How to Scrape Zillow Real Estate Data in 2026

Why scrape Zillow?

Real estate professionals and data teams scrape Zillow for actionable market intelligence:

Price monitoring

Track listing prices across zip codes. Detect price drops, identify undervalued properties, and spot market trends.

Market research

Analyze median prices, days on market, and inventory levels across neighborhoods for investment decisions.

Investment analysis

Compare Zestimates vs. listing prices at scale to find properties priced below their estimated value.

Why Zillow is hard to scrape

Zillow is one of the most aggressively protected sites on the web. Here is what makes it difficult:

Challenges

!All listing data is rendered client-side with React — plain HTTP requests return an empty shell
!Zillow uses PerimeterX bot detection that fingerprints your browser, TLS stack, and behavior
!Aggressive rate limiting: too many requests from one IP triggers CAPTCHA walls
!Dynamic selectors that change with each deployment (data-testid attributes shift)
!Search result pages use infinite scroll — you need to scroll and wait for new listings to load
!Zillow actively monitors and blocks cloud IP ranges (AWS, GCP, Azure)

Method 1: DIY with Puppeteer

The classic approach: launch a headless browser, navigate to a Zillow property page, and extract data from the rendered DOM. Here is a working example for a single listing:

scraper.js

#E8A0BF">const puppeteer = #E8A0BF">require(#A8D4A0">'puppeteer');

(#E8A0BF">async () => {
  #E8A0BF">const browser = #E8A0BF">await puppeteer.#87CEEB">launch({
    headless: #A8D4A0">'new',
    args: [#A8D4A0">'--no-sandbox'],
  });
  #E8A0BF">const page = #E8A0BF">await browser.#87CEEB">newPage();

  #E8A0BF">await page.setUserAgent(
    #A8D4A0">'Mozilla/5.0 (Windows NT 10.0; Win64; x64) ' +
    #A8D4A0">'AppleWebKit/537.36 (KHTML, like Gecko) ' +
    #A8D4A0">'Chrome/124.0.0.0 Safari/537.36'
  );

  #E8A0BF">await page.#87CEEB">goto(
    #A8D4A0">'https://www.zillow.com/homedetails/123-Main-St/12345678_zpid/',
    { waitUntil: #A8D4A0">'networkidle2', timeout: 30000 }
  );

  // Wait #E8A0BF">for price to render (JS#FFB347">-dependent)
  #E8A0BF">await page.#87CEEB">waitForSelector(#A8D4A0">'[data-testid=#A8D4A0">"price"]', { timeout: 15000 });

  #E8A0BF">const listing = #E8A0BF">await page.evaluate(() => ({
    price: document.#87CEEB">querySelector(#A8D4A0">'[data-testid=#A8D4A0">"price"]')?.innerText,
    address: document.#87CEEB">querySelector(#A8D4A0">'h1')?.innerText,
    beds: document.#87CEEB">querySelector(#A8D4A0">'[data-testid=#A8D4A0">"bed-bath-item"]:nth-child(1)')?.innerText,
    baths: document.#87CEEB">querySelector(#A8D4A0">'[data-testid=#A8D4A0">"bed-bath-item"]:nth-child(2)')?.innerText,
    sqft: document.#87CEEB">querySelector(#A8D4A0">'[data-testid=#A8D4A0">"bed-bath-item"]:nth-child(3)')?.innerText,
  }));

  console.#87CEEB">log(listing);
  #E8A0BF">await browser.#87CEEB">close();
})();

This works for one-off scrapes, but Zillow's PerimeterX protection will detect headless Chromium within a few dozen requests. You would need stealth plugins, residential proxies, and CAPTCHA-solving services — adding $50-200/month in costs before you scrape a single listing at scale.

Method 2: SnapRender API

Same result, no browser infrastructure. SnapRender's /render endpoint returns the fully rendered page as clean markdown, and /extract pulls structured fields using CSS selectors.

