Airbnb Scraper

Airbnb Scraper API extracts public Airbnb listing data without an Airbnb API key, which does not exist for developers. It returns 99 fields per property — nightly and total price as numbers, all six rating categories, host details, amenities, day-by-day availability and guest reviews — from any city, region or room URL, as JSON, CSV or Excel.

99 fields per listing, with the availability calendar in the same run

Airbnb has no public API, so most Airbnb scrapers hand you the search card: a title, a price label and a rating. This one opens every property page and returns the price broken down line by line as a number you can sort on, all six rating categories, the host, every amenity, day by day availability, and every guest review if you ask for them.

You pay per listing returned. Walking the search pages to find a property is free, because finding one is not a product. Search mode returns card-level records, billed per search result. The prices for each, and the discounts your Apify plan earns, are on the Pricing tab of this page.

Listings that fail are free too. If a property has been pulled, or Airbnb refuses the request, you get a record with the id, the url and what went wrong, and you are not billed for it.

Reviews are billed per review, and off unless you ask. A busy property carries several hundred, so folding them into the listing price would charge everyone for something plenty of callers do not want. Turn on include_reviews and you get every review a listing has, up to the cap you set.

Measured, not claimed

Every number on this page comes from a run, on the date given, not from a spec sheet.

What	Measured	When
Fields per listing	99	1 Sep 2026
Currencies	28, each run against Airbnb and returning that currency	2 Sep 2026
Languages	18, each run and returned translated	2 Sep 2026
Default run	20 listings, all 99 fields, 22 seconds	2 Sep 2026
Listings priced	9 of 10 in Paris, Chamonix and Aspen alike	2 Sep 2026
Billing	8 listings and 80 reviews delivered, 8 and 80 charged	1 Sep 2026

Pass the dates you care about, because Airbnb quotes a different price for every stay.

Airbnb data export: 99 fields, in tabs you can read

A record this wide is unreadable as one table, so the dataset arrives grouped. Seven tabs above your results, each answering one question:

Tab	What it answers
Listings	The whole picture: photo, name, city, type, capacity, all three prices with the stay they were quoted for, rating, review count, Guest Favourite, Superhost, occupancy and the booking terms
Availability	The day-by-day calendar, minimum and maximum nights, days free, days blocked, occupancy rate and the next free date
Ratings & reviews	All six category scores behind the star, the rating distribution, and the reviews themselves
Host	Host and co-hosts, Superhost status, licence, whether the address is verified
Location	Coordinates and whether they are exact rather than Airbnb's privacy circle, address, neighbourhood, map link
Amenities & rules	The full amenity list by category, direct flags for the ones people filter on, house rules, cancellation terms, safety features
Description & photos	The listing's own copy, highlights, sleeping arrangements, badges and every image

Switch tabs at the top of the dataset, or export any of them to JSON, CSV or Excel. All fields shows the raw record if you would rather have everything at once.

Is there an Airbnb API?

Not a public one. Airbnb's API is closed to approved partners — channel managers and property-management software — and there is no key you can sign up for as a developer. Searching for an Airbnb API key, or for free Airbnb API access, turns up partner application forms rather than documentation you can use.

This is the practical substitute: give it a location and it walks Airbnb's search results, opens each property page, and returns one record per listing with 99 fields, through a REST API you already have credentials for. No Airbnb login, no partner application, no rate-limit negotiation. Export to JSON, CSV, Excel or HTML, or pull it straight from the API.

You can run it two ways. Full detail opens every property page and returns everything below. Search mode reads only the results pages and returns the card-level fields for each listing, billed per search result rather than per listing. Sweep a whole market in search mode, then go deep on the properties that matter.

What Airbnb data can you extract?

Every full detail record contains:

Group	Fields
Identity	id, url, name, title, subtitle, description, description language, SEO title, thumbnail, images
Location	latitude, longitude, coordinates, neighbourhood, location descriptions, and whether the coordinates are the exact spot rather than Airbnb's privacy circle
Capacity	person capacity, bedrooms, beds, bathrooms, room type, property type, home tier
Price	nightly rate and stay total as numbers, currency, original and discounted price, nights, and the breakdown line by line. Airbnb quotes all-in prices and no longer itemises cleaning or service fees, so neither does this
Ratings	guest satisfaction overall, plus accuracy, check-in, cleanliness, communication, location and value
Host	name, id, profile URL, photo, superhost and verified status, years hosting, response rate and time, rating average and count, highlights, about (co-hosts are a separate top-level field)
Amenities	the complete list, plus direct flags for wifi, air conditioning, heating, kitchen, parking, washer, dedicated workspace and pets
Reviews	reviewer, date, rating, review text, highlights and the host response, up to a limit you set
Availability	day by day calendar, minimum and maximum nights, and from today on: days total, days available, days blocked and occupancy rate
Rules and policies	house rules, cancellation policy, check-in and check-out times, self check-in, smoking, parties, commercial photography, licence number
Metadata	instant book, highlights, scraped_at timestamp

