Realestate Australia Scraper

Every property on the search page — price, agent, land, history, coordinates.

Search realestate.com.au the way you normally would. Filter by suburb, price, bedrooms, property type, buy or rent. Paste the URL. Get every listing behind it as structured data, 44 fields per property.

Why this one

Buy, rent and sold, from the same actor. Whatever the search URL points at is what you get — listing_type tells you which. No separate scraper per mode.

Map-ready out of the box. Every listing carries lat and lon alongside suburb, state and postcode, so results drop straight into a map, a geo-join or a catchment analysis without geocoding a single address.

The agent comes with the property. Names and profile links for the listing agents, plus the agency branding — the lead data most property scrapers leave behind.

Sales history and valuation, not just the asking price. Past sale dates and agencies, plus the automated valuation estimate with its low/high range and a confidence level, so you can see what a property is asking and what it is reckoned to be worth.

What you get

The property — full street address, suburb, state, postcode, property type, house type, bedrooms, bathrooms, parking, land size and floor area (both as text and as numbers), year built, availability and off-market status.

The money — asking or estimated price, rent price with currency and bond, and the valuation estimate with its low, high and confidence.

The location — latitude and longitude, suburb, full suburb string, state and postcode.

The people — listing agents with profile links, agency branding, and the find-agents link.

The history — sales history, last sold date and agency, sold date, and the date the listing was published.

The media — image URLs and a photo count.

Sample output

One real row, abridged:

{
  "street_address": "31F/2 Watermans Quay",
  "suburb": "Barangaroo",
  "state": "NSW",
  "postcode": "2000",
  "property_type": "Apartment",
  "bedrooms": "2",
  "bathrooms": "2",
  "floor_area": "106",
  "estimated_price": "Contact Agent",
  "listing_type": "Buy",
  "lat": -33.8631339,
  "lon": 151.20209675,
  "agents": [{ "name": "Victoria Wu", "link": "https://www.realestate.com.au/..." }],
  "url": "https://www.realestate.com.au/property-apartment-nsw-barangaroo-...",
  "discovery_input": { "url": "https://www.realestate.com.au/buy/in-sydney,+nsw/list-1" }
}

That row came from a live run — 31 of its 34 present fields were populated. Export to JSON, CSV, Excel or XML, or pull it straight from the API.

Fields realestate.com.au does not publish for a property come back empty rather than guessed at, and how completely a listing is filled in varies: agent details and coordinates are near-universal, while valuation estimates and sales history depend on the property.

How it works

1. Search on realestate.com.au and copy the URL from your address bar.
2. Paste it into realestate.com.au search URLs. Add more URLs to run several searches at once.
3. Set a limit if you want one, and run it.

Input

Field	Required	What it does
realestate.com.au search URLs	yes	One or more buy, rent or sold search URLs. Every property behind each one is collected.
Max listings per URL	no	Stop after this many properties from each search. Prefilled at 10, so a first run is a quick sample. Raise it up to 1,000, or clear the field to collect 1,000 per URL.
Max listings in total	no	Stop the whole run after this many properties, across all searches. Up to 10,000; empty means 10,000.

Both limits are applied during collection rather than to the results afterwards, so a limited run genuinely does less work and finishes sooner. Every run is bounded, so a broad search can never run away with itself.

Run it once to see the shape of the data, then open it up. The prefilled 10 listings per URL keeps a first run quick and cheap.

Built to be trusted with real work

Stop a run at any time and keep what it found. Aborting stops the collection and delivers every property completed up to that moment. Nothing is abandoned and nothing half-fetched is passed off as a result.

You are never charged for a listing you did not receive. Properties that failed to fetch are reported separately and never reach your dataset.

Runs are self-limiting. Time budgets scale with the size of the request.

Clean, stable output. Field names come straight from the source schema and are not renamed or reshaped between runs.

No invented data. A field the site does not publish comes back empty. Nothing is inferred, averaged or filled in to make a row look complete.

What people use it for

• Investment screening — filter by yield, land size, price and location across whole suburbs at once.
• Comparable market analysis — pull every comparable listing in a catchment with coordinates and sales history attached.
• Agent and agency intelligence — see who is listing what, where, and at what price point.
• Market monitoring — track stock levels, asking prices and days on market by suburb over time.
• Lead generation — find agents and agencies active in a target area.

Free accounts

On a free Apify plan a run collects up to 10 property listings, whatever the limits above say. Nothing beyond that is collected, so a capped run finishes quickly. Upgrade to a paid plan and the limits above apply in full.

Good to know

• A search URL is checked for shape, not for results. Whether a search returns any properties is not knowable until collection runs.
• Repeated search URLs are collected once, so a duplicate never costs twice.
• Collection takes a few minutes even for a small run — most of the time goes into working through the search itself, not into the individual properties.
• If a search cannot be crawled, it is reported in the log and counted in the run summary rather than silently dropped.