Scrape Real Estate Listings from Zillow Download real estate listings from the Zillow search results page. Just provide the Zillow search results URLs to extract property listings, and the scraper will get you the updated real estate data from Zillow in a spreadsheet. Zillow Scraping With zillow basic scraper you will get fresh Real Estate FSBO, FSBA $ Rental leads. Scraping pricing history of properties listed on Zillow. The following video shows how WebHarvy can be configured to scrape pricing history of properties listed on Zillow. In addition to scraping pricing history other details like address, zestimate, owner/agent contact details etc. Can also be scraped. Create a free Zillow account to use with the API. Get a Zillow Web Services ID (ZWSID) to use when making your API calls. Read the details for your choice of API to get instructions for making Web Service calls. Integrate into your existing experience, following Zillow's branding requirements, making sure to use your ZWSID when making the calls. Zillow Group is committed to ensuring digital accessibility for individuals with disabilities. We are continuously working to improve the accessibility of our web experience for everyone, and we welcome feedback and accommodation requests. If you wish to report an issue or seek an accommodation, please let us know.
Web scraping can often lead to you having scraped address data which are unstructured. If you have come across a large number of freeform address as a single string, for example – “9 Downing St Westminster London SW1A, UK”, you know how hard it would be to validate, compare and deduplicate these addresses. To start with you’ll have to split this address into a more structured form with house number, street name, city, state, country and zip code separately. It’s quite easy to parse address in Python and this tutorial will show you how.
Available Python Address Parser Packages
Python provides few packages to parse address in python –
- Address – This package is an address parsing library, it takes the guesswork out of using addresses in your applications.
- USAAddress – USAAddress is a python library for parsing unstructured address strings into address components, using advanced NLP methods. You can try their web interface at the link here.
- Street Address – Used as a street address formatter and parser. Based on the test cases from http://pyparsing.wikispaces.com/file/view/streetAddressParser.py
These packages get the job done for most of the addresses, using Natural Language Processing.
Address Parsing using the Google Maps Geocoding API
In this tutorial, we will show you how to convert a freeform single string address into a structured address with Latitude and Longitude using Google Maps Geocoding API. You can also use this API for Reverse Geocoding. i.e., you can convert geo-coordinates into addresses.
What is Geocoding?
Geocoding is the process of converting addresses such as – “71 Pilgrim Avenue Chevy Chase, Md 20815” into geographic coordinates like – latitude 38.9292172, longitude -77.07120479.
Google Maps Geocoding API
Google Maps Geocoding API is a service that provides geocoding and reverse geocoding for an address. So this Python script is a kind of wrapper for this API.
Each Google Maps Web Service request requires an API key that is freely available with a Google Account at Google Developers Console. The type of API key you need is a Server key.
How to get an API Key
- Visit the Google Developers Console and log in with a Google Account.
- Select one of your existing projects, or create a new project.
- Enable the Geocoding API.
- Create a new Server Key.
- You can restrict requests to a particular IP address, but it is optional.
Important: Do not share your API Key, take care to keep them secure. You can delete an old one and generate a new one if needed.
API Usage Limits
Standard usage: 2500 free requests per day and 50 requests per second
Premium usage: 100,000 requests per day and 50* server-side requests per second
* The default limit can be changed
A Simple Demo – Parse Address using Python
The script below can accept address strings as a CSV, or you can just paste the addresses into a list. The script would output the results as a clean CSV file.
If the embed to parse address in python above does not work, you can get the code from GIST here.
Save the file and run the script in command prompt or terminal as:
Once it completes running, you will get an output in a CSV file data.csv. You can modify the file name from line no. 47. You can also modify the code to supply the file name as a positional argument too.
You can go ahead and modify the lines that read the addresses and writes it, to read from a data pipeline and write it to a database. It’s relatively easy, but beyond the scope of this simple demonstration.
Let us know in comments below how this script to parse address in python worked for you or if you have a better solution.
If you need professional help with scraping complex websites, contact us by filling up the form below.
Tell us about your complex web scraping projects
Turn the Internet into meaningful, structured and usable data