GG.Deals Price Scraper

A web-based price lookup tool built for Steam game traders. Quickly check current best prices on gg.deals for bulk game lists — perfect for evaluating trade offers, pricing your inventory, or comparing your collection against a trader's list.

Whether you're buying, selling, or swapping Steam keys, this tool lets you paste a list of game names and instantly see the best available prices across all stores tracked by gg.deals.

Features

• Dual-tab interface — two independent tabs ("Trader Games" & "My Games") for managing separate game lists
• Parallel scraping — both tabs can scrape simultaneously with configurable worker counts
• Side-by-side comparison — compare results from both tabs to evaluate trade value at a glance
• Multi-worker scraping — configurable number of parallel browser instances per tab
• Real-time progress — live progress bar via Server-Sent Events
• Search & filter — filter results by price availability or match confidence
• Sort & export — sort by name/price, export to CSV or clipboard
• Delete individual results — remove specific games from the results
• Compare view tools — search and sort by price within the comparison view

Use Cases

• Evaluating trade offers — paste the trader's game list in one tab and your games in the other, then compare total values side-by-side
• Pricing your inventory — bulk-check current prices for all your tradeable Steam keys
• Finding deals — identify undervalued games in a trade offer by sorting by price

Getting Started

Prerequisite: Google Chrome must be installed.

Option 1: Download the .exe (Windows — no Python needed)

1. Download GG Deals Scraper.exe from the Releases page
2. Double-click the .exe — a console window opens and your browser launches automatically
3. Start scraping!

Option 2: Run from source

1. Make sure you have Python 3.10+ and Google Chrome installed
2. Set up the project:

   # Create virtual environment
   python -m venv venv
   
   # Activate it
   # Windows:
   venv\Scripts\activate
   # Linux/macOS:
   source venv/bin/activate
   
   # Install dependencies
   pip install -r requirements.txt

3. Run the app:

   python app.py

4. Open http://127.0.0.1:5000 in your browser

Option 3: Build the .exe yourself

1. Follow the setup steps from Option 2
2. Build:

   pip install pyinstaller
   pyinstaller --clean GG_Deals_Scraper.spec

   Or on Windows, just double-click build.bat.
3. The executable will be at dist/GG Deals Scraper.exe

Screenshot

Side-by-side comparison view after scraping both tabs and clicking "Compare Results Side-by-Side":

How to Use

1. Add games — type game names (one per line) or upload a .txt file in either tab:

   Frostpunk
   DOOM Eternal
   Borderlands 3
   Hollow Knight
   Celeste
   

2. Set workers — choose how many parallel browsers to run per tab (more = faster, but heavier on resources)
3. Start scraping — click "Start Scraping" on one or both tabs and watch the progress bars
4. View results — browse, search, filter, and export the scraped prices
5. Compare — when both tabs have results, click "Compare Results Side-by-Side" to see total values and search/sort within each column

Note: The scraper runs Chrome in visible mode because gg.deals blocks headless browsers. Running both tabs with 3+ workers each may strain system resources.

Project Structure

├── app.py                  # Flask web server & per-tab API endpoints
├── scraper.py              # Multi-threaded scraping logic (per-instance state)
├── templates/
│   └── index.html          # Frontend UI (dual-tab single-page app)
├── games.txt               # Default game list
├── requirements.txt        # Python dependencies
├── GG_Deals_Scraper.spec   # PyInstaller build config
├── build.bat               # One-click build script (Windows)
├── *_results.json          # Scraped results per tab (generated at runtime)
└── *_progress.json         # Scraping progress per tab (generated at runtime)

Tech Stack

• Backend: Flask, Selenium, undetected-chromedriver
• Frontend: Vanilla HTML/CSS/JS with a dark theme
• Scraping: Multi-threaded with per-instance browser workers