Hostelworld Scraper: 17,000+ Properties Covered (2026)

Hostelworld Scraper extracts hostel and budget accommodation data from Hostelworld.com, providing up to 1,000 results a month on Apify's free plan. Each record includes a property name, ID, type, city, country, address, coordinates, overall rating and breakdown, review count, starting price per night, currency code, amenities, distance to center, check-in/out times, description, and up to five image URLs. This Actor is well-suited for developers building travel apps, researchers studying budget tourism, or content creators crafting travel guides. It is not for anyone needing real-time booking availability beyond specified date ranges, as the scraper primarily captures static property details.

Try it: open Hostelworld Scraper on Apify, sign in on the free plan and run the prefilled example.

Can you try Hostelworld Scraper before paying?

Yes. Apify's free plan includes $5.00 of prepaid usage every month and asks for no credit card. At $0.005 per result, that covers up to 1,000 results of Hostelworld Scraper a month, before run-start charges and platform usage.

The example request further down caps maxItems at 50, so a first run returns at most 50 results and costs at most $0.25 in result charges. That is enough to see the real shape of the data before deciding anything.

Hostelworld Scraper was last updated on 2026-05-27. It is one of 1,725 Actors CrawlerBros publishes on Apify, which together have 692,561 lifetime public runs and an average rating of 4.63 out of 5 across 416 reviews.

What does it cost to run Hostelworld Scraper?

Each result costs $0.005 on Apify's free plan, which is $5.00 per 1,000 results. Starting a run is charged separately at $0.005 per GB of Actor memory. Apify also bills the platform usage each run consumes, at the rates of your Apify plan, on top of these charges.

The primary driver for cost is the number of results returned, which is largely controlled by the "maxItems" input. Each result costs $0.005, which is $5.00 per 1,000 results on the free plan. To gauge whether this Actor meets your needs before incurring significant charges, test it with the example input, which caps results at 50, costing at most $0.25 in result charges.

How do you run Hostelworld Scraper from the API?

The schema marks 1 of its 9 controls as required: mode. The payload below uses the schema's own prefilled values, so it runs as written once you substitute your API token.

Call the synchronous endpoint to start a run and receive dataset items in one request:

curl -X POST "https://api.apify.com/v2/acts/crawlerbros~hostelworld-scraper/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"mode":"search","searchQuery":"London","guests":1,"propertyUrls":[],"maxItems":50}'

The same run from Python, using the official client:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")

run_input = {
  "mode": "search",
  "searchQuery": "London",
  "guests": 1,
  "propertyUrls": [],
  "maxItems": 50
}

run = client.actor("crawlerbros~hostelworld-scraper").call(run_input=run_input)

for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

And from Node.js:

import { ApifyClient } from 'apify-client'

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' })

const input = {
  "mode": "search",
  "searchQuery": "London",
  "guests": 1,
  "propertyUrls": [],
  "maxItems": 50
}

const run = await client.actor('crawlerbros~hostelworld-scraper').call(input)
const { items } = await client.dataset(run.defaultDatasetId).listItems()
console.log(items)

The synchronous endpoint holds the connection open until the run finishes, which is convenient for small batches and wrong for large ones. For anything long running, start the run asynchronously and poll, or attach a webhook, so a dropped connection does not cost you the results.

Which Hostelworld Scraper inputs matter, and which can you skip?

The input schema offers 9 controls, with "mode" as the single required field. The "mode" control, set to "search" by default, allows you to find hostels by city. Most users will start by providing a "searchQuery" to specify their desired city. Other controls like "dateFrom", "dateTo", "guests", "minRating", and "maxPrice" are useful for filtering, but on a first run, you can generally leave them at their defaults to explore the breadth of the output.

• mode (string): What to scrape. Default: "search".
• searchQuery (string): City or destination name (mode=search). Works best with major cities like 'London', 'Paris', 'Bangkok', 'New York', 'Sydney', etc.
• dateFrom (string): Check-in date in YYYY-MM-DD format (optional, used to filter by availability and show prices).
• dateTo (string): Check-out date in YYYY-MM-DD format (optional, used together with dateFrom).
• guests (integer): Number of guests for the booking (default: 1). Default: 1.
• minRating (number): Only return properties with rating at or above this value (0-10 scale).
• maxPrice (number): Only return properties with price per night at or below this value (in the property's local currency).
• propertyUrls (array): Specific Hostelworld property URLs to scrape (e.g. https://www.hostelworld.com/hostels/p/88047/wombat-s-city-hostel-london/). Default: [].
• maxItems (integer): Hard cap on records returned. Default: 50.

Fixed-choice controls: mode accepts search (Search Hostels), byUrl (Fetch by URL), topCities (Top Cities).

What does Hostelworld Scraper return?

