Hostelworld Scraper [$1.40/1K💰] | Listings + Reviews

Hostelworld Scraper — Hostel Listings, Nightly Prices and Full Review Text

Extract Hostelworld hostel data by city, country, URL or property page — nightly prices from, dorm vs private tiers, guest ratings, amenities, policies, photos, geo-coordinates and full review text with traveller nationality.

Two datasets: one row per property, one row per review. Built for hostel price comparison, hostel market research, review sentiment analysis and travel-content datasets.

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Two datasets, one run

Listings (default dataset) — one row per property, ~45 fields: name, price-from, dorm and private minimums, rating, review count, city-centre distance, amenities, policies, photos, coordinates.

Reviews (named reviews dataset) — one row per review with the review text itself, the date, the score, the breakdown by category, and the reviewer's nationality and nickname.

The review dataset is what most combined scrapers split out. Dedicated review-only Actors exist — but they return reviews without the property records, so you pay twice, make two calls and join the results yourself. Here both datasets come from one run, already keyed.

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What makes this different from other Hostelworld scrapers

Hostelworld's own mobile app API is what most scrapers hit, and it is protected by JA3 TLS fingerprinting — it rejects most datacenter requests outright. This Actor instead uses Hostelworld's first-party web APIs: the Apigee-backed api.hostelworld.net endpoints that power the website itself, plus the static-pages API for the long-form content (descriptions, policies, amenities, "things to note").

Because it calls the same endpoints the website calls, you get the full property record — not just the card fields — and you do not need browser fingerprint spoofing or a paid proxy to do it.

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Main use cases

• Hostel price comparison — nightly price-from across every property in a city, dorm vs private, in any currency
• Hostel market research — capacity, rating distribution and review volume per property
• Review sentiment and language analysis — full review text with traveller nationality
• Hostel directory or travel content datasets — amenities, photos, policies and descriptions for thousands of properties
• Location and catchment analysis — coordinates plus cityCentreDistanceKm for map and walkability work
• Price and availability tracking — re-run the same city on a schedule and diff priceFrom
• City hostel inventory planning — scrape a whole country and get every active city's hostels
• Competitive hostel benchmarking — ratings, review counts and badges side by side

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Input

Field	Type	Required	Default	Notes
startUrls	array	no	London city page	Hostelworld city pages (/hostels/europe/england/london/) or property pages (/hostels/p/502/slug). The URL type is auto-detected.
cities	array	no	[]	Cities to scrape, as "City" or "City, Country". Use "City, Country" — a bare city name is resolved by probing the largest hostel countries, which costs extra requests.
countries	array	no	[]	Whole countries to crawl. Every active city is enumerated, then its hostels are listed.
propertyType	string	no	hostel	hostel or hotel. Note: Hostelworld's listing API currently returns the same city inventory for both, so this does not filter results — it is kept for URL/API path compatibility.
currency	string	no	GBP	ISO code for all price fields: GBP, EUR, USD, AUD, CAD, THB, MXN, BRL, ZAR.
language	string	no	en	Accept-Language sent to the API (en, de, es, fr, ...).
maxListings	integer	no	200	Hard cap on properties written to the dataset (1–5000). Free-tier users are capped at 10.
maxCitiesPerCountry	integer	no	25	When crawling a whole country, how many of its cities to enumerate (1–500).
maxReviewsPerProperty	integer	no	10	Newest reviews to fetch per property, 10 per API page (0–200). 0 skips reviews entirely.
includeDetails	boolean	no	true	Fetch the full property record — amenities, photos, policies, price stats, badges, "things to note". Turn off for fast listing-only runs.
includeReviews	boolean	no	true	Fetch review text, date and nationality into the reviews dataset.
concurrency	integer	no	8	Parallel API requests (1–50). 8–10 is safe.
maxExpansionCountries	integer	no	10	Auto-expansion only: how many of the largest hostel countries to draw extra cities from when no country is given.
maxCountryProbes	integer	no	20	When a city is given without a country, how many countries to probe before giving up (1–60).
maxRequestsPerCrawl	integer	no	0	Safety cap per crawl round. 0 = unlimited (recommended) — a non-zero value can cut a large run short.
proxy	object	no	useApifyProxy: false	Standard Apify proxy picker. Not needed — the first-party API does not block.

