Realtor.com Rental Scraper: Rents & Lease Terms in 2026

The rent is only half the price

A $2,000 apartment with water, trash and in-unit laundry included is not the same deal as a $2,000 apartment that adds a pet fee, a parking fee and a deposit worth a month’s rent. The headline number hides the terms that decide what a tenant pays.

Realtor.com, one of the main US property portals, publishes those terms on its rental listings. Read one at a time, they help a tenant choose. Read across a whole market, they show what rentals really cost, and who is offering them.

What you can extract

50+ fields per rental:

Location: address, unit number, ZIP, county, neighborhood, coordinates
Pricing: rent, plus a min/max range for multi-unit buildings
Unit: beds, baths, square footage, year built, building name
Availability: available date, listing date, days on market
Rental terms: lease term, security deposit, application fee
Pet policy: cats and dogs allowed, pet deposit, pet fee
Utilities and building: which utilities are included, laundry type, parking type and fee
Amenities, description and photos
Listing agent: name, phone, email and office

The technical challenge

Search pages and listing pages are two different datasets. Bulk extraction has to handle:

Two layers of data: search results carry rent, beds, baths, pet policy, amenities and agent contact; lease terms, utilities, deposits, fees and move-in dates only appear on the detail page, one extra request per listing.
Multi-unit buildings: one listing can stand for many floor plans, so a single rent figure misleads; a min/max range keeps the data honest.
Uneven fields: some listings don’t specify a pet policy; your schema needs empty values, not guesses.
Scale: New York or Los Angeles list thousands of rentals: pagination, concurrency and proxies follow.

DIY or a ready-made Actor?

Our Realtor.com Rental Scraper on Apify takes a location (city and state, neighborhood or ZIP code) or Realtor.com URLs, including filtered searches copied from your browser and individual listings. Optional keywords such as pool or washer dryer keep only the rentals that match every one, with filters for property type, sort order and a listing cap. Detail pages are collected by default, proxies are included, and 100 listings with full details typically take under 30 seconds. Pay-per-result at about $0.0012 per listing.

A practical workflow

Define the market: a city, a set of ZIP codes, or one filtered search URL per city.
Schedule snapshots: weekly runs turn listing dates and days on market into inventory curves; a pipeline that doesn’t break matters more than the first run.
Normalize the real cost: add pet fees, parking and non-included utilities to the rent, so units compare on what tenants pay.
Act: reprice your units, shortlist rentals for a relocating client, or flag ZIP codes where inventory is piling up.

Use cases that pay off

Rent benchmarking: your asking rent against comparable units by ZIP code, bedroom count and property type.
Investment analysis: rental yields and saturation by area before you buy. Multi-portal merging is covered in our real estate data aggregation guide.
Market monitoring: new listings and price changes over time.
Relocation services: shortlists filtered by pets, parking or furnishing.

The legal boundaries

Public listings: the scraper collects rentals any visitor can see on realtor.com, nothing behind an account.
Agents are people: names, phones and emails are personal data. For outreach, CAN-SPAM covers commercial email and the TCPA covers automated calls and texts.
Analyze, don’t republish: rents and terms are facts; listing photos and descriptions are copyrighted work that doesn’t belong on your site.
Reasonable volumes: snapshots of the markets you need, not a constant crawl.