kestrel actors › Hotel & flight prices

Booking.com Scraper — Hotel Prices & Availability by Date

This Booking.com scraper is a hotel price scraper for exact dates, guests and rooms: it returns Booking.com hotel prices for every property in a destination, or for a list of hotels by URL, name or id, each as one clean row with the stay total in your currency, the nightly price, the taxes and fees Booking leaves out, free-cancellation and breakfast flags, stars, review score, location and the cheapest room. It reads the same call Booking.com's own search results page makes, so there is no browser, no login and no Booking.com API key — a way to scrape Booking.com without API access — and you pay per priced property, never for sold-out ones.

Run Booking.com Scraper on Apify →

Booking.com scraper pricing: what one row costs

$0.004 per priced hotel row and $0.002 per room row, plus nothing else: sold-out and unpriced properties, status rows, filtered rows and refused runs are free. Pricing 100 Lisbon properties is $0.40; a daily comp set of 10 hotels with room rates (say 60 rooms) is $0.16 a day. Apify's platform usage for a 100-property search is well under a cent.

Booking.com scraper input reference

Every field of Booking.com Prices, straight from the actor's input schema.

Example input

{
  "locationQueries": ["Lisbon"],
  "maxHotelsPerQuery": 100,
  "checkIn": "6 weeks",
  "nights": 2,
  "adults": 2,
  "currency": "EUR",
  "sortBy": "price"
}

{
  "hotelIds": ["536251", "2251985", "1471925"],
  "checkIn": "30 days",
  "nights": 1,
  "adults": 2,
  "currency": "USD",
  "includeRooms": true
}

Booking.com scraper output fields

One row per property with its price for the stay, optional room-rate rows, and one status row per target.

Dataset views in the Apify Console: Overview, Hotels, Cheapest first, Room rates, Status.

Example row from a real run

Taken from the actor's README — this is the shape your dataset holds.

{
  "type": "hotel",
  "hotel_id": "536251",
  "name": "Memmo Alfama - Design Hotels",
  "url": "https://www.booking.com/hotel/pt/memmo-alfama.html",
  "property_type": "hotel",
  "stars": 4,
  "review_score": 9.3,
  "review_count": 894,
  "city": "Lisboa",
  "country_code": "pt",
  "display_location": "Santa Maria Maior, Lisbon",
  "distance_from_center": "0.8 km from downtown",
  "check_in": "2026-09-28",
  "check_out": "2026-09-29",
  "nights": 1,
  "adults": 2,
  "currency": "EUR",
  "price_total": 415.09,
  "price_nightly": 415.09,
  "price_display": "€ 415.09",
  "hotel_currency": "EUR",
  "taxes_included": true,
  "free_cancellation": true,
  "breakfast_included": true,
  "room_name": "Superior Double Room with Terrace",
  "rooms_listed": 3,
  "sold_out": false,
  "rank": 1,
  "query": "Memmo Alfama Lisbon"
}

Booking.com scraper in Python, JavaScript and curl

Python

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("kestrel/booking-prices-scraper").call(run_input={
    "locationQueries": ["Lisbon"], "maxHotelsPerQuery": 50,
    "checkIn": "30 days", "nights": 1, "adults": 2, "currency": "EUR", "sortBy": "price",
})
rows = [r for r in client.dataset(run["defaultDatasetId"]).iterate_items() if r["type"] == "hotel" and r["price_total"] is not None]
for r in rows[:10]:
    print(r["rank"], r["name"], r["stars"], r["review_score"], r["price_nightly"], r["currency"], r["room_name"])

JavaScript (Node)

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('kestrel/booking-prices-scraper').call({
    hotelIds: ['536251', '2251985'], checkIn: '30 days', nights: 1, adults: 2, currency: 'USD', includeRooms: true,
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
const hotels = items.filter(r => r.type === 'hotel');
console.log(hotels.map(h => [h.name, h.price_nightly, h.free_cancellation]));

curl

curl -X POST "https://api.apify.com/v2/acts/kestrel~booking-prices-scraper/run-sync-get-dataset-items?token=<YOUR_APIFY_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"locationQueries": ["Algarve"], "maxHotelsPerQuery": 30, "checkIn": "6 weeks", "nights": 3, "adults": 2, "currency": "GBP", "sortBy": "review_score", "minStars": 4}'

The same three calls are runnable files in the examples repository: examples/booking-prices-scraper.py|.js|.sh.