Search mode returns what the result card carries: id, url, name, title, subtitle, thumbnail, images, latitude, longitude and coordinates, nightly rate, stay total and original price as numbers, nights, the price label and breakdown, the check_in and check_out it was quoted for, rating, review count, Superhost, badges and the scraped_at timestamp. Room type, capacity and everything else below the card are full-detail fields.

Airbnb prices as numbers, not screenshots of numbers

A price label tells you what a listing asks. "$2,119 for 5 nights" is a string; 2119 and 423.63 are numbers you can sort, filter and average. This returns the nightly rate and the stay total as numbers, the pre-discount price where a stay is discounted, and whether the listing can actually be booked for those dates at all — seven of eight listings sampled in one city could not be.

Ratings work the same way. An overall 4.9 hides whether guests marked a place down on cleanliness or on value, and six category scores tell you which.

Then there is the calendar. Nightly rates alone tell you what a market advertises. Rates with occupancy tell you what it books.

Airbnb API pricing: what a run costs

You are billed per event, at the prices on the Pricing tab of this page:

Event	When it is billed
Listing	Each full-detail record returned, with its calendar
Search result	Each card-level record returned in search mode
Review	Each guest review returned, when you ask for them
Search page	Each search results page walked — free

Volume discounts follow your Apify plan.

Reviews are the one line that depends on the properties rather than on how many you asked for. A busy listing carries a couple of hundred, so pulling all of them costs far more than the listing itself; max_reviews_per_listing caps it. If you are budgeting a run, this is the number to look at twice.

Why pay per event

You are charged for listings the scraper returns, not for the work it did to find them. Paginating a city of 240 listings takes about 14 search pages and costs nothing.

Failures are free as well. A removed property, or one Airbnb refuses to serve, still comes back as a record carrying the id, the url and what happened, and that record is not billed. You pay for listings you can use.

How to scrape Airbnb listings without an API key

1. Add the locations you want under location_queries, or paste listing URLs into start_urls.
2. Set check_in and check_out for the stay you care about. Airbnb quotes a different rate for every stay, so leaving them empty prices a single night a month out instead — every record reports the check_in and check_out it was priced for.
3. Choose mode. Use full for complete property data, search for a quick sweep of the result cards.
4. Set max_listings to cap the run. Turn on include_reviews if you want reviews, and max_reviews_per_listing to bound how many of them you pay for.
5. Start the run. Results appear in the dataset while the run is still going, so you can begin reading before it finishes.

Input

Search one city or many

Each location becomes its own search and all of them merge into a single dataset. Covering ten cities takes one run rather than ten.

{
  "location_queries": ["Porto, Portugal", "Lisbon, Portugal", "Braga, Portugal"],
  "mode": "full",
  "max_listings": 500
}

Set dates, guests and prices

Airbnb prices depend on the stay, so pass the nights you care about. Guest counts change both the price and which listings appear.

{
  "location_queries": ["Barcelona, Spain"],
  "check_in": "2026-09-10",
  "check_out": "2026-09-15",
  "adults": 2,
  "children": 1,
  "price_min": 80,
  "price_max": 300
}

Scrape Airbnb from another country

Airbnb ranks results and shows prices and availability differently depending on where you browse from. A Paris search seen from France is not the same result set as the one you get from a US connection — different ordering, different totals, sometimes different listings.

proxy_country picks the country to browse from. 23 markets are supported:

{
  "location_queries": ["Paris, France"],
  "proxy_country": "FR"
}

Europe	United Kingdom, France, Germany, Spain, Italy, Portugal, Netherlands, Poland, Sweden, Denmark, Austria, Ireland, Greece, Turkey
Americas	United States, Canada, Brazil, Mexico
Asia-Pacific	Japan, South Korea, India, Singapore, Australia

Leave it empty and the market follows the language you chose, so locale: "de-DE" browses Germany. Set both when you want them to differ — an English-speaking buyer researching the German market, for example.

The scraper follows Airbnb's own country sites, so a German market run reads airbnb.de and returns what a visitor there actually sees. China and Russia are not offered: Airbnb withdrew from both, and a search from either returns nothing. Russian and Chinese are still offered as languages, and left to follow the language they browse the United States.

