Hotpads Scraper

Scrape rental listings from HotPads.com — rent, beds, baths, square footage, address, coordinates, photos, amenities, pet policies, nearby schools and per-unit availability — for any US city, neighbourhood or ZIP code. Paste a HotPads search URL, press start, and get a clean spreadsheet.

What does HotPads Scraper do?

HotPads Scraper turns any HotPads.com search page into structured rental data. Give it a search URL — a city, a neighbourhood, or a filtered search — and it walks the results and returns one row per listing with plain-English columns you can open directly in Excel, Google Sheets, or load through the API.

It runs in two modes:

• Fast mode (default) reads everything the search pages carry: rent, beds, baths, sqft, full address, coordinates, photos, unit counts, price drops and a contact phone. Roughly 200 listings in 20 seconds.
• Detail mode additionally opens each listing page for the full description, complete amenity list, pet policies and fees, lease terms, office hours, nearby schools, popularity stats, and a per-unit breakdown of every available apartment in a building.

Running on Apify means you also get scheduling, a REST API, webhooks, integrations with Make, Zapier, Google Sheets and Slack, automatic proxy rotation, and run monitoring — without maintaining any of it yourself.

Why use HotPads Scraper?

• Rental market research — track asking rents, price drops and availability across neighbourhoods over time.
• Lead generation — build lists of property managers and landlords with contact phone numbers.
• Competitive analysis — see how comparable buildings price, what they offer, and how long they sit on the market.
• Real estate investment — evaluate rental yields by area with square footage, bed/bath mix and per-unit pricing.
• Relocation and tenant search — filter thousands of listings offline instead of clicking through pages.
• Academic and policy research — assemble reproducible housing datasets with coordinates and timestamps.

How to use HotPads Scraper

1. Find your search on HotPads.com — pick a city, then apply any filters you want (price, beds, property type). Copy the URL from your browser, e.g. https://hotpads.com/san-francisco-ca/apartments-for-rent.
2. Open this Actor and click Try for free.
3. Paste the URL into Start URLs. You can add several at once.
4. Set your limits — Max Items caps how many listings you save, Max Pages caps how many result pages are followed (HotPads itself stops at 40 pages, about 1,600 listings per search).
5. Choose a mode — leave Scrape Detail Pages off for a fast, cheap run, or switch it on for the full dataset.
6. Click Start, then download from the Output tab as JSON, CSV, Excel or HTML — or pull it through the API.

Getting more than 1,600 listings from one city

HotPads caps any single search at 40 pages. To go deeper, split the city into several narrower searches — by neighbourhood, by ZIP, or by price band — and pass them all as Start URLs. Each one gets its own 40-page allowance.

Input

Field	Type	Default	Description
Start URLs	URL list	—	One or more HotPads search page URLs
Max Items	integer	0 (unlimited)	Stop after this many listings
Max Pages	integer	40	Result pages to follow per URL (40 is HotPads' own cap)
Scrape Detail Pages	boolean	false	Off: search-page data only, ~10× faster and cheaper. On: opens every listing for description, amenities, pets, schools and per-unit pricing
Block Images	boolean	false	Skips downloading listing photos to cut proxy bandwidth. Photo URLs are still extracted. Note it does not make runs faster — measured slightly slower — so leave it off unless bandwidth is what you are optimising
Proxy Configuration	proxy	Apify Residential (US)	Residential proxies are required. HotPads blocks datacenter IPs outright

Example input:

{
  "startUrls": [{ "url": "https://hotpads.com/san-francisco-ca/apartments-for-rent" }],
  "maxItems": 100,
  "maxPages": 3,
  "includeDetails": false,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  }
}

Output

One row per listing. Download as JSON, CSV, Excel or HTML.

{
  "url": "https://hotpads.com/33-8th-at-trinity-place-san-francisco-ca-94103-23y7253/pad",
  "name": "33 8th at Trinity Place",
  "property_type": "Apartment building",
  "rent": 4114,
  "rent_max": 6341,
  "rent_display": "$4,114 – $6,341",
  "bedrooms": 0,
  "bedrooms_max": 2,
  "bathrooms": 1,
  "sqft": 382,
  "sqft_max": 685,
  "full_address": "33 8th St, San Francisco, CA 94103",
  "address": "33 8th St",
  "city": "San Francisco",
  "state": "CA",
  "zip": "94103",
  "latitude": 37.77844882678356,
  "longitude": -122.41362422704697,
  "units_available": 15,
  "price_drops": 7,
  "contact_phone": "1-707-847-4228",
  "photos": ["https://photos.zillowstatic.com/fp/01ae778a92392c6dcf1a5755615b23d2-rentals_medium_500_500.webp"],
  "photo_count": 12,
  "listed_date": "2023-07-27T12:33:33.979Z",
  "updated_date": "2026-08-20T12:30:31.416Z",
  "scraped_at": "2026-08-20T20:33:07.112Z",
  "source": "hotpads.com"
}

How ranges work

Most listings quote a single figure, so rent, bedrooms, bathrooms and sqft hold that value and the matching _max column stays empty. When a building spans a range — a 15-unit building from studios to 2-beds — rent holds the starting figure and rent_max the top of the range. rent_display gives the formatted version for reports.

