9db298c027
Replace pandas+openpyxl with exceljs for Excel file processing. This migration enables seamless integration with the Electron main process and maintains 1:1 functional parity with the Python implementation. Key changes: - Add exceljs dependency (v4.4.0) - Implement ExcelConverter class in TypeScript with strict types - Add comprehensive unit tests (13 test cases, all passing) - Support field name mapping, order parsing, and material extraction - Handle empty data tables and file conflicts gracefully Verification: - Successfully tested with sample Excel file (99 orders, 625 records) - All unit tests passing - Output format matches Python version Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
107 lines
3.7 KiB
Markdown
107 lines
3.7 KiB
Markdown
# ExcelConverter Migration Summary
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## Task Completed: ExcelConverter Migration from Python to TypeScript
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Successfully migrated `playwrite/utils/excel_converter.py` to `src/main/utils/excelConverter.ts`.
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## Files Created/Modified
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### 1. ✅ `src/main/utils/excelConverter.ts` - Main Converter Class
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- Replaced `pandas` + `openpyxl` with `exceljs`
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- Preserved all parsing logic and data transformation
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- Implemented strict TypeScript types and interfaces
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- Followed project patterns matching `authService.ts`
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### 2. ✅ `tests/unit/excelConverter.test.ts` - Unit Tests
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- 13 comprehensive unit tests covering:
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- Header row parsing logic
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- Field name mapping
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- Material extraction
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- Empty data handling
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- Multiple orders parsing
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- Footer information handling
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- Data conversion to records
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- File output handling
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- All tests passing ✅
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### 3. ✅ `package.json` - Dependency Added
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- Added `exceljs`: ^4.4.0
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## Implementation Details
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### Core Methods Implemented
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| Python Method | TypeScript Method | Purpose |
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|--------------|-------------------|---------|
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| `convert(input_file, output_file)` | `async convert(inputPath: string, options?: ConverterOptions): Promise<ConverterResult>` | Main conversion entry |
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| `_parse_sheet(ws)` | `private parseSheet(worksheet: Worksheet): OrderData[]` | Parse worksheet into orders |
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| `_parse_header_row(row, info)` | `private parseHeaderRow(row: any[], info: Record<string, string>): void` | Extract field-value pairs |
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| `_convert_to_dataframe(orders)` | `private convertToRecords(orders: OrderData[]): MaterialRow[]` | Flatten to array |
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| `_handle_output_file(path)` | `private handleOutputFile(path: string): string` | Handle file conflicts |
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### Key Features
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1. **Field Name Mapping** - Resolves field name conflicts (计划数量 → 产品计划数量)
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2. **Order Parsing** - Extracts order info and materials from complex Excel layouts
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3. **Empty Data Handling** - Correctly handles orders with no material data
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4. **Footer Information** - Captures 制单人/打印人 information
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5. **File Conflict Handling** - Handles locked files by appending "_new" suffix
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## Verification
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### Unit Tests
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```bash
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npm test -- tests/unit/excelConverter.test.ts
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```
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**Result**: ✅ 13/13 tests passing
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### Manual Testing
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Tested with actual sample file `references/samples/离散备料计划数据样例.xlsx`:
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- **Orders processed**: 99
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- **Records extracted**: 625
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- **Output**: Successfully converted to Excel format
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## Success Criteria
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1. ✅ All tests pass (13/13 unit tests)
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2. ✅ Output matches Python version (verified with sample data)
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3. ✅ Code follows project conventions (matches `authService.ts` pattern)
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4. ✅ Proper TypeScript types with strict interfaces
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5. ✅ Proper error handling and logging (verbose mode)
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## Technical Notes
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### Excel Cell Reading Pattern
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```typescript
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// ExcelJS row.values[0] is undefined, actual data starts at index 1
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const cellValue = row.values[1]; // First column of actual data
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```
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### Row Iteration
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```typescript
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const allRows: any[][] = [];
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worksheet.eachRow((row, rowNumber) => {
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allRows.push(row.values as any[]);
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});
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```
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### Field Parsing Logic
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The header rows contain field-value pairs separated by "：" (colon). The parser correctly handles:
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- Field names with colons
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- Empty cells between field names and values
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- Multiple field-value pairs per row
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## Integration Points
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The ExcelConverter can now be used in:
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- Main process services for Excel file processing
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- Batch conversion workflows
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- Data import/export functionality
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## Next Steps
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The ExcelConverter is ready for integration into the main application workflow. It can be called from:
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- IPC handlers for renderer process requests
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- Background data processing tasks
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- File system watchers for automatic conversion
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