The returned records are ideal for building hostel comparison tools, populating travel guides, or conducting market analysis on budget accommodation. Each property record provides comprehensive details, including granular rating breakdowns, amenity lists, and geographical coordinates. However, the output does not include real-time booking availability beyond the date range specified in the input, nor does it provide direct booking links.

• name: Property name
• propertyId: Unique Hostelworld property ID
• type: Property type (Hostel, Hotel, Guesthouse, etc.)
• city: City name
• country: Country name
• address: Street address
• postalCode: Postal/ZIP code
• latitude, longitude: GPS coordinates
• rating: Overall rating (0-10 scale)
• reviewCount: Total number of reviews
• ratingBreakdown: Scores for atmosphere, cleanliness, facilities, location, security, staff, value
• pricePerNight: Starting price per night
• currencyCode: Currency of the price
• amenities: Full list of facilities (Free WiFi, Bar, Kitchen, Security Lockers, etc.)
• dormAvailable: Whether dormitory beds are offered
• privateRoomAvailable: Whether private rooms are available
• distanceToCenter: Distance from city centre (km)
• checkinTime, checkoutTime: Check-in and check-out times
• description: Property description
• hostelworldUrl: Property page URL
• imageUrl: Main property image URL
• imageUrls: Up to 5 property image URLs

These are the documented fields. Optional ones can be empty on a given record, so measure how often each field your deliverable depends on is populated across a real sample before automating the handoff.

How do you build the workflow end to end?

Open Hostelworld Scraper and work through these in order. Each step ends with something to check, so a bad configuration surfaces on a small run rather than a scheduled one.

1. Set the "mode" to "search" and enter a "searchQuery" like "London". Run once with the default "maxItems" of 50.
2. Inspect the dataset for records with non-null "rating" and "reviewCount" values, and verify "pricePerNight" and "currencyCode" are present.
3. If the initial run is successful, consider adding "dateFrom" and "dateTo" to filter by availability and get specific pricing.
4. Check that the returned "amenities" list is populated for a few sample properties; this indicates full detail page scraping.
5. To scrape specific properties, switch the "mode" to "byUrl" and populate the "propertyUrls" array with direct Hostelworld links.
6. For a general overview, set the "mode" to "topCities" and verify that the output contains a curated list of popular destinations.
7. Before scheduling, confirm that the "maxItems" control is set appropriately for your expected volume, as it directly impacts results and cost.

How do you apply it? Three worked playbooks

These are Hostelworld Scraper's own documented use cases, each worked through as an operating pattern rather than a description.

Use case 1: Budget travel research

Outcome: Find the highest-rated hostels in any city

Configure: Set "mode" to "search", "searchQuery" to a specific city (e.g., "Paris"), and "minRating" to 8.0 or higher. Set "maxPrice" to an appropriate budget.

Working method: Start with a single city and a high "minRating" to identify top-tier hostels. Review the "ratingBreakdown" for specific insights on atmosphere or value. Expand to more cities after verifying the quality of the initial results.

Deliverable: A spreadsheet of highly-rated hostels for selected cities, including their "pricePerNight", "amenities", and overall "rating".

Stop condition: Records consistently have null "rating" or "pricePerNight" values for top-rated properties.

Use case 2: Content creation

Outcome: Gather data for travel blogs and guides

Configure: Set "mode" to "search" with a broad "searchQuery" (e.g., "Rome") and ensure "maxItems" is high enough to capture a representative sample. Alternatively, use "mode": "byUrl" with a list of hand-picked hostels.

Working method: Begin by searching a popular destination to get a general overview of hostel types and prices. Then, selectively fetch detailed information for specific hostels that stand out in terms of "description", "amenities", or "ratingBreakdown" for deeper content.

Deliverable: A collection of rich hostel profiles, including descriptions, amenity lists, and image URLs, suitable for blog posts or city guides.

Stop condition: The "description" field is consistently empty or truncated across multiple records for well-known hostels.

Use case 3: Travel app development

Outcome: Build hostel comparison or travel planning features

Configure: Set "mode" to "topCities" to get a base list of destinations, then iterate using "mode": "search" for each city. For specific comparisons, use "mode": "byUrl" with a list of competing property URLs.

Working method: First, fetch the list of "topCities" to identify major hostel hubs. Then, for each of those cities, run the scraper in "search" mode to gather a comprehensive dataset of hostels. Focus on extracting "latitude", "longitude", "pricePerNight", and "amenities" for comparison features.

Deliverable: A structured dataset of hostel properties across multiple cities, including geographical coordinates, pricing, and key amenities, ready for integration into a travel application.

Stop condition: Geographical coordinates ("latitude", "longitude") are frequently missing or incorrect, making location-based features unreliable.

What breaks, and how do you design around it?

When searching by city, if your target city isn't supported by the scraper's pre-built lookup table, the run may return no results. In such cases, try to construct the Hostelworld city page URL manually and use the "byUrl" mode for specific property pages. For very large datasets, consider splitting your requests into multiple runs with smaller "maxItems" values to manage output volume and prevent potential timeouts.

