{"id":6381,"date":"2023-10-18T14:47:43","date_gmt":"2023-10-18T14:47:43","guid":{"rendered":"https:\/\/royadata.io\/blog\/?p=6381"},"modified":"2023-10-18T14:47:43","modified_gmt":"2023-10-18T14:47:43","slug":"realtor-scraper","status":"publish","type":"post","link":"http:\/\/royadata.io\/blog\/realtor-scraper\/","title":{"rendered":"Realtor Scraper 2022: How to Scrape Real Estate Websites for Property Data with Python"},"content":{"rendered":"
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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.<\/p>\n<\/blockquote>\n

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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.<\/p>\n

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.<\/p>\n

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.<\/p>\n\n

<\/span>Realtor Scraping \u2013 an Overview<\/strong><\/span><\/h2>\n

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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<\/a> and Zillow<\/a>. 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.<\/p>\n

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 \u2013 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.<\/p>\n

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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<\/a> and social media platforms<\/a> 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.<\/p>\n\n

<\/span>How to Scrape Real Estate Websites Using Python<\/strong><\/span><\/h2>\n

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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.\u00a0 There is no specific programming language required for coding realtor scrapers.<\/p>\n

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.\u00a0 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.<\/p>\n

The real estate niche has a good number of websites in each with each having its own peculiarities. This means that you can\u2019t 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<\/a> and Beautifulsoup<\/a>. 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>, a web browser automator.<\/p>\n

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