🏢 Apartments.com Scraper

Apartments.com Scraper — Rent, Address, Coordinates and Transit

Apartments.com Scraper extracts public rental property listings from Apartments.com as structured JSON: property name, full street address, GPS coordinates, monthly rent range, aggregate rating, Verified Listing status and nearby transit stops. Feed it property URLs, location-search URLs, map bounding-box URLs or a plain-text city, and rows stream into the dataset as each page is parsed. No HTML parsing, no selectors, no login. Open it on Apify and press Start.

⚠️ The proxy input does not work the way the editor implies. Apartments.com sits behind Akamai Bot Manager and denies datacenter and direct traffic, so this Actor enforces Apify US Residential proxy. The Use Apify Proxy toggle and the proxy-group selection in proxyConfiguration are ignored. Custom proxyUrls, if you paste any, are used instead. Details in How does Apartments.com Scraper handle rate limits and blocking?.

What is Apartments.com Scraper?

Apartments.com Scraper is an Apify Actor that turns any Apartments.com property page, location search or map search into a clean rental-listing dataset. Each row is one property, with 13 top-level keys covering identity, address, geography, rent band, trust signals and nearby transit — plus a capture timestamp and an error field so every URL you submit is accounted for.

No Apartments.com account, login or cookie is required. Every value it returns is already visible to any anonymous visitor on the property page.

It is built for rental-market analysts benchmarking prices, proptech teams building address-level inventory, relocation services scoring commute access, and developers piping normalized listing data into a warehouse or an AI agent.

What Apartments.com rental listing data is publicly available to scrape?

Apartments.com renders the whole public offer on the property page before any login — name, address, coordinates, advertised rent, rating, badges and nearby transit are all in the served document. What sits behind a gate is the leasing and application flow, not the listing data.

Data Category	Public on the listing page	Behind an Apartments.com account
Property name, street address, city, state, ZIP	✅ Public	—
Advertised monthly rent range	✅ Public	Actual negotiated lease rent
GPS latitude and longitude	✅ Public	—
Aggregate star rating, Verified Listing badge	✅ Public	—
Nearby transit stops with drive time and distance	✅ Public	—
Breadcrumb geography (state → city → locality)	✅ Public	—
Floor plans, unit inventory, amenities, fees, photos	✅ Public — but not returned by this Actor (building-level output only)	—
Tour requests, messages with the leasing office	❌	Renter account / inquiry form
Rental application and screening data	❌	Renter account + application
Property-manager lead and performance data	❌	Property-manager account

Apartments.com Scraper only returns publicly visible data — what any visitor sees on the property page. Nothing behind a login wall.

What data can I extract with Apartments.com Scraper?

Every property row carries four groups of data: what and where the property is, what it costs, how Apartments.com labels and rates it, and what transit sits nearby. Nested objects are plain JSON objects, not stringified blobs.

Field Name	Description
id	Apartments.com property identifier — the 7-character slug at the end of the canonical URL
propertyName	Building name on multi-unit complexes; the street address on single-unit listings (condos, houses, individual units)
url	Canonical property URL, trailing slash removed
breadcrumbs	Site breadcrumb trail as an array of strings, with the property name appended if the trail does not already end on it
lastUpdated	Listing update stamp exactly as Apartments.com publishes it — a US-format date string, not ISO-8601
location	Object: fullAddress, state, city, neighborhood, postalCode, streetAddress
location.fullAddress	Street, city and STATE ZIP joined with commas
location.streetAddress	Street line only
location.city	City as printed in the address block
location.state	Full state name, expanded from the two-letter code
location.postalCode	ZIP code
location.neighborhood	Breadcrumb parent locality — see the caveat below the tables
coordinates	Object: latitude, longitude
coordinates.latitude	Decimal latitude from the page's place metadata, or null
coordinates.longitude	Decimal longitude from the page's place metadata, or null
rating	Aggregate review rating on the site's 1–5 scale, or null when the property publishes none
isVerified	Boolean — whether the page carries the Verified Listing badge
rent	Object: min, max — advertised monthly rent in USD as integers
rent.min	Low end of the advertised band; equal to rent.max when a single price is advertised
rent.max	High end of the advertised band
transportation	Array of nearby transit objects: name, drive, distance, and url when the site links the stop
errorReason	null on a successful row; a typed reason string on an uncharged accounting row
scrapedAt	ISO-8601 UTC timestamp of the capture, second precision

