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How to Build a Labubu Bot with Residential Proxies: Step-by-Step Guide

Getting your hands on limited-edition Labubu figures like The Monsters, Big Into Energy, or Labubu Exciting Macaron has gotten absolutely wild lately. Once Pop Mart announced that they would no longer sell these figures in physical stores, the online shop got some serious traffic. But we're also talking about these Pop Mart drops selling out in literal seconds – forget about trying to cop manually, you'll never make it past the cart page. And thousands of users complain that they can’t cop a mystery box for themselves. Luckily, there’s an automated solution that’ll help you to get at least a couple of Labubus. The trusty bot, tuned with residential proxies, will handle CAPTCHAs, geo-blocks, and IP bans, helping you reach the checkout page as quickly as possible. This guide breaks down all the tactics that actually work, straight from people who've been crushing these drops consistently.

Zilvinas Tamulis

Jul 09, 2025

9 min read

What is Labubu?

Labubu is this mischievous little character created by artist Kasing Lung. Picture sharp little teeth, big expressive eyes, and this quirky personality that's somehow both adorable and slightly unsettling, that's Labubu in a nutshell. Many collectors believe Labubu has an edge that sets it apart from everything else in Kasing Lung's collection.

The whole thing started with The Monsters series back in 2015. However, it gained viral popularity only in 2019 when toy company Pop Mart introduced it as collectible blind-box toys. And in 2025, collectors can even customize their Labubu figures with custom outfits and accessories from the world’s biggest brands.

But here's the thing – Labubu isn't just another toy. It has become a whole cultural phenomenon that combines art and collecting in one. The hype around new drops is real, and it's basically become the poster child for the entire designer toy scene.

When will Labubu restock?

Labubu restocks on Pop Mart are highly anticipated and often sell out within minutes. While Pop Mart doesn’t publish an official restock schedule, the collector communities on Reddit have identified consistent patterns based on repeated drops and shared experiences.

Restocks typically happen several times a week, especially between Tuesday and Thursday, with occasional drops on Sundays. Pop Mart restocks are most common in the evening for U.S. users, which translates to early morning or late-night restocks for international fans.

Here’s a table of the most common restock times by region:

Region

Approx. restock time

Notes

USA (Pacific)

7:00PM – 10:00PM PT

Most common window (Monday to Saturday)

USA (Eastern)

10:00PM – 1:00AM ET

Matches West Coast drop times

Europe (CET)

4:00AM – 7:00AM CET

Early morning drops

Asia (HKT/SGT)

10:00AM – 1:00PM HKT/SGT

Mid-morning drops, often the next day after the U.S. drop

Pop Mart releases can vary slightly from day to day, sometimes happening 10 to 15 minutes before or after the expected time. Because of this, collectors recommend refreshing the site or app early and frequently around the restock window.

To increase your chances, use the Notify Me option on Pop Mart’s product pages, which alerts you as soon as an item becomes available. Additionally, joining online communities like Reddit’s r/labubu, TikTok collector pages, or Discord groups can give you real-time alerts when drops go live.

While there's no guaranteed way to predict a specific restock, tracking patterns and being prepared during the hours above will maximize your chances of grabbing the Labubu figure you’re hunting for.

Why use a bot and proxies for Labubu?

Using a bot and residential proxies can improve your chances of securing limited-edition Labubu figures from Pop Mart, especially during high-demand drops that sell out in seconds. A bot automates the buying process, refreshing pages, adding items to the cart, and pushing you straight to the checkout page.

Basically, residential proxies make it look like you're just a regular person shopping from different spots around the world. This keeps you from getting IP banned, dodges CAPTCHAs, gets around location blocks, and stops you from getting shut down right when you're about to check out.

Together, bots and proxies give collectors a competitive edge in beating the rush and resellers, especially for rare releases that often disappear within moments.

What you’ll need to get a Labubu

To get your hands on a Labubu figure, especially during limited Pop Mart drops, you'll need to set up a few key things:

  • Python (latest version) – you’ll use this to run the automation script.
  • Playwright – a browser automation tool that helps your script interact with the Pop Mart website, just like a real user.
  • Chrome or Firefox browser + driver – needed for Playwright to control the browser. Ensure the driver is compatible with your browser version.
  • Residential proxies – help you avoid IP bans by rotating your IP and mimicking a real user's behavior.
  • Pop Mart account(s) – you’ll need at least one active account to log in and complete the purchase; having more accounts increases your chances.

