How to scrape Zillow using Python
Tags: zillowscraper, datascraping, webscraping, zillowscraping
Published: 2023-04-09 18:41:07

Zillow is a popular online real estate marketplace that provides listings, home values, and other data related to the housing market. If you're interested in scraping data from Zillow, you can use Python and web scraping libraries to automate the process. However there are many popular [zillow scraper](https://www.crawlmagic.com/housing-data-scraping) in the market, you can buy in just second.


![scrape-zillow-using-python](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/pbs8ohi13ibv8uh88fay.png)
In this article, we'll provide you with a step-by-step guide and code examples for scraping Zillow data using Python.

**Getting Started**

Before we dive into the code, you'll need to install a few libraries:

beautifulsoup4: A Python library for web scraping.
requests: A Python library for making HTTP requests.
You can install these libraries using pip:

> pip install beautifulsoup4 requests

**Scraping Zillow Listings**

To scrape Zillow listings, we'll need to first retrieve the HTML content of the search results page. We can do this using the requests library:

> import requests
> url = "https://www.zillow.com/homes/for_sale/San-Francisco-CA_rb/"
> response = requests.get(url)
> print(response.text)

This will print the HTML content of the search results page to the console. We can then use the beautifulsoup4 library to parse the HTML and extract the data we're interested in.

> from bs4 import BeautifulSoup
> soup = BeautifulSoup(response.text, 'html.parser')
> listings = soup.find_all('article', class_='list-card')
> for listing in listings:
>     address = listing.find('address')
>     price = listing.find('div', class_='list-card-price')
>     beds = listing.find('ul', class_='list-card-details').find_all('li')[0]
>     baths = listing.find('ul', class_='list-card-details').find_all('li')[1]
>     sqft = listing.find('ul', class_='list-card-details').find_all('li')[2]
>     print(address.text, price.text, beds.text, baths.text, sqft.text)

This code will extract the address, price, number of bedrooms, number of bathrooms, and square footage for each listing on the search results page.

**Scraping Zillow Home Values**

Zillow also provides home value estimates for properties. We can scrape this data using a similar approach.

url = "https://www.zillow.com/homes/San-Francisco-CA_rb/"
response = requests.get(url)

soup = BeautifulSoup(response.text, 'html.parser')

home_values = soup.find_all('div', class_='zestimate')

for home_value in home_values:
    value = home_value.find('div', class_='value').text
    last_updated = home_value.find('div', class_='last-updated').text
    print(value, last_updated)


This code will extract the home value estimate and last updated date for each property on the page.

**Conclusion**

Scraping data from Zillow using Python can provide valuable insights into the housing market. In this article, we provided you with a step-by-step guide and code examples for scraping Zillow listings and home values. However, it's important to keep in mind that [web scraping](https://www.crawlmagic.com/) may be prohibited by a website's terms of service. Be sure to use this information responsibly and in compliance with Zillow's guidelines.