Scrape Recently Sold Property Prices & Dates on Property.com.au
Tuyen Tran
Collect Richmond sold listings with published prices and dates; edit the location to compare another Australian suburb. Returns up to 25 rows, subject to source availability. No schedule is created.
Input
Output fields
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The Property.com.au Scraper: Sold History & Estimates Actor is ready to run with the inputs already set for "Scrape Recently Sold Property Prices & Dates on Property.com.au". Sign up or log in and you'll land in Apify Console with a copy of this exact task.
Start the "Scrape Recently Sold Property Prices & Dates on Property.com.au" task
The Property.com.au Scraper: Sold History & Estimates Actor will start running based on the input automatically. You can also change all the input fields, like channel, state, and more, to match your specific use case.
Receive the "Scrape Recently Sold Property Prices & Dates on Property.com.au" output
Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as listing id, channel, full address, and more.
Integrate into your workflow
The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also run the "Scrape Recently Sold Property Prices & Dates on Property.com.au" task via API.

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Connect "Scrape Recently Sold Property Prices & Dates on Property.com.au" with 100+ integrations, or run it via API or MCP.
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The melbourne-sydney-sold-property-prices task returns addresses, priceDisplay, sold_date and listingUrl where the source publishes them.
The melbourne-sydney-sold-property-prices task starts with Richmond, VIC, 3121. It returns up to 25 rows; change the public location and filter fields for another search.
The melbourne-sydney-sold-property-prices task starts in Richmond, Melbourne. Sydney requires another run with a Sydney suburb and postcode.
The melbourne-sydney-sold-property-prices task can run from Apify Console or the task API. Export its dataset as CSV or JSON; configure schedules and integrations separately.