How to build a Labubu bot

To set yourself up for success, you’ll need a foolproof bot that automates the Labubu purchasing process.

Step #1 – set up your environment

To get started, install the Python programming language with the required libraries:

  • Install Python. Get the latest version of Python from the downloads page. During installation, ensure that you add it to your system's PATH for easy script execution.
  • Get Playwright. To install Playwright, you'll need to run a pip command in your terminal, followed by another command that installs the required browser binaries:
pip install playwright
python -m playwright install
  • Grab a scheduler. You'll want to write a script that performs specific actions at a defined time, so you'll need a way to schedule your jobs. APScheduler is a great option here:
pip install apscheduler

Step #2 – create a project directory

You'll need to create a new folder for your project to store the script and result files. It's also a great idea to keep your project isolated with a virtual environment. Navigate to the folder inside your terminal:

cd path/to/your/project

The bot will consist of several files. You can create them all now, or do it as you follow along. For visual clarity, here's the project structure:

popmart-bot (folder)
- data (folder)
- products.json
- job-scheduler.py
- main.py
- popmart-scraper.py
- purchase-bot.py

Step #3 – write the main script

To begin, you'll need to create an entry point for your bot. Create a main.py file and write the following code:

import subprocess
import time
from apscheduler.schedulers.blocking import BlockingScheduler
from datetime import datetime, timedelta
# Maximum number of retries for scraper
MAX_RETRIES = 5
RETRY_DELAY = 10
# Scheduled time for daily scraper run
HOUR = 6
MINUTE = 0
scheduler = BlockingScheduler()
def run_daily_scraper():
    # This function runs the popmart-scraper.py script and schedules job-scheduler.py to run shortly after.
    print(f"\nRunning popmart-scraper at {datetime.now().strftime('%H:%M:%S')}")
    for attempt in range(1, MAX_RETRIES + 1):
        print(f"Attempt {attempt} to run scraper...")
        try:
            subprocess.run(["python3", "popmart-scraper.py"], check=True)
            print("New arrival scraper launched successfully.")
            
            # Schedule job-scheduler to run shortly after
            run_time = datetime.now() + timedelta(seconds=5)
            scheduler.add_job(run_job_scheduler, trigger='date', run_date=run_time)
            print(f"The job-scheduler.py will run at {run_time.strftime('%H:%M:%S')}")
            return  # Exit early on success
        except subprocess.CalledProcessError as e:
            print(f"Scraper failed (attempt {attempt}) with exit code {e.returncode}")
            if attempt < MAX_RETRIES:
                print(f"Retrying in {RETRY_DELAY} seconds...")
                time.sleep(RETRY_DELAY)
    print("All attempts to run the scraper failed. Check popmart-scraper.py for issues.")
def run_job_scheduler():
    print(f"\nRunning job-scheduler.py")
    try:
        subprocess.run(["python3", "job-scheduler.py"], check=True)
    except subprocess.CalledProcessError as e:
        print(f"Job scheduler failed with exit code {e.returncode}")
        print("Please check job-scheduler.py for issues.")
if __name__ == "__main__":
    print("main.py started...")
    run_daily_scraper()  # run once immediately on startup
    # Schedule scraper to run daily at configured time
    scheduler.add_job(run_daily_scraper, 'cron', hour=HOUR, minute=MINUTE)
    print(f"Daily scraper has been scheduled to run at {HOUR:02d}:{MINUTE:02d} every day.")
    
    try:
        scheduler.start()
    except (KeyboardInterrupt, SystemExit):
        scheduler.shutdown()
        print("Scheduler stopped.")

What this does:

  • Runs the web scraper. The script executes popmart-scraper.py as soon as main.py is launched.
  • Schedules automatic job processing. After the scraper runs successfully, it automatically schedules job-scheduler.py to process the scraped data.
  • Implements retry logic. If the popmart-scraper.py script fails, it waits 10 seconds between each retry attempt, attempting up to 5 times before giving up.
  • Sets up daily scraping. The script schedules popmart-scraper.py to run automatically every day at a set time using a cron-style scheduler.

