Scraping Allegro: How to Extract Product Data Easily

Allegro is Poland’s largest e-commerce platform, serving over 20 million users and listing millions of products across various categories.

Unlike Amazon or eBay, Allegro primarily operates as an online marketplace for third-party sellers, making it a goldmine for pricing, availability, and customer review data.

But scraping Allegro? Not so simple.

Like many large e-commerce sites, Allegro actively prevents bots from accessing its data. Traditional scraping methods don’t work—but with the right tools, you can extract product details efficiently.

Why Scraping Allegro Is Challenging

Scraping Allegro isn’t impossible, but it requires a proper setup. Unlike some marketplaces that allow basic requests, Allegro enforces strict anti-bot measures to block scrapers.

Residential IP Requirement

One of the biggest challenges with scraping Allegro is that it blocks non-residential IPs almost instantly.

Datacenter proxies don’t work – Allegro detects and blocks requests from datacenter proxies or cloud providers like AWS or Google Cloud.
Frequent requests trigger blocks – Too many requests in a short period will get your scraper flagged.

To avoid this, you must use residential proxies—which mimic real users browsing from Poland.

Allegro’s Web Application Firewall (WAF)

Allegro employs a custom Web Application Firewall (WAF) that adds an extra layer of protection:

It detects and blocks unusual browsing patterns.
It enforces geo-restrictions—you must use a Polish IP to access product data.
It injects bot-detection mechanisms that disrupt automation tools.

JavaScript-Rendered Pages

Most product details—like price and ratings—aren’t present in the initial HTML response.

Allegro loads key product data dynamically using JavaScript, meaning simple requests.get() calls won’t fetch the information that you see as a real user.

How Scrape.do Solves These Challenges

Instead of dealing with residential IPs, JavaScript rendering, and WAF bypassing manually, Scrape.do handles it for you:

✅ Residential Proxy Support – Scrape.do routes your requests through a Polish residential proxy pool, ensuring access.
✅ Automatic WAF Bypass – Scrape.do manages cookies and headers dynamically, preventing detection.
✅ JavaScript Rendering When Needed – Scrape.do can render pages when necessary, but in this case, we can extract data directly from the source without extra processing.

With Scrape.do, you don’t need to manage proxies, headers, or session handling. Just send a request and extract the data with ease.

Scraping Product Data from Allegro

To scrape Allegro, we need consistent access and structured data extraction. Scrape.do ensures we avoid blocks by using Polish residential IPs and handling cookies automatically.

Now, let’s first get a response and then extract product details.

Prerequisites

Install dependencies if you haven’t already:

pip install requests beautifulsoup4

For this article, we’ll be targeting this product listing for a MacBook Air M2:

Click to view full-size image

Getting Access

Allegro requires Polish IPs, and requests from outside Poland will fail. We configure Scrape.do to:

Use Polish proxies (geoCode=pl)
Bypass bot detection (super=true)

Here’s how we send a request:

from bs4 import BeautifulSoup
import requests
import urllib.parse

# Scrape.do API Token
token = "your_token"

# Allegro Product URL
target_url = urllib.parse.quote_plus("https://allegro.pl/oferta/macbook-air-m2-13-6-16gb-256gb-space-gray-16784193631")

# Scrape.do Parameters
render = "false"  # JavaScript rendering not needed
geo_code = "pl"  # Ensures access to the Polish site
super_mode = "true"  # Enables residential proxies

# API Endpoint
url = f"http://api.scrape.do/?token={token}&url={target_url}&render={render}&geoCode={geo_code}&super={super_mode}"

# Send Request
response = requests.get(url)

# Parse HTML
soup = BeautifulSoup(response.text, "html.parser")

# Print response status to verify access
print("Response Status:", response.status_code)

And here’s our expected output:

Response Status: 200

Now that we have access, let’s start extracting data.

Extracting Product Name

The product name is inside an <h1> tag.

You’ve already gotten the response in the previous section, so with a simple modification to the code its simple to get the product name:

# Extract Product Name
product_name = soup.find("h1").text.strip()

print("Product Name:", product_name)

Extracting Price and Rating

Allegro structures prices inside a meta tag, while ratings are stored in a span with data-testid="aggregateRatingValue" (for this guide, I’m parsing the review score from the bottom of the page rather than directly on the top of the page, because it was easier to parse and gives the same data.).

You can extract them like this:

# Extract Product Price
product_price = soup.find("meta", attrs={"itemprop": "price"})["content"]

# Extract Product Rating
product_rating = soup.find("span", attrs={"data-testid": "aggregateRatingValue"}).text.strip()

print("Product Price:", product_price)
print("Product Rating:", product_rating)

Full Code

Here’s everything combined into one final working script:

from bs4 import BeautifulSoup
import requests
import urllib.parse

# Scrape.do API Token
token = "your_token"

# Allegro Product URL
target_url = urllib.parse.quote_plus("https://allegro.pl/oferta/macbook-air-m2-13-6-16gb-256gb-space-gray-16784193631")

# Scrape.do Parameters
render = "false"
geo_code = "pl"
super_mode = "true"

# API Endpoint
url = f"http://api.scrape.do/?token={token}&url={target_url}&render={render}&geoCode={geo_code}&super={super_mode}"

# Send Request
response = requests.get(url)
soup = BeautifulSoup(response.text, "html.parser")

# Extract Data
product_name = soup.find("h1").text.strip()
product_price = soup.find("meta", attrs={"itemprop": "price"})["content"]
product_rating = soup.find("span", attrs={"data-testid": "aggregateRatingValue"}).text.strip()

# Print Results
print("Product Name:", product_name)
print("Product Price:", product_price)
print("Product Rating:", product_rating)

Once you replace API key with your token and run the code, this is the output you’ll get if all previous steps were followed correctly:

Product Name: MacBook Air M2 13.6" 16GB 256GB Space Gray
Product Price: 4649.00
Product Rating: 4.98

Congratulations! You’re now able to scrape Allegro :)

Conclusion

With Scrape.do handling IP rotation and session management, we bypass Allegro’s restrictions and extract product details without blocks.

This method is fast, scalable, and works without JavaScript rendering.

Need to scrape Allegro at scale? Scrape.do makes it easy:

✅ Bypasses IP blocks with Polish proxies

✅ Handles cookies and sessions automatically

✅ Extracts structured product data efficiently

Get 1000 free API calls and start scraping today.