符(排除常见规格字符)
if re.search(r'[^\d.*xX\-LlKkGgMm升毫瓶桶盒箱件提\s]', spec):
return True
return False
def fill_template(self, products: List[Dict], output_file_path: str) -> bool:
"""
填充采购单模板
@@ -490,8 +494,21 @@ class ExcelProcessor:
# 如果数量为0但单价和金额都存在,计算数量 = 金额/单价
if (quantity == 0 or quantity is None) and price > 0 and amount:
try:
amount = parse_monetary_string(amount)
if amount is not None and amount > 0:
# 确保金额是数字
if isinstance(amount, str):
# 移除货币符号和非数字字符,保留数字、小数点和逗号
amount_str = re.sub(r'[^\d\.,]', '', amount.strip())
# 替换逗号为小数点(如果逗号作为小数分隔符)
if ',' in amount_str and '.' not in amount_str:
amount_str = amount_str.replace(',', '.')
# 处理既有逗号又有小数点的情况(通常逗号是千位分隔符)
elif ',' in amount_str and '.' in amount_str:
amount_str = amount_str.replace(',', '')
amount = float(amount_str)
else:
amount = float(amount)
# 计算数量
if amount > 0:
quantity = amount / price
logger.info(f"数量为空或为0,通过金额({amount})和单价({price})计算得出数量: {quantity}")
product['quantity'] = quantity
@@ -588,16 +605,72 @@ class ExcelProcessor:
return False
def _find_header_row(self, df: pd.DataFrame) -> Optional[int]:
"""自动识别表头行,委托给 ColumnMapper.detect_header_row"""
result = ColumnMapper.detect_header_row(df, max_rows=30)
if result >= 0:
logger.info(f"找到表头行: 第{result+1}")
return result
# 回退:找第一个非空行
"""
自动识别表头行
通过多种规则识别表头
1. 检查行是否包含典型的表头关键词条码商品名称数量等
2. 检查是否是第一个非空行
3. 检查行是否有较多的字符串类型单元格表头通常是字符串
Args:
df: 数据帧
Returns:
表头行索引如果未找到则返回None
"""
header_keywords = [
'条码', '条形码', '商品条码', '商品名称', '名称', '数量', '单位', '单价',
'规格', '商品编码', '采购数量', '采购单位', '商品', '品名',
'金额', '小计', '总计', '合计', '合计金额'
]
# 存储每行的匹配分数
row_scores = []
max_rows_to_check = min(30, len(df))
for row in range(max_rows_to_check):
row_data = df.iloc[row]
score = 0
# 检查1: 关键词匹配
for cell in row_data:
if isinstance(cell, str):
cell_clean = str(cell).strip().lower()
for keyword in header_keywords:
if keyword.lower() in cell_clean:
score += 5 # 每匹配一个关键词加5分
# 检查2: 非空单元格比例
non_empty_cells = row_data.count()
if non_empty_cells / len(row_data) > 0.5: # 如果超过一半的单元格有内容
score += 2
# 检查3: 字符串类型单元格比例
string_cells = sum(1 for cell in row_data if isinstance(cell, str))
if string_cells / len(row_data) > 0.5: # 如果超过一半的单元格是字符串
score += 3
row_scores.append((row, score))
# 日志记录每行的评分情况
logger.debug(f"{row+1}行评分: {score},内容: {row_data.values}")
# 按评分排序
row_scores.sort(key=lambda x: x[1], reverse=True)
# 如果最高分达到一定阈值,认为是表头
if row_scores and row_scores[0][1] >= 5:
best_row = row_scores[0][0]
logger.info(f"找到可能的表头行: 第{best_row+1}行,评分: {row_scores[0][1]}")
return best_row
# 如果没有找到明确的表头,尝试找第一个非空行
for row in range(len(df)):
if df.iloc[row].notna().sum() > 3:
if df.iloc[row].notna().sum() > 3: # 至少有3个非空单元格
logger.info(f"未找到明确表头,使用第一个有效行: 第{row+1}")
return row
logger.warning("无法识别表头行")
return None
@@ -660,22 +733,14 @@ class ExcelProcessor:
logger.warning("未提取到有效商品信息")
return None
# 生成输出文件名,保存到result目录
# 生成输出文件名,保存到data/result目录
file_name = os.path.splitext(os.path.basename(file_path))[0]
result_dir = self.config.get_path('Paths', 'result_folder', fallback='data/result', create=True) if hasattr(self.config, 'get_path') else os.path.abspath('data/result')
result_dir = "data/result"
os.makedirs(result_dir, exist_ok=True)
output_file = os.path.join(result_dir, f"采购单_{file_name}.xls")
# 填充模板并保存
if self.fill_template(products, output_file):
# 从处理结果中学习商品记忆
try:
self.product_db.learn_from_products(products, source='ocr')
self.product_db._export_memory_json()
logger.info(f"已从处理结果学习 {len(products)} 条商品记忆")
except Exception as e:
logger.warning(f"学习商品记忆失败: {e}")
# 记录已处理文件
self.processed_files[file_path] = output_file
self._save_processed_files()
@@ -724,32 +789,51 @@ class ExcelProcessor:
"""
# 提取有用的列
barcode_cols = self.extract_barcode(df)
# 如果没有找到条码列,无法继续处理
if not barcode_cols:
logger.error("未找到条码列,无法处理")
return {}
# 使用 ColumnMapper 统一查找列名
mapped_columns = {'barcode': barcode_cols[0]}
# 定义列名映射
column_mapping = {
'name': ['商品名称', '名称', '品名', '商品', '商品名', '商品或服务名称', '品项名', '产品名称', '品项', '名 称'],
'specification': ['规格', '规格型号', '型号', '商品规格', '产品规格', '包装规格','规 格'],
'quantity': ['数量', '采购数量', '购买数量', '采购数量', '订单数量', '数量(必填)', '入库数', '入库数量','数 量'],
'unit': ['单位', '采购单位', '计量单位', '单位(必填)', '单位名称', '计价单位','单 位'],
'price': ['单价', '价格', '采购单价', '销售价', '进货价', '单价(必填)', '采购价', '参考价', '入库单价','单 价'],
'amount': ['金额', '小计', '总价', '合计金额', '小计金额', '金额(元)', '金额合计', '合计', '总额']
}
# 映射列名到标准名称
mapped_columns = {'barcode': barcode_cols[0]} # 使用第一个找到的条码列
# 记录列名映射详情
logger.info(f"使用条码列: {mapped_columns['barcode']}")
# 内部键名 -> 标准列名映射 (processor.py 使用 price/amount 作为内部键名)
field_map = [
('name', 'name'),
('specification', 'specification'),
('quantity', 'quantity'),
('unit', 'unit'),
('price', 'unit_price'),
('amount', 'total_price'),
]
for internal_key, standard_name in field_map:
matched = ColumnMapper.find_column(list(df.columns), standard_name)
if matched:
mapped_columns[internal_key] = matched
logger.info(f"找到{internal_key}列: {matched}")
for target, possible_names in column_mapping.items():
for col in df.columns:
col_str = str(col).strip()
for name in possible_names:
if col_str == name:
mapped_columns[target] = col
logger.info(f"找到{target}列: {col}")
break
if target in mapped_columns:
break
# 如果没有找到精确匹配,尝试部分匹配
if target not in mapped_columns:
for col in df.columns:
col_str = str(col).strip().lower()
for name in possible_names:
if name.lower() in col_str:
mapped_columns[target] = col
logger.info(f"找到{target}列(部分匹配): {col}")
break
if target in mapped_columns:
break
return mapped_columns
def infer_specification_from_name(self, product_name: str) -> Tuple[Optional[str], Optional[int]]:
+50 -8
View File
@@ -9,7 +9,6 @@ import logging
from typing import Dict, Any, Optional, List, Tuple, Union
from ..utils.log_utils import get_logger
from ..utils.string_utils import parse_monetary_string
logger = get_logger(__name__)
@@ -157,8 +156,23 @@ class ProductValidator:
if price_str in ["赠品", "gift", "赠送", "0", ""]:
return True, 0.0, True, None
price_value = parse_monetary_string(price_str)
if price_value is None:
# 去除空白和非数字字符(保留小数点和逗号)
price_clean = re.sub(r'[^\d\.,]', '', price_str)
# 处理小数点和逗号
if ',' in price_clean and '.' not in price_clean:
# 如果只有逗号没有小数点,将逗号视为小数点
price_clean = price_clean.replace(',', '.')
elif ',' in price_clean and '.' in price_clean:
# 如果既有逗号又有小数点,移除逗号(认为逗号是千位分隔符)
price_clean = price_clean.replace(',', '')
if not price_clean:
return False, 0.0, True, "单价不包含数字,视为赠品"
try:
price_value = float(price_clean)
except ValueError:
return False, 0.0, True, f"无法将单价 '{price}' 转换为数字,视为赠品"
else:
# 尝试直接转换
@@ -215,9 +229,28 @@ class ProductValidator:
amount = product.get('amount', None)
try:
is_amount_gift = False
parsed_amount = parse_monetary_string(amount)
if parsed_amount is None or parsed_amount == 0.0:
if amount is None:
is_amount_gift = True
elif isinstance(amount, str):
s = amount.strip()
if s == '' or s.lower() == 'o' or s == '0':
is_amount_gift = True
else:
amt_clean = re.sub(r'[^\d\.,]', '', s)
if ',' in amt_clean and '.' not in amt_clean:
amt_clean = amt_clean.replace(',', '.')
elif ',' in amt_clean and '.' in amt_clean:
amt_clean = amt_clean.replace(',', '')
if amt_clean:
try:
is_amount_gift = float(amt_clean) == 0.0
except ValueError:
pass
else:
try:
is_amount_gift = float(amount) == 0.0
except (ValueError, TypeError):
pass
if is_amount_gift:
validated_product['is_gift'] = True
except Exception:
@@ -236,9 +269,18 @@ class ProductValidator:
if fixed_price > 0 and amount is not None:
try:
# 确保金额是数字
amount = parse_monetary_string(amount)
if amount is None:
raise ValueError("无法解析金额")
if isinstance(amount, str):
# 移除货币符号和非数字字符,保留数字、小数点和逗号
amount_str = re.sub(r'[^\d\.,]', '', amount.strip())
# 替换逗号为小数点(如果逗号作为小数分隔符)
if ',' in amount_str and '.' not in amount_str:
amount_str = amount_str.replace(',', '.')
# 处理既有逗号又有小数点的情况(通常逗号是千位分隔符)
elif ',' in amount_str and '.' in amount_str:
amount_str = amount_str.replace(',', '')
amount = float(amount_str)
else:
amount = float(amount)
# 计算数量 = 金额 / 单价
if amount > 0:
+10 -116
View File
@@ -4,7 +4,6 @@
提供列名映射和转换功能支持不同供应商的列名标准化
"""
import re
import pandas as pd
from typing import Dict, Any, Optional, List, Union
from ...core.utils.log_utils import get_logger
@@ -18,47 +17,18 @@ class ColumnMapper:
提供列名标准化功能将不同供应商的列名映射到标准列名
"""
# 标准列名定义(所有列名别名的唯一来源)
# 标准列名定义
STANDARD_COLUMNS = {
'barcode': [
'条码', '条形码', '商品条码', '商品条形码', '产品条码', '商品编码',
'商品编', '条码(必填)', '电脑条码', '条码ID',
'barcode', 'Barcode', 'BarCode', 'code', '编码',
],
'name': [
'商品名称', '产品名称', '名称', '商品', '产品', '商品名', '品名',
'品项名', '商品或服务名称', '品项', '名 称',
'name', 'product_name',
],
'specification': [
'规格', '规格型号', '型号', '商品规格', '产品规格', '包装规格', '规 格',
'specification', 'spec', 'model',
],
'quantity': [
'数量', '采购量', '订货数量', '订单量', '需求量', '采购数量', '购买数量',
'订单数量', '数量(必填)', '采购量(必填)', '入库数', '入库数量', '数 量',
'quantity', 'qty',
],
'unit': [
'单位', '计量单位', '采购单位', '单位(必填)', '单位名称', '计价单位', '单 位',
'unit', 'units',
],
'unit_price': [
'单价', '价格', '采购单价', '进货价', '销售价', '采购价', '参考价',
'入库单价', '单价(必填)', '采购单价(必填)', '价格(必填)', '单 价',
'unit_price', 'price',
],
'total_price': [
'总价', '金额', '小计', '合计金额', '小计金额', '金额(元)',
'金额合计', '合计', '总额',
'total_price', 'total', 'amount',
],
'gift_quantity': [
'赠送量', '赠品数量', '赠送数量', '赠品',
],
'barcode': ['条码', '条形码', '商品条码', '产品条码', '条码(必填)', 'barcode', 'code'],
'name': ['商品名称', '产品名称', '名称', '商品', '产品', 'name', 'product_name'],
'specification': ['规格', '规格型', '型号', 'specification', 'spec', 'model'],
'quantity': ['数量', '采购量', '订货数量', '订单量', '需求量', 'quantity', 'qty', '采购量(必填)'],
'unit': ['单位', '计量单位', 'unit', 'units'],
'unit_price': ['单价', '价格', '采购单价', '进货价', 'unit_price', 'price', '采购单价(必填)'],
'total_price': ['总价', '金额', '小计', 'total_price', 'total', 'amount'],
'category': ['类别', '分类', '商品类别', 'category', 'type'],
'brand': ['品牌', '商标', 'brand'],
'supplier': ['供应商', '供货商', 'supplier', 'vendor'],
'supplier': ['供应商', '供货商', 'supplier', 'vendor']
}
def __init__(self, mapping_config: Optional[Dict[str, Any]] = None):
@@ -303,80 +273,4 @@ class ColumnMapper:
if col in df.columns and not pd.api.types.is_numeric_dtype(df[col]):
result['warnings'].append(f"'{col}' 不是数值类型")
return result
@classmethod
def find_column(cls, columns: List[str], standard_name: str) -> Optional[str]:
"""在列名列表中查找匹配标准列名的列
匹配策略: 精确匹配 忽略空白匹配 子串匹配
Args:
columns: 实际列名列表
standard_name: 标准列名 (STANDARD_COLUMNS 的键)
Returns:
匹配到的实际列名未找到返回 None
"""
candidates = cls.STANDARD_COLUMNS.get(standard_name, [])
if not candidates:
return None
columns_str = [str(c) for c in columns]
# 精确匹配
for col in columns_str:
col_clean = col.strip()
for candidate in candidates:
if col_clean == candidate:
return col
# 忽略空白匹配
for col in columns_str:
col_clean = re.sub(r'\s+', '', col.strip())
for candidate in candidates:
if col_clean == re.sub(r'\s+', '', candidate):
return col
# 子串匹配 (候选名包含在列名中)
for col in columns_str:
col_lower = col.strip().lower()
for candidate in candidates:
if candidate.lower() in col_lower:
return col
return None
@staticmethod
def detect_header_row(df: pd.DataFrame, max_rows: int = 10, min_matches: int = 3) -> int:
"""检测表头所在行
扫描前 max_rows 返回包含最多关键词匹配的行索引
Args:
df: 数据框
max_rows: 最大扫描行数
min_matches: 最少关键词匹配数
Returns:
表头行索引未找到返回 -1
"""
header_keywords = [
'条码', '条形码', '商品条码', '商品名称', '名称', '规格',
'单价', '数量', '金额', '单位', '必填', '编码',
]
best_row = -1
best_matches = 0
for row_idx in range(min(max_rows, len(df))):
row_values = df.iloc[row_idx].astype(str)
matches = sum(
1 for kw in header_keywords
if any(kw in str(val) for val in row_values.values)
)
if matches >= min_matches and matches > best_matches:
best_matches = matches
best_row = row_idx
return best_row
return result
+2 -2
View File
@@ -19,7 +19,7 @@ def _split_quantity_unit(df: pd.DataFrame, source: str, dictionary: Optional[Dic
try:
nums.append(float(v))
units.append(unit_synonyms.get(default_unit, default_unit))
except Exception:
except:
nums.append(0.0)
units.append(unit_synonyms.get(default_unit, default_unit))
df["quantity"] = nums
@@ -44,7 +44,7 @@ def _extract_spec_from_name(df: pd.DataFrame, source: str, dictionary: Optional[
if m and len(m.groups()) >= 2:
try:
qty = int(m.group(len(m.groups())))
except Exception:
except:
qty = None
specs.append(s)
packs.append(qty)
+13 -18
View File
@@ -4,40 +4,37 @@
提供百度OCR API的访问和调用功能
"""
import os
import time
import base64
import requests
from typing import Dict, Optional, Union
import logging
from typing import Dict, Optional, Any, Union
from ...config.settings import ConfigManager
from ..utils.log_utils import get_logger
logger = get_logger(__name__)
# Token 过期相关常量
_DEFAULT_TOKEN_LIFETIME = 30 * 24 * 3600 # 30天(秒)
_TOKEN_EARLY_EXPIRY = 3600 # 提前1小时刷新(秒)
class TokenManager:
"""
令牌管理类负责获取和刷新百度API访问令牌
"""
def __init__(self, api_key: str, secret_key: str, max_retries: int = 3, retry_delay: int = 2, token_url: str = None):
def __init__(self, api_key: str, secret_key: str, max_retries: int = 3, retry_delay: int = 2):
"""
初始化令牌管理器
Args:
api_key: 百度API Key
secret_key: 百度Secret Key
max_retries: 最大重试次数
retry_delay: 重试延迟
token_url: 令牌获取地址
"""
self.api_key = api_key
self.secret_key = secret_key
self.max_retries = max_retries
self.retry_delay = retry_delay
self.token_url = token_url or 'https://aip.baidubce.com/oauth/2.0/token'
self.access_token = None
self.token_expiry = 0
@@ -72,7 +69,7 @@ class TokenManager:
Returns:
新的访问令牌如果获取失败则返回None
"""
url = self.token_url
url = "https://aip.baidubce.com/oauth/2.0/token"
params = {
"grant_type": "client_credentials",
"client_id": self.api_key,
@@ -87,7 +84,7 @@ class TokenManager:
if "access_token" in result:
self.access_token = result["access_token"]
# 设置令牌过期时间(默认30天,提前1小时过期以确保安全)
self.token_expiry = time.time() + result.get("expires_in", _DEFAULT_TOKEN_LIFETIME) - _TOKEN_EARLY_EXPIRY
self.token_expiry = time.time() + result.get("expires_in", 2592000) - 3600
logger.info("成功获取访问令牌")
return self.access_token
@@ -144,11 +141,10 @@ class BaiduOCRClient:
# 创建令牌管理器
self.token_manager = TokenManager(
self.api_key,
self.secret_key,
self.max_retries,
self.retry_delay,
token_url=config.get('API', 'token_url', fallback='https://aip.baidubce.com/oauth/2.0/token')
self.api_key,
self.secret_key,
self.max_retries,
self.retry_delay
)
# 验证API配置
@@ -303,8 +299,7 @@ class BaiduOCRClient:
logger.error(f"无法从结果中提取有效的request_id: {request_id_or_result}")
return None
base_url = self.config.get('API', 'form_ocr_url', fallback='https://aip.baidubce.com/rest/2.0/solution/v1/form_ocr/get_request_result')
url = f"{base_url}?access_token={access_token}"
url = f"https://aip.baidubce.com/rest/2.0/solution/v1/form_ocr/get_request_result?access_token={access_token}"
payload = {
'request_id': request_id,
+16 -12
View File
@@ -5,11 +5,15 @@
"""
import os
import sys
import time
import json
import base64
from datetime import datetime
from concurrent.futures import ThreadPoolExecutor
from typing import Dict, List, Optional, Tuple, Callable
from typing import Dict, List, Optional, Tuple, Union, Any, Callable
from ...config.settings import ConfigManager
from ..utils.log_utils import get_logger
from ..utils.file_utils import (
ensure_dir,
@@ -114,9 +118,9 @@ class OCRProcessor:
# 修复ConfigParser对象没有get_path方法的问题
try:
# 获取输入和输出目录
self.input_folder = config.get_path('Paths', 'input_folder', fallback='data/input', create=True) if hasattr(config, 'get_path') else os.path.abspath('data/input')
self.output_folder = config.get_path('Paths', 'output_folder', fallback='data/output', create=True) if hasattr(config, 'get_path') else os.path.abspath('data/output')
self.temp_folder = config.get_path('Paths', 'temp_folder', fallback='data/temp', create=True) if hasattr(config, 'get_path') else os.path.abspath('data/temp')
self.input_folder = config.get('Paths', 'input_folder', fallback='data/input')
self.output_folder = config.get('Paths', 'output_folder', fallback='data/output')
self.temp_folder = config.get('Paths', 'temp_folder', fallback='data/temp')
# 确保目录存在
os.makedirs(self.input_folder, exist_ok=True)
@@ -173,9 +177,9 @@ class OCRProcessor:
skip_existing = True
try:
skip_existing = self.config.getboolean('Performance', 'skip_existing', fallback=True)
except Exception:
except:
pass
if skip_existing:
# 过滤已处理的文件
unprocessed_files = self.record_manager.get_unprocessed_files(image_files)
@@ -210,7 +214,7 @@ class OCRProcessor:
max_size_mb = 4.0
try:
max_size_mb = float(self.config.get('File', 'max_file_size_mb', fallback='4.0'))
except Exception:
except:
pass
if not is_file_size_valid(image_path, max_size_mb):
@@ -237,7 +241,7 @@ class OCRProcessor:
skip_existing = True
try:
skip_existing = self.config.getboolean('Performance', 'skip_existing', fallback=True)
except Exception:
except:
pass
# 如果需要跳过已处理的文件
@@ -253,7 +257,7 @@ class OCRProcessor:
excel_extension = '.xlsx'
try:
excel_extension = self.config.get('File', 'excel_extension', fallback='.xlsx')
except Exception:
except:
pass
# 生成输出文件路径
@@ -343,13 +347,13 @@ class OCRProcessor:
if batch_size is None:
try:
batch_size = self.config.getint('Performance', 'batch_size', fallback=5)
except Exception:
except:
batch_size = 5
if max_workers is None:
try:
max_workers = self.config.getint('Performance', 'max_workers', fallback=4)
except Exception:
except:
max_workers = 4
# 获取未处理的图片
+3 -31
View File
@@ -8,11 +8,8 @@ from abc import ABC, abstractmethod
from typing import Dict, Any, Optional, List
from pathlib import Path
import logging
import pandas as pd
from ...core.utils.log_utils import get_logger
logger = get_logger(__name__)
logger = logging.getLogger(__name__)
class BaseProcessor(ABC):
@@ -109,40 +106,15 @@ class BaseProcessor(ABC):
def get_output_filename(self, input_file: Path, suffix: str = "_processed") -> str:
"""生成输出文件名
Args:
input_file: 输入文件路径
suffix: 文件名后缀
Returns:
输出文件名
"""
return f"{input_file.stem}{suffix}{input_file.suffix}"
def _read_excel_safely(self, file_path: Path, **kwargs) -> pd.DataFrame:
"""根据扩展名选择合适的读取引擎
Args:
file_path: 文件路径
**kwargs: 传递给 pd.read_excel 的参数
Returns:
DataFrame
Raises:
Exception: 读取失败时抛出
"""
suffix = file_path.suffix.lower()
if suffix == '.xlsx':
return pd.read_excel(file_path, engine='openpyxl', **kwargs)
elif suffix == '.xls':
try:
return pd.read_excel(file_path, engine='xlrd', **kwargs)
except Exception as e:
self.logger.warning(f"读取xls失败,可能缺少xlrd: {e}")
raise
else:
return pd.read_excel(file_path, **kwargs)
def log_processing_start(self, input_file: Path):
"""记录处理开始日志"""
@@ -12,9 +12,6 @@ from pathlib import Path
from ..base import BaseProcessor
from ...utils.log_utils import get_logger
from ...handlers.rule_engine import apply_rules
from ...handlers.column_mapper import ColumnMapper
from ...handlers.data_cleaner import DataCleaner
from ...handlers.calculator import DataCalculator
logger = get_logger(__name__)
@@ -240,9 +237,57 @@ class GenericSupplierProcessor(BaseProcessor):
self.logger.error(f"读取数据失败: {e}")
return None
def _read_excel_safely(self, file_path: Path, **kwargs) -> pd.DataFrame:
"""根据扩展名选择合适的读取引擎并带有回退"""
suffix = file_path.suffix.lower()
try:
if suffix == '.xlsx':
return pd.read_excel(file_path, engine='openpyxl', **kwargs)
elif suffix == '.xls':
try:
return pd.read_excel(file_path, engine='xlrd', **kwargs)
except Exception as e:
self.logger.warning(f"读取xls失败,可能缺少xlrd: {e}")
raise
else:
return pd.read_excel(file_path, **kwargs)
except Exception as e:
self.logger.error(f"读取Excel失败: {file_path} - {e}")
raise
def _find_header_row(self, df: pd.DataFrame) -> Optional[int]:
result = ColumnMapper.detect_header_row(df, max_rows=30)
return result if result >= 0 else None
try:
header_keywords = [
'条码','条形码','商品编码','商品名称','名称','数量','单位','单价','规格',
'金额','小计','总计','合计','合计金额'
]
scores = []
rows_to_check = min(30, len(df))
for r in range(rows_to_check):
row = df.iloc[r]
score = 0
for cell in row:
if isinstance(cell, str):
s = cell.strip().lower()
for kw in header_keywords:
if kw.lower() in s:
score += 5
non_empty = row.count()
if non_empty / max(1, len(row)) > 0.5:
score += 2
str_count = sum(1 for c in row if isinstance(c, str))
if str_count / max(1, len(row)) > 0.5:
score += 3
scores.append((r, score))
scores.sort(key=lambda x: x[1], reverse=True)
if scores and scores[0][1] >= 5:
return scores[0][0]
for r in range(len(df)):
if df.iloc[r].notna().sum() > 3:
return r
return None
except Exception:
return None
def _apply_column_mapping(self, df: pd.DataFrame) -> Optional[pd.DataFrame]:
"""应用列映射
@@ -280,33 +325,131 @@ class GenericSupplierProcessor(BaseProcessor):
return None
def _apply_data_cleaning(self, df: pd.DataFrame) -> Optional[pd.DataFrame]:
"""应用数据清洗规则,委托给 DataCleaner"""
"""应用数据清洗规则
Args:
df: 映射后的数据
Returns:
清洗后的数据或None
"""
if not self.cleaning_rules:
self.logger.info("没有数据清洗规则")
return df
try:
cleaner = DataCleaner()
df_cleaned = df.copy()
for rule in self.cleaning_rules:
cleaner.add_rule(rule.get('type'), **{k: v for k, v in rule.items() if k != 'type'})
result = cleaner.clean(df)
self.logger.info(f"数据清洗完成,数据形状: {result.shape}")
return result
rule_type = rule.get('type')
if rule_type == 'remove_rows':
# 删除行
condition = rule.get('condition')
if condition:
before_count = len(df_cleaned)
df_cleaned = df_cleaned.query(condition)
after_count = len(df_cleaned)
self.logger.info(f"删除行规则: {condition}, 删除数量: {before_count - after_count}")
elif rule_type == 'fill_na':
# 填充空值,兼容单列和多列
columns = rule.get('columns') or [rule.get('column')] if rule.get('column') else []
value = rule.get('value', 0)
for col in columns:
if col and col in df_cleaned.columns:
na_count = df_cleaned[col].isna().sum()
df_cleaned[col] = df_cleaned[col].fillna(value)
self.logger.info(f"填充空值: {col} -> {value}, 填充数量: {na_count}")
elif rule_type == 'convert_type':
# 类型转换,兼容单列和多列
target_type = rule.get('target_type', 'float')
columns = rule.get('columns') or [rule.get('column')] if rule.get('column') else []
for col in columns:
if col and col in df_cleaned.columns:
try:
if target_type == 'float':
df_cleaned[col] = pd.to_numeric(df_cleaned[col], errors='coerce')
elif target_type == 'int':
df_cleaned[col] = pd.to_numeric(df_cleaned[col], errors='coerce').astype('Int64')
self.logger.info(f"类型转换: {col} -> {target_type}")
except Exception as e:
self.logger.warning(f"类型转换失败: {col} -> {target_type}: {e}")
else:
self.logger.warning(f"未知的清洗规则类型: {rule_type}")
self.logger.info(f"数据清洗完成,数据形状: {df_cleaned.shape}")
return df_cleaned
except Exception as e:
self.logger.error(f"数据清洗失败: {e}")
return None
def _apply_calculations(self, df: pd.DataFrame) -> Optional[pd.DataFrame]:
"""应用计算处理,委托给 DataCalculator"""
"""应用计算处理
Args:
df: 清洗后的数据
Returns:
计算后的数据或None
"""
if not self.calculations:
self.logger.info("没有计算规则")
return df
try:
calculator = DataCalculator()
for calc in self.calculations:
calculator.add_rule(calc.get('type'), **{k: v for k, v in calc.items() if k != 'type'})
result = calculator.calculate(df)
self.logger.info(f"计算处理完成,数据形状: {result.shape}")
return result
df_calculated = df.copy()
for calculation in self.calculations:
calc_type = calculation.get('type')
if calc_type == 'multiply':
# 乘法计算
source_column = calculation.get('source_column')
target_column = calculation.get('target_column')
factor = calculation.get('factor', 1)
if source_column and target_column:
if source_column in df_calculated.columns:
df_calculated[target_column] = df_calculated[source_column] * factor
self.logger.info(f"乘法计算: {source_column} * {factor} -> {target_column}")
else:
self.logger.warning(f"源列不存在: {source_column}")
elif calc_type == 'divide':
# 除法计算
source_column = calculation.get('source_column')
target_column = calculation.get('target_column')
divisor = calculation.get('divisor', 1)
if source_column and target_column and divisor != 0:
if source_column in df_calculated.columns:
df_calculated[target_column] = df_calculated[source_column] / divisor
self.logger.info(f"除法计算: {source_column} / {divisor} -> {target_column}")
else:
self.logger.warning(f"源列不存在: {source_column}")
elif calc_type == 'formula':
# 公式计算
formula = calculation.get('formula')
target_column = calculation.get('target_column')
if formula and target_column:
try:
df_calculated[target_column] = df_calculated.eval(formula)
self.logger.info(f"公式计算: {formula} -> {target_column}")
except Exception as e:
self.logger.error(f"公式计算失败: {formula}: {e}")
else:
self.logger.warning(f"未知的计算类型: {calc_type}")
self.logger.info(f"计算处理完成,数据形状: {df_calculated.shape}")
return df_calculated
except Exception as e:
self.logger.error(f"计算处理失败: {e}")
return None
+21 -6
View File
@@ -16,7 +16,6 @@ from pathlib import Path
from .base import BaseProcessor
from ...core.utils.log_utils import get_logger
from ...core.utils.string_utils import parse_monetary_string
from ...core.utils.dialog_utils import show_custom_dialog
logger = get_logger(__name__)
@@ -39,7 +38,7 @@ class TobaccoProcessor(BaseProcessor):
self.template_file = config.get('Paths', 'template_file', fallback='templates/银豹-采购单模板.xls')
# 输出目录配置
self.result_dir = Path(config.get_path('Paths', 'result_folder', fallback='data/result', create=True) if hasattr(config, 'get_path') else os.path.abspath('data/result'))
self.result_dir = Path("data/result")
self.result_dir.mkdir(exist_ok=True)
# 默认输出文件名
@@ -207,6 +206,19 @@ class TobaccoProcessor(BaseProcessor):
self.logger.error(f"读取订单数据失败: {e}")
return None
def _read_excel_safely(self, file_path: Path, **kwargs) -> pd.DataFrame:
suffix = file_path.suffix.lower()
if suffix == '.xlsx':
return pd.read_excel(file_path, engine='openpyxl', **kwargs)
elif suffix == '.xls':
try:
return pd.read_excel(file_path, engine='xlrd', **kwargs)
except Exception as e:
self.logger.error(f"读取xls失败,可能缺少xlrd: {e}")
raise
else:
return pd.read_excel(file_path, **kwargs)
def _generate_pospal_order(self, order_data: pd.DataFrame, order_time: str, output_file: Path) -> bool:
"""生成银豹采购单
@@ -284,9 +296,12 @@ class TobaccoProcessor(BaseProcessor):
}
# 格式化金额显示
parsed = parse_monetary_string(total_amount)
total_amount = parsed if parsed is not None else 0.0
amount_display = f"¥{total_amount:.2f}"
try:
if isinstance(total_amount, str):
total_amount = float(total_amount.replace(',', ''))
amount_display = f"¥{total_amount:.2f}"
except (ValueError, TypeError):
amount_display = f"¥{total_amount}"
# 显示自定义对话框
show_custom_dialog(
@@ -316,7 +331,7 @@ class TobaccoProcessor(BaseProcessor):
today_start = datetime.datetime.combine(today, datetime.time.min).timestamp()
# 查找订单明细文件
result_dir = Path(self.config.get_path('Paths', 'output_folder', fallback='data/output') if hasattr(self.config, 'get_path') else os.path.abspath('data/output'))
result_dir = Path("data/output")
if not result_dir.exists():
return None
-247
View File
@@ -1,247 +0,0 @@
"""云端同步模块 — 基于 Gitea REST API 的文件同步"""
import base64
import json
from typing import Optional, Tuple
import requests
from .log_utils import get_logger
logger = get_logger(__name__)
class GiteaSync:
"""通过 Gitea REST API 读写仓库文件"""
def __init__(self, base_url: str, owner: str, repo: str, token: str, timeout: int = 15):
self.base_url = base_url.rstrip("/")
self.owner = owner
self.repo = repo
self.token = token
self.timeout = timeout
@property
def _headers(self) -> dict:
return {"Authorization": f"token {self.token}"}
def _api_url(self, path: str) -> str:
return f"{self.base_url}/api/v1/repos/{self.owner}/{self.repo}/contents/{path}"
def pull_file(self, remote_path: str) -> Optional[Tuple[bytes, str]]:
"""从仓库下载文件
Returns:
(content_bytes, sha) None文件不存在或失败
"""
try:
resp = requests.get(
self._api_url(remote_path),
headers=self._headers,
timeout=self.timeout,
)
if resp.status_code == 404:
logger.info(f"云端文件不存在: {remote_path}")
return None
if resp.status_code != 200:
logger.warning(f"拉取文件失败: {resp.status_code} {resp.text[:200]}")
return None
data = resp.json()
sha = data.get("sha", "")
content_b64 = data.get("content", "")
# Gitea 返回的 base64 可能含换行
content_bytes = base64.b64decode(content_b64.replace("\n", ""))
logger.info(f"拉取文件成功: {remote_path} ({len(content_bytes)} bytes)")
return content_bytes, sha
except requests.RequestException as e:
logger.error(f"拉取文件网络错误: {e}")
return None
def push_file(
self,
remote_path: str,
content: bytes,
message: str,
sha: Optional[str] = None,
) -> Optional[str]:
"""上传或更新文件到仓库
Args:
remote_path: 仓库中的文件路径
content: 文件内容bytes
message: commit message
sha: 文件当前 sha更新时必传新建时省略
Returns:
新的 sha失败返回 None
"""
payload = {
"message": message,
"content": base64.b64encode(content).decode("ascii"),
}
if sha:
payload["sha"] = sha
try:
resp = requests.put(
self._api_url(remote_path),
headers={**self._headers, "Content-Type": "application/json"},
json=payload,
timeout=self.timeout,
)
if resp.status_code not in (200, 201):
logger.warning(f"推送文件失败: {resp.status_code} {resp.text[:200]}")
return None
new_sha = resp.json().get("content", {}).get("sha", "")
logger.info(f"推送文件成功: {remote_path} (sha={new_sha[:12]})")
return new_sha
except requests.RequestException as e:
logger.error(f"推送文件网络错误: {e}")
return None
def file_exists(self, remote_path: str) -> Optional[str]:
"""检查文件是否存在
Returns:
文件 sha存在 None不存在
"""
try:
resp = requests.head(
self._api_url(remote_path),
headers=self._headers,
timeout=self.timeout,
)
if resp.status_code == 200:
# HEAD 不返回 body,需要 GET 获取 sha
result = self.pull_file(remote_path)
return result[1] if result else None
return None
except requests.RequestException:
return None
def pull_json(self, remote_path: str) -> Optional[Tuple[dict, str]]:
"""拉取并解析 JSON 文件
Returns:
(parsed_dict, sha) None
"""
result = self.pull_file(remote_path)
if result is None:
return None
content_bytes, sha = result
try:
data = json.loads(content_bytes)
return data, sha
except json.JSONDecodeError as e:
logger.error(f"解析 JSON 失败: {e}")
return None
def push_json(self, remote_path: str, data: dict, message: str, sha: Optional[str] = None) -> Optional[str]:
"""将 dict 序列化为 JSON 并推送
Returns:
新的 sha失败返回 None
"""
content = json.dumps(data, ensure_ascii=False, indent=2).encode("utf-8")
return self.push_file(remote_path, content, message, sha)
def push_binary(self, remote_path: str, local_path: str, message: str) -> Optional[str]:
"""读取本地二进制文件并推送到云端
Returns:
新的 sha失败返回 None
"""
try:
with open(local_path, "rb") as f:
content = f.read()
except OSError as e:
logger.error(f"读取本地文件失败: {local_path}{e}")
return None
existing_sha = self.file_exists(remote_path)
return self.push_file(remote_path, content, message, sha=existing_sha)
def push(self) -> str:
"""推送本地数据到云端:product_cache.json + barcode_mappings.json"""
import os
from pathlib import Path
project_root = Path(__file__).resolve().parent.parent.parent.parent
results = []
# 1. Product cache
from app.core.db.product_db import ProductDatabase
excel_source = str(project_root / "templates" / "商品资料.xlsx")
db_path = str(project_root / "data" / "product_cache.db")
product_db = ProductDatabase(db_path, excel_source)
product_data = product_db.export_for_sync()
sha = self.push_json("product_cache.json", product_data, "sync: update product cache")
results.append(f"product_cache: {'ok' if sha else 'skip'}")
# 2. Barcode mappings
barcode_path = project_root / "config" / "barcode_mappings.json"
if barcode_path.exists():
with open(barcode_path, "r", encoding="utf-8") as f:
barcode_data = json.loads(f.read())
sha = self.push_json("barcode_mappings.json", barcode_data, "sync: update barcode mappings")
results.append(f"barcode_mappings: {'ok' if sha else 'skip'}")
return "; ".join(results) if results else "无数据需要同步"
def pull(self) -> str:
"""从云端拉取数据并写入本地文件"""
import os
from pathlib import Path
project_root = Path(__file__).resolve().parent.parent.parent.parent
results = []
# 1. Product cache
result = self.pull_json("product_cache.json")
if result is not None:
data, sha = result
from app.core.db.product_db import ProductDatabase
excel_source = str(project_root / "templates" / "商品资料.xlsx")
db_path = str(project_root / "data" / "product_cache.db")
os.makedirs(os.path.dirname(db_path), exist_ok=True)
product_db = ProductDatabase(db_path, excel_source)
count = product_db.import_from_sync(data)
results.append(f"product_cache: 导入 {count}")
else:
results.append("product_cache: 云端无数据")
# 2. Barcode mappings
barcode_result = self.pull_json("barcode_mappings.json")
if barcode_result is not None:
barcode_data, sha = barcode_result
barcode_path = project_root / "config" / "barcode_mappings.json"
barcode_path.parent.mkdir(parents=True, exist_ok=True)
with open(barcode_path, "w", encoding="utf-8") as f:
json.dump(barcode_data, f, ensure_ascii=False, indent=2)
results.append(f"barcode_mappings: 已更新")
else:
results.append("barcode_mappings: 云端无数据")
return "; ".join(results) if results else "无数据需要同步"
@classmethod
def from_config(cls, config) -> Optional["GiteaSync"]:
"""从 ConfigManager 创建实例
Returns:
GiteaSync 实例配置不完整时返回 None
"""
base_url = config.get("Gitea", "base_url", fallback="").strip()
owner = config.get("Gitea", "owner", fallback="").strip()
repo = config.get("Gitea", "repo", fallback="").strip()
token = config.get("Gitea", "token", fallback="").strip()
if not all([base_url, owner, repo, token]):
logger.debug("Gitea 配置不完整,跳过云端同步")
return None
return cls(base_url=base_url, owner=owner, repo=repo, token=token)
+7 -498
View File
@@ -8,14 +8,10 @@
"""
import os
import json
import tkinter as tk
from tkinter import messagebox, ttk, simpledialog
from datetime import datetime
from .cloud_sync import GiteaSync
from app.config.settings import ConfigManager
def create_custom_dialog(title="提示", message="", result_file=None, time_info=None,
count_info=None, amount_info=None, additional_info=None):
"""
@@ -82,12 +78,11 @@ def create_custom_dialog(title="提示", message="", result_file=None, time_info
file_size = os.path.getsize(result_file)
file_time = datetime.fromtimestamp(os.path.getmtime(result_file))
from .file_utils import format_file_size
size_text = format_file_size(file_size)
size_text = f"{file_size / 1024:.1f} KB" if file_size < 1024*1024 else f"{file_size / (1024*1024):.1f} MB"
tk.Label(file_frame, text=f"文件大小: {size_text}", font=("Arial", 10)).pack(anchor=tk.W, padx=10, pady=2)
tk.Label(file_frame, text=f"创建时间: {file_time.strftime('%Y-%m-%d %H:%M:%S')}", font=("Arial", 10)).pack(anchor=tk.W, padx=10, pady=2)
except Exception:
except:
tk.Label(file_frame, text="无法获取文件信息", font=("Arial", 10)).pack(anchor=tk.W, padx=10, pady=2)
# 添加按钮
@@ -107,7 +102,7 @@ def create_custom_dialog(title="提示", message="", result_file=None, time_info
button_frame = tk.Frame(dialog)
button_frame.pack(pady=10)
tk.Button(button_frame, text="打开输出目录", command=lambda: os.startfile(ConfigManager().get_path('Paths', 'output_folder', fallback='data/output', create=True))).pack(side=tk.LEFT, padx=5)
tk.Button(button_frame, text="打开输出目录", command=lambda: os.startfile(os.path.abspath("data/output"))).pack(side=tk.LEFT, padx=5)
tk.Button(button_frame, text="关闭", command=dialog.destroy).pack(side=tk.LEFT, padx=5)
# 确保窗口显示在最前
@@ -484,138 +479,9 @@ def create_barcode_mapping_dialog(parent=None, on_save=None, current_mappings=No
