Booking Hotel Scraper
Pricing
from $2.49 / 1,000 results
Booking Hotel Scraper
It extracts hotel name, location, price per night, star rating, guest rating, review count, amenities, room types, images, and property description by navigating search results and visiting individual hotel detail pages. Suitable for price monitoring, hotel dataset creation, and market analysis.
Pricing
from $2.49 / 1,000 results
Rating
5.0
(3)
Developer
ScrapeAI
Maintained by CommunityActor stats
1
Bookmarked
14
Total users
0
Monthly active users
10 days ago
Last modified
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Booking.com live hotel scraper
Collects genuine Booking.com hotel cards and optional native detail fields. HTTP search is attempted first, with a public browser fallback. Hotel detail pages run concurrently (default two, maximum three). Source card data survives a failed detail request with detailStatus=unavailable. A partial detail response is not marked complete.
Input
Supply ss (destination, default Chennai) or explicit HTTPS Booking.com search/hotel startUrls. Optional checkin/checkout must be supplied together in YYYY-MM-DD order. Guest and room counts build the actual search URL. Explicit URLs retain their source filters and override individual search parameters. maxItems is a global maximum (default 10). includeDetails defaults true. proxy or proxyConfiguration supports Apify/custom proxies; proxyConfiguration takes precedence.
Output
hotel_url is the canonical property identity; sourcePropertyUrl preserves the observed card link and query context. Rows include actual hotel name, source address, thumbnail and available displayed prices/review summary. Star classification (rating) is separate from numeric guest review_score and review_scale. Price labels are price_display/price_context: they are not guessed to be per-night amounts.
Optional details retain the observed property description, amenities, matched Hotel JSON-LD, address, geo, photos and source review aggregate. Unobserved fields are omitted. A blocked detail page retains the real search card, not another hotel's data. Explicit detailSourceUrl and extraction provenance distinguish the surfaces. No synthetic properties, default zero metrics or anonymous user-session reuse are used.
Run and scope
Run apify run --input-file input.json, then inspect the Dataset and RUN_SUMMARY. Search HTML is retained in run storage. Availability, prices and detail richness depend on the source and supplied dates. No CAPTCHA solving is performed. Compute and configured proxy usage incur platform charges. Counts describe genuine hotel records; detailStatus documents whether extra detail extraction succeeded.
