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Big Box Art - Order Processing & Image Automation System

Project Overview

A comprehensive desktop application I engineered from scratch for my print-on-demand business, Big Box Art, leveraging AI-assisted development and Python programming to eliminate manual workflows and achieve end-to-end order fulfillment automation. Processing hundreds of daily orders across multiple sales channels (eBay, Amazon, Amazon Prime, Wayfair) while coordinating with various print suppliers presented significant operational bottlenecks that I resolved through custom software development.

Utilizing AI collaboration and my Python expertise, I designed and implemented sophisticated data processing pipelines, intelligent caching mechanisms, and seamless external system integrations. The application ingests purchase order data from Order Desk, processes multi-channel orders, and generates supplier-ready files with embedded product images. This solution reduced order processing time from hours to minutes, eliminated data entry errors, and enabled business scaling without proportional labor cost increases—transforming a manual, time-intensive workflow into a single-click automated process.

Business
Impact

  • Reduced order processing time from hours to minutes

  • Eliminated manual data entry errors across multiple platforms

  • Automated image preparation for multiple print suppliers

  • Streamlined shipping label generation for hundreds of daily orders

  • Consolidated multi-item orders for accurate weight calculation and cost optimization

  • Enabled scalable operations without additional staff overhead

Key
Features

Intelligent Order Processing

  • Purchase order data import with automatic field mapping and validation

  • Automated CSV generation for multiple print suppliers and product categories

  • Smart sales channel detection with conditional logic for platform-specific requirements

  • Dynamic quantity expansion and print naming with multi-copy tracking

  • Multi-purchase discount tagging for eBay bulk orders (3+ items)

 

Image Automation Pipeline

  • Automated image downloading from Azure Blob Storage with SAS token authentication

  • Integration with Adobe Photoshop via AppleScript for batch processing

  • Dynamic filename generation with order tracking, sales channel codes, and print specifications

  • Automatic prefix removal post-processing for clean file organization

 

Shipping & Fulfillment Integration

  • Automated shipping label generation with weight calculation and address consolidation

  • Tracking number converter with one-click clipboard functionality for bulk shipment updates

  • Excel export with embedded product thumbnails using PIL image processing

  • Conditional address logic (label-provided vs. full address) based on fulfillment channel

 

Advanced Product Handling

  • Platform-specific SKU lookup system with multi-file caching architecture

  • Real-time postcode validation and data integrity checks

  • Support for 5 product categories across 4 sales channels

  • Intelligent supplier routing based on product type and order specifications

Technical
Stack

  • Development: Claude Sonnet 4.5 | ChatGPT o1

  • Language: Python 3.12

  • GUI Framework: PyQt6 with custom dark theme and tabbed interface

  • Data Processing: Pandas for CSV manipulation and data transformation

  • Image Processing: Pillow (PIL) for thumbnail generation

  • Excel Generation: openpyxl for embedded image support

  • External Integration: AppleScript automation for Photoshop

  • Cloud Storage: Azure Blob Storage with SAS token authentication

Technical
Highlights

  • Caching System: Intelligent multi-level caching for lookup files and product data to minimize I/O operations

  • Error Handling: Comprehensive logging with detailed error tracking and CSV export for failed operations

  • Memory Management: Temporary file lifecycle management for thumbnail processing

  • UI/UX: Progress tracking with real-time status updates and visual feedback

  • Data Validation: Weight calculation from lookup tables, SKU pattern matching, and address formatting

Deployment

  • Packaged using PyInstaller for standalone macOS application

  • Resource bundling for CSV lookup files and branding assets

  • Version-controlled configuration for supplier specifications

  • Dynamic Photoshop version detection for system compatibility

Technologies: Python | PyQt6 | Pandas | Pillow | openpyxl | AppleScript | Azure Storage | Claude 4.5 | ChatGPT 5

Type: Desktop Application | Business Automation | E-commerce Integration

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