Airbnb Images Scraper By Location

Airbnb Images Scraper by Location — Photos, Ratings & Coordinates

Airbnb Images Scraper by Location extracts listing photos, ratings, and structured details straight from Airbnb search results — give it a city or neighborhood and skip collecting room URLs by hand. Each run returns listing title, location, rating, review count, room type, coordinates, and every image URL exposed on the page, delivered as clean, typed JSON ready to pass to an LLM, load into a spreadsheet, or feed into an image pipeline. Direct room URLs work too, alongside or instead of location discovery.

What is Airbnb Images Scraper by Location?

Airbnb Images Scraper by Location is a location-driven Airbnb scraper: you give it a city, neighborhood, free-text search query, or an exact Airbnb search-results URL, and it discovers matching listings and pulls their images and details automatically. It also accepts specific room URLs directly, so you can mix discovery with known listings in the same run. No Airbnb account or login is required — the Actor fetches public listing and search pages the same way a visitor's browser would.

Key capabilities:

• 📍 Discover listings from a city, neighborhood, or free-text location query — no need to know room URLs in advance
• 🔎 Or supply an exact Airbnb search-results URL for precise control over the discovery page
• 🔗 Add specific room URLs directly, combined with or instead of location discovery
• 🖼️ Extract every image URL exposed in each listing's structured data, up to a configurable cap per listing
• ⭐ Capture rating, review count, room type, and geocoordinates alongside each listing
• 🛡️ Automatic escalation to Apify Proxy on blocked or failed requests, with retries

What data can you get with Airbnb Images Scraper by Location?

Every run returns per-listing detail records and the images tied to each one.

Result Type	Extracted Fields	Primary Use Case
Listing details	id, title, location, rating, reviews, roomType, coordinates, url	Building a structured directory of listings in a market
Listing images	images, imageCount	Sourcing property photos tied to metadata for cataloguing or ML pipelines

Listing images

Every listing record carries its own images array — the full list of image URLs Airbnb embeds in the listing page's JSON-LD structured-data block, capped at maxImagesPerListing (default 50, maximum 300). imageCount reports how many were kept. Because Airbnb's JSON-LD typically exposes fewer photos than a visitor could scroll through in the app or website gallery, imageCount is usually well under the cap you set — raising maxImagesPerListing further rarely returns more images for a given listing.

{
  "images": [
    "https://a0.muscache.com/im/pictures/miami-listing-1-large.jpg",
    "https://a0.muscache.com/im/pictures/miami-listing-2-large.jpg"
  ],
  "imageCount": 2
}

Why not build this yourself?

Airbnb does not publish a public API for searching listings or reading listing details — the only way to get this data is by fetching and parsing the same pages a browser loads. Airbnb Images Scraper by Location handles that surface for you: it converts a location into a working search URL, decodes the base64-encoded listing IDs that modern Airbnb search-results pages embed instead of literal room links, parses each listing's JSON-LD block for title, rating, coordinates and images, and escalates to Apify Proxy automatically when a page comes back blocked. Building and maintaining this yourself means tracking Airbnb's markup and anti-bot changes indefinitely, sourcing and rotating your own proxies, and re-implementing retry logic — all before you get a single row of data.

How to scrape Airbnb listings by location with Airbnb Images Scraper by Location?

1. Open Airbnb Images Scraper by Location in the Apify Console (or find it on the Apify Store and click Try for free).
2. Enter a location or search query in locationQuery — e.g. Miami Beach — or paste an exact Airbnb search URL into searchUrl.
3. Set maxListings (1–200) to cap how many listings to discover, and maxImagesPerListing (1–300) to cap images kept per listing. Optionally add specific urls to pull direct room pages in the same run.
4. Start the run.
5. Download results as JSON, CSV, Excel, or another supported dataset export format from the run, or pull them via the Apify API.

Example input:

{
  "locationQuery": "Miami Beach",
  "maxListings": 20,
  "maxImagesPerListing": 50
}

How to run multiple queries in one job

locationQuery and searchUrl each accept a single query per run — there is no array input for scraping several locations in one job. To cover multiple cities or neighborhoods, start a separate run per location (for example, looping over locations with the Apify API or apify-client, or scheduling one run per query). Within a single run, you can still combine one location query with a list of specific urls — those direct room URLs are scraped alongside whatever the location discovery finds.

⬇️ Input

Provide a location query, an exact search URL, a list of direct room URLs, or any combination — at least one of locationQuery, searchUrl, or urls must be set, or the run fails validation before starting.