Identity, address and geography fields

id, propertyName and url identify the property. breadcrumbs gives you the site's own geographic hierarchy as an ordered array, which is useful for grouping rows by state or city without parsing the address. location holds the split address — streetAddress, city, state (expanded to the full state name from the two-letter code), postalCode — plus fullAddress pre-joined for display. coordinates.latitude and coordinates.longitude come from the page's own place metadata, so they are the site's geocode rather than a re-geocode of the address string.

Both Apartments.com page templates are parsed. Multi-unit complexes publish the name in an <h1 id="propertyName">; single-unit listings — condos, houses, individual rented units — use a different template with a bare <h1> inside the delivery-address block and no propertyName id. Both produce a populated propertyName and address.

Rent, rating and trust fields

rent is an object with min and max in whole US dollars. It is read from the rendered rent line first, and falls back to the listing's own published offers band for templates that do not render that line — which is what makes rent populate on houses and individual units. Equal min and max means a single advertised price. Nothing is derived or estimated: when a listing genuinely says "call for rent", both stay null.

rating is Apartments.com's own aggregate on a 1–5 scale, read from the property's structured-data node. It is sparse by nature — the source notes roughly one property in three publishes a rating at all, and the rest are honestly null rather than zero-filled. isVerified reflects the Verified Listing badge on the page.

Nearby transit

transportation is an array, one object per nearby stop, each with name, drive (drive time as printed) and distance (as printed, e.g. "0.4 mi"). A url key is present only when Apartments.com links that stop to its own transit page. Properties with no transportation section return an empty array.

Documented limitation — location.neighborhood. This value is the breadcrumb parent locality, not a guaranteed sub-city neighborhood. When the site's breadcrumb trail includes a neighborhood level, you get a real neighborhood name. When it does not, the parent is the city, so location.neighborhood repeats location.city. Apartments.com also publishes a neighborhood name elsewhere in its page metadata, but that node is absent on a minority of properties even on a fully rendered capture — mixing the two would make the column mean different things from row to row. The Actor keeps the one deterministic value and documents it here instead.

🤖 Add-on: Need additional real estate data?

Two companion Scraper Engine Actors cover the rest of the property stack. Realtor.com Agents Scraper pulls the agent and brokerage side of the US market, which pairs well with a building-level rental inventory. Booking Scraper covers short-stay accommodation for the same geography, useful when you are comparing long-term rent against nightly rates in a submarket.

Why not build this yourself?

Apartments.com publishes no public API, so a DIY scraper is the alternative — and the access layer is the real cost, not the parsing.

Akamai Bot Manager gates the site on two independent layers: a TLS fingerprint check that only tolerates Firefox, and a JavaScript interstitial served to the client that clears the first check. The Actor's source records what that means in practice, measured on 2026-07-18: a curl_cffi client impersonating Firefox returned 0 clean pages across 120 US-residential IP rolls; Chrome and Safari impersonations were refused with 403 at the TLS level; Playwright Chromium was refused on every attempt, direct and residential alike. Playwright Firefox on US residential returned real pages on the first try. A real browser is therefore the engine, not a fallback — which means Playwright, a Firefox binary in your image, and the memory to run it.

Three more details cost time to discover. The interstitial is served with HTTP 200, so status codes alone cannot detect a block — the Actor keys on the Akamai container id (sec-if-cpt-container) and other explicit markers instead, because a size heuristic waves a 2,490-byte challenge straight through. The user agent must not be overridden: presenting a Windows UA from a Linux container is an OS/stack mismatch that Akamai hard-denies on every exit IP. And navigating straight to a property URL on a cold context is treated far more harshly than arriving via the homepage, so every browser session warms up on / first.

On top of that you need US residential egress with sticky sessions you can roll on demand, a render-completion gate that a half-streamed page cannot satisfy, and per-item error accounting so a blocked page does not silently vanish from your dataset. All of that is infrastructure to run and pay for before you have parsed a single rent figure.