Step #4 – scrape the New Arrivals page

Following the process of the main.py file, the first thing that will run is the popmart-scraper.py script. Here's what's inside it:

import asyncio
import json
import os
from playwright.async_api import async_playwright
import sys
TARGET_KEYWORDS = ["THE MONSTERS", "Labubu"]
BASE_URL = "https://www.popmart.com"
OUTPUT_FILE = os.path.join("data", "products.json")
# Proxy config (replace with your credentials)
PROXY_SERVER = "http://us.decodo.com:10001"
PROXY_USERNAME = "username"
PROXY_PASSWORD = "password"
async def scrape_popmart():
    print("New arrivals scraping started...")
    try:
        async with async_playwright() as p:
            browser = await p.chromium.launch(
                headless=True,
                proxy={"server": PROXY_SERVER}
                )
            
            context = await browser.new_context(
                proxy={
                    "server": PROXY_SERVER,
                    "username": PROXY_USERNAME,
                    "password": PROXY_PASSWORD
                }
            )
            page = await context.new_page()
            await page.goto("https://www.popmart.com/us/new-arrivals", timeout=30000)
            await page.wait_for_selector("div.index_title__jgc2z")
            # Try to close location popup if present
            try:
                await page.wait_for_selector("div.index_siteCountry___tWaj", timeout=15000)
                popup_selector = "div.index_siteCountry___tWaj"
                # Wait briefly (2 seconds) for popup to appear without failing if it doesn't
                await page.wait_for_selector(popup_selector, timeout=2000)
                await page.click(popup_selector)
                print("Closed location pop-up.")
            except Exception:
                # Popup not present -- continue normally
                print("No location pop-up detected.")
            # Close policy acceptance pop-up if present (after country pop-up)
            try:
                policy_selector = "div.policy_acceptBtn__ZNU71"
                # Wait until it's visible
                await page.wait_for_selector(policy_selector, timeout=8000, state="visible")
                # Get the element
                policy_btn = await page.query_selector(policy_selector)
                if policy_btn:
                    await asyncio.sleep(1)  # slight buffer for JS readiness
                    await policy_btn.click()
                    print("Clicked policy ACCEPT div.")
                else:
                    print("Could not find the policy ACCEPT div.")
            except Exception as e:
                print(f"Policy ACCEPT pop-up not detected or failed to click: {e}")
            results = []
            sections = await page.query_selector_all("div.index_title__jgc2z")
            for section in sections:
                release_date = (await section.text_content()).strip()
                # Get sibling product list container
                sibling = await section.evaluate_handle("el => el.nextElementSibling")
                product_cards = await sibling.query_selector_all("div.index_productCardCalendarContainer__B96oH")
                for card in product_cards:
                    # Product title
                    title_elem = await card.query_selector("div.index_title__9DEwH span")
                    title = await title_elem.text_content() if title_elem else ""
                    if not any(keyword.lower() in title.lower() for keyword in TARGET_KEYWORDS):
                        continue
                    # Release time
                    time_elem = await card.query_selector("div.index_time__EyE6b")
                    time_text = await time_elem.text_content() if time_elem else "N/A"
                    # Product URL
                    a_elem = await card.query_selector("a[href^='/us']")
                    href = await a_elem.get_attribute("href") if a_elem else None
                    full_url = f"{BASE_URL}{href}" if href else "N/A"
                    # Build entry
                    result = {
                        "title": title.strip(),
                        "release_date": release_date.strip(),  # Raw text like "Upcoming JUL 11"
                        "release_time": time_text.strip(),     # Raw text like "09:00"
                        "url": full_url
                    }
                    results.append(result)
            await browser.close()
            # Save to JSON
            os.makedirs("data", exist_ok=True)
            with open(OUTPUT_FILE, "w", encoding="utf-8") as f:
                json.dump(results, f, indent=2, ensure_ascii=False)
            print(f"Scraped {len(results)} matching products. Saved to {OUTPUT_FILE}")
    except Exception as e:
        print(f"Error during scraping: {e}")
        sys.exit(1)  # Exit with error code 1 on failure
if __name__ == "__main__":
    asyncio.run(scrape_popmart())

