ISSUE-052: Incomplete Bulk Import Functionality

[AliiiBenn]

ISSUE-052: Incomplete Bulk Import Functionality

Description

The bulk Excel import feature exists but is incomplete (approximately 50% done). This is critical for initial system setup with 50+ employees, as manual data entry would be impractical and error-prone.

Affected Files

• src/excel_import/excel_importer.py - Main import logic (partial)
• src/ui_ctk/views/import_view.py - Import UI (partial)
• src/excel_import/template_generator.py - Excel template generator

Current State

What Works:

• Basic Excel file reading
• Simple employee record creation
• Template file generation
• Basic UI for file selection

What's Missing:

1. Complete field mapping - Not all employee fields are imported
2. Contact information - Phone and email not imported (see ISSUE-051)
3. Relationship handling - CACES, medical visits, trainings not imported
4. Validation - Insufficient validation before import
5. Error handling - Poor error reporting and rollback
6. Progress tracking - No progress indication for large imports
7. Duplicate detection - No duplicate matricule detection
8. Batch processing - No transaction batching for performance

Expected Behavior

1. Complete Field Mapping

Import should support ALL employee fields:

• ✅ first_name
• ✅ last_name
• ✅ matricule
• ✅ position
• ✅ department
• ✅ status
• ✅ entry_date
• ❌ phone_number (missing - see ISSUE-051)
• ❌ email_address (missing - see ISSUE-051)
• ❌ CACES certifications (not implemented)
• ❌ Medical visits (not implemented)
• ❌ Trainings (not implemented)

2. Multi-Sheet Import

Excel file should have multiple sheets:

• Sheet 1: Employees - Basic employee information
• Sheet 2: CACES - Certification records
• Sheet 3: Medical - Medical visit records
• Sheet 4: Training - Training records

3. Validation

Pre-import validation should check:

• Required fields present
• Matricule uniqueness
• Valid email format
• Valid phone format
• Valid dates
• Valid status values
• Foreign key integrity (position, department)

4. Error Handling

• Collect all validation errors before import
• Show detailed error report
• Allow user to fix and retry
• Rollback on import failure
• Log all errors

5. Progress Tracking

For large datasets (50-100 employees):

• Show progress bar
• Display "Processing X of Y records"
• Show elapsed/estimated time
• Allow cancellation

6. Duplicate Detection

• Check for duplicate matricules
• Warn user of duplicates
• Allow: skip, update, or cancel

7. Transaction Management

• Use database transactions
• Batch inserts (10-20 records per transaction)
• Commit on success, rollback on failure
• Maintain data integrity

Proposed Solution

Phase 1: Complete Employee Import (2-3 days)

1.1 Add Missing Field Support

• Import phone_number (when ISSUE-051 is fixed)
• Import email_address (when ISSUE-051 is fixed)
• Map all fields correctly

1.2 Improve Validation

def validate_employee_row(row: dict) -> list[str]:
    """Validate employee row, return list of errors."""
    errors = []

    # Required fields
    if not row.get('first_name'):
        errors.append("First name is required")
    if not row.get('last_name'):
        errors.append("Last name is required")
    if not row.get('matricule'):
        errors.append("Matricule is required")

    # Unique matricule
    if Employee.select().where(Employee.matricule == row['matricule']).exists():
        errors.append(f"Matricule {row['matricule']} already exists")

    # Valid email format
    if row.get('email_address') and not validate_email(row['email_address']):
        errors.append(f"Invalid email format: {row['email_address']}")

    # Valid phone format
    if row.get('phone_number') and not validate_phone(row['phone_number']):
        errors.append(f"Invalid phone format: {row['phone_number']}")

    # Valid date
    try:
        parse_date(row['entry_date'])
    except:
        errors.append(f"Invalid entry date: {row['entry_date']}")

    return errors

1.3 Batch Processing

def import_employees_in_batches(employees: list[dict], batch_size=20):
    """Import employees in batches for performance."""
    total = len(employees)
    imported = 0
    errors = []

    with database.atomic():
        for i in range(0, total, batch_size):
            batch = employees[i:i + batch_size]

            for employee_data in batch:
                try:
                    Employee.create(**employee_data)
                    imported += 1
                    update_progress(imported, total)
                except Exception as e:
                    errors.append({
                        'employee': employee_data,
                        'error': str(e)
                    })

    return imported, errors

Phase 2: Multi-Sheet Import (2-3 days)

2.1 CACES Import

• Read CACES sheet
• Validate employee references
• Import CACES records
• Handle related employees

2.2 Medical Visits Import

• Read Medical sheet
• Validate employee references
• Import medical visit records
• Calculate next due dates

2.3 Training Import

• Read Training sheet
• Validate employee references
• Import training records
• Handle expiring certifications

Phase 3: Improve UI (2 days)

File: src/ui_ctk/views/import_view.py

Add:

• File preview with row count
• Validation results display
• Progress bar for import
• Error report with details
• Success/failure summary
• Retry capability

Phase 4: Template Generator (1 day)

File: src/excel_import/template_generator.py

Create comprehensive template with:

• All employee fields
• Example data
• Data validation rules
• Instructions sheet
• Dropdown lists for position, department, status

Dependencies

• ISSUE-051: Missing Contact Fields (phone, email)
• ISSUE-047: Missing Data Entry Forms (for manual fix capability)
• Validation utilities: ✅ Complete

Related Issues

• ISSUE-051: Missing Contact Information Fields
• ISSUE-047: Missing Data Entry Forms
• ISSUE-053: Incomplete Excel Export

Acceptance Criteria

• All employee fields import correctly
• Phone and email import (when ISSUE-051 fixed)
• CACES records import from separate sheet
• Medical visits import from separate sheet
• Training records import from separate sheet
• Validation catches all errors before import
• Duplicate matricules detected
• Progress bar shows import progress
• Transactions ensure data integrity
• Rollback works on failure
• Error report is detailed and helpful
• Template file includes all fields and examples
• Can import 50-100 employees in < 30 seconds
• All tests pass

Estimated Effort

Total: 5-7 days

• Complete employee import: 2-3 days
• Multi-sheet import: 2-3 days
• Improve UI: 2 days
• Template generator: 1 day

Notes

This is a critical feature for production deployment. Manual data entry for 50+ employees is not practical. The import feature must be robust, validated, and handle errors gracefully.

Use Cases

1. Initial System Setup - Import 50-100 existing employees
2. Bulk Updates - Import updated data from HR system
3. Migration from Legacy System - Migrate all employee data
4. Regular Updates - Weekly/monthly bulk updates

Performance Targets

• 50 employees: < 10 seconds
• 100 employees: < 20 seconds
• 500 employees: < 60 seconds
• 1000 employees: < 120 seconds

References

• openpyxl documentation: https://openpyxl.readthedocs.io/
• Excel file format best practices: https://www.ibm.com/docs/en/ssd_for_is?topic=formats-excel-file-format