Forem: Batuhan

Scraping Properties from RealEstate.com.AU w/ Python

Batuhan — Tue, 08 Jul 2025 23:53:57 +0000

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.
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.

2. 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.
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.

3. 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`

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 = "<your_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)

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

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"

Extracting the Property Name

RealEstate.com.au stores the listing title inside an <h1> 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)

BeautifulSoup finds the <h1> tag, extracts its text, and removes extra spaces. The output should look like this:

Listing Name: House with 898m² land size and 6 bedrooms

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 <span> 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)

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

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

Find the correct <li> 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 = "<your-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 <li> 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)

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

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

Best Scraping Tools For Amazon: How to Shake the Market

Batuhan — Sat, 15 Jan 2022 12:46:43 +0000

Selling an online product is such a challenging job due to its harshly competitive environment. The only way to survive in a monopolistically competitive market is to have good strategic moves against your competitor’s movers. Wouldn’t it be great if you built your strategy based on your rival’s available pieces of information and plans? Yes, it would be great, and it is a popular method.

Today, to find their place in the market, most firms scrape all the necessary information related to their rivals’, subsidiaries of their product, or products similar to their development. Innovative firms extract this information to understand their rival’s next move, whether to see if there is a market gap or an unserved customer segment. These data extracted from Amazon via Amazon scrapers could be highly profitable if a firm detects an unserved part for several product types.

By the way, see more about US proxies for eCommerce, without wasting time!

Besides market penetration, firms also do scrape Amazon to see their place in the market. Competent firms position themselves uniquely compared to their rivals to gain a competitive advantage by the differentiation method. They could use web scraping tools to scrape the Amazon database to gain insight related to their opponents. With such information, a firm can decide the optimal price for their product or how they can improve their value proposition by focusing on the rough edges of competitor product lines.

There are many advantages of data extracted from Amazon as it contains all the necessary publicly available data of competitors. All you need to do is harvest all these data, eliminate the unrelated information, analyze the remaining data on the hand, and gain awareness about the environment of the market.

Today, we are here to share a detailed guide about how you can scrape valuable data from Amazon’s data and other details you may need to know. Without further ado, let’s get started!

Why Is Scraping Amazon Data Important?

You know there are some essential factors when you experience the selling process of an item on the Internet. As it is already mentioned in the article, selling online products is in a perfectly competitive market. And, this market is the lion’s den. You need to keep the analysis of competitor’s as recent as possible. Besides, you need to keep enhancing your product’s features so that your competitors can not overthrow your features. And, again, be constantly aware and do not miss any market trends and macro environmental factors that affect the specific market you are operating in.

You need to determine if your firms position in the market space. So, you can get valuable information, and then you can compare this information with your strategies, and keep monitoring your rivals’ moves so that you can always be up-to-date and never miss any news related to the market. You can do all of these with the help of web scraping tools that are specialized in scraping the data on Amazon. A firm could also use Amazon scraping means to have proper cost management planning and find the best possible time to offer deals to their potential customers.

Using the vast data buried under Amazon’s database, you will benefit from the gained insights from all of this valuable information. And you can have this helpful information by doing all these actions manually, finding your competitors pages on Amazon, scanning thousands of products related to your firm’s products, and reading tons of reviews to understand customers’ wishes and complaints. And controversially, all these actions could be executed via an Amazon scraping tool, which is the most outstanding advantage of these tools. It eliminates human error risk and provides all the time in the world, which could be wasted in doing all of these steps manually so that you can save your time and energy for the core parts of your project.

Best Scraping Tools For Amazon Data

You can use web scraping tools designed to scrape data from Amazon to not have to worry about the coding part of the steps. Mainly because the scraping tools in the market are designed very professionally, and they are pretty successful at what they are supposed to do. Here, we will give short reviews about some good web scraping tools services and their Amazon-specified scraping products.

Scrape.do

Scrape.do offer robust web scraping tools so that you cant start harvesting any HTML, XML, JSON data from a website you targeted. The plans also include a rotating proxy integrated with the web scraping tools so that the users use the web scraping tools provided by Scrape.Do do not have to worry about any restrictions related to IP address bans or geo-restrictions. Scrape.Do’s web scraping tools keep their IP address different for a time period, so it reduces the risk of bans to nearly 0 percent.

In addition to these, it is designed to save you from the overuse of RAM and CPU, thanks to its more brilliant data gathering process. With this more competent method, your computer spends less RAM and CPU when conducting the scraping steps.

Scrape.do aims to save time for its users with its reliable, super-fast, newly innovated data scraping technology so that they can spend their saved time on the more vital parts of the project. Its rotating IP address enables its web scraping tools to surf the Internet freely, without struggling with geo-block restrictions or CAPTCHAs. So all these make Scrape.do’s scraping services one of the best in the market.

BrightData

BrightData’s BrightData Amazon Collector aims to eliminate the glass ceiling effect for the scraping era, as it removes the necessity of coding skills to scrape the web. The Amazon Collector by BrightData is one of the best web scraping tools explicitly designed to harvest the data of Amazon as it has been detected nor banned yet so, which means that BrightData’s Amazon Collector seems to be a reliable source to scrape information on Amazon.

The scraping tool offers excellent services, including scraping product features, scanning offers of products, and checking any newly introduced product so that you always can be up to date.

In addition to this, you can also scrape customer reviews about some particular product and rating of that product after contacting BrightData and asking for a custom collector who has more advanced customization options. You would be able to adjust settings to meet your project’s objectives.

Octoparse

Octoparse’s web scraping tool is a cloud-based tool specially designed to extract data from Amazon. Octoparse also offers an installable version of the same application, which comes with the same features.

Octoparse’s user-friendly design provides their customer with convenience, and it makes Octoparse one of the best and most preferred web scraping tools providers in the market. You can focus on the data from Amazon, as Octoparse is also providing many templates ready to use, whichever you want to work with for the requirements of your project.

Octoparse decides to differentiate itself with its mission to provide its customer with user-friendly templates, interfaces, and tutorials. Having a software with brilliant pattern detection abilities also helps Octoparse create more value for their customers to get value from them in return.

Octoparse has a free trial version of its web scraping tool. It might be logical to try on a basic project first, in order to decide to buy the full version or not.

Apify

Apify is a web scraping tool specialized in Amazon’s data, and its aim is to provide what the official API of Amazon can not provide for the users. Apify’s Amazon Scraper harvest and download data, including detailed descriptions of online products, images of the items, prices, pictures, the name of the seller, condition of the article, whether they are new, refurbished, or broken, and all other information related to the product.

The web scraping tool of Apify for Amazon scraping can filter its research options by keywords so that you can specify the critical factors in your search. Besides all, Apify also provides a proxy service that is optimized for web scraping applications. So the users of Apify’s Amazon Crawler can enjoy a rapid and reliable web scraping experience.