When should you not use Hostelworld Scraper?

This Actor is not suitable if your primary goal is to obtain real-time, dynamic pricing for a large number of properties across many dates, as it's designed more for comprehensive property detail extraction rather than a booking-engine-like price comparison. For broader vacation rental data that includes more property types and booking links across various platforms, you might find HomeToGo Scraper or CozyCozy Scraper to be better alternatives. Similarly, if your focus is exclusively on apartment or house rentals, dedicated property portals like those scraped by QuintoAndar Scraper or MyHome.ie Scraper could offer more relevant data. Do not use this Actor if you require contact details for property owners or managers, as this data is not publicly available on Hostelworld and is not returned.

What should you check before trusting the output?

• Watch for missing "rating" or "reviewCount" values, which may indicate incomplete property details.
• Validate that "pricePerNight" and "currencyCode" are consistently returned and correctly formatted, as pricing data is critical.
• Alert if the "amenities" array is empty for a significant number of records; this suggests an issue with detail extraction.
• Check the consistency of "latitude" and "longitude" for geographical accuracy; outliers may indicate data parsing problems.
• Ensure that "hostelworldUrl" and "imageUrl" fields are valid and accessible, as broken links point to malformed records.
• If using date filters, confirm that the "pricePerNight" reflects availability for the specified dates and is not a base price.

None of this proves a record is correct. It gives a scheduled Hostelworld Scraper run defined points where it should stop instead of quietly passing bad data downstream.

Frequently asked questions

How many results can I get for free?

Apify's free plan includes $5.00 of monthly usage without requiring a credit card. This covers up to 1,000 results of this Actor at the free-plan price of $0.005 per result. This allows you to perform substantial data collection and assess the Actor's suitability for your needs before committing to a paid plan.

Do dates affect the results for Hostelworld Scraper?

Yes, the presence of "dateFrom" and "dateTo" in your input significantly affects the output. Without these dates, you receive standard city listings with base prices. When you include check-in and check-out dates, the results reflect actual availability for those specific dates, and prices shown will be those available during that period.

Which currency will the prices be in?

Prices are displayed in the currency configured for the Hostelworld browsing session. This often defaults to a local currency based on the origin of the request (e.g., PKR for Pakistan, EUR for Europe). The "currencyCode" field in the output explicitly identifies the currency of the "pricePerNight" for each property, allowing you to correctly interpret the monetary values.

Why might some cities not return results in search mode?

The scraper has a pre-built lookup table that supports over 60 major cities. For cities not on this list, the scraper attempts to automatically construct a URL, which may not always succeed. If a specific city you need does not work in "search" mode, your best approach is to use the "byUrl" mode with a direct Hostelworld city page URL.

Does Hostelworld Scraper require login details or API keys?

No, Hostelworld Scraper operates entirely without the need for login credentials or API keys. All the data it extracts is publicly available on Hostelworld.com. This simplifies the setup process and allows for immediate use without any authentication overhead.

Where to go next

When you are ready to run it, open Hostelworld Scraper on Apify; the free plan covers up to 1,000 results a month.

Start with the Hostelworld Scraper Actor page for the current input schema, pricing tier, and run history.

Other Actors we maintain for related data:

• HomeToGo Scraper: Scrape HomeToGo vacation rental listings by destination - prices, images, amenities, property type, geo-coordinates, and booking links from the world's largest vacation rental metasearch engine.
• ChavesNaMao Scraper: Scrape ChavesNaMao - one of Brazil's largest property portals.
• CozyCozy Scraper: Scrape lodging listings from CozyCozy's public catalog pages - hotels, vacation rentals, hostels, apartments, and more, across 13 English-language markets, with price, rating, review count, geo-coordinates, and address.
• QuintoAndar Scraper: Scrape QuintoAndar - Brazil's leading property rental and sales platform.
• MyHome.ie Scraper: Scrape MyHome.ie - Ireland's leading property portal.
• UK Funeral Director Directory Scraper (FuneralGuide): Scrape funeralguide.co.uk - the UK's largest funeral director directory.
• OnTheMarket Property Listings Scraper: Scrape OnTheMarket.com, UK's third largest property portal.
• Trip.com Hotels Scraper: Scrape hotel listings from Trip.com.

Related guides:

• Nestpick Scraper: 3 Practical Use Cases
• Guide to Furnished Finder Data Extraction for Rental Markets
• Spotahome Mid-Term Rentals Scraper: 92 Cities Covered (2026)
• Airbnb Scraper: 3 Practical Use Cases

Resources

• Actor documentation, input schema, and pricing: verified against the published Actor on 2026-09-28.

• Actor last updated by its maintainers on 2026-05-27.

• Run outcome figures cover the 30 day public window ending 2026-09-28.

• Hostelworld Scraper on Apify