Parameter	Required	Type	Description	Example Value
locationQuery	No	string	A city, neighborhood, or free-text search query to discover Airbnb listings in. The Actor builds an Airbnb search URL from this and harvests matching listing URLs automatically. Leave empty if you provide searchUrl or urls instead.	"Austin Texas"
searchUrl	No	string	An exact Airbnb search-results URL to use for discovery instead of building one from locationQuery. Must start with https://www.airbnb.com/s/. Takes precedence over locationQuery when both are set.	"https://www.airbnb.com/s/Miami-Beach--FL/homes"
maxListings	No	integer	Maximum number of listings to discover from the location/search URL and scrape. Default: 20. Minimum: 1. Maximum: 200.	20
maxImagesPerListing	No	integer	Maximum number of image URLs to keep per listing, applied to discovered listings and direct urls alike. Default: 50. Minimum: 1. Maximum: 300.	50
urls	No	array of strings	One or more specific Airbnb room URLs to scrape directly, in addition to anything discovered via locationQuery/searchUrl. Each must be a valid room page URL (https://www.airbnb.com/rooms/...). Default: [].	["https://www.airbnb.com/rooms/782682596976136912"]
requestTimeoutSecs	No	integer	Maximum time in seconds to wait for each HTTP response before the request is skipped. Default: 30. Minimum: 5. Maximum: 120.	30
proxyConfiguration	No	object	Apify Proxy settings for this run: useApifyProxy (boolean), apifyProxyGroups (array of strings), apifyProxyCountry (ISO-2 country code string). Default: {"useApifyProxy": false}.	{"useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"]}

Common pitfall: searchUrl is validated against https://www.airbnb.com/s/ — a room URL, a shortened link, or a search URL missing that exact prefix fails validation before the run starts. The same applies to each entry in urls, which must match https://www.airbnb.com/rooms/....

⚠️ Discovery reads one search-results page, not infinite scroll. maxListings sets an upper bound (up to 200), but the Actor fetches the search URL once and extracts whatever listing IDs Airbnb embeds in that single HTML response — it does not paginate or scroll for more. The number of listings actually discovered depends on how many Airbnb embeds on that first page, which is often well below 200 even when maxListings is set higher.

⬆️ Output

Results are typed, normalized JSON with a consistent schema across runs, available from the dataset as JSON, CSV, Excel, or any other export format the Apify platform supports.

Scraped results

[
  {
    "url": "https://www.airbnb.com/rooms/782682596976136912",
    "id": "782682596976136912",
    "title": "Oceanfront Studio Steps from the Beach",
    "location": "Miami Beach, FL, US",
    "rating": 4.87,
    "reviews": 214,
    "roomType": "Entire rental unit",
    "coordinates": { "lat": 25.7907, "lng": -80.13 },
    "images": [
      "https://a0.muscache.com/im/pictures/miami-1-large.jpg",
      "https://a0.muscache.com/im/pictures/miami-2-large.jpg"
    ],
    "imageCount": 2
  },
  {
    "url": "https://www.airbnb.com/rooms/611234567890123456",
    "id": "611234567890123456",
    "title": "Modern Downtown Loft with City Views",
    "location": "Austin, TX, US",
    "rating": 4.92,
    "reviews": 87,
    "roomType": null,
    "coordinates": null,
    "images": [
      "https://a0.muscache.com/im/pictures/austin-1-large.jpg"
    ],
    "imageCount": 1
  },
  {
    "url": "https://www.airbnb.com/rooms/598765432109876543",
    "id": "598765432109876543",
    "title": "Cozy Cottage Near the Trailhead",
    "location": null,
    "rating": null,
    "reviews": null,
    "roomType": "Private room",
    "coordinates": { "lat": 39.7392, "lng": -104.9903 },
    "images": [],
    "imageCount": 0
  }
]

Fields the source page doesn't provide (an address component, a rating, coordinates) come back as null rather than a fabricated value.

When a listing page fails to fetch or has no parseable structured data, the Actor pushes a minimal record instead of a full row:

{ "url": "https://www.airbnb.com/rooms/000000000", "error": "Fetch failed after retries" }

Only successfully extracted listings are billed, under the row_result charged event. Failed fetch/extraction rows are stored in the dataset for visibility but are not charged — filter them out by keeping items that have an id field, or by excluding items where error is present.

How can I use the data extracted with Airbnb Images Scraper by Location?

• 🏠 Vacation rental hosts and property managers: benchmark how competing listings in your market present themselves — image counts, room types, and rating/review levels — to spot gaps in your own listing.
• 📊 Real estate and travel market researchers: plot listing density, room-type mix, and ratings across neighborhoods using the coordinates and location fields.
• 🤖 AI engineers and LLM developers: ground a travel or rental research agent with live, structured Airbnb data instead of stale training data.
• 🖼️ Content and marketing teams: source structured photo sets and listing details for city or neighborhood roundups, respecting Airbnb's Terms of Service and each photo's copyright.

How do you monitor Airbnb listings in a location over time?

Monitoring here means re-running the same location or search query on a schedule and comparing what comes back against the previous run, rather than treating each run as a one-off snapshot. Because listing IDs, ratings, and review counts change as a market moves, diffing two runs surfaces what actually changed: new id values that weren't in the previous run indicate new inventory; ids that disappear suggest a listing was removed or delisted; and rising reviews or a shifting rating on an existing id show a listing gaining or losing traction. imageCount changes can also flag when a host refreshes their listing photos.