The code simply navigates to the New Arrivals page and retrieves information on when products are scheduled for release. It then saves the product names, release date, time, and URLs to the data/products.json file. In addition, it also:

  • Handles website popups and navigation. The script automatically detects and closes location selection and policy acceptance pop-ups.
  • Uses a proxy server for web requests. All browser traffic is routed through a specified proxy server with authentication credentials, allowing it to bypass restrictions or rate limiting. In this example, Decodo's residential proxies are utilized, which reliably evade detection and provide a secure method for scraping the website.
  • Filters products by keywords. The script only collects data for products whose titles contain "THE MONSTERS" or "Labubu", ignoring all other items on the new arrivals page.

Step #5 – set up a job scheduler

The job-scheduler.py script is the key component in setting up automated jobs:

import json
from datetime import datetime
from apscheduler.schedulers.background import BackgroundScheduler
import subprocess
import os
import time
DATA_FILE = os.path.join("data", "products.json")
MAX_RETRIES = 5
RETRY_DELAY = 10
def parse_release_datetime(date_str, time_str):
    # Convert strings like "Upcoming JUL 11" and "09:00" into a datetime object. Assumes the current year.
    try:
        # Remove unwanted keywords
        for keyword in ["Upcoming", "In Stock"]:
            date_str = date_str.replace(keyword, "").strip()
        
        full_date_str = f"{date_str} {datetime.now().year} {time_str}"
        # Example: "JUL 11 2025 09:00"
        return datetime.strptime(full_date_str, "%b %d %Y %H:%M")
    except Exception as e:
        print(f"Failed to parse datetime from '{date_str} {time_str}': {e}")
        return None
def launch_purchase_bot(product):
    # Launch purchase-bot.py with retry logic
    url = product.get("url")
    title = product.get("title")
    
    for attempt in range(MAX_RETRIES + 1):  # +1 for initial attempt
        print(f"Launching purchase bot for '{title}' (attempt {attempt + 1}/{MAX_RETRIES + 1}) at {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}")
        
        try:
            # Run the purchase bot and wait for it to complete
            result = subprocess.run(
                ["python3", "purchase-bot.py", url],
                capture_output=True,
                text=True,
                timeout=300  # 5 minute timeout
            )
            
            if result.returncode == 0:
                print(f"✅ Purchase bot succeeded for '{title}' on attempt {attempt + 1}")
                return  # Success - exit the retry loop
            else:
                print(f"Purchase bot failed for '{title}' on attempt {attempt + 1}")
                print(f"Return code: {result.returncode}")
                print(f"STDOUT: {result.stdout}")
                print(f"STDERR: {result.stderr}")
                
        except subprocess.TimeoutExpired:
            print(f"⏰ Purchase bot timed out for '{title}' on attempt {attempt + 1}")
        except Exception as e:
            print(f"💥 Exception running purchase bot for '{title}' on attempt {attempt + 1}: {e}")
        
        # If this wasn't the last attempt, wait before retrying
        if attempt < MAX_RETRIES:
            print(f"⏳ Waiting {RETRY_DELAY} seconds before retry...")
            time.sleep(RETRY_DELAY)
    
    print(f"All {MAX_RETRIES + 1} attempts failed for '{title}'.")
def schedule_all_jobs_from_json(json_path):
    scheduler = BackgroundScheduler()
    job_count = 0
    with open(json_path, "r", encoding="utf-8") as f:
        products = json.load(f)
    for product in products:
        run_time = parse_release_datetime(product["release_date"], product["release_time"])
        if not run_time:
            continue
        if run_time < datetime.now():
            continue
        
        scheduler.add_job(launch_purchase_bot, "date", run_date=run_time, args=[product])
        print(f"🧸 Scheduled '{product['title']}' for {run_time}")
        job_count += 1
    if job_count == 0:
        print("No upcoming valid jobs found in JSON. Nothing scheduled.")
        return
    scheduler.start()
    print("Scheduler started. Jobs will run at their scheduled times.")
    try:
        # Keep the scheduler alive
        while True:
            pass
    except (KeyboardInterrupt, SystemExit):
        scheduler.shutdown()
        print("Scheduler stopped.")
if __name__ == "__main__":
    schedule_all_jobs_from_json(DATA_FILE)

The script gets data from the products.json file, parses the data, and sets up a schedule to run a bot at the time of releases.

