Guides / Scrape Zillow

How to Scrape Zillow in 2026

Zillow uses JavaScript-rendered property cards, anti-bot detection, and IP-based rate limiting to prevent automated access. Both search results and individual listings require a real browser to render. With Browser7, you get fully rendered property data in a single API call.

What makes Zillow hard to scrape

JavaScript-rendered listings

Zillow renders property cards, map data, and listing details using client-side JavaScript. A simple HTTP request returns a page shell without property data. You need a real browser to get the actual listings.

Anti-bot protection

Zillow detects and blocks automated traffic using CAPTCHA challenges, browser fingerprinting, and IP reputation scoring. Datacenter proxies are blocked immediately, and even residential IPs can be flagged with high request volumes.

Two page types to parse

Zillow has search results pages (lists of properties in an area) and individual listing pages (full details for one property). Each has a different HTML structure and different data available, requiring separate parsing logic.

Scrape Zillow search results

Browser7 handles proxy rotation, CAPTCHA solving, and JavaScript rendering automatically. This example scrapes homes for sale in Syracuse, NY and returns the fully rendered HTML with all property cards.

from browser7 import Browser7

client = Browser7(
    api_key="b7_your_api_key",
    base_url="https://ca-api.browser7.com/v1"
)

result = client.render(
    "https://www.zillow.com/homes/7353_rid/",
    country_code="US",
    captcha="auto"
)

print(result.html)

Data you can extract

The rendered HTML contains all the property data Zillow shows to a real visitor. The data available differs between search results and individual listings:

Search results (per property)

  • Listing price
  • Street address, city, state, ZIP
  • Beds, baths, square footage
  • Property type
  • Link to full listing
  • Listing status (for sale, pending, etc.)

Individual listing (full details)

  • Everything from search results, plus:
  • Full property description
  • Photo gallery URLs
  • Price history
  • Tax records and Zestimate
  • School district and nearby schools
  • Agent and brokerage info

Complete example: parse search results

Extract structured property data from a Zillow search results page. Each property card contains price, address, beds, baths, square footage, and a link to the full listing.

from browser7 import Browser7
from bs4 import BeautifulSoup
import json

client = Browser7(
    api_key="b7_your_api_key",
    base_url="https://ca-api.browser7.com/v1"
)

result = client.render(
    "https://www.zillow.com/homes/7353_rid/",
    country_code="US",
    captcha="auto"
)

soup = BeautifulSoup(result.html, "html.parser")

properties = []
for i, card in enumerate(soup.select("article.property-card")):
    prop = {
        "position": i + 1,
        "price": None,
        "address": None,
        "beds": None,
        "baths": None,
        "sqft": None,
        "url": None,
    }

    price = card.select_one('span[data-test="property-card-price"]')
    if price:
        prop["price"] = price.get_text(strip=True)

    address = card.select_one("address")
    if address:
        prop["address"] = address.get_text(strip=True)

    for li in card.select("li"):
        text = li.get_text(strip=True)
        if "bd" in text.lower():
            prop["beds"] = text.split("bd")[0].strip()
        elif "ba" in text.lower():
            prop["baths"] = text.split("ba")[0].strip()
        elif "sqft" in text.lower():
            prop["sqft"] = text.replace("sqft", "").strip()

    link = card.select_one('a[href*="/homedetails/"]')
    if link:
        prop["url"] = link.get("href")

    properties.append(prop)

print(json.dumps(properties, indent=2))

CSS selectors may change if Zillow updates their page structure. Inspect the current page if any fields return null.