Examples

City price sweep, no reviews — the cheap hostel-comparison run:

{
  "cities": ["Barcelona, Spain", "Lisbon, Portugal"],
  "maxListings": 500,
  "includeDetails": false,
  "includeReviews": false,
  "currency": "EUR"
}

Full property records for one city, in euros:

{
  "cities": ["Berlin, Germany"],
  "maxListings": 300,
  "includeDetails": true,
  "includeReviews": false,
  "currency": "EUR",
  "language": "en"
}

Review dataset for sentiment analysis:

{
  "cities": ["Bangkok, Thailand"],
  "maxListings": 200,
  "includeDetails": false,
  "includeReviews": true,
  "maxReviewsPerProperty": 50,
  "currency": "THB"
}

Whole-country inventory:

{
  "countries": ["Portugal"],
  "maxCitiesPerCountry": 40,
  "maxListings": 1500,
  "currency": "EUR"
}

Straight from URLs you already have:

{
  "startUrls": [
    "https://www.hostelworld.com/hostels/europe/england/london/",
    "https://www.hostelworld.com/hostels/p/502/the-london-hostel"
  ],
  "currency": "GBP"
}

---

Output

Listings dataset

Field	Description
id / slug / name / url	Hostelworld property ID, slug, name and canonical URL
propertyType	hostel, hotel or bed-and-breakfast
address / city / cityId / country / region / continent	Full location
geo	{ latitude, longitude }
cityCentreDistanceKm	Distance from the city centre — the walkability signal
currency	ISO code of every price field in the row
priceFrom	Lowest nightly price per person
priceFromDorm / priceFromPrivate	Dorm and private room minimums
priceStats	Hostelworld's own price statistics
roomTiers[]	Structured tiers: type (dorm/shared, private), from, currency
rating	Average guest rating (0–10 scale normalised)
ratingOverallPct	Overall score as published (percentage scale)
numberOfReviews	Total review count on the property
ratingBreakdown	Per-category rating breakdown
reviewCountFetched	How many reviews this run actually retrieved — compare against numberOfReviews to see coverage
checkInFrom / checkOutUntil / freeCancellation	Booking policy fields
cancellationPolicy / policies[] / thingsToNote[]	House rules and guest-facing notes
photo / photoCount / photos[]	Hero image, photo count and up to 20 full-size photo URLs
description / shortDescription / hostelworldSays	Long, short and Hostelworld's own editorial description
badges[] / bestFor[]	Featured badges and "best for" tags
paymentMethods[]	Accepted payment methods
reviewsDataset	Name of the reviews dataset, or null when reviews were off
source	city:<name> or country:<name> — where this row was seeded from
scrapedAt	ISO timestamp

Reviews dataset

Field	Description
id	Review ID
propertyId / propertyName / propertySlug / propertyUrl	Join key back to the listing row
city / country	Denormalized, so the review dataset stands alone
date	Review date
text	Full review text
rating / ratingBreakdown	Overall score and per-category breakdown
nationality / nationalityCode	Reviewer's nationality
travellerNickname / travellerReviews	Reviewer identity and how many reviews they have written
groupType / ageRange / tripTypes	Solo / group, age band, leisure vs business
language	Language the review was written in
scrapedAt	ISO timestamp

reviewCountFetched is the coverage flag

numberOfReviews is what the property has; reviewCountFetched is what this run retrieved. A property with numberOfReviews: 412 and reviewCountFetched: 10 has 2% coverage — fine for a quick read, not fine for sentiment analysis. Raise maxReviewsPerProperty (up to 200) when the review corpus is the point of the run.

Example output

Listings row:

{
  "id": 502,
  "slug": "the-london-hostel",
  "name": "The London Hostel",
  "url": "https://www.hostelworld.com/hostels/p/502/the-london-hostel-europe-england-london/",
  "propertyType": "hostel",
  "address": "256-262 Kingsland Road, London, E2 8AA",
  "city": "London",
  "cityId": 2796,
  "country": "United Kingdom",
  "region": null,
  "continent": "Europe",
  "geo": { "latitude": 51.5289, "longitude": -0.0762 },
  "cityCentreDistanceKm": 2.4,
  "currency": "GBP",
  "priceFrom": 21.5,
  "priceFromDorm": 21.5,
  "priceFromPrivate": 44.0,
  "priceStats": { "minPrice": 21.5, "maxPrice": 89.0 },
  "roomTiers": [
    { "type": "dorm/shared", "from": 21.5, "currency": "GBP" },
    { "type": "private", "from": 44.0, "currency": "GBP" }
  ],
  "rating": 8.9,
  "ratingOverallPct": 89,
  "numberOfReviews": 1284,
  "ratingBreakdown": { "staff": 9.3, "cleanliness": 8.8, "location": 8.4, "value": 8.7 },
  "checkInFrom": "14:00",
  "checkOutUntil": "10:00",
  "freeCancellation": true,
  "cancellationPolicy": "Free cancellation up to 1 day before arrival",
  "photo": "https://images.hostelworld.com/hostels/p/502/the-london-hostel.jpg",
  "photoCount": 24,
  "photos": ["https://images.hostelworld.com/hostels/p/502/1.jpg"],
  "description": "A large independent hostel in the heart of East London, minutes from Shoreditch...",
  "shortDescription": "Large independent hostel in East London",
  "badges": ["Best Location"],
  "bestFor": ["Solo travellers", "Groups"],
  "paymentMethods": ["Visa", "Mastercard", "Cash"],
  "policies": ["No smoking", "Curfew 23:00-07:00"],
  "thingsToNote": ["Bring a photo ID", "Lockers available"],
  "reviewCountFetched": 10,
  "reviewsDataset": "reviews",
  "source": "city:london",
  "scrapedAt": "2026-09-30T10:02:41.000Z"
}