save_btn = tk.Button(bottom_frame, text="保存", command=save_mappings)
save_btn.pack(side=tk.RIGHT, padx=5)
cancel_btn = tk.Button(bottom_frame, text="取消", command=cancel)
cancel_btn.pack(side=tk.RIGHT, padx=5)
# ---- 云端同步按钮 ----
def _build_current_mappings():
"""从弹窗当前数据构建 mappings dict(与 save_mappings 逻辑相同)"""
mappings = {}
for source, target in mapping_list:
mappings[source] = {
'map_to': target,
'description': f'条码映射:{source} -> {target}'
}
for barcode, multiplier, unit, price, spec, desc in special_list:
if barcode not in mappings:
mappings[barcode] = {}
if multiplier:
try:
if isinstance(multiplier, str):
mappings[barcode]['multiplier'] = float(multiplier) if '.' in multiplier else int(multiplier)
else:
mappings[barcode]['multiplier'] = multiplier
except ValueError:
mappings[barcode]['multiplier'] = multiplier
if unit:
mappings[barcode]['target_unit'] = unit
if price:
try:
mappings[barcode]['fixed_price'] = float(price)
except ValueError:
mappings[barcode]['fixed_price'] = price
if spec:
mappings[barcode]['specification'] = spec
if desc and "映射到:" in desc:
parts = desc.split("映射到:")
base_desc = parts[0].strip()
target_barcode = parts[1].strip()
if base_desc:
mappings[barcode]['description'] = base_desc
mappings[barcode]['map_to'] = target_barcode
elif desc:
mappings[barcode]['description'] = desc
return mappings
def _get_sync():
"""获取 GiteaSync 实例,配置不完整时提示用户"""
sync = GiteaSync.from_config(ConfigManager())
if sync is None:
messagebox.showwarning("云端同步", "请先在「系统设置」中配置 Gitea 云端同步参数(token")
return sync
def _refresh_trees(new_mappings):
"""用新数据刷新两个 Treeview"""
# 清空
for item in mapping_tree.get_children():
mapping_tree.delete(item)
mapping_list.clear()
for item in special_tree.get_children():
special_tree.delete(item)
special_list.clear()
# 重新填充
if new_mappings:
for barcode, data in new_mappings.items():
if 'map_to' in data and 'multiplier' not in data:
mapping_list.append((barcode, data['map_to']))
mapping_tree.insert('', 'end', values=(barcode, data['map_to']))
else:
mult = data.get('multiplier', '')
unit = data.get('target_unit', '')
price = data.get('fixed_price', '')
spec = data.get('specification', '')
desc = data.get('description', '')
if 'map_to' in data:
desc = f"{desc} 映射到: {data['map_to']}" if desc else f"映射到: {data['map_to']}"
special_list.append((barcode, mult, unit, price, spec, desc))
tags = ("mapped",) if 'map_to' in data else ()
special_tree.insert('', 'end', values=(barcode, mult, unit, price, spec, desc), tags=tags)
if any('map_to' in d for d in new_mappings.values()):
special_tree.tag_configure("mapped", foreground="blue")
def push_to_cloud():
sync = _get_sync()
if not sync:
return
mappings = _build_current_mappings()
if not mappings:
messagebox.showwarning("同步到云端", "当前没有映射数据可同步")
return
# 先获取当前 sha(如果文件已存在)
sha = None
existing = sync.pull_file("barcode_mappings.json")
if existing:
sha = existing[1]
new_sha = sync.push_json(
"barcode_mappings.json",
mappings,
f"同步条码映射 ({len(mappings)} 条)",
sha=sha,
)
if new_sha:
messagebox.showinfo("同步成功", f"已推送 {len(mappings)} 条映射到云端")
else:
messagebox.showerror("同步失败", "推送到云端失败,请检查网络和 Gitea 配置")
def pull_from_cloud():
sync = _get_sync()
if not sync:
return
result = sync.pull_json("barcode_mappings.json")
if result is None:
messagebox.showwarning("拉取失败", "云端没有找到条码映射文件,或网络错误")
return
data, sha = result
if not isinstance(data, dict) or len(data) == 0:
messagebox.showwarning("拉取失败", "云端数据格式异常")
return
# 同时保存到本地
from app.core.excel.converter import UnitConverter
uc = UnitConverter()
uc.update_barcode_mappings(data)
# 刷新弹窗
_refresh_trees(data)
messagebox.showinfo("拉取成功", f"已从云端拉取 {len(data)} 条映射,本地已同步更新")
sync_frame = tk.Frame(bottom_frame)
sync_frame.pack(side=tk.LEFT, padx=5)
push_btn = tk.Button(sync_frame, text="同步到云端", command=push_to_cloud, fg="white", bg="#4a90d9")
push_btn.pack(side=tk.LEFT, padx=3)
pull_btn = tk.Button(sync_frame, text="从云端拉取", command=pull_from_cloud, fg="white", bg="#5cb85c")
pull_btn.pack(side=tk.LEFT, padx=3)
# 导入当前映射数据
if current_mappings:
@@ -799,363 +665,6 @@ def show_config_dialog(parent, config_manager, on_save=None):
# 设置模态
dialog.transient(parent)
dialog.grab_set()
# ──────────────────────────────────────────────────────────────
# 云端同步管理对话框
# ──────────────────────────────────────────────────────────────
SYNC_FILES = [
{
"name": "条码映射",
"remote": "barcode_mappings.json",
"local": "config/barcode_mappings.json",
"type": "json",
},
{
"name": "供应商配置",
"remote": "suppliers_config.json",
"local": "config/suppliers_config.json",
"type": "json",
},
{
"name": "商品资料",
"remote": "templates/商品资料.xlsx",
"local": "templates/商品资料.xlsx",
"type": "binary",
},
{
"name": "采购单模板",
"remote": "templates/银豹-采购单模板.xls",
"local": "templates/银豹-采购单模板.xls",
"type": "binary",
},
{
"name": "商品记忆库",
"remote": "product_memory.json",
"local": "data/product_memory.json",
"type": "json",
},
]
def _format_size(path: str) -> str:
try:
size = os.path.getsize(path)
if size < 1024 * 1024:
return f"{size / 1024:.1f} KB"
return f"{size / (1024 * 1024):.1f} MB"
except OSError:
return ""
def show_cloud_sync_dialog(parent=None):
"""统一云端同步管理对话框"""
sync = GiteaSync.from_config(ConfigManager())
if sync is None:
messagebox.showwarning(
"配置不完整",
"请先在「系统设置」中配置 Gitea 地址和 Access Token",
)
return
dlg = tk.Toplevel(parent)
dlg.title("云端同步管理")
dlg.geometry("620x440")
dlg.resizable(False, False)
# 居中
dlg.update_idletasks()
x = (dlg.winfo_screenwidth() - 620) // 2
y = (dlg.winfo_screenheight() - 440) // 2
dlg.geometry(f"620x440+{x}+{y}")
# ── Treeview ──
columns = ("name", "local_status", "cloud_status")
tree = ttk.Treeview(dlg, columns=columns, show="headings", height=6)
tree.heading("name", text="文件")
tree.heading("local_status", text="本地状态")
tree.heading("cloud_status", text="云端状态")
tree.column("name", width=140)
tree.column("local_status", width=220)
tree.column("cloud_status", width=220)
tree.pack(fill=tk.BOTH, expand=True, padx=16, pady=(16, 8))
# tag 颜色
tree.tag_configure("synced", foreground="#2e7d32")
tree.tag_configure("cloud_only", foreground="#e65100")
tree.tag_configure("local_only", foreground="#1565c0")
tree.tag_configure("missing", foreground="#999999")
# 用 iid = remote_path 标识每行
cloud_sha_cache: dict = {} # remote_path -> sha
def _load_local_status():
"""仅加载本地状态,不发网络请求"""
for item in tree.get_children():
tree.delete(item)
for entry in SYNC_FILES:
local = entry["local"]
if os.path.exists(local):
if entry["type"] == "json":
try:
with open(local, "r", encoding="utf-8") as f:
data = json.load(f)
if isinstance(data, dict):
local_text = f"{len(data)}"
elif isinstance(data, list):
local_text = f"{len(data)} 条记录"
else:
local_text = "已存在"
except Exception:
local_text = "已存在(解析异常)"
else:
local_text = _format_size(local)
tag = "local_only"
else:
local_text = "不存在"
tag = "missing"
tree.insert(
"", tk.END,
iid=entry["remote"],
values=(entry["name"], local_text, "点「刷新状态」检查"),
tags=(tag,),
)
def refresh_status():
"""刷新每行的本地/云端状态"""
cloud_sha_cache.clear()
for item in tree.get_children():
tree.delete(item)
for entry in SYNC_FILES:
remote = entry["remote"]
local = entry["local"]
# 本地状态
if os.path.exists(local):
if entry["type"] == "json":
try:
with open(local, "r", encoding="utf-8") as f:
data = json.load(f)
if isinstance(data, dict):
local_text = f"{len(data)}"
elif isinstance(data, list):
local_text = f"{len(data)} 条记录"
else:
local_text = "已存在"
except Exception:
local_text = "已存在(解析异常)"
else:
local_text = _format_size(local)
else:
local_text = "不存在"
# 云端状态 — 网络请求,可能慢
sha = sync.file_exists(remote)
if sha:
cloud_sha_cache[remote] = sha
cloud_text = "已存在"
else:
cloud_text = "未上传"
# tag
local_ok = os.path.exists(local)
cloud_ok = sha is not None
if local_ok and cloud_ok:
tag = "synced"
elif cloud_ok and not local_ok:
tag = "cloud_only"
elif local_ok and not cloud_ok:
tag = "local_only"
else:
tag = "missing"
tree.insert(
"", tk.END,
iid=remote,
values=(entry["name"], local_text, cloud_text),
tags=(tag,),
)
# ── 操作函数 ──
def _get_selected_entries():
"""获取选中的文件条目列表"""
selected = tree.selection()
if not selected:
messagebox.showinfo("提示", "请先选中要操作的文件")
return []
return [e for e in SYNC_FILES if e["remote"] in selected]
def push_selected():
entries = _get_selected_entries()
if not entries:
return
ok, fail = 0, 0
for entry in entries:
local, remote = entry["local"], entry["remote"]
if not os.path.exists(local):
messagebox.showwarning("跳过", f"本地文件不存在: {local}")
fail += 1
continue
if entry["type"] == "json":
try:
with open(local, "r", encoding="utf-8") as f:
data = json.load(f)
sha = cloud_sha_cache.get(remote)
result = sync.push_json(remote, data, f"同步 {entry['name']}", sha=sha)
except Exception as e:
messagebox.showerror("推送失败", f"{entry['name']}: {e}")
fail += 1
continue
else:
result = sync.push_binary(remote, local, f"同步 {entry['name']}")
if result:
ok += 1
else:
fail += 1
if ok:
messagebox.showinfo("推送完成", f"成功 {ok}" + (f",失败 {fail}" if fail else ""))
refresh_status()
def pull_selected():
entries = _get_selected_entries()
if not entries:
return
ok, fail = 0, 0
for entry in entries:
remote, local = entry["remote"], entry["local"]
if entry["type"] == "json":
result = sync.pull_json(remote)
if result is None:
messagebox.showwarning("拉取失败", f"云端文件不存在: {entry['name']}")
fail += 1
continue
content, sha = result
# 写入本地
os.makedirs(os.path.dirname(local) or ".", exist_ok=True)
with open(local, "w", encoding="utf-8") as f:
json.dump(content, f, ensure_ascii=False, indent=2)
# 特殊后处理
_post_pull(entry, content)
else:
result = sync.pull_file(remote)
if result is None:
messagebox.showwarning("拉取失败", f"云端文件不存在: {entry['name']}")
fail += 1
continue
content, sha = result
os.makedirs(os.path.dirname(local) or ".", exist_ok=True)
with open(local, "wb") as f:
f.write(content)
ok += 1
if ok:
messagebox.showinfo("拉取完成", f"成功 {ok}" + (f",失败 {fail}" if fail else ""))
refresh_status()
def _post_pull(entry, data):
"""拉取 JSON 文件后的特殊处理"""
if entry["remote"] == "barcode_mappings.json":
try:
from app.core.excel.converter import UnitConverter
UnitConverter().update_barcode_mappings(data)
except Exception:
pass
elif entry["remote"] == "suppliers_config.json":
try:
from app.services.processor_service import ProcessorService
ProcessorService(ConfigManager()).reload_processors()
except Exception:
pass
elif entry["remote"] == "product_memory.json":
try:
from app.core.db.product_db import ProductDatabase
cfg = ConfigManager()
db_path = cfg.get_path('Paths', 'product_db', fallback='data/product_cache.db') if hasattr(cfg, 'get_path') else 'data/product_cache.db'
tpl_folder = cfg.get('Paths', 'template_folder', fallback='templates')
item_data = cfg.get('Templates', 'item_data', fallback='商品资料.xlsx')
tpl_path = os.path.join(tpl_folder, item_data)
db = ProductDatabase(db_path, tpl_path)
count = db.import_from_sync(data)
logger.info(f"从云端导入商品记忆: {count}")
except Exception:
pass
def push_all():
ok, fail = 0, 0
for entry in SYNC_FILES:
local, remote = entry["local"], entry["remote"]
if not os.path.exists(local):
fail += 1
continue
if entry["type"] == "json":
try:
with open(local, "r", encoding="utf-8") as f:
data = json.load(f)
sha = cloud_sha_cache.get(remote)
result = sync.push_json(remote, data, f"批量同步 {entry['name']}", sha=sha)
except Exception:
fail += 1
continue
else:
result = sync.push_binary(remote, local, f"批量同步 {entry['name']}")
if result:
ok += 1
else:
fail += 1
messagebox.showinfo("批量推送完成", f"成功 {ok} 个,失败 {fail}")
refresh_status()
def pull_all():
ok, fail = 0, 0
for entry in SYNC_FILES:
remote, local = entry["remote"], entry["local"]
if entry["type"] == "json":
result = sync.pull_json(remote)
if result is None:
fail += 1
continue
content, sha = result
os.makedirs(os.path.dirname(local) or ".", exist_ok=True)
with open(local, "w", encoding="utf-8") as f:
json.dump(content, f, ensure_ascii=False, indent=2)
_post_pull(entry, content)
else:
result = sync.pull_file(remote)
if result is None:
fail += 1
continue
content, sha = result
os.makedirs(os.path.dirname(local) or ".", exist_ok=True)
with open(local, "wb") as f:
f.write(content)
ok += 1
messagebox.showinfo("批量拉取完成", f"成功 {ok} 个,失败 {fail}")
refresh_status()
# ── 按钮区域 ──
btn_frame = ttk.Frame(dlg)
btn_frame.pack(fill=tk.X, padx=16, pady=(4, 16))
# 左侧:批量操作
ttk.Button(btn_frame, text="全部推送到云端", command=push_all).pack(side=tk.LEFT, padx=4)
ttk.Button(btn_frame, text="全部从云端拉取", command=pull_all).pack(side=tk.LEFT, padx=4)
# 右侧:选中操作 + 刷新 + 关闭
ttk.Button(btn_frame, text="关闭", command=dlg.destroy).pack(side=tk.RIGHT, padx=4)
ttk.Button(btn_frame, text="刷新状态", command=refresh_status).pack(side=tk.RIGHT, padx=4)
tk.Button(btn_frame, text="推送到云端", command=push_selected, fg="white", bg="#4a90d9").pack(side=tk.RIGHT, padx=4)
tk.Button(btn_frame, text="从云端拉取", command=pull_selected, fg="white", bg="#5cb85c").pack(side=tk.RIGHT, padx=4)
# 仅显示本地状态,云端状态需手动点"刷新状态"
_load_local_status()
dlg.transient(parent)
dlg.grab_set()
# 等待窗口关闭
parent.wait_window(dialog)
+1 -8
View File
@@ -276,11 +276,4 @@ def is_file_size_valid(file_path: str, max_size_mb: float) -> bool:
"""
size_bytes = get_file_size(file_path)
max_size_bytes = max_size_mb * 1024 * 1024
return size_bytes <= max_size_bytes
def format_file_size(size_bytes: int) -> str:
"""将字节数格式化为可读的文件大小字符串(KB/MB)"""
if size_bytes < 1024 * 1024:
return f"{size_bytes / 1024:.1f} KB"
return f"{size_bytes / (1024 * 1024):.1f} MB"
return size_bytes <= max_size_bytes
+1 -46
View File
@@ -5,7 +5,7 @@
"""
import re
from typing import Dict, List, Optional, Tuple, Any
from typing import Dict, List, Optional, Tuple, Any, Match, Pattern
def clean_string(text: str) -> str:
"""
@@ -192,51 +192,6 @@ def is_scientific_notation(value: str) -> bool:
"""
return bool(re.match(r'^-?\d+(\.\d+)?[eE][+-]?\d+$', str(value)))
def parse_monetary_string(value: Any) -> Optional[float]:
"""
解析金额/数量字符串为浮点数
处理: 货币符号(¥/$)逗号作小数点逗号作千位分隔符中文""后缀等
Args:
value: 金额值字符串数字或其他类型
Returns:
解析后的浮点数无法解析则返回 None
"""
if value is None:
return None
if isinstance(value, (int, float)):
return float(value)
if not isinstance(value, str):
return None
s = value.strip()
if not s or s.lower() in ('o', 'none', 'null', '-', '--'):
return None
# 移除非数字字符,保留数字、小数点、逗号和负号
cleaned = re.sub(r'[^\d\.\-,]', '', s)
if not cleaned or cleaned in ('-', '.', '-.', ','):
return None
# 逗号处理策略:
# 多个逗号 -> 千位分隔符,全部移除 (如 "1,234,567" = 1234567)
# 一个逗号 + 无小数点 -> 逗号当小数点 (如 "1,5" = 1.5)
# 一个逗号 + 有小数点 -> 千位分隔符,移除 (如 "1,234.56" = 1234.56)
comma_count = cleaned.count(',')
if comma_count > 1:
cleaned = cleaned.replace(',', '')
elif comma_count == 1 and '.' not in cleaned:
cleaned = cleaned.replace(',', '.')
elif comma_count == 1 and '.' in cleaned:
cleaned = cleaned.replace(',', '')
try:
return float(cleaned)
except (ValueError, TypeError):
return None
def format_barcode(barcode: Any) -> str:
"""
格式化条码处理科学计数法
+1 -1
View File
@@ -154,7 +154,7 @@ class OCRService:
# 获取文件名(不含扩展名)
base_name = os.path.splitext(os.path.basename(image_path))[0]
# 生成Excel文件路径
output_dir = self.config.get_path('Paths', 'output_folder', fallback='data/output', create=True) if hasattr(self.config, 'get_path') else os.path.abspath('data/output')
output_dir = self.config.get('Paths', 'output_folder', fallback='data/output')
excel_path = os.path.join(output_dir, f"{base_name}.xlsx")
return excel_path
+50 -44
View File
@@ -11,7 +11,6 @@ from ..config.settings import ConfigManager
from ..core.utils.log_utils import get_logger
from ..core.excel.processor import ExcelProcessor
from ..core.excel.merger import PurchaseOrderMerger
from ..core.db.product_db import ProductDatabase
logger = get_logger(__name__)
@@ -29,16 +28,9 @@ class OrderService:
"""
logger.info("初始化OrderService")
self.config = config or ConfigManager()
# 创建共享的商品数据库实例
db_path = self.config.get_path('Paths', 'product_db', fallback='data/product_cache.db') if hasattr(self.config, 'get_path') else 'data/product_cache.db'
tpl_folder = self.config.get('Paths', 'template_folder', fallback='templates')
item_data = self.config.get('Templates', 'item_data', fallback='商品资料.xlsx')
tpl_path = os.path.join(tpl_folder, item_data)
self.product_db = ProductDatabase(db_path, tpl_path)
# 创建Excel处理器和采购单合并器
self.excel_processor = ExcelProcessor(self.config, product_db=self.product_db)
self.excel_processor = ExcelProcessor(self.config)
self.order_merger = PurchaseOrderMerger(self.config)
logger.info("OrderService初始化完成")
@@ -202,44 +194,58 @@ class OrderService:
"""
try:
import pandas as pd
import os
from app.core.utils.file_utils import smart_read_excel
from app.core.handlers.column_mapper import ColumnMapper as CM
# 使用共享的商品数据库实例
product_db = self.product_db
# 读取待校验的采购单
df_res = smart_read_excel(result_path)
res_barcode_col = CM.find_column(list(df_res.columns), 'barcode')
res_price_col = CM.find_column(list(df_res.columns), 'unit_price')
if not res_barcode_col or not res_price_col:
logger.warning("未能在采购单中找到条码或单价列")
item_path = os.path.join('templates', '商品资料.xlsx')
if not os.path.exists(item_path):
logger.warning(f"未找到商品资料文件: {item_path}")
return []
# 批量查询进货价
barcodes = df_res[res_barcode_col].astype(str).str.strip().tolist()
item_prices = product_db.get_prices(barcodes)
df_item = smart_read_excel(item_path)
df_res = smart_read_excel(result_path)
def _find_col(df, candidates, contains=None):
cols = list(df.columns)
for c in candidates:
if c in cols:
return c
if contains:
for c in cols:
if contains in str(c):
return c
return None
item_barcode_col = _find_col(df_item, ['商品条码','商品条码(小条码)','条码','barcode'], contains='条码')
item_price_col = _find_col(df_item, ['进货价','进货价(必填)'], contains='进货价')
res_barcode_col = _find_col(df_res, ['条码','barcode'], contains='条码')
res_price_col = _find_col(df_res, ['采购单价','unit_price','单价'], contains='单价')
if not all([item_barcode_col, item_price_col, res_barcode_col, res_price_col]):
logger.warning("未能在文件和商品资料中找到完整的校验列(条码、单价)")
return []
item_map = df_item[[item_barcode_col, item_price_col]].dropna()
item_map[item_price_col] = pd.to_numeric(item_map[item_price_col], errors='coerce')
item_map = item_map.dropna()
imap = dict(zip(item_map[item_barcode_col].astype(str).str.strip(), item_map[item_price_col]))
df_res['_bc_'] = df_res[res_barcode_col].astype(str).str.strip()
df_res['_res_price_'] = pd.to_numeric(df_res[res_price_col], errors='coerce')
df_res['_item_price_'] = df_res['_bc_'].map(imap)
df_check = df_res.dropna(subset=['_res_price_','_item_price_'])
df_check['_diff_'] = (df_check['_res_price_'] - df_check['_item_price_']).abs()
bad = df_check[df_check['_diff_'] > 1.0]
results = []
for _, row in df_res.iterrows():
bc = str(row[res_barcode_col]).strip()
if bc not in item_prices:
continue
try:
res_price = float(row[res_price_col])
except (ValueError, TypeError):
continue
item_price = item_prices[bc]
diff = abs(res_price - item_price)
if diff > 1.0:
results.append(f"条码 {bc}: 采购单价={res_price} vs 进货价={item_price} 差异={diff:.2f}")
if not bad.empty:
for i in range(len(bad)):
r = bad.iloc[i]
results.append(f"条码 {r['_bc_']}: 采购单价={r['_res_price_']} vs 进货价={r['_item_price_']} 差异={r['_diff_']:.2f}")
return results
except Exception as e:
logger.error(f"单价校验过程中发生错误: {e}")
return []
+9 -23
View File
@@ -5,11 +5,10 @@ import os
import re
import time
import pandas as pd
import logging
from typing import Optional, Callable
from ..core.utils.log_utils import get_logger
logger = get_logger(__name__)
logger = logging.getLogger(__name__)
class SpecialSuppliersService:
"""
@@ -86,17 +85,12 @@ class SpecialSuppliersService:
# 过滤掉空的条码行
df_clean = df_clean.dropna(subset=['商品条码'])
# 保存预处理文件到输出目录(而非源文件目录)
if self.config_manager and hasattr(self.config_manager, 'get_path'):
out_dir = self.config_manager.get_path('Paths', 'output_folder', fallback='data/output', create=True)
else:
from app.config.settings import ConfigManager
out_dir = ConfigManager().get_path('Paths', 'output_folder', fallback='data/output', create=True)
os.makedirs(out_dir, exist_ok=True)
# 保存预处理文件
out_dir = os.path.dirname(src_path)
base = os.path.basename(src_path)
final_path = os.path.join(out_dir, f"预处理之后_{base}")
df_clean.to_excel(final_path, index=False)
return final_path
except Exception as e:
logger.error(f"预处理杨碧月订单出错: {e}")
@@ -200,20 +194,14 @@ class SpecialSuppliersService:
try:
up = float(new_row['单价'] or 0)
new_row['金额'] = up * current_qty
except Exception:
pass
except: pass
rows.append(new_row)
continue
rows.append(row)
df2 = pd.DataFrame(rows)
# 保存预处理文件到输出目录(而非源文件目录)
if self.config_manager and hasattr(self.config_manager, 'get_path'):
out_dir = self.config_manager.get_path('Paths', 'output_folder', fallback='data/output', create=True)
else:
from app.config.settings import ConfigManager
out_dir = ConfigManager().get_path('Paths', 'output_folder', fallback='data/output', create=True)
os.makedirs(out_dir, exist_ok=True)
# 保存预处理文件
out_dir = os.path.dirname(src_path)
base = os.path.basename(src_path)
final_path = os.path.join(out_dir, f"预处理之后_{base}")
df2.to_excel(final_path, index=False)
@@ -231,7 +219,5 @@ class SpecialSuppliersService:
"""
cleaned_path = self.preprocess_rongcheng_yigou(src_path, progress_cb)
if cleaned_path:
from app.services.order_service import OrderService
order_service = OrderService(self.config_manager)
return order_service.process_excel(cleaned_path, progress_cb=lambda p: progress_cb(60 + int(p*0.4), "生成采购单中...") if progress_cb else None)
return self.order_service.process_excel(cleaned_path, progress_cb=lambda p: progress_cb(60 + int(p*0.4), "生成采购单中...") if progress_cb else None)
return None
+11 -9
View File
@@ -18,7 +18,6 @@ from xlutils.copy import copy
from openpyxl import load_workbook
from typing import Optional, Dict, Any, List, Tuple
from app.core.utils.log_utils import get_logger
from app.core.utils.string_utils import parse_monetary_string
from app.core.utils.dialog_utils import show_custom_dialog # 导入自定义弹窗工具
from ..config.settings import ConfigManager
@@ -36,10 +35,10 @@ class TobaccoService:
"""
self.config = config
# 修复配置获取方式,使用fallback机制
self.output_dir = config.get_path('Paths', 'output_folder', fallback='data/output', create=True) if hasattr(config, 'get_path') else os.path.abspath('data/output')
self.output_dir = config.get('Paths', 'output_folder', fallback='data/output')
self.template_file = config.get('Paths', 'template_file', fallback='templates/银豹-采购单模板.xls')
# 将烟草订单保存到result目录
result_dir = config.get_path('Paths', 'result_folder', fallback='data/result', create=True) if hasattr(config, 'get_path') else os.path.abspath('data/result')
result_dir = "data/result"
os.makedirs(result_dir, exist_ok=True)
self.output_file = os.path.join(result_dir, '银豹采购单_烟草公司.xls')
@@ -132,9 +131,8 @@ class TobaccoService:
final_cols = ['商品条码', '商品名称', '数量', '单价', '金额']
df_final = df[final_cols].copy()
# 保存预处理文件到输出目录(而非源文件目录)
out_dir = self.output_dir
os.makedirs(out_dir, exist_ok=True)
# 保存预处理文件
out_dir = os.path.dirname(file_path)
base = os.path.basename(file_path)
final_path = os.path.join(out_dir, f"预处理之后_{base}")
df_final.to_excel(final_path, index=False)
@@ -318,9 +316,13 @@ class TobaccoService:
}
# 确保 total_amount 是数字类型
parsed = parse_monetary_string(total_amount)
total_amount = parsed if parsed is not None else 0.0
amount_display = f"¥{total_amount:.2f}"
try:
if isinstance(total_amount, str):
total_amount = float(total_amount.replace(',', ''))
amount_display = f"¥{total_amount:.2f}"
except (ValueError, TypeError):
# 如果转换失败,直接使用原始值
amount_display = f"¥{total_amount}"
# 显示自定义对话框
show_custom_dialog(
-2
View File
@@ -1,2 +0,0 @@
# -*- coding: utf-8 -*-
"""益选-OCR订单处理系统 UI 模块"""
-565
View File
@@ -1,565 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""业务操作处理模块"""
import os
import time
import datetime
import json
import logging
import tkinter as tk
from tkinter import messagebox
from threading import Thread
from app.config.settings import ConfigManager
from app.services.ocr_service import OCRService
from app.services.order_service import OrderService
from app.core.utils.log_utils import get_logger
from .logging_ui import add_to_log, init_gui_logger, dispose_gui_logger, GUILogHandler
from .ui_widgets import ProgressReporter
from .error_utils import show_error_dialog, get_error_suggestion
logger = get_logger(__name__)
from .result_previews import show_ocr_result_preview, show_excel_result_preview, show_merge_result_preview
from .user_settings import add_recent_file
from .command_runner import get_running_task, set_running_task
from .file_operations import select_file, select_excel_file, validate_unit_price_against_item_data
def _ask_and_merge_purchase_orders(order_service, log_widget, add_to_recent=False):
"""弹窗询问是否合并采购单,返回合并结果路径或 None。
用于 run_pipeline_directly batch_process_orders_with_status 的共享逻辑
"""
try:
purchase_orders = order_service.get_purchase_orders()
if len(purchase_orders) == 0:
add_to_log(log_widget, "没有找到采购单文件,跳过合并步骤\n", "info")
elif len(purchase_orders) == 1:
add_to_log(log_widget, f"只有1个采购单文件,无需合并: {os.path.basename(purchase_orders[0])}\n", "info")
else:
add_to_log(log_widget, f"找到{len(purchase_orders)}个采购单文件\n", "info")
file_list = "\n".join([f"{os.path.basename(f)}" for f in purchase_orders])
merge_choice = messagebox.askyesnocancel(
"采购单合并选择",
f"发现{len(purchase_orders)}个采购单文件:\n\n{file_list}\n\n是否需要合并这些采购单?\n\n• 选择'':合并所有采购单\n• 选择'':保持文件分离\n• 选择'取消':跳过此步骤",
icon='question'
)
if merge_choice is True:
add_to_log(log_widget, "开始合并采购单...\n", "info")
merge_result = order_service.merge_all_purchase_orders()
if merge_result:
add_to_log(log_widget, "采购单合并完成\n", "success")
if add_to_recent:
try:
add_recent_file(merge_result)
except Exception as e:
logger.debug(f"添加最近文件失败: {e}")
return merge_result
else:
add_to_log(log_widget, "合并失败\n", "warning")
elif merge_choice is False:
add_to_log(log_widget, "用户选择不合并采购单,保持文件分离\n", "info")
else:
add_to_log(log_widget, "用户取消合并操作\n", "info")
except Exception as e:
add_to_log(log_widget, f"合并过程出现问题: {str(e)}\n", "warning")
return None
def process_single_image_with_status(log_widget, status_bar):
status_bar.set_status("选择图片中...")
file_path = select_file(log_widget, [("图片文件", "*.jpg *.jpeg *.png *.bmp"), ("所有文件", "*.*")], "选择图片")
if not file_path:
status_bar.set_status("操作已取消")
add_to_log(log_widget, "未选择文件,操作已取消\n", "warning")
return
def run_in_thread():
try:
status_bar.set_running(True)
status_bar.set_status("开始处理图片...")
gui_handler = GUILogHandler(log_widget)
gui_handler.setLevel(logging.INFO)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
gui_handler.setFormatter(formatter)
root_logger = logging.getLogger()
for handler in root_logger.handlers[:]:
if isinstance(handler, logging.StreamHandler):
root_logger.removeHandler(handler)
root_logger.addHandler(gui_handler)
root_logger.setLevel(logging.INFO)
ocr_service = OCRService()
add_to_log(log_widget, f"开始处理图片: {file_path}\n", "info")
try:
add_recent_file(file_path)
except Exception as e:
logger.debug(f"添加最近文件失败: {e}")
excel_path = ocr_service.process_image(file_path)
if excel_path:
add_to_log(log_widget, "图片OCR处理完成\n", "success")
preview_output = f"采购单已保存到: {excel_path}\n"
show_excel_result_preview(preview_output)
try:
add_recent_file(excel_path)
except Exception as e:
logger.debug(f"添加最近文件失败: {e}")
else:
add_to_log(log_widget, "图片OCR处理失败\n", "error")
except Exception as e:
add_to_log(log_widget, f"处理单个图片时出错: {str(e)}\n", "error")
sugg = get_error_suggestion(str(e))
if sugg:
show_error_dialog("OCR处理错误", str(e), sugg)
finally:
try:
root_logger = logging.getLogger()
for handler in root_logger.handlers[:]:
if isinstance(handler, GUILogHandler):
root_logger.removeHandler(handler)
handler.close()
except Exception as e:
logger.debug(f"清理日志处理器失败: {e}")
status_bar.set_running(False)
status_bar.set_status("就绪")
thread = Thread(target=run_in_thread)
thread.daemon = True
thread.start()
def run_pipeline_directly(log_widget, status_bar):
"""直接运行完整处理流程"""
if get_running_task() is not None:
messagebox.showinfo("任务进行中", "请等待当前任务完成后再执行新的操作。")
return
def run_in_thread():
set_running_task("pipeline")
if status_bar:
status_bar.set_running(True)
status_bar.set_status("开始完整处理流程...")
start_time = datetime.datetime.now()
start_perf = time.perf_counter()
log_widget.configure(state=tk.NORMAL)
log_widget.delete(1.0, tk.END)
log_widget.insert(tk.END, "执行命令: 完整处理流程\n", "command")
log_widget.insert(tk.END, f"开始时间: {start_time.strftime('%Y-%m-%d %H:%M:%S')}\n", "time")
log_widget.insert(tk.END, "=" * 50 + "\n\n", "separator")
log_widget.configure(state=tk.DISABLED)
try:
config = ConfigManager()
gui_handler = init_gui_logger(log_widget)
ocr_service = OCRService(config)
order_service = OrderService(config)
reporter = ProgressReporter(status_bar)
reporter.running()
reporter.set("开始OCR批量处理...", 10)
total, success = ocr_service.batch_process(progress_cb=lambda p: reporter.set("OCR处理中...", p))
if total == 0:
add_to_log(log_widget, "没有找到需要处理的图片\n", "warning")
if status_bar:
status_bar.set_status("未找到图片文件")
return
elif success == 0:
add_to_log(log_widget, "OCR处理没有成功处理任何新文件\n", "warning")
else:
add_to_log(log_widget, f"OCR处理完成,共处理 {success}/{total} 个文件\n", "success")
try:
processed_map = {}
config = ConfigManager()
pjson = config.get('Paths', 'processed_record', fallback='data/processed_files.json')
if os.path.exists(pjson):
with open(pjson, 'r', encoding='utf-8') as f:
processed_map = json.load(f)
outputs = list(processed_map.values())
for p in outputs[-10:]:
if p:
add_recent_file(os.path.abspath(p))
except Exception as e:
logger.debug(f"加载已处理文件记录失败: {e}")
reporter.set("开始Excel处理...", 92)
add_to_log(log_widget, "开始Excel处理...\n", "info")
result = order_service.process_excel()
if not result:
add_to_log(log_widget, "Excel处理失败\n", "error")
else:
add_to_log(log_widget, "Excel处理完成\n", "success")
try:
add_recent_file(result)
except Exception as e:
logger.debug(f"添加最近文件失败: {e}")
try:
validate_unit_price_against_item_data(result, log_widget)
except Exception as e:
logger.debug(f"单价校验失败: {e}")
reporter.set("检查是否需要合并采购单...", 80)
_ask_and_merge_purchase_orders(order_service, log_widget, add_to_recent=True)
end_time = datetime.datetime.now()
duration_sec = max(0.0, time.perf_counter() - start_perf)
add_to_log(log_widget, f"\n{'=' * 50}\n", "separator")
add_to_log(log_widget, "完整处理流程执行完毕!\n", "success")
add_to_log(log_widget, f"结束时间: {end_time.strftime('%Y-%m-%d %H:%M:%S')}\n", "time")
add_to_log(log_widget, f"耗时: {duration_sec:.2f}\n", "time")
reporter.set("处理完成", 100)
except Exception as e:
add_to_log(log_widget, f"执行过程中发生错误: {str(e)}\n", "error")
import traceback
add_to_log(log_widget, f"详细错误信息: {traceback.format_exc()}\n", "error")
finally:
dispose_gui_logger()
reporter.done()
set_running_task(None)
if status_bar:
status_bar.set_running(False)
status_bar.set_status("就绪")
thread = Thread(target=run_in_thread)
thread.daemon = True
thread.start()
def batch_ocr_with_status(log_widget, status_bar):
"""OCR批量识别"""
def run_in_thread():
try:
reporter = ProgressReporter(status_bar)
reporter.running()
reporter.set("正在进行OCR批量识别...", 10)
add_to_log(log_widget, "开始OCR批量识别\n", "info")
init_gui_logger(log_widget)
ocr_service = OCRService()
result = ocr_service.batch_process()
if result:
add_to_log(log_widget, "OCR批量识别完成\n", "success")
show_ocr_result_preview("OCR批量识别成功完成")
reporter.set("批量识别完成", 100)
try:
processed_map = {}
config = ConfigManager()
pjson = config.get('Paths', 'processed_record', fallback='data/processed_files.json')
if os.path.exists(pjson):
with open(pjson, 'r', encoding='utf-8') as f:
processed_map = json.load(f)
outputs = list(processed_map.values())
for p in outputs[-10:]:
if p:
add_recent_file(p)
inputs = list(processed_map.keys())
for p in inputs[-10:]:
if p:
add_recent_file(p)
except Exception as e:
logger.debug(f"加载已处理文件记录失败: {e}")
else:
add_to_log(log_widget, "OCR批量识别失败\n", "error")
except Exception as e:
add_to_log(log_widget, f"OCR批量识别出错: {str(e)}\n", "error")
sugg = get_error_suggestion(str(e))
if sugg:
show_error_dialog("OCR处理错误", str(e), sugg)
finally:
dispose_gui_logger()
reporter.done()
thread = Thread(target=run_in_thread)
thread.daemon = True
thread.start()
def batch_process_orders_with_status(log_widget, status_bar):
"""批量处理订单(仅Excel处理,包含合并确认)"""
def run_in_thread():
try:
reporter = ProgressReporter(status_bar)
reporter.running()
reporter.set("正在批量处理订单...", 10)
add_to_log(log_widget, "开始批量处理订单\n", "info")
init_gui_logger(log_widget)
order_service = OrderService()
add_to_log(log_widget, "开始Excel处理...\n", "info")
try:
latest_input = order_service.get_latest_excel()
if latest_input:
add_recent_file(latest_input)
except Exception as e:
logger.debug(f"获取最新Excel失败: {e}")
result = order_service.process_excel(progress_cb=lambda p: reporter.set("Excel处理中...", p))
if result:
add_to_log(log_widget, "Excel处理完成\n", "success")
try:
validate_unit_price_against_item_data(result, log_widget)
except Exception as e:
logger.debug(f"单价校验失败: {e}")
reporter.set("检查是否需要合并采购单...", 70)
add_to_log(log_widget, "检查是否需要合并采购单...\n", "info")
_ask_and_merge_purchase_orders(order_service, log_widget)
add_to_log(log_widget, "批量处理订单完成\n", "success")
reporter.set("批量处理订单完成", 100)
show_excel_result_preview(f"采购单已保存到: {result}\n")
try:
add_recent_file(result)
except Exception as e:
logger.debug(f"添加最近文件失败: {e}")
else:
add_to_log(log_widget, "批量处理订单失败\n", "error")
except Exception as e:
add_to_log(log_widget, f"批量处理订单时出错: {str(e)}\n", "error")
sugg = get_error_suggestion(str(e))
if sugg:
show_error_dialog("Excel处理错误", str(e), sugg)
finally:
dispose_gui_logger()
reporter.done()
thread = Thread(target=run_in_thread)
thread.daemon = True
thread.start()
def merge_orders_with_status(log_widget, status_bar):
"""合并采购单"""
def run_in_thread():
try:
reporter = ProgressReporter(status_bar)
reporter.running()
reporter.set("正在合并采购单...", 10)
add_to_log(log_widget, "开始合并采购单\n", "info")
init_gui_logger(log_widget)
order_service = OrderService()
result = order_service.merge_all_purchase_orders(progress_cb=lambda p: reporter.set("合并处理中...", p))
if result:
add_to_log(log_widget, "采购单合并完成\n", "success")
show_merge_result_preview(f"已保存到: {result}\n")
try:
add_recent_file(result)
except Exception as e:
logger.debug(f"添加最近文件失败: {e}")
try:
validate_unit_price_against_item_data(result, log_widget)
except Exception as e:
logger.debug(f"单价校验失败: {e}")
else:
add_to_log(log_widget, "采购单合并失败\n", "error")
except Exception as e:
add_to_log(log_widget, f"采购单合并出错: {str(e)}\n", "error")
sugg = get_error_suggestion(str(e))
if sugg:
show_error_dialog("合并错误", str(e), sugg)
finally:
dispose_gui_logger()
reporter.done()
thread = Thread(target=run_in_thread)
thread.daemon = True
thread.start()
def process_excel_file_with_status(log_widget, status_bar):
"""处理Excel文件"""
def run_in_thread():
try:
status_bar.set_running(True)
status_bar.set_status("选择Excel文件中...")
file_path = select_excel_file(log_widget)
if file_path:
status_bar.set_status("开始处理Excel文件...")
