Labubu Bot - Automated Collectible Purchase Tool

Introduction

The Labubu Bot is a specialized automation tool designed to help collectors secure limited-edition Labubu figures from Pop Mart during high-demand drops that sell out in seconds.

Built with Python and Playwright, this bot automatically monitors new arrivals, schedules purchase attempts, and handles the entire buying process up to checkout - giving you a competitive edge against resellers and manual buyers in the collectible toy market.

Features

• Automated product monitoring. Continuously scrapes Pop Mart's New Arrivals page for Labubu and THE MONSTERS series releases.
• Intelligent job scheduling. Automatically schedules purchase attempts based on official release times and dates.
• Residential proxy integration. Built-in proxy rotation support to avoid IP bans and bypass geo-restrictions.
• Anti-detection mechanisms. Handles CAPTCHAs, pop-ups, and mimics human browsing behavior to evade bot detection.
• Retry logic & error handling. Robust error recovery with configurable retry attempts and delay intervals.

Installation

Prerequisites

• Python 3.8+
• Chrome or Firefox browser
• Playwright
• APScheduler

Step-by-step setup

1. Clone the repository

git clone https://github.com/yourusername/labubu-bot.git
cd labubu-bot

2. Install dependencies

pip install playwright apscheduler
python -m playwright install

3. Configure proxy settings Edit the proxy credentials in both popmart-scraper.py and purchase-bot.py:

PROXY_SERVER = "http://us.decodo.com:10001"
PROXY_USERNAME = "your_username"
PROXY_PASSWORD = "your_password"

Usage examples

Basic CLI usage

Launch the complete automation system:

python main.py

Programmatic uzage

Run individual components:

# Run the web scraper manually
python popmart-scraper.py

# Process scheduled jobs
python job-scheduler.py

# Execute purchase bot for specific URL
python purchase-bot.py "https://www.popmart.com/us/products/product-name"

Sample output

The scraper generates a data/products.json file with upcoming releases:

[
  {
    "title": "Labubu THE MONSTERS Series",
    "release_date": "Upcoming JUL 25",
    "release_time": "21:00",
    "url": "https://www.popmart.com/us/products/labubu-the-monsters-series"
  }
]

Project structure

popmart-bot/
├── data/
│   └── products.json          # Scraped product data and release schedules
├── main.py                    # Main entry point and daily scheduler
├── popmart-scraper.py         # Web scraper for New Arrivals page
├── job-scheduler.py           # Automated job scheduling system
├── purchase-bot.py            # Purchase automation and cart management
└── README.md                  # Project documentation

Configuration

Proxy settings

For optimal performance, configure residential proxies in both scraper files. Replace PROXY_SERVER, PROXY_USERNAME, and PROXY_PASSWORD with your credentials from the Decodo dashboard.

Scheduling options

Modify timing in main.py:

HOUR = 6      # Daily scraper run hour (24h format)
MINUTE = 0    # Daily scraper run minute

Target keywords

Customize product filtering in popmart-scraper.py:

TARGET_KEYWORDS = ["THE MONSTERS", "Labubu", "Add product name"]

Best practices

• Use unique proxies. Assign different residential IPs to each browser session.
• Test before major drops. Run the bot on regular products to verify functionality.
• Multiple payment methods. Have backup payment options configured in Pop Mart accounts.
• Check release patterns. Pop Mart typically drops between 7-10 PM PT on weekdays.

Documentation links

For advanced proxy configuration and troubleshooting:

• Proxy setup guide
• Proxy code integration

License

This project is licensed under the MIT License.

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