Reviews row:

{
  "id": 8871234,
  "propertyId": 502,
  "propertyName": "The London Hostel",
  "propertySlug": "the-london-hostel",
  "propertyUrl": "https://www.hostelworld.com/hostels/p/502/the-london-hostel-europe-england-london/",
  "city": "London",
  "country": "United Kingdom",
  "date": "2026-08-14",
  "text": "Great location for East London and the staff were genuinely helpful. Dorms are basic but spotless, and the bike storage was a bonus.",
  "rating": 8.8,
  "ratingBreakdown": { "staff": 9.5, "cleanliness": 9.0, "location": 9.2, "value": 8.5 },
  "nationality": "Australia",
  "nationalityCode": "AU",
  "travellerNickname": "Traveller_4821",
  "travellerReviews": 14,
  "groupType": "solo",
  "ageRange": "25-34",
  "tripTypes": ["leisure"],
  "language": "en",
  "scrapedAt": "2026-09-30T10:02:43.000Z"
}

---

Track hostel prices and reviews on a schedule

Hostel pricing moves with season, events and demand. Recurring runs turn the dataset into a live price and reputation feed:

• Weekly — same cities; diff priceFrom and priceFromDorm for high-frequency cities
• Monthly — diff rating and reviewCountFetched to track reputation movement over time
• Peak-season baseline — run once a month across a whole country in EUR for market sizing
• New-opening detection — keep only rows with an id not seen in the previous run
• Wire into your stack — Apify webhooks, Zapier, Make, Google Sheets and 100+ integrations fire on run completion; both datasets export as JSON, CSV, Excel, XML, HTML or RSS

Split your schedules by cost: includeReviews: false on the weekly price run, includeReviews: true with a higher maxReviewsPerProperty on the monthly reputation run. Reviews are billed per row, listings are billed per property.

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Related Actors

• Booking.com Review Scraper (ahmed_jasarevic/booking-com-hotel-review-scraper) — hotel-scale review text and sentiment data at much larger volume
• Booking.com Scraper (ahmed_jasarevic/fast-booking-scraper) — wider property coverage for cross-platform price comparison
• Airbnb Scraper (ahmed_jasarevic/airbnb-scraper-listings-prices-hosts) — peer-to-peer accommodation for a different segment of the same trip
• Hostelworld Listings Scraper by easyapi (easyapi/hostelworld-listings-scraper) — listing fields only; pairs with their separate reviews Actor
• Hostelworld Reviews Scraper by easyapi (easyapi/hostelworld-reviews-scraper) — the most-used dedicated review Actor; reviews only, no property records

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FAQ

Why not use the official Hostelworld Partner API?

Because you need to be an approved affiliate partner first — it is not an open developer API. If you run a booking engine or a monetised travel site, apply for affiliate access and use the official Partner API; it is the correct route for that use case. For research, comparison, dataset building and analysis, there is no self-serve access, which is what this Actor covers.

Why do other Hostelworld scrapers return less?

Because most of them hit Hostelworld's mobile app API, which is protected by JA3 TLS fingerprinting — it rejects requests that do not come from the real app. This Actor calls the first-party web APIs that power the website instead, which is why it returns amenities, policies, badges, "things to note", the full description and the review text without browser fingerprint spoofing or a paid proxy.

Does propertyType: "hotel" give me hotels?

No — and this is a real limitation, stated plainly. Hostelworld's listing API currently returns the same city inventory for both hostel and hotel, so the field changes the API path but does not filter results. Treat propertyType as a path selector, not a filter. If you need true hotel-only inventory, use a different source.

How do I avoid wasted requests on ambiguous city names?

Always write "City, Country" in cities. A bare city name forces the Actor to probe the largest hostel countries until it finds a match, up to maxCountryProbes — real wasted calls on a big run. If a city genuinely appears in several countries, that probe is what you want, but be aware of it in the log.

Why is rating not the same scale as ratingOverallPct?

rating is the normalised average on Hostelworld's 0–10 scale; ratingOverallPct is the raw overall score as published on a percentage scale. They track each other but are not interchangeable — use rating for aggregation and ratingOverallPct if you need to reproduce what a reader sees on the page.

How complete is the review dataset?

reviewCountFetched tells you exactly. Hostelworld returns reviews 10 per API page, so maxReviewsPerProperty: 10 is one page. Raise it up to 200 for deeper corpora, and compare reviewCountFetched against numberOfReviews to know your coverage before running analysis on it.

