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Adam Gendreau
Adam Gendreau

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How to Get Zillow Data Using a REST API in 2026 (No Scraping Required)

#api #data #tutorial #webdev

How to Get Zillow Data Using a REST API in 2026 (No Scraping Required)

Getting property data from Zillow has always been a headache for developers. The official Zillow API was deprecated in 2021, and the replacement - Bridge Interactive - requires an enterprise application, weeks of waiting, and pricing that starts at $500/month.

But what if you could get 50+ data fields from any Zillow listing with a simple API call? No browser automation. No proxy management. No CAPTCHA solving. Just send a request, get JSON back.

This guide walks you through using a Zillow API to pull structured property data into your application in under 5 minutes.

Why Developers Need a Zillow API

Zillow is the largest real estate marketplace in the US, with data on over 100 million properties. Accessing this data programmatically opens up use cases like:

  • Market analysis - Compare prices, Zestimates, and trends across neighborhoods or ZIP codes
  • Investment modeling - Calculate rental yields using listing prices and rent Zestimates
  • Property monitoring - Track price changes, days on market, and new listings
  • Lead generation - Pull listing agent contact info, property details, and photos for outreach
  • Proptech applications - Build apps that need real-time property data without maintaining a scraper
  • Data science - Train models on property features, tax history, school ratings, and comparable sales

The problem? There's no official public Zillow API anymore. And building your own scraper means dealing with anti-bot systems, rotating proxies, browser fingerprinting, and constant maintenance when Zillow changes their frontend.

What Data Can You Get?

A good Zillow API returns structured JSON with 50+ fields per property:

Pricing & Valuation

  • Listing price, Zestimate (Zillow's estimated market value), rent Zestimate, last sold price, tax assessed value

Property Details

  • Bedrooms, bathrooms, square footage, lot size, year built, property type (house, condo, land, etc.), HOA fees

History

  • Full price history (every listing, sale, and price change), tax history (yearly tax paid and assessed values)

Location

  • Street address, city, state, ZIP, latitude/longitude, nearby school ratings and distances

Listing Info

  • Days on Zillow, listing agent name/phone/email, brokerage, page views, favorites count

Media

  • Property photo URLs, virtual tour links, listing description, interior/exterior features

Comparable Properties

  • Nearby comps with price, beds, baths, and square footage

The Problem with Scraping Zillow Yourself

If you've tried to scrape Zillow, you know the pain:

  1. PerimeterX bot detection - Zillow uses one of the most aggressive anti-bot systems on the web. Standard HTTP requests get blocked instantly. You need browser-level TLS fingerprinting to even get a response.

  2. IP blocking - Datacenter proxies are blacklisted. You need residential or mobile proxies, which cost $2-10/GB and require rotation logic.

  3. Browser fingerprinting - Zillow checks TLS fingerprints, HTTP/2 settings, and JavaScript execution. Tools like Selenium and Puppeteer are detected immediately.

  4. Constant maintenance - Zillow changes their frontend regularly. Your parser breaks, your selectors stop working, and you spend more time fixing the scraper than using the data.

  5. Legal gray area - While scraping publicly available data is generally legal (per the hiQ Labs v. LinkedIn ruling), running large-scale automated requests against Zillow carries risk.

This is why most developers prefer using an API - let someone else handle the infrastructure and just consume the data.

The Solution: APIllow - A Zillow API That Just Works

APIllow is a REST API that returns structured Zillow property data. You send a search query, get back JSON. No scraping setup, no proxy management, no browser automation.

What sets APIllow apart from alternatives:

  • 50+ fields per property - Most Zillow scrapers return 10-15 fields. APIllow extracts everything: price history, tax records, school ratings, comparable properties, agent contact info, and photos.

  • Server-side filters - Filter by property type (land, condo, house, townhouse) and price range (price_min, price_max) before results are returned. This means you only pay for results you actually want.

  • Multiple input types - Search by city name, ZIP code, street address, Zillow Property ID (ZPID), or Zillow URL. Combine multiple input types in a single request.

  • Free tier - 50 requests/month with all data fields, no credit card required. Paid plans start at $9.99/month for 3,333 requests.

  • No proxy setup - Residential and mobile proxies are handled on the backend. You never deal with proxy rotation, IP bans, or CAPTCHAs.

  • Async for speed - Submit a request, get a job ID instantly, poll for results. Typical response time is 3-10 seconds for up to 200 properties.

Step-by-Step: Get Zillow Data with Python

Step 1: Get Your API Key

Sign up at apillow.co - enter your email and you'll get an API key in under 60 seconds. No credit card required.

Step 2: Search for Properties 

import requests
import time

API_URL = "https://api.apillow.co"
API_KEY = "your_api_key_here"
HEADERS = {
    "Content-Type": "application/json",
    "X-API-Key": API_KEY
}

# Search for homes in Austin, TX
response = requests.post(f"{API_URL}/v1/properties", headers=HEADERS, json={
    "search": "Austin TX",
    "type": "sale",
    "max_items": 10
})

job_id = response.json()["job_id"]
print(f"Job submitted: {job_id}")
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Step 3: Poll for Results 

# Poll every 5 seconds until results are ready
while True:
    result = requests.get(
        f"{API_URL}/v1/results/{job_id}",
        headers=HEADERS
    ).json()

    if result["status"] == "complete":
        break
    print("Processing...")
    time.sleep(5)

# Print results
for item in result["results"]:
    p = item["property"]
    print(f"{p['street_address']}, {p['city']} {p['state']} {p['zipcode']}")
    print(f"  Price: ${p['price']:,}")
    print(f"  Beds: {p['bedrooms']}  Baths: {p['bathrooms']}  Sqft: {p['living_area']}")
    print(f"  Zestimate: ${p['zestimate']:,}" if p.get('zestimate') else "")
    print()
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Step 4: Example Output 