How to use Apartments.com Scraper

Apartments.com Scraper runs on Apify. Start it from the Apify Console, or call it through the Apify API from your own code.

1. Open Apartments.com Scraper on Apify and click Try for free
2. Give it a target: paste Apartments.com URLs into Apartments.com URLs (startUrls), type a location into Search term (search), or do both. No input is marked required in the schema, but a run with neither logs "nothing to do" and exits without pushing a row
3. Set Maximum properties to scrape (maxItems) — this is the total row cap across every URL you supplied
4. Optionally set Search end page (endPage) to stop pagination early, and leave the Proxy & networking section collapsed unless you have your own residential proxy
5. Click Start, then export the dataset as JSON, CSV or Excel — or read it live through the Apify API while the run is still going

Three URL shapes are auto-detected, so you can mix them freely in one list:

URL shape	Example	What the Actor does
Property URL	https://www.apartments.com/sobe-apartment-rentals-miami-beach-fl/26xc7jb/	Queues that one property directly
Location or filtered search URL	https://www.apartments.com/brookline-ma/2-bedrooms/	Paginates the results and queues every property card it finds
Map / bounding-box URL	https://www.apartments.com/?bb=0nijpwq7qH0t1s0oB	Paginates the map result set with a page= parameter

Apartments.com expresses its filters as URL path segments, so build the search you want in your browser — bedrooms, price ceiling, pet policy — and paste the address bar in. https://www.apartments.com/brookline-ma/2-bedrooms-under-3000-pet-friendly-dog/ is crawled exactly like an unfiltered index. URLs that are not on apartments.com, or that have no http/https scheme, are skipped with a warning rather than failing the run.

How to scale to bulk property extraction

startUrls is a list, so bulk extraction is the default mode: paste as many property, search and map URLs as you need and each is processed in turn. Both plain strings and objects are accepted — an entry can be "https://…" or {"url": "https://…"}, and requestsFromUrl / loadedUrl keys are read too, so output from another tool usually feeds in unchanged.

maxItems is a total across all URLs, not a per-URL figure, and it is applied during discovery — the Actor stops queueing property pages once the quota is met, so it never fetches pages it will not save. search adds one more search URL to the front of the list. For very large metros, split the work into several narrower URLs (by neighborhood, bedroom count or price band) rather than paging deeper — the reason is in the Input section below.

What can you do with Apartments.com rental listing data?

• 🏙️ A rental market analyst benchmarking a submarket paginates a city search and aggregates rent.min and rent.max by location.city and location.postalCode to produce a price band per ZIP, using isVerified to weight actively managed listings.
• 📈 A property manager tracking comparable buildings re-runs the same search URLs weekly and diffs rent.min per id to see which competitors moved price, with lastUpdated confirming the listing was actually refreshed.
• 🚆 A relocation consultant shortlisting properties for a client filters on coordinates distance to the office and reads the transportation array's drive and distance values to rank candidates by commute rather than by rent alone.
• 🏗️ A proptech engineer building an address-level inventory loads location.fullAddress, coordinates.latitude and coordinates.longitude straight into PostGIS, keyed on id, with no geocoding step because the coordinates are the site's own.
• 🤖 An AI engineer building a rental assistant indexes propertyName, location.fullAddress, breadcrumbs and the transportation names into a vector store so an agent can answer "two-bed buildings in Brookline within a 5-minute drive of a T stop, under $3,500" against live listings instead of a stale export.

Every one of these is callable from an agent framework over the Apify API, since the Actor is a standard HTTP-triggered run.

How does Apartments.com Scraper handle rate limits and blocking?

Apartments.com is protected by Akamai Bot Manager, so the Actor's whole fetch path is built around clearing it rather than retrying into it.

One Playwright Firefox browser and one browser context are opened per run and reused for every page, bound to a single sticky Apify US-residential exit IP. The context warms up on the Apartments.com homepage first so that IP earns its cookies before any target is requested. Images, media and fonts are aborted at the route level to cut bandwidth. The native Linux-Firefox user agent is deliberately left in place.