Limits and honest notes

FAQ

Does it need a Booking.com API key or login?

No. It uses the same GraphQL call Booking's public search results page makes, anonymously, and only needs Apify's residential proxy group.

Can I get Booking.com hotel prices for exact dates?

Yes — that is the whole point. checkIn plus nights sets the stay; adults, childrenAges and rooms set the party; currency sets the money. Every row carries those values.

How is this different from a browser-based Booking.com scraper?

It never renders a page. A 100-property search is one request that takes about three seconds, so a market scan costs a few cents of platform time instead of minutes of browser time, and it does not break when Booking changes its page layout.

Which sort orders are repeatable?

price, price_desc, review_score, stars, stars_asc, distance and their combinations are deterministic. popularity is Booking's personalised "top picks" and moves between pages.

Can I filter by star rating or price before paying?

Yes. minStars is sent to Booking as its own filter, so those properties are never fetched; maxPrice drops rows above your nightly cap before they are billed.

Does it return room-level rates?

With includeRooms: true you get one room row per room and rate combination, billed at $0.002 each. Without it you still get the cheapest room's name on the hotel row.

What does taxes_included: false mean?

Booking lists charges it excludes from the displayed total (city tax, VAT, resort fees). taxes_fees_excluded holds their amount in your currency and charges_note Booking's wording.

Why does the same hotel come back at a slightly different price on the next run?

Booking.com prices a stay per session. Two runs seconds apart can differ by a few per cent to a quarter — the site rotates promotional rates, mobile-only deals and currency handling per session, and price_before_discount is present on some answers and absent on others. That is the site's behaviour, not a parsing artefact, and every scraper of it sees the same thing.

Three ways to work with it rather than against it:

• Compare the same field across runs (price_total against price_total), never a nightly rate from one run with a stay total from another.
• Give a price-drop alert a threshold — three per cent filters the noise, and the n8n price-drop template ships with exactly that knob.
• For a decision that must be defensible (a rate-parity report, a revenue-management brief), take the median of a few runs rather than a single reading, or cross-check the stay against Google Hotels Prices Scraper, which reports what Google's own comparison shows for the same dates.

Can I use it for hotel price comparison across sites?

Yes — pair it with the Google Hotels and rate-parity actors below, which return every booking site's rate for the same stay, and compare the price_total columns.

How do I build a Booking.com price history?

Schedule a run with a relative checkIn and a deterministic sortBy; each day's rows share the same lead time and columns, so appending them to a sheet or a table is a price history.

Can I scrape Booking.com without an API?

That is what this does: no Booking.com API, no key, no browser — a plain request through Apify's proxy. If you have been searching for a "Booking.com API" for prices, this is the practical answer: the same data the site shows, as rows.

What does bulk work cost?

1,000 properties across ten destinations is 1,000 × $0.004 = $4.00 plus a cent or two of platform usage; ten requests of 100 rows each.

How to use Booking.com Scraper

• How to Scrape Booking.com Reviews Without a Browser — Booking.com hotel pages need a browser and 60 seconds each. The review endpoint behind them does not. Here is the difference, with working Python.
• How to Check Hotel Rate Parity Across OTAs — Find out when an OTA undercuts your direct rate: one row per property per date with every source compared, the spread and who is cheapest.
• How to Scrape Booking.com Hotel Prices by Date — Stay totals, taxes, cancellation and room rates for a destination or a comp set — and the per-session pricing that makes naive comparisons wrong.
• How to Track Competitor Prices Daily with n8n — A schedule, one HTTP node, a compare-with-yesterday code node and an alert. The workflow shape that turns any price scraper into a daily drop feed.
• How to Schedule a Scraper So It Never Goes Stale — Hard-coded dates rot the day after you set them. Relative date inputs keep a scheduled scraper meaning the same thing every morning — here is the grammar.

Related scrapers

• Booking.com Reviews Scraper — every guest review of a Booking.com property, filtered by language and score before billing.
• Google Hotels Prices Scraper — every booking site's rate for a stay, one row per source.
• Hotel Rate Parity Checker — one row per property with every source side by side and the parity math done.
• Hotel Price Tracker — the lowest rate per property and check-in date over a window, for daily price history.
• Agoda Reviews Scraper — Agoda guest reviews with separate positives and negatives.

Run Booking.com Scraper

The actor lives on the Apify Store, where the pricing tab carries the live per-row price and the input form has every field above: apify.com/kestrel/booking-prices-scraper