Realtor Scraper 2022: How to Scrape Real Estate Websites for Property Data with Python

Are you looking for ways to scrape real estate data from real estate websites? Realtor scrapers can help you do that and we would be recommending some of them in the article below. We would also show you how to develop a custom one as a programmer using Python.

Best Realtor Scrapers

The real estate industry is one of the most profitable in the market provided you know what you are doing. However, knowing what you are doing means taking the guesswork out of the way and using data in your decision-making processes and the Internet is one of the largest sources of real estate data as there are many real estate listing websites available.

With the right data at your disposal, you can not only make an informed decision but also predict the market and make sure you can guess rightly, what the future hold. When it comes to collecting data from real estate websites, it is impractical to manually collect data from many properties.

You will need to do that in an automated manner with the help of web scrapers. In this article, we would be providing you recommendations on some of the best web scrapers in the market that you can use to scrape real estate websites such as Realtor. We would also be providing a guide on how you can develop your own custom web scraper if you have coding knowledge. Before going into that proper, let take a look at what scraping realtor sites entails.


Realtor Scraping – an Overview

Realtor Scraping Overview

The term realtor scraping is a coined term that describes the process of using computer bots known as web scrapers or more specifically realtor scrapers to automatically extract data from real estate listing websites such as Realtor and Zillow. Some of the data that can be collected from a property from these sites includes name, address, year of built, price, amenities, and many other publicly available data.

Because bots do the extraction of data, many requests can be sent within a short period of time, making it possible to quickly extract data across millions of web pages in a short period of time – a time impossible for humans. This can potentially hurt the website you are extracting data from if its server is low-powered and that is why it is advisable to follow best practices and avoid overwhelming servers with too many requests.

Zillow Homepage

Because of the negative effects, web scrapers can have their own real estate websites and theft that the process is seen as data theft, real estate websites do not support the use of web scrapers. To keep web scrapers away, their anti-spam systems are configured to detect bot traffic and keep them away. Fortunately for us, real estate websites are not as effective as the big e-commerce and social media platforms at detecting web scrapers, and as such, we can easily bypass their anti-spam system using various techniques such as using rotating proxies to hide IP footprints, tweaking user agent to mimic popular browsers, and setting delays between requests, among others. If you are using an already-made scraper, the only measure you might need to implement is proxies.


How to Scrape Real Estate Websites Using Python

Scrape Real Estate Websites Using Python

If you have coding skills and want to develop a custom realtor scraper, then this section has been written for you. Else, I will advise you to move to the next section where we recommend some of the best web scrapers in the market that can be used for scraping property listing websites.  There is no specific programming language required for coding realtor scrapers.

All you need is a full programming language that provides you with an HTTP client for sending web requests and a library for parsing out required data.  For the article, we would be using Python as it is the most beginner-friendly language out there and there are many web scraping libraries and frameworks available.

The real estate niche has a good number of websites in each with each having its own peculiarities. This means that you can’t use the same library for scraping all of the real estate websites. If a website does not require Javascript to render completely, then you can use the duo of Requests and Beautifulsoup. Requests is for sending HTTP requests to download a web page while Beautifulsoup I for traversing the HTML of the downloaded page to extract data o interest. Requests do not render Javascript and as such, if a page requires Javascript, you will need to use Selenium, a web browser automator.

YouTube video

One thing you need to know is that realtor websites do not support web scraping and as such, scraping them wouldn’t be possible except you hide the fact that you are using a web scraper. They easily identify web scrapers because of the unnatural amount of requests that originate from them within a short period of time.

To hide your web scraper footprint, you will need to use proxies.

Residential proxies from Bright Data and Smartproxy are some of the best for hiding IP footprints.

Other measures to make sure you are not discovered include setting the user-agent header to mimic popular web browsers, setting delays between requests, and randomizing the content of the referer header.

  • Sample Code for Scraping Real Estate Data

The code below is a sample code for scraping Zillow, one of the popular real estate websites. What the code does is that it scrape the list of properties listed for rent for specific cities. Zillow property listing pages render without Javascript. For this reason, we would be using the duo of Requests and Beautifulsoup. It is important you know that the script is a basic scraper and does not handle exceptions or integrate anti-detection techniques to avoid block

import requests

from bs4 import BeautifulSoup


class ZillowScraper:

   def __init__(self):

      self.url = "https://www.zillow.com/homes/for_sale/Los-Angeles-CA_rb/?fromHomePage=true&shouldFireSellPageImplicitClaimGA=false&fromHomePageTab=buy"

      self.properties = []

   def scrape_properties(self):

       headers = {

           'accept':

'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8',

           'accept-encoding': 'gzip, deflate, br',

           'accept-language': 'en-US,en;q=0.8',

           'upgrade-insecure-requests': '1',

           'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/61.0.3163.100 Safari/537.36'

        }

       content = requests.get(self.url, headers=headers)

       soup = BeautifulSoup(content.text, "html.parser")

       properties = soup.find("ul", {"class": "photo-cards photo-cards_wow photo-cards_short"}).find_all("li")

       for e in properties:

           price = e.find("article").find("div", {"class": "list-card-price"}).text

           address = e.find("article").find("div", {"class": "list-card-addr"}).text

           self.properties.append([price, address])

           print(self.properties)

x = ZillowScraper()

x.scrape_properties()

Best Realtor Scrapers

Scraping real estate websites is not only limited to those that can code or afford to pay coders — thanks to already-made web scrapers that require no coding knowledge to use. There are a good number of these web scrapers in the market that you can use. Some of them are free while others come with a price tag. In this section of the article, we would recommend 5 of the best realtor scrapers you can use to scrape property data from real estate websites.


