Pricing
from $3.00 / 1,000 results
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Apartments.com Property Scraper
Scrape Apartments.com rentals. 10 endpoints: • Property record by listingKey, URL, or street address (auto-detected) • 6 search modes — location, ZIP, coords, polygon, region ID, or URL (auto-routed) • Location autocomplete One row per listing; full upstream JSON in the Raw column.
Pricing
from $3.00 / 1,000 results
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2
Bookmarked
27
Total users
19
Monthly active users
a month ago
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Scrape Apartments.com rentals — property records, every sub-block, search by 6 different inputs, autocomplete, and rental market trends.
What it does
- Property Details — auto-detects each input as
listingKey, URL, or address; returns the full record - 18 sub-blocks per listing — info, amenities, availabilities, schools, transits, office hours, pet policy, parking policy, lease terms, management, expenses, walkscore, fees, rental costs, similar, reviews, photos, attachments
- 6 search modes — by location name, ZIP, coordinates, polygon, region ID, or apartments.com URL
- Autocomplete — typeahead for cities, neighbourhoods, ZIPs (use the returned
idasgeographyIdfor region search) - Rental Market Trends — state-level (and some city-level) average rent + YoY change
Output
- One flat dataset row per listing / sub-block / autocomplete suggestion / trends snapshot
- Columns:
Mode,Listing Key,Name,Address,City/State/ZIP,Phone,Rating,Bed Range,Rent Range,Photo(cover image),Listing URL - Full upstream JSON kept in
Rawcolumn for power users
Inputs
- Each section is independent — fill only the ones you need
- Multiple inputs per section: one per line in the textarea
Pricing
- Pay per result:
$3 per 1,000dataset items, every plan tier - Apify start fee:
$0.00005per run
Notes
- Sub-blocks always run for every selected listingKey × every selected block — so 5 keys × 18 blocks = 90 rows
- Search results are capped to ~50 listings per page (apartments.com upstream limit); paginate via the
pagefield rental/trendsworks state-wide; city support depends on apartments.com coverage
Errors
- Failures land in the dataset as rows with
Name = "ERROR: ..."so nothing is silently dropped
