How to Scrape Zillow for Real Estate Listings using Python and LXML?

Introduction

Web extracting real-estate data is a feasible way to track real-estate list accessible for agents and sellers. Being in tenure of Scraped real estate data from real-estate websites like Zillow.com can assist you to regulate rates of list on your website or assist you to make a dataset for your organizations. In this blog, we will extract python Web Scraping real estate data, and show you how to scrape real estate data. We will also show you how can you extract real estate list depend on zip code.

Below are the steps to Extract Zillow: –

1. Build the URL of exploring out comes page from Zillow.com for Example – https://www.zillow.com/homes/02126_rb/
2. Downloading the HTML of explore out come page utilizing Python Needs.
3. Analyze the page utilizing LXML – LXML catch you route the HTML Structure utilizing Xpaths.
4. Save the information to a CSV file.

We Extract the following details from Zillow: –

• Real-Estate Title
• Name of Street
• City of Real-Estate
• Province
• Zip Code
• Pricing of House
• Features and Facts
• Real-Estate Provider
• URL of Real-Estate Company

Below is the Screen Shot of Listing of Data Fields, which we scrape from Zillow: –

Here is a guidebook to mount Python 3 in Linux

http://docs.python-guide.org/en/latest/starting/install3/linux/

Mac clients can follow this guidebook

Windows Users go here

http://www.websitescraper.com/python-package-for-web-scraping-in-windows-10/

Windows clients can contact us for more details

http://www.websitescraper.com/contact-us/

Plan to scrape real-estate data?

Get a Quote!

Packages

PIP to mount the following instructions in Python

(https://pip.pypa.io/en/stable/installing/ )

Python Requests, to make download and requests the HTML content of the given pages.

(http://docs.python-requests.org/en/master/user/install/)

Python LXML, for analyzing the HTML Tree Structure utilizing Xpaths

(Learn how to install that here – http://lxml.de/installation.html)

The Code

https://gist.github.com/websitescraper/27994d3c71fcd420c9b0f15b83e63960

If the above link doesn’t work then you can download the code from the below-given link

https://gist.github.com/websitescraper/27994d3c71fcd420c9b0f15b83e63960

If you like Python 2 then you can contact us for another code.

http://www.websitescraper.com/contact-us/

Running the Scraper Zillow

Guess the script is titled, zillow.py. Once you sort the script title in a terminal with a –h or command prompt.

usage: zillow.py [-h] zipcode sort
positional arguments:
zipcode
sort
available sort orders are:
newest: Latest property details
cheapest: Properties with cheapest price
optional arguments:
-h, --help  show this help message and exit

You should mount the Zillow scraping tool with influences for sort and zip code. The sort influence has the choices ‘cheapest’ and ‘newest’ listings accessible. For example, to search the list of the latest properties for sale in Massachusetts, Boston we will mount the script as:

python3 zillow.py 02126 newest

This would help you to make a CSV file name properties-02126.csv that remains in a similar file as the script. Below are some trial data scraped from Zillow.com for the order above.

Click on the below-given link to download the code: –

https://gist.github.com/websitescraper

Conclusion

This Extracting Zillow must be capable to scrape real estate listings in Zillow of the greatest zip codes offered. To know more about real-estate information administration, you can go via post –Quality and Real Estate Challenges.

If you want to Scrape Zillow Listings Data of millions of pages, then you can contact Scraping Intelligence. How you can build an extractor on a huge scale and how you can stop yourself from being blacklisted while extracting.