add_to_log(log_widget, f"开始处理Excel文件: {file_path}\n", "info")
else:
status_bar.set_status("操作已取消")
add_to_log(log_widget, "未选择文件,操作已取消\n", "warning")
return
init_gui_logger(log_widget)
order_service = OrderService()
if file_path:
try:
add_recent_file(file_path)
except Exception as e:
logger.debug(f"添加最近文件失败: {e}")
result = order_service.process_excel(file_path, progress_cb=lambda p: status_bar.set_status("Excel处理中...", p))
else:
try:
latest_input = order_service.get_latest_excel()
if latest_input:
add_recent_file(latest_input)
except Exception as e:
logger.debug(f"获取最新Excel失败: {e}")
result = order_service.process_excel(progress_cb=lambda p: status_bar.set_status("Excel处理中...", p))
if result:
add_to_log(log_widget, "Excel文件处理完成\n", "success")
show_excel_result_preview(f"采购单已保存到: {result}\n")
try:
add_recent_file(result)
except Exception as e:
logger.debug(f"添加最近文件失败: {e}")
try:
validate_unit_price_against_item_data(result, log_widget)
except Exception as e:
logger.debug(f"单价校验失败: {e}")
else:
add_to_log(log_widget, "Excel文件处理失败\n", "error")
except Exception as e:
add_to_log(log_widget, f"Excel文件处理出错: {str(e)}\n", "error")
msg = str(e)
suggestion = None
if 'openpyxl' in msg or 'engine' in msg:
suggestion = "安装依赖:pip install openpyxl"
elif 'xlrd' in msg:
suggestion = "安装依赖:pip install xlrd"
if suggestion:
show_error_dialog("Excel处理错误", msg, suggestion)
finally:
dispose_gui_logger()
status_bar.set_running(False)
status_bar.set_status("就绪")
thread = Thread(target=run_in_thread)
thread.daemon = True
thread.start()
def process_dropped_file(log_widget, status_bar, file_path):
try:
ext = os.path.splitext(file_path)[1].lower()
if ext in ['.jpg', '.jpeg', '.png', '.bmp']:
def _run_img():
try:
reporter = ProgressReporter(status_bar)
reporter.running()
init_gui_logger(log_widget)
add_to_log(log_widget, f"开始一键处理图片: {file_path}\n", "info")
try:
add_recent_file(file_path)
except Exception as e:
logger.debug(f"添加最近文件失败: {e}")
# 步骤1: OCR识别
reporter.set("OCR识别中...", 10)
ocr_service = OCRService()
excel_path = ocr_service.process_image(file_path)
if not excel_path:
add_to_log(log_widget, "图片OCR处理失败\n", "error")
return
add_to_log(log_widget, f"OCR识别完成: {excel_path}\n", "success")
# 步骤2: Excel处理
reporter.set("Excel处理中...", 40)
order_service = OrderService()
result = order_service.process_excel(excel_path, progress_cb=lambda p: reporter.set("Excel处理中...", p))
if not result:
add_to_log(log_widget, "Excel处理失败\n", "error")
return
add_to_log(log_widget, f"Excel处理完成: {result}\n", "success")
try:
add_recent_file(result)
except Exception as e:
logger.debug(f"添加最近文件失败: {e}")
try:
validate_unit_price_against_item_data(result, log_widget)
except Exception as e:
logger.debug(f"单价校验失败: {e}")
# 步骤3: 合并采购单
reporter.set("检查合并采购单...", 80)
_ask_and_merge_purchase_orders(order_service, log_widget, add_to_recent=True)
reporter.set("处理完成", 100)
add_to_log(log_widget, "一键处理完成!\n", "success")
finally:
dispose_gui_logger()
reporter.done()
t = Thread(target=_run_img)
t.daemon = True
t.start()
elif ext in ['.xlsx', '.xls']:
def _run_xls():
try:
reporter = ProgressReporter(status_bar)
reporter.running()
init_gui_logger(log_widget)
order_service = OrderService()
add_to_log(log_widget, f"开始一键处理Excel文件: {file_path}\n", "info")
try:
add_recent_file(file_path)
except Exception as e:
logger.debug(f"添加最近文件失败: {e}")
# 步骤1: Excel处理
reporter.set("Excel处理中...", 20)
result = order_service.process_excel(file_path, progress_cb=lambda p: reporter.set("Excel处理中...", p))
if not result:
add_to_log(log_widget, "Excel文件处理失败\n", "error")
return
add_to_log(log_widget, f"Excel处理完成: {result}\n", "success")
try:
add_recent_file(result)
except Exception as e:
logger.debug(f"添加最近文件失败: {e}")
try:
validate_unit_price_against_item_data(result, log_widget)
except Exception as e:
logger.debug(f"单价校验失败: {e}")
# 步骤2: 合并采购单
reporter.set("检查合并采购单...", 80)
_ask_and_merge_purchase_orders(order_service, log_widget, add_to_recent=True)
reporter.set("处理完成", 100)
add_to_log(log_widget, "一键处理完成!\n", "success")
finally:
dispose_gui_logger()
reporter.done()
t = Thread(target=_run_xls)
t.daemon = True
t.start()
else:
add_to_log(log_widget, f"不支持的文件类型: {file_path}\n", "warning")
except Exception as e:
add_to_log(log_widget, f"处理拖拽文件失败: {str(e)}\n", "error")
-33
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@@ -1,33 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""条码映射编辑模块"""
from tkinter import messagebox
from app.core.excel.converter import UnitConverter
from app.core.utils.dialog_utils import show_barcode_mapping_dialog
from .logging_ui import add_to_log
def edit_barcode_mappings(log_widget):
"""编辑条码映射配置"""
try:
add_to_log(log_widget, "正在加载条码映射配置...\n", "info")
unit_converter = UnitConverter()
current_mappings = unit_converter.special_barcodes
def save_mappings(new_mappings):
success = unit_converter.update_barcode_mappings(new_mappings)
if success:
add_to_log(log_widget, f"成功保存条码映射配置,共{len(new_mappings)}\n", "success")
else:
add_to_log(log_widget, "保存条码映射配置失败\n", "error")
show_barcode_mapping_dialog(None, save_mappings, current_mappings)
except Exception as e:
add_to_log(log_widget, f"编辑条码映射时出错: {str(e)}\n", "error")
messagebox.showerror("错误", f"编辑条码映射时出错: {str(e)}")
-160
View File
@@ -1,160 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""命令执行器模块"""
import os
import sys
import time
import subprocess
import datetime
import re
import tkinter as tk
from tkinter import messagebox
from threading import Thread
from .logging_ui import LogRedirector
from .result_previews import show_result_preview
# 任务状态跟踪
_RUNNING_TASK = None
def get_running_task():
return _RUNNING_TASK
def set_running_task(val):
global _RUNNING_TASK
_RUNNING_TASK = val
def run_command_with_logging(command, log_widget, status_bar=None, on_complete=None):
"""运行命令并将输出重定向到日志窗口"""
if _RUNNING_TASK is not None:
messagebox.showinfo("任务进行中", "请等待当前任务完成后再执行新的操作。")
return
def run_in_thread():
global _RUNNING_TASK
_RUNNING_TASK = command
if status_bar:
status_bar.set_running(True)
start_time = datetime.datetime.now()
start_perf = time.perf_counter()
log_widget.configure(state=tk.NORMAL)
log_widget.delete(1.0, tk.END)
log_widget.insert(tk.END, f"执行命令: {' '.join(command)}\n", "command")
log_widget.insert(tk.END, f"开始时间: {start_time.strftime('%Y-%m-%d %H:%M:%S')}\n", "time")
log_widget.insert(tk.END, "=" * 50 + "\n\n", "separator")
log_widget.configure(state=tk.DISABLED)
old_stdout = sys.stdout
old_stderr = sys.stderr
log_redirector = LogRedirector(log_widget)
env = os.environ.copy()
try:
from app.config.settings import ConfigManager
cfg = ConfigManager()
env["OCR_OUTPUT_DIR"] = cfg.get_path('Paths', 'output_folder', fallback='data/output', create=True)
env["OCR_INPUT_DIR"] = cfg.get_path('Paths', 'input_folder', fallback='data/input', create=True)
env["OCR_TEMP_DIR"] = cfg.get_path('Paths', 'temp_folder', fallback='data/temp', create=True)
except Exception:
# 回退:使用 exe/脚本所在目录
app_root = os.path.dirname(sys.executable) if getattr(sys, 'frozen', False) else os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
env["OCR_OUTPUT_DIR"] = os.path.join(app_root, "data", "output")
env["OCR_INPUT_DIR"] = os.path.join(app_root, "data", "input")
env["OCR_TEMP_DIR"] = os.path.join(app_root, "data", "temp")
env["OCR_LOG_LEVEL"] = "DEBUG"
try:
sys.stdout = log_redirector
sys.stderr = log_redirector
print("日志重定向已启动,现在同时输出到终端和GUI")
process = subprocess.Popen(
command,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
text=True,
bufsize=1,
universal_newlines=True,
env=env
)
output_data = []
for line in process.stdout:
output_data.append(line)
print(line.rstrip())
if status_bar:
progress = extract_progress_from_log(line)
if progress is not None:
log_widget.after(0, lambda p=progress: status_bar.set_status(f"处理中: {p}%完成", p))
process.wait()
end_time = datetime.datetime.now()
duration_sec = max(0.0, time.perf_counter() - start_perf)
print(f"\n{'=' * 50}")
print(f"执行完毕!返回码: {process.returncode}")
print(f"结束时间: {end_time.strftime('%Y-%m-%d %H:%M:%S')}")
print(f"耗时: {duration_sec:.2f}")
output_text = ''.join(output_data)
is_pipeline = "pipeline" in command
no_merge_files = "未找到采购单文件" in output_text
single_file = "只有1个采购单文件" in output_text
if is_pipeline and (no_merge_files or single_file):
print("完整流程中没有需要合并的文件,但其他步骤执行成功,视为成功完成")
if status_bar:
log_widget.after(0, lambda: status_bar.set_status("处理完成", 100))
log_widget.after(0, lambda: show_result_preview(command, output_text))
else:
if on_complete:
log_widget.after(0, lambda: on_complete(process.returncode, output_text))
elif process.returncode == 0:
if status_bar:
log_widget.after(0, lambda: status_bar.set_status("处理完成", 100))
log_widget.after(0, lambda: show_result_preview(command, output_text))
else:
if status_bar:
log_widget.after(0, lambda: status_bar.set_status(f"处理失败 (返回码: {process.returncode})", 0))
log_widget.after(0, lambda: messagebox.showerror("操作失败", f"处理失败,返回码:{process.returncode}"))
except Exception as e:
print(f"\n执行出错: {str(e)}")
if status_bar:
log_widget.after(0, lambda: status_bar.set_status(f"执行出错: {str(e)}", 0))
log_widget.after(0, lambda: messagebox.showerror("执行错误", f"执行命令时出错: {str(e)}"))
finally:
sys.stdout = old_stdout
sys.stderr = old_stderr
_RUNNING_TASK = None
if status_bar:
log_widget.after(0, lambda: status_bar.set_running(False))
Thread(target=run_in_thread).start()
def extract_progress_from_log(log_line):
"""从日志行中提取进度信息"""
batch_match = re.search(r'处理批次 (\d+)/(\d+)', log_line)
if batch_match:
current = int(batch_match.group(1))
total = int(batch_match.group(2))
return int(current / total * 100)
percent_match = re.search(r'(\d+)%', log_line)
if percent_match:
return int(percent_match.group(1))
return None
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""系统设置对话框模块"""
import os
import tkinter as tk
from tkinter import messagebox, filedialog, ttk
from app.config.settings import ConfigManager
from .user_settings import load_user_settings, save_user_settings
from .ui_widgets import center_window
from app.core.utils.dialog_utils import show_cloud_sync_dialog
def show_config_dialog(root, cfg: ConfigManager):
settings = load_user_settings()
dlg = tk.Toplevel(root)
dlg.title("系统设置")
dlg.geometry("700x460")
center_window(dlg)
content = ttk.Frame(dlg)
content.pack(fill=tk.BOTH, expand=True, padx=12, pady=12)
content.columnconfigure(0, weight=1)
# ── 辅助函数 ──
def _add_pair(parent, row, col, label_text, widget, label_width=None):
"""在 parent 的 (row, col*2) 放 label, (row, col*2+1) 放 widget"""
lbl = ttk.Label(parent, text=label_text)
if label_width:
lbl.configure(width=label_width)
lbl.grid(row=row, column=col * 2, sticky='w', padx=(6, 2), pady=3)
widget.grid(row=row, column=col * 2 + 1, sticky='ew', padx=(2, 6), pady=3)
def _make_dir_widget(parent, var, label):
f = ttk.Frame(parent)
e = ttk.Entry(f, textvariable=var)
e.pack(side=tk.LEFT, fill=tk.X, expand=True)
def _select_dir():
d = filedialog.askdirectory(title=f"选择{label}")
if d:
try:
var.set(os.path.relpath(d, os.getcwd()))
except Exception:
var.set(d)
ttk.Button(f, text="选择", command=_select_dir).pack(side=tk.LEFT, padx=4)
return f
# ── 当前值 ──
log_level_val = tk.StringVar(value=settings.get('log_level', 'INFO'))
max_workers_val = tk.StringVar(value=str(settings.get('concurrency_max_workers', cfg.getint('Performance', 'max_workers', 4))))
batch_size_val = tk.StringVar(value=str(settings.get('concurrency_batch_size', cfg.getint('Performance', 'batch_size', 5))))
template_path_val = tk.StringVar(value=settings.get('template_path', os.path.join(cfg.get('Paths', 'template_folder', 'templates'), cfg.get('Templates', 'purchase_order', '银豹-采购单模板.xls'))))
input_dir_val = tk.StringVar(value=settings.get('input_folder', cfg.get('Paths', 'input_folder', 'data/input')))
output_dir_val = tk.StringVar(value=settings.get('output_folder', cfg.get('Paths', 'output_folder', 'data/output')))
result_dir_val = tk.StringVar(value=settings.get('result_folder', 'data/result'))
api_key_val = tk.StringVar(value=settings.get('api_key', cfg.get('API', 'api_key', '')))
secret_key_val = tk.StringVar(value=settings.get('secret_key', cfg.get('API', 'secret_key', '')))
timeout_val = tk.StringVar(value=str(settings.get('timeout', cfg.getint('API', 'timeout', 30))))
max_retries_val = tk.StringVar(value=str(settings.get('max_retries', cfg.getint('API', 'max_retries', 3))))
retry_delay_val = tk.StringVar(value=str(settings.get('retry_delay', cfg.getint('API', 'retry_delay', 2))))
api_url_val = tk.StringVar(value=settings.get('api_url', cfg.get('API', 'api_url', '')))
gitea_url_val = tk.StringVar(value=cfg.get('Gitea', 'base_url', fallback='https://gitea.94kan.cn'))
gitea_owner_val = tk.StringVar(value=cfg.get('Gitea', 'owner', fallback='houhuan'))
gitea_repo_val = tk.StringVar(value=cfg.get('Gitea', 'repo', fallback='yixuan-sync-data'))
gitea_token_val = tk.StringVar(value=cfg.get('Gitea', 'token', fallback=''))
# ═══════════════════════════════════════════════════
# 区块 1: 基本设置
# ═══════════════════════════════════════════════════
f1 = ttk.LabelFrame(content, text=" 基本设置 ", padding=(8, 4))
f1.pack(fill=tk.X, pady=(0, 6))
for c in range(4):
f1.columnconfigure(c, weight=1 if c % 2 == 1 else 0)
lvl = ttk.Combobox(f1, textvariable=log_level_val, values=['DEBUG', 'INFO', 'WARNING', 'ERROR'], state='readonly', width=12)
_add_pair(f1, 0, 0, "日志级别", lvl)
_add_pair(f1, 0, 1, "最大并发", ttk.Entry(f1, textvariable=max_workers_val, width=6))
_add_pair(f1, 1, 0, "批次大小", ttk.Entry(f1, textvariable=batch_size_val, width=6))
# 模板路径(带选择按钮,占右列)
tpl_frame = ttk.Frame(f1)
tpl_entry = ttk.Entry(tpl_frame, textvariable=template_path_val)
tpl_entry.pack(side=tk.LEFT, fill=tk.X, expand=True)
def _select_template():
p = filedialog.askopenfilename(title="选择模板文件", filetypes=[("Excel模板", "*.xls *.xlsx"), ("所有文件", "*.*")])
if p:
try:
template_path_val.set(os.path.relpath(p, os.getcwd()))
except Exception:
template_path_val.set(p)
ttk.Button(tpl_frame, text="选择", command=_select_template).pack(side=tk.LEFT, padx=4)
_add_pair(f1, 1, 1, "采购模板", tpl_frame)
_add_pair(f1, 2, 0, "输入目录", _make_dir_widget(f1, input_dir_val, "输入目录"))
_add_pair(f1, 2, 1, "输出目录", _make_dir_widget(f1, output_dir_val, "输出目录"))
_add_pair(f1, 3, 0, "结果目录", _make_dir_widget(f1, result_dir_val, "结果目录"))
# ═══════════════════════════════════════════════════
# 区块 2: API 设置
# ═══════════════════════════════════════════════════
f2 = ttk.LabelFrame(content, text=" API 设置 ", padding=(8, 4))
f2.pack(fill=tk.X, pady=(0, 6))
for c in range(4):
f2.columnconfigure(c, weight=1 if c % 2 == 1 else 0)
_add_pair(f2, 0, 0, "API Key", ttk.Entry(f2, textvariable=api_key_val))
secret_entry = ttk.Entry(f2, textvariable=secret_key_val, show='*')
_add_pair(f2, 0, 1, "Secret Key", secret_entry)
_add_pair(f2, 1, 0, "Timeout", ttk.Entry(f2, textvariable=timeout_val, width=6))
_add_pair(f2, 1, 1, "Max Retries", ttk.Entry(f2, textvariable=max_retries_val, width=6))
_add_pair(f2, 2, 0, "Retry Delay", ttk.Entry(f2, textvariable=retry_delay_val, width=6))
_add_pair(f2, 2, 1, "API URL", ttk.Entry(f2, textvariable=api_url_val))
# ═══════════════════════════════════════════════════
# 区块 3: 云端同步 (Gitea)
# ═══════════════════════════════════════════════════
f3 = ttk.LabelFrame(content, text=" 云端同步 (Gitea) ", padding=(8, 4))
f3.pack(fill=tk.X, pady=(0, 8))
for c in range(4):
f3.columnconfigure(c, weight=1 if c % 2 == 1 else 0)
_add_pair(f3, 0, 0, "Gitea 地址", ttk.Entry(f3, textvariable=gitea_url_val))
_add_pair(f3, 0, 1, "仓库所有者", ttk.Entry(f3, textvariable=gitea_owner_val))
_add_pair(f3, 1, 0, "仓库名称", ttk.Entry(f3, textvariable=gitea_repo_val))
_add_pair(f3, 1, 1, "Access Token", ttk.Entry(f3, textvariable=gitea_token_val, show='*'))
# ═══════════════════════════════════════════════════
# 按钮区
# ═══════════════════════════════════════════════════
btns = ttk.Frame(content)
btns.pack(fill=tk.X, pady=(4, 0))
def save_settings():
try:
s = load_user_settings()
s['log_level'] = log_level_val.get()
s['concurrency_max_workers'] = int(max_workers_val.get() or '4')
s['concurrency_batch_size'] = int(batch_size_val.get() or '5')
tp = template_path_val.get()
inp = input_dir_val.get()
outp = output_dir_val.get()
resp = result_dir_val.get()
try:
if tp:
tp = os.path.relpath(tp, os.getcwd()) if os.path.isabs(tp) else tp
if inp:
inp = os.path.relpath(inp, os.getcwd()) if os.path.isabs(inp) else inp
if outp:
outp = os.path.relpath(outp, os.getcwd()) if os.path.isabs(outp) else outp
if resp:
resp = os.path.relpath(resp, os.getcwd()) if os.path.isabs(resp) else resp
except Exception:
pass
s['template_path'] = tp
s['input_folder'] = inp
s['output_folder'] = outp
s['result_folder'] = resp
save_user_settings(s)
try:
from app.core.utils.log_utils import set_log_level
set_log_level(s['log_level'])
except Exception:
pass
try:
tpl_path = s['template_path']
tpl_dir = os.path.dirname(tpl_path)
tpl_name = os.path.basename(tpl_path)
cfg.update('Paths', 'template_folder', tpl_dir)
cfg.update('Templates', 'purchase_order', tpl_name)
try:
cfg.update('Paths', 'template_file', os.path.join(tpl_dir, tpl_name))
except Exception:
pass
cfg.update('Paths', 'input_folder', s['input_folder'])
cfg.update('Paths', 'output_folder', s['output_folder'])
cfg.update('Performance', 'max_workers', s['concurrency_max_workers'])
cfg.update('Performance', 'batch_size', s['concurrency_batch_size'])
cfg.update('API', 'api_key', api_key_val.get())
cfg.update('API', 'secret_key', secret_key_val.get())
cfg.update('API', 'timeout', timeout_val.get())
cfg.update('API', 'max_retries', max_retries_val.get())
cfg.update('API', 'retry_delay', retry_delay_val.get())
cfg.update('API', 'api_url', api_url_val.get())
cfg.update('Gitea', 'base_url', gitea_url_val.get())
cfg.update('Gitea', 'owner', gitea_owner_val.get())
cfg.update('Gitea', 'repo', gitea_repo_val.get())
cfg.update('Gitea', 'token', gitea_token_val.get())
cfg.save_config()
except Exception:
pass
messagebox.showinfo("设置已保存", "系统设置已更新并保存")
dlg.destroy()
except Exception as e:
messagebox.showerror("保存失败", str(e))
ttk.Button(btns, text="云端同步", command=lambda: show_cloud_sync_dialog(dlg)).pack(side=tk.LEFT)
ttk.Button(btns, text="取消", command=dlg.destroy).pack(side=tk.RIGHT)
ttk.Button(btns, text="保存", command=save_settings).pack(side=tk.RIGHT, padx=6)
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""错误处理工具模块"""
from tkinter import messagebox
from typing import Optional
from app.core.utils.log_utils import get_logger
logger = get_logger(__name__)
def show_error_dialog(title: str, message: str, suggestion: Optional[str] = None):
try:
full_msg = message
if suggestion:
full_msg = f"{message}\n\n建议操作:\n- {suggestion}"
messagebox.showerror(title, full_msg)
except Exception as e:
logger.debug(f"显示错误对话框失败: {e}")
def get_error_suggestion(message: str) -> Optional[str]:
msg = (message or "").lower()
if 'openpyxl' in msg or ('engine' in msg and 'xlsx' in msg):
return '安装依赖:pip install openpyxl'
if 'xlrd' in msg or ('engine' in msg and 'xls' in msg):
return '安装依赖:pip install xlrd'
if 'timeout' in msg or 'timed out' in msg:
return '检查网络,增大API超时时间或稍后重试'
if 'invalid access_token' in msg or 'access token' in msg:
return '刷新百度OCR令牌或检查api_key/secret_key'
if '429' in msg or 'too many requests' in msg:
return '降低识别频率或稍后重试'
if '模板文件不存在' in msg or ('no such file' in msg and '模板' in msg):
return '在系统设置中选择正确的模板文件路径'
if '没有找到采购单' in msg or '未在' in msg and '找到采购单' in msg:
return '确认result目录内存在采购单文件'
if 'permission denied' in msg:
return '以管理员权限运行或更改目录写入权限'
return None
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@@ -1,205 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""文件与目录操作模块"""
import os
import json
import tkinter as tk
from tkinter import messagebox, filedialog, scrolledtext
from .logging_ui import add_to_log
from .ui_widgets import center_window
from app.config.settings import ConfigManager
def select_file(log_widget, file_types=None, title="选择文件"):
"""通用文件选择对话框"""
if file_types is None:
file_types = [("所有文件", "*.*")]
file_path = filedialog.askopenfilename(title=title, filetypes=file_types)
if file_path:
add_to_log(log_widget, f"已选择文件: {file_path}\n", "info")
return file_path
def select_excel_file(log_widget):
"""选择Excel文件"""
return select_file(
log_widget,
[("Excel文件", "*.xlsx *.xls"), ("所有文件", "*.*")],
"选择Excel文件"
)
def ensure_directories():
"""确保必要的目录结构存在"""
config = ConfigManager()
directories = [
config.get_path('Paths', 'input_folder', fallback='data/input', create=True),
config.get_path('Paths', 'output_folder', fallback='data/output', create=True),
config.get_path('Paths', 'result_folder', fallback='data/result', create=True),
config.get_path('Paths', 'temp_folder', fallback='data/temp', create=True),
os.path.join(config.app_root, 'logs')
]
for directory in directories:
if not os.path.exists(directory):
os.makedirs(directory, exist_ok=True)
print(f"创建目录: {directory}")
def clean_cache(log_widget):
"""清除处理缓存"""
from .command_runner import set_running_task
try:
config = ConfigManager()
processed_record = config.get_path('Paths', 'processed_record', fallback='data/processed_files.json')
output_folder = config.get_path('Paths', 'output_folder', fallback='data/output')
cache_files = [
processed_record,
os.path.join(output_folder, "processed_files.json"),
os.path.join(output_folder, "merged_files.json")
]
for cache_file in cache_files:
if os.path.exists(cache_file):
os.remove(cache_file)
add_to_log(log_widget, f"已清除缓存文件: {cache_file}\n", "success")
temp_dir = config.get_path('Paths', 'temp_folder', fallback='data/temp')
if os.path.exists(temp_dir):
for file in os.listdir(temp_dir):
file_path = os.path.join(temp_dir, file)
try:
if os.path.isfile(file_path):
os.remove(file_path)
add_to_log(log_widget, f"已清除临时文件: {file_path}\n", "info")
except Exception as e:
add_to_log(log_widget, f"清除文件时出错: {file_path}, 错误: {str(e)}\n", "error")
log_dir = os.path.join(config.app_root, 'logs')
if os.path.exists(log_dir):
for file in os.listdir(log_dir):
if file.endswith(".active"):
file_path = os.path.join(log_dir, file)
try:
os.remove(file_path)
add_to_log(log_widget, f"已清除活动日志标记: {file_path}\n", "info")
except Exception as e:
add_to_log(log_widget, f"清除文件时出错: {file_path}, 错误: {str(e)}\n", "error")
set_running_task(None)
add_to_log(log_widget, "缓存清除完成,系统将重新处理所有文件\n", "success")
messagebox.showinfo("缓存清除", "缓存已清除,系统将重新处理所有文件。")
except Exception as e:
add_to_log(log_widget, f"清除缓存时出错: {str(e)}\n", "error")
messagebox.showerror("错误", f"清除缓存时出错: {str(e)}")
def open_result_directory():
try:
config = ConfigManager()
result_dir = config.get_path('Paths', 'result_folder', fallback='data/result', create=True)
os.startfile(result_dir)
except Exception as e:
messagebox.showerror("错误", f"无法打开结果目录: {str(e)}")
def _open_directory_from_settings(config_key, default_path, label):
"""通用的从配置读取路径并打开目录"""
try:
config = ConfigManager()
path = config.get_path('Paths', config_key, fallback=default_path, create=True)
os.startfile(path)
except Exception as e:
messagebox.showerror("错误", f"无法打开{label}: {str(e)}")
def open_input_directory_from_settings():
_open_directory_from_settings('input_folder', 'data/input', '输入目录')
def open_output_directory_from_settings():
_open_directory_from_settings('output_folder', 'data/output', '输出目录')
def open_result_directory_from_settings():
_open_directory_from_settings('result_folder', 'data/result', '结果目录')
def clean_data_files(log_widget):
"""清理数据文件(仅清理input和output目录)"""
try:
if not messagebox.askyesno("确认清理", "确定要清理input和output目录的文件吗?这将删除所有输入和输出数据。"):
add_to_log(log_widget, "操作已取消\n", "info")
return
config = ConfigManager()
files_cleaned = 0
input_dir = config.get_path('Paths', 'input_folder', fallback='data/input')
if os.path.exists(input_dir):
for file in os.listdir(input_dir):
file_path = os.path.join(input_dir, file)
if os.path.isfile(file_path):
os.remove(file_path)
files_cleaned += 1
add_to_log(log_widget, "已清理input目录\n", "info")
output_dir = config.get_path('Paths', 'output_folder', fallback='data/output')
if os.path.exists(output_dir):
for file in os.listdir(output_dir):
file_path = os.path.join(output_dir, file)
if os.path.isfile(file_path):
os.remove(file_path)
files_cleaned += 1
add_to_log(log_widget, "已清理output目录\n", "info")
add_to_log(log_widget, f"清理完成,共清理 {files_cleaned} 个文件\n", "success")
messagebox.showinfo("清理完成", f"已成功清理 {files_cleaned} 个文件")
except Exception as e:
add_to_log(log_widget, f"清理数据文件时出错: {str(e)}\n", "error")
messagebox.showerror("错误", f"清理数据文件时出错: {str(e)}")
def clean_result_files(log_widget):
try:
if not messagebox.askyesno("确认清理", "确定要清理result目录的文件吗?这将删除所有已生成的采购单文件。"):
add_to_log(log_widget, "操作已取消\n", "info")
return
config = ConfigManager()
count = 0
result_dir = config.get_path('Paths', 'result_folder', fallback='data/result')
if os.path.exists(result_dir):
for file in os.listdir(result_dir):
file_path = os.path.join(result_dir, file)
if os.path.isfile(file_path):
os.remove(file_path)
count += 1
add_to_log(log_widget, f"已清理result目录,共 {count} 个文件\n", "success")
messagebox.showinfo("清理完成", f"已清理result目录 {count} 个文件")
except Exception as e:
add_to_log(log_widget, f"清理result目录时出错: {str(e)}\n", "error")
messagebox.showerror("错误", f"清理result目录时出错: {str(e)}")
def validate_unit_price_against_item_data(result_path: str, log_widget=None):
try:
from app.services.order_service import OrderService
service = OrderService()
bad_results = service.validate_unit_price(result_path)
if bad_results:
display_count = min(len(bad_results), 10)
msg = f"存在{len(bad_results)}条单价与商品资料进货价差异超过1元:\n" + "\n".join(bad_results[:display_count])
if len(bad_results) > 10:
msg += f"\n...(其余 {len(bad_results) - 10} 条已省略)"
messagebox.showwarning("单价校验提示", msg)
if log_widget is not None:
add_to_log(log_widget, f"单价校验发现{len(bad_results)}条差异>1元\n", "warning")
else:
if log_widget is not None:
add_to_log(log_widget, "单价校验通过(差异<=1元)\n", "success")
except Exception as e:
if log_widget is not None:
add_to_log(log_widget, f"单价校验出错: {str(e)}\n", "error")
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#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""GUI日志处理模块"""
import logging
import queue
import sys
import tkinter as tk
# 全局日志队列,用于异步更新UI
LOG_QUEUE = queue.Queue()
class LogRedirector:
"""日志重定向器,用于捕获命令输出并显示到界面"""
def __init__(self, text_widget):
self.text_widget = text_widget
self.buffer = ""
self.terminal = sys.__stdout__
def write(self, string):
self.buffer += string
self.terminal.write(string)
self.text_widget.after(0, self.update_text_widget)
def update_text_widget(self):
self.text_widget.configure(state=tk.NORMAL)
if self.buffer.strip():
if any(marker in self.buffer.lower() for marker in ["错误", "error", "失败", "异常", "exception"]):
self.text_widget.insert(tk.END, self.buffer, "error")
elif any(marker in self.buffer.lower() for marker in ["警告", "warning"]):
self.text_widget.insert(tk.END, self.buffer, "warning")
elif any(marker in self.buffer.lower() for marker in ["成功", "success", "完成", "成功处理"]):
self.text_widget.insert(tk.END, self.buffer, "success")
elif any(marker in self.buffer.lower() for marker in ["info", "信息", "开始", "处理中"]):
self.text_widget.insert(tk.END, self.buffer, "info")
else:
self.text_widget.insert(tk.END, self.buffer, "normal")
else:
self.text_widget.insert(tk.END, self.buffer)
self.text_widget.see(tk.END)
self.text_widget.configure(state=tk.DISABLED)
self.buffer = ""
def flush(self):
self.terminal.flush()
class GUILogHandler(logging.Handler):
"""自定义日志处理器,将日志放入队列,由GUI主线程定时消费"""
def __init__(self, text_widget):
super().__init__()
self.text_widget = text_widget
def emit(self, record):
try:
msg = self.format(record)
if record.levelno >= logging.ERROR:
tag = "error"
elif record.levelno >= logging.WARNING:
tag = "warning"
elif record.levelno >= logging.INFO:
tag = "info"
else:
tag = "normal"
LOG_QUEUE.put((msg + "\n", tag))
except Exception:
self.handleError(record)
def poll_log_queue(text_widget):
"""定期从队列中读取日志并更新UI"""
try:
updated = False
while not LOG_QUEUE.empty():
msg, tag = LOG_QUEUE.get_nowait()
text_widget.configure(state=tk.NORMAL)
text_widget.insert(tk.END, msg, tag)
updated = True
if updated:
text_widget.see(tk.END)
text_widget.configure(state=tk.DISABLED)
except Exception:
pass
finally:
text_widget.after(100, lambda: poll_log_queue(text_widget))
def init_gui_logger(text_widget, level=logging.INFO):
handler = GUILogHandler(text_widget)
handler.setLevel(level)
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
handler.setFormatter(formatter)
root_logger = logging.getLogger()
for h in root_logger.handlers[:]:
if isinstance(h, logging.StreamHandler):
root_logger.removeHandler(h)
if not any(isinstance(h, GUILogHandler) for h in root_logger.handlers):
root_logger.addHandler(handler)
root_logger.setLevel(level)
return handler
def dispose_gui_logger():
root_logger = logging.getLogger()
for handler in root_logger.handlers[:]:
if isinstance(handler, GUILogHandler):
root_logger.removeHandler(handler)
try:
handler.close()
except Exception:
pass
def add_to_log(log_widget, text, tag="normal"):
"""向日志队列添加文本,由 poll_log_queue 消费并更新 UI"""
if log_widget is None:
print(f"[{tag}] {text}", end="")
return
LOG_QUEUE.put((text, tag))
-501
View File
@@ -1,501 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""主窗口模块"""
import os
import sys
import subprocess
import tkinter as tk
from tkinter import messagebox, filedialog, scrolledtext
from app.config.settings import ConfigManager
from app.core.utils.log_utils import set_log_level
from .theme import THEMES, get_theme_mode, set_theme_mode, create_modern_button, create_card_frame
from .logging_ui import add_to_log, poll_log_queue
from .ui_widgets import StatusBar
from .user_settings import (
load_user_settings, save_user_settings, refresh_recent_list_widget,
_extract_path_from_recent_item, clear_recent_files, RECENT_LIST_WIDGET,
)
from .file_operations import (
ensure_directories, open_result_directory, clean_cache,
clean_data_files, clean_result_files,
)
from .action_handlers import (
process_single_image_with_status, run_pipeline_directly,
batch_ocr_with_status, batch_process_orders_with_status,
merge_orders_with_status, process_excel_file_with_status,
process_dropped_file,
)
from .memory_editor import show_memory_editor
from .config_dialog import show_config_dialog
from .barcode_editor import edit_barcode_mappings
from .shortcuts import bind_keyboard_shortcuts
from app.core.utils.dialog_utils import show_cloud_sync_dialog
def _init_window():
"""初始化窗口、主题和设置,返回 (root, theme, settings, dnd_supported)"""
ensure_directories()
dnd_supported = False
try:
from tkinterdnd2 import TkinterDnD, DND_FILES
root = TkinterDnD.Tk()
dnd_supported = True
except Exception:
root = tk.Tk()
settings = load_user_settings()
theme_mode = settings.get('theme_mode', get_theme_mode())
set_theme_mode(theme_mode)
try:
cfg_for_title = ConfigManager()
ver = cfg_for_title.get('App', 'version', fallback='dev')
root.title(f"益选-OCR订单处理系统 v{ver} by 欢欢欢")
except Exception:
root.title("益选-OCR订单处理系统 by 欢欢欢")
root.geometry("900x600")
settings['window_size'] = "900x600"
theme = THEMES[get_theme_mode()]
root.configure(bg=theme["bg"])
try:
log_level = settings.get('log_level')
if log_level:
set_log_level(log_level)
concurrency = settings.get('concurrency_max_workers')
if concurrency:
cfg = ConfigManager()
cfg.update('Performance', 'max_workers', str(concurrency))
cfg.save_config()
except Exception:
pass
try:
root.iconbitmap(default="")
except Exception:
pass
return root, theme, settings, dnd_supported
def _create_left_panel(content_frame, theme, log_text, status_bar):
"""创建左侧面板:完整流程、OCR处理、Excel处理、最近文件"""
left_panel = create_card_frame(content_frame)
left_panel.pack(side=tk.LEFT, fill=tk.BOTH, expand=False, padx=(0, 5), pady=5)
left_panel.configure(width=160)
panel_content = tk.Frame(left_panel, bg=theme["card_bg"])
panel_content.pack(fill=tk.BOTH, expand=True, padx=10, pady=(5, 10))
# 完整流程区
pipeline_section = tk.LabelFrame(
panel_content, text="完整流程", bg=theme["card_bg"], fg=theme["fg"],
font=("Microsoft YaHei UI", 10, "bold"), relief="flat", borderwidth=0
)
pipeline_section.pack(fill=tk.X, pady=(0, 8))
pipeline_frame = tk.Frame(pipeline_section, bg=theme["card_bg"])
pipeline_frame.pack(fill=tk.X, padx=8, pady=6)
create_modern_button(pipeline_frame, "一键处理", lambda: run_pipeline_directly(log_text, status_bar), "primary", px_width=150, px_height=32).pack(anchor='w', pady=3)
# OCR处理区
core_section = tk.LabelFrame(
panel_content, text="OCR处理", bg=theme["card_bg"], fg=theme["fg"],
font=("Microsoft YaHei UI", 10, "bold"), relief="flat", borderwidth=0
)
core_section.pack(fill=tk.X, pady=(0, 8))
core_buttons_frame = tk.Frame(core_section, bg=theme["card_bg"])
core_buttons_frame.pack(fill=tk.X, padx=8, pady=6)
core_row1 = tk.Frame(core_buttons_frame, bg=theme["card_bg"])
core_row1.pack(fill=tk.X, pady=3)
create_modern_button(core_row1, "批量识别", lambda: batch_ocr_with_status(log_text, status_bar), "primary", px_width=72, px_height=32).pack(side=tk.LEFT, padx=(0, 3))
create_modern_button(core_row1, "单个识别", lambda: process_single_image_with_status(log_text, status_bar), "primary", px_width=72, px_height=32).pack(side=tk.LEFT, padx=(3, 0))
# Excel处理区
ocr_section = tk.LabelFrame(
panel_content, text="Excel处理", bg=theme["card_bg"], fg=theme["fg"],
font=("Microsoft YaHei UI", 10, "bold"), relief="flat", borderwidth=0
)
ocr_section.pack(fill=tk.X, pady=(0, 8))
ocr_buttons_frame = tk.Frame(ocr_section, bg=theme["card_bg"])
ocr_buttons_frame.pack(fill=tk.X, padx=8, pady=6)
ocr_row1 = tk.Frame(ocr_buttons_frame, bg=theme["card_bg"])
ocr_row1.pack(fill=tk.X, pady=3)
create_modern_button(ocr_row1, "批量处理", lambda: batch_process_orders_with_status(log_text, status_bar), "primary", px_width=72, px_height=32).pack(side=tk.LEFT, padx=(0, 3))
create_modern_button(ocr_row1, "单个处理", lambda: process_excel_file_with_status(log_text, status_bar), "primary", px_width=72, px_height=32).pack(side=tk.LEFT, padx=(3, 0))
# 最近文件区
_create_recent_files_section(panel_content, theme, log_text)
def _create_recent_files_section(parent, theme, log_text):
"""创建最近文件列表区域"""
recent_section = tk.LabelFrame(
parent, text="最近文件", bg=theme["card_bg"], fg=theme["fg"],
font=("Microsoft YaHei UI", 10, "bold"), relief="flat", borderwidth=0
)
recent_section.pack(fill=tk.BOTH, pady=(0, 12))
recent_frame = tk.Frame(recent_section, bg=theme["card_bg"])
recent_frame.pack(fill=tk.BOTH, padx=8, pady=6)
recent_top = tk.Frame(recent_frame, bg=theme["card_bg"])
recent_top.pack(fill=tk.X)
def _resize_recent_top(e):
try:
h = max(int(e.height * 0.85), 180)
recent_top.configure(height=h)
except Exception:
pass
try:
recent_top.pack_propagate(False)
except Exception:
pass
recent_frame.bind('<Configure>', _resize_recent_top)
recent_rect = tk.Frame(recent_top, bg=theme["card_bg"], highlightbackground=theme["border"], highlightthickness=1)
recent_rect.pack(fill=tk.BOTH, expand=True)
recent_list = tk.Listbox(recent_rect, height=20)
recent_scrollbar = tk.Scrollbar(recent_rect)
recent_list.configure(yscrollcommand=recent_scrollbar.set)
recent_scrollbar.configure(command=recent_list.yview)
recent_list.pack(side=tk.LEFT, fill=tk.BOTH, expand=True)
recent_scrollbar.pack(side=tk.RIGHT, fill=tk.Y)
import app.ui.user_settings as _us_mod
_us_mod.RECENT_LIST_WIDGET = recent_list
def _open_selected_event(evt=None):
try:
idxs = recent_list.curselection()
if not idxs:
return
p = _extract_path_from_recent_item(recent_list.get(idxs[0]))
if os.path.exists(p):
os.startfile(p)
else:
messagebox.showwarning("文件不存在", p)
except Exception as e:
messagebox.showerror("打开失败", str(e))
recent_list.bind('<Double-Button-1>', _open_selected_event)
refresh_recent_list_widget()
rf_btns = tk.Frame(recent_frame, bg=theme["card_bg"])
rf_btns.pack(fill=tk.X, pady=6)
def clear_list():
clear_recent_files()
recent_list.delete(0, tk.END)
create_modern_button(rf_btns, "清空列表", clear_list, "primary", px_width=72, px_height=32).pack(side=tk.LEFT, padx=(3, 0))
def purge_invalid():
try:
kept = []
for i in range(recent_list.size()):
item = recent_list.get(i)
p = _extract_path_from_recent_item(item)
if os.path.exists(p):
kept.append(p)
try:
kept_sorted = sorted(kept, key=lambda p: os.path.getmtime(p), reverse=True)
except Exception:
kept_sorted = kept
s = load_user_settings()
s['recent_files'] = kept_sorted
save_user_settings(s)
recent_list.delete(0, tk.END)
for i, p in enumerate(s['recent_files'][:recent_list.size() or len(s['recent_files'])], start=1):
recent_list.insert(tk.END, f"{i}. {p}")
refresh_recent_list_widget()
add_to_log(log_text, "已清理无效的最近文件条目\n", "success")
except Exception as e:
messagebox.showerror("清理失败", str(e))
create_modern_button(rf_btns, "清理无效", purge_invalid, "primary", px_width=72, px_height=32).pack(side=tk.LEFT, padx=(3, 0))
def _create_right_panel(content_frame, theme, log_text, root):
"""创建右侧面板:快捷操作、系统设置"""
right_panel = create_card_frame(content_frame)
right_panel.pack(side=tk.RIGHT, fill=tk.BOTH, expand=False, padx=(5, 0), pady=5)
right_panel.configure(width=380)
right_panel_content = tk.Frame(right_panel, bg=theme["card_bg"])
right_panel_content.pack(fill=tk.BOTH, expand=True, padx=10, pady=(5, 10))
# 工具功能区
tools_section = tk.LabelFrame(
right_panel_content, text="快捷操作", bg=theme["card_bg"], fg=theme["fg"],
font=("Microsoft YaHei UI", 10, "bold"), relief="flat", borderwidth=0
)
tools_section.pack(fill=tk.X, pady=(0, 8))
tools_buttons_frame = tk.Frame(tools_section, bg=theme["card_bg"])
tools_buttons_frame.pack(fill=tk.X, padx=8, pady=6)
tk.Frame(tools_buttons_frame, bg=theme["card_bg"]).pack(fill=tk.X, pady=3)
create_modern_button(tools_buttons_frame, "打开结果目录", lambda: open_result_directory(), "primary", px_width=132, px_height=32).pack(anchor='w', pady=3)
create_modern_button(tools_buttons_frame, "打开输出目录", lambda: os.startfile(ConfigManager().get_path('Paths', 'output_folder', fallback='data/output', create=True)), "primary", px_width=132, px_height=32).pack(anchor='w', pady=3)
create_modern_button(tools_buttons_frame, "打开输入目录", lambda: os.startfile(ConfigManager().get_path('Paths', 'input_folder', fallback='data/input', create=True)), "primary", px_width=132, px_height=32).pack(anchor='w', pady=3)
create_modern_button(tools_buttons_frame, "合并订单", lambda: merge_orders_with_status(log_text, StatusBar(root)), "primary", px_width=132, px_height=32).pack(anchor='w', pady=3)
create_modern_button(tools_buttons_frame, "清除缓存", lambda: clean_cache(log_text), "primary", px_width=132, px_height=32).pack(anchor='w', pady=3)
create_modern_button(tools_buttons_frame, "清理input/out文件", lambda: clean_data_files(log_text), "primary", px_width=132, px_height=32).pack(anchor='w', pady=3)
create_modern_button(tools_buttons_frame, "清理result文件", lambda: clean_result_files(log_text), "primary", px_width=132, px_height=32).pack(anchor='w', pady=3)
# 系统设置区
settings_section = tk.LabelFrame(
right_panel_content, text="系统设置", bg=theme["card_bg"], fg=theme["fg"],
font=("Microsoft YaHei UI", 10, "bold"), relief="flat", borderwidth=0
)
settings_section.pack(fill=tk.X, pady=(0, 8))
settings_buttons_frame = tk.Frame(settings_section, bg=theme["card_bg"])
settings_buttons_frame.pack(fill=tk.X, padx=8, pady=6)
create_modern_button(settings_buttons_frame, "系统设置", lambda: show_config_dialog(root, ConfigManager()), "primary", px_width=132, px_height=32).pack(anchor='w', pady=3)
create_modern_button(settings_buttons_frame, "条码映射", lambda: edit_barcode_mappings(log_text), "primary", px_width=132, px_height=32).pack(anchor='w', pady=3)
create_modern_button(settings_buttons_frame, "云端同步", lambda: show_cloud_sync_dialog(root), "primary", px_width=132, px_height=32).pack(anchor='w', pady=3)
create_modern_button(settings_buttons_frame, "商品记忆库", lambda: show_memory_editor(root), "primary", px_width=132, px_height=32).pack(anchor='w', pady=3)
def _setup_drag_area(mid_container, theme, dnd_supported, log_text, status_bar):
"""创建拖拽/点击选择文件区域"""
drag_panel = create_card_frame(mid_container)
drag_panel.pack(side=tk.TOP, fill=tk.X, padx=(5, 5), pady=(0, 5))
drag_panel_content = tk.Frame(drag_panel, bg=theme["card_bg"])
drag_panel_content.pack(fill=tk.X, padx=10, pady=6)
dnd_section = tk.LabelFrame(
drag_panel_content, bg=theme["card_bg"], fg=theme["fg"],
font=("Microsoft YaHei UI", 10, "bold"), relief="flat", borderwidth=0
)
dnd_section.pack(fill=tk.X, pady=(0, 0))
dnd_frame = tk.Frame(dnd_section, bg=theme["card_bg"], highlightthickness=1, highlightbackground=theme["border"])
dnd_frame.configure(height=60)
dnd_frame.pack(fill=tk.X, padx=8, pady=6)
try:
dnd_frame.pack_propagate(False)
except Exception:
pass
def _set_highlight(active: bool):
try:
dnd_frame.configure(highlightbackground=theme["info"] if active else theme["border"])
except Exception:
pass
dnd_frame.bind('<Enter>', lambda e: _set_highlight(True))
dnd_frame.bind('<Leave>', lambda e: _set_highlight(False))
msg_row = tk.Frame(dnd_frame, bg=theme["card_bg"])
msg_row.pack(fill=tk.X)
if dnd_supported:
tk.Label(
msg_row, text="拖拽已启用:拖拽或点击此区域选择文件",
bg=theme["card_bg"], fg="#999999", justify="center"
).pack(fill=tk.X)
else:
tk.Label(
msg_row, text="点击此区域选择文件;可安装拖拽支持",
bg=theme["card_bg"], fg="#999999", justify="center"
).pack(fill=tk.X)
if not dnd_supported:
btn_row = tk.Frame(dnd_frame, bg=theme["card_bg"])
btn_row.pack(fill=tk.X)
is_frozen = getattr(sys, 'frozen', False)
def copy_install():
try:
mid_container.winfo_toplevel().clipboard_clear()
mid_container.winfo_toplevel().clipboard_append("pip install tkinterdnd2")
messagebox.showinfo("已复制", "已复制安装命令:pip install tkinterdnd2")
except Exception as e:
messagebox.showwarning("复制失败", str(e))
if is_frozen:
tk.Label(
btn_row, text="EXE版不支持运行时安装,请用源码版安装后重新打包",