Success is never decided by HTTP status, because the Akamai interstitial is served with HTTP 200. Instead every response must satisfy a content gate: a property page counts only once its structured-data property blob parses, and a search page only once it carries listing cards, its result header, and its card count has stopped growing between two consecutive polls — so a page still streaming in cards cannot truncate discovery. A response matching an explicit Akamai block marker, or failing its gate within the wait window, triggers a fresh sticky exit IP and another attempt, up to 6 IP rolls per page. A real HTTP 404 is returned immediately as the site's own answer instead of burning rolls on it. If 3 pages in a row exhaust every roll, the Actor concludes the site is hard-blocking, stops cleanly, and logs how many URLs were skipped.

The proxy input, honestly

proxyConfiguration is only partly honoured, and it is worth stating plainly:

• US Residential is enforced. The Actor builds its proxy configuration with the RESIDENTIAL group and country code US regardless of what you selected, because nothing else clears Akamai on this site.
• The Use Apify Proxy toggle and group selection are ignored. Turning the toggle off, or picking datacenter, changes nothing.
• Custom proxyUrls are used when supplied. Paste your own proxy URLs and the Actor uses those instead, rotating through them on each IP roll. If they cannot be initialised, it logs a warning and falls back to Apify US Residential.

What happens when a page cannot be read

Nothing is silently dropped and nothing unreadable is billed. Every target that fails produces an uncharged accounting row with the same column set as a result row and a typed errorReason:

errorReason	Meaning
blocked	Every IP roll returned a block marker or an incomplete page
http_404	Apartments.com answered 404 — the property or slug does not exist
navigation_failed	The browser could not complete navigation within the timeout
engine_exhausted	The run had already stopped after 3 consecutive total failures; remaining URLs are recorded, not fetched
fetch_failed	Fetch failed without a more specific reason
parse_failed	The page loaded but no property id could be read from it
unsupported_page_template	The page yielded an id but no property name and no address — an unrecognised template, never charged as a result

The Actor is on pay-per-event pricing and charges exactly one row_result event per successfully parsed property. Error rows are pushed with errorReason set and are never charged, so filtering them out is a single condition — row.get("errorReason") is None in Python, errorReason == null in a dataset filter.

⬇️ Input

Every parameter below is read from .actor/input_schema.json. None of them is marked required. In practice you need at least one target: startUrls, search, or both.

Parameter	Required	Type	Description	Example Value
startUrls	No	array	Apartments.com URLs in bulk — property URLs and/or location-search and map URLs (with ?bb=…), mixed freely. The Actor auto-detects which is which. Plain strings and { "url": "..." } objects are both accepted. Prefilled with one Brookline search URL.	["https://www.apartments.com/brookline-ma/"]
search	No	string	A free-text query — city, neighborhood or ZIP code. Converted into an Apartments.com search URL and crawled like any other start URL. Nullable.	"Brookline MA"
maxItems	No	integer	Total property rows to return across all URLs. 0 means unlimited. Minimum 0, maximum 10000. Default 10.	25
endPage	No	integer	Last search-results page to crawl. 0 paginates until results run out, up to Apartments.com's own 28-page cap. Minimum 0, maximum 28. Default 0. Nullable.	3
requestDelay	No	integer	Pause in seconds before each page load, plus a small random jitter. Raise it if you see repeated bot challenges. Minimum 0, maximum 30. Default 1.	1
proxyConfiguration	No	object	Apify Proxy settings. US Residential is enforced; the Use Apify Proxy toggle and group selection are ignored. Custom proxyUrls are used instead when supplied. Default {"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"]}.	{"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"]}

⚠️ Apartments.com caps a paginated search at 28 pages. That is the site's own limit, not the Actor's, which is why endPage maxes out at 28 and why endPage: 0 paginates only up to that ceiling. Each results page holds up to 40 property cards. To reach inventory beyond the cap, split your search into several narrower URLs — by neighborhood, bedroom count or price band — instead of paging deeper.

Common pitfall: maxItems: 0 means unlimited, not zero. A run with maxItems: 0 keeps queueing properties until the page set is exhausted or endPage stops it. Set maxItems: 1 for a smoke test, not 0.