Scrape specific listings

Skip search entirely when you already know the properties. start_urls accepts room URLs and bare listing ids in the same list.

{
  "start_urls": [
    "https://www.airbnb.com/rooms/691479",
    "https://www.airbnb.com/rooms/1478285053144011262",
    "1733326288002241501"
  ],
  "mode": "full"
}

Filter what comes back

{
  "location_queries": ["Lisbon, Portugal"],
  "room_types": ["Entire home/apt"],
  "property_types": ["Apartment", "Loft"],
  "min_bedrooms": 2,
  "min_bathrooms": 1,
  "min_rating": 4.8
}

Scrape Airbnb reviews and the availability calendar

The calendar comes with every full listing. Reviews are opt-in and billed per review, so ask for them when you want them — both arrive nested inside the listing record, so a property and its history stay together.

{
  "location_queries": ["Madrid, Spain"],
  "include_reviews": true,
  "max_reviews_per_listing": 20,
  "calendar_months": 3
}

max_reviews_per_listing defaults to 50, which keeps one very popular property from dominating the bill. Set it to 0 to take every review a listing has.

All input options

Option	Type	What it does
location_queries	array	Locations to search. Each becomes its own search, merged into one dataset.
start_urls	array	Room URLs or bare listing ids to fetch directly, skipping search. Give this or location_queries, not both.
mode	string	full opens every property page. search reads results pages only.
check_in, check_out	string	Stay dates, so prices reflect a real booking.
adults, children, infants, pets	integer	Guest counts. These change price and availability.
price_min, price_max	integer	Nightly price bounds.
min_beds, min_bedrooms, min_bathrooms	integer	Size filters.
room_types	array	Entire home/apt, private room, shared room, hotel room.
property_types	array	Keep only listings matching these property types.
min_rating	number	Drop listings rated below this.
max_pages	integer	Search pages to walk per location. Usually leave empty; max_listings already bounds the run.
max_listings	integer	How many listings to return. Defaults to 20; 0 takes every listing found.
include_reviews	boolean	Fetch guest reviews. Off by default; billed per review.
max_reviews_per_listing	integer	Reviews per property, at most. Defaults to 50; 0 fetches every one.
calendar_months	integer	Months of availability to pull, from today. 0 skips the calendar.
calendar_start_month, calendar_start_year	integer	Start the calendar somewhere other than today. Defaults to the current month and year.
currency	string	Prices converted to this. 28 options, each checked against Airbnb.
locale	string	Language for review dates, house rules and cancellation terms. 18 options.

Output

Table view

id	name	person_capacity	price.label	rating.guest_satisfaction	number_of_reviews
691479	Loft in Porto	5	$1,457 for 5 nights, originally $1,633	4.96	412
1478285053144011262	Apartment in Porto	4	$487 for 5 nights	4.99	128
1599392401671897626	Apartment in Porto	6	$828 for 5 nights	4.97	76

JSON

{
  "id": "691479",
  "url": "https://www.airbnb.com/rooms/691479",
  "name": "Apartreboleira. Terrace with a view",
  "room_type": "Entire home/apt",
  "property_type": "Entire loft",
  "person_capacity": 6,
  "bedrooms": 3,
  "beds": 5,
  "bathrooms": 2,
  "latitude": 41.13951,
  "longitude": -8.61515,
  "is_super_host": true,
  "price": {
    "amount": null,
    "breakdown": [],
    "currency": "USD",
    "discounted_price": null,
    "label": null,
    "original_price": null,
    "qualifier": null
  },
  "rating": {
    "accuracy": 4.97,
    "checkin": 4.98,
    "cleanliness": 4.99,
    "communication": 4.99,
    "guest_satisfaction": 4.96,
    "location": 4.99,
    "value": 4.92
  },
  "host": {
    "about": "Native from Switzerland, leaving in Porto for more then thirty years. Working as an architect (among other act...",
    "details": [
      "Superhost"
    ],
    "highlights": [
      {
        "icon": "SYSTEM_EVENTS",
        "text": "Born in the 60s"
      }
    ],
    "id": "RGVtYW5kVXNlcjozNTM0ODY0",
    "is_super_host": true,
    "is_verified": true,
    "name": "Anne"
  },
  "amenities": [
    {
      "available": true,
      "icon": "SYSTEM_VIEW_OCEAN",
      "name": "River view"
    }
  ],
  "amenity_wifi": true,
  "amenity_kitchen": true,
  "images": [
    {
      "caption": "Terrace",
      "orientation": "LANDSCAPE",
      "url": "https://a0.muscache.com/im/pictures/9221831/8034b59a_original.jpg"
    }
  ],
  "reviews": [
    {
      "collection_tag": null,
      "created_at": "2026-08-10T13:42:09Z",
      "date": "2 weeks ago",
      "highlight_type": "LENGTH_OF_STAY",
      "id": "1749297646833504458",
      "language": "en",
      "photos": [],
      "rating": 5
    }
  ],
  "availability": [
    {
      "available": false,
      "available_for_checkin": false,
      "available_for_checkout": false,
      "bookable": false,
      "date": "2026-09-01",
      "max_nights": 30,
      "min_nights": 2
    }
  ],
  "availability_days_total": 30,
  "availability_days_available": 5,
  "occupancy_rate": 0.8333333333333334,
  "min_nights": 2,
  "check_in_time": "Check-in: 3:00 PM - 11:00 PM",
  "house_rules": [
    {
      "icon": "SYSTEM_CLOCK",
      "rule": "Check-in: 3:00 PM - 11:00 PM"
    }
  ],
  "scraped_at": "2026-08-28T00:49:37.684113927Z",
  "error": null
}

