# Harcourts Scraper · AU Property Listings & Agents · $2/1k (`memo23/harcourts-scraper`) Actor Scrape Harcourts Australia property listings — buy, sold & rent search (with location, price & bedroom filters) or individual property URLs. Returns address, beds/baths/car, price, listing agents and photos in clean JSON/CSV. Auto-paginated, pure HTTP, no browser. - **URL**: https://apify.com/memo23/harcourts-scraper.md - **Developed by:** [Muhamed Didovic](https://apify.com/memo23) (community) - **Categories:** Real estate, Agents, Lead generation - **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Harcourts Scraper — Australian Property Listings, Prices & Agents Scrape **Harcourts Australia (harcourts.com.au) property listings** — search by buy / sold / rent (with location, price and bedroom filters) or pass individual property URLs. Every property comes back in one clean schema with address, beds/baths/car, price, agents, and photos. Pure HTTP, no browser. ![How it works](https://raw.githubusercontent.com/muhamed-didovic/muhamed-didovic.github.io/main/assets/how-it-works-harcourts.png) ### Why use this scraper - **Any Harcourts search, filters and all** — paste a `buy` / `sold` / `rent` URL with whatever filters you set (suburb, price range, bedrooms, bathrooms, property type) and the actor honours them and paginates through every matching result. - **Full property detail** — address (split into suburb/state/postcode), bedrooms, bathrooms, car spaces, price, listing agents, and photos on every row. - **Agent contacts** — each listing's agents (name, profile, photo) so you can build lead lists by office or region. - **Clean, flat output** — one row per property; toggle flattening for CSV-ready columns or keep nested JSON for code. - **Pure HTTP, no browser** — fast, cheap, reliable. Reads Harcourts' server-rendered pages directly. ### Overview The actor classifies each Harcourts URL (search / property / office), walks search results page by page (12 per page), fans out to each property, and normalises everything into a consistent `PropertyRow`. Ideal for buyers' agents, investors, PropTech teams, and B2B lead generation. ### Supported inputs | Input URL shape | Example | |---|---| | **Listing search** | `harcourts.com.au/au/listings/buy` (also `/sold`, `/rent`) | | **Filtered search** | `harcourts.com.au/au/listings/buy?location=…&bedrooms=3&minPrice=…` | | **Individual property** | `harcourts.com.au/au/office/{office}/listing/{id}-{slug}` | | **Office page** | `harcourts.com.au/au/office/{office}` (fans out to that office's listings) | > **Tip:** run a search on the Harcourts website, then copy the URL from your browser's address bar — the filter parameters drop straight into `startUrls`. ### Use cases - **Buyers' agents** — monitor new / sold listings by suburb and price band; pull listing-agent contacts. - **Investors & analysts** — track sold comparables and asking prices across regions. - **PropTech / data teams** — feed structured Harcourts listings into valuation models, CRMs, dashboards. - **Lead generation** — harvest agent + office contacts by area. ### How it works 1. You provide one or more Harcourts URLs (search, property, or office). 2. The actor classifies each URL and walks search results with `?page=N` pagination (filters preserved). 3. Each property is fetched and parsed (server-rendered HTML + JSON-LD). 4. Rows are normalised to one schema and streamed to your dataset — JSON or CSV. ### Input configuration | Field | Type | Default | Description | |---|---|---|---| | `startUrls` | array | — | Harcourts URLs (search / property / office) | | `harvestEmails` | boolean | `true` | Follow the office website + harvest contact emails | | `flatten` | boolean | `true` | Flatten nested fields for CSV-friendly output | | `maxItems` | integer | `10000` | Hard cap on rows collected | | `maxConcurrency` | integer | `8` | Parallel detail fetches | ### Output overview One row per property. Nested objects (`address`, `office`, `agents`) flatten to underscore keys (`address_suburb`, `office_name`) when `flatten` is on; arrays of objects become `*_json` strings. Disable `flatten` for full nested JSON. ### Output samples **Flattened (`flatten: true`, default):** ```json { "portal": "harcourts", "listingId": "40906443", "canonicalUrl": "https://harcourts.net/au/office/mandurah/listing/l40906443-49-willoughbridge-crescent-erskine-wa-6210", "listingMode": "sale", "propertyType": "House", "headline": "49 Willoughbridge Crescent, ERSKINE, WA 6210", "address_displayAddress": "49 Willoughbridge Crescent, ERSKINE, WA, 6210", "address_suburb": "ERSKINE", "address_state": "WA", "address_postcode": "6210", "bedrooms": 4, "bathrooms": 2, "priceDisplay": "From $895,000", "photosCount": 26, "office_name": "Mandurah", "agents_json": "[{\"name\":\"Keith Prevost\",\"profileUrl\":\"https://harcourts.net/...\"}]", "harvestedEmails": [] } ```` ### Key output fields | Field | Description | |---|---| | `listingId`, `canonicalUrl` | Identity | | `listingMode` | `sale` / `sold` / `rent` | | `propertyType` | House / Unit / Land / … | | `headline`, `description` | Listing copy | | `address` / `address_*` | display address, suburb, state, postcode | | `bedrooms`, `bathrooms`, `carspaces` | Specs | | `priceDisplay` | "From $895,000" / "Auction …" / "Offers Over …" / "Contact Agent" | | `photos[]`, `photosCount` | Listing photos | | `agents[]` / `agents_json` | Each agent's name, profile URL, photo | | `office` / `office_*` | Office name + profile URL | | `harvestedEmails[]` | Emails from the office website (when enabled) | ### FAQ **Can I scrape a filtered search?