{
  "zpid": 29381838,
  "street_address": "400 Academy Dr",
  "city": "Austin",
  "state": "TX",
  "zipcode": "78704",
  "price": 7900000,
  "zestimate": 7450000,
  "rent_zestimate": 18500,
  "bedrooms": 5,
  "bathrooms": 4,
  "living_area": 4354,
  "lot_size": 34800,
  "year_built": 1889,
  "property_type": "SINGLE_FAMILY",
  "home_status": "FOR_SALE",
  "days_on_zillow": 54,
  "listing_agent": {
    "name": "Kathryn Scarborough",
    "phone": "512-555-0123",
    "company": "Compass"
  },
  "price_history": [
    {"date": "2026-02-20", "event": "Listed for sale", "price": 7900000}
  ],
  "tax_history": [
    {"year": 2025, "tax_paid": 82000, "value": 6800000}
  ],
  "nearby_schools": [
    {"name": "Becker Elementary", "rating": 8, "distance": 0.4}
  ],
  "image_urls": ["https://photos.zillowstatic.com/..."],
  "description": "Historic Austin estate on 0.8 acres..."
}
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Advanced: Filter by Property Type and Price

One of the biggest advantages of APIllow over other Zillow APIs is server-side filtering. Instead of fetching 200 properties and discarding 190 of them client-side, you can tell the API exactly what you want:

# Find vacant land under $50K in rural Colorado
response = requests.post(f"{API_URL}/v1/properties", headers=HEADERS, json={
    "zipcodes": ["80831", "80832", "80833"],
    "type": "sale",
    "property_type": "land",
    "price_max": 50000,
    "max_items": 50
})
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Supported property types: house, condo, townhouse, land, apartment, manufactured, multi_family

This is especially valuable for niche use cases like land investors, condo searchers, or multi-family property analysts - you only pay for results that match your criteria.

Advanced: Look Up Specific Addresses 

# Look up specific properties by address
response = requests.post(f"{API_URL}/v1/properties", headers=HEADERS, json={
    "addresses": [
        "123 Main St, Austin, TX 78701",
        "456 Oak Ave, Dallas, TX 75201"
    ]
})
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You can also look up by Zillow Property ID (ZPID) or Zillow URL:

# By ZPID
response = requests.post(f"{API_URL}/v1/properties", headers=HEADERS, json={
    "zpids": [20794780, 20637558]
})

# By Zillow URL
response = requests.post(f"{API_URL}/v1/properties", headers=HEADERS, json={
    "urls": ["https://www.zillow.com/beverly-hills-ca/"],
    "max_items": 20
})
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Real-World Use Case: Rental Yield Calculator

Here's a practical example that uses the Zillow API to calculate rental yield estimates:

import requests
import time

API_URL = "https://api.apillow.co"
HEADERS = {
    "Content-Type": "application/json",
    "X-API-Key": "your_api_key_here"
}

# Search for properties in Columbus, OH
resp = requests.post(f"{API_URL}/v1/properties", headers=HEADERS, json={
    "search": "Columbus OH",
    "type": "sale",
    "property_type": "house",
    "price_max": 300000,
    "max_items": 20
})
job_id = resp.json()["job_id"]

# Wait for results
while True:
    data = requests.get(f"{API_URL}/v1/results/{job_id}", headers=HEADERS).json()
    if data["status"] == "complete":
        break
    time.sleep(5)

# Calculate rental yields
print(f"{'Address':<40} {'Price':>10} {'Rent':>10} {'Yield':>8}")
print("-" * 72)

for item in data["results"]:
    p = item["property"]
    price = p.get("price")
    rent = p.get("rent_zestimate")

    if price and rent and price > 0:
        annual_rent = rent * 12
        gross_yield = (annual_rent / price) * 100
        print(f"{p['street_address']:<40} ${price:>8,} ${rent:>8,}/mo {gross_yield:>6.1f}%")
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How APIllow Compares to Alternatives

APIllow - 50+ fields per property. Free tier (50 req/mo). Server-side filters for property type and price. Proxies included. Setup in 60 seconds. From $9.99/mo. Zero maintenance.

Bridge Interactive (Official Zillow) - Enterprise-only. No free tier. Weeks-long application process. Starts at $500/mo.

Apify Zillow Scraper - 20-30 fields per property. No free tier. No server-side filters. Users must provide their own proxies or pay for Apify's. ~$3.60 per 1,000 results.

DIY Scraper - Field count depends on your parser. No cost beyond proxies ($2-10/GB). Days to weeks to build. You manage proxy rotation, browser fingerprinting, and ongoing maintenance when Zillow changes their frontend.

Is Using a Zillow API Legal?

Web scraping publicly available data is generally legal in the United States, following the 2022 hiQ Labs v. LinkedIn ruling by the Ninth Circuit Court of Appeals. The court ruled that scraping publicly accessible data does not violate the Computer Fraud and Abuse Act (CFAA).

APIllow accesses publicly available Zillow listing pages - the same data any person can see by visiting zillow.com in a browser.

That said, always review Zillow's Terms of Service for your specific use case, especially if you plan to redistribute data commercially.

Getting Started

  1. Sign up at apillow.co - free, no credit card
  2. Get your API key - instant, in your dashboard
  3. Make your first request - copy the Python code above
  4. Explore the docs - full API reference at apillow.co/docs

The free tier gives you 50 requests per month with all 50+ data fields. That's enough to test your integration, build a prototype, or run a small analysis. When you're ready to scale, paid plans start at $9.99/month.

Stop fighting with scrapers. Start building with data.

Get your free API key at apillow.co

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