HotPads Scraper

🏠 HotPads Scraper

Scrape rental listings from HotPads.com: monthly rent, beds, baths, square feet, full address with coordinates, the landlord or property manager with phone number, photos, description, amenities, pet policy, floor plans with unit prices and nearby schools. Search by city, neighborhood, ZIP code, map point or HotPads URL. No login, no browser, and you pay only for the listings you get.

✨ Why use HotPads Scraper?

• ⚡ Fast — reads HotPads' own listing data directly, 200 properties per search page, with full details loaded in parallel (1,000 listings with full details in about a minute in our tests).
• 🗺️ Every way to search — cities, neighborhoods, boroughs and ZIP codes, map points with a radius, HotPads search URLs with their filters, or single listing and building URLs.
• 📞 Contact data included — company name, contact name and phone number of the landlord or property manager, plus office hours.
• 🧾 Full listing records — description, amenities, cats and dogs policy, every floor plan and unit with its own rent, photos, schools, views and inquiries.
• 📈 No small caps — big areas are split into smaller map tiles automatically, so you can collect thousands of listings in one run.
• 💸 Simple pricing — one flat price per saved listing, details included.

🎯 Use cases

• 🏢 Rent price research — track asking rents by neighborhood, bedroom count or building across US cities.
• 📇 Lead generation — build lists of property managers and landlords with their phone numbers.
• 🔔 Market monitoring — schedule daily runs sorted by newest to catch new rentals and specials as they appear.
• 🧮 Investment analysis — compare rent per bedroom and per square foot, amenities and pet policies across areas.
• 🎓 Relocation and student housing — collect listings near a campus or office with a map point and radius.

🚀 How to use

1. Enter one or more locations such as New York, NY, Brooklyn or 78758, or paste HotPads search or listing URLs.
2. Optionally add map coordinates (latitude,longitude,radiusMiles) and set filters: property type, rent, beds, baths, size, pets, amenities, keywords, listing age.
3. Set Maximum listings per search (0 means no limit).
4. Click Start and wait for the run to finish.
5. Download the results as JSON, CSV or Excel, or read them through the API.

📥 Input

{
  "locations": ["New York, NY", "78758"],
  "coordinates": ["40.7128,-74.006,1"],
  "maxItems": 100,
  "propertyTypes": ["apartment", "condo"],
  "minBeds": 1,
  "maxPrice": 4000,
  "pets": ["dogs"],
  "sortBy": "newest"
}

Filters apply to locations and coordinates. A pasted HotPads search URL keeps its own filters (price, beds, pets, sort and so on).

📤 Output

One row per rental listing. A building with several available units gives one row per unit listing.

Example row from a test run (shortened; the contact person is fictional):

{
  "id": "syn9c2ywsmde",
  "buildingId": "252qc3k",
  "unit": "9J",
  "url": "https://hotpads.com/43-15-52nd-st-woodside-ny-11377-252qc3k/9j/pad",
  "title": "43-15 52nd St #9J",
  "propertyType": "condo",
  "listingType": "rental",
  "price": 5150,
  "beds": 2,
  "baths": 2,
  "street": "43-15 52nd St",
  "city": "Woodside",
  "state": "NY",
  "zip": "11377",
  "neighborhood": "Woodside",
  "latitude": 40.7435677,
  "longitude": -73.9123689,
  "companyName": "Example Property Management Inc",
  "contactName": "Jordan Example",
  "contactPhone": "718-555-0142",
  "description": "Top floor penthouse unit with large terrace with city views! ...",
  "amenities": ["Bicycle Storage", "Central Air Conditioning", "Dishwasher", "Fitness Center", "Laundry: In Unit", "Terrace"],
  "allowsCats": true,
  "allowsDogs": true,
  "units": [{ "name": "9J", "type": "floorplan", "beds": 2, "baths": 2, "priceMin": 5150, "priceMax": 5150 }],
  "totalUnits": 87,
  "photoCount": 14,
  "coverPhoto": "https://photos.zillowstatic.com/fp/c4bf267bf6df306a75f97c4d29da0f7f-rentals_large_1200_1200.webp",
  "schools": [{ "name": "Ps 11 Kathryn Phelan", "type": "primaryschool", "rating": 9, "grades": "PK-6" }],
  "listedAt": "2026-10-22T04:18:35+00:00",
  "searchInput": "New York, NY",
  "scrapedAt": "2026-10-22T06:58:19+00:00"
}

💰 Pricing

You pay $2.00 per 1,000 listings ($0.002 per listing saved), with or without full details, plus a small amount of platform usage (compute and datacenter proxy traffic). Example: 1,000 listings ≈ $2.00 in listing fees plus about two cents of usage (measured: about 55 seconds of compute at the default 512 MB and 14 MB of datacenter proxy traffic). Inputs that return nothing cost nothing, and the run stops cleanly when it reaches your maximum charge.

❓ FAQ

Is it legal to scrape HotPads? The actor only collects data that HotPads shows publicly to every visitor, without logging in. Check the site's terms and your local laws (including privacy rules for contact data) for your use case.

Do I need a HotPads account or my own proxy? No. No login is needed. The actor uses datacenter proxies by default and moves to US residential proxies by itself if HotPads keeps blocking them.

How many listings can I get? As many as HotPads has for your search. HotPads serves about 4,200 properties per map area, so bigger areas such as all of New York City are split into smaller map tiles automatically. Set maxItems to 0 to collect everything.

Why is a field empty? Fields are only filled when the listing has them. For example, many individual apartments in New York show no square footage, and small landlords often list no company name.

Can I schedule it or use it from my code? Yes. Schedule runs in the console (for example daily, sorted by newest) and call the actor through the API. Results export to JSON, CSV, Excel and more.

I used a similar actor on another platform. Will my workflow fit? Yes. Location, coordinate, URL and listing ID inputs are all supported, with one flat row per listing.

⚠️ Limits

• Rentals only: HotPads has no homes for sale or sold data.
• The location search covers the US (HotPads' market), including Alaska, Hawaii and Puerto Rico.
• Sort order applies within each map tile when a large area is split, so a "newest" sort on a whole city is newest per tile.
• Map coordinates use a square box around the point (radius in miles), not a circle.
• Location autocomplete is not offered as a separate output; type the place name in locations instead.