bg=theme["card_bg"], fg="#999999", font=("Microsoft YaHei UI", 8)
).pack(side=tk.RIGHT, padx=4)
else:
def install_and_restart():
try:
add_to_log(log_text, "开始安装拖拽支持库 tkinterdnd2...\n", "info")
cmd = [sys.executable, "-m", "pip", "install", "tkinterdnd2"]
result = subprocess.run(cmd, check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE, text=True)
add_to_log(log_text, result.stdout + "\n", "info")
add_to_log(log_text, "安装成功,准备重启程序以启用拖拽...\n", "success")
if messagebox.askyesno("安装完成", "已安装拖拽支持,是否立即重启应用?"):
os.execl(sys.executable, sys.executable, *sys.argv)
except subprocess.CalledProcessError as e:
add_to_log(log_text, f"安装失败: {e.stderr}\n", "error")
messagebox.showerror("安装失败", f"安装输出:\n{e.stderr}")
except Exception as e:
add_to_log(log_text, f"安装失败: {str(e)}\n", "error")
messagebox.showerror("安装失败", str(e))
create_modern_button(btn_row, "一键安装拖拽", install_and_restart, "primary", px_width=132, px_height=28).pack(side=tk.RIGHT, padx=(3, 0))
create_modern_button(btn_row, "复制安装命令", copy_install, "primary", px_width=132, px_height=28).pack(side=tk.RIGHT)
# 点击拖拽框选择文件
def _click_select(evt=None):
try:
files = filedialog.askopenfilenames(
title="选择图片或Excel文件",
filetypes=[
("支持文件", "*.xlsx *.xls *.jpg *.jpeg *.png *.bmp"),
("Excel", "*.xlsx *.xls"),
("图片", "*.jpg *.jpeg *.png *.bmp"),
("所有文件", "*.*"),
]
)
if not files:
return
for p in files:
process_dropped_file(log_text, status_bar, p)
except Exception as e:
messagebox.showerror("选择失败", str(e))
dnd_frame.bind('<Button-1>', _click_select)
msg_row.bind('<Button-1>', _click_select)
if dnd_supported:
def _on_drop(event):
try:
data = event.data
paths = []
buf = ""
in_brace = False
for ch in data:
if ch == '{':
in_brace = True
buf = ""
elif ch == '}':
in_brace = False
paths.append(buf)
buf = ""
elif ch == ' ' and not in_brace:
if buf:
paths.append(buf)
buf = ""
else:
buf += ch
if buf:
paths.append(buf)
for p in paths:
process_dropped_file(log_text, status_bar, p)
except Exception as e:
add_to_log(log_text, f"拖拽处理失败: {str(e)}\n", "error")
try:
from tkinterdnd2 import DND_FILES
dnd_frame.drop_target_register(DND_FILES)
dnd_frame.dnd_bind('<<Drop>>', _on_drop)
except Exception:
pass
def _create_log_panel(mid_container, theme):
"""创建中间日志面板,返回 log_text widget"""
log_panel = create_card_frame(mid_container, "处理日志")
log_panel.pack(side=tk.TOP, fill=tk.BOTH, expand=True, padx=(5, 5), pady=5)
log_text = scrolledtext.ScrolledText(
log_panel, wrap=tk.WORD, width=68, height=26,
bg=theme["log_bg"], fg=theme["log_fg"],
font=("Consolas", 9), state=tk.DISABLED,
relief="flat", borderwidth=0
)
log_text.pack(fill=tk.BOTH, expand=True, padx=10, pady=(5, 10))
log_text.tag_configure("command", foreground=theme["info"], font=("Consolas", 9, "bold"))
log_text.tag_configure("time", foreground=theme["secondary_bg"], font=("Consolas", 8))
log_text.tag_configure("separator", foreground=theme["border"])
log_text.tag_configure("success", foreground=theme["success"], font=("Consolas", 9, "bold"))
log_text.tag_configure("error", foreground=theme["error"], font=("Consolas", 9, "bold"))
log_text.tag_configure("warning", foreground=theme["warning"], font=("Consolas", 9, "bold"))
log_text.tag_configure("info", foreground=theme["info"], font=("Consolas", 9))
poll_log_queue(log_text)
try:
_ver = ConfigManager().get('App', 'version', fallback='')
_ver_str = f" v{_ver}" if _ver else ""
except Exception:
_ver_str = ""
add_to_log(log_text, f"欢迎使用 益选-OCR订单处理系统{_ver_str}\n", "success")
add_to_log(log_text, "系统已就绪,请选择相应功能进行操作。\n\n", "info")
add_to_log(log_text, "功能说明:\n", "command")
add_to_log(log_text, "• 完整处理流程:一键完成OCR识别和Excel处理\n", "info")
add_to_log(log_text, "• 批量处理订单:批量处理多个订单文件\n", "info")
add_to_log(log_text, "• 处理烟草订单:专门处理烟草类订单\n", "info")
add_to_log(log_text, "• 合并订单:将多个订单合并为一个文件\n\n", "info")
cfg = ConfigManager()
add_to_log(log_text, f"请将需要处理的图片文件放入 {cfg.get_path('Paths', 'input_folder', fallback='data/input')} 目录中。\n", "warning")
add_to_log(log_text, f"OCR识别结果保存在 {cfg.get_path('Paths', 'output_folder', fallback='data/output')} 目录,处理完成的订单保存在 {cfg.get_path('Paths', 'result_folder', fallback='data/result')} 目录中。\n\n", "warning")
add_to_log(log_text, "=" * 50 + "\n\n", "separator")
return log_text
def main():
"""主函数"""
try:
root, theme, settings, dnd_supported = _init_window()
# 主容器
main_container = tk.Frame(root, bg=theme["bg"])
main_container.pack(fill=tk.BOTH, expand=True, padx=10, pady=10)
content_frame = tk.Frame(main_container, bg=theme["bg"])
content_frame.pack(fill=tk.BOTH, expand=True)
# 中间容器(拖拽区 + 日志区)
mid_container = tk.Frame(content_frame, bg=theme["bg"])
mid_container.pack(side=tk.LEFT, fill=tk.BOTH, expand=True, padx=(5, 5), pady=5)
log_text = _create_log_panel(mid_container, theme)
# 状态栏
status_bar = StatusBar(root)
status_bar.pack(side=tk.BOTTOM, fill=tk.X)
# 左侧面板
_create_left_panel(content_frame, theme, log_text, status_bar)
# 右侧面板
_create_right_panel(content_frame, theme, log_text, root)
# 拖拽区域
_setup_drag_area(mid_container, theme, dnd_supported, log_text, status_bar)
# 快捷键 + 关闭事件
def on_close():
try:
w = root.winfo_width()
h = root.winfo_height()
settings['window_size'] = f"{w}x{h}"
settings['theme_mode'] = get_theme_mode()
save_user_settings(settings)
except Exception:
pass
root.destroy()
root.protocol("WM_DELETE_WINDOW", on_close)
bind_keyboard_shortcuts(root, log_text, status_bar)
root.mainloop()
except Exception as e:
import traceback
error_msg = f"程序启动失败: {str(e)}\n详细错误信息:\n{traceback.format_exc()}"
print(error_msg)
try:
import tkinter.messagebox as mb
mb.showerror("启动错误", f"程序启动失败:\n{str(e)}")
except Exception:
pass
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@@ -1,198 +0,0 @@
"""商品记忆库查看/编辑对话框"""
import os
import tkinter as tk
from tkinter import ttk, messagebox, simpledialog
from app.config.settings import ConfigManager
from app.core.db.product_db import ProductDatabase
from .ui_widgets import center_window
def _get_product_db():
cfg = ConfigManager()
db_path = cfg.get_path('Paths', 'product_db', fallback='data/product_cache.db') if hasattr(cfg, 'get_path') else 'data/product_cache.db'
tpl_folder = cfg.get('Paths', 'template_folder', fallback='templates')
item_data = cfg.get('Templates', 'item_data', fallback='商品资料.xlsx')
tpl_path = os.path.join(tpl_folder, item_data)
return ProductDatabase(db_path, tpl_path)
def show_memory_editor(root):
"""显示商品记忆库编辑器"""
db = _get_product_db()
dlg = tk.Toplevel(root)
dlg.title("商品记忆库")
dlg.geometry("950x520")
center_window(dlg)
# ── 顶部搜索栏 ──
top = ttk.Frame(dlg)
top.pack(fill=tk.X, padx=8, pady=(8, 4))
ttk.Label(top, text="搜索:").pack(side=tk.LEFT)
search_var = tk.StringVar()
search_entry = ttk.Entry(top, textvariable=search_var, width=30)
search_entry.pack(side=tk.LEFT, padx=4)
# ── 统计标签 ──
stats_label = ttk.Label(top, text="")
stats_label.pack(side=tk.RIGHT)
# ── Treeview ──
columns = ("barcode", "name", "specification", "unit", "price", "source", "confidence", "usage_count", "last_seen")
tree = ttk.Treeview(dlg, columns=columns, show="headings", height=18)
headers = {
"barcode": ("条码", 120),
"name": ("名称", 180),
"specification": ("规格", 80),
"unit": ("单位", 50),
"price": ("单价", 70),
"source": ("来源", 80),
"confidence": ("置信度", 60),
"usage_count": ("使用次数", 70),
"last_seen": ("最后使用", 140),
}
for col, (text, width) in headers.items():
tree.heading(col, text=text)
tree.column(col, width=width, anchor="center")
# 置信度颜色标签
tree.tag_configure("high", foreground="#28a745") # >= 80 绿
tree.tag_configure("medium", foreground="#ffc107") # 50-79 黄
tree.tag_configure("low", foreground="#dc3545") # < 50 红
scrollbar = ttk.Scrollbar(dlg, orient=tk.VERTICAL, command=tree.yview)
tree.configure(yscrollcommand=scrollbar.set)
tree.pack(side=tk.LEFT, fill=tk.BOTH, expand=True, padx=(8, 0), pady=4)
scrollbar.pack(side=tk.LEFT, fill=tk.Y, padx=(0, 8), pady=4)
# ── 数据加载 ──
all_records = []
def load_data(filter_text=""):
nonlocal all_records
all_records = db.get_all_memories()
tree.delete(*tree.get_children())
filtered = all_records
if filter_text:
ft = filter_text.lower()
filtered = [r for r in all_records
if ft in str(r.get('barcode', '')).lower()
or ft in str(r.get('name', '')).lower()]
for r in filtered:
conf = r.get('confidence', 0) or 0
tag = "high" if conf >= 80 else ("medium" if conf >= 50 else "low")
last_seen = r.get('last_seen', '') or ''
if last_seen and len(last_seen) > 16:
last_seen = last_seen[:16]
source_display = {
'template': '模板',
'ocr': 'OCR',
'user_confirmed': '手动',
}.get(r.get('source', ''), r.get('source', ''))
tree.insert("", tk.END, values=(
r.get('barcode', ''),
r.get('name', ''),
r.get('specification', ''),
r.get('unit', ''),
f"{r.get('price', 0):.2f}" if r.get('price') else '',
source_display,
conf,
r.get('usage_count', 0) or 0,
last_seen,
), tags=(tag,))
stats_label.config(text=f"{len(filtered)} / {len(all_records)}")
def on_search(*_):
load_data(search_var.get())
search_var.trace_add("write", on_search)
# ── 按钮区 ──
btn_frame = ttk.Frame(dlg)
btn_frame.pack(fill=tk.X, padx=8, pady=(0, 8))
def edit_selected():
sel = tree.selection()
if not sel:
messagebox.showwarning("提示", "请先选择一条记录")
return
item = tree.item(sel[0])
vals = item['values']
barcode = vals[0]
# 弹出编辑对话框
edit_dlg = tk.Toplevel(dlg)
edit_dlg.title(f"编辑: {barcode}")
edit_dlg.geometry("380x260")
center_window(edit_dlg)
fields = [
("名称", "name", vals[1]),
("规格", "specification", vals[2]),
("单位", "unit", vals[3]),
("单价", "price", vals[4]),
]
entries = {}
for i, (label, key, val) in enumerate(fields):
ttk.Label(edit_dlg, text=label).grid(row=i, column=0, sticky='w', padx=8, pady=4)
var = tk.StringVar(value=str(val) if val else '')
ttk.Entry(edit_dlg, textvariable=var, width=30).grid(row=i, column=1, padx=8, pady=4)
entries[key] = var
def save_edit():
updates = {}
for key, var in entries.items():
v = var.get().strip()
if key == 'price':
try:
updates[key] = float(v) if v else 0
except ValueError:
updates[key] = 0
else:
updates[key] = v
db.update_memory(barcode, updates)
edit_dlg.destroy()
load_data(search_var.get())
ttk.Button(edit_dlg, text="保存", command=save_edit).grid(row=len(fields), column=0, columnspan=2, pady=12)
def delete_selected():
sel = tree.selection()
if not sel:
messagebox.showwarning("提示", "请先选择一条记录")
return
item = tree.item(sel[0])
barcode = item['values'][0]
if messagebox.askyesno("确认删除", f"确定要删除条码 {barcode} 的记忆记录吗?"):
db.delete_memory(barcode)
load_data(search_var.get())
def reimport_template():
if messagebox.askyesno("确认", "重新从商品资料导入将重置所有模板商品的置信度为100,确定继续吗?"):
count = db.reimport()
messagebox.showinfo("完成", f"已重新导入 {count} 条记录")
load_data(search_var.get())
ttk.Button(btn_frame, text="编辑", command=edit_selected).pack(side=tk.LEFT, padx=4)
ttk.Button(btn_frame, text="删除", command=delete_selected).pack(side=tk.LEFT, padx=4)
ttk.Button(btn_frame, text="重新导入模板", command=reimport_template).pack(side=tk.LEFT, padx=4)
ttk.Button(btn_frame, text="刷新", command=lambda: load_data(search_var.get())).pack(side=tk.LEFT, padx=4)
ttk.Button(btn_frame, text="关闭", command=dlg.destroy).pack(side=tk.RIGHT, padx=4)
# 双击编辑
tree.bind("<Double-1>", lambda e: edit_selected())
# 初始加载
load_data()
-377
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@@ -1,377 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""处理结果预览对话框模块"""
import os
import re
import datetime
import tkinter as tk
from tkinter import messagebox, scrolledtext
from .theme import THEMES, get_theme_mode, apply_theme
from .ui_widgets import center_window
from app.core.utils.file_utils import format_file_size
from app.config.settings import ConfigManager
TOBACCO_PREVIEW_WINDOW = None
def _get_output_dir():
"""获取输出目录的绝对路径"""
return ConfigManager().get_path('Paths', 'output_folder', fallback='data/output', create=True)
def show_result_preview(command, output):
"""显示处理结果预览"""
if "ocr" in command:
show_ocr_result_preview(output)
elif "excel" in command:
show_excel_result_preview(output)
elif "merge" in command:
show_merge_result_preview(output)
elif "pipeline" in command:
show_pipeline_result_preview(output)
else:
messagebox.showinfo("处理完成", f"操作已成功完成!\n请在{_get_output_dir()}目录查看结果。")
def show_ocr_result_preview(output):
"""显示OCR处理结果预览"""
files_match = re.search(r'找到 (\d+) 个图片文件,其中 (\d+) 个未处理', output)
processed_match = re.search(r'所有图片处理完成, 总计: (\d+), 成功: (\d+)', output)
if processed_match:
total = int(processed_match.group(1))
success = int(processed_match.group(2))
preview = tk.Toplevel()
preview.title("OCR处理结果")
preview.geometry("400x300")
preview.resizable(False, False)
center_window(preview)
tk.Label(preview, text="OCR处理完成", font=("Arial", 16, "bold")).pack(pady=10)
result_frame = tk.Frame(preview)
result_frame.pack(pady=10, fill=tk.BOTH, expand=True)
tk.Label(result_frame, text=f"总共处理: {total} 个文件", font=("Arial", 12)).pack(anchor=tk.W, padx=20, pady=5)
tk.Label(result_frame, text=f"成功处理: {success} 个文件", font=("Arial", 12)).pack(anchor=tk.W, padx=20, pady=5)
tk.Label(result_frame, text=f"失败数量: {total - success} 个文件", font=("Arial", 12)).pack(anchor=tk.W, padx=20, pady=5)
if success == total:
result_text = "全部处理成功!"
result_color = "#28a745"
elif success > total * 0.8:
result_text = "大部分处理成功。"
result_color = "#ffc107"
else:
result_text = "处理失败较多,请检查日志。"
result_color = "#dc3545"
tk.Label(result_frame, text=result_text, font=("Arial", 12, "bold"), fg=result_color).pack(pady=10)
button_frame = tk.Frame(preview)
button_frame.pack(pady=10)
tk.Button(button_frame, text="查看输出文件", command=lambda: os.startfile(_get_output_dir())).pack(side=tk.LEFT, padx=10)
tk.Button(button_frame, text="关闭", command=preview.destroy).pack(side=tk.LEFT, padx=10)
else:
messagebox.showinfo("OCR处理完成", f"OCR处理已完成,请在{_get_output_dir()}目录查看结果。")
def show_excel_result_preview(output):
"""显示Excel处理结果预览"""
extract_match = re.search(r'提取到 (\d+) 个商品信息', output)
file_match = re.search(r'采购单已保存到: (.+?)(?:\n|$)', output)
if extract_match and file_match:
products_count = int(extract_match.group(1))
output_file = file_match.group(1)
preview = tk.Toplevel()
preview.title("Excel处理结果")
preview.geometry("450x320")
preview.resizable(False, False)
center_window(preview)
tk.Label(preview, text="Excel处理完成", font=("Arial", 16, "bold")).pack(pady=10)
result_frame = tk.Frame(preview)
result_frame.pack(pady=10, fill=tk.BOTH, expand=True)
tk.Label(result_frame, text=f"提取商品数量: {products_count}", font=("Arial", 12)).pack(anchor=tk.W, padx=20, pady=5)
tk.Label(result_frame, text=f"输出文件: {os.path.basename(output_file)}", font=("Arial", 12)).pack(anchor=tk.W, padx=20, pady=5)
tk.Label(result_frame, text="采购单已成功生成!", font=("Arial", 12, "bold"), fg="#28a745").pack(pady=10)
file_frame = tk.Frame(result_frame, relief=tk.GROOVE, borderwidth=1)
file_frame.pack(fill=tk.X, padx=15, pady=5)
tk.Label(file_frame, text="文件信息", font=("Arial", 10, "bold")).pack(anchor=tk.W, padx=10, pady=5)
try:
file_size = os.path.getsize(output_file)
file_time = datetime.datetime.fromtimestamp(os.path.getmtime(output_file))
size_text = format_file_size(file_size)
tk.Label(file_frame, text=f"文件大小: {size_text}", font=("Arial", 10)).pack(anchor=tk.W, padx=10, pady=2)
tk.Label(file_frame, text=f"创建时间: {file_time.strftime('%Y-%m-%d %H:%M:%S')}", font=("Arial", 10)).pack(anchor=tk.W, padx=10, pady=2)
except Exception:
tk.Label(file_frame, text="无法获取文件信息", font=("Arial", 10)).pack(anchor=tk.W, padx=10, pady=2)
button_frame = tk.Frame(preview)
button_frame.pack(pady=10)
tk.Button(button_frame, text="打开文件", command=lambda: os.startfile(output_file)).pack(side=tk.LEFT, padx=5)
tk.Button(button_frame, text="打开所在文件夹", command=lambda: os.startfile(os.path.dirname(output_file))).pack(side=tk.LEFT, padx=5)
tk.Button(button_frame, text="关闭", command=preview.destroy).pack(side=tk.LEFT, padx=5)
else:
messagebox.showinfo("Excel处理完成", f"Excel处理已完成,请在{_get_output_dir()}目录查看结果。")
def show_merge_result_preview(output):
"""显示合并结果预览"""
merged_match = re.search(r'合并了 (\d+) 个采购单', output)
product_match = re.search(r'共处理 (\d+) 个商品', output)
output_match = re.search(r'已保存到: (.+?)(?:\n|$)', output)
if merged_match and output_match:
merged_count = int(merged_match.group(1))
product_count = int(product_match.group(1)) if product_match else 0
output_file = output_match.group(1)
preview = tk.Toplevel()
preview.title("采购单合并结果")
preview.geometry("450x300")
preview.resizable(False, False)
apply_theme(preview)
tk.Label(preview, text="采购单合并完成", font=("Arial", 16, "bold")).pack(pady=10)
result_frame = tk.Frame(preview)
result_frame.pack(pady=10, fill=tk.BOTH, expand=True)
tk.Label(result_frame, text=f"合并采购单数量: {merged_count}", font=("Arial", 12)).pack(anchor=tk.W, padx=20, pady=5)
tk.Label(result_frame, text=f"处理商品数量: {product_count}", font=("Arial", 12)).pack(anchor=tk.W, padx=20, pady=5)
tk.Label(result_frame, text=f"输出文件: {os.path.basename(output_file)}", font=("Arial", 12)).pack(anchor=tk.W, padx=20, pady=5)
theme = THEMES[get_theme_mode()]
tk.Label(result_frame, text="采购单已成功合并!", font=("Arial", 12, "bold"), fg=theme["success"]).pack(pady=10)
button_frame = tk.Frame(preview)
button_frame.pack(pady=10)
tk.Button(button_frame, text="打开文件", command=lambda: os.startfile(output_file)).pack(side=tk.LEFT, padx=10)
tk.Button(button_frame, text="打开所在文件夹", command=lambda: os.startfile(os.path.dirname(output_file))).pack(side=tk.LEFT, padx=10)
tk.Button(button_frame, text="关闭", command=preview.destroy).pack(side=tk.LEFT, padx=10)
else:
messagebox.showinfo("采购单合并完成", f"采购单合并已完成,请在{_get_output_dir()}目录查看结果。")
def show_pipeline_result_preview(output):
"""显示完整流程结果预览"""
ocr_match = re.search(r'所有图片处理完成, 总计: (\d+), 成功: (\d+)', output)
excel_match = re.search(r'提取到 (\d+) 个商品信息', output)
output_file_match = re.search(r'采购单已保存到: (.+?)(?:\n|$)', output)
preview = tk.Toplevel()
preview.title("完整流程处理结果")
preview.geometry("500x400")
preview.resizable(False, False)
center_window(preview)
tk.Label(preview, text="完整处理流程已完成", font=("Arial", 16, "bold")).pack(pady=10)
no_files_match = re.search(r'未找到可合并的文件', output)
if no_files_match:
tk.Label(preview, text="未找到可合并的文件,但其他步骤已成功执行", font=("Arial", 12)).pack(pady=0)
result_frame = tk.Frame(preview)
result_frame.pack(pady=10, fill=tk.BOTH, expand=True)
result_text = scrolledtext.ScrolledText(result_frame, wrap=tk.WORD, height=15, width=60)
result_text.pack(fill=tk.BOTH, expand=True, padx=15, pady=5)
result_text.configure(state=tk.NORMAL)
result_text.insert(tk.END, "===== 流程执行结果 =====\n\n", "title")
result_text.insert(tk.END, "步骤1: OCR识别\n", "step")
if ocr_match:
total = int(ocr_match.group(1))
success = int(ocr_match.group(2))
result_text.insert(tk.END, f" 处理图片: {total}\n", "info")
result_text.insert(tk.END, f" 成功识别: {success}\n", "info")
if success == total:
result_text.insert(tk.END, " 结果: 全部识别成功\n", "success")
else:
result_text.insert(tk.END, f" 结果: 部分识别成功 ({success}/{total})\n", "warning")
else:
result_text.insert(tk.END, " 结果: 无OCR处理或处理信息不完整\n", "warning")
result_text.insert(tk.END, "\n步骤2: Excel处理\n", "step")
if excel_match:
products = int(excel_match.group(1))
result_text.insert(tk.END, f" 提取商品: {products}\n", "info")
result_text.insert(tk.END, " 结果: 成功生成采购单\n", "success")
if output_file_match:
output_file = output_file_match.group(1)
result_text.insert(tk.END, f" 输出文件: {os.path.basename(output_file)}\n", "info")
else:
result_text.insert(tk.END, " 结果: 无Excel处理或处理信息不完整\n", "warning")
result_text.insert(tk.END, "\n===== 整体评估 =====\n", "title")
has_errors = "错误" in output or "失败" in output
no_files_match2 = re.search(r'未找到采购单文件', output)
single_file_match = re.search(r'只有1个采购单文件', output)
if no_files_match2:
result_text.insert(tk.END, "没有找到可合并的文件,但处理流程已成功完成。\n", "warning")
result_text.insert(tk.END, "可以选择打开Excel文件或查看输出文件夹。\n", "info")
elif single_file_match:
result_text.insert(tk.END, "只有一个采购单文件,无需合并,处理流程已成功完成。\n", "warning")
result_text.insert(tk.END, "可以选择打开生成的Excel文件。\n", "info")
elif ocr_match and excel_match and not has_errors:
result_text.insert(tk.END, "流程完整执行成功!\n", "success")
elif ocr_match or excel_match:
result_text.insert(tk.END, "流程部分执行成功,请检查日志获取详情。\n", "warning")
else:
result_text.insert(tk.END, "流程执行可能存在问题,请查看详细日志。\n", "error")
result_text.tag_configure("title", font=("Arial", 12, "bold"))
result_text.tag_configure("step", font=("Arial", 11, "bold"))
result_text.tag_configure("info", font=("Arial", 10))
result_text.tag_configure("success", font=("Arial", 10, "bold"), foreground="#28a745")
result_text.tag_configure("warning", font=("Arial", 10, "bold"), foreground="#ffc107")
result_text.tag_configure("error", font=("Arial", 10, "bold"), foreground="#dc3545")
result_text.configure(state=tk.DISABLED)
button_frame = tk.Frame(preview)
button_frame.pack(pady=10)
if output_file_match:
output_file = output_file_match.group(1)
tk.Button(button_frame, text="打开Excel文件", command=lambda: os.startfile(output_file)).pack(side=tk.LEFT, padx=10)
else:
if excel_match or no_files_match or single_file_match:
output_dir = _get_output_dir()
excel_files = [f for f in os.listdir(output_dir) if f.startswith('采购单_') and (f.endswith('.xls') or f.endswith('.xlsx'))]
if excel_files:
excel_files.sort(key=lambda x: os.path.getmtime(os.path.join(output_dir, x)), reverse=True)
latest_file = os.path.join(output_dir, excel_files[0])
tk.Button(button_frame, text="打开最新Excel文件",
command=lambda: os.startfile(latest_file)).pack(side=tk.LEFT, padx=10)
tk.Button(button_frame, text="查看输出文件夹", command=lambda: os.startfile(_get_output_dir())).pack(side=tk.LEFT, padx=10)
tk.Button(button_frame, text="关闭", command=preview.destroy).pack(side=tk.LEFT, padx=10)
def show_tobacco_result_preview(returncode, output):
"""显示烟草订单处理结果预览"""
global TOBACCO_PREVIEW_WINDOW
if returncode != 0:
return
try:
try:
if TOBACCO_PREVIEW_WINDOW and TOBACCO_PREVIEW_WINDOW.winfo_exists():
TOBACCO_PREVIEW_WINDOW.lift()
return
except Exception:
TOBACCO_PREVIEW_WINDOW = None
result_file = None
order_time = "(未知)"
total_amount = "(未知)"
items_count = 0
abs_path_match = re.search(r'烟草订单处理完成,绝对路径: (.+)(?:\n|$)', output)
if abs_path_match:
result_file = abs_path_match.group(1).strip()
for line in output.split('\n'):
if "烟草公司订单处理成功" in line and "订单时间" in line:
time_match = re.search(r'订单时间: ([^,]+)', line)
amount_match = re.search(r'总金额: ([^,]+)', line)
items_match = re.search(r'处理条目: (\d+)', line)
if time_match:
order_time = time_match.group(1).strip()
if amount_match:
total_amount = amount_match.group(1).strip()
if items_match:
items_count = int(items_match.group(1).strip())
if not result_file or not os.path.exists(result_file):
default_path = os.path.join(_get_output_dir(), "银豹采购单_烟草公司.xls")
if os.path.exists(default_path):
result_file = default_path
preview = tk.Toplevel()
preview.title("烟草订单处理结果")
preview.geometry("450x320")
preview.resizable(False, False)
TOBACCO_PREVIEW_WINDOW = preview
def _close_preview():
global TOBACCO_PREVIEW_WINDOW
TOBACCO_PREVIEW_WINDOW = None
try:
preview.destroy()
except Exception:
pass
preview.protocol("WM_DELETE_WINDOW", _close_preview)
center_window(preview)
tk.Label(preview, text="烟草订单处理完成", font=("Arial", 16, "bold")).pack(pady=10)
result_frame = tk.Frame(preview)
result_frame.pack(pady=10, fill=tk.BOTH, expand=True)
tk.Label(result_frame, text=f"订单时间: {order_time}", font=("Arial", 12)).pack(anchor=tk.W, padx=20, pady=5)
tk.Label(result_frame, text=f"订单总金额: {total_amount}", font=("Arial", 12)).pack(anchor=tk.W, padx=20, pady=5)
tk.Label(result_frame, text=f"处理商品数量: {items_count}", font=("Arial", 12)).pack(anchor=tk.W, padx=20, pady=5)
if result_file and os.path.exists(result_file):
tk.Label(result_frame, text=f"输出文件: {os.path.basename(result_file)}", font=("Arial", 12)).pack(anchor=tk.W, padx=20, pady=5)
tk.Label(result_frame, text="银豹采购单已成功生成!", font=("Arial", 12, "bold"), fg="#28a745").pack(pady=10)
file_frame = tk.Frame(result_frame, relief=tk.GROOVE, borderwidth=1)
file_frame.pack(fill=tk.X, padx=15, pady=5)
tk.Label(file_frame, text="文件信息", font=("Arial", 10, "bold")).pack(anchor=tk.W, padx=10, pady=5)
try:
file_size = os.path.getsize(result_file)
file_time = datetime.datetime.fromtimestamp(os.path.getmtime(result_file))
size_text = format_file_size(file_size)
tk.Label(file_frame, text=f"文件大小: {size_text}", font=("Arial", 10)).pack(anchor=tk.W, padx=10, pady=2)
tk.Label(file_frame, text=f"创建时间: {file_time.strftime('%Y-%m-%d %H:%M:%S')}", font=("Arial", 10)).pack(anchor=tk.W, padx=10, pady=2)
except Exception:
tk.Label(file_frame, text="无法获取文件信息", font=("Arial", 10)).pack(anchor=tk.W, padx=10, pady=2)
button_frame = tk.Frame(preview)
button_frame.pack(pady=10)
tk.Button(button_frame, text="打开文件", command=lambda: os.startfile(result_file)).pack(side=tk.LEFT, padx=5)
tk.Button(button_frame, text="打开所在文件夹", command=lambda: os.startfile(os.path.dirname(result_file))).pack(side=tk.LEFT, padx=5)
tk.Button(button_frame, text="关闭", command=_close_preview).pack(side=tk.LEFT, padx=5)
else:
tk.Label(result_frame, text="未找到输出文件", font=("Arial", 12)).pack(anchor=tk.W, padx=20, pady=5)
tk.Label(result_frame, text=f"请检查{_get_output_dir()}目录", font=("Arial", 12, "bold"), fg="#dc3545").pack(pady=10)
button_frame = tk.Frame(preview)
button_frame.pack(pady=10)
tk.Button(button_frame, text="打开输出目录", command=lambda: os.startfile(_get_output_dir())).pack(side=tk.LEFT, padx=5)
tk.Button(button_frame, text="关闭", command=_close_preview).pack(side=tk.LEFT, padx=5)
preview.lift()
preview.attributes('-topmost', True)
preview.after_idle(lambda: preview.attributes('-topmost', False))
except Exception as e:
messagebox.showerror(
"处理异常",
f"显示预览时发生错误: {e}\n请检查日志了解详细信息。"
)
-60
View File
@@ -1,60 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""键盘快捷键模块"""
import tkinter as tk
from tkinter import messagebox
from .ui_widgets import center_window
from .action_handlers import (
process_single_image_with_status,
process_excel_file_with_status,
batch_ocr_with_status,
run_pipeline_directly,
merge_orders_with_status,
)
from .file_operations import clean_cache
def bind_keyboard_shortcuts(root, log_widget, status_bar):
"""绑定键盘快捷键"""
root.bind('<Control-o>', lambda e: process_single_image_with_status(log_widget, status_bar))
root.bind('<Control-e>', lambda e: process_excel_file_with_status(log_widget, status_bar))
root.bind('<Control-b>', lambda e: batch_ocr_with_status(log_widget, status_bar))
root.bind('<Control-p>', lambda e: run_pipeline_directly(log_widget, status_bar))
root.bind('<Control-m>', lambda e: merge_orders_with_status(log_widget, status_bar))
root.bind('<F5>', lambda e: clean_cache(log_widget))
root.bind('<Escape>', lambda e: root.quit() if messagebox.askyesno("确认退出", "确定要退出程序吗?") else None)
root.bind('<F1>', lambda e: show_shortcuts_help())
def show_shortcuts_help():
"""显示快捷键帮助对话框"""
help_dialog = tk.Toplevel()
help_dialog.title("快捷键帮助")
help_dialog.geometry("400x450")
center_window(help_dialog)
tk.Label(help_dialog, text="键盘快捷键", font=("Arial", 16, "bold")).pack(pady=10)
help_text = tk.Text(help_dialog, wrap=tk.WORD, width=50, height=20)
help_text.pack(padx=20, pady=10, fill=tk.BOTH, expand=True)
shortcuts = """
Ctrl+O: 处理单个图片
Ctrl+E: 处理Excel文件
Ctrl+B: OCR批量识别
Ctrl+P: 完整处理流程
Ctrl+M: 合并采购单
F5: 清除处理缓存
Esc: 退出程序
"""
help_text.insert(tk.END, shortcuts)
help_text.configure(state=tk.DISABLED)
tk.Button(help_dialog, text="确定", command=help_dialog.destroy).pack(pady=10)
help_dialog.lift()
help_dialog.attributes('-topmost', True)
help_dialog.after_idle(lambda: help_dialog.attributes('-topmost', False))
-193
View File
@@ -1,193 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""主题管理模块"""
import tkinter as tk
from tkinter import scrolledtext, ttk
# 私有主题模式变量
_theme_mode = "light"
# 浅色和深色主题颜色
THEMES = {
"light": {
"bg": "#f8f9fa",
"fg": "#212529",
"button_bg": "#ffffff",
"button_fg": "#495057",
"button_hover": "#e9ecef",
"primary_bg": "#007bff",
"primary_fg": "#ffffff",
"secondary_bg": "#6c757d",
"secondary_fg": "#ffffff",
"log_bg": "#ffffff",
"log_fg": "#212529",
"highlight_bg": "#007bff",
"highlight_fg": "#ffffff",
"border": "#dee2e6",
"success": "#28a745",
"error": "#dc3545",
"warning": "#ffc107",
"info": "#17a2b8",
"card_bg": "#ffffff",
"shadow": "#00000010"
},
"dark": {
"bg": "#1a1a1a",
"fg": "#e9ecef",
"button_bg": "#343a40",
"button_fg": "#e9ecef",
"button_hover": "#495057",
"primary_bg": "#0d6efd",
"primary_fg": "#ffffff",
"secondary_bg": "#6c757d",
"secondary_fg": "#ffffff",
"log_bg": "#212529",
"log_fg": "#e9ecef",
"highlight_bg": "#0d6efd",
"highlight_fg": "#ffffff",
"border": "#495057",
"success": "#198754",
"error": "#dc3545",
"warning": "#ffc107",
"info": "#0dcaf0",
"card_bg": "#2d3748",
"shadow": "#00000030"
}
}
def get_theme_mode() -> str:
return _theme_mode
def set_theme_mode(mode: str):
global _theme_mode
_theme_mode = mode
def create_modern_button(parent, text, command, style="primary", width=None, height=None, px_width=None, px_height=None):
"""创建现代化样式的按钮"""
theme = THEMES[_theme_mode]
if style == "primary":
bg_color = "white"
fg_color = theme["primary_bg"]
hover_color = "#f0f8ff"
border_color = theme["primary_bg"]
elif style == "secondary":
bg_color = theme["secondary_bg"]
fg_color = theme["secondary_fg"]
hover_color = theme["button_hover"]
border_color = theme["secondary_bg"]
else:
bg_color = "white"
fg_color = theme["primary_bg"]
hover_color = "#f0f8ff"
border_color = theme["primary_bg"]
button_frame = tk.Frame(parent, bg=border_color, highlightthickness=0)
button_frame.configure(relief="flat", bd=0)
if px_width or px_height:
try:
w = px_width if px_width else button_frame.winfo_reqwidth()
h = px_height if px_height else 32
button_frame.configure(width=w, height=h)
button_frame.pack_propagate(False)
except Exception:
pass
button = tk.Button(
button_frame,
text=text,
command=command,
bg=bg_color,
fg=fg_color,
font=("Microsoft YaHei UI", 8),
relief="flat",
bd=0,
padx=14,
pady=4,
anchor="center",
cursor="hand2",
activebackground=hover_color,
activeforeground=fg_color
)
if width:
button.configure(width=width)
else:
button.configure(width=12)
if height is not None:
button.configure(height=height)
else:
button.configure(height=1)
if height:
button.configure(height=height)
# 悬停效果
def on_enter(e):
button.configure(bg=hover_color)
def on_leave(e):
button.configure(bg=bg_color)
button.bind("<Enter>", on_enter)
button.bind("<Leave>", on_leave)
button_frame.bind("<Enter>", on_enter)
button_frame.bind("<Leave>", on_leave)
button.pack(fill=tk.BOTH, expand=True, padx=1, pady=1)
return button_frame
def create_card_frame(parent, title=None):
"""创建卡片样式的框架"""
theme = THEMES[_theme_mode]
card = tk.Frame(
parent,
bg=theme["card_bg"],
relief="flat",
borderwidth=1,
highlightbackground=theme["border"],
highlightthickness=1
)
if title:
title_label = tk.Label(
card,
text=title,
bg=theme["card_bg"],
fg=theme["fg"],
font=("Microsoft YaHei UI", 10, "bold")
)
title_label.pack(pady=(6, 3))
return card
def apply_theme(widget, theme_mode=None):
"""应用主题到小部件"""
if theme_mode is None:
theme_mode = _theme_mode
theme = THEMES[theme_mode]
try:
widget.configure(bg=theme["bg"], fg=theme["fg"])
except Exception:
pass
for child in widget.winfo_children():
if isinstance(child, tk.Button) and not isinstance(child, ttk.Button):
child.configure(bg=theme["button_bg"], fg=theme["button_fg"])
elif isinstance(child, scrolledtext.ScrolledText):
child.configure(bg=theme["log_bg"], fg=theme["log_fg"])
else:
try:
child.configure(bg=theme["bg"], fg=theme["fg"])
except Exception:
pass
apply_theme(child, theme_mode)
-121
View File
@@ -1,121 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""UI控件模块 - StatusBar、ProgressReporter、可折叠框架等"""
import tkinter as tk
from tkinter import ttk
from .theme import THEMES, get_theme_mode
class StatusBar(tk.Frame):
"""状态栏,显示当前系统状态和进度"""
def __init__(self, master, **kwargs):
super().__init__(master, **kwargs)
self.configure(height=25, relief=tk.SUNKEN, borderwidth=1)
self.status_label = tk.Label(self, text="就绪", anchor=tk.W, padx=5)
self.status_label.pack(side=tk.LEFT, fill=tk.X, expand=True)
self.progress = ttk.Progressbar(self, orient=tk.HORIZONTAL, length=200, mode='determinate')
self.progress.pack(side=tk.RIGHT, padx=5, pady=2)
self.progress.pack_forget()
def set_status(self, text, progress=None):
"""设置状态栏文本和进度"""
self.status_label.config(text=text)
if progress is not None and 0 <= progress <= 100:
self.progress.pack(side=tk.RIGHT, padx=5, pady=2)
self.progress.config(value=progress)
else:
self.progress.pack_forget()
def set_running(self, is_running=True):
"""设置运行状态"""
theme = THEMES[get_theme_mode()]
if is_running:
self.status_label.config(text="处理中...", foreground=theme["info"])
self.progress.pack(side=tk.RIGHT, padx=5, pady=2)
self.progress.config(mode='indeterminate')
self.progress.start()
else:
self.status_label.config(text="就绪", foreground=theme["fg"])
self.progress.stop()
self.progress.pack_forget()
class ProgressReporter:
def __init__(self, status_bar: StatusBar):
self.status_bar = status_bar
def set(self, text: str, percent: int = None):
try:
if percent is not None:
self.status_bar.set_status(text, percent)
else:
self.status_bar.set_status(text)
except Exception:
pass
def running(self):
try:
self.status_bar.set_running(True)
except Exception:
pass
def done(self):
try:
self.status_bar.set_running(False)
self.status_bar.set_status("就绪")
except Exception:
pass
def create_collapsible_frame(parent, title, initial_state=True):
"""创建可折叠的面板"""
frame = tk.Frame(parent)
frame.pack(fill=tk.X, pady=5)
title_frame = tk.Frame(frame)
title_frame.pack(fill=tk.X)
state_var = tk.BooleanVar(value=initial_state)
indicator = "" if initial_state else ""
state_label = tk.Label(title_frame, text=indicator, font=("Arial", 10, "bold"))
state_label.pack(side=tk.LEFT, padx=5)
title_label = tk.Label(title_frame, text=title, font=("Arial", 11, "bold"))
title_label.pack(side=tk.LEFT, padx=5)
content_frame = tk.Frame(frame)
if initial_state:
content_frame.pack(fill=tk.X, padx=20, pady=5)
def toggle_collapse(event=None):
current_state = state_var.get()
new_state = not current_state
state_var.set(new_state)
state_label.config(text="" if new_state else "")
if new_state:
content_frame.pack(fill=tk.X, padx=20, pady=5)
else:
content_frame.pack_forget()
title_frame.bind("<Button-1>", toggle_collapse)
state_label.bind("<Button-1>", toggle_collapse)
title_label.bind("<Button-1>", toggle_collapse)
return content_frame, state_var
def center_window(window):
"""使窗口居中显示"""
window.update_idletasks()
width = window.winfo_width()
height = window.winfo_height()
x = (window.winfo_screenwidth() // 2) - (width // 2)
y = (window.winfo_screenheight() // 2) - (height // 2)
window.geometry('{}x{}+{}+{}'.format(width, height, x, y))
-130
View File
@@ -1,130 +0,0 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""用户设置与最近文件管理模块"""
import os
import json
import re
import tkinter as tk
from typing import Dict, List, Any
from app.core.utils.log_utils import get_logger
from app.config.settings import ConfigManager
logger = get_logger(__name__)
RECENT_LIST_WIDGET = None
def load_user_settings():
try:
path = os.path.abspath(os.path.join('data', 'user_settings.json'))
if os.path.exists(path):
with open(path, 'r', encoding='utf-8') as f:
return json.load(f)
except Exception as e:
logger.debug(f"加载用户设置失败: {e}")
return {}
def save_user_settings(settings: Dict[str, Any]):
try:
os.makedirs('data', exist_ok=True)
path = os.path.abspath(os.path.join('data', 'user_settings.json'))
with open(path, 'w', encoding='utf-8') as f:
json.dump(settings, f, ensure_ascii=False, indent=2)
except Exception as e:
logger.debug(f"保存用户设置失败: {e}")
def get_recent_files() -> List[str]:
s = load_user_settings()
items = s.get('recent_files', [])
if not isinstance(items, list):
return []
def _allowed(p: str) -> bool:
try:
if not isinstance(p, str) or not os.path.isfile(p):
return False
ext = os.path.splitext(p)[1].lower()
return ext in {'.xlsx', '.xls', '.jpg', '.jpeg', '.png', '.bmp'}
except Exception:
return False
kept = [p for p in items if _allowed(p)]
if not kept:
candidates = []
cfg = ConfigManager()
for d in [cfg.get_path('Paths', 'output_folder', fallback='data/output'), cfg.get_path('Paths', 'result_folder', fallback='data/result')]:
try:
if os.path.exists(d):
for name in os.listdir(d):
p = os.path.join(d, name)
if _allowed(p):
candidates.append(p)
except Exception:
pass
if candidates:
kept = candidates
try:
kept_sorted = sorted(kept, key=lambda p: os.path.getmtime(p), reverse=True)
except Exception:
kept_sorted = kept
if kept_sorted != items or len(kept_sorted) != len(items):
s['recent_files'] = kept_sorted[:20]
save_user_settings(s)
return kept_sorted[:10]
def refresh_recent_list_widget():
try:
global RECENT_LIST_WIDGET
if RECENT_LIST_WIDGET is None:
return
RECENT_LIST_WIDGET.delete(0, tk.END)
for i, p in enumerate(get_recent_files(), start=1):
RECENT_LIST_WIDGET.insert(tk.END, f"{i}. {p}")
except Exception as e:
logger.debug(f"刷新最近文件列表失败: {e}")
def _extract_path_from_recent_item(s: str) -> str:
try:
m = re.match(r'^(\d+)\.\s+(.*)$', s)
p = m.group(2) if m else s
return p.strip().strip('"')
except Exception:
return s.strip().strip('"')
def add_recent_file(path: str) -> None:
try:
if not path:
return
try:
if not os.path.isfile(path):
return
ext = os.path.splitext(path)[1].lower()
if ext not in {'.xlsx', '.xls', '.jpg', '.jpeg', '.png', '.bmp'}:
return
except Exception:
return
s = load_user_settings()
items = s.get('recent_files', [])
items = [p for p in items if p != path]
items.insert(0, path)
s['recent_files'] = items[:20]
save_user_settings(s)
refresh_recent_list_widget()
except Exception as e:
logger.debug(f"添加最近文件失败: {e}")
def clear_recent_files():
try:
s = load_user_settings()
s['recent_files'] = []
save_user_settings(s)
except Exception as e:
logger.debug(f"清空最近文件失败: {e}")
-22
View File
@@ -57,8 +57,6 @@ hidden_imports = [
'xlwt',
'xlutils',
'requests',
'dotenv',
'tkinterdnd2',
'configparser',
'threading',
'datetime',
@@ -70,28 +68,8 @@ hidden_imports = [
'app.services.ocr_service',
'app.services.order_service',
'app.services.tobacco_service',
'app.services.processor_service',
'app.core.utils.dialog_utils',
'app.core.utils.file_utils',
'app.core.utils.log_utils',
'app.core.utils.string_utils',
'app.core.handlers.column_mapper',
'app.core.excel.converter',
'app.core.db.product_db',
'app.ui.error_utils',
'app.ui.theme',
'app.ui.logging_ui',
'app.ui.ui_widgets',
'app.ui.user_settings',
'app.ui.result_previews',
'app.ui.command_runner',
'app.ui.file_operations',
'app.ui.action_handlers',
'app.ui.barcode_editor',
'app.ui.config_dialog',
'app.ui.shortcuts',
'app.ui.main_window',
'app.ui.memory_editor',
]
a = Analysis(
+5 -22
View File
@@ -1,23 +1,17 @@
[API]
api_key =
secret_key =
api_key = O0Fgk3o69RWJ86eAX8BTHRaB
secret_key = VyZD5lzcIMgsup1uuD6Cw0pfzS20IGPZ
timeout = 30
max_retries = 3
retry_delay = 2
api_url = https://aip.baidubce.com/rest/2.0/ocr/v1/table
token_url = https://aip.baidubce.com/oauth/2.0/token
form_ocr_url = https://aip.baidubce.com/rest/2.0/solution/v1/form_ocr/get_request_result
[Paths]
input_folder = data/input
output_folder = data/output
temp_folder = data/temp
template_folder = templates
template_file = templates/银豹-采购单模板.xls
template_folder = E:\2025Code\python\orc-order-v2\templates
processed_record = data/processed_files.json
data_dir = data
product_db = data/product_cache.db
result_folder = data/result
[Performance]
max_workers = 4
@@ -27,22 +21,11 @@ skip_existing = true
[File]
allowed_extensions = .jpg,.jpeg,.png,.bmp
excel_extension = .xlsx
max_file_size_mb = 5
max_file_size_mb = 4
[Templates]
purchase_order = 银豹-采购单模板.xls
item_data = 商品资料.xlsx
[App]
version = 2026.05.05.0239
[Gitea]
base_url = https://gitea.94kan.cn
owner = houhuan
repo = yixuan-sync-data
token =
[WebAuth]
username = admin
password_hash = $2b$12$nllT8o1QIMfWKuTlpQI3G./E2NS.gqf0EHZyNkJ8gMpVa9grTXRoC
version = 2026.03.30.1036
-16
View File
@@ -231,10 +231,6 @@
"map_to": "6977826050028",
"description": "条码映射:6972556000022 -> 6977826050028"
},
"6949352266280": {
"map_to": "6949352266273",
"description": "条码映射:6949352266280 -> 6949352266273"
},
"6925019900087": {
"multiplier": 10,
"target_unit": "瓶",
@@ -257,17 +253,5 @@
"target_unit": "个",
"specification": "1*14",
"description": "友臣肉松,1盒14个"
},
"6921734933485": {
"multiplier": 12,
"target_unit": "支",
"specification": "1*12",
"description": "得力铅笔"
},
"6901826888244": {
"multiplier": 30,
"target_unit": "对",
"specification": "1*30",
"description": "南孚电池"
}
}
+2 -15
View File
@@ -1,23 +1,17 @@
[API]
api_key =
secret_key =
api_key = O0Fgk3o69RWJ86eAX8BTHRaB
secret_key = VyZD5lzcIMgsup1uuD6Cw0pfzS20IGPZ
timeout = 30
max_retries = 3
retry_delay = 2
api_url = https://aip.baidubce.com/rest/2.0/ocr/v1/table
token_url = https://aip.baidubce.com/oauth/2.0/token
form_ocr_url = https://aip.baidubce.com/rest/2.0/solution/v1/form_ocr/get_request_result
[Paths]
input_folder = data/input
output_folder = data/output
result_folder = data/result
temp_folder = data/temp
template_folder = templates
template_file = templates/银豹-采购单模板.xls
processed_record = data/processed_files.json
data_dir = data
product_db = data/product_cache.db
[Performance]
max_workers = 4
@@ -31,11 +25,4 @@ max_file_size_mb = 4
[Templates]
purchase_order = 银豹-采购单模板.xls
item_data = 商品资料.xlsx
[Gitea]
base_url = https://gitea.94kan.cn
owner = houhuan
repo = yixuan-sync-data
token = 50b61e43a141d606ae2529cd1755bc666d800e08
+10
View File
@@ -0,0 +1,10 @@
{
"window_size": "900x600",
"theme_mode": "light",
"recent_files": [
"data/result\\采购单_预处理之后_订单1774849009841.xls",
"data/output\\预处理之后_订单1774849009841.xlsx",
"E:/2025Code/python/orc-order-v2/data/output/订单1774849009841.xlsx",
"data/output\\订单1774849009841.xlsx"
]
}
-27
View File
@@ -1,27 +0,0 @@
services:
backend:
build:
context: .