What a run with no target does: if startUrls contains no valid Apartments.com URL and search is empty, the Actor logs No valid Apartments.com URLs and no search term provided - nothing to do and exits cleanly. No browser is launched, no rows are pushed, nothing is charged. A search value that cannot be turned into a URL slug logs a warning and is skipped the same way. Note that startUrls arrives prefilled in the Console, so this state usually only happens if you clear the field deliberately or call the Actor over the API with an empty input.

Example input

{
  "startUrls": [
    "https://www.apartments.com/brookline-ma/2-bedrooms/",
    "https://www.apartments.com/sobe-apartment-rentals-miami-beach-fl/26xc7jb/",
    "https://www.apartments.com/?bb=0nijpwq7qH0t1s0oB"
  ],
  "search": "Miami Beach FL",
  "maxItems": 25,
  "endPage": 3,
  "requestDelay": 1,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"]
  }
}

⬆️ Output

One dataset row per property, with the same 13 top-level keys in the same order on every row, run after run — including on error rows, which share the result row's column set so they render in the dataset views instead of appearing as a foreign-shaped diagnostic record. Values are typed: strings, integers, floats, booleans, arrays and plain nested objects. Nothing is derived or estimated — a value the page does not publish comes back as null, an empty array, or null inside its nested object.

Rows are pushed the moment each property is parsed, so the dataset fills while the run is still going. Export as JSON, CSV or Excel, or read the dataset through the Apify API. The Output tab opens on an Overview view, with Location, Rent and Transit tabs that narrow the columns to those sections.

Example output

A successful property row:

{
  "id": "wqc416h",
  "propertyName": "Forte at 1440 Beacon",
  "url": "https://www.apartments.com/forte-at-1440-beacon-brookline-ma/wqc416h",
  "breadcrumbs": ["Massachusetts", "Brookline", "Forte at 1440 Beacon"],
  "lastUpdated": "5/13/2026 11:39:31 AM",
  "location": {
    "fullAddress": "1440 Beacon St, Brookline, MA 02446",
    "state": "Massachusetts",
    "city": "Brookline",
    "neighborhood": "Brookline",
    "postalCode": "02446",
    "streetAddress": "1440 Beacon St"
  },
  "coordinates": {
    "latitude": 42.34103,
    "longitude": -71.13512
  },
  "rating": 3.7,
  "isVerified": true,
  "rent": {
    "min": 2910,
    "max": 6500
  },
  "transportation": [
    {
      "name": "Tappan Street Station",
      "drive": "3 min",
      "distance": "0.4 mi",
      "url": "https://www.apartments.com/transit/ma/brookline/tappan-street-station/8n7kq2v/"
    },
    {
      "name": "Brookline Village Station",
      "drive": "6 min",
      "distance": "1.1 mi"
    }
  ],
  "errorReason": null,
  "scrapedAt": "2026-07-25T09:14:07Z"
}

An uncharged accounting row for a target that could not be read — same keys, errorReason set:

{
  "id": null,
  "propertyName": null,
  "url": "https://www.apartments.com/the-hudson-brookline-ma/x9v2m4q",
  "breadcrumbs": [],
  "lastUpdated": null,
  "location": null,
  "coordinates": null,
  "rating": null,
  "isVerified": null,
  "rent": null,
  "transportation": [],
  "errorReason": "blocked",
  "scrapedAt": "2026-07-25T09:15:22Z"
}

How does it work?

Apartments.com serves its pages through Akamai Bot Manager, which refuses static HTTP clients outright. So Apartments.com Scraper drives a real Playwright Firefox browser through an Apify US-residential exit IP, warms the session up on the homepage, then visits your targets one at a time on that same sticky IP.

Search and map URLs are resolved into individual property URLs first. Because the results page streams its cards in progressively, the Actor waits for the card count to stop growing before reading it, so discovery is never truncated halfway through a page. Each property page is then accepted only once its structured-data property blob parses — the last block to arrive on the document — and the row is parsed from the site's own published data rather than from fragile visual selectors, with both the multi-unit and single-unit templates handled.

Only publicly visible listing data is collected. No account, cookie or session is used. Field names and types stay the same regardless of how Apartments.com restyles its pages, so your downstream code does not move when the site does.

Integrations

Apartments.com Scraper is an Apify Actor, so it works with anything that can call the Apify API or consume a dataset — your own code, no-code automation platforms, and Apify's own schedules and webhooks.