Apify Web Scrapers

Apify Logo

  • Pricing: Starts at $49 per month for 100 Actor compute units
  • Free Trials: Starter plan comes with 10 Actor compute units
  • Data Output Format: JSON
  • Supported OS: cloud-based – accessed via API

apify web scraper

If you are a NodeJS developer and do not want to develop a custom realtor scraper, then you can utilize the Apify platform for scraping real estate websites. Apify is an automation and web data extraction platform that has support for scraping real estate websites.

Some of the web scrapers known as actors by Apify that you can use for property listing scraping include Zillow Real Estate Scraper, Realtor.com Scraper, and Trulia Scraper, among others. You can search the Apify store for the specific target property website and if there’s no web scraper for it, you can request for it and it would be created for you. You can also use the Apify SDK to develop a custom property scraper and rent it out on Apify.


Octoparse

Octoparse

  • Pricing: Starts at $75 per month
  • Free Trials: 14 days of free trial with limitations
  • Data Output Format: CSV, Excel, JSON, MySQL, SQLServer
  • Supported Platform: Cloud, Desktop 

Octoparse Best Scrapers

Octoparse is one of the best web scrapers out there available to non-coders. You can use it for scraping property websites for real estate data really quickly. Using Octoparse, you can convert property data across the pages of property listing into a spreadsheet with just a few clicks.

The tool provides an easy-to-use point and click interface for selecting the data you want to scrape on a trained page and then you can use such to extract data on multiple other pages with the same elements. Octoparse isn’t developed only for scraping real estate websites, you can use it for scraping other websites as well. The tool is not free but new users are provided a 14 day free trial before being required to make payment.


ScrapeStorm

Scrapestorm Logo

  • Pricing: Starts at $49.99 per month
  • Free Trials: Starter plan is free – comes with limitations
  • Data Output Format: TXT, CSV, Excel, JSON, MySQL, Google Sheets, etc.
  • Supported Platforms: Desktop, Cloud

ScrapeStorm Homepage

The ScrapeStorm tool is one of the best web scrapers you can use to scrape property data from real estate websites such as Realtor and Zillow. This web scraper has not been developed specifically for this purpose. It is a generic web scraper that is built for all kinds of websites. ScrapeStorm is powered by an AI and has an intelligent data detection that automatically identifies data of interest on a page.

It also comes with an intelligent pattern detection that highlights similar elements and you go about identifying data of interest using the point and click interface. For this bot, all you need to prevent blocks are proxies and I will advise you to buy residential proxies from either Bright Data or Smartproxy as their proxies are some of the best in the market.


WebHarvy

Webharvy Logo

  • Pricing: Starts at $139 for a single user license
  • Free Trials: Not available
  • Data Output Format: TXT, CSV, Excel, JSON, XML. TSV, etc.
  • Supported Platforms: Desktop

WebHarvy Best Scrapers

WebHarvy is another generic web scraper for scraping property websites for real estate data. WebHarvy is incredibly easy to use and you can get started within a few minutes. Just like ScrapeStorm, you will need to add proxies to avoid getting blocked.

WebHarvy does not only extract data, it also handles web automation tasks such as logging in, form submission, and other repetitive tasks. The tool has got support for intelligent pattern detection, could scrape multiple pages with data trained for only a page, search forms, and have support for either saving extracted data into files or database systems. This web scraper can also render Javascript, scrape property images, and allow you to apply Regular Expression.


ParseHub

Parsehub Logo

  • Pricing: Free with a paid plan
  • Free Trials: Free – advance features come at an extra cost
  • Data Output Format: Excel, JSON,
  • Supported Platform: Cloud, Desktop

Parsehub Homepage

If you do not have a budget for a web scraper for real estate websites then you can make use of the ParseHub web scraper. This web scraping is marketed as a free web scraping tool that you can use to scrape any website on the Internet. It is built for the modern web and as such, it can be used for scraping heavily Ajaxified web pages.

With only a few steps, you can start scraping details of properties listed on property websites and even generate leads you could convert into customers using this tool. There is an article on the ParseHub blog that highlights the process to follow to scrape real estate data using this tool. While the free ParseHub works, the true power of ParseHub is unleashed when you opt-in for their paid plan.


Conclusion

From the above, you can see that there are a good number of realtor scrapers available that you can use even without coding skills. It is important I state here again that all of the web scrapers described above require residential proxies to hide your IP footprint.

Without proxies, you will get blocked after a few requests. If you do not have any high-quality provider in mind, we suggest you buy from Bright Data or Smartproxy as their proxies are some of the best and have proven to work well for scraping real estate websites.


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