dockerfile: Dockerfile.backend
container_name: yixuan-backend
ports:
- "18889:18889"
volumes:
- ./data:/app/data
- ./config.ini:/app/config.ini:ro
- ./config:/app/config:ro
- ./templates:/app/templates:ro
env_file:
- .env
restart: unless-stopped
frontend:
build:
context: .
dockerfile: Dockerfile.frontend
container_name: yixuan-frontend
ports:
- "18888:18888"
depends_on:
- backend
restart: unless-stopped
+208
View File
@@ -0,0 +1,208 @@
# OCR 订单处理系统 - 系统架构文档 (v2.2)
本文件详述了“OCR 订单处理系统”的技术架构、业务流向、数据模型及部署方案。
## 1. 系统整体架构图 (System Overall Architecture)
```mermaid
graph TB
subgraph 用户交互层
UI[启动器.py / Tkinter GUI]
CLI[headless_api.py / CLI]
end
subgraph 核心业务逻辑层
OS[OrderService / 订单调度]
OCR[OCRService / 图片识别]
SSS[SpecialSuppliersService / 特殊供应商处理]
TS[TobaccoService / 烟草处理]
EP[ExcelProcessor / 标准化转换]
end
subgraph 基础设施与存储
CONFIG[ConfigManager / JSON 配置]
FS[FileSystem / Excel 数据存储]
LOG[QueueLogger / 异步日志队列]
end
subgraph 第三方集成
OPENCLAW[OpenClaw 自动化平台]
POSPAL[银豹 POS 系统 (导出模板)]
end
UI --> OS
CLI --> OS
OPENCLAW -- 调用 --> CLI
OS --> OCR
OS --> SSS
OS --> TS
OS --> EP
EP --> FS
EP --> CONFIG
SSS --> EP
TS --> EP
OS -- 验证 --> FS
```
### 图例说明
- **用户交互层**:支持桌面 GUI 操作及专为 OpenClaw 设计的无界面 API 接入。
- **核心业务层**:各服务高度解耦,通过 `OrderService` 进行智能路由分发。
- **存储层**:系统采用“文件即数据库”的设计,利用 Excel 存储模板和商品资料,JSON 存储映射关系。
- **第三方集成**:与 OpenClaw 平台通过 CLI 接口对接,最终生成符合银豹 POS 要求的采购单。
---
## 2. 核心业务逻辑流程图 (Core Business Logic)
以“智能订单识别与预处理”为例:
```mermaid
sequenceDiagram
participant User as 用户/OpenClaw
participant OS as OrderService
participant SSS as SpecialSuppliersService
participant TS as TobaccoService
participant EP as ExcelProcessor
User->>OS: 提交 Excel 文件
OS->>OS: 扫描前50行内容特征
alt 包含 "RCDH"
OS->>SSS: 路由至蓉城易购预处理
SSS->>SSS: 按 E, N, Q, S 列强制清洗
SSS-->>OS: 返回清洗后的临时文件
else 包含 "专卖证号"
OS->>TS: 路由至烟草专用预处理
TS->>TS: 数量*10 / 单价/10 / B,E,G,H列映射
TS-->>OS: 返回清洗后的临时文件
else 包含 "杨碧月"
OS->>SSS: 路由至杨碧月列对齐流程
SSS-->>OS: 返回标准列临时文件
else 通用格式
OS->>OS: 直接跳过预处理
end
OS->>EP: 执行标准条码映射与模板填充
EP->>EP: 校验单价 (与商品资料比对)
EP-->>User: 输出最终银豹采购单 (data/result)
```
### 技术注解
- **智能指纹识别**:通过 `header=None` 读取前 50 行,避免了因标题行位置不固定导致的识别失败。
- **原子化预处理**:每个供应商逻辑独立,预处理结果均为统一格式的中间文件,确立了系统的可扩展性。
---
## 3. 技术架构分层图 (Layered Architecture)
| 分层 | 技术栈 / 组件 | 功能描述 |
| :--- | :--- | :--- |
| **表现层 (Presentation)** | Tkinter, headless_api.py | 桌面 GUI 交互与 OpenClaw 命令行接口 |
| **业务逻辑层 (Business)** | Python 3.x, Pandas, OCRService | 核心数据清洗、条码分裂、供应商特征识别 |
| **数据访问层 (Data)** | Pandas (Excel Engine), Json | 对 Excel 模板、映射表、用户设置的读写 |
| **基础设施层 (Infrastructure)** | Queue, Logging, PyInstaller | 异步日志分发、全局错误处理、EXE 打包工具 |
---
## 4. 数据架构设计 (Data Architecture)
系统未采用传统关系型数据库,而是基于 **JSON + Excel** 的混合存储架构。
### 4.1 表间关系示意 (JSON Mapping)
```mermaid
erDiagram
CONFIG_JSON ||--o{ BARCODE_MAPPING_JSON : "存储映射"
BARCODE_MAPPING_JSON {
string original_barcode "OCR识别出的原始条码"
string target_barcode "系统目标条码"
}
ITEM_DATA_EXCEL ||--o{ PURCHASE_ORDER_EXCEL : "验证单价"
ITEM_DATA_EXCEL {
string barcode "条码 (主键)"
float cost_price "进货价"
}
```
### 4.2 存储方案
- **映射关系**`barcode_mappings.json`。支持运行时动态更新,通过 `headless_api.py --update-mapping` 修改。
- **业务数据**`templates/商品资料.xlsx`。作为单价校验的权威数据源。
---
## 5. 微服务与模块化设计 (Microservices & Modularity)
虽然系统目前采用单体架构(Monolithic Architecture)以适配桌面部署环境,但在逻辑上采用了**微服务式的模块化设计**:
- **服务拆分**:每个供应商逻辑(Rongcheng, Tobacco, YangBiyue)都是独立的类,具备高度自治性。
- **解耦机制**:通过统一的 `preprocess` 契约(输入:原始文件,输出:清洗后文件)进行交互,未来可轻松迁移至独立服务。
- **进程隔离**GUI 主进程与业务处理线程通过 `queue.Queue` 进行解耦,确保处理逻辑不阻塞用户界面。
---
## 6. 部署架构图 (Deployment)
```mermaid
graph LR
subgraph 生产服务器 (Windows)
APP[orc-order-v2.exe]
DATA[data/ 目录]
LOGS[logs/ 目录]
end
subgraph 自动化平台
OC[OpenClaw]
end
OC -- 命令行调用 --> APP
APP -- 读写 --> DATA
APP -- 记录 --> LOGS
```
### 部署要点
- **便携化**:通过 PyInstaller 将 Python 运行环境与依赖打包,实现单文件/单目录部署。
- **路径无关性**:系统内部通过 `os.path.abspath` 动态计算路径,支持安装在任意盘符。
---
## 6. 安全架构图 (Security)
```mermaid
graph TD
A[外部输入] --> B{文件类型校验}
B -- 非图片/Excel --> C[拒绝处理]
B -- 图片/Excel --> D[清洗逻辑]
D --> E{单价偏差校验}
E -- 差值 > 1.0 --> F[生成警告日志/弹窗]
E -- 正常 --> G[生成采购单]
G --> H[日志埋点与审计]
```
### 安全策略
- **数据隔离**:所有处理后的文件存放在 `data/output``data/result`,不修改原始输入文件。
- **权限控制**:系统运行于用户权限下,利用 Windows 文件系统权限保护配置文件。
---
## 7. 技术债务与优化建议 (Tech Debt & Optimization)
### 7.1 当前技术债务
1. **并发限制**:目前为单进程串行处理,面对超大规模订单(万行级)可能存在阻塞。
2. **持久化局限**:使用 JSON 存储映射关系在条码量达到万级时,查询性能会下降。
3. **环境依赖**OCR 引擎高度依赖 Tesseract/PaddleOCR 等本地二进制库,部署复杂。
### 7.2 单点故障风险 (SPOF Analysis)
1. **本地环境强依赖**:所有 OCR 与 Excel 处理均在单一 Windows 节点,若该节点故障,OpenClaw 对接将完全中断。
2. **核心模板丢失**`templates/` 下的商品资料或采购单模板缺失会导致全流程崩溃。
3. **OCR 精度波动**:OCR 结果受图片质量影响,若 OCR 识别条码错误且无映射表,则该行数据将丢失。
### 7.3 架构优化建议方案
- **容灾备份**:建议将 `templates/``barcode_mappings.json` 定期备份至远程 Git 仓库(如 Gitea)。
- **分布式识别**:引入 PaddleOCR 服务端,支持多节点并发 OCR 识别,减少本地算力依赖。
- **配置热更新**:支持从远程 URL 加载 `barcode_mappings.json`,实现多机条码库同步。
- **数据回退机制**:增加中间文件持久化策略,允许在处理失败时手动干预已清洗的 Excel。
---
*附注:本文档图表均采用 Mermaid 标准编写,可直接在 VS Code (需安装 Mermaid 插件) 或 [Mermaid Live Editor](https://mermaid.live/) 中实时渲染并导出为高清 PNG/SVG 格式。*
---
*文档版本:2.2.0 | 生成日期:2026-03-31*
+23 -52
View File
@@ -10,6 +10,7 @@ OCR订单处理系统 - 无界面自动化接口
import os
import sys
import logging
import time
import argparse
import json
@@ -24,9 +25,15 @@ from app.services.ocr_service import OCRService
from app.services.order_service import OrderService
from app.services.tobacco_service import TobaccoService
from app.services.special_suppliers_service import SpecialSuppliersService
from app.core.utils.log_utils import get_logger, set_log_level
from app.core.utils.log_utils import set_log_level
logger = get_logger("HeadlessAPI")
# 配置日志输出到 stderr
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
stream=sys.stderr
)
logger = logging.getLogger("HeadlessAPI")
def get_latest_file(directory: str, extensions: List[str]) -> Optional[str]:
"""获取目录中最新的指定后缀文件"""
@@ -45,8 +52,8 @@ def get_latest_file(directory: str, extensions: List[str]) -> Optional[str]:
latest_file = max(files, key=lambda p: p.stat().st_mtime)
return str(latest_file)
def update_barcode_mapping(barcode: str, target_barcode: str = None, multiplier: float = None, unit: str = None, price: float = None, spec: str = None):
"""更新条码映射或特殊处理配置"""
def update_barcode_mapping(barcode: str, target_barcode: str):
"""更新条码映射"""
try:
config_path = os.path.join("config", "barcode_mappings.json")
mappings = {}
@@ -54,38 +61,15 @@ def update_barcode_mapping(barcode: str, target_barcode: str = None, multiplier:
with open(config_path, 'r', encoding='utf-8') as f:
mappings = json.load(f)
# 获取或创建该条码的配置
config = mappings.get(barcode, {})
if target_barcode:
config["map_to"] = target_barcode
config["description"] = config.get("description", "") + f" 条码映射 -> {target_barcode}"
if multiplier is not None:
config["multiplier"] = multiplier
config["description"] = config.get("description", "") + f" 数量倍数*{multiplier}"
if unit:
config["target_unit"] = unit
if price is not None:
config["fixed_price"] = price
if spec:
config["specification"] = spec
if not config.get("description"):
config["description"] = f"特殊条码配置: {barcode}"
mappings[barcode] = config
mappings[barcode] = target_barcode
with open(config_path, 'w', encoding='utf-8') as f:
json.dump(mappings, f, ensure_ascii=False, indent=2)
logger.info(f"成功更新条码配置: {barcode} -> {config}")
logger.info(f"成功更新条码映射: {barcode} -> {target_barcode}")
return True
except Exception as e:
logger.error(f"更新条码配置失败: {e}")
logger.error(f"更新条码映射失败: {e}")
return False
def run_pipeline(args):
@@ -96,28 +80,19 @@ def run_pipeline(args):
start_time = time.perf_counter()
final_excel = None
input_folder = config_manager.get('Paths', 'input_folder', fallback='data/input')
output_folder = config_manager.get('Paths', 'output_folder', fallback='data/output')
# 1. 处理条码映射更新
if args.update_mapping:
if not args.barcode:
print("ERROR: --barcode is required for --update-mapping", file=sys.stderr)
if not args.barcode or not args.target:
print("ERROR: --barcode and --target are required for --update-mapping", file=sys.stderr)
return None
# 至少需要一个更新项
if not any([args.target, args.multiplier, args.unit, args.price, args.spec]):
print("ERROR: At least one update option (--target, --multiplier, --unit, --price, --spec) is required", file=sys.stderr)
return None
if update_barcode_mapping(args.barcode, args.target, args.multiplier, args.unit, args.price, args.spec):
print(f"SUCCESS: Barcode configuration updated for {args.barcode}")
if update_barcode_mapping(args.barcode, args.target):
print(f"SUCCESS: Mapping updated {args.barcode} -> {args.target}")
return "MAPPING_UPDATED"
return None
# 2. 烟草公司处理 (显式指定)
if args.tobacco:
input_path = args.input or get_latest_file(output_folder, [".xlsx", ".xls"])
input_path = args.input or get_latest_file("data/output", [".xlsx", ".xls"])
if not input_path:
print("ERROR: No tobacco order file found.", file=sys.stderr)
return None
@@ -128,7 +103,7 @@ def run_pipeline(args):
# 3. 蓉城易购处理 (显式指定)
elif args.rongcheng:
input_path = args.input or get_latest_file(output_folder, [".xlsx", ".xls"])
input_path = args.input or get_latest_file("data/output", [".xlsx", ".xls"])
if not input_path:
print("ERROR: No Rongcheng Yigou order file found.", file=sys.stderr)
return None
@@ -138,7 +113,7 @@ def run_pipeline(args):
# 4. 普通 Excel 处理 (支持自动识别烟草/蓉城/杨碧月)
elif args.excel:
input_path = args.input or get_latest_file(input_folder, [".xlsx", ".xls"])
input_path = args.input or get_latest_file("data/input", [".xlsx", ".xls"])
if not input_path:
print("ERROR: No Excel file found in input.", file=sys.stderr)
return None
@@ -148,9 +123,9 @@ def run_pipeline(args):
# 5. 智能处理 (默认逻辑:自动判断图片还是 Excel)
else:
input_path = args.input or get_latest_file(input_folder, [".jpg", ".jpeg", ".png", ".bmp", ".xlsx", ".xls"])
input_path = args.input or get_latest_file("data/input", [".jpg", ".jpeg", ".png", ".bmp", ".xlsx", ".xls"])
if not input_path:
print(f"ERROR: No input file found in {input_folder}.", file=sys.stderr)
print("ERROR: No input file found in data/input.", file=sys.stderr)
return None
ext = os.path.splitext(input_path)[1].lower()
@@ -202,10 +177,6 @@ if __name__ == "__main__":
parser.add_argument('--barcode', help='待映射的原始条码 (用于 --update-mapping)')
parser.add_argument('--target', help='目标条码 (用于 --update-mapping)')
parser.add_argument('--multiplier', type=float, help='数量倍数 (例如箱转瓶填写30)')
parser.add_argument('--unit', help='目标单位 (例如"")')
parser.add_argument('--price', type=float, help='固定单价')
parser.add_argument('--spec', help='固定规格 (例如"1*30")')
args = parser.parse_args()
result = run_pipeline(args)
File diff suppressed because it is too large Load Diff
@@ -0,0 +1,2 @@
2025-08-16 00:52:17,210 - app.core.excel.handlers.barcode_mapper - INFO - 条码映射: 6937003706322 -> 6937003703833
2025-11-15 16:34:22,181 - app.core.excel.handlers.barcode_mapper - INFO - 条码映射: 6923450653012 -> 69021343
File diff suppressed because it is too large Load Diff
+369
View File
@@ -0,0 +1,369 @@
2025-08-16 00:52:16,853 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-08-16 00:52:16,861 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-14 20:52:59,975 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 20:52:59,975 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-14 20:52:59,980 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 20:52:59,980 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-14 20:52:59,985 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 20:52:59,985 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-14 20:52:59,999 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 20:52:59,999 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-14 20:53:00,004 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 20:53:00,004 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-14 21:55:05,648 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 21:55:05,656 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-14 21:55:14,957 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 21:55:14,960 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-14 21:56:00,538 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 21:56:00,562 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-14 22:00:56,344 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 22:00:56,344 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-14 22:00:56,357 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 22:00:56,357 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-14 22:00:56,364 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 22:00:56,365 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-14 23:22:38,475 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 23:22:38,475 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-14 23:53:32,028 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 23:53:32,028 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-14 23:56:57,447 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 23:56:57,447 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-15 00:18:49,537 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 00:18:49,537 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-15 00:44:36,719 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 00:44:36,720 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-15 01:58:02,054 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 01:58:02,054 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-15 09:48:24,108 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 09:48:24,126 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-15 10:06:56,596 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:06:56,620 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-15 10:10:31,639 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:10:31,653 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: templates\银豹-采购单模板.xls
2025-11-15 10:39:24,612 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:39:24,612 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 10:39:48,326 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:39:48,337 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 10:39:52,727 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 10:39:52,728 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-15 10:49:13,775 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:49:13,775 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 10:51:44,473 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:51:44,475 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 10:51:49,960 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:51:49,960 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 10:54:02,883 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:54:02,886 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 10:54:06,684 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 10:54:06,705 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-15 10:58:26,607 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:58:26,621 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 10:58:36,067 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:58:36,082 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 14:17:23,600 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 14:17:23,608 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 14:17:23,670 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 14:17:23,682 - app.core.excel.merger - WARNING - 未在 data/result 目录下找到采购单Excel文件
2025-11-15 14:17:23,718 - app.core.excel.merger - WARNING - 没有找到可合并的采购单文件
2025-11-15 14:22:16,926 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 14:22:16,935 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 15:11:57,981 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:11:57,984 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 15:11:59,649 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 15:11:59,650 - app.core.excel.merger - INFO - 找到 2 个采购单Excel文件
2025-11-15 15:12:52,674 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:12:52,692 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 15:12:54,195 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 15:12:54,206 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-15 15:21:05,667 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:21:05,673 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 15:22:01,186 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:22:01,202 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 15:25:41,372 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:25:41,379 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 15:25:42,598 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 15:25:42,601 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-15 15:34:06,486 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:34:06,497 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 15:34:08,030 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 15:34:08,041 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-15 15:37:42,584 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:37:42,592 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 15:39:11,314 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:39:11,314 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 15:43:33,538 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:43:33,548 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 15:43:37,053 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 15:43:37,054 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-15 15:54:35,546 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:54:35,559 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 15:54:38,702 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 15:54:38,713 - app.core.excel.merger - INFO - 找到 2 个采购单Excel文件
2025-11-15 16:19:42,388 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 16:19:42,388 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 16:34:22,131 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 16:34:22,132 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 16:46:22,429 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 16:46:22,440 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 16:46:28,876 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 16:46:28,896 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 16:46:37,767 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 16:46:37,782 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 16:46:39,219 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 16:46:39,230 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-15 16:48:30,476 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 16:48:30,488 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 16:48:42,047 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 16:48:42,063 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 16:48:43,633 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 16:48:43,644 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-15 16:52:35,959 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 16:52:35,969 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 16:52:37,531 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 16:52:37,541 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-15 16:57:42,442 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 16:57:42,451 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 16:59:07,007 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 16:59:07,016 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 16:59:14,595 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 16:59:14,604 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 16:59:16,171 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 16:59:16,180 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-15 17:01:30,240 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 17:01:30,245 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 17:01:31,385 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 17:01:31,395 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-15 17:04:33,243 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 17:04:33,255 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 17:04:45,041 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 17:04:45,048 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 17:04:46,493 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 17:04:46,505 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-15 17:09:39,846 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 17:09:39,851 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 17:12:37,471 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 17:12:37,476 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 17:12:39,165 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 17:12:39,173 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-15 17:28:46,834 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 17:28:46,847 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 17:28:49,875 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 17:28:49,876 - app.core.excel.merger - INFO - 找到 2 个采购单Excel文件
2025-11-15 17:59:22,818 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 17:59:22,823 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 17:59:33,491 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 17:59:33,506 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 17:59:39,835 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 17:59:39,849 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 18:00:04,153 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 18:00:04,165 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-15 18:00:07,581 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-15 18:00:07,582 - app.core.excel.merger - INFO - 找到 3 个采购单Excel文件
2025-11-15 18:01:51,698 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 18:01:51,710 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 10:48:45,534 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 10:48:45,552 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 10:56:22,516 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 10:56:22,516 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 11:23:59,373 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 11:23:59,373 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 11:26:06,795 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 11:26:06,795 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 12:51:06,910 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 12:51:06,910 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 13:03:10,562 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 13:03:10,563 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 13:03:10,583 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 13:03:10,584 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 13:18:18,247 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 13:18:18,248 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 13:18:18,270 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 13:18:18,271 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 13:51:09,017 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 13:51:09,018 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 14:25:50,027 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 14:25:50,031 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 14:25:55,596 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 14:25:55,612 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 14:25:56,992 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-16 14:25:57,001 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-16 14:39:42,980 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 14:39:42,980 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 14:39:42,995 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 14:39:42,996 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 14:59:35,437 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 14:59:35,437 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 15:03:21,893 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 15:03:21,893 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 15:08:33,545 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 15:08:33,546 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 15:11:11,240 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 15:11:11,254 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 15:11:12,200 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-16 15:11:12,212 - app.core.excel.merger - INFO - 找到 2 个采购单Excel文件
2025-11-16 15:13:47,399 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 15:13:47,401 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 15:13:50,815 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-16 15:13:50,816 - app.core.excel.merger - INFO - 找到 3 个采购单Excel文件
2025-11-16 15:15:36,200 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 15:15:36,203 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-16 15:15:39,032 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-16 15:15:39,033 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-20 18:36:13,285 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-20 18:36:13,295 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-20 18:36:14,159 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-20 18:36:14,170 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-20 18:36:42,097 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-20 18:36:42,104 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-20 18:36:43,288 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-20 18:36:43,297 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-20 18:42:25,918 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-20 18:42:25,932 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-20 18:42:26,808 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-20 18:42:26,819 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-20 18:44:11,119 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-20 18:44:11,128 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-20 18:46:17,345 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-20 18:46:17,346 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-20 18:47:03,916 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-20 18:47:03,919 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-20 18:50:11,046 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-20 18:50:11,047 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-11-20 18:56:30,337 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-20 18:56:30,348 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-11-20 18:56:34,058 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-11-20 18:56:34,061 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-12-01 22:21:09,101 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-12-01 22:21:09,105 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-12-01 22:21:20,388 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2025-12-01 22:21:20,390 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2025-12-12 11:00:14,089 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-12-12 11:00:14,095 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-12-12 11:13:15,287 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-12-12 11:13:15,288 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-12-12 11:22:25,990 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-12-12 11:22:25,990 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-12-12 11:32:26,694 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-12-12 11:32:26,694 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-12-12 11:34:40,238 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-12-12 11:34:40,238 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-12-12 11:38:53,256 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-12-12 11:38:53,260 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-12-12 11:49:38,203 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-12-12 11:49:38,203 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-12-12 12:30:07,698 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-12-12 12:30:07,700 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2025-12-12 12:32:20,579 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-12-12 12:32:20,579 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 10:20:20,144 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 10:20:20,145 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 10:21:25,355 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 10:21:25,356 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 10:21:52,469 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 10:21:52,470 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:28:54,451 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:28:54,451 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:29:24,575 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:29:24,576 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:29:24,580 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:29:24,580 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:29:58,483 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:29:58,484 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:29:58,488 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:29:58,488 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:30:29,317 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:30:29,317 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:30:29,321 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:30:29,322 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:31:51,946 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:31:51,947 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:31:51,951 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:31:51,952 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:46:00,210 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:46:00,211 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:46:00,229 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:46:00,230 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:46:02,785 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:46:02,785 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:47:05,233 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:47:05,233 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:47:05,255 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:47:05,256 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:47:06,654 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:47:06,654 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:48:28,519 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:48:28,519 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:48:28,525 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:48:28,525 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:48:30,802 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:48:30,802 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:51:44,156 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:51:44,156 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:51:44,170 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:51:44,171 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 13:51:46,072 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 13:51:46,072 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:00:52,374 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:00:52,374 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:00:52,392 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:00:52,392 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:01:20,295 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:01:20,295 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:01:20,307 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:01:20,308 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:01:24,376 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:01:24,376 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:06:58,242 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:06:58,243 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:07:00,055 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:07:00,055 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:14:46,832 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:14:46,832 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:14:47,891 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:14:47,891 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:23:18,310 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:23:18,310 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:23:20,043 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:23:20,043 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:24:02,882 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:24:02,883 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:24:04,318 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:24:04,318 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:28:39,039 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:28:39,040 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:28:39,737 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:28:39,738 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:41:11,949 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:41:11,949 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:41:33,388 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:41:33,388 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:41:47,796 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:41:47,796 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-30 14:41:49,673 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-30 14:41:49,673 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-31 08:50:15,740 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-31 08:50:15,754 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-31 08:50:17,775 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-31 08:50:17,775 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-31 08:52:46,014 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-31 08:52:46,014 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-31 08:52:47,191 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-31 08:52:47,192 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-31 09:00:01,693 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-31 09:00:01,693 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-31 09:03:11,828 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-31 09:03:11,829 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-31 09:03:13,872 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-31 09:03:13,872 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-31 09:05:33,093 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-31 09:05:33,094 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-31 09:05:33,868 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-31 09:05:33,868 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-31 09:05:36,165 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2026-03-31 09:05:36,165 - app.core.excel.merger - INFO - 找到 1 个采购单Excel文件
2026-03-31 09:07:58,235 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-31 09:07:58,235 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-31 09:07:58,352 - app.core.excel.merger - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2026-03-31 09:07:58,353 - app.core.excel.merger - INFO - 初始化PurchaseOrderMerger完成,模板文件: E:\2025Code\python\orc-order-v2\templates\银豹-采购单模板.xls
2026-03-31 09:08:00,645 - app.core.excel.merger - INFO - 搜索目录 data/result 中的采购单Excel文件
2026-03-31 09:08:00,646 - app.core.excel.merger - INFO - 找到 2 个采购单Excel文件
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2025-11-14 21:55:30,948 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-14 23:53:34,369 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-15 00:20:01,697 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-15 09:53:49,682 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-15 10:06:38,107 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-15 10:39:49,255 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-15 10:54:03,264 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-15 14:16:12,391 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-15 14:41:42,507 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-15 15:12:40,831 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-15 15:25:05,333 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-15 15:33:48,514 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-15 15:43:34,042 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-15 16:39:06,073 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-15 17:28:47,324 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-15 18:00:04,623 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-16 12:50:38,921 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-16 15:11:07,710 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-16 15:13:47,756 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-11-16 15:15:36,568 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
2025-12-01 22:21:09,536 - app.core.ocr.baidu_ocr - INFO - 成功获取访问令牌
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2025-11-14 20:52:59,972 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-14 20:52:59,973 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 20:52:59,973 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-14 20:52:59,973 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-14 20:52:59,974 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-14 20:52:59,976 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-14 20:52:59,978 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 20:52:59,978 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-14 20:52:59,978 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-14 20:52:59,978 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-14 20:52:59,982 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-14 20:52:59,982 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 20:52:59,982 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-14 20:52:59,984 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-14 20:52:59,984 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-14 20:52:59,996 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-14 20:52:59,996 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 20:52:59,996 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-14 20:52:59,997 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-14 20:52:59,997 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-14 20:53:00,001 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-14 20:53:00,001 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 20:53:00,001 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-14 20:53:00,001 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-14 20:53:00,002 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-14 21:55:14,932 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-14 21:55:14,933 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 21:55:14,935 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-14 21:55:14,936 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-14 21:55:14,937 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-14 21:55:15,025 - app.core.ocr.table_ocr - INFO - 找到 0 个图片文件,其中 0 个未处理
2025-11-14 21:55:15,031 - app.core.ocr.table_ocr - WARNING - 没有需要处理的图片
2025-11-14 21:55:30,512 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-14 21:55:30,522 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 21:55:30,535 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-14 21:55:30,547 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-14 21:55:30,563 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-14 21:55:30,612 - app.core.ocr.table_ocr - INFO - 开始处理图片: E:/2025Code/python/orc-order-v2/data/input/微信图片_20250909184135_44_108.jpg
2025-11-14 21:55:32,256 - app.core.ocr.table_ocr - INFO - 图片处理成功: E:/2025Code/python/orc-order-v2/data/input/微信图片_20250909184135_44_108.jpg, 输出文件: data/output\微信图片_20250909184135_44_108.xlsx
2025-11-14 22:00:56,334 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-14 22:00:56,335 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 22:00:56,336 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-14 22:00:56,336 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-14 22:00:56,338 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-14 22:00:56,354 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-14 22:00:56,354 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 22:00:56,354 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-14 22:00:56,355 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-14 22:00:56,355 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-14 22:00:56,361 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-14 22:00:56,361 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 22:00:56,361 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-14 22:00:56,361 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-14 22:00:56,362 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-14 23:22:38,471 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-14 23:22:38,471 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 23:22:38,472 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-14 23:22:38,472 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-14 23:22:38,472 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-14 23:53:32,026 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-14 23:53:32,026 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 23:53:32,026 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-14 23:53:32,026 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-14 23:53:32,026 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-14 23:53:34,048 - app.core.ocr.table_ocr - INFO - 开始处理图片: data\input\微信图片_20250909184135_44_108.jpg
2025-11-14 23:53:35,690 - app.core.ocr.table_ocr - INFO - 图片处理成功: data\input\微信图片_20250909184135_44_108.jpg, 输出文件: data/output\微信图片_20250909184135_44_108.xlsx
2025-11-14 23:54:00,127 - app.core.ocr.table_ocr - INFO - 开始处理图片: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:01,441 - app.core.ocr.table_ocr - INFO - 图片处理成功: data\input\微信图片_20251027125604_98_108.jpg, 输出文件: data/output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:50,647 - app.core.ocr.table_ocr - INFO - 开始处理图片: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:54:51,981 - app.core.ocr.table_ocr - INFO - 图片处理成功: data\input\微信图片_20251019141843_92_108.jpg, 输出文件: data/output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:56:57,443 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-14 23:56:57,443 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-14 23:56:57,443 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-14 23:56:57,443 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-14 23:56:57,443 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 00:18:49,534 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 00:18:49,534 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 00:18:49,534 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 00:18:49,534 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 00:18:49,535 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 00:20:01,395 - app.core.ocr.table_ocr - INFO - 开始处理图片: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:20:03,253 - app.core.ocr.table_ocr - INFO - 图片处理成功: data\input\微信图片_20251019141843_92_108.jpg, 输出文件: data/output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:44:36,717 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 00:44:36,717 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 00:44:36,717 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 00:44:36,717 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 00:44:36,718 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 01:58:02,050 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 01:58:02,051 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 01:58:02,051 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 01:58:02,051 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 01:58:02,051 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 09:48:24,086 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 09:48:24,087 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 09:48:24,087 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 09:48:24,087 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 09:48:24,088 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 09:49:24,553 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 09:49:24,553 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 09:49:24,557 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 09:49:24,560 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 09:49:24,563 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 09:53:49,094 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 09:53:49,107 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 09:53:49,118 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 09:53:49,132 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 09:53:49,147 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 09:53:49,215 - app.core.ocr.table_ocr - INFO - 找到 1 个图片文件,其中 1 个未处理
2025-11-15 09:53:49,231 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-15 09:53:49,248 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251027125604_98_108.jpg
2025-11-15 09:53:51,046 - app.core.ocr.table_ocr - INFO - 图片处理成功: data/input\微信图片_20251027125604_98_108.jpg, 输出文件: data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 09:53:51,047 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-11-15 10:06:37,789 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 10:06:37,795 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:06:37,803 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 10:06:37,811 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 10:06:37,818 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 10:06:37,843 - app.core.ocr.table_ocr - INFO - 开始处理图片: E:/2025Code/python/orc-order-v2/data/input/微信图片_20251027125604_98_108.jpg
2025-11-15 10:06:39,473 - app.core.ocr.table_ocr - INFO - 图片处理成功: E:/2025Code/python/orc-order-v2/data/input/微信图片_20251027125604_98_108.jpg, 输出文件: data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 10:39:24,607 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 10:39:24,607 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:39:24,608 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 10:39:24,608 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 10:39:24,609 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 10:39:48,299 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 10:39:48,301 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:39:48,303 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 10:39:48,305 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 10:39:48,308 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 10:39:48,365 - app.core.ocr.table_ocr - INFO - 找到 1 个图片文件,其中 1 个未处理
2025-11-15 10:39:48,368 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-15 10:39:48,392 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251027125604_98_108.jpg
2025-11-15 10:39:50,666 - app.core.ocr.table_ocr - INFO - 图片处理成功: data/input\微信图片_20251027125604_98_108.jpg, 输出文件: data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 10:39:50,667 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-11-15 10:49:13,768 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 10:49:13,769 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:49:13,769 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 10:49:13,769 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 10:49:13,770 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 10:51:44,469 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 10:51:44,469 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:51:44,469 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 10:51:44,470 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 10:51:44,470 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 10:51:49,953 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 10:51:49,954 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:51:49,954 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 10:51:49,955 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 10:51:49,955 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 10:54:02,833 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 10:54:02,834 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 10:54:02,837 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 10:54:02,841 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 10:54:02,846 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 10:54:02,940 - app.core.ocr.table_ocr - INFO - 找到 1 个图片文件,其中 1 个未处理
2025-11-15 10:54:02,943 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-15 10:54:02,973 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251027125604_98_108.jpg
2025-11-15 10:54:04,733 - app.core.ocr.table_ocr - INFO - 图片处理成功: data/input\微信图片_20251027125604_98_108.jpg, 输出文件: data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 10:54:04,738 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-11-15 14:16:11,980 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 14:16:11,982 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 14:16:11,985 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 14:16:11,997 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 14:16:11,999 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 14:16:12,028 - app.core.ocr.table_ocr - INFO - 开始处理图片: E:/2025Code/python/orc-order-v2/data/input/微信图片_20251113183218_594_278.jpg
2025-11-15 14:16:14,042 - app.core.ocr.table_ocr - INFO - 图片处理成功: E:/2025Code/python/orc-order-v2/data/input/微信图片_20251113183218_594_278.jpg, 输出文件: data/output\微信图片_20251113183218_594_278.xlsx
2025-11-15 14:41:42,172 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 14:41:42,173 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 14:41:42,175 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 14:41:42,176 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 14:41:42,179 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 14:41:42,198 - app.core.ocr.table_ocr - INFO - 开始处理图片: F:/下载/微信图片_20251027125604_98_108.jpg
2025-11-15 14:41:44,478 - app.core.ocr.table_ocr - INFO - 图片处理成功: F:/下载/微信图片_20251027125604_98_108.jpg, 输出文件: data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 15:11:57,934 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 15:11:57,937 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:11:57,939 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 15:11:57,945 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 15:11:57,946 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 15:11:58,040 - app.core.ocr.table_ocr - INFO - 找到 1 个图片文件,其中 1 个未处理
2025-11-15 15:11:58,053 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-15 15:11:58,081 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251113183218_594_278.jpg
2025-11-15 15:11:58,091 - app.core.ocr.table_ocr - INFO - 已存在对应的Excel文件,跳过处理: 微信图片_20251113183218_594_278.jpg -> 微信图片_20251113183218_594_278.xlsx
2025-11-15 15:11:58,132 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-11-15 15:12:40,318 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 15:12:40,333 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:12:40,345 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 15:12:40,358 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 15:12:40,370 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 15:12:40,403 - app.core.ocr.table_ocr - INFO - 开始处理图片: F:/下载/微信图片_20251027125604_98_108.jpg
2025-11-15 15:12:42,172 - app.core.ocr.table_ocr - INFO - 图片处理成功: F:/下载/微信图片_20251027125604_98_108.jpg, 输出文件: data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 15:25:05,003 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 15:25:05,004 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:25:05,006 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 15:25:05,009 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 15:25:05,019 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 15:25:05,052 - app.core.ocr.table_ocr - INFO - 开始处理图片: F:/下载/微信图片_20251027125604_98_108.jpg
2025-11-15 15:25:06,786 - app.core.ocr.table_ocr - INFO - 图片处理成功: F:/下载/微信图片_20251027125604_98_108.jpg, 输出文件: data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 15:33:47,219 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 15:33:47,225 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:33:47,228 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 15:33:47,229 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 15:33:47,234 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 15:33:47,269 - app.core.ocr.table_ocr - INFO - 开始处理图片: F:/下载/微信图片_20251027125604_98_108.jpg
2025-11-15 15:33:50,403 - app.core.ocr.table_ocr - INFO - 图片处理成功: F:/下载/微信图片_20251027125604_98_108.jpg, 输出文件: data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 15:39:11,309 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 15:39:11,310 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:39:11,310 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 15:39:11,310 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 15:39:11,311 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 15:43:33,473 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 15:43:33,474 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 15:43:33,478 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 15:43:33,481 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 15:43:33,485 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 15:43:33,617 - app.core.ocr.table_ocr - INFO - 找到 1 个图片文件,其中 1 个未处理
2025-11-15 15:43:33,637 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-15 15:43:33,670 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251113183218_594_278.jpg
2025-11-15 15:43:35,235 - app.core.ocr.table_ocr - INFO - 图片处理成功: data/input\微信图片_20251113183218_594_278.jpg, 输出文件: data/output\微信图片_20251113183218_594_278.xlsx
2025-11-15 15:43:35,236 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-11-15 16:39:05,575 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 16:39:05,581 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 16:39:05,587 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 16:39:05,594 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 16:39:05,597 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 16:39:05,641 - app.core.ocr.table_ocr - INFO - 开始处理图片: F:/下载/微信图片_20251027125604_98_108.jpg
2025-11-15 16:39:07,420 - app.core.ocr.table_ocr - INFO - 图片处理成功: F:/下载/微信图片_20251027125604_98_108.jpg, 输出文件: data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 16:46:22,388 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 16:46:22,388 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 16:46:22,390 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 16:46:22,390 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 16:46:22,392 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 16:46:22,501 - app.core.ocr.table_ocr - INFO - 找到 0 个图片文件,其中 0 个未处理
2025-11-15 16:46:22,522 - app.core.ocr.table_ocr - WARNING - 没有需要处理的图片
2025-11-15 17:28:46,777 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 17:28:46,778 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 17:28:46,781 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 17:28:46,784 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 17:28:46,789 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 17:28:46,913 - app.core.ocr.table_ocr - INFO - 找到 1 个图片文件,其中 1 个未处理
2025-11-15 17:28:46,930 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-15 17:28:46,975 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251115145536_614_278.jpg
2025-11-15 17:28:48,564 - app.core.ocr.table_ocr - INFO - 图片处理成功: data/input\微信图片_20251115145536_614_278.jpg, 输出文件: data/output\微信图片_20251115145536_614_278.xlsx
2025-11-15 17:28:48,566 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-11-15 17:29:22,057 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 17:29:22,070 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 17:29:22,076 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 17:29:22,084 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 17:29:22,098 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 17:29:22,147 - app.core.ocr.table_ocr - INFO - 找到 1 个图片文件,其中 1 个未处理
2025-11-15 17:29:22,159 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-15 17:29:22,180 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251115145536_614_278.jpg
2025-11-15 17:29:22,198 - app.core.ocr.table_ocr - INFO - 已存在对应的Excel文件,跳过处理: 微信图片_20251115145536_614_278.jpg -> 微信图片_20251115145536_614_278.xlsx
2025-11-15 17:29:22,217 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-11-15 17:59:39,798 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 17:59:39,799 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 17:59:39,800 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 17:59:39,800 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 17:59:39,801 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 17:59:39,913 - app.core.ocr.table_ocr - INFO - 找到 1 个图片文件,其中 0 个未处理
2025-11-15 17:59:39,930 - app.core.ocr.table_ocr - WARNING - 没有需要处理的图片
2025-11-15 18:00:04,112 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-15 18:00:04,114 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-15 18:00:04,116 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-15 18:00:04,117 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-15 18:00:04,119 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-15 18:00:04,224 - app.core.ocr.table_ocr - INFO - 找到 2 个图片文件,其中 1 个未处理
2025-11-15 18:00:04,247 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-15 18:00:04,278 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251114131924_600_278.jpg
2025-11-15 18:00:05,870 - app.core.ocr.table_ocr - INFO - 图片处理成功: data/input\微信图片_20251114131924_600_278.jpg, 输出文件: data/output\微信图片_20251114131924_600_278.xlsx
2025-11-15 18:00:05,872 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-11-16 11:23:59,369 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-16 11:23:59,369 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 11:23:59,369 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-16 11:23:59,369 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-16 11:23:59,369 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-16 11:26:06,790 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-16 11:26:06,791 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 11:26:06,791 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-16 11:26:06,791 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-16 11:26:06,792 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-16 12:50:38,502 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-16 12:50:38,503 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 12:50:38,504 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-16 12:50:38,506 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-16 12:50:38,508 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-16 12:50:38,541 - app.core.ocr.table_ocr - INFO - 找到 1 个图片文件,其中 1 个未处理
2025-11-16 12:50:38,550 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-16 12:50:38,560 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251115212128_148_108.jpg
2025-11-16 12:50:40,143 - app.core.ocr.table_ocr - INFO - 图片处理成功: data/input\微信图片_20251115212128_148_108.jpg, 输出文件: data/output\微信图片_20251115212128_148_108.xlsx
2025-11-16 12:50:40,149 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-11-16 12:51:06,904 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-16 12:51:06,906 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 12:51:06,906 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-16 12:51:06,906 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-16 12:51:06,907 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-16 13:03:10,557 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-16 13:03:10,557 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 13:03:10,557 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-16 13:03:10,558 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-16 13:03:10,558 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-16 13:03:10,578 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-16 13:03:10,578 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 13:03:10,579 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-16 13:03:10,579 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-16 13:03:10,580 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-16 13:18:18,243 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-16 13:18:18,243 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 13:18:18,244 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-16 13:18:18,244 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-16 13:18:18,244 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-16 13:18:18,265 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-16 13:18:18,265 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 13:18:18,266 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-16 13:18:18,266 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-16 13:18:18,267 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-16 13:51:09,012 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-16 13:51:09,013 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 13:51:09,013 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-16 13:51:09,013 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-16 13:51:09,014 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-16 14:39:42,975 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-16 14:39:42,976 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 14:39:42,976 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-16 14:39:42,976 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-16 14:39:42,977 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-16 14:39:42,990 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-16 14:39:42,991 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 14:39:42,991 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-16 14:39:42,991 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-16 14:39:42,992 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-16 15:11:05,478 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-16 15:11:05,485 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 15:11:05,487 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-16 15:11:05,489 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-16 15:11:05,498 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-16 15:11:05,536 - app.core.ocr.table_ocr - INFO - 找到 2 个图片文件,其中 1 个未处理
2025-11-16 15:11:05,549 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-16 15:11:05,571 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251116151001_152_108.jpg
2025-11-16 15:11:08,994 - app.core.ocr.table_ocr - INFO - 图片处理成功: data/input\微信图片_20251116151001_152_108.jpg, 输出文件: data/output\微信图片_20251116151001_152_108.xlsx
2025-11-16 15:11:08,995 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-11-16 15:13:47,370 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-16 15:13:47,372 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 15:13:47,375 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-16 15:13:47,381 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-16 15:13:47,383 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-16 15:13:47,457 - app.core.ocr.table_ocr - INFO - 找到 3 个图片文件,其中 1 个未处理
2025-11-16 15:13:47,470 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-16 15:13:47,510 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251116151334_153_108.jpg
2025-11-16 15:13:49,392 - app.core.ocr.table_ocr - INFO - 图片处理成功: data/input\微信图片_20251116151334_153_108.jpg, 输出文件: data/output\微信图片_20251116151334_153_108.xlsx
2025-11-16 15:13:49,397 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-11-16 15:15:36,173 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-16 15:15:36,173 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-16 15:15:36,174 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-16 15:15:36,175 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-16 15:15:36,177 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-16 15:15:36,243 - app.core.ocr.table_ocr - INFO - 找到 1 个图片文件,其中 1 个未处理
2025-11-16 15:15:36,257 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-16 15:15:36,299 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251116151514_154_108.jpg
2025-11-16 15:15:37,808 - app.core.ocr.table_ocr - INFO - 图片处理成功: data/input\微信图片_20251116151514_154_108.jpg, 输出文件: data/output\微信图片_20251116151514_154_108.xlsx
2025-11-16 15:15:37,809 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-11-20 18:44:11,080 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-20 18:44:11,083 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-20 18:44:11,087 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-20 18:44:11,089 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-20 18:44:11,094 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-20 18:44:11,194 - app.core.ocr.table_ocr - INFO - 找到 1 个图片文件,其中 1 个未处理
2025-11-20 18:44:11,216 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-20 18:44:11,261 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251116151514_154_108.jpg
2025-11-20 18:44:11,261 - app.core.ocr.table_ocr - INFO - 已存在对应的Excel文件,跳过处理: 微信图片_20251116151514_154_108.jpg -> 微信图片_20251116151514_154_108.xlsx
2025-11-20 18:44:11,295 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-11-20 18:47:03,864 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-20 18:47:03,867 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-20 18:47:03,867 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-20 18:47:03,869 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-20 18:47:03,871 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-20 18:47:03,990 - app.core.ocr.table_ocr - INFO - 找到 1 个图片文件,其中 1 个未处理
2025-11-20 18:47:04,011 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-20 18:47:04,048 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251116151514_154_108.jpg
2025-11-20 18:47:04,058 - app.core.ocr.table_ocr - INFO - 已存在对应的Excel文件,跳过处理: 微信图片_20251116151514_154_108.jpg -> 微信图片_20251116151514_154_108.xlsx
2025-11-20 18:47:04,080 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-11-20 18:56:30,283 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-11-20 18:56:30,284 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-11-20 18:56:30,287 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-11-20 18:56:30,289 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-11-20 18:56:30,291 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-11-20 18:56:30,417 - app.core.ocr.table_ocr - INFO - 找到 1 个图片文件,其中 1 个未处理
2025-11-20 18:56:30,439 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-11-20 18:56:30,483 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251116151514_154_108.jpg
2025-11-20 18:56:30,483 - app.core.ocr.table_ocr - INFO - 已存在对应的Excel文件,跳过处理: 微信图片_20251116151514_154_108.jpg -> 微信图片_20251116151514_154_108.xlsx
2025-11-20 18:56:30,495 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
2025-12-01 22:21:09,028 - app.core.ocr.table_ocr - INFO - 使用输入目录: E:\2025Code\python\orc-order-v2\data\input
2025-12-01 22:21:09,043 - app.core.ocr.table_ocr - INFO - 使用输出目录: E:\2025Code\python\orc-order-v2\data\output
2025-12-01 22:21:09,046 - app.core.ocr.table_ocr - INFO - 使用临时目录: E:\2025Code\python\orc-order-v2\data\temp
2025-12-01 22:21:09,048 - app.core.ocr.table_ocr - INFO - 允许的文件类型: ['.jpg', '.jpeg', '.png', '.bmp']
2025-12-01 22:21:09,052 - app.core.ocr.table_ocr - INFO - 初始化OCRProcessor完成:输入目录=data/input, 输出目录=data/output
2025-12-01 22:21:09,173 - app.core.ocr.table_ocr - INFO - 找到 1 个图片文件,其中 1 个未处理
2025-12-01 22:21:09,198 - app.core.ocr.table_ocr - INFO - 处理批次 1/1: 1 个文件
2025-12-01 22:21:09,246 - app.core.ocr.table_ocr - INFO - 开始处理图片: data/input\微信图片_20251201221738_176_108.jpg
2025-12-01 22:21:10,536 - app.core.ocr.table_ocr - INFO - 图片处理成功: data/input\微信图片_20251201221738_176_108.jpg, 输出文件: data/output\微信图片_20251201221738_176_108.xlsx
2025-12-01 22:21:10,538 - app.core.ocr.table_ocr - INFO - 所有图片处理完成, 总计: 1, 成功: 1
+4
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2025-11-14 21:55:05,688 - app.core.utils.file_utils - WARNING - 未在目录 data/output 中找到符合条件的文件
2025-11-16 10:48:45,595 - app.core.utils.file_utils - WARNING - 未在目录 data/output 中找到符合条件的文件
2025-11-16 10:48:45,656 - app.core.utils.file_utils - WARNING - 未在目录 data/output 中找到符合条件的文件
2025-11-16 10:56:22,516 - app.core.utils.file_utils - WARNING - 未在目录 data/output 中找到符合条件的文件
+589
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2025-11-14 20:52:59,971 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-14 20:52:59,974 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-14 20:52:59,976 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-14 20:52:59,978 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-14 20:52:59,982 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-14 20:52:59,984 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-14 20:52:59,995 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-14 20:52:59,997 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-14 20:53:00,000 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-14 20:53:00,002 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-14 21:55:14,931 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-14 21:55:14,939 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-14 21:55:14,988 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-14 21:55:15,019 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-14 21:55:30,504 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-14 21:55:30,576 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-14 21:55:32,258 - app.services.ocr_service - INFO - 处理完成: E:/2025Code/python/orc-order-v2/data/input/微信图片_20250909184135_44_108.jpg -> data/output\微信图片_20250909184135_44_108.xlsx
2025-11-14 22:00:56,331 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-14 22:00:56,339 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-14 22:00:56,354 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-14 22:00:56,355 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-14 22:00:56,360 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-14 22:00:56,362 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-14 23:22:38,470 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-14 23:22:38,472 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-14 23:53:32,025 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-14 23:53:32,027 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-14 23:53:35,691 - app.services.ocr_service - INFO - 处理完成: data\input\微信图片_20250909184135_44_108.jpg -> data/output\微信图片_20250909184135_44_108.xlsx
2025-11-14 23:53:37,742 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20250909184135_44_108.jpg
2025-11-14 23:53:39,788 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20250909184135_44_108.jpg
2025-11-14 23:53:41,832 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20250909184135_44_108.jpg
2025-11-14 23:53:43,881 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20250909184135_44_108.jpg
2025-11-14 23:53:45,934 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20250909184135_44_108.jpg
2025-11-14 23:53:48,001 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20250909184135_44_108.jpg
2025-11-14 23:53:50,039 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20250909184135_44_108.jpg