Render as markdown

Get the full listing page as LLM-ready markdown — ideal for feeding into AI analysis pipelines or storing in a database.

render.py

#E8A0BF">import requests

# Render a Zillow listing #E8A0BF">as clean markdown
render = requests.#87CEEB">post(
    #A8D4A0">"https://api.snaprender.dev/v1/render",
    headers={#A8D4A0">"x-api-key": #A8D4A0">"sr_live_YOUR_KEY"},
    json={
        #A8D4A0">"url": #A8D4A0">"https://www.zillow.com/homedetails/123-Main-St/12345678_zpid/",
        #A8D4A0">"format": #A8D4A0">"markdown",
        #A8D4A0">"use_flaresolverr": #E8A0BF">True
    }
)
#E8A0BF">print(render.#87CEEB">json()[#A8D4A0">"data"][#A8D4A0">"markdown"])

Extract structured data

Use CSS selectors to pull price, address, beds, baths, sqft, and Zestimate. Returns clean JSON — no HTML parsing required.

extract.py

#E8A0BF">import requests

# Extract structured listing data #E8A0BF">with CSS selectors
extract = requests.#87CEEB">post(
    #A8D4A0">"https://api.snaprender.dev/v1/extract",
    headers={#A8D4A0">"x-api-key": #A8D4A0">"sr_live_YOUR_KEY"},
    json={
        #A8D4A0">"url": #A8D4A0">"https://www.zillow.com/homedetails/123-Main-St/12345678_zpid/",
        #A8D4A0">"use_flaresolverr": #E8A0BF">True,
        #A8D4A0">"selectors": {
            #A8D4A0">"price": #A8D4A0">"[data-testid=#A8D4A0">'price']",
            #A8D4A0">"address": #A8D4A0">"h1",
            #A8D4A0">"beds": #A8D4A0">"[data-testid=#A8D4A0">'bed-bath-item']:nth-child(1)",
            #A8D4A0">"baths": #A8D4A0">"[data-testid=#A8D4A0">'bed-bath-item']:nth-child(2)",
            #A8D4A0">"sqft": #A8D4A0">"[data-testid=#A8D4A0">'bed-bath-item']:nth-child(3)",
            #A8D4A0">"zestimate": #A8D4A0">"[data-testid=#A8D4A0">'zestimate-text']"
        }
    }
)
#E8A0BF">print(extract.#87CEEB">json())

Example response

response.json

{
  #A8D4A0">"status": #A8D4A0">"success",
  #A8D4A0">"data": {
    #A8D4A0">"price": #A8D4A0">"$485,000",
    #A8D4A0">"address": #A8D4A0">"123 Main St, Austin, TX 78701",
    #A8D4A0">"beds": #A8D4A0">"3 bd",
    #A8D4A0">"baths": #A8D4A0">"2 ba",
    #A8D4A0">"sqft": #A8D4A0">"1,850 sqft",
    #A8D4A0">"zestimate": #A8D4A0">"$492,100"
  },
  #A8D4A0">"url": #A8D4A0">"https://www.zillow.com/homedetails/123-Main-St/12345678_zpid/",
  #A8D4A0">"elapsed_ms": 3420
}

Scraping Zillow search results

Individual property pages are straightforward, but search result pages are trickier. Zillow loads listings dynamically via infinite scroll, and the URL encodes search parameters including map bounds, filters, and pagination.

The most reliable approach: render the search URL as markdown with SnapRender, then parse the listing cards from the output. Each card contains the price, address, and a link to the full listing page. Follow each link with /extract to get the full property details.

Pro tip: use the API endpoint

Zillow's search page makes XHR requests to an internal API. If you render the page as markdown, the listing data is embedded in the page's initial state as JSON. Parse the __NEXT_DATA__ script tag for structured results without needing individual selectors.

Start free — 100 requests/month

Get your API key in 30 seconds. Scrape Zillow listings with five lines of code. No browser fleet, no proxy bills, no PerimeterX headaches.

Get Your API Key

Frequently asked questions

Zillow's Terms of Use prohibit scraping, and they actively enforce this through cease-and-desist letters. However, scraping publicly available data is generally protected under the hiQ v. LinkedIn ruling in the US. Stick to public listing data, rate-limit your requests, and consult a lawyer for your specific use case.

Zillow heavily relies on JavaScript to render listing data. Simple HTTP requests (like Python's requests library) only get the initial HTML shell — no listings. You need a headless browser or a rendering API like SnapRender to execute the JavaScript first.

Zestimate values are rendered client-side on individual property pages. You can extract them using a CSS selector like .zestimate or by rendering the page as markdown with SnapRender. Note that Zillow considers Zestimate data proprietary, so check their ToS before using it commercially.

SnapRender starts free with 100 requests/month. Paid plans begin at $9/month for 1,500 requests. Each Zillow page render or extraction counts as one request — no credit multipliers or hidden fees.