A practical workflow: schedule a run of the same locationQuery (or a fixed list of searchUrls covering several neighborhoods) at a regular interval, store each run's dataset, and diff the current set of id, rating, reviews, and imageCount values against the previous run's. Alert on the deltas that matter to you — a new competitor listing appearing, or an existing listing's rating dropping.

Airbnb Images Scraper by Location has no built-in diffing — set up the repeated runs using Apify's Schedule feature in the Console or API, and do the comparison in your own pipeline against the stored dataset from each run.

Integrate Airbnb Images Scraper by Location and automate your workflow

Airbnb Images Scraper by Location works with any language or tool that can send an HTTP request.

REST API with Python

from apify_client import ApifyClient

client = ApifyClient("<APIFY_API_TOKEN>")
run = client.actor("<your-username>/airbnb-images-scraper-by-location").call(
    run_input={"locationQuery": "Austin Texas", "maxListings": 20}
)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    if "error" not in item:
        print(item["title"], item["imageCount"])

Scheduled monitoring and delivery

Attach an Apify Schedule to run Airbnb Images Scraper by Location automatically at a fixed interval from the Console or API — no manual restarts needed. Each run's dataset is retrievable via the Apify API or apify-client immediately after it finishes; the Actor itself does not push results to a webhook, but the Apify platform's dataset and run-level webhooks can be attached from the Console if you want a push notification when a run completes.

⚖️ Is it legal to scrape Airbnb listings and images?

Yes — scraping publicly accessible Airbnb pages for data any visitor's browser can already see is generally lawful, subject to Airbnb's own Terms of Service. Airbnb Images Scraper by Location returns only listing details and image URLs already published on the public listing page — no host or reviewer profile data is extracted, so GDPR and CCPA's personal-data provisions generally do not attach to the fields this Actor returns. The frameworks that do apply are Airbnb's Terms of Service, which restrict automated access, and, in some jurisdictions, database or copyright rights the property owner or photographer may hold over the compiled listing content and photos. Scraping for a one-off research report and scraping to build a dataset for AI training or resale carry different risk profiles. Consult your legal team for commercial use cases involving bulk data storage.

❓ Frequently asked questions

How many listings does Airbnb Images Scraper by Location return per search?

Up to maxListings (default 20, maximum 200) — but discovery reads only the single search-results page Airbnb returns for that query; it does not paginate. The number of listings actually found is capped by however many listing IDs are embedded on that one page, which is often below the maxListings value you set.

How many images does it return per listing?

Up to maxImagesPerListing (default 50, maximum 300) per listing. In practice the actual count is bounded by how many images Airbnb's JSON-LD structured-data block exposes for that listing, which is usually fewer than the cap.

Does Airbnb Images Scraper by Location support pagination or infinite scroll on the search-results page?

No. It fetches the search URL once and extracts whatever listing IDs are embedded in that single HTML response, then stops at maxListings. It does not simulate scrolling or request additional search pages.

How does Airbnb Images Scraper by Location handle Airbnb's anti-bot measures?

It starts with a direct request unless proxyConfiguration.useApifyProxy is enabled, checks each response for block signals (HTTP 401/403/429/5xx, or page text like "access denied," "bot detection," or a CAPTCHA prompt), and automatically escalates to Apify Proxy — defaulting to the RESIDENTIAL proxy group if none is specified — on the first failure or block. Once escalated, it retries a failed request up to 3 times and stays on proxy for the rest of the run.

Can I scrape specific Airbnb room URLs instead of a location?

Yes — add them to urls. They're scraped directly and combined with anything found via locationQuery or searchUrl, with duplicates removed.

Can I use Airbnb Images Scraper by Location without managing my own proxies?

Yes. No Airbnb account or login is required, and proxy handling — including escalation to Apify Proxy on blocks — is automatic. You only need an Apify account to run the Actor.

What happens if a listing page fails to load or has no structured data?

The Actor pushes a {"url": ..., "error": ...} record to the dataset instead of dropping the listing silently, so failures stay visible. These error rows are not billed — only listings that push a full record under the row_result event are charged.

How do I monitor listings in a location over time?

Schedule repeated runs of the same locationQuery or searchUrl using Apify's Schedule feature, then diff the id, rating, reviews, and imageCount fields between consecutive runs to catch new listings, delisted ones, and rating or review changes. See "How do you monitor Airbnb listings in a location over time?" above.

Does Airbnb Images Scraper by Location work with Claude, ChatGPT, and AI agent frameworks?

It's callable as an HTTP endpoint via the Apify API or apify-client from any agent framework that can make a request and parse JSON — an agent can trigger a run for a location, wait for the dataset, and use the listing and image data as grounded context for its answer.

💬 Your feedback

Found a bug or missing a field? Let us know — open an issue from the Actor's page in Apify Console, or reach out through Scrapier's Store listing. Feedback like this shapes what gets fixed and built next.