Step #6 – automate the purchase

The final piece of code is the script that does the most important thing – gets your Labubu in your shopping cart.

import sys
import asyncio
from playwright.async_api import async_playwright
# Proxy config (replace with your credentials)
PROXY_SERVER = "http://us.decodo.com:10001"
PROXY_USERNAME = "username"
PROXY_PASSWORD = "password"
async def run(url):
    try:
        async with async_playwright() as p:
            browser = await p.chromium.launch(
                headless=False, # Visible browser for purchase
                proxy={"server": PROXY_SERVER}
                ) 
            context = await browser.new_context( # Create a new incognito context
                proxy={
                    "server": PROXY_SERVER,
                    "username": PROXY_USERNAME,
                    "password": PROXY_PASSWORD
                }
            )  
            page = await browser.new_page()
            await page.goto(url)
            # Try to close location popup if present
            try:
                await page.wait_for_selector("div.index_siteCountry___tWaj", timeout=15000)
                popup_selector = "div.index_siteCountry___tWaj"
                # Wait briefly (2 seconds) for popup to appear without failing if it doesn't
                await page.wait_for_selector(popup_selector, timeout=2000)
                await page.click(popup_selector)
                print("Closed location pop-up.")
            except Exception:
                # Popup not present -- continue normally
                print("No location pop-up detected.")
            # Close policy acceptance pop-up if present (after country pop-up)
            try:
                policy_selector = "div.policy_acceptBtn__ZNU71"
                # Wait until it's visible
                await page.wait_for_selector(policy_selector, timeout=8000, state="visible")
                # Get the element
                policy_btn = await page.query_selector(policy_selector)
                if policy_btn:
                    await asyncio.sleep(1)  # slight buffer for JS readiness
                    await policy_btn.click()
                    print("Clicked policy ACCEPT div.")
                else:
                    print("Could not find the policy ACCEPT div.")
            except Exception as e:
                print(f"Policy ACCEPT pop-up not detected or failed to click: {e}")
            
            # Wait for ADD TO BAG button and click it
            add_to_bag_selector = "div.index_usBtn__2KlEx.index_red__kx6Ql.index_btnFull__F7k90"
            
            # Wait and click button safely
            try:
                await page.wait_for_selector(add_to_bag_selector, timeout=15000)  # 15 seconds timeout
                await page.click(add_to_bag_selector)
                print("Clicked 'ADD TO BAG' button.")
            except Exception as e:
                print(f"Failed to find or click 'ADD TO BAG' button: {e}")
                await browser.close()
                return 1  # Return error code
            
            await asyncio.sleep(3)  # Give it time to process
            # Go to the shopping cart page
            try:
                await page.goto("https://www.popmart.com/us/largeShoppingCart")
                print("Navigated to shopping cart.")
                # Click the checkbox to select all items
                await page.click("div.index_checkbox__w_166")
                # Keep the browser open to allow manual checkout
                print("Browser will stay open for manual checkout. Close it when done.")
                #await asyncio.Future()  # Keeps script running indefinitely until manually closed
                await page.wait_for_event("close", timeout=0)  # Wait until user closes the visible browser tab
            except Exception as e:
                print(f"Failed during checkout preparation: {e}")
                return 1  # Return error code
            finally:
                await context.close() # Clean up incognito session
                await browser.close() # Fully shut down Playwright
            
            return 0  # Success
            
    except Exception as e:
        print(f"Fatal error in purchase bot: {e}")
        return 1  # Return error code
if __name__ == "__main__":
    if len(sys.argv) < 2:
        print("Usage: python3 purchase-bot.py <product_url>")
        sys.exit(1)
    
    product_url = sys.argv[1]
    exit_code = asyncio.run(run(product_url))
    sys.exit(exit_code)

The script navigates to all of the product URLs at the time of release, clicks the ADD TO BAG button, then navigates to the shopping cart. The browser window remains open, allowing you to log in and complete the purchase!

