🎵 Discogs Data Processor GUI Project 💿

A powerful desktop application for efficiently managing Discogs data dumps. Download, extract, convert to CSV, and create custom cover arts via a modern interface.

✨ Key Features

• 🚀 Multi-threaded Downloads (8 threads)
• 📦 Smart .gz Extraction
• 🔄 Efficient XML → CSV conversion
• 📊 Real-time Progress (speed, ETA)
• 🎨 Dark Themed Modern UI
• 📝 Detailed Logging (color-coded)
• 💾 Custom Download Location
• 🖼️ Cover Art Generator
• ⚙️ Auto Mode (Download → Extract → Convert)

🖼️ Preview

🚀 Getting Started

Prerequisites

• Python 3.7+
• ttkbootstrap, pandas, requests

Installation

git clone https://github.com/ofurkancoban/discogs-data-processor.git
cd discogs-data-processor
pip install -r requirements.txt
python main.py

📖 How to Use

Setup

• Click Settings to choose a download folder (default: ~/Downloads/Discogs)

Main Operations

1️⃣ Fetch Data: auto on startup or use Fetch
2️⃣ Download: select files & click Download
3️⃣ Extract: convert .gz to .xml
4️⃣ Convert: convert .xml to .csv
5️⃣ Cover Art: image + year/month → output
6️⃣ Manage Files: delete, status, disk size

⚙️ Auto Mode

• Enable Auto Mode
• Select rows → click Download
• Automatically runs: Download → Extract → Convert
• Perfect for batch automation!

📁 Folder Structure

Discogs/
├── Datasets/
│   ├── YYYY-MM/
│   │   ├── discogs_YYYY-MM-DD_type.xml.gz
│   │   ├── discogs_YYYY-MM-DD_type.xml
│   │   └── discogs_YYYY-MM-DD_type.csv
│   └── ...
├── Cover Arts/
└── discogs_data.csv
└── discogs_data.log

🔍 Technical Details

Download Process

• Multi-threaded downloading (8 threads)
• Automatic fallback to single-thread
• Built-in retry mechanism
• Real-time progress tracking

XML Processing

• Memory-efficient streaming parser
• Two-pass conversion:
  1. Column discovery
  2. Data extraction
• Chunking for large files

Logging System

• Timestamp-based logging
• Color-coded messages
• Both UI and file logging
• Detailed operation tracking

🛠️ Tech Stack

• Python 3.7+
• ttkbootstrap (UI)
• pandas, requests

👤 Author

Furkan Coban

• LinkedIn: ofurkancoban
• GitHub: ofurkancoban
• Kaggle: ofurkancoban

🙏 Thanks To

• Discogs (Data dumps)
• ttkbootstrap (UI framework)
• Icons8 (Icons)

📞 Support

• Check logs inside the app
• Open an issue on GitHub
• Reach out on LinkedIn

Made with ❤️ by ofurkancoban