2025-11-14 23:54:01,442 - app.services.ocr_service - INFO - 处理完成: data\input\微信图片_20251027125604_98_108.jpg -> data/output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:03,487 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:05,528 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:07,576 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:09,616 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:13,773 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:15,821 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:17,867 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:19,919 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:21,962 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:24,008 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:26,046 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:28,097 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:30,151 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:32,204 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:34,250 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:36,296 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:38,351 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:40,404 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:42,458 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:44,502 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:46,556 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:48,600 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:51,982 - app.services.ocr_service - INFO - 处理完成: data\input\微信图片_20251019141843_92_108.jpg -> data/output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:54:52,021 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:54,069 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:54:54,107 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:56,148 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:54:56,189 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:54:58,238 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:54:58,275 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:00,326 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:00,364 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:02,419 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:02,462 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:04,521 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:04,558 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:06,605 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:06,642 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:08,703 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:08,740 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:10,786 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:10,827 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:12,879 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:12,916 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:14,960 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:14,996 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:17,036 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:17,073 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:19,125 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:19,162 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:21,204 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:21,242 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:23,294 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:23,335 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:25,382 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:25,421 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:27,467 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:27,505 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:29,547 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:29,582 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:31,622 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:31,669 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:33,737 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:33,774 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:35,817 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:35,853 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:37,920 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:37,961 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:40,013 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:40,051 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:42,108 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:42,146 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:44,193 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:44,229 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:46,275 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:46,315 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:48,365 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:48,404 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:50,443 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:50,482 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:52,535 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:52,573 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:54,614 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:54,653 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:56,710 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:56,748 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:55:58,800 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:55:58,838 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:56:00,891 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:56:00,933 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:56:02,979 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:56:03,018 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:56:05,062 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:56:05,105 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:56:07,162 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:56:07,210 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:56:57,442 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-14 23:56:57,445 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-14 23:56:59,616 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:57:01,537 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:57:05,227 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:57:06,470 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:57:09,653 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:57:11,576 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:57:15,136 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:57:16,887 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:57:20,234 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:57:21,430 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:57:24,780 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:57:26,265 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:57:29,872 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:57:31,572 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:57:35,123 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:57:36,918 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:57:40,537 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:57:42,112 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:57:45,416 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:57:46,720 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:57:49,990 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:57:51,501 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:57:54,894 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:57:56,395 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:57:59,834 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:58:01,639 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:58:05,077 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:58:06,547 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:58:09,915 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:58:11,351 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:58:14,705 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:58:16,392 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:58:19,888 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:58:21,532 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:58:24,978 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:58:26,500 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:58:29,831 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:58:31,416 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:58:34,852 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:58:36,575 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:58:39,921 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:58:41,452 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:58:44,946 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:58:46,443 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:58:50,034 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:58:51,597 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:58:55,053 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:58:56,555 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:59:00,070 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:59:01,844 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:59:05,320 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:59:06,825 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:59:10,473 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:59:12,139 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:59:15,603 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:59:17,192 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:59:20,612 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:59:22,114 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:59:25,589 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:59:27,211 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:59:30,767 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:59:32,326 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:59:36,011 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:59:37,686 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:59:41,201 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:59:42,778 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:59:46,304 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:59:47,761 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:59:51,191 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:59:52,841 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-14 23:59:56,216 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-14 23:59:57,611 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:00:01,219 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:00:02,758 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:00:06,052 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:00:07,434 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:00:10,840 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:00:12,561 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:00:16,097 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:00:17,522 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:00:20,868 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:00:22,464 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:00:26,088 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:00:27,515 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:00:31,017 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:00:32,515 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:00:36,053 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:00:37,624 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:00:41,060 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:00:42,493 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:00:45,839 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:00:47,275 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:00:50,609 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:00:52,109 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:00:55,459 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:00:57,222 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:01:00,688 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:01:02,298 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:01:05,719 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:01:07,317 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:01:10,858 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:01:12,551 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:01:16,041 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:01:17,743 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:01:21,145 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:01:22,630 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:01:26,026 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:01:27,349 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:01:30,913 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:01:32,597 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:01:35,986 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:01:37,481 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:01:40,840 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:01:42,630 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:01:46,085 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:01:47,711 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:01:51,307 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:01:53,097 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:01:56,452 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:01:57,944 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:02:01,308 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:02:02,944 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:02:06,570 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:02:08,356 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:02:12,004 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:02:13,757 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:02:17,556 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:02:19,476 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:02:22,928 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:02:24,545 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:02:27,890 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:02:29,443 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:02:32,790 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:02:34,247 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:02:37,750 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:02:39,242 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:02:42,620 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:02:44,196 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:02:47,546 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:02:49,236 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:02:52,656 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:02:54,352 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:02:57,747 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:02:59,241 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:03:02,582 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:03:03,966 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:03:07,396 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:03:09,150 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:03:12,454 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:03:14,078 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:03:17,563 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:03:18,931 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:03:22,254 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:03:23,958 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:03:27,433 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:03:28,875 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:03:32,492 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:03:33,730 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:03:37,280 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:03:38,745 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:03:42,378 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:03:44,064 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:03:47,518 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:03:49,323 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:03:52,839 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:03:54,315 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:03:57,762 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:03:59,377 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:04:02,912 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:04:04,333 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:04:07,634 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:04:09,217 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:04:12,781 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:04:14,391 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:04:17,952 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:04:19,426 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:04:22,773 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:04:24,437 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:04:27,786 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:04:29,491 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:04:33,208 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:04:34,834 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:04:38,270 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:04:39,870 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:04:43,227 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:04:44,671 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:04:48,011 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:04:49,544 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:04:52,898 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:04:54,514 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:04:58,133 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:04:59,637 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:05:03,203 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:05:04,439 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:05:07,802 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:05:09,420 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:05:13,002 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:05:14,449 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:05:17,865 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:05:19,351 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:05:22,585 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:05:24,115 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:05:27,622 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:05:29,332 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:05:32,669 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:05:34,242 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:05:37,801 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:05:39,407 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:05:42,969 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:05:44,554 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:05:48,144 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:05:49,714 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:05:53,196 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:05:54,908 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:05:58,328 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:05:59,736 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:18:49,533 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 00:18:49,535 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 00:18:51,772 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:18:53,982 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:18:57,742 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:18:59,499 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:19:02,811 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:19:04,852 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:19:08,780 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:19:10,559 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:19:14,369 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:19:16,366 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251027125604_98_108.jpg
2025-11-15 00:20:03,254 - app.services.ocr_service - INFO - 处理完成: data\input\微信图片_20251019141843_92_108.jpg -> data/output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:20:06,966 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:20:10,786 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:20:14,177 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:20:17,835 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:20:21,070 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:20:24,531 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:20:28,407 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:20:31,774 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:20:35,631 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:20:39,543 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:20:43,297 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:44:36,716 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 00:44:36,718 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 00:44:39,002 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:44:43,224 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 00:44:47,343 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:58:02,050 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 01:58:02,051 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 01:58:04,310 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:58:08,536 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:58:12,817 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:58:17,274 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:58:21,129 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:58:39,915 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:58:43,786 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:58:47,743 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:58:52,055 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:58:56,257 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:59:38,855 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:59:42,879 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:59:46,931 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:59:51,017 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 01:59:55,157 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:00:39,353 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:00:43,387 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:00:47,550 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:00:52,036 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:00:56,180 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:01:40,371 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:01:44,582 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:01:48,847 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:01:53,093 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:01:57,105 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:02:41,519 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:02:45,567 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:02:49,844 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:02:53,881 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:02:57,870 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:03:42,078 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:03:46,476 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:03:50,820 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:03:54,976 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:03:59,499 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:04:44,020 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:04:48,141 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:04:52,372 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:04:56,700 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:05:00,874 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:05:45,362 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:05:49,450 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:05:53,666 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:05:57,703 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:06:01,736 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:06:46,004 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:06:50,334 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:06:54,620 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:06:59,012 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:07:03,137 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:07:47,221 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:07:51,451 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:07:55,498 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:07:59,518 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:08:03,656 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:08:47,835 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:08:52,031 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:08:56,234 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:09:00,502 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:09:04,593 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:09:48,844 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:09:52,817 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:09:56,979 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:10:01,030 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:10:05,248 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:10:49,756 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:10:53,930 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:10:57,881 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:11:01,994 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:11:05,986 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:11:50,114 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:11:54,250 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:11:58,403 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:12:02,467 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:12:06,514 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:12:50,982 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:12:55,311 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:12:59,508 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:13:03,771 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 02:13:08,205 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: data\input\微信图片_20251019141843_92_108.jpg
2025-11-15 09:48:24,085 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 09:48:24,088 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 09:49:24,549 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 09:49:24,565 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 09:49:24,572 - app.services.ocr_service - INFO - 文件已处理过,跳过OCR识别: E:/2025Code/python/orc-order-v2/data/input/微信图片_20251019141843_92_108.jpg
2025-11-15 09:53:49,066 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 09:53:49,162 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 09:53:49,180 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-15 09:53:49,195 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-15 10:06:37,768 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 10:06:37,827 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 10:06:39,474 - app.services.ocr_service - INFO - 处理完成: E:/2025Code/python/orc-order-v2/data/input/微信图片_20251027125604_98_108.jpg -> data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 10:39:24,605 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 10:39:24,609 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 10:39:48,296 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 10:39:48,310 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 10:39:48,360 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-15 10:39:48,361 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-15 10:49:13,767 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 10:49:13,771 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 10:51:44,468 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 10:51:44,471 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 10:51:49,953 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 10:51:49,956 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 10:54:02,829 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 10:54:02,847 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 10:54:02,925 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-15 10:54:02,926 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-15 14:16:11,975 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 14:16:12,005 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 14:16:14,043 - app.services.ocr_service - INFO - 处理完成: E:/2025Code/python/orc-order-v2/data/input/微信图片_20251113183218_594_278.jpg -> data/output\微信图片_20251113183218_594_278.xlsx
2025-11-15 14:41:42,157 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 14:41:42,185 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 14:41:44,498 - app.services.ocr_service - INFO - 处理完成: F:/下载/微信图片_20251027125604_98_108.jpg -> data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 15:11:57,934 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 15:11:57,950 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 15:11:58,027 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-15 15:11:58,027 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-15 15:12:40,317 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 15:12:40,382 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 15:12:42,173 - app.services.ocr_service - INFO - 处理完成: F:/下载/微信图片_20251027125604_98_108.jpg -> data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 15:25:04,977 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 15:25:05,031 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 15:25:06,788 - app.services.ocr_service - INFO - 处理完成: F:/下载/微信图片_20251027125604_98_108.jpg -> data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 15:33:47,199 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 15:33:47,245 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 15:33:50,404 - app.services.ocr_service - INFO - 处理完成: F:/下载/微信图片_20251027125604_98_108.jpg -> data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 15:39:11,308 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 15:39:11,311 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 15:43:33,472 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 15:43:33,492 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 15:43:33,597 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-15 15:43:33,597 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-15 16:39:05,552 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 16:39:05,605 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 16:39:07,421 - app.services.ocr_service - INFO - 处理完成: F:/下载/微信图片_20251027125604_98_108.jpg -> data/output\微信图片_20251027125604_98_108.xlsx
2025-11-15 16:46:22,384 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 16:46:22,392 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 16:46:22,491 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-15 16:46:22,491 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-15 17:28:46,775 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 17:28:46,794 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 17:28:46,901 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-15 17:28:46,901 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-15 17:29:22,045 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 17:29:22,113 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 17:29:22,124 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-15 17:29:22,138 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-15 17:59:39,797 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 17:59:39,802 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 17:59:39,891 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-15 17:59:39,892 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-15 18:00:04,109 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-15 18:00:04,120 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-15 18:00:04,212 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-15 18:00:04,213 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-16 11:23:59,366 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-16 11:23:59,369 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-16 11:26:06,789 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-16 11:26:06,792 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-16 12:50:38,497 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-16 12:50:38,510 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-16 12:50:38,512 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-16 12:50:38,524 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-16 12:51:06,904 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-16 12:51:06,907 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-16 13:03:10,556 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-16 13:03:10,559 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-16 13:03:10,577 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-16 13:03:10,580 - app.services.ocr_service - INFO - OCRService初始化完成
2025-11-16 13:18:18,242 - app.services.ocr_service - INFO - 初始化OCRService
2025-11-16 13:18:18,246 - app.services.ocr_service - INFO - OCRService初始化完成
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2025-11-16 15:11:05,514 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-16 15:11:05,525 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-16 15:13:47,369 - app.services.ocr_service - INFO - 初始化OCRService
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2025-11-16 15:13:47,444 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-16 15:13:47,445 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-16 15:15:36,170 - app.services.ocr_service - INFO - 初始化OCRService
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2025-11-16 15:15:36,232 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-20 18:44:11,053 - app.services.ocr_service - INFO - 初始化OCRService
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2025-11-20 18:44:11,171 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-20 18:44:11,173 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-20 18:47:03,863 - app.services.ocr_service - INFO - 初始化OCRService
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2025-11-20 18:47:03,967 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-11-20 18:56:30,280 - app.services.ocr_service - INFO - 初始化OCRService
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2025-11-20 18:56:30,390 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-11-20 18:56:30,399 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
2025-12-01 22:21:09,016 - app.services.ocr_service - INFO - 初始化OCRService
2025-12-01 22:21:09,058 - app.services.ocr_service - INFO - OCRService初始化完成
2025-12-01 22:21:09,151 - app.services.ocr_service - INFO - OCRService.batch_process被调用,转发到process_images_batch
2025-12-01 22:21:09,161 - app.services.ocr_service - INFO - OCRService开始批量处理图片, batch_size=None, max_workers=None
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2025-08-16 00:52:16,815 - app.services.order_service - INFO - 初始化OrderService
2025-08-16 00:52:16,863 - app.services.order_service - INFO - OrderService初始化完成
2025-08-16 00:52:16,867 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-14 20:52:59,974 - app.services.order_service - INFO - 初始化OrderService
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2025-11-14 20:52:59,997 - app.services.order_service - INFO - 初始化OrderService
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2025-11-14 20:53:00,002 - app.services.order_service - INFO - 初始化OrderService
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2025-11-14 21:55:05,594 - app.services.order_service - INFO - 初始化OrderService
2025-11-14 21:55:05,663 - app.services.order_service - INFO - OrderService初始化完成
2025-11-14 21:55:05,672 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-14 21:55:14,941 - app.services.order_service - INFO - 初始化OrderService
2025-11-14 21:55:14,963 - app.services.order_service - INFO - OrderService初始化完成
2025-11-14 21:56:00,461 - app.services.order_service - INFO - 初始化OrderService
2025-11-14 21:56:00,575 - app.services.order_service - INFO - OrderService初始化完成
2025-11-14 21:56:00,599 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/微信图片_20250909184135_44_108.xlsx
2025-11-14 22:00:56,339 - app.services.order_service - INFO - 初始化OrderService
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2025-11-14 22:00:56,355 - app.services.order_service - INFO - 初始化OrderService
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2025-11-14 22:00:56,365 - app.services.order_service - INFO - OrderService初始化完成
2025-11-14 23:22:38,472 - app.services.order_service - INFO - 初始化OrderService
2025-11-14 23:22:38,475 - app.services.order_service - INFO - OrderService初始化完成
2025-11-14 23:53:32,027 - app.services.order_service - INFO - 初始化OrderService
2025-11-14 23:53:32,028 - app.services.order_service - INFO - OrderService初始化完成
2025-11-14 23:53:35,691 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20250909184135_44_108.xlsx
2025-11-14 23:53:37,742 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20250909184135_44_108.xlsx
2025-11-14 23:53:39,788 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20250909184135_44_108.xlsx
2025-11-14 23:53:41,832 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20250909184135_44_108.xlsx
2025-11-14 23:53:43,882 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20250909184135_44_108.xlsx
2025-11-14 23:53:45,934 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20250909184135_44_108.xlsx
2025-11-14 23:53:48,001 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20250909184135_44_108.xlsx
2025-11-14 23:53:50,039 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20250909184135_44_108.xlsx
2025-11-14 23:54:01,442 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:03,487 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:05,529 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
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2025-11-14 23:54:09,616 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:13,773 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:15,821 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:17,867 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:19,919 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:21,962 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:24,008 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:26,047 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:28,098 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:30,151 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:32,204 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:34,250 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:36,296 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:38,351 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:40,404 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:42,458 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:44,502 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:46,556 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:48,600 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:51,983 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:54:52,021 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:54,069 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:54:54,107 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:56,148 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:54:56,189 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:54:58,238 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:54:58,275 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:00,326 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:00,365 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:02,420 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:02,462 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:04,521 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:04,558 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:06,605 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:06,643 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:08,703 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:08,740 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:10,788 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:10,828 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:12,879 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:12,916 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:14,960 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:14,996 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:17,036 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:17,073 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:19,125 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:19,162 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:21,205 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:21,243 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:23,295 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:23,335 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:25,382 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:25,421 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:27,467 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:27,505 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:29,547 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:29,582 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:31,622 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:31,669 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:33,737 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:33,774 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:35,817 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:35,853 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:37,921 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:37,961 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:40,014 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:40,051 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:42,108 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:42,147 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:44,193 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:44,229 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:46,275 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:46,315 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:48,365 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:48,404 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:50,443 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:50,482 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:52,535 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:52,573 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:54,614 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:54,653 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:56,710 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:56,748 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:55:58,800 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:55:58,838 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:56:00,891 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:56:00,935 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:56:02,980 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:56:03,018 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:56:05,062 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:56:05,106 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:56:07,162 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:56:07,210 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:56:57,445 - app.services.order_service - INFO - 初始化OrderService
2025-11-14 23:56:57,448 - app.services.order_service - INFO - OrderService初始化完成
2025-11-14 23:56:59,671 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:57:01,610 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:57:05,270 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:57:06,524 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:57:09,725 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:57:11,648 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:57:15,205 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:57:16,956 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:57:20,272 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:57:21,477 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:57:24,830 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:57:26,314 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:57:29,933 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:57:31,639 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:57:35,183 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:57:36,999 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:57:40,585 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:57:42,149 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:57:45,471 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:57:46,771 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:57:50,045 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:57:51,537 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:57:54,947 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:57:56,455 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:57:59,886 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:58:01,675 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:58:05,116 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:58:06,597 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:58:09,988 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:58:11,402 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:58:14,762 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:58:16,456 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:58:19,926 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:58:21,593 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:58:25,017 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:58:26,549 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:58:29,869 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:58:31,480 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:58:34,917 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:58:36,626 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:58:39,970 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:58:41,505 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:58:45,014 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:58:46,495 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:58:50,070 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:58:51,660 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:58:55,105 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:58:56,605 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:59:00,139 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:59:01,892 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:59:05,383 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:59:06,901 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:59:10,551 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:59:12,206 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:59:15,639 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:59:17,241 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:59:20,663 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:59:22,160 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:59:25,634 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:59:27,248 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:59:30,819 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:59:32,365 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:59:36,079 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:59:37,734 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:59:41,258 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:59:42,824 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:59:46,370 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:59:47,834 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:59:51,254 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:59:52,905 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-14 23:59:56,269 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-14 23:59:57,672 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:00:01,256 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:00:02,807 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:00:06,104 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:00:07,485 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:00:10,893 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:00:12,610 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:00:16,149 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:00:17,562 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:00:20,946 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:00:22,538 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:00:26,131 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:00:27,583 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:00:31,069 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:00:32,567 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:00:36,102 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:00:37,675 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:00:41,096 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:00:42,559 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:00:45,876 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:00:47,314 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:00:50,657 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:00:52,159 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:00:55,531 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:00:57,287 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:01:00,725 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:01:02,358 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:01:05,756 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:01:07,382 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:01:10,909 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:01:12,635 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:01:16,124 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:01:17,810 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:01:21,182 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:01:22,681 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:01:26,069 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:01:27,398 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:01:30,983 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:01:32,654 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:01:36,036 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:01:37,546 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:01:40,916 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:01:42,666 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:01:46,135 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:01:47,771 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:01:51,376 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:01:53,154 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:01:56,488 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:01:58,006 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:02:01,361 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:02:03,000 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:02:06,651 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:02:08,438 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:02:12,057 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:02:13,824 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:02:17,635 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:02:19,526 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:02:23,005 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:02:24,594 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:02:27,928 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:02:29,505 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:02:32,852 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:02:34,299 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:02:37,813 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:02:39,281 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:02:42,672 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:02:44,232 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:02:47,595 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:02:49,284 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:02:52,743 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:02:54,437 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:02:57,797 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:02:59,304 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:03:02,645 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:03:04,003 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:03:07,447 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:03:09,204 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:03:12,509 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:03:14,146 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:03:17,611 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:03:18,970 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:03:22,320 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:03:23,995 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:03:27,472 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:03:28,938 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:03:32,546 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:03:33,779 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:03:37,358 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:03:38,810 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:03:42,430 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:03:44,137 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:03:47,587 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:03:49,403 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:03:52,901 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:03:54,388 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:03:57,810 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:03:59,455 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:04:02,984 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:04:04,394 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:04:07,710 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:04:09,289 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:04:12,859 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:04:14,474 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:04:17,989 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:04:19,500 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:04:22,822 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:04:24,473 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:04:27,848 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:04:29,568 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:04:33,270 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:04:34,897 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:04:38,318 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:04:39,934 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:04:43,278 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:04:44,722 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:04:48,052 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:04:49,619 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:04:52,975 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:04:54,572 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:04:58,173 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:04:59,694 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:05:03,261 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:05:04,491 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:05:07,887 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:05:09,478 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:05:13,079 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:05:14,500 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:05:17,918 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:05:19,387 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:05:22,622 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:05:24,193 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:05:27,664 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:05:29,394 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:05:32,717 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:05:34,328 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:05:37,870 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:05:39,473 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:05:43,044 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:05:44,606 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:05:48,195 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:05:49,765 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:05:53,268 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:05:54,963 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:05:58,364 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:05:59,802 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:18:49,535 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 00:18:49,538 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 00:18:51,832 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:18:54,057 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:18:57,817 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:18:59,547 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:19:02,881 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:19:04,937 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:19:08,852 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:19:10,644 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:19:14,425 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:19:16,439 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251027125604_98_108.xlsx
2025-11-15 00:20:03,324 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:20:07,029 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:20:10,864 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:20:14,215 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:20:17,878 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:20:21,109 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:20:24,592 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:20:28,474 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:20:31,856 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:20:35,700 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:20:39,605 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:20:43,355 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:44:36,718 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 00:44:36,720 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 00:44:39,085 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:44:43,294 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 00:44:47,418 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:58:02,052 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 01:58:02,054 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 01:58:04,404 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:58:08,613 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:58:12,905 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:58:17,338 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:58:21,192 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:58:39,977 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:58:43,852 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:58:47,831 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:58:52,175 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:58:56,355 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:59:38,962 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:59:42,963 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:59:47,041 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:59:51,100 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 01:59:55,247 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:00:39,437 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:00:43,455 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:00:47,653 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:00:52,105 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:00:56,245 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:01:40,456 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:01:44,653 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:01:48,950 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:01:53,159 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:01:57,193 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:02:41,611 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:02:45,668 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:02:49,948 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:02:53,952 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:02:57,956 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:03:42,179 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:03:46,610 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:03:50,918 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:03:55,072 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:03:59,598 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:04:44,111 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:04:48,235 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:04:52,463 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:04:56,788 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:05:01,024 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:05:45,464 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:05:49,519 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:05:53,734 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:05:57,788 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:06:01,836 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:06:46,074 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:06:50,451 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:06:54,716 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:06:59,148 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:07:03,221 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:07:47,305 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:07:51,518 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:07:55,599 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:07:59,603 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:08:03,773 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:08:47,930 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:08:52,146 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:08:56,363 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:09:00,604 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:09:04,679 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:09:48,912 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:09:52,927 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:09:57,080 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:10:01,136 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:10:05,339 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:10:49,825 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:10:53,995 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:10:57,962 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:11:02,097 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:11:06,075 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:11:50,181 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:11:54,337 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:11:58,472 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:12:02,549 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:12:06,611 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:12:51,091 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:12:55,402 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:12:59,595 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:13:03,883 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 02:13:08,305 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data\output\微信图片_20251019141843_92_108.xlsx
2025-11-15 09:48:24,088 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 09:48:24,126 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 10:06:56,495 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 10:06:56,644 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 10:06:56,677 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/微信图片_20251027125604_98_108.xlsx
2025-11-15 10:10:31,568 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 10:10:31,669 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 10:10:31,686 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/微信图片_20251027125604_98_108.xlsx
2025-11-15 10:39:24,610 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 10:39:24,613 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 10:39:48,312 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 10:39:48,340 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 10:39:50,736 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 10:49:13,771 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 10:49:13,775 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 10:51:44,471 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 10:51:44,475 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 10:51:49,956 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 10:51:49,960 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 10:54:02,853 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 10:54:02,897 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 10:54:04,837 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 10:58:26,517 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 10:58:26,634 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 10:58:26,651 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 10:58:36,001 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 10:58:36,098 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 10:58:36,133 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/微信图片_20251027125604_98_108.xlsx
2025-11-15 14:17:23,548 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 14:17:23,617 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 14:17:23,630 - app.services.order_service - INFO - OrderService开始合并所有采购单
2025-11-15 14:17:23,648 - app.services.order_service - INFO - OrderService开始合并所有采购单
2025-11-15 14:22:16,889 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 14:22:16,949 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 14:22:16,977 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: F:/下载/订单1762933924814.xlsx
2025-11-15 15:11:57,955 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 15:11:57,991 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 15:11:58,198 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 15:12:52,608 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 15:12:52,708 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 15:12:52,745 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 15:21:05,637 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 15:21:05,678 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 15:21:05,686 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/微信图片_20251027125604_98_108.xlsx
2025-11-15 15:22:01,116 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 15:22:01,217 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 15:22:01,232 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/微信图片_20251027125604_98_108.xlsx
2025-11-15 15:25:41,328 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 15:25:41,393 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 15:25:41,435 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 15:34:06,437 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 15:34:06,514 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 15:34:06,543 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 15:37:42,545 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 15:37:42,599 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 15:37:42,606 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 15:39:11,311 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 15:39:11,314 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 15:43:33,496 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 15:43:33,561 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 15:43:35,318 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 15:54:35,478 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 15:54:35,573 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 15:54:35,609 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 16:19:42,366 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 16:19:42,388 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 16:19:42,389 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\蓉城易购-订单明细20251115154455.xlsx
2025-11-15 16:34:22,100 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 16:34:22,132 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 16:34:22,132 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\蓉城易购-订单1762933924814.xlsx
2025-11-15 16:46:22,393 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 16:46:22,453 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 16:46:28,800 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 16:46:28,913 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 16:46:29,004 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 16:46:37,684 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 16:46:37,798 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 16:46:37,873 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 16:48:30,424 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 16:48:30,499 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 16:48:30,574 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 16:48:41,962 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 16:48:42,077 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 16:48:42,154 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 16:52:35,911 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 16:52:35,973 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 16:52:36,050 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 16:57:42,391 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 16:57:42,459 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 16:57:42,542 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 16:59:06,951 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 16:59:07,027 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 16:59:07,102 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 16:59:14,530 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 16:59:14,619 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 16:59:14,678 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 17:01:30,192 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 17:01:30,257 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 17:01:30,308 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 17:04:33,184 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 17:04:33,258 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 17:04:33,323 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 17:04:44,983 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 17:04:45,063 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 17:04:45,134 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 17:09:39,792 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 17:09:39,862 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 17:09:39,929 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 17:12:37,423 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 17:12:37,485 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 17:12:37,545 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 17:28:46,799 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 17:28:46,861 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 17:28:48,645 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 17:59:22,782 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 17:59:22,828 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 17:59:22,867 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 17:59:33,421 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 17:59:33,523 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 17:59:33,585 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 17:59:39,804 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 17:59:39,862 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 18:00:04,123 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 18:00:04,180 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 18:00:05,990 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-15 18:01:51,643 - app.services.order_service - INFO - 初始化OrderService
2025-11-15 18:01:51,715 - app.services.order_service - INFO - OrderService初始化完成
2025-11-15 18:01:51,763 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-16 10:48:45,445 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 10:48:45,564 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 10:48:45,630 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-16 10:56:22,512 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 10:56:22,516 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 11:23:59,369 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 11:23:59,374 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 11:26:06,793 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 11:26:06,795 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 12:51:06,907 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 12:51:06,910 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 13:03:10,559 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 13:03:10,563 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 13:03:10,580 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 13:03:10,584 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 13:18:18,246 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 13:18:18,248 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 13:18:18,268 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 13:18:18,271 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 13:51:09,015 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 13:51:09,018 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 14:25:50,009 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 14:25:50,033 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 14:25:50,107 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-16 14:25:55,548 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 14:25:55,619 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 14:25:55,699 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-16 14:39:42,977 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 14:39:42,981 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 14:39:42,993 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 14:39:42,996 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 14:59:35,433 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 14:59:35,437 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 14:59:35,437 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/微信图片_20251115212128_148_108.xlsx
2025-11-16 15:03:21,889 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 15:03:21,893 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 15:03:21,894 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/微信图片_20251115212128_148_108.xlsx
2025-11-16 15:08:33,542 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 15:08:33,546 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 15:08:33,546 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/微信图片_20251115212128_148_108.xlsx
2025-11-16 15:11:11,179 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 15:11:11,268 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 15:11:11,345 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-16 15:13:47,387 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 15:13:47,411 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 15:13:49,534 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-16 15:15:36,186 - app.services.order_service - INFO - 初始化OrderService
2025-11-16 15:15:36,205 - app.services.order_service - INFO - OrderService初始化完成
2025-11-16 15:15:37,909 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-20 18:36:13,245 - app.services.order_service - INFO - 初始化OrderService
2025-11-20 18:36:13,299 - app.services.order_service - INFO - OrderService初始化完成
2025-11-20 18:36:13,371 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-20 18:36:42,069 - app.services.order_service - INFO - 初始化OrderService
2025-11-20 18:36:42,111 - app.services.order_service - INFO - OrderService初始化完成
2025-11-20 18:36:42,174 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-20 18:42:25,860 - app.services.order_service - INFO - 初始化OrderService
2025-11-20 18:42:25,947 - app.services.order_service - INFO - OrderService初始化完成
2025-11-20 18:42:26,024 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-20 18:44:11,101 - app.services.order_service - INFO - 初始化OrderService
2025-11-20 18:44:11,134 - app.services.order_service - INFO - OrderService初始化完成
2025-11-20 18:44:11,376 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-20 18:47:03,878 - app.services.order_service - INFO - 初始化OrderService
2025-11-20 18:47:03,927 - app.services.order_service - INFO - OrderService初始化完成
2025-11-20 18:47:04,166 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-11-20 18:56:30,301 - app.services.order_service - INFO - 初始化OrderService
2025-11-20 18:56:30,361 - app.services.order_service - INFO - OrderService初始化完成
2025-11-20 18:56:30,593 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-12-01 22:21:09,063 - app.services.order_service - INFO - 初始化OrderService
2025-12-01 22:21:09,121 - app.services.order_service - INFO - OrderService初始化完成
2025-12-01 22:21:10,614 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2025-12-12 11:00:14,048 - app.services.order_service - INFO - 初始化OrderService
2025-12-12 11:00:14,096 - app.services.order_service - INFO - OrderService初始化完成
2025-12-12 11:00:14,097 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\蓉城易购-订单1765440157955.xlsx
2025-12-12 11:13:15,273 - app.services.order_service - INFO - 初始化OrderService
2025-12-12 11:13:15,288 - app.services.order_service - INFO - OrderService初始化完成
2025-12-12 11:13:15,289 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\蓉城易购-订单1765440157955.xlsx
2025-12-12 11:22:25,989 - app.services.order_service - INFO - 初始化OrderService
2025-12-12 11:22:25,990 - app.services.order_service - INFO - OrderService初始化完成
2025-12-12 11:22:25,990 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\蓉城易购-订单1765440157955.xlsx
2025-12-12 11:32:26,688 - app.services.order_service - INFO - 初始化OrderService
2025-12-12 11:32:26,694 - app.services.order_service - INFO - OrderService初始化完成
2025-12-12 11:32:26,696 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\蓉城易购-订单1765440157955.xlsx
2025-12-12 11:34:40,235 - app.services.order_service - INFO - 初始化OrderService
2025-12-12 11:34:40,238 - app.services.order_service - INFO - OrderService初始化完成
2025-12-12 11:34:40,238 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\蓉城易购-订单1765440157955.xlsx
2025-12-12 11:38:53,256 - app.services.order_service - INFO - 初始化OrderService
2025-12-12 11:38:53,260 - app.services.order_service - INFO - OrderService初始化完成
2025-12-12 11:38:53,260 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\蓉城易购-订单1765440157955.xlsx
2025-12-12 11:49:38,202 - app.services.order_service - INFO - 初始化OrderService
2025-12-12 11:49:38,203 - app.services.order_service - INFO - OrderService初始化完成
2025-12-12 11:49:38,206 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\蓉城易购-订单1765440157955.xlsx
2025-12-12 12:30:07,696 - app.services.order_service - INFO - 初始化OrderService
2025-12-12 12:30:07,700 - app.services.order_service - INFO - OrderService初始化完成
2025-12-12 12:30:07,700 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\蓉城易购-订单1765513775092.xlsx
2025-12-12 12:32:20,576 - app.services.order_service - INFO - 初始化OrderService
2025-12-12 12:32:20,579 - app.services.order_service - INFO - OrderService初始化完成
2025-12-12 12:32:20,579 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\蓉城易购-订单1765513867817.xlsx
2026-03-30 10:20:20,106 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 10:20:20,145 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 10:20:20,145 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: e:\2025Code\python\orc-order-v2\data\output\495a630b-87cf-4245-834e-2705a3dcd12f.xlsx
2026-03-30 10:21:25,351 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 10:21:25,356 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 10:21:25,356 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: e:\2025Code\python\orc-order-v2\data\output\495a630b-87cf-4245-834e-2705a3dcd12f.xlsx
2026-03-30 10:21:52,466 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 10:21:52,470 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 10:21:52,470 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: e:\2025Code\python\orc-order-v2\data\output\495a630b-87cf-4245-834e-2705a3dcd12f.xlsx
2026-03-30 13:28:54,447 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:28:54,451 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:28:54,452 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\原始数据.xlsx
2026-03-30 13:28:54,461 - app.services.order_service - ERROR - 检查特殊预处理时出错: 'OrderService' object has no attribute 'config_manager'
2026-03-30 13:29:24,572 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:29:24,576 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:29:24,576 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\原始数据.xlsx
2026-03-30 13:29:24,577 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:29:24,581 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:29:24,854 - app.services.order_service - INFO - 识别到杨碧月订单,执行预处理...