What people use Airbnb data for

Property managers and hosts track what comparable listings nearby charge for the same nights, and how their occupancy compares. The availability calendar and the price breakdown together show what a market books at, rather than what it advertises.

Real estate investors screen neighbourhoods before buying by pulling every listing in an area with occupancy rates and nightly rates attached.

Travel and booking sites build inventory feeds, comparing Airbnb prices against their own.

Researchers and journalists study short term rental density in cities considering regulation, using coordinates, licence numbers and host portfolios.

Anyone doing due diligence on a host can pull their full portfolio through start_urls and check ratings, response rates and review history across properties.

How the Airbnb scraper handles blocks and failures

A listing that cannot be fetched becomes a record instead of disappearing. It carries the id and url you asked for, plus an error array explaining what happened:

{
  "id": "999999999999999",
  "url": "https://www.airbnb.com/rooms/999999999999999",
  "error": [
    {
      "scope": "listing",
      "type": "listing.state_missing",
      "message": "the detail page carried no listing state, so every field below the search card is null"
    }
  ]
}

The run carries on and finishes normally. One removed property does not cost you the other 499, and error records are not charged.

Problems that affect the whole run, such as a location Airbnb does not recognise, appear in the run summary rather than being attached to a listing.

Frequently asked questions

Do I need an Airbnb API key? No. There is no public Airbnb API to get a key for — it is restricted to approved partner integrations. This reads the same public pages a browser does, so there is nothing to apply for and no quota to negotiate.

Do I need an Airbnb account? No. The scraper reads public listing pages and needs no login or cookies.

Can I call it from Python or n8n? Yes. It is an ordinary Apify Actor, so anything that can make an HTTP request can start a run and read the dataset — the Python and JavaScript clients, n8n, Make, Zapier, or plain curl. The API tab on this page has the exact call with your token filled in.

Why are prices different from what I see on Airbnb? Airbnb quotes by stay, so the same listing has no single price. Without check_in and check_out this prices one night about a month out and tells you which night on every record. Pass your own dates and guest counts and the numbers match what a guest is shown.

Can I get every listing in a city? Airbnb caps how deep its own search goes, so no scraper can return literally every property from one query. Splitting a city into neighbourhoods or price bands and passing them as separate location_queries reaches more of the inventory.

How many reviews can I get? As many as a listing has, up to max_reviews_per_listing — 50 by default, or 0 for every one. Reviews add time, so cap it when you are sweeping a whole market.

What does search mode leave out? Everything that only exists on the property page: room type and capacity, the availability calendar, reviews, the full amenity list, host details and house rules. Search mode gives you the card: id, url, title, prices, rating, review count, coordinates, thumbnail and images.

Is the output shape stable? Fields are consistent across records. A field Airbnb does not publish for a given listing comes back null rather than being dropped, so a column that exists for one listing exists for all of them.

Can I run this on a schedule? Yes. Schedule it like any other Actor and results append to the dataset each run. The scraped_at field on every record tells you which run it came from.

Notes

This is an unofficial scraper. It is not affiliated with, authorised by, sponsored by or endorsed by Airbnb, and "Airbnb" is used only to say which public website it reads.

Prices, availability and ratings change constantly. A record is a snapshot at scraped_at, not a standing fact.

Review counts and calendar depth are the two settings that drive run length. A market sweep with reviews off and calendar_months at 1 finishes far quicker than the same sweep with every review and a year of availability.

Start scraping

Paste a city into location_queries, set check_in and check_out, and run it.