Scrape Recently Sold Property Prices on Realestate.com.au
Collect recently sold Richmond, VIC listings with published sale prices, property fields and source links. Returns up to 25 rows, subject to source availability. No schedule is created.
Input
Output fields
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The Realestate.com.au Scraper: Price Drops & Agent Leads Actor is ready to run with the inputs already set for "Scrape Recently Sold Property Prices on Realestate.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 on Realestate.com.au" task
The Realestate.com.au Scraper: Price Drops & Agent Leads 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 on Realestate.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, property type, 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 on Realestate.com.au" task via API.
Integrate "Scrape Recently Sold Property Prices on Realestate.com.au" into your workflow
Connect "Scrape Recently Sold Property Prices on Realestate.com.au" with 100+ integrations, or run it via API or MCP.
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The recently-sold-property-prices-au task returns sold listing addresses, published priceDisplay and listingUrl for Richmond, VIC.
The recently-sold-property-prices-au task starts with Richmond, VIC, 3121. It returns up to 25 rows; change the public location and filter fields for another search.
The recently-sold-property-prices-au task cannot recover withheld sale prices. Undisclosed values stay empty or retain the source text.
The recently-sold-property-prices-au task can run from Apify Console or the task API. Export its dataset as CSV or JSON; configure schedules and integrations separately.