Calling Apartments.com Scraper programmatically

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")

run = client.actor("<YOUR_USERNAME>/apartments-com-scraper-pay-per-events").call(run_input={
    "startUrls": ["https://www.apartments.com/brookline-ma/2-bedrooms/"],
    "maxItems": 50,
    "endPage": 3,
})

for row in client.dataset(run["defaultDatasetId"]).iterate_items():
    if row.get("errorReason") is None:
        rent = row["rent"]
        print(row["propertyName"], rent["min"], rent["max"], row["location"]["city"])

Works in Go, Ruby, Node.js, cURL — any language that can make an HTTP request. The errorReason is None check is what separates charged result rows from uncharged accounting rows.

Scheduling and webhooks

Attach an Apify schedule to run the same search URLs nightly or weekly, which is the pattern for rent-change tracking: each run writes its own dataset, and id plus scrapedAt give you a clean join key for diffing. Add an Apify webhook on run success to POST the dataset id to your own endpoint, so a completed run can trigger a load into your warehouse without polling.

No-code tools (n8n, Make, LangChain)

In n8n, use the Apify node — or an HTTP Request node pointed at the Actor's run endpoint with your token — and pass the same JSON input shown above; an IF node on errorReason splits clean rows from error rows. In Make, use the Apify module with run-and-wait and map the dataset output straight into a Google Sheets or Airtable step. In LangChain, wrap the run call as a tool: the rows are already typed JSON, so the tool output needs no parsing before it reaches the model.

Is it legal to scrape Apartments.com rental listings?

Scraping publicly listed rental property data is broadly treated as permissible where the data is accessible without authentication, and Apartments.com Scraper collects only what an anonymous visitor already sees on the property page.

The output is property and business records: building names, street addresses, advertised rent bands, coordinates, the site's own rating and badge, and nearby transit stops. These are not personal data — there is no person in the row, no renter, no contact detail, no reviewer identity — so GDPR and equivalent personal-data regimes do not attach to this output the way they would to a profile scraper.

What does apply is contractual and database-related: Apartments.com's terms of service, and any local database-rights or unfair-competition rules covering systematic reuse of a compiled listings catalogue. Consult legal counsel before republishing extracted listings as a competing rental catalogue, or before reselling them as a standalone dataset.

❓ Frequently asked questions

What Apartments.com property fields does Apartments.com Scraper return?

The five most used are propertyName, location.fullAddress, rent (min/max), coordinates (latitude/longitude) and rating. Thirteen top-level keys are returned in total, including the nested location, coordinates, rent and transportation structures — see the data fields table above for all of them.

Does Apartments.com Scraper require an Apartments.com account or login?

No. No account, no cookie, no session. The Actor browses anonymously and reads only public property pages. The one credential you need is your Apify token.

How many properties can I extract in one run?

maxItems accepts up to 10,000 and is a total across every URL you supply. The practical ceiling per search URL is set by Apartments.com, not by the Actor: a paginated search stops at 28 pages, and each page holds up to 40 property cards. To go wider, supply several narrower search URLs in one run — by neighborhood, bedroom count or price band.

What happens if a property page is blocked, removed or uses an unrecognised template?

You still get a row, and you are not charged for it. Blocked pages are retried on fresh residential exit IPs — up to 6 rolls — and if the page still cannot be read, the Actor writes an accounting row with the same columns and a typed errorReason: blocked, http_404, navigation_failed, engine_exhausted or fetch_failed. A page that loads but yields no property id becomes parse_failed; one that yields an id but no name and no address becomes unsupported_page_template. Only errorReason: null rows are charged, so filter on row.get("errorReason") is None and your dataset still accounts for every URL you submitted.

Can I scrape multiple Apartments.com locations at once?

Yes. startUrls is a list and accepts property URLs, location-search URLs and map/bbox URLs mixed together — the Actor detects each shape and crawls it accordingly. search adds one more location on top as free text. maxItems caps the combined row total across all of them.

Why does location.neighborhood sometimes repeat location.city?

