Zoopla Scraper

Zoopla Scraper creates a structured dataset of property listing records collected from Zoopla.co.uk. Each dataset item can include the property address, title, price (amount, frequency, and currency), image and gallery, bedroom and bathroom counts, size, property type, tenure, key features, and listing URL. Query the source using one or more Zoopla search URLs, control the result limit with maxListings, and retrieve records through the Apify Dataset API or export them as JSON, CSV, Excel, or XML.

Dataset at a glance

Property	Value
Source	zoopla.co.uk
Record unit	One property listing
Input methods	Search URLs
Main identifiers	id, propertyUrl
Delivery	Apify Dataset and API
Export formats	JSON, CSV, Excel, XML
Update model	Fresh records per Actor run
Pricing	Pay per event, $10 per 1,000 listings

Coverage and available records

The Actor starts from one or more Zoopla search URLs and returns one record per property listing, including residential and commercial results. maxListings caps the number of listings per URL and resets for each URL in the list. A US residential proxy is used by default.

Data dictionary

Field	Type	Nullable	Description	Example
id	integer	No	Property ID	136625822
displayAddress	string	Yes	Display address	6 Duke Street St. James's, London, SW1Y 6BN
summary	string	Yes	Listing summary	Newly fitted office space...
title	string	Yes	Listing title/heading	Featured Property
bedrooms	integer	Yes	Number of bedrooms	0
bathrooms	integer	Yes	Number of bathrooms	—
numberOfImages	integer	Yes	Image count	11
price	object	Yes	Price object (amount, frequency, currencyCode, displayPrices)	{ "amount": 19241, "currencyCode": "GBP" }
location	object	Yes	Coordinates (latitude, longitude)	{ "latitude": 51.5, "longitude": -0.13 }
imageUrl	string	Yes	Primary image URL	https://media...jpeg
images	array	Yes	Image objects (srcUrl, url, caption)	[...]
propertyUrl	string	Yes	Listing URL	https://www.zoopla.co.uk/properties/136625822
propertySubType	string	Yes	Property sub-type	Office
propertyTypeFullDescription	string	Yes	Full property type	Office
tenure	object	Yes	Tenure (tenureType)	{ "tenureType": "LEASEHOLD" }
transactionType	string	Yes	rent or sale	rent
firstVisibleDate	string	Yes	First published date	2023-06-27T13:28:52Z
keyFeatures	array	Yes	Key feature objects (description)	[{"description": "Fully Fitted"}]
countryCode	string	Yes	Country code	GB

Example dataset record

{
  "id": 136625822,
  "bedrooms": 0,
  "bathrooms": null,
  "summary": "Newly fitted office space available on ground and 1st floors.",
  "displayAddress": "6 Duke Street St. James's, London, SW1Y 6BN",
  "countryCode": "GB",
  "location": { "latitude": 51.507105, "longitude": -0.137131 },
  "propertySubType": "Office",
  "price": {
    "amount": 19241,
    "frequency": "monthly",
    "currencyCode": "GBP"
  },
  "transactionType": "rent",
  "propertyUrl": "https://www.zoopla.co.uk/properties/136625822",
  "firstVisibleDate": "2023-06-27T13:28:52Z",
  "imageUrl": "https://media.zoopla.co.uk/dir/crop/property-photo/...jpeg"
}

The record above was produced by the input in the next section: a search for properties in London.

Query and input reference

Input	Type	Required	Default	Accepted values	Description
urls	array	Yes	—	Zoopla search URLs	Listing search URLs to scrape
maxListings	integer	No	0	0 = unlimited	Maximum listings per URL (resets for each URL)
proxyConfiguration	object	No	US residential	Apify proxy settings	Proxy configuration

Minimal request:

{
  "urls": [
    { "url": "https://www.zoopla.co.uk/for-sale/property/london/?q=London&search_source=for-sale" }
  ]
}

Advanced request:

{
  "urls": [
    { "url": "https://www.zoopla.co.uk/for-sale/property/london/?q=London&search_source=for-sale" }
  ],
  "maxListings": 100,
  "proxyConfiguration": {
    "useApifyProxy": true,
    "apifyProxyGroups": ["RESIDENTIAL"],
    "apifyProxyCountry": "US"
  }
}

Retrieve the data through the API

1. Start the Actor with a JSON input containing at least one urls entry.
2. Wait for the run to finish.
3. Read records from the run's default dataset.
4. Paginate or export the dataset.

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")
run = client.actor("datascrapers/zoopla-scraper").call(
    run_input={
        "urls": [{"url": "https://www.zoopla.co.uk/for-sale/property/london/?q=London&search_source=for-sale"}],
        "maxListings": 100,
    }
)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item.get("id"), item.get("displayAddress"), item.get("price"))

Apify's generated API tab documents the equivalent calls for other languages.

Data quality and record handling

• Completeness — most fields are optional; id is always present.
• Source changes — pricing and availability reflect the response at scrape time.
• Deduplication — the Actor does not deduplicate across runs; use id as the stable key.
• Retry/error behavior — listings that cannot be resolved are skipped; the run continues.
• Normalization — price is an object with amount, frequency, and currency; dates are ISO 8601.

Export and pipeline examples

Destination	Recommended method	Typical use
PostgreSQL/Supabase	Dataset API or webhook consumer	Property market analysis
Google Sheets	Apify integration	Price monitoring
S3/cloud storage	Scheduled export or integration	Listing snapshots

Pricing and cost examples

Billing is pay per event: each listing record pushed to the dataset is one charge. Platform compute is included in the actor usage fee.

Records	Estimated base cost
1,000	$10.00
10,000	$100.00
100,000	$1,000.00

Estimates depend on the verified pricing model and the number of listings you request.

Limitations and responsible data use

• Only publicly accessible Zoopla listing data is returned.
• Prices and availability change frequently and reflect the moment of collection.
• Fields may be missing or conditional depending on the listing.
• No historical snapshots are stored unless you keep them yourself.
• You are responsible for complying with Zoopla's terms and applicable laws.

Dataset questions

What does one dataset item represent?

One property listing.

Which field should I use as a unique identifier?

Use id, the property identifier.

Are fields nullable or conditional?

Yes. Only id is always present; price, location, and other fields are conditional.

Can I retrieve the records as CSV or JSON?

Yes. Export the default dataset as JSON, CSV, Excel, or XML, or read it through the Apify Dataset API.

How do I paginate large datasets?

Set maxListings per URL, or paginate the dataset through the Dataset API.

What counts as a billable result?

Each listing record pushed to the dataset is one event charge.

Related datasets from Data Scrapers

• Rightmove Scraper — UK property listings for the same market analysis.
• Idealista Scraper — European property records that join with Zoopla data for cross-market comparison.
• Realtor Scraper — US property records for broader real estate datasets.
• Immobilienscout24 Scraper — German property listings for adjacent European markets.

Data Scrapers support

Need an additional field, record type, or export workflow? Contact Data Scrapers at stardustspotlight@gmail.com. Include a sample source URL, required fields, expected record volume, and preferred delivery format.