apify-booking-client

Booking.com properties, live prices, and full room-rate tables — by destination search or by hotel ID.

Python client for the rl1987/booking-api-scraper Apify Actor. No local scraping, no proxy management, no anti-bot maintenance — the Actor runs on Apify's infrastructure and this package just starts it, waits, and hands you back the dataset as plain Python dicts.

Install · Quickstart · Getting an API token · Input reference · Output fields · Error handling · Pricing · Async / long-running runs · Links

Install

pip install apify-booking-client

Requires Python 3.9+. Only dependency is requests.

Quickstart

from apify_booking_client import BookingClient

client = BookingClient(api_token="apify_api_...")  # see "Getting an API token" below
items = client.run({"search": "Amsterdam", "rooms": 1, "adults": 2, "maxItems": 20})

for item in items:
    print(item)

Real output from the example above (trimmed to a few fields):

{"id": 6331862, "currency": "USD", "checkin": "2026-09-23", "checkout": "2026-09-24", "url": "https://www.booking.com/hotel/nl/holiday-inn-express-amsterdam-motorkade.html?..."}

run() blocks until the Actor finishes (usually a few seconds to ~30s depending on maxItems) and returns a plain list[dict] — the Actor's dataset, one dict per result row.

Getting an API token

1. Sign up for a free account at console.apify.com.

2. Go to Settings → Integrations and copy your Personal API token.

3. Pass it to the client: BookingClient(api_token="..."), or read it from an environment variable:

   import os
   client = BookingClient(api_token=os.environ["APIFY_TOKEN"])
   

Never hardcode the token in source control — use an environment variable or secrets manager.

Input reference

run() takes a single dict matching the Actor's input schema. Full/authoritative schema: the Input tab on the Actor's Apify page.

Output fields

Each dict in the returned list is one row from the Actor's dataset. Common fields:

id, price, currency, checkin, checkout, url, deep_link_url, plus details/products/rooms/reviews objects when the matching include* flag is set.

Exact field availability can vary by input flags (see table above) — treat unfamiliar/missing keys as optional and use .get() rather than [...] indexing.

Error handling

from apify_booking_client import BookingClient, ApifyActorError
import requests

client = BookingClient(api_token="...")

try:
    items = client.run({"search": "Amsterdam", "rooms": 1, "adults": 2, "maxItems": 20})
except ApifyActorError as e:
    # The Actor run itself failed, timed out, or was aborted on the Apify side.
    print(f"Actor run did not succeed: {e}")
except requests.HTTPError as e:
    # Bad token, malformed input, rate limiting, etc. — an HTTP-level error
    # calling the Apify API (not the Actor run).
    print(f"Apify API request failed: {e}")

ApifyActorError is raised when the run reaches a terminal non-success status (FAILED, TIMED-OUT, ABORTED) or doesn't finish within timeout_secs (default 300s — raise it for run() calls with a large maxItems, e.g. BookingClient(api_token="...", timeout_secs=900)).

Pricing

Pay-per-event: $0.001/search result, $0.001/hotel-details row, $0.0001/room option, $0.0001/review. No subscription — see the Actor's pricing tab for current rates. Apify also includes a free monthly usage tier that covers light use.

Advanced: longer timeouts & polling

client = BookingClient(api_token="...", timeout_secs=900)  # allow up to 15 min
items = client.run(actor_input, poll_interval_secs=3.0)   # poll less aggressively

Links

• Booking.com API Scraper on Apify — Actor page, input schema, pricing
• PyPI package
• Apify API reference — what this client wraps under the hood

License

MIT