2026-03-30 13:29:24,868 - app.services.order_service - WARNING - 预处理识别失败: name 'os' is not defined
2026-03-30 13:29:58,480 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:29:58,484 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:29:58,484 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\原始数据.xlsx
2026-03-30 13:29:58,485 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:29:58,488 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:29:58,758 - app.services.order_service - INFO - 识别到杨碧月订单,执行预处理...
2026-03-30 13:29:58,893 - app.services.order_service - INFO - 检测到特殊供应商,已生成预处理文件: E:\2025Code\python\orc-order-v2\data\output\预处理之后.xlsx
2026-03-30 13:30:29,313 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:30:29,317 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:30:29,318 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\原始数据.xlsx
2026-03-30 13:30:29,319 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:30:29,322 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:30:29,597 - app.services.order_service - INFO - 识别到杨碧月订单,执行预处理...
2026-03-30 13:30:29,734 - app.services.order_service - INFO - 检测到特殊供应商,已生成预处理文件: E:\2025Code\python\orc-order-v2\data\output\预处理之后.xlsx
2026-03-30 13:31:51,943 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:31:51,947 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:31:51,947 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:\2025Code\python\orc-order-v2\data\output\原始数据.xlsx
2026-03-30 13:31:51,948 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:31:51,952 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:31:52,230 - app.services.order_service - INFO - 识别到杨碧月订单,执行预处理...
2026-03-30 13:31:52,367 - app.services.order_service - INFO - 检测到特殊供应商,已生成预处理文件: E:\2025Code\python\orc-order-v2\data\output\预处理之后.xlsx
2026-03-30 13:46:00,207 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:46:00,211 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:46:00,225 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/原始数据.xlsx
2026-03-30 13:46:00,227 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:46:00,230 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:46:00,255 - app.services.order_service - INFO - 识别到杨碧月订单,执行通用预处理...
2026-03-30 13:46:00,355 - app.services.order_service - INFO - 检测到特殊供应商,已生成预处理文件: E:/2025Code/python/orc-order-v2/data/output\预处理之后.xlsx
2026-03-30 13:46:02,782 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:46:02,785 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:47:05,230 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:47:05,233 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:47:05,252 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/订单1765513867817.xlsx
2026-03-30 13:47:05,253 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:47:05,256 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:47:06,651 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:47:06,655 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:48:28,517 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:48:28,520 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:48:28,522 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/订单1774849009841.xlsx
2026-03-30 13:48:28,522 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:48:28,525 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:48:30,799 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:48:30,802 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:51:44,153 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:51:44,156 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:51:44,167 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/订单明细20260330133908.xlsx
2026-03-30 13:51:44,168 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:51:44,171 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 13:51:46,069 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 13:51:46,072 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:00:52,371 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:00:52,375 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:00:52,389 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/订单1774849009841.xlsx
2026-03-30 14:00:52,389 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:00:52,393 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:01:20,292 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:01:20,295 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:01:20,304 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/订单1774849009841.xlsx
2026-03-30 14:01:20,305 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:01:20,308 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:01:24,373 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:01:24,376 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:06:58,240 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:06:58,243 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:06:58,248 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/订单1774849009841.xlsx
2026-03-30 14:07:00,053 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:07:00,055 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:14:46,829 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:14:46,832 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:14:46,844 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/订单明细20260330133908.xlsx
2026-03-30 14:14:47,889 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:14:47,891 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:23:18,308 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:23:18,311 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:23:18,320 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/订单1774849009841.xlsx
2026-03-30 14:23:20,041 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:23:20,043 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:24:02,880 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:24:02,883 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:24:02,890 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/订单1774849009841.xlsx
2026-03-30 14:24:04,316 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:24:04,318 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:28:39,036 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:28:39,040 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:28:39,040 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data/output/订单1774849009841.xlsx
2026-03-30 14:28:39,333 - app.services.order_service - INFO - 识别到蓉城易购订单,执行专用预处理...
2026-03-30 14:28:39,514 - app.services.order_service - INFO - 检测到特殊供应商,已生成预处理文件: data/output\预处理之后_订单1774849009841.xlsx
2026-03-30 14:28:39,734 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:28:39,738 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:28:39,738 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data/output/订单明细20260330133908.xlsx
2026-03-30 14:28:39,746 - app.services.order_service - INFO - 识别到烟草公司订单,执行专用预处理...
2026-03-30 14:28:39,828 - app.services.order_service - INFO - 检测到特殊供应商,已生成预处理文件: data/output\预处理之后_订单明细20260330133908.xlsx
2026-03-30 14:41:11,945 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:41:11,949 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:41:11,957 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/订单1774849009841.xlsx
2026-03-30 14:41:11,994 - app.services.order_service - INFO - 识别到蓉城易购订单,执行专用预处理...
2026-03-30 14:41:12,128 - app.services.order_service - INFO - 检测到特殊供应商,已生成预处理文件: E:/2025Code/python/orc-order-v2/data/output\预处理之后_订单1774849009841.xlsx
2026-03-30 14:41:33,385 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:41:33,388 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:41:47,793 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:41:47,796 - app.services.order_service - INFO - OrderService初始化完成
2026-03-30 14:41:47,810 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/订单明细20260330133908.xlsx
2026-03-30 14:41:47,819 - app.services.order_service - INFO - 识别到烟草公司订单,执行专用预处理...
2026-03-30 14:41:47,865 - app.services.order_service - INFO - 检测到特殊供应商,已生成预处理文件: E:/2025Code/python/orc-order-v2/data/output\预处理之后_订单明细20260330133908.xlsx
2026-03-30 14:41:49,670 - app.services.order_service - INFO - 初始化OrderService
2026-03-30 14:41:49,674 - app.services.order_service - INFO - OrderService初始化完成
2026-03-31 08:50:15,691 - app.services.order_service - INFO - 初始化OrderService
2026-03-31 08:50:15,754 - app.services.order_service - INFO - OrderService初始化完成
2026-03-31 08:50:15,757 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/订单1774849009841.xlsx
2026-03-31 08:50:15,811 - app.services.order_service - INFO - 识别到蓉城易购订单,执行专用预处理...
2026-03-31 08:50:15,872 - app.services.order_service - INFO - 检测到特殊供应商,已生成预处理文件: E:/2025Code/python/orc-order-v2/data/output\预处理之后_订单1774849009841.xlsx
2026-03-31 08:50:17,773 - app.services.order_service - INFO - 初始化OrderService
2026-03-31 08:50:17,775 - app.services.order_service - INFO - OrderService初始化完成
2026-03-31 08:52:46,011 - app.services.order_service - INFO - 初始化OrderService
2026-03-31 08:52:46,014 - app.services.order_service - INFO - OrderService初始化完成
2026-03-31 08:52:46,029 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/原始数据.xlsx
2026-03-31 08:52:46,087 - app.services.order_service - INFO - 检测到特殊供应商,已生成预处理文件: E:/2025Code/python/orc-order-v2/data/output\预处理之后_原始数据.xlsx
2026-03-31 08:52:47,190 - app.services.order_service - INFO - 初始化OrderService
2026-03-31 08:52:47,192 - app.services.order_service - INFO - OrderService初始化完成
2026-03-31 09:00:01,690 - app.services.order_service - INFO - 初始化OrderService
2026-03-31 09:00:01,694 - app.services.order_service - INFO - OrderService初始化完成
2026-03-31 09:00:01,694 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: data/output/原始数据.xlsx
2026-03-31 09:00:01,984 - app.services.order_service - INFO - 识别到杨碧月订单,执行专用预处理...
2026-03-31 09:00:02,134 - app.services.order_service - INFO - 检测到特殊供应商,已生成预处理文件: data/output\预处理之后_原始数据.xlsx
2026-03-31 09:03:11,825 - app.services.order_service - INFO - 初始化OrderService
2026-03-31 09:03:11,829 - app.services.order_service - INFO - OrderService初始化完成
2026-03-31 09:03:11,832 - app.services.order_service - INFO - OrderService开始处理指定Excel文件: E:/2025Code/python/orc-order-v2/data/output/原始数据.xlsx
2026-03-31 09:03:11,886 - app.services.order_service - INFO - 识别到杨碧月订单,执行专用预处理...
2026-03-31 09:03:11,970 - app.services.order_service - INFO - 检测到特殊供应商,已生成预处理文件: E:/2025Code/python/orc-order-v2/data/output\预处理之后_原始数据.xlsx
2026-03-31 09:03:13,869 - app.services.order_service - INFO - 初始化OrderService
2026-03-31 09:03:13,873 - app.services.order_service - INFO - OrderService初始化完成
2026-03-31 09:05:33,091 - app.services.order_service - INFO - 初始化OrderService
2026-03-31 09:05:33,094 - app.services.order_service - INFO - OrderService初始化完成
2026-03-31 09:05:33,098 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2026-03-31 09:05:33,126 - app.services.order_service - INFO - 识别到蓉城易购订单,执行专用预处理...
2026-03-31 09:05:33,174 - app.services.order_service - INFO - 检测到特殊供应商,已生成预处理文件: data/output\预处理之后_订单1774849009841.xlsx
2026-03-31 09:05:33,865 - app.services.order_service - INFO - 初始化OrderService
2026-03-31 09:05:33,869 - app.services.order_service - INFO - OrderService初始化完成
2026-03-31 09:07:58,232 - app.services.order_service - INFO - 初始化OrderService
2026-03-31 09:07:58,236 - app.services.order_service - INFO - OrderService初始化完成
2026-03-31 09:07:58,241 - app.services.order_service - INFO - OrderService开始处理最新Excel文件
2026-03-31 09:07:58,250 - app.services.order_service - INFO - 识别到烟草公司订单,执行专用预处理...
2026-03-31 09:07:58,289 - app.services.order_service - INFO - 检测到特殊供应商,已生成预处理文件: data/output\预处理之后_订单明细20260331090709.xlsx
2026-03-31 09:07:58,350 - app.services.order_service - INFO - 初始化OrderService
2026-03-31 09:07:58,354 - app.services.order_service - INFO - OrderService初始化完成
+51
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@@ -0,0 +1,51 @@
2025-11-15 15:44:36,108 - app.services.tobacco_service - WARNING - 未找到烟草公司订单明细文件
2025-11-15 15:44:36,116 - app.services.tobacco_service - WARNING - 未找到烟草公司订单明细文件
2025-11-15 15:44:36,125 - app.services.tobacco_service - ERROR - 未找到可处理的烟草订单明细文件
2025-11-15 15:45:17,682 - app.services.tobacco_service - INFO - 找到最新烟草订单明细文件: data/output\订单明细20251115154455.xlsx
2025-11-15 15:45:17,689 - app.services.tobacco_service - INFO - 开始处理烟草公司订单: data/output\订单明细20251115154455.xlsx
2025-11-15 15:45:17,724 - app.services.tobacco_service - INFO - 采购单生成成功: data/result\银豹采购单_烟草公司.xls
2025-11-15 15:45:17,726 - app.services.tobacco_service - INFO - 烟草公司订单处理成功,订单时间: 2025-11-10, 总金额: 12226.22, 处理条目: 34
2025-11-15 15:45:17,738 - app.services.tobacco_service - INFO - 采购单已生成: data/result\银豹采购单_烟草公司.xls
2025-11-15 15:45:17,850 - app.services.tobacco_service - INFO - 烟草公司订单处理成功,订单时间: 2025-11-10, 总金额: 12226.22, 处理条目: 34
2025-11-15 15:46:55,566 - app.services.tobacco_service - INFO - 找到最新烟草订单明细文件: data/output\订单明细20251115154455.xlsx
2025-11-15 15:46:55,572 - app.services.tobacco_service - INFO - 开始处理烟草公司订单: data/output\订单明细20251115154455.xlsx
2025-11-15 15:46:55,599 - app.services.tobacco_service - INFO - 采购单生成成功: data/result\银豹采购单_烟草公司.xls
2025-11-15 15:46:55,600 - app.services.tobacco_service - INFO - 烟草公司订单处理成功,订单时间: 2025-11-10, 总金额: 12226.22, 处理条目: 34
2025-11-15 15:46:55,607 - app.services.tobacco_service - INFO - 采购单已生成: data/result\银豹采购单_烟草公司.xls
2025-11-15 15:46:55,667 - app.services.tobacco_service - INFO - 烟草公司订单处理成功,订单时间: 2025-11-10, 总金额: 12226.22, 处理条目: 34
2025-11-15 15:47:59,480 - app.services.tobacco_service - INFO - 找到最新烟草订单明细文件: data/output\订单明细20251115154455.xlsx
2025-11-15 15:47:59,485 - app.services.tobacco_service - INFO - 开始处理烟草公司订单: data/output\订单明细20251115154455.xlsx
2025-11-15 15:47:59,512 - app.services.tobacco_service - INFO - 采购单生成成功: data/result\银豹采购单_烟草公司.xls
2025-11-15 15:47:59,513 - app.services.tobacco_service - INFO - 烟草公司订单处理成功,订单时间: 2025-11-10, 总金额: 12226.22, 处理条目: 34
2025-11-15 15:47:59,520 - app.services.tobacco_service - INFO - 采购单已生成: data/result\银豹采购单_烟草公司.xls
2025-11-15 15:47:59,582 - app.services.tobacco_service - INFO - 烟草公司订单处理成功,订单时间: 2025-11-10, 总金额: 12226.22, 处理条目: 34
2025-11-15 15:50:32,432 - app.services.tobacco_service - INFO - 找到最新烟草订单明细文件: data/output\订单明细20251115154455.xlsx
2025-11-15 15:50:32,432 - app.services.tobacco_service - INFO - 开始处理烟草公司订单: data/output\订单明细20251115154455.xlsx
2025-11-15 15:50:32,455 - app.services.tobacco_service - INFO - 采购单生成成功: data/result\银豹采购单_烟草公司.xls
2025-11-15 15:50:32,456 - app.services.tobacco_service - INFO - 烟草公司订单处理成功,订单时间: 2025-11-10, 总金额: 12226.22, 处理条目: 34
2025-11-15 15:50:32,463 - app.services.tobacco_service - INFO - 采购单已生成: data/result\银豹采购单_烟草公司.xls
2025-11-15 15:50:32,519 - app.services.tobacco_service - INFO - 烟草公司订单处理成功,订单时间: 2025-11-10, 总金额: 12226.22, 处理条目: 34
2025-11-15 15:51:02,790 - app.services.tobacco_service - INFO - 找到最新烟草订单明细文件: data/output\订单明细20251115154455.xlsx
2025-11-15 15:51:02,791 - app.services.tobacco_service - INFO - 开始处理烟草公司订单: data/output\订单明细20251115154455.xlsx
2025-11-15 15:51:02,814 - app.services.tobacco_service - INFO - 采购单生成成功: data/result\银豹采购单_烟草公司.xls
2025-11-15 15:51:02,815 - app.services.tobacco_service - INFO - 烟草公司订单处理成功,订单时间: 2025-11-10, 总金额: 12226.22, 处理条目: 34
2025-11-15 15:51:02,827 - app.services.tobacco_service - INFO - 采购单已生成: data/result\银豹采购单_烟草公司.xls
2025-11-15 15:51:02,885 - app.services.tobacco_service - INFO - 烟草公司订单处理成功,订单时间: 2025-11-10, 总金额: 12226.22, 处理条目: 34
2025-11-15 15:53:51,294 - app.services.tobacco_service - INFO - 找到最新烟草订单明细文件: data/output\订单明细20251115154455.xlsx
2025-11-15 15:53:51,298 - app.services.tobacco_service - INFO - 开始处理烟草公司订单: data/output\订单明细20251115154455.xlsx
2025-11-15 15:53:51,328 - app.services.tobacco_service - INFO - 采购单生成成功: data/result\银豹采购单_烟草公司.xls
2025-11-15 15:53:51,329 - app.services.tobacco_service - INFO - 烟草公司订单处理成功,订单时间: 2025-11-10, 总金额: 12226.22, 处理条目: 34
2025-11-15 15:53:51,337 - app.services.tobacco_service - INFO - 采购单已生成: data/result\银豹采购单_烟草公司.xls
2025-11-15 15:53:51,391 - app.services.tobacco_service - INFO - 烟草公司订单处理成功,订单时间: 2025-11-10, 总金额: 12226.22, 处理条目: 34
2025-11-15 15:54:07,757 - app.services.tobacco_service - INFO - 找到最新烟草订单明细文件: data/output\订单明细20251115154455.xlsx
2025-11-15 15:54:07,758 - app.services.tobacco_service - INFO - 开始处理烟草公司订单: data/output\订单明细20251115154455.xlsx
2025-11-15 15:54:07,783 - app.services.tobacco_service - INFO - 采购单生成成功: data/result\银豹采购单_烟草公司.xls
2025-11-15 15:54:07,783 - app.services.tobacco_service - INFO - 烟草公司订单处理成功,订单时间: 2025-11-10, 总金额: 12226.22, 处理条目: 34
2025-11-15 15:54:07,796 - app.services.tobacco_service - INFO - 采购单已生成: data/result\银豹采购单_烟草公司.xls
2025-11-15 15:54:07,930 - app.services.tobacco_service - INFO - 烟草公司订单处理成功,订单时间: 2025-11-10, 总金额: 12226.22, 处理条目: 34
2026-03-30 14:28:39,783 - app.services.tobacco_service - INFO - 执行烟草订单专用预处理: data/output/订单明细20260330133908.xlsx
2026-03-30 14:28:39,828 - app.services.tobacco_service - INFO - 烟草订单预处理完成: data/output\预处理之后_订单明细20260330133908.xlsx
2026-03-30 14:41:47,819 - app.services.tobacco_service - INFO - 执行烟草订单专用预处理: E:/2025Code/python/orc-order-v2/data/output/订单明细20260330133908.xlsx
2026-03-30 14:41:47,865 - app.services.tobacco_service - INFO - 烟草订单预处理完成: E:/2025Code/python/orc-order-v2/data/output\预处理之后_订单明细20260330133908.xlsx
2026-03-31 09:07:58,250 - app.services.tobacco_service - INFO - 执行烟草订单专用预处理: data/output\订单明细20260331090709.xlsx
2026-03-31 09:07:58,289 - app.services.tobacco_service - INFO - 烟草订单预处理完成: data/output\预处理之后_订单明细20260331090709.xlsx
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server {
listen 18888;
server_name _;
root /usr/share/nginx/html;
index index.html;
# Gzip compression
gzip on;
gzip_types text/plain text/css application/json application/javascript text/xml;
gzip_min_length 1000;
# API proxy to backend
location /api/ {
proxy_pass http://backend:18889;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
proxy_set_header X-Forwarded-Proto $scheme;
}
# WebSocket proxy to backend
location /ws/ {
proxy_pass http://backend:18889;
proxy_http_version 1.1;
proxy_set_header Upgrade $http_upgrade;
proxy_set_header Connection "upgrade";
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
proxy_read_timeout 86400;
}
# Vue Router history mode - serve index.html for all routes
location / {
try_files $uri $uri/ /index.html;
}
# Cache static assets
location ~* \.(js|css|png|jpg|jpeg|gif|ico|svg|woff|woff2|ttf|eot)$ {
expires 30d;
add_header Cache-Control "public, immutable";
}
}
-1
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@@ -1,5 +1,4 @@
configparser>=5.0.0
python-dotenv>=1.0.0
numpy>=1.19.0
openpyxl>=3.0.0
pandas>=1.3.0
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"""app.core.handlers.calculator 单元测试"""
import pytest
import pandas as pd
import numpy as np
from app.core.handlers.calculator import DataCalculator
@pytest.fixture
def sample_df():
return pd.DataFrame({
'price': [10.0, 20.0, 30.0],
'quantity': [2, 5, 10],
'name': ['A', 'B', 'C'],
})
class TestMultiply:
def test_basic_multiply(self, sample_df):
calc = DataCalculator()
calc.add_rule('multiply', source_column='price', target_column='total', factor=2)
result = calc.calculate(sample_df)
assert list(result['total']) == [20.0, 40.0, 60.0]
def test_multiply_missing_source(self, sample_df):
calc = DataCalculator()
calc.add_rule('multiply', source_column='nonexistent', target_column='total', factor=2)
result = calc.calculate(sample_df)
assert 'total' not in result.columns
def test_multiply_default_factor(self, sample_df):
calc = DataCalculator()
calc.add_rule('multiply', source_column='price', target_column='copy', factor=1)
result = calc.calculate(sample_df)
assert list(result['copy']) == [10.0, 20.0, 30.0]
def test_convenience_method(self, sample_df):
calc = DataCalculator()
calc.multiply('price', 'total', 3)
result = calc.calculate(sample_df)
assert list(result['total']) == [30.0, 60.0, 90.0]
class TestDivide:
def test_basic_divide(self, sample_df):
calc = DataCalculator()
calc.add_rule('divide', source_column='price', target_column='half', divisor=2)
result = calc.calculate(sample_df)
assert list(result['half']) == [5.0, 10.0, 15.0]
def test_divide_by_zero(self, sample_df):
calc = DataCalculator()
calc.add_rule('divide', source_column='price', target_column='half', divisor=0)
result = calc.calculate(sample_df)
assert 'half' not in result.columns
def test_divide_missing_source(self, sample_df):
calc = DataCalculator()
calc.add_rule('divide', source_column='nonexistent', target_column='x', divisor=2)
result = calc.calculate(sample_df)
assert 'x' not in result.columns
class TestAdd:
def test_add_columns(self):
df = pd.DataFrame({'a': [1, 2, 3], 'b': [10, 20, 30]})
calc = DataCalculator()
calc.add_rule('add', columns=['a', 'b'], target_column='sum')
result = calc.calculate(df)
assert list(result['sum']) == [11, 22, 33]
def test_add_constant(self):
df = pd.DataFrame({'a': [1, 2, 3]})
calc = DataCalculator()
calc.add_rule('add', target_column='a', constant=100)
result = calc.calculate(df)
assert list(result['a']) == [101, 102, 103]
def test_add_columns_with_constant(self):
df = pd.DataFrame({'a': [1, 2], 'b': [3, 4]})
calc = DataCalculator()
calc.add_rule('add', columns=['a', 'b'], target_column='total', constant=10)
result = calc.calculate(df)
assert list(result['total']) == [14, 16]
def test_add_string_column(self):
df = pd.DataFrame({'a': [1, 2]})
calc = DataCalculator()
calc.add_rule('add', columns='a', target_column='total')
result = calc.calculate(df)
assert list(result['total']) == [1, 2]
class TestSubtract:
def test_subtract_two_columns(self):
df = pd.DataFrame({'income': [100, 200], 'cost': [30, 80]})
calc = DataCalculator()
calc.add_rule('subtract', minuend='income', subtrahend='cost', target_column='profit')
result = calc.calculate(df)
assert list(result['profit']) == [70, 120]
def test_subtract_constant(self):
df = pd.DataFrame({'price': [100, 200]})
calc = DataCalculator()
calc.add_rule('subtract', minuend='price', target_column='discounted', constant=10)
result = calc.calculate(df)
assert list(result['discounted']) == [90, 190]
def test_subtract_missing_minuend(self):
df = pd.DataFrame({'a': [1, 2]})
calc = DataCalculator()
calc.add_rule('subtract', minuend='nonexistent', target_column='x', constant=1)
result = calc.calculate(df)
assert 'x' not in result.columns
class TestFormula:
def test_basic_formula(self, sample_df):
calc = DataCalculator()
calc.add_rule('formula', formula='price * quantity', target_column='total')
result = calc.calculate(sample_df)
assert list(result['total']) == [20.0, 100.0, 300.0]
def test_invalid_formula(self, sample_df):
calc = DataCalculator()
calc.add_rule('formula', formula='nonexistent + 1', target_column='x')
result = calc.calculate(sample_df)
# formula fails, original df returned
assert 'x' not in result.columns
def test_formula_missing_target(self, sample_df):
calc = DataCalculator()
calc.add_rule('formula', formula='price * 2')
result = calc.calculate(sample_df)
# no target_column, nothing happens
assert list(result['price']) == [10.0, 20.0, 30.0]
class TestRound:
def test_round_specific_columns(self):
df = pd.DataFrame({'a': [1.234, 2.567], 'b': [3.1, 4.9]})
calc = DataCalculator()
calc.add_rule('round', columns=['a'], decimals=1)
result = calc.calculate(df)
assert list(result['a']) == [1.2, 2.6]
assert list(result['b']) == [3.1, 4.9] # unchanged
def test_round_all_numeric(self):
df = pd.DataFrame({'a': [1.234, 2.567], 'b': [3.111, 4.999]})
calc = DataCalculator()
calc.add_rule('round', decimals=0)
result = calc.calculate(df)
assert list(result['a']) == [1.0, 3.0]
assert list(result['b']) == [3.0, 5.0]
def test_round_string_column_skipped(self):
df = pd.DataFrame({'name': ['a', 'b'], 'val': [1.5, 2.5]})
calc = DataCalculator()
calc.add_rule('round', columns=['name', 'val'], decimals=0)
result = calc.calculate(df)
assert list(result['val']) == [2.0, 2.0]
class TestSum:
def test_sum_columns_to_target(self):
df = pd.DataFrame({'a': [1, 2], 'b': [3, 4], 'c': [5, 6]})
calc = DataCalculator()
calc.add_rule('sum', columns=['a', 'b'], target_column='total')
result = calc.calculate(df)
assert list(result['total']) == [4, 6]
def test_sum_missing_columns(self):
df = pd.DataFrame({'a': [1, 2]})
calc = DataCalculator()
calc.add_rule('sum', columns=['a', 'missing'], target_column='total')
result = calc.calculate(df)
assert list(result['total']) == [1, 2]
class TestChaining:
def test_multiple_rules(self, sample_df):
calc = DataCalculator()
calc.add_rule('multiply', source_column='price', target_column='total', factor=2)
calc.add_rule('add', columns=['total', 'quantity'], target_column='grand')
result = calc.calculate(sample_df)
assert list(result['total']) == [20.0, 40.0, 60.0]
assert list(result['grand']) == [22.0, 45.0, 70.0]
def test_chaining_convenience(self, sample_df):
calc = DataCalculator()
calc.multiply('price', 'total', 2).round_columns('total', 0)
result = calc.calculate(sample_df)
assert list(result['total']) == [20.0, 40.0, 60.0]
class TestEdgeCases:
def test_empty_dataframe(self):
df = pd.DataFrame({'a': pd.Series([], dtype=float)})
calc = DataCalculator()
calc.add_rule('multiply', source_column='a', target_column='b', factor=2)
result = calc.calculate(df)
assert len(result) == 0
def test_no_rules(self, sample_df):
calc = DataCalculator()
result = calc.calculate(sample_df)
assert list(result['price']) == [10.0, 20.0, 30.0]
def test_unknown_rule_type(self, sample_df):
calc = DataCalculator()
calc.add_rule('unknown_op', source_column='price', target_column='x')
result = calc.calculate(sample_df)
# unknown rule is skipped, df unchanged
assert list(result['price']) == [10.0, 20.0, 30.0]
def test_rule_failure_continues(self, sample_df):
calc = DataCalculator()
calc.add_rule('formula', formula='nonexistent + 1', target_column='x')
calc.add_rule('multiply', source_column='price', target_column='y', factor=2)
result = calc.calculate(sample_df)
assert list(result['y']) == [20.0, 40.0, 60.0]
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"""app.core.handlers.column_mapper 单元测试"""
import pytest
import pandas as pd
from app.core.handlers.column_mapper import ColumnMapper
class TestStandardColumns:
"""STANDARD_COLUMNS 完整性测试"""
def test_has_all_standard_fields(self):
expected = {'barcode', 'name', 'specification', 'quantity', 'unit',
'unit_price', 'total_price', 'gift_quantity',
'category', 'brand', 'supplier'}
assert set(ColumnMapper.STANDARD_COLUMNS.keys()) == expected
def test_no_empty_alias_lists(self):
for field, aliases in ColumnMapper.STANDARD_COLUMNS.items():
assert len(aliases) > 0, f"{field} has no aliases"
def test_barcode_includes_key_names(self):
bc = ColumnMapper.STANDARD_COLUMNS['barcode']
assert '条码' in bc
assert '商品条码' in bc
assert 'barcode' in bc
def test_gift_quantity_includes_common_names(self):
gq = ColumnMapper.STANDARD_COLUMNS['gift_quantity']
assert '赠送量' in gq
assert '赠品数量' in gq
class TestFindColumn:
"""ColumnMapper.find_column 列查找测试"""
def test_exact_match(self):
cols = ['商品条码', '商品名称', '数量', '单价']
assert ColumnMapper.find_column(cols, 'barcode') == '商品条码'
def test_exact_match_standard_english(self):
cols = ['barcode', 'name', 'quantity']
assert ColumnMapper.find_column(cols, 'barcode') == 'barcode'
def test_whitespace_match(self):
"""列名含空格时应匹配"""
cols = ['名 称', '数 量']
assert ColumnMapper.find_column(cols, 'name') == '名 称'
assert ColumnMapper.find_column(cols, 'quantity') == '数 量'
def test_partial_match_substring(self):
"""列名包含候选名时应匹配"""
cols = ['商品条码(小条码)', '商品名称']
assert ColumnMapper.find_column(cols, 'barcode') == '商品条码(小条码)'
def test_not_found_returns_none(self):
cols = ['日期', '备注', '编号']
assert ColumnMapper.find_column(cols, 'barcode') is None
def test_unknown_standard_name_returns_none(self):
cols = ['商品条码']
assert ColumnMapper.find_column(cols, 'nonexistent_field') is None
def test_first_match_wins(self):
"""多个列都能匹配时返回第一个"""
cols = ['条码', '商品条码', 'barcode']
assert ColumnMapper.find_column(cols, 'barcode') == '条码'
def test_case_insensitive(self):
cols = ['Barcode', 'Name']
assert ColumnMapper.find_column(cols, 'barcode') == 'Barcode'
def test_all_fields_matchable(self):
"""每个标准字段都能找到至少一个匹配"""
cols = [
'商品条码', '商品名称', '规格', '数量', '单位',
'单价', '金额', '赠送量', '类别', '品牌', '供应商',
]
for std_name in ColumnMapper.STANDARD_COLUMNS:
result = ColumnMapper.find_column(cols, std_name)
assert result is not None, f"Could not find {std_name} in {cols}"
class TestDetectHeaderRow:
"""ColumnMapper.detect_header_row 表头检测测试"""
def test_header_on_first_row(self):
df = pd.DataFrame({
'A': ['条码', '123456', '789012'],
'B': ['数量', '10', '20'],
'C': ['单价', '5.5', '3.0'],
})
assert ColumnMapper.detect_header_row(df, min_matches=2) == 0
def test_header_on_second_row(self):
df = pd.DataFrame({
'A': ['备注', '条码', '123456'],
'B': ['日期', '数量', '10'],
'C': ['时间', '单价', '5.5'],
})
assert ColumnMapper.detect_header_row(df, min_matches=2) == 1
def test_no_header_returns_minus_one(self):
df = pd.DataFrame({
'A': ['aaa', 'bbb', 'ccc'],
'B': ['ddd', 'eee', 'fff'],
})
assert ColumnMapper.detect_header_row(df, min_matches=3) == -1
def test_empty_dataframe(self):
df = pd.DataFrame()
assert ColumnMapper.detect_header_row(df) == -1
def test_max_rows_limits_scan(self):
"""表头在第 10 行但 max_rows=5 时应返回 -1"""
data = {f'col{i}': ['x'] * 15 for i in range(3)}
data['col0'][10] = '条码'
data['col1'][10] = '数量'
data['col2'][10] = '单价'
df = pd.DataFrame(data)
assert ColumnMapper.detect_header_row(df, max_rows=5, min_matches=2) == -1
class TestColumnMapperInstance:
"""ColumnMapper 实例方法测试"""
def test_init_with_no_config(self):
mapper = ColumnMapper()
assert mapper.mapping_config == {}
def test_init_with_custom_config(self):
mapper = ColumnMapper(mapping_config={'barcode': ['我的条码']})
assert '我的条码' in mapper.custom_mappings
def test_map_columns_renames(self):
mapper = ColumnMapper()
df = pd.DataFrame({'商品条码': ['123'], '商品名称': ['测试'], '数量': [10]})
result = mapper.map_columns(df, target_columns=['barcode', 'name', 'quantity'])
assert 'barcode' in result.columns
assert 'name' in result.columns
assert 'quantity' in result.columns
def test_map_columns_fills_missing(self):
mapper = ColumnMapper()
df = pd.DataFrame({'商品条码': ['123']})
result = mapper.map_columns(df, target_columns=['barcode', 'quantity'])
assert 'barcode' in result.columns
assert 'quantity' in result.columns
assert result['quantity'].iloc[0] == 0 # default value
def test_add_custom_mapping(self):
mapper = ColumnMapper()
mapper.add_custom_mapping('barcode', '自定义条码列')
assert '自定义条码列' in mapper.reverse_mapping
assert mapper.reverse_mapping['自定义条码列'] == 'barcode'
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"""app.core.handlers.data_cleaner 单元测试"""
import pytest
import pandas as pd
from app.core.handlers.data_cleaner import DataCleaner
@pytest.fixture
def sample_df():
return pd.DataFrame({
'name': [' Alice ', 'Bob', 'Charlie', 'Dave'],
'age': [25, 30, None, 40],
'score': [80.5, 90.0, 70.0, 85.0],
'city': ['Beijing', 'Shanghai', 'Beijing', 'Guangzhou'],
})
class TestFillNa:
def test_fill_na_with_value(self, sample_df):
cleaner = DataCleaner()
cleaner.add_rule('fill_na', columns=['age'], value=0)
result = cleaner.clean(sample_df)
assert result['age'].isna().sum() == 0
assert result.loc[2, 'age'] == 0
def test_fill_na_all_columns(self, sample_df):
cleaner = DataCleaner()
cleaner.add_rule('fill_na', value=-1)
result = cleaner.clean(sample_df)
assert result.isna().sum().sum() == 0
def test_fill_na_string_column(self):
df = pd.DataFrame({'a': ['x', None, 'z']})
cleaner = DataCleaner()
cleaner.add_rule('fill_na', columns=['a'], value='unknown')
result = cleaner.clean(df)
assert result.loc[1, 'a'] == 'unknown'
def test_convenience_method(self, sample_df):
cleaner = DataCleaner()
cleaner.fill_na(columns='age', value=99)
result = cleaner.clean(sample_df)
assert result.loc[2, 'age'] == 99
class TestRemoveDuplicates:
def test_remove_by_subset(self):
df = pd.DataFrame({
'name': ['A', 'B', 'A', 'C'],
'val': [1, 2, 3, 4],
})
cleaner = DataCleaner()
cleaner.add_rule('remove_duplicates', subset=['name'], keep='first')
result = cleaner.clean(df)
assert len(result) == 3
assert list(result['name']) == ['A', 'B', 'C']
def test_remove_all_columns(self):
df = pd.DataFrame({
'a': [1, 1, 2],
'b': [10, 10, 20],
})
cleaner = DataCleaner()
cleaner.add_rule('remove_duplicates')
result = cleaner.clean(df)
assert len(result) == 2
def test_no_duplicates(self, sample_df):
cleaner = DataCleaner()
cleaner.add_rule('remove_duplicates', subset=['name'])
result = cleaner.clean(sample_df)
assert len(result) == 4
class TestRemoveRows:
def test_remove_by_condition(self, sample_df):
cleaner = DataCleaner()
cleaner.add_rule('remove_rows', condition='age > 25')
result = cleaner.clean(sample_df)
assert len(result) == 2
def test_remove_by_values(self, sample_df):
cleaner = DataCleaner()
cleaner.add_rule('remove_rows', columns=['city'], values=['Beijing'])
result = cleaner.clean(sample_df)
assert len(result) == 2
assert 'Beijing' not in result['city'].values
def test_remove_no_match(self, sample_df):
cleaner = DataCleaner()
cleaner.add_rule('remove_rows', condition='age > 100')
result = cleaner.clean(sample_df)
assert len(result) == 0 # condition filter: no rows match age > 100
def test_convenience_method(self, sample_df):
cleaner = DataCleaner()
cleaner.remove_rows(condition='score < 75')
result = cleaner.clean(sample_df)
assert len(result) == 1 # condition filter: keeps only Charlie (score=70.0)
class TestConvertType:
def test_to_float(self):
df = pd.DataFrame({'val': ['1.5', '2.7', 'abc']})
cleaner = DataCleaner()
cleaner.add_rule('convert_type', columns=['val'], target_type='float')
result = cleaner.clean(df)
assert result['val'].dtype.kind == 'f'
assert result.loc[0, 'val'] == 1.5
assert pd.isna(result.loc[2, 'val'])
def test_to_int(self):
df = pd.DataFrame({'val': ['1', '2', '3']})
cleaner = DataCleaner()
cleaner.add_rule('convert_type', columns=['val'], target_type='int')
result = cleaner.clean(df)
assert result.loc[0, 'val'] == 1
def test_to_string(self):
df = pd.DataFrame({'val': [1, 2, 3]})
cleaner = DataCleaner()
cleaner.add_rule('convert_type', columns=['val'], target_type='string')
result = cleaner.clean(df)
assert result.loc[0, 'val'] == '1'
def test_missing_column_skipped(self, sample_df):
cleaner = DataCleaner()
cleaner.add_rule('convert_type', columns=['nonexistent'], target_type='float')
result = cleaner.clean(sample_df)
assert len(result) == 4
class TestStripWhitespace:
def test_strip_specific_columns(self, sample_df):
cleaner = DataCleaner()
cleaner.add_rule('strip_whitespace', columns=['name'])
result = cleaner.clean(sample_df)
assert result.loc[0, 'name'] == 'Alice'
def test_strip_all_text(self, sample_df):
cleaner = DataCleaner()
cleaner.add_rule('strip_whitespace')
result = cleaner.clean(sample_df)
assert result.loc[0, 'name'] == 'Alice'
def test_strip_non_text_skipped(self):
df = pd.DataFrame({'val': [1, 2, 3]})
cleaner = DataCleaner()
cleaner.add_rule('strip_whitespace', columns=['val'])
result = cleaner.clean(df)
assert list(result['val']) == [1, 2, 3]
class TestNormalizeText:
def test_lowercase(self):
df = pd.DataFrame({'name': ['ALICE', 'BOB']})
cleaner = DataCleaner()
cleaner.add_rule('normalize_text', columns=['name'], lowercase=True)
result = cleaner.clean(df)
assert list(result['name']) == ['alice', 'bob']
def test_uppercase(self):
df = pd.DataFrame({'name': ['alice', 'bob']})
cleaner = DataCleaner()
cleaner.add_rule('normalize_text', columns=['name'], uppercase=True)
result = cleaner.clean(df)
assert list(result['name']) == ['ALICE', 'BOB']
def test_replace_map(self):
df = pd.DataFrame({'city': ['BJ', 'SH']})
cleaner = DataCleaner()
cleaner.add_rule('normalize_text', columns=['city'], replace_map={'BJ': 'Beijing', 'SH': 'Shanghai'})
result = cleaner.clean(df)
assert list(result['city']) == ['Beijing', 'Shanghai']
class TestValidateData:
def test_validate_logs_but_does_not_modify(self, sample_df):
cleaner = DataCleaner()
cleaner.add_rule('validate_data', columns=['score'], min_value=0, max_value=100)
result = cleaner.clean(sample_df)
assert len(result) == 4
def test_validate_required(self, sample_df):
cleaner = DataCleaner()
cleaner.add_rule('validate_data', columns=['age'], required=True)
result = cleaner.clean(sample_df)
assert len(result) == 4
class TestChaining:
def test_multiple_rules(self, sample_df):
cleaner = DataCleaner()
cleaner.add_rule('strip_whitespace', columns=['name'])
cleaner.add_rule('fill_na', columns=['age'], value=0)
cleaner.add_rule('convert_type', columns=['age'], target_type='int')
result = cleaner.clean(sample_df)
assert result.loc[0, 'name'] == 'Alice'
assert result['age'].isna().sum() == 0
assert result.loc[2, 'age'] == 0
def test_convenience_chaining(self, sample_df):
cleaner = DataCleaner()
cleaner.strip_whitespace('name').fill_na('age', value=0)
result = cleaner.clean(sample_df)
assert result.loc[0, 'name'] == 'Alice'
assert result.loc[2, 'age'] == 0
class TestEdgeCases:
def test_empty_dataframe(self):
df = pd.DataFrame({'a': pd.Series([], dtype=float)})
cleaner = DataCleaner()
cleaner.add_rule('fill_na', value=0)
result = cleaner.clean(df)
assert len(result) == 0
def test_no_rules(self, sample_df):
cleaner = DataCleaner()
result = cleaner.clean(sample_df)
assert len(result) == 4
def test_unknown_rule_type(self, sample_df):
cleaner = DataCleaner()
cleaner.add_rule('unknown_op', columns=['name'])
result = cleaner.clean(sample_df)
assert len(result) == 4
def test_rule_failure_continues(self, sample_df):
"""A failing rule should not block subsequent rules."""
