UniAcco Student Accommodation Scraper

Scrape student accommodation listings from UniAcco (uniacco.com) — pull title, description, weekly price range, full address, coordinates, contact number, amenities, rating and guest reviews for every property on a city listing page or a single property URL. Results export as JSON, CSV or Excel, or feed straight into your own pipeline through the API. Paste a city listing URL or a property URL and press Start — no configuration required.

Target website: uniacco.com

✨ Features of this UniAcco scraper

• Property extraction — title, description, weekly price range, full address, coordinates, contact number, amenities, rating and reviews.
• Review capture — up to 10 published reviews per property, with author, rating and date.
• Pagination support — walks listing pages automatically until the per-URL item limit is reached.
• Automatic URL detection — listing and property URLs are told apart automatically, so you can mix both in Start URLs.
• Whole-site mode — one toggle crawls the site's main sections instead of a hand-picked list.
• Cross-run caching — an optional project name skips properties already scraped in an earlier run.
• Proxy support — optional Apify proxy configuration (datacenter or residential).

🚀 How to scrape UniAcco listings in 5 steps

1. Sign up for a free Apify account — includes $5 monthly credit.
2. Open the actor page and click Try for free.
3. Fill in the Input fields (at least one start URL is required).
4. Click Start and wait for the run to complete.
5. Download results from the Output tab in JSON, CSV, or Excel format.

You can also run this actor via the Apify API or integrate it directly into your workflows using Zapier, Make, or n8n.

💰 Pricing

This actor uses pay-per-result billing based on the compute units a run consumes.

• New Apify accounts include $5 of free monthly credit.
• Listings render in a real browser, so runs use more compute per item than a plain HTTP scraper — keep maxItems tight for daily monitoring runs to control cost.

🔧 Input configuration

Field	Type	Required	Default	Description
startUrls	array	✅	[{"url": "https://uniacco.com/uk/london"}]	UniAcco city listing URLs (/{country}/{city}) or direct property URLs (/{country}/{city}/{property}). The type of each URL is detected automatically.
maxItems	integer	—	3	Maximum number of properties to scrape for each start URL.
scrapeWholeSite	boolean	—	false	Ignore Start URLs and crawl UniAcco's main city listing pages instead.
cacheProjectName	string	—	—	Optional. When set, properties already scraped under this project name in a previous run are skipped instead of being scraped again.
proxyConfiguration	object	—	{"useApifyProxy": false}	UniAcco responds fine without a proxy. Enable datacenter proxies first if you start seeing blocks, and residential only if datacenter still fails.

Supported URL types:

• Listing pages — city pages such as https://uniacco.com/uk/london or https://uniacco.com/australia/sydney.
• Property pages — https://uniacco.com/{country}/{city}/{property-slug}, e.g. https://uniacco.com/uk/london/dean-house.

📦 UniAcco scraper output data

Each run produces a JSON dataset (exportable to CSV or Excel) with one record per property containing: url, title, description, lowPrice, highPrice, currency, city, region, country, streetAddress, postalCode, latitude, longitude, telephone, rating, reviewCount, amenities, reviews and images. The dataset has one view, Overview, showing title, city, price range, currency, rating, review count and URL in a compact table.

Sample output:

{
    "url": "https://uniacco.com/uk/london/durham",
    "title": "Durham",
    "description": "Durham offers contemporary student accommodation in London with fully furnished rooms, modern facilities and inclusive utilities, ideal for students seeking comfort, community, and convenience close to major universities.",
    "lowPrice": 202,
    "highPrice": 207,
    "currency": "GBP",
    "city": "London",
    "region": "London",
    "country": "United Kingdom",
    "streetAddress": null,
    "postalCode": null,
    "latitude": 51.44871502662388,
    "longitude": -0.24343924568347255,
    "telephone": "+44 808 501 5198",
    "rating": 4.5,
    "reviewCount": 1,
    "amenities": ["Electric Stove", "Microwave", "Fridge", "WiFi"],
    "reviews": [
        {
            "author": "UniAcco",
            "rating": 5,
            "datePublished": null,
            "body": null
        }
    ],
    "images": ["https://uniacco.imgix.net/inventory/Whitelands_Durham-Gilesgate_halls_2.jpg"]
}

🐍 How to scrape UniAcco with Python, JavaScript or the API

Run the actor programmatically with the official Apify clients. Replace <YOUR_API_TOKEN> with the token from your Apify Console.