Sample output:

[
  {
    "position": 1,
    "price": "$215,000",
    "address": "541 Whittier Ave, Syracuse, NY 13204",
    "beds": "3",
    "baths": "1",
    "sqft": "1,312",
    "url": "https://www.zillow.com/homedetails/541-Whittier-Ave-..."
  },
  {
    "position": 2,
    "price": "$274,900",
    "address": "221 Croyden Rd, Syracuse, NY 13224",
    "beds": "4",
    "baths": "2",
    "sqft": "1,327",
    "url": "https://www.zillow.com/homedetails/221-Croyden-Rd-..."
  },
  ...
]

Complete example: parse an individual listing

Individual Zillow listing pages contain full property details including the description, which is not available on search results. Use the listing URL from the search results to fetch the complete data.

from browser7 import Browser7
from bs4 import BeautifulSoup
import json

client = Browser7(
    api_key="b7_your_api_key",
    base_url="https://ca-api.browser7.com/v1"
)

result = client.render(
    "https://www.zillow.com/homedetails/541-Whittier-Ave-Syracuse-NY-13204/31685360_zpid/",
    country_code="US",
    captcha="auto"
)

soup = BeautifulSoup(result.html, "html.parser")

listing = {
    "price": None,
    "address": None,
    "beds": None,
    "baths": None,
    "sqft": None,
    "description": None,
}

el = soup.select_one('span[data-testid="price"]')
if el:
    listing["price"] = el.get_text(strip=True)

el = soup.select_one("h1")
if el:
    listing["address"] = el.get_text(strip=True)

for fact in soup.select('div[data-testid="bed-bath-sqft-fact-container"]'):
    text = fact.get_text(strip=True)
    if "bed" in text:
        listing["beds"] = text.replace("beds", "").replace("bed", "").strip()
    elif "bath" in text:
        listing["baths"] = text.replace("baths", "").replace("bath", "").strip()
    elif "sqft" in text:
        listing["sqft"] = text.replace("sqft", "").strip()

el = soup.select_one('div[data-testid="description"]')
if el:
    listing["description"] = el.get_text(strip=True)

print(json.dumps(listing, indent=2))

Sample output:

{
  "price": "$215,000",
  "address": "541 Whittier Ave, Syracuse, NY 13204",
  "beds": "3",
  "baths": "1",
  "sqft": "1,312",
  "description": "Located in the heart of Tipperary Hill, 541 Whittier Ave is a must see..."
}

Scrape page 2 and beyond

Zillow uses URL path segments for pagination. Page 1 is the default, page 2 is /2_p/, page 3 is /3_p/, and so on. Append the page segment to the search URL.

from browser7 import Browser7
from bs4 import BeautifulSoup

client = Browser7(
    api_key="b7_your_api_key",
    base_url="https://ca-api.browser7.com/v1"
)

# Page 2: append /2_p/ to the URL
result = client.render(
    "https://www.zillow.com/homes/7353_rid/2_p/",
    country_code="US",
    captcha="auto"
)

soup = BeautifulSoup(result.html, "html.parser")
for card in soup.select("article.property-card"):
    addr = card.select_one("address")
    price = card.select_one('span[data-test="property-card-price"]')
    print(f"{addr.get_text(strip=True)} - {price.get_text(strip=True)}")

Take a screenshot of search results

Capture Zillow search results as an image for market analysis reports, investment dashboards, or historical tracking of property listings and prices over time.

import base64
from browser7 import Browser7

client = Browser7(
    api_key="b7_your_api_key",
    base_url="https://ca-api.browser7.com/v1"
)

result = client.render(
    "https://www.zillow.com/homes/7353_rid/",
    country_code="US",
    captcha="auto",
    block_images=False,
    include_screenshot=True,
    screenshot_full_page=True,
    screenshot_format="png"
)

# Save the screenshot
with open("zillow-search.png", "wb") as f:
    f.write(base64.b64decode(result.screenshot))

print("Screenshot saved")

What this costs

Every Zillow page render costs $0.01 - the same as any other website. Search results pages and individual listing pages both cost $0.01 per render. Residential proxies, JavaScript rendering, CAPTCHA solving, and screenshots are all included.

Scraping 100 search result pages plus 1,000 individual listings costs $11. You know this before you start.

Try it yourself

100 free renders - enough to test Zillow scraping with no payment required.