cleaner = DataCleaner()
cleaner.add_rule('convert_type', columns=['nonexistent'], target_type='float')
cleaner.add_rule('fill_na', columns=['age'], value=0)
result = cleaner.clean(sample_df)
assert result.loc[2, 'age'] == 0
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"""app.core.db.product_db 单元测试"""
import os
import tempfile
import pytest
import pandas as pd
from app.core.db.product_db import ProductDatabase
@pytest.fixture
def db_dir():
"""临时目录"""
with tempfile.TemporaryDirectory() as d:
yield d
@pytest.fixture
def sample_excel(db_dir):
"""创建测试用 Excel 文件"""
path = os.path.join(db_dir, '商品资料.xlsx')
df = pd.DataFrame({
'商品条码': ['6920584471055', '6901028001133', '6925303800013'],
'商品名称': ['农夫山泉550ml', '蒙牛纯牛奶', '可口可乐330ml'],
'进货价': [1.2, 3.5, 1.8],
'单位': ['', '', ''],
})
df.to_excel(path, index=False)
return path
@pytest.fixture
def db_with_data(db_dir, sample_excel):
"""已导入数据的数据库"""
db_path = os.path.join(db_dir, 'product_cache.db')
db = ProductDatabase(db_path, sample_excel)
return db
class TestProductDatabaseInit:
"""数据库初始化测试"""
def test_auto_import_on_first_run(self, db_dir, sample_excel):
"""首次运行自动从 Excel 导入"""
db_path = os.path.join(db_dir, 'product_cache.db')
assert not os.path.exists(db_path)
db = ProductDatabase(db_path, sample_excel)
assert os.path.exists(db_path)
assert db.count() == 3
def test_no_reimport_on_existing_db(self, db_dir, sample_excel):
"""数据库已存在时不重新导入"""
db_path = os.path.join(db_dir, 'product_cache.db')
db1 = ProductDatabase(db_path, sample_excel)
assert db1.count() == 3
# 删除 Excel 后仍能打开已有数据库
os.remove(sample_excel)
db2 = ProductDatabase(db_path, sample_excel)
assert db2.count() == 3
def test_missing_excel_creates_empty_db(self, db_dir):
"""Excel 不存在时创建空数据库"""
db_path = os.path.join(db_dir, 'product_cache.db')
fake_excel = os.path.join(db_dir, '不存在.xlsx')
db = ProductDatabase(db_path, fake_excel)
assert os.path.exists(db_path)
assert db.count() == 0
def test_missing_dir_created(self, db_dir, sample_excel):
"""数据库目录不存在时自动创建"""
db_path = os.path.join(db_dir, 'subdir', 'product_cache.db')
db = ProductDatabase(db_path, sample_excel)
assert os.path.exists(db_path)
assert db.count() == 3
class TestGetPrice:
"""单条查询测试"""
def test_existing_barcode(self, db_with_data):
price = db_with_data.get_price('6920584471055')
assert price == pytest.approx(1.2)
def test_nonexistent_barcode(self, db_with_data):
price = db_with_data.get_price('0000000000000')
assert price is None
def test_empty_barcode(self, db_with_data):
price = db_with_data.get_price('')
assert price is None
def test_barcode_with_spaces(self, db_with_data):
"""条码前后空格应能匹配"""
price = db_with_data.get_price(' 6920584471055 ')
assert price == pytest.approx(1.2)
class TestGetPrices:
"""批量查询测试"""
def test_multiple_barcodes(self, db_with_data):
result = db_with_data.get_prices(['6920584471055', '6901028001133'])
assert len(result) == 2
assert result['6920584471055'] == pytest.approx(1.2)
assert result['6901028001133'] == pytest.approx(3.5)
def test_partial_match(self, db_with_data):
"""部分条码存在,部分不存在"""
result = db_with_data.get_prices(['6920584471055', '0000000000000'])
assert len(result) == 1
assert '6920584471055' in result
def test_empty_list(self, db_with_data):
result = db_with_data.get_prices([])
assert result == {}
def test_all_nonexistent(self, db_with_data):
result = db_with_data.get_prices(['0000000000000', '1111111111111'])
assert result == {}
class TestReimport:
"""重新导入测试"""
def test_reimport_clears_and_reloads(self, db_dir, sample_excel):
db_path = os.path.join(db_dir, 'product_cache.db')
db = ProductDatabase(db_path, sample_excel)
assert db.count() == 3
# 修改 Excel,添加一行
df = pd.read_excel(sample_excel)
df = pd.concat([df, pd.DataFrame({
'商品条码': ['6954365200123'],
'商品名称': ['测试商品'],
'进货价': [5.0],
'单位': [''],
})])
df.to_excel(sample_excel, index=False)
count = db.reimport()
assert count == 4
assert db.count() == 4
assert db.get_price('6954365200123') == pytest.approx(5.0)
class TestEdgeCases:
"""边界条件测试"""
def test_excel_with_missing_price(self, db_dir):
"""Excel 中价格列为空的行"""
path = os.path.join(db_dir, '商品资料.xlsx')
df = pd.DataFrame({
'商品条码': ['6920584471055', '6901028001133'],
'商品名称': ['商品A', '商品B'],
'进货价': [1.5, None],
})
df.to_excel(path, index=False)
db_path = os.path.join(db_dir, 'product_cache.db')
db = ProductDatabase(db_path, path)
assert db.count() == 2
assert db.get_price('6920584471055') == pytest.approx(1.5)
assert db.get_price('6901028001133') == pytest.approx(0.0)
def test_excel_with_duplicate_barcodes(self, db_dir):
"""重复条码取最后一条 (INSERT OR REPLACE)"""
path = os.path.join(db_dir, '商品资料.xlsx')
df = pd.DataFrame({
'商品条码': ['6920584471055', '6920584471055'],
'商品名称': ['商品A', '商品A-新'],
'进货价': [1.0, 2.0],
})
df.to_excel(path, index=False)
db_path = os.path.join(db_dir, 'product_cache.db')
db = ProductDatabase(db_path, path)
assert db.count() == 1
assert db.get_price('6920584471055') == pytest.approx(2.0)
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"""app.core.handlers.rule_engine 单元测试"""
import pytest
import pandas as pd
from app.core.handlers.rule_engine import (
apply_rules,
_split_quantity_unit,
_extract_spec_from_name,
_normalize_unit,
_compute_quantity_from_total,
_fill_missing,
_mark_gift,
)
@pytest.fixture
def sample_df():
return pd.DataFrame({
'name': ['农夫山泉550ml*24', '蒙牛纯牛奶', '可口可乐330ml*6'],
'quantity_raw': ['2箱', '5', '3提'],
'unit_price': [28.8, 3.5, 10.8],
'total_price': [57.6, 17.5, 32.4],
})
class TestSplitQuantityUnit:
def test_split_with_unit(self):
df = pd.DataFrame({'quantity_raw': ['2箱', '5瓶', '3提']})
result = _split_quantity_unit(df, 'quantity_raw')
assert list(result['quantity']) == [2.0, 5.0, 3.0]
assert list(result['unit']) == ['', '', '']
def test_split_number_only(self):
df = pd.DataFrame({'quantity_raw': ['10', '20']})
result = _split_quantity_unit(df, 'quantity_raw')
assert list(result['quantity']) == [10.0, 20.0]
def test_split_with_synonyms(self):
df = pd.DataFrame({'quantity_raw': ['2件']})
dictionary = {'unit_synonyms': {'': ''}, 'default_unit': ''}
result = _split_quantity_unit(df, 'quantity_raw', dictionary)
assert result.loc[0, 'unit'] == ''
def test_split_missing_column(self):
df = pd.DataFrame({'other': [1, 2]})
result = _split_quantity_unit(df, 'quantity_raw')
assert 'quantity' not in result.columns
def test_split_invalid_value(self):
df = pd.DataFrame({'quantity_raw': ['abc']})
result = _split_quantity_unit(df, 'quantity_raw')
assert result.loc[0, 'quantity'] == 0.0
class TestExtractSpecFromName:
def test_extract_550ml_24(self):
df = pd.DataFrame({'name': ['农夫山泉550ml*24']})
result = _extract_spec_from_name(df, 'name')
assert result.loc[0, 'package_quantity'] == 24
def test_extract_330ml_6(self):
df = pd.DataFrame({'name': ['可口可乐330ml*6']})
result = _extract_spec_from_name(df, 'name')
assert result.loc[0, 'package_quantity'] == 6
def test_extract_1_star_pattern(self):
df = pd.DataFrame({'name': ['啤酒1*12']})
result = _extract_spec_from_name(df, 'name')
assert result.loc[0, 'package_quantity'] == 12
def test_no_spec(self):
df = pd.DataFrame({'name': ['蒙牛纯牛奶']})
result = _extract_spec_from_name(df, 'name')
assert result.loc[0, 'package_quantity'] is None
def test_missing_column(self):
df = pd.DataFrame({'other': ['test']})
result = _extract_spec_from_name(df, 'name')
assert 'package_quantity' not in result.columns
def test_with_ignore_words(self):
df = pd.DataFrame({'name': ['新品 农夫山泉550ml*24']})
dictionary = {'ignore_words': ['新品'], 'name_patterns': []}
result = _extract_spec_from_name(df, 'name', dictionary)
assert result.loc[0, 'package_quantity'] == 24
class TestNormalizeUnit:
def test_map_units(self):
df = pd.DataFrame({'unit': ['', '', '', ''], 'quantity': [1, 2, 3, 4]})
unit_map = {'': '', '': '', '': ''}
result = _normalize_unit(df, 'unit', unit_map)
# _normalize_unit maps via unit_map, then converts 件→瓶 as packed unit
assert list(result['unit']) == ['', '', '', '']
def test_convert_quantity_for_packed_units(self):
df = pd.DataFrame({
'unit': ['', ''],
'quantity': [2, 5],
'package_quantity': [12, None],
})
unit_map = {'': ''}
result = _normalize_unit(df, 'unit', unit_map)
assert result.loc[0, 'quantity'] == 24 # 2 * 12
assert result.loc[1, 'quantity'] == 5 # unchanged
def test_missing_column(self):
df = pd.DataFrame({'other': [1]})
result = _normalize_unit(df, 'unit', {})
assert 'unit' not in result.columns
class TestComputeQuantityFromTotal:
def test_compute_when_qty_zero(self):
df = pd.DataFrame({
'quantity': [0, 5, 0],
'unit_price': [10.0, 20.0, 0.0],
'total_price': [50.0, 100.0, 30.0],
})
result = _compute_quantity_from_total(df)
assert result.loc[0, 'quantity'] == 5.0 # 50 / 10
assert result.loc[1, 'quantity'] == 5 # unchanged
def test_no_compute_when_qty_positive(self):
df = pd.DataFrame({
'quantity': [3, 5],
'unit_price': [10.0, 20.0],
'total_price': [50.0, 100.0],
})
result = _compute_quantity_from_total(df)
assert list(result['quantity']) == [3, 5]
class TestFillMissing:
def test_fill_existing_column(self):
df = pd.DataFrame({'a': [1, None, 3], 'b': [None, 2, None]})
result = _fill_missing(df, {'a': 0, 'b': 99})
assert result.loc[1, 'a'] == 0
assert result.loc[0, 'b'] == 99
def test_fill_new_column(self):
df = pd.DataFrame({'a': [1, 2]})
result = _fill_missing(df, {'new_col': 'default'})
assert list(result['new_col']) == ['default', 'default']
class TestMarkGift:
def test_gift_by_zero_price(self):
df = pd.DataFrame({
'name': ['商品A', '商品B'],
'unit_price': [10.0, 0.0],
'total_price': [20.0, 0.0],
})
result = _mark_gift(df)
assert result.loc[0, 'is_gift'] == False
assert result.loc[1, 'is_gift'] == True
def test_gift_by_name(self):
df = pd.DataFrame({
'name': ['赠品-杯子', '商品A'],
'unit_price': [0.0, 10.0],
'total_price': [0.0, 20.0],
})
result = _mark_gift(df)
assert result.loc[0, 'is_gift'] == True
assert result.loc[1, 'is_gift'] == False
def test_gift_no_price_columns(self):
df = pd.DataFrame({'name': ['赠品', '正常']})
result = _mark_gift(df)
assert result.loc[0, 'is_gift'] == True
assert result.loc[1, 'is_gift'] == False
class TestApplyRules:
def test_multiple_rules(self, sample_df):
rules = [
{'type': 'split_quantity_unit', 'source': 'quantity_raw'},
{'type': 'extract_spec_from_name', 'source': 'name'},
{'type': 'mark_gift'},
{'type': 'fill_missing', 'fills': {'unit': ''}},
]
result = apply_rules(sample_df, rules)
assert 'quantity' in result.columns
assert 'unit' in result.columns
assert 'package_quantity' in result.columns
assert 'is_gift' in result.columns
def test_empty_rules(self, sample_df):
result = apply_rules(sample_df, [])
assert len(result) == len(sample_df)
def test_none_rules(self, sample_df):
result = apply_rules(sample_df, None)
assert len(result) == len(sample_df)
def test_unknown_rule_type(self, sample_df):
rules = [{'type': 'unknown_operation'}]
result = apply_rules(sample_df, rules)
assert len(result) == len(sample_df)
def test_with_dictionary(self):
df = pd.DataFrame({
'name': ['农夫山泉550ml*24'],
'quantity_raw': ['2箱'],
})
dictionary = {
'unit_synonyms': {'': ''},
'default_unit': '',
'ignore_words': [],
'name_patterns': [],
'pack_multipliers': {'': 12},
'default_package_quantity': 1,
}
rules = [
{'type': 'split_quantity_unit', 'source': 'quantity_raw'},
{'type': 'extract_spec_from_name', 'source': 'name'},
{'type': 'normalize_unit', 'target': 'unit', 'map': {'': ''}},
]
result = apply_rules(df, rules, dictionary)
assert 'quantity' in result.columns
assert 'unit' in result.columns
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"""app.core.utils.string_utils 单元测试"""
import pytest
from app.core.utils.string_utils import parse_monetary_string, format_barcode
class TestParseMonetaryString:
"""parse_monetary_string 金额/数量字符串解析测试"""
# --- 基本类型 ---
def test_none_returns_none(self):
assert parse_monetary_string(None) is None
def test_int_passthrough(self):
assert parse_monetary_string(42) == 42.0
def test_float_passthrough(self):
assert parse_monetary_string(3.14) == 3.14
def test_zero_int(self):
assert parse_monetary_string(0) == 0.0
# --- 正常字符串 ---
def test_plain_number(self):
assert parse_monetary_string("123.45") == 123.45
def test_integer_string(self):
assert parse_monetary_string("100") == 100.0
# --- 货币符号 ---
def test_yen_prefix(self):
assert parse_monetary_string("¥1234.56") == 1234.56
def test_dollar_prefix(self):
assert parse_monetary_string("$99.9") == 99.9
def test_yuan_suffix(self):
assert parse_monetary_string("100元") == 100.0
# --- 逗号处理 ---
def test_comma_as_decimal_point(self):
"""逗号当小数点: "1,5" = 1.5"""
assert parse_monetary_string("1,5") == 1.5
def test_comma_as_thousands_sep(self):
"""逗号当千位分隔符: "1,234.56" = 1234.56"""
assert parse_monetary_string("1,234.56") == 1234.56
def test_multiple_commas_thousands(self):
"""多个逗号: "1,234,567" = 1234567"""
assert parse_monetary_string("1,234,567") == 1234567.0
# --- 空值/无效值 ---
def test_empty_string(self):
assert parse_monetary_string("") is None
def test_whitespace_only(self):
assert parse_monetary_string(" ") is None
def test_o_string(self):
"""OCR 常见误识别: 字母 o 当数字 0"""
assert parse_monetary_string("o") is None
def test_none_string(self):
assert parse_monetary_string("none") is None
def test_null_string(self):
assert parse_monetary_string("null") is None
def test_dash(self):
assert parse_monetary_string("-") is None
def test_double_dash(self):
assert parse_monetary_string("--") is None
def test_no_digits(self):
assert parse_monetary_string("赠品") is None
# --- 负数 ---
def test_negative_number(self):
assert parse_monetary_string("-5.5") == -5.5
# --- 非字符串非数字类型 ---
def test_list_returns_none(self):
assert parse_monetary_string([1, 2]) is None
def test_dict_returns_none(self):
assert parse_monetary_string({"a": 1}) is None
class TestFormatBarcode:
"""format_barcode 条码格式化测试"""
def test_none_returns_empty(self):
assert format_barcode(None) == ""
def test_normal_digit_string(self):
assert format_barcode("6920584471055") == "6920584471055"
def test_integer_input(self):
assert format_barcode(6920584471055) == "6920584471055"
def test_float_with_zero_decimal(self):
assert format_barcode(6920584471055.0) == "6920584471055"
def test_scientific_notation(self):
assert format_barcode("6.920584e+12") == "6920584000000"
def test_trailing_zeros_stripped(self):
assert format_barcode("123456.0") == "123456"
def test_long_barcode_with_trailing_zeros(self):
"""14位条码末尾是0时应截断到13位"""
assert format_barcode("69205844710550") == "6920584471055"
def test_long_barcode_without_trailing_zeros(self):
"""14位条码末尾不是0时不截断"""
assert format_barcode("69205844710551") == "69205844710551"
def test_non_digit_chars_removed(self):
assert format_barcode("692-058-4471055") == "6920584471055"
def test_empty_string(self):
assert format_barcode("") == ""
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"""app.core.excel.validators 单元测试"""
import pytest
from app.core.excel.validators import ProductValidator
@pytest.fixture
def validator():
return ProductValidator()
class TestValidateBarcode:
"""条码验证测试"""
def test_valid_barcode_13_digits(self, validator):
ok, val, err = validator.validate_barcode("6920584471055")
assert ok is True
assert val == "6920584471055"
assert err is None
def test_valid_barcode_8_digits(self, validator):
ok, val, err = validator.validate_barcode("12345678")
assert ok is True
assert val == "12345678"
def test_valid_barcode_12_digits(self, validator):
ok, val, err = validator.validate_barcode("692058447105")
assert ok is True
def test_none_returns_invalid(self, validator):
ok, val, err = validator.validate_barcode(None)
assert ok is False
assert err == "条码为空"
def test_warehouse_identifier(self, validator):
ok, val, err = validator.validate_barcode("仓库")
assert ok is False
assert val == "仓库"
assert err == "条码为仓库标识"
def test_warehouse_full_name(self, validator):
ok, val, err = validator.validate_barcode("仓库全名")
assert ok is False
def test_prefix_5_to_6_correction(self, validator):
"""5开头(非53)的长条码应修正为6开头"""
ok, val, err = validator.validate_barcode("5920584471055")
assert ok is True
assert val.startswith("6")
assert val == "6920584471055"
def test_prefix_53_not_corrected(self, validator):
"""53开头的条码不修正"""
ok, val, err = validator.validate_barcode("5321545613000")
assert ok is True
assert val.startswith("53")
def test_14_digit_trailing_zero_truncated(self, validator):
"""14位条码末尾是0时截断到13位"""
ok, val, err = validator.validate_barcode("69205844710550")
assert ok is True
assert len(val) == 13
def test_14_digit_no_trailing_zero_invalid(self, validator):
"""14位条码末尾不是0时报错"""
ok, val, err = validator.validate_barcode("69205844710551")
assert ok is False
assert "长度异常" in err
def test_too_short_invalid(self, validator):
ok, val, err = validator.validate_barcode("1234567")
assert ok is False
assert "长度异常" in err
def test_too_long_invalid(self, validator):
ok, val, err = validator.validate_barcode("1" * 14)
# 14 digits with trailing 0s gets truncated, but "111...1" has no trailing 0
ok2, val2, err2 = validator.validate_barcode("1" * 15)
assert ok2 is False
def test_no_digits_invalid(self, validator):
ok, val, err = validator.validate_barcode("abc")
assert ok is False
assert err == "条码不包含数字"
def test_float_input_cleaned(self, validator):
"""浮点数输入应清理为整数字符串"""
ok, val, err = validator.validate_barcode(6920584471055.0)
assert ok is True
assert val == "6920584471055"
def test_special_barcode_5321545613(self, validator):
"""特殊条码 5321545613 应通过验证"""
ok, val, err = validator.validate_barcode("5321545613")
assert ok is True
assert val == "5321545613"
class TestValidatePrice:
"""单价验证测试"""
def test_valid_price(self, validator):
ok, val, is_gift, err = validator.validate_price(10.5)
assert ok is True
assert val == 10.5
assert is_gift is False
def test_zero_price_is_gift(self, validator):
ok, val, is_gift, err = validator.validate_price(0)
assert ok is True
assert val == 0.0
assert is_gift is True
def test_none_is_gift(self, validator):
ok, val, is_gift, err = validator.validate_price(None)
assert ok is False
assert is_gift is True
def test_gift_string(self, validator):
ok, val, is_gift, err = validator.validate_price("赠品")
assert ok is True
assert is_gift is True
def test_gift_english(self, validator):
ok, val, is_gift, err = validator.validate_price("gift")
assert ok is True
assert is_gift is True
def test_price_string_with_yen(self, validator):
ok, val, is_gift, err = validator.validate_price("¥123.45")
assert ok is True
assert val == 123.45
assert is_gift is False
def test_price_string_with_comma(self, validator):
ok, val, is_gift, err = validator.validate_price("1,234.56")
assert ok is True
assert val == 1234.56
def test_negative_price_invalid(self, validator):
ok, val, is_gift, err = validator.validate_price(-5)
assert ok is False
assert is_gift is True
def test_empty_string_is_gift(self, validator):
ok, val, is_gift, err = validator.validate_price("")
assert ok is True
assert is_gift is True
class TestValidateQuantity:
"""数量验证测试"""
def test_valid_quantity(self, validator):
ok, val, err = validator.validate_quantity(10)
assert ok is True
assert val == 10.0
def test_float_quantity(self, validator):
ok, val, err = validator.validate_quantity(2.5)
assert ok is True
assert val == 2.5
def test_string_quantity(self, validator):
ok, val, err = validator.validate_quantity("15")
assert ok is True
assert val == 15.0
def test_string_with_unit(self, validator):
ok, val, err = validator.validate_quantity("10瓶")
assert ok is True
assert val == 10.0
def test_none_invalid(self, validator):
ok, val, err = validator.validate_quantity(None)
assert ok is False
assert err == "数量为空"
def test_zero_invalid(self, validator):
ok, val, err = validator.validate_quantity(0)
assert ok is False
assert "必须大于0" in err
def test_negative_invalid(self, validator):
ok, val, err = validator.validate_quantity(-3)
assert ok is False
assert "必须大于0" in err
def test_non_numeric_string_invalid(self, validator):
ok, val, err = validator.validate_quantity("abc")
assert ok is False
assert err == "数量不包含数字"
class TestValidateProduct:
"""商品数据整体验证测试"""
def test_valid_product(self, validator):
product = {
'barcode': '6920584471055',
'price': 10.5,
'quantity': 5,
'amount': 52.5,
}
result = validator.validate_product(product)
assert result['barcode'] == '6920584471055'
assert result['price'] == 10.5
assert result['quantity'] == 5.0
assert result.get('is_gift') is None or result.get('is_gift') is False
def test_gift_product(self, validator):
product = {
'barcode': '6920584471055',
'price': '赠品',
'quantity': 5,
}
result = validator.validate_product(product)
assert result['is_gift'] is True
assert result['price'] == 0.0
def test_quantity_from_amount_and_price(self, validator):
"""数量为空时,通过金额/单价计算"""
product = {
'barcode': '6920584471055',
'price': 10.0,
'amount': 50.0,
'quantity': None,
}
result = validator.validate_product(product)
assert result['quantity'] == 5.0 # 50 / 10
def test_invalid_barcode_still_uses_fixed(self, validator):
"""条码验证失败但有修复值时仍使用修复值"""
product = {
'barcode': '5920584471055', # 5开头, 会被修正为6开头
'price': 10.0,
'quantity': 5,
}
result = validator.validate_product(product)
assert result['barcode'] == '6920584471055'
def test_amount_zero_marks_gift(self, validator):
"""金额为0时标记为赠品"""
product = {
'barcode': '6920584471055',
'price': 10.0,
'quantity': 5,
'amount': 0,
}
result = validator.validate_product(product)
assert result.get('is_gift') is True
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"""FastAPI auth dependencies"""
from fastapi import Depends, HTTPException, status, Query, Request
from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
from .jwt_handler import decode_token
security = HTTPBearer()
async def get_current_user(
credentials: HTTPAuthorizationCredentials = Depends(security),
) -> dict:
try:
payload = decode_token(credentials.credentials)
username = payload.get("sub")
if username is None:
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED)
return {"username": username}
except Exception:
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="无效的认证凭据")
async def get_current_user_ws(token: str = Query(...)) -> dict:
"""WebSocket auth via query parameter"""
try:
payload = decode_token(token)
username = payload.get("sub")
if username is None:
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED)
return {"username": username}
except Exception:
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="无效的认证凭据")
async def get_current_user_flexible(
request: Request,
credentials: HTTPAuthorizationCredentials = Depends(HTTPBearer(auto_error=False)),
token: str = Query(None),
) -> dict:
"""Auth from header OR query param (for file downloads in browser)."""
token_str = None
if credentials:
token_str = credentials.credentials
elif token:
token_str = token
if not token_str:
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="未提供认证凭据")
try:
payload = decode_token(token_str)
username = payload.get("sub")
if username is None:
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED)
return {"username": username}
except Exception:
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="无效的认证凭据")
-19
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@@ -1,19 +0,0 @@
"""JWT token creation and validation"""
from datetime import datetime, timedelta, timezone
from typing import Optional
from jose import jwt, JWTError
from ..config import get_or_generate_secret, JWT_ALGORITHM, JWT_EXPIRE_HOURS
def create_access_token(data: dict, expires_delta: Optional[timedelta] = None) -> str:
to_encode = data.copy()
expire = datetime.now(timezone.utc) + (expires_delta or timedelta(hours=JWT_EXPIRE_HOURS))
to_encode.update({"exp": expire})
return jwt.encode(to_encode, get_or_generate_secret(), algorithm=JWT_ALGORITHM)
def decode_token(token: str) -> dict:
return jwt.decode(token, get_or_generate_secret(), algorithms=[JWT_ALGORITHM])
-89
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@@ -1,89 +0,0 @@
"""Auth API endpoints"""
import os
import bcrypt
from fastapi import APIRouter, HTTPException, Depends, status
from pydantic import BaseModel
from .jwt_handler import create_access_token
from .dependencies import get_current_user
router = APIRouter(prefix="/api/auth", tags=["auth"])
# Default credentials (should be changed on first login)
DEFAULT_USERNAME = "admin"
DEFAULT_PASSWORD = "admin123"
class LoginRequest(BaseModel):
username: str
password: str
class LoginResponse(BaseModel):
access_token: str
token_type: str = "bearer"
def _get_credentials() -> tuple[str, bytes]:
"""Get username and password hash from config or defaults"""
try:
from app.config.settings import ConfigManager
cfg = ConfigManager()
username = cfg.get('WebAuth', 'username', fallback=DEFAULT_USERNAME)
pw_hash = cfg.get('WebAuth', 'password_hash', fallback='')
if not pw_hash:
# First run: store default password hash
pw_hash = bcrypt.hashpw(DEFAULT_PASSWORD.encode(), bcrypt.gensalt()).decode()
try:
cfg.update('WebAuth', 'username', DEFAULT_USERNAME)
cfg.update('WebAuth', 'password_hash', pw_hash)
cfg.save_config()
except Exception:
pass
return username, pw_hash.encode()
except Exception:
return DEFAULT_USERNAME, bcrypt.hashpw(DEFAULT_PASSWORD.encode(), bcrypt.gensalt())
@router.post("/login", response_model=LoginResponse)
async def login(req: LoginRequest):
stored_username, stored_hash = _get_credentials()
if req.username != stored_username:
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="用户名或密码错误")
if not bcrypt.checkpw(req.password.encode(), stored_hash):
raise HTTPException(status_code=status.HTTP_401_UNAUTHORIZED, detail="用户名或密码错误")
token = create_access_token({"sub": req.username})
return LoginResponse(access_token=token)
@router.get("/me")
async def me(current_user: dict = Depends(get_current_user)):
return current_user
class ChangePasswordRequest(BaseModel):
old_password: str
new_password: str
@router.post("/change-password")
async def change_password(req: ChangePasswordRequest, current_user: dict = Depends(get_current_user)):
_, stored_hash = _get_credentials()
if not bcrypt.checkpw(req.old_password.encode(), stored_hash):
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail="旧密码错误")
new_hash = bcrypt.hashpw(req.new_password.encode(), bcrypt.gensalt()).decode()
try:
from app.config.settings import ConfigManager
cfg = ConfigManager()
cfg.update('WebAuth', 'password_hash', new_hash)
cfg.save_config()
except Exception as e:
raise HTTPException(status_code=500, detail=f"保存密码失败: {e}")
return {"message": "密码修改成功"}
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@@ -1,40 +0,0 @@
"""Web-specific configuration"""
import os
import secrets
# JWT
JWT_SECRET_KEY = os.getenv("JWT_SECRET_KEY", "")
JWT_ALGORITHM = "HS256"
JWT_EXPIRE_HOURS = 24
# File upload
MAX_UPLOAD_SIZE = 50 * 1024 * 1024 # 50MB
ALLOWED_IMAGE_EXTENSIONS = {'.jpg', '.jpeg', '.png', '.bmp'}
ALLOWED_EXCEL_EXTENSIONS = {'.xlsx', '.xls'}
ALLOWED_EXTENSIONS = ALLOWED_IMAGE_EXTENSIONS | ALLOWED_EXCEL_EXTENSIONS
# CORS
CORS_ORIGINS = os.getenv("CORS_ORIGINS", "*").split(",")
# Auth rate limit
LOGIN_RATE_LIMIT = 5 # per minute
def get_or_generate_secret() -> str:
"""Get JWT secret from env or auto-generate on first run"""
global JWT_SECRET_KEY
if not JWT_SECRET_KEY:
secret_file = os.path.join(
os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__)))),
'data', '.jwt_secret'
)
if os.path.exists(secret_file):
with open(secret_file, 'r') as f:
JWT_SECRET_KEY = f.read().strip()
if not JWT_SECRET_KEY:
JWT_SECRET_KEY = secrets.token_urlsafe(48)
os.makedirs(os.path.dirname(secret_file), exist_ok=True)
with open(secret_file, 'w') as f:
f.write(JWT_SECRET_KEY)
return JWT_SECRET_KEY
-112
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@@ -1,112 +0,0 @@
"""FastAPI application entry point for the web-based OCR order processing system."""
import sys
import os
from contextlib import asynccontextmanager
from pathlib import Path
# Ensure app/ is importable
_web_dir = Path(__file__).resolve().parent.parent # web/
_project_root = _web_dir.parent # project root
if str(_project_root) not in sys.path:
sys.path.insert(0, str(_project_root))
from fastapi import FastAPI
from fastapi.staticfiles import StaticFiles
from fastapi.responses import FileResponse
from .config import get_or_generate_secret # noqa: trigger secret generation
from .services.task_manager import TaskManager
from .services.db_pool import DBPool
from .auth.router import router as auth_router
from .routers.files import router as files_router
from .routers.processing import router as processing_router
from .routers.memory import router as memory_router
from .routers.config_api import router as config_router
from .routers.barcodes import router as barcodes_router
from .routers.sync import router as sync_router
from .routers.websocket import router as ws_router
from .routers.logs import router as logs_router
from .routers.tasks import router as tasks_router
from .middleware.logging import LoggingMiddleware
# Shared singletons
task_manager = TaskManager()
db_pool = DBPool()
@asynccontextmanager
async def lifespan(app: FastAPI):
"""Initialize shared resources on startup."""
from app.config.settings import ConfigManager
ConfigManager()
# Initialize DB and cleanup old records
from .services.db_schema import init_db, cleanup_old_records, sync_file_relations
init_db()
cleanup_old_records()
# Sync file relations from existing files
sync_file_relations()
# Wire up DB pool to task manager
task_manager.set_db_pool(db_pool)
app.state.task_manager = task_manager
app.state.db_pool = db_pool
yield
app = FastAPI(
title="益选 OCR 订单处理系统",
version="1.0.0",
lifespan=lifespan,
)
# CORS
from fastapi.middleware.cors import CORSMiddleware
app.add_middleware(
CORSMiddleware,
allow_origins=["http://localhost:5173", "http://127.0.0.1:5173", "http://localhost:8000"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
# HTTP logging middleware (after CORS, before routes)
app.add_middleware(LoggingMiddleware)
# Make task_manager and db_pool accessible via request.state
@app.middleware("http")
async def inject_services(request, call_next):
request.state.task_manager = task_manager
request.state.db_pool = db_pool
return await call_next(request)
# Mount routers
app.include_router(auth_router)
app.include_router(files_router)
app.include_router(processing_router)
app.include_router(memory_router)
app.include_router(config_router)
app.include_router(barcodes_router)
app.include_router(sync_router)
app.include_router(ws_router)
app.include_router(logs_router)
app.include_router(tasks_router)
# Serve Vue SPA static files
_static_dir = Path(__file__).resolve().parent / "static"
if _static_dir.is_dir():
app.mount("/assets", StaticFiles(directory=str(_static_dir / "assets")), name="assets")
@app.get("/{full_path:path}")
async def serve_spa(full_path: str):
"""Catch-all: serve index.html for Vue Router history mode."""
file_path = _static_dir / full_path
if file_path.is_file():
return FileResponse(str(file_path))
return FileResponse(str(_static_dir / "index.html"))
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"""HTTP request logging middleware."""
import asyncio
import logging
import time
from starlette.middleware.base import BaseHTTPMiddleware
from starlette.requests import Request
from starlette.responses import Response
logger = logging.getLogger(__name__)
# Paths that should not be logged
_SKIP_PREFIXES = ("/assets", "/ws")
_SKIP_PATHS = ("/favicon.ico",)
class LoggingMiddleware(BaseHTTPMiddleware):
"""Logs every HTTP request to the database via db_schema.insert_http_log.
- Skips static assets, WebSocket, and favicon paths.
- Measures request duration in milliseconds.
- Extracts username from request.state.user when available.
- Writes logs asynchronously (non-blocking).
- Never lets logging failures break a request.
"""
async def dispatch(self, request: Request, call_next) -> Response:
path = request.url.path
# Skip paths that should not be logged
if path in _SKIP_PATHS or any(path.startswith(p) for p in _SKIP_PREFIXES):
return await call_next(request)
start = time.perf_counter()
status_code = 500 # default if call_next raises
try:
response = await call_next(request)
status_code = response.status_code
return response
finally:
duration_ms = (time.perf_counter() - start) * 1000
method = request.method
user = getattr(request.state, "user", None)
ip = request.client.host if request.client else None
# Fire-and-forget: never block the response
asyncio.create_task(
self._write_log(method, path, status_code, duration_ms, user, ip)
)
@staticmethod
async def _write_log(
method: str,
path: str,
status_code: int,
duration_ms: float,
user: str | None,
ip: str | None,
) -> None:
"""Write the log entry in a thread executor to avoid blocking."""
try:
loop = asyncio.get_event_loop()
await loop.run_in_executor(
None,
lambda: _db_insert(method, path, status_code, duration_ms, user, ip),
)
except Exception:
# Logging must never break the request
logger.debug("Failed to write HTTP log", exc_info=True)
def _db_insert(
method: str,
path: str,
status_code: int,
duration_ms: float,
user: str | None,
ip: str | None,
) -> None:
"""Synchronous DB insert — called inside run_in_executor."""
try:
from web.backend.services.db_schema import insert_http_log
insert_http_log(
method=method,
path=path,
status_code=status_code,
duration_ms=duration_ms,
user=user,
ip=ip,
)
except Exception:
logger.debug("DB insert_http_log failed", exc_info=True)
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@@ -1,19 +0,0 @@
# Web backend dependencies
fastapi>=0.104.0
uvicorn[standard]>=0.24.0
python-jose[cryptography]>=3.3.0
bcrypt>=4.0.0
python-multipart>=0.0.6
httpx>=0.25.0
werkzeug>=3.0.0
# Core app dependencies (needed by processing endpoints)
pandas>=1.3.0
openpyxl>=3.0.0
xlrd>=2.0.0,<2.1.0
xlwt>=1.3.0
xlutils>=2.0.0
numpy>=1.19.0
requests>=2.25.0
python-dotenv>=1.0.0
configparser>=5.0.0
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@@ -1,178 +0,0 @@
"""Barcode mapping CRUD endpoints."""
import json
from pathlib import Path
from typing import Dict, Optional, List
from fastapi import APIRouter, HTTPException, Depends
from pydantic import BaseModel
from ..auth.dependencies import get_current_user
router = APIRouter(prefix="/api/barcodes", tags=["barcodes"])
_project_root = Path(__file__).resolve().parent.parent.parent.parent
_mappings_file = _project_root / "config" / "barcode_mappings.json"
class BarcodeMapping(BaseModel):
barcode: str
target: Optional[str] = None
description: Optional[str] = None
# Special rule fields
multiplier: Optional[int] = None
target_unit: Optional[str] = None
fixed_price: Optional[float] = None
specification: Optional[str] = None
class BarcodeMappingUpdate(BaseModel):
target: Optional[str] = None
description: Optional[str] = None
multiplier: Optional[int] = None
target_unit: Optional[str] = None
fixed_price: Optional[float] = None
specification: Optional[str] = None
def _load_mappings() -> Dict:
if not _mappings_file.is_file():
return {}
try:
return json.loads(_mappings_file.read_text(encoding="utf-8"))
except Exception:
return {}
def _save_mappings(data: Dict):
_mappings_file.parent.mkdir(parents=True, exist_ok=True)
_mappings_file.write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding="utf-8")
@router.get("")
async def list_barcodes(
search: str = "",
current_user: dict = Depends(get_current_user),
):
mappings = _load_mappings()
items = []
for barcode, info in mappings.items():
if isinstance(info, dict):
target = info.get("map_to", info.get("target", ""))
desc = info.get("description", "")
item = {
"barcode": barcode,
"target": target,
"description": desc,
"multiplier": info.get("multiplier"),
"target_unit": info.get("target_unit"),
"fixed_price": info.get("fixed_price"),
"specification": info.get("specification"),
}
else:
item = {
"barcode": barcode,
"target": str(info),
"description": "",
"multiplier": None,
"target_unit": None,
"fixed_price": None,
"specification": None,
}
s = search.lower() if search else ""
if s and s not in barcode.lower() and s not in item["target"].lower() and s not in (desc or "").lower():
continue
items.append(item)
return {"items": items, "total": len(items)}
@router.get("/{barcode}")
async def get_barcode(
barcode: str,
current_user: dict = Depends(get_current_user),
):
mappings = _load_mappings()
if barcode not in mappings:
raise HTTPException(404, f"未找到条码映射 {barcode}")
info = mappings[barcode]
if isinstance(info, dict):
return {"barcode": barcode, "target": info.get("map_to", info.get("target", "")), "description": info.get("description", "")}
return {"barcode": barcode, "target": str(info), "description": ""}
@router.post("")
async def create_barcode(
body: BarcodeMapping,
current_user: dict = Depends(get_current_user),
):
mappings = _load_mappings()
if body.barcode in mappings:
raise HTTPException(409, f"条码 {body.barcode} 已存在")
entry: dict = {"description": body.description or ""}
if body.multiplier:
entry["multiplier"] = body.multiplier
if body.target_unit:
entry["target_unit"] = body.target_unit
if body.fixed_price is not None:
entry["fixed_price"] = body.fixed_price
if body.specification:
entry["specification"] = body.specification
else:
entry["map_to"] = body.target or ""
mappings[body.barcode] = entry
_save_mappings(mappings)
return {"message": f"已创建规则 {body.barcode}"}
@router.put("/{barcode}")
async def update_barcode(
barcode: str,
body: BarcodeMappingUpdate,
current_user: dict = Depends(get_current_user),
):
mappings = _load_mappings()
if barcode not in mappings:
raise HTTPException(404, f"未找到条码规则 {barcode}")
existing = mappings[barcode]
if not isinstance(existing, dict):
existing = {"map_to": str(existing), "description": ""}
# Check if this is a special rule (has multiplier) or being converted to one
if body.multiplier is not None:
# Convert to special rule: remove map_to, add multiplier fields
existing.pop("map_to", None)
existing["multiplier"] = body.multiplier
if body.target_unit is not None:
existing["target_unit"] = body.target_unit
if body.fixed_price is not None:
existing["fixed_price"] = body.fixed_price
if body.specification is not None:
existing["specification"] = body.specification
elif body.target is not None:
# Convert to simple mapping: remove special fields, add map_to
for k in ("multiplier", "target_unit", "fixed_price", "specification"):
existing.pop(k, None)
existing["map_to"] = body.target
if body.description is not None:
existing["description"] = body.description
mappings[barcode] = existing
_save_mappings(mappings)
return {"message": f"已更新规则 {barcode}"}
@router.delete("/{barcode}")
async def delete_barcode(
barcode: str,
current_user: dict = Depends(get_current_user),
):
mappings = _load_mappings()
if barcode not in mappings:
raise HTTPException(404, f"未找到条码映射 {barcode}")
del mappings[barcode]
_save_mappings(mappings)
return {"message": f"已删除映射 {barcode}"}

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