Python (pip install apify-client):

from apify_client import ApifyClient

client = ApifyClient("<YOUR_API_TOKEN>")

run = client.actor("<username>/uniacco-property-scraper").call(run_input={
    "startUrls": [{"url": "https://uniacco.com/uk/london"}],
    "maxItems": 20,
})

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

JavaScript (npm install apify-client):

import { ApifyClient } from 'apify-client';

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

const run = await client.actor('<username>/uniacco-property-scraper').call({
    startUrls: [{ url: 'https://uniacco.com/uk/london' }],
    maxItems: 20,
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

cURL — start a run and wait for the dataset:

curl -X POST "https://api.apify.com/v2/acts/<username>~uniacco-property-scraper/run-sync-get-dataset-items?token=<YOUR_API_TOKEN>" \
  -H "Content-Type: application/json" \
  -d '{"startUrls": [{"url": "https://uniacco.com/uk/london"}], "maxItems": 20}'

💡 What you can use UniAcco student accommodation data for

• Comparing student accommodation pricing across university cities
• Tracking weekly rent changes through the booking season
• Amenity benchmarking against competing properties
• Sourcing inventory for a relocation or student-housing service
• Feeding dashboards with current availability and ratings

Student housing operators, relocation advisers and market analysts use this data to track current student accommodation pricing and amenities across university cities in the UK, Europe and Australia.

⚠️ Limitations & known issues

• Listings render in a browser — this actor drives a real browser, so runs are slower and use more memory than a plain HTTP scraper.
• Prices are a range — UniAcco advertises a low/high weekly range per property rather than one figure per room.

❓ Frequently asked questions

Can I scrape UniAcco legally?

Yes — this actor only collects data that is already publicly visible on UniAcco property pages; it does not log in, submit enquiries, or access account-only areas. Scraping publicly available data is generally considered lawful (see hiQ Labs v. LinkedIn as precedent). Note that the reviews field contains reviewer names published on the site, so you remain responsible for complying with UniAcco's Terms of Service and applicable privacy law (e.g. GDPR) when processing it.

Why are prices given as a range instead of one number?

UniAcco lists a low/high weekly price range per property rather than a fixed rate per room, since actual room prices vary by room type and availability. The lowPrice and highPrice fields reflect exactly what's shown on the property page.

How many properties can I scrape from one URL?

Set maxItems to control how many properties are collected per start URL — there's no hard cap, though very high values on a single city listing will take longer and use more compute units.

Do I need a proxy to scrape UniAcco?

No. UniAcco responds reliably without one, which keeps run costs down. Enable datacenter proxies first if you start seeing blocks, and residential only if datacenter still fails.

How do I scrape UniAcco with Python?

Install apify-client, call this actor with your startUrls and maxItems in run_input, then iterate the resulting dataset — see the Python example above.

Can I run this UniAcco scraper on a schedule?

Yes, use Apify Schedules to run it daily or weekly. Set cacheProjectName to the same value across scheduled runs so previously scraped properties are skipped automatically.

What output formats are supported?

JSON, CSV, Excel, XML and RSS, either from the Output tab or through the Apify API.

🔗 Other actors you may find useful - Student Housing and Rent Website Scrapers

Actor	Description
🏠 HousingAnywhere Property Scraper	Scrapes rental listings from HousingAnywhere, including price, address, coordinates, room count and amenities.
🏡 Spotahome Property Scraper	Scrapes mid-term rental listings from Spotahome, including price, address, coordinates, room count and amenities.
🎓 Casita Property Scraper	Scrapes student accommodation listings from Casita, including property details, room types, pricing and facilities.
🛏️ Amber Student Accommodation Scraper	Scrapes Amber Student accommodation listings — pricing, availability, photos, amenities, location and reviews — from city, area or individual property pages.
🎓 University Living Housing Scraper	Scrapes student housing listings and property details from University Living.

💬 Support & Contact

If you encounter any issues or have questions, please open an issue

You can also find more of my actors on the page Actor Flow .