Блог о программировании: методика обхода защиты RealEstate.com.au с использованием Scrape.do для надежного скрапинга данных.

Disclaimer: This post scrapes publicly available data from RealEstate.com.AU without violating Digital Services Act signed by EU and UK or Copyright Act of 1968, Computer Crimes Act of 1995 and Privacy Act of 1988 in the Australia. There is no large-scale collection of data from the website or no scraping behind login, purely crafted for test purposes.

RealEstate.com.au is Australia's biggest real estate platform, listing thousands of properties every day.

Maybe you want to track property prices, analyze trends, or collect property details. But if you've tried scraping the site, you've probably run into blocks.

Like many big platforms, RealEstate.com.au uses Cloudflare and advanced bot detection to stop automated access.

But don't worry, we'll get through it together.

In this guide, we'll break down why scraping RealEstate.com.au is difficult and how to bypass it using Scrape.do, so you can extract property data without headaches.

Why Scraping RealEstate.com.au is Challenging

Scraping a real estate platform sounds simple. Just send a request, get the data, and move on. But the moment you try it, you hit a wall.

RealEstate.com.au doesn't just let scrapers walk in. It actively detects and blocks bots with Cloudflare Enterprise, rate limits, and JavaScript-based content loading. Here's why it's difficult:

1. Cloudflare Enterprise Protection

Cloudflare's job is to separate humans from bots, and it's very good at it.

Every request gets checked to see if it's coming from a real browser or a script.

or a script. If your request doesn't execute JavaScript like a normal user, you'll get blocked.

It even monitors mouse movements and scrolling behavior to detect automation.

1. IP Tracking and Rate Limits

If you think rotating proxies will help, think again.

RealEstate.com.au tracks IPs aggressively , flagging requests from data centers.

, flagging requests from data centers. If you send too many requests too fast, your IP gets banned.

Even using multiple proxies won't work unless they mimic human browsing behavior.

1. JavaScript-Rendered Content

Not all the data loads when the page first opens.

Some parts of the page (like price history and dynamic filters) only appear after JavaScript runs.

A simple requests.get() won't see the full page, leaving you with missing or incomplete data.

So, what's the solution? You need a way to bypass Cloudflare, handle session tracking, and load JavaScript properly without getting blocked.

How Scrape.do Bypasses These Blocks

Instead of fighting against Cloudflare, Scrape.do does all the heavy lifting for you.

With Scrape.do, your scraper doesn't look like a bot—it looks like a real person browsing the site.

✅ Cloudflare Bypass – Handles JavaScript challenges and bot detection automatically.

✅ Real Residential IPs – Routes requests through Australia-based IPs so you aren't flagged as a bot.

✅ Session Handling – Manages cookies and headers just like a real browser.

✅ Dynamic Request Optimization – Mimics real user behavior to avoid detection.

With these, you can scrape RealEstate.com.au without getting blocked, no complicated workarounds needed.

Now, let's send our first request and see if we get access. 🚀

Extracting Data from RealEstate.com.au Without Getting Blocked

Now that we know how to bypass RealEstate.com.au's protections, we'll extract the property name, price, and square meters from a real estate listing.

Prerequisites

Before making any requests, install the required dependencies:

pip install requests beautifulsoup4 Enter fullscreen mode Exit fullscreen mode

You'll also need an API key from Scrape.do, which you can get by signing up for free.

For this guide, we'll scrape the following RealEstate.com.au listing:

House in Tamworth, NSW

Sending a Request and Verifying Access

First, we'll send a request through Scrape.do to ensure we can access the page without getting blocked.

import requests import urllib.parse # Our token provided by Scrape.do token = " " # Target RealEstate listing URL target_url = urllib . parse . quote_plus ( " https://www.realestate.com.au/property-house-nsw-tamworth-145889224 " ) # Optional parameters geo_code = " au " superproxy = " true " # Scrape.do API endpoint url = f " https://api.scrape.do/?token= { token } &url= { target_url } &super= { superproxy } " # Send the request response = requests . request ( " GET " , url ) # Print response status print ( " Response Status: " , response . status_code ) Enter fullscreen mode Exit fullscreen mode

This request routes through Scrape.do's Australian proxies, ensuring it looks like a normal user browsing the site. If everything works, you should see:

