🏠 Student Accommodation Scraper

🚀 Collect student housing listings in minutes. Search by city, category, and bathroom type. Export prices, locations, amenities, and availability. No coding, no account required.

🕒 Last updated: 2026-04-16 · 📊 15+ fields per listing · 🔍 City + category filters · 🏠 Accommodation data · 🚫 No auth required

The Student Accommodation Scraper collects student housing listings, returning 15+ fields per property: title, price, location, bedrooms, bathrooms, amenities, availability, images, and listing URL. Filter by city, accommodation category, and bathroom type.

🎯 Target Audience	💡 Primary Use Cases
Students, university housing offices, property managers, relocation services, real estate researchers	Housing search, market analysis, rent benchmarking, accommodation comparison, student services

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📋 What the Student Accommodation Scraper does

• 🔗 URL mode. Paste a listing page URL.
• 🏙️ City filter. Search by city slug.
• 📂 Category filter. Accommodation type categories.
• 🛁 Bathroom filter. Private or shared bathroom options.

💡 Why it matters: finding student housing means browsing dozens of listings one by one. This Actor exports structured accommodation data for comparison and analysis.

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🎬 Full Demo

🚧 Coming soon.

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⚙️ Input

Input	Type	Default	Behavior
startUrl	string	""	Direct listing page URL.
citySlug	string	""	City slug for location filter.
categorySlugs	array	[]	Accommodation categories.
bathroomTypes	array	[]	Private or shared bathroom.

Example: student housing in London.

{ "citySlug": "london", "maxItems": 50 }

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📊 Output

🧾 Schema

Field	Type	Example
📝 title	string	"Studio Apartment near UCL"
💰 price	string	"£250/week"
📍 location	string	"Bloomsbury, London"
🛏️ bedrooms	number	1
🛁 bathroomType	string	"Private"
🔗 url	string	"https://..."
🕒 scrapedAt	ISO 8601	"2026-04-16T00:00:00.000Z"

📦 Sample records

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✨ Why choose this Actor

	Capability
🏙️	City-based search. Find housing by location.
📂	Category filters. Accommodation types.
🛁	Bathroom filters. Private or shared.
💰	Price data. Weekly/monthly rent per listing.
⚡	Scalable. Quick lookups to full city sweeps.
🚫	No authentication. Public listing data.

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📈 How it compares to alternatives

Approach	Cost	Coverage	Refresh	Filters	Setup
⭐ Student Accommodation Scraper (this Actor)	$5 free credit, then pay-per-use	Listing site	Live per run	city, category, bathroom	⚡ 2 min
Manual browsing	Free	One at a time	Manual	UI only	🕒 Hours

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🚀 How to use

1. 📝 Sign up. Create a free account with $5 credit (takes 2 minutes).
2. 🌐 Open the Actor. Go to the Student Accommodation Scraper page.
3. 🎯 Set input. Enter a city and filters.
4. 🚀 Run it. Click Start.
5. 📥 Download. Grab results in the Dataset tab.

⏱️ Total time: 3-5 minutes. No coding required.

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💼 Business use cases

🎓 Students & Parents Compare housing options Track pricing by neighborhood Find accommodation near campus Build shortlists

🏢 Property & University Monitor market rent rates Track accommodation supply Build housing databases Benchmark against competitors

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🔌 Automating Student Accommodation Scraper

• 🟢 Node.js. Install the apify-client NPM package.
• 🐍 Python. Use the apify-client PyPI package.
• 📚 See the Apify API documentation for full details.

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❓ Frequently Asked Questions

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🔌 Integrate with any app

• Make - Automate workflows
• Zapier - Connect 5,000+ apps
• Slack - Get notifications
• Airbyte - Data pipelines
• GitHub - Trigger from commits
• Google Drive - Export to Sheets

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🔗 Recommended Actors

• 🏠 Zillow Scraper - Property listings
• 🏠 Apartments.com Scraper - Rental listings
• 📚 Rate My Professors Scraper - Professor ratings
• 🏠 Auction.com Scraper - Property auctions
• 📍 Address Normalizer - Address cleaning

💡 Pro Tip: browse the complete ParseForge collection for more real estate and education scrapers.

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🆘 Need Help? Open our contact form to request a new scraper, propose a custom data project, or report an issue.

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⚠️ Disclaimer: this Actor is an independent tool. All trademarks mentioned are the property of their respective owners. Only publicly available listing data is collected.