Step #7 – launch the code

To launch the Pop Mart scraper bot, simply run the main.py file from your terminal:

python main.py

That's all you need to do to get that limited edition Labubu! Here's a full breakdown of how it works:

  1. The script scrapes the New Arrivals page, retrieves the product names, links, release dates, and release times, and saves them to a JSON file. It will then repeat the process daily.
  2. A job scheduler runs immediately after, checking the JSON file and creating scheduled tasks to run at product release times.
  3. At release time, the bot will navigate to the specified URLs and automate the purchase process up to the checkout stage.

Best practices for botting Labubu drops

To increase your chances of getting that Labubu collectible, keep these tips on your side:

  • Use a unique proxy per account – assign a different proxy to each browser profile or bot instance.
  • Rotate proxies – for bulk operations, rotate your IP address after each checkout attempt.
  • Randomize actions – add small delays and random mouse movements to mimic human behavior.
  • Monitor for errors – if a checkout fails, switch proxies and attempt the checkout again.
  • Test before drop – run your bot on non-peak products to ensure everything works smoothly.

Bottom line

Securing limited-edition Labubu figures has evolved from a casual hobby to a competitive digital sprint where milliseconds matter. While manual purchasing remains nearly impossible for high-demand drops, this automated approach levels the playing field for genuine collectors. The combination of Python automation, Playwright browser control, and residential proxies creates a robust system that handles the technical challenges, from bypassing geo-restrictions to managing CAPTCHAs.

Success ultimately depends on proper preparation – reliable residential proxies, thorough testing, and understanding that even the best-configured bot can't guarantee success in a market where demand consistently outstrips supply.

Now it's time to set up your Labubu bot and secure that blind box once again!

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About the author

Zilvinas Tamulis

Technical Copywriter

A technical writer with over 4 years of experience, Žilvinas blends his studies in Multimedia & Computer Design with practical expertise in creating user manuals, guides, and technical documentation. His work includes developing web projects used by hundreds daily, drawing from hands-on experience with JavaScript, PHP, and Python.


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All information on Decodo Blog is provided on an as is basis and for informational purposes only. We make no representation and disclaim all liability with respect to your use of any information contained on Decodo Blog or any third-party websites that may belinked therein.

Frequently asked questions

How much does Labubu cost?

Labubu blind-box figures typically retail for $20 to $30 through Pop Mart, depending on the series. Prices for sets, plush pendants, or special editions can range from $40 to over $80.


On the resale market, popular or rare figures often sell for $30 to $100, while limited or collaboration editions can fetch hundreds or even thousands of dollars. Ultra-rare or life-size Labubu collectibles have been known to sell for over $150K at auction. Overall, pricing varies widely based on rarity, series, and condition.

What is a Labubu bot?

The Labubu bot is a specialized automation tool designed to assist users in purchasing collectible Labubu figures. It automates the process until the checkout process on limited-edition drops, increasing the chances of successfully securing a figure before it sells out.

Which sites does the Labubu bot support?

Labubu bots primarily support purchasing from Pop Mart's official website, which is the main platform for new Labubu figure releases. However, with just a few tweaks, these bots can also support a wide range of other retailers, such as Amazon, Walmart, Target, and various Shopify-based stores, providing users with broader opportunities to secure limited-edition Labubu collectibles.

Do I need coding skills to use Labubu bot?

No, you don’t need coding skills to use a Labubu bot. Using our step-by-step guide automation features, you can set it up and purchase Labubu figures with just a few clicks.


While there are advanced features users can leverage, like custom scripts or proxy management, the experience is designed to be plug-and-play for most users.

Can I purchase the Popmart bot?

You can find Popmart bots for purchase on platforms like Fiverr and other marketplaces, but these third-party bots are often unreliable and poorly constructed. They frequently fail to complete purchases successfully, lack essential features like proxy integration for avoiding detection, and may not work with current website updates.

Many users report wasted money on bots that don't deliver the promised functionality or stop working after brief periods. For better results and reliability, it's recommended to build your own bot or use established botting communities where you can get proper support and updates.

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