Response Status : 200 Enter fullscreen mode Exit fullscreen mode

If you see 403 Forbidden or a Cloudflare error, RealEstate.com.au is blocking your request. In that case, add JavaScript rendering by tweaking the URL:

url = f " https://api.scrape.do/?token= { token } &url= { target_url } &super= { superproxy } &render=true " Enter fullscreen mode Exit fullscreen mode

Extracting the Property Name

RealEstate.com.au stores the listing title inside an

tag, making it one of the easiest elements to extract.

from bs4 import BeautifulSoup <----- Previous section until the Print command -----> # Parse the response using BeautifulSoup soup = BeautifulSoup ( response . text , " html.parser " ) # Extract listing name listing_name = soup . find ( " h1 " ). text . strip () print ( " Listing Name: " , listing_name ) Enter fullscreen mode Exit fullscreen mode

BeautifulSoup finds the

tag, extracts its text, and removes extra spaces. The output should look like this:

Listing Name : House with 898m² land size and 6 bedrooms Enter fullscreen mode Exit fullscreen mode

Now that we have the property title, let's move on to extracting the price.

Extracting the Sale Price

The property price is stored inside a tag with the class "property-price property-info__price" . Instead of pulling all the text, we'll extract only the price value.

<----- Previous section until the Print command -----> # Extract sale price price = soup . find ( " span " , class_ = " property-price property-info__price " ). text . strip () print ( " Listing Name: " , listing_name ) print ( " Sale Price: " , price ) Enter fullscreen mode Exit fullscreen mode

This ensures we grab only the price and clean up any unnecessary spaces.

The output should look like this:

Listing Name : House with 898m² land size and 6 bedrooms Sale Price : $969,000 Enter fullscreen mode Exit fullscreen mode

Now that we have the property name and price, let's extract the square meters.

Extracting the Square Meters

The square meter value is not in a simple tag—it's inside a

element within "property-info__header" , along with other property details. To ensure we extract only the land size, we:

Find the correct

tag using its aria-label . Use regex ( re.search ) to extract only the number before "m²" .

With the code for the square meter section added, the final code should look like this:

from bs4 import BeautifulSoup import requests import urllib.parse import re # Our token provided by Scrape.do token = " " # Target RealEstate listing URL target_url = urllib . parse . quote_plus ( " https://www.realestate.com.au/property-house-nsw-tamworth-145889224 " ) # Optional parameters geo_code = " au " superproxy = " true " # Scrape.do API endpoint url = f " https://api.scrape.do/?token= { token } &url= { target_url } &super= { superproxy } " # Send the request response = requests . request ( " GET " , url ) # Parse the response using BeautifulSoup soup = BeautifulSoup ( response . text , " html.parser " ) # Extract listing name listing_name = soup . find ( " h1 " ). text . strip () # Extract sale price price = soup . find ( " span " , class_ = " property-price property-info_price " ). text . strip () # Extract square meters # First locate the correct

tag inside property-info

_header square_meters_element = soup . find ( " li " , attrs = { " aria-label " : re . compile ( r " \d+\s*m² " )}) # Then extract text and filter out only the number before "m²" square_meters = re . search ( r " (\d+)\s*m² " , square_meters_element . text ). group ( 1 ) # Print extracted data print ( " Listing Name: " , listing_name ) print ( " Sale Price: " , price ) print ( " Square Meters: " , square_meters ) Enter fullscreen mode Exit fullscreen mode

Instead of pulling everything inside "property-info__header" , this approach finds the specific square meter value and removes any extra text.

And here's the output you'll get:

Listing Name : House with 898m² land size and 6 bedrooms Sale Price : $969,000 Square Meters : 898 Enter fullscreen mode Exit fullscreen mode

Good job, you just scraped realestate.com.au!

Conclusion

Scraping RealEstate.com.au is tough due to Cloudflare protection, session tracking, and JavaScript-rendered content, but with Scrape.do, we extracted:

✅ Property Name

✅ Sale Price

✅ Square Meters

Programming Blog: A method for bypassing RealEstate.com.au's protection using Scrape.do for reliable data scraping.

Powerful blocking bypass! Facing Cloudflare hurdles and aggressive IP tracking?

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Блог о программировании: методика обхода защиты RealEstate.com.au с использованием Scrape.do для надежного скрапинга данных.

Мощный обход блокировок! Столкнулись с преградами Cloudflare и агрессивным трекингом IP?

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