Data dictionary

Returned in both modes

Column	Type	Description
url	string	Listing page URL
name	string	Building or listing name
property_type	string	Apartment building, House, Condo, Townhouse, Room for rent
rent	number	Monthly rent, or the starting rent for a range
rent_max	number	Top of the rent range, empty when there is a single price
rent_display	string	Formatted rent, e.g. $4,114 – $6,341
bedrooms, bedrooms_max	number	Bedroom count (0 means studio)
bathrooms, bathrooms_max	number	Bathroom count
sqft, sqft_max	number	Interior square footage
full_address	string	Single-line address, ready for geocoding or a CRM
address, city, state, zip	string	Address components
latitude, longitude	number	Coordinates
unit	string	Unit number, when the listing is a specific unit
units_available	number	Units currently available in the building
new_units, price_drops	number	Recently added units, and units whose price dropped
accepting_applications	boolean	Whether the landlord takes applications; empty when unstated
special_offer	string	Promotion text, e.g. one month free
has_3d_tour	boolean	Whether a 3D tour exists
contact_phone	string	Listing contact number
photos	array	Photo URLs
photo_count	number	Number of photos
listed_date, updated_date	date	When the listing appeared and last changed
scraped_at	date	When this row was collected
source	string	Always hotpads.com

Added by detail mode

Column	Type	Description
description	string	Full listing description
neighborhood	string	Neighbourhood name
available_date	string	Soonest move-in date
amenities, unit_amenities	array	Building and in-unit amenity lists
laundry, parking, security	string	e.g. In Unit, Yes
air_conditioning, gym, pool, dishwasher, furnished	boolean	Amenity flags
pets_allowed	string	e.g. Cats and Dogs Allowed
cat_allowed, dog_allowed	boolean	Per-species permission
cat_deposit, dog_deposit, cat_monthly_fee, dog_monthly_fee	number	Pet costs
pet_restrictions	string	Breed or size restrictions
lease_terms, office_hours	string	Lease lengths offered, leasing office hours
fees_and_deposits	array	Fees and deposits
total_units_in_building	number	Total units in the building
units	array	Per-unit rows: unit number, floorplan, beds, baths, sqft, rent, availability, price drop
schools	array	Nearby schools with name, type, rating, grades and distance
views_count, favorites_count, inquiries_count	number	Popularity on HotPads
contact_name, contact_company	string	Leasing contact and company
is_broker_listing	boolean	Whether a broker listed it
website	string	Property website
student_housing, senior_housing, military_housing	boolean	Housing programme flags

Search pages do not carry amenity, school or description data, so those columns are omitted in fast mode rather than returned empty. Turn on detail mode to populate them.

How much does it cost to scrape HotPads?

This Actor is pay per result: $0.003 per listing saved, plus a negligible start fee. There is no platform surcharge on top of the result price.

Run	Listings	Approximate cost
Quick sample	10	$0.03
One city page	40	$0.12
Full search (40 pages)	~1,600	$4.80

Detail mode returns the same number of rows, so the result cost is identical — it simply takes longer and uses more proxy bandwidth, since it opens a page per listing.

Keeping costs down: set Max Items on exploratory runs, leave detail mode off unless you need descriptions or amenities, and schedule incremental runs (a few pages, sorted by newest) instead of re-scraping whole cities.

Tips and advanced usage

• Filter on HotPads first. Applying price, bed and property-type filters on the site produces a narrower search URL and means fewer paid rows.
• Multiple cities in one run. Add several Start URLs; each is paginated independently.
• Schedule it. Daily or weekly runs with updated_date make it easy to spot new listings and price changes.
• Deduplicate on url. It is stable per listing and is the natural key for joining runs over time.
• Residential proxies are not optional. HotPads is behind PerimeterX and refuses datacenter IPs immediately.

Migrating from version 2

Version 3 renames the output columns to plain English, decodes HotPads' internal codes, and drops columns that were always empty. If you have a pipeline built on v2 field names:

v2	v3
display_name	name
price_min / price_max	rent / rent_max
price_display	rent_display
bedrooms_min / bedrooms_max	bedrooms / bedrooms_max
bathrooms_min, sqft_min	bathrooms, sqft
street_address	address (plus the new full_address)
property_type: "large"	property_type: "Apartment building"
rental_application_status: "accepted"	accepting_applications: true
is_apartment_building	folded into property_type
listed_by_phone / listed_by_name / listed_by_company	contact_phone / contact_name / contact_company
posted_date	listed_date
listing_source	source
hvac	air_conditioning
unit_count	units_available
pet_policy	pets_allowed

FAQ

Is scraping HotPads legal? This Actor collects only publicly available listing information — no login, no personal accounts. Public data collection is broadly lawful, but how you use the data is your responsibility, particularly for contact details, which are subject to privacy and marketing rules such as GDPR and CCPA. Review HotPads' Terms of Use and take your own legal advice for commercial use.

Why do I need residential proxies? HotPads sits behind PerimeterX, which blocks datacenter IP ranges on sight. The default Apify Residential (US) configuration works out of the box.

Why did a few listings fail? Anti-bot systems occasionally challenge individual requests. The Actor retries with a fresh session, and the run log states exactly why anything was skipped. A small number of failures in a large run is normal.

Can I get more than 1,600 listings from one city? Not from a single search — that is HotPads' own limit. Split the city into neighbourhood, ZIP or price-band searches and pass them together.

Some detail columns are empty on a few listings. HotPads occasionally serves a detail page that omits part of its data. Those rows still carry everything from the search result — rent, address, coordinates, photos and contact — so the row remains usable.

Support

Found a bug or need a field that is missing? Open an issue on the Issues tab and include the run ID and input you used. Requests for related scrapers or custom real estate data pipelines are welcome.

Disclaimer

This Actor is not affiliated with, endorsed by, or connected to HotPads or Zillow Group. It collects publicly accessible information only. You are responsible for ensuring your use complies with applicable laws and with HotPads' Terms of Use.