Does it need a browser or a proxy?

No. It is API-only — no JavaScript rendering, no headless browser, no CAPTCHA solving. The default run uses no proxy at 256 MB and 8 parallel requests, which is comfortably within what the API accepts.

Can I crawl a whole country?

Yes — put the country in countries. The Actor enumerates every active city in that country, then lists each city's hostels. maxCitiesPerCountry (default 25) caps how many cities are taken, and the log tells you how many were skipped, so nothing disappears silently.

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For AI Agents & LLM Apps

Callable via the Apify MCP server and the Apify API. Returns two named datasets: dataset (default) with one row per property, and reviews with one row per review.

Minimal valid input — one city, listing data only, cheapest:

{ "cities": ["Barcelona, Spain"], "includeDetails": false, "includeReviews": false, "currency": "EUR" }

Full run with review text:

{
  "cities": ["Berlin, Germany"],
  "maxListings": 300,
  "includeDetails": true,
  "includeReviews": true,
  "maxReviewsPerProperty": 50,
  "currency": "EUR"
}

Whole-country inventory:

{ "countries": ["Portugal"], "maxCitiesPerCountry": 40, "maxListings": 1500, "currency": "EUR" }

Output field list — listings: id, slug, name, url, propertyType, address, city, cityId, country, region, continent, geo, cityCentreDistanceKm, currency, priceFrom, priceFromDorm, priceFromPrivate, priceStats, roomTiers, rating, ratingOverallPct, numberOfReviews, ratingBreakdown, reviewCountFetched, checkInFrom, checkOutUntil, freeCancellation, cancellationPolicy, policies, thingsToNote, photo, photoCount, photos, description, shortDescription, hostelworldSays, badges, bestFor, paymentMethods, reviewsDataset, source, scrapedAt. Reviews: id, propertyId, propertyName, propertySlug, propertyUrl, city, country, date, text, rating, ratingBreakdown, nationality, nationalityCode, travellerNickname, travellerReviews, groupType, ageRange, tripTypes, language, scrapedAt.

Behaviors an agent should know

• Two separately billed events. includeReviews: false bills only the listing event; the reviews dataset is skipped entirely and reviewsDataset comes back null on every row.
• Reviews are billed per review row, not per property. maxReviewsPerProperty: 50 adds up to 50 review charges per property on top of the listing charge. If the review corpus is not the point of the run, set it to 0.
• propertyType does not filter. hotel returns the same inventory as hostel. Do not promise the caller hotels.
• Always pass "City, Country". A bare city name triggers country probing and wastes requests; maxCountryProbes caps the waste at 20 lookups by default.
• maxRequestsPerCrawl defaults to 0, meaning unlimited — a non-zero value can cut a large run short. Leave it at 0 unless you have a specific reason.
• propertyType is kept only for URL/API-path compatibility, so a start URL like /hotels/.../london/ is parsed correctly even though the results are not hotel-filtered.
• Join key is id ↔ propertyId. Use it to attach reviews to listings.
• reviewCountFetched vs numberOfReviews is your coverage check — never run sentiment analysis without comparing them.
• Two dataset schemas, both with an overview view — select the reviews storage to read review rows.
• currency applies to every price field in the row. priceFrom, priceFromDorm, priceFromPrivate, priceStats and each roomTiers[].from are all in row.currency.

Billing model — pay per event: listing ($0.0014–$0.0015 per property row) and review ($0.00075–$0.0008 per review row), plus a per-run Actor Start event scaled by memory. Free-plan users are capped at 10 properties.

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Legal & Compliance Disclaimer

This Actor is an independent third-party tool. It is not affiliated with, endorsed by, sponsored by, or connected with Hostel Group / Hostelworld.

It reads only publicly available data — the JSON endpoints that power Hostelworld's own public website, plus publicly visible property pages. It does not log in, does not create an account, does not use an affiliate or partner token, does not solve CAPTCHAs, does not use proxies by default, and does not bypass the official Partner API agreement.

Output includes guest review content — free-text review bodies, reviewer nicknames, reviewer nationalities, age bands and group types. This is personal data about identifiable individuals under GDPR and UK GDPR. You are responsible for your own lawful basis for processing it, for honouring deletion requests, and for keeping retention periods short. Do not use review text or reviewer profiles to build marketing lists, and do not re-publish review text without the appropriate permission.

Commercial or high-volume extraction may fall under Hostelworld's terms of use, and monetised use of their content normally requires affiliate or partner agreement — review their terms before large-scale collection or redistribution. Review text and property descriptions remain the property of their authors and Hostelworld.

This Actor is a data-collection tool; it does not provide legal advice and makes no claim that any particular use is permitted.

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