Because it is the breadcrumb parent locality, not a guaranteed sub-city neighborhood. When Apartments.com's breadcrumb trail has a neighborhood level, that is what you get; when it does not, the parent is the city and the two fields match. This is deliberate: the site publishes a neighborhood name elsewhere in its metadata too, but that node is missing on a minority of properties even on a complete capture, and mixing the sources would make the column mean different things from row to row. Read breadcrumbs if you want the full hierarchy the value came from.

Does Apartments.com Scraper work with Claude, ChatGPT and other AI agent tools?

Yes. It is callable as a standard HTTP endpoint through the Apify API, so LangChain, CrewAI, n8n or a hand-written tool definition can invoke it and receive typed JSON with no parsing step. Rows are pushed live, so a long run can be read while it is still going.

How does Apartments.com Scraper compare to other Apartments.com scrapers?

Checked on the Apify Store on 25 July 2026, the three most visible alternatives take different angles. epctex/apartments-scraper is the most used and documents by far the widest output — beds, baths, sqft, amenities, fees, schools, floor-plan models, photos and a contact phone — but its README now opens with a banner stating the Actor is no longer working due to new security protections on Apartments.com, and directs users to a separate pay-per-event Actor instead. arlusm/apartments-scraper documents a compact nine-field row (id, title, address, pricing, beds, amenities, phone, url, imageUrl) and a proxyCountryCode input defaulting to FR. pro100chok/apartments-scraper-usage documents a three-step chained pipeline — search, then details with 90+ fields, then email extraction from property websites — states a maximum of 18 search pages per query on its listing, and describes using a TLS-impersonation client rather than a browser.

Apartments.com Scraper is narrower on fields by design and explicit about the parts the others do not document: a real Firefox browser on enforced US residential proxy as the engine, a render-completion gate instead of an HTTP-status check, auto-detection of property, search and map/bbox URLs in one list, and per-item uncharged error rows with a typed errorReason. If you need floor plans, amenities, photos or leasing emails, one of the above is the better fit; if you need dependable building-level rent, address, coordinates and transit with honest accounting, this one is.

What happens when Apartments.com changes its layout or anti-bot system?

The scraper is maintained, and it is deliberately built to absorb layout change: rows are parsed from the page's own published structured data and address block rather than from deep CSS selectors, and both the multi-unit and single-unit templates are handled. Anti-bot changes are handled at the engine level — block detection keys on explicit Akamai markers, and unreadable pages degrade into typed, uncharged error rows rather than silently corrupting your dataset. Your field names and types stay the same on your end.

Can I use Apartments.com Scraper without managing proxies or browser infrastructure?

Yes — that is the point of running it on Apify. The Actor launches and tears down its own Playwright Firefox browser, warms up the session, and requests US-residential sticky sessions from Apify Proxy, rolling a fresh exit IP whenever a page comes back blocked. You never install a browser, create a proxy account or rotate an IP. If you already have residential egress, paste it into proxyConfiguration as custom proxyUrls and the Actor uses that instead.

Which Apartments.com fields work best for AI training data and RAG indexing?

For RAG indexing: propertyName, location.fullAddress, breadcrumbs and the name values inside transportation carry the most descriptive text per property and chunk cleanly by city. For training data or analytics: rent.min, rent.max, rating, isVerified, coordinates.latitude and coordinates.longitude are the most structurally consistent fields across records. Everything returns as typed primitives, arrays or plain nested objects, so no normalization pass is needed before indexing — and because unpublished values are null rather than zero, you can drop incomplete records without misreading a 0 as a real rent.

🔗 Related scrapers

Scraper Name	What it extracts
Realtor.com Agents Scraper	US real estate agent and brokerage profiles
Booking Scraper	Accommodation listings with prices, ratings and location
Google Maps Scraper with Reviews Sentiment Analysis	Local business listings, coordinates and review sentiment
Google News Scraper by Publisher Site Filter	News coverage for a market, filtered by publisher
Twitter Trends Scraper	Trending topics for timely market and location research

💬 Your feedback

Found a bug, or need a field that is on the Apartments.com property page but not in the output — floor plans, amenities, photos? Open an issue on the Actor's Issues tab and it will be looked at. Reports that include the exact input JSON and the property URL that misbehaved are the fastest to reproduce and fix.