** Yes — paste any Harcourts search URL with its filters (location, price, bedrooms, etc.). They're preserved and paginated automatically. **Does it cover sold and rental listings?** Yes — `/au/listings/sold` and `/au/listings/rent` work the same as `/au/listings/buy`. **Why are some emails empty?** Email harvest follows the office website, which not all offices publish. Agent names + profile links are on every row regardless. ### Support Found a bug or need a field added? Open an issue on the actor's Apify Console page. ### Explore more scrapers - **[AU Property Multi-Portal Scraper](https://apify.com/memo23/au-property-multi-portal-scraper)** — Domain + Commercial + Ray White + Harcourts in one - **[Commercialrealestate.com.au Scraper](https://apify.com/memo23/commercialrealestate-au-scraper)** — AU commercial property - **[Domain.com.au Scraper](https://apify.com/memo23/domain-com-au-scraper)** — residential + agents Full portfolio: [apify.com/memo23](https://apify.com/memo23) ### ⚠️ Disclaimer This scraper accesses only publicly available data. Use the extracted data in compliance with Harcourts' Terms of Use, the Australian Privacy Act 1988, the Spam Act 2003, and all applicable laws. You are responsible for how you use scraped data — particularly personal information (agent names, contact details). This actor is not affiliated with, endorsed by, or connected to Harcourts International or any of its offices. ### SEO Keywords harcourts scraper, harcourts australia scraper, harcourts.com.au scraper, australian property scraper, harcourts listings scraper, real estate agent contacts scraper, property data australia, harcourts sold prices, harcourts rentals scraper, AU real estate data, property listings api australia, buyers agent data, harcourts property scraper, real estate scraper australia # Actor input Schema ## `startUrls` (type: `array`): Full harcourts.com.au URLs. Search/listing URLs are paginated and fanned out to individual properties automatically until `Maximum items` is reached. ## `harvestEmails` (type: `boolean`): When enabled (default), each row's office `websiteUrl` is followed and any contact emails found on that site are added to `harvestedEmails`. Per-URL deduped across the run. ## `flatten` (type: `boolean`): When enabled (default), nested objects (`address`, `office`, `agents`) are expanded to underscore-separated top-level keys (e.g. `address_suburb`). Arrays of objects are JSON-stringified into `*_json` fields. Disable to keep the full nested JSON. ## `maxItems` (type: `integer`): Hard cap on the number of properties collected. Harcourts search pages return 12 results each; use this cap to control billing. ## `maxConcurrency` (type: `integer`): Maximum number of detail pages fetched in parallel. 6-10 is the sweet spot. ## `minConcurrency` (type: `integer`): Minimum number of detail pages fetched in parallel. ## `maxRequestRetries` (type: `integer`): Number of retries before a failed request is given up. ## `proxy` (type: `object`): Defaults to Apify Residential with `country=AU` — the recommended pool for reliable Harcourts runs. Override with your own residential proxy provider if you prefer. ## Actor input object example ```json { "startUrls": [ "https://www.harcourts.com.au/au/listings/buy", "https://www.harcourts.com.au/au/listings/sold", "https://www.harcourts.com.au/au/listings/rent" ], "harvestEmails": true, "flatten": true, "maxItems": 10000, "maxConcurrency": 8, "minConcurrency": 1, "maxRequestRetries": 5, "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "AU" } } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "startUrls": [ "https://www.harcourts.com.au/au/listings/buy", "https://www.harcourts.com.au/au/listings/sold", "https://www.harcourts.com.au/au/listings/rent" ], "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "AU" } }; // Run the Actor and wait for it to finish const run = await client.actor("memo23/harcourts-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "startUrls": [ "https://www.harcourts.com.au/au/listings/buy", "https://www.harcourts.com.au/au/listings/sold", "https://www.harcourts.com.au/au/listings/rent", ], "proxy": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "AU", }, } # Run the Actor and wait for it to finish run = client.actor("memo23/harcourts-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "startUrls": [ "https://www.harcourts.com.au/au/listings/buy", "https://www.harcourts.com.au/au/listings/sold", "https://www.harcourts.com.au/au/listings/rent" ], "proxy": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "AU" } }' | apify call memo23/harcourts-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=memo23/harcourts-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Harcourts Scraper · AU Property Listings & Agents · $2/1k", "description": "Scrape Harcourts Australia property listings — buy, sold & rent search (with location, price & bedroom filters) or individual property URLs. Returns address, beds/baths/car, price, listing agents and photos in clean JSON/CSV. Auto-paginated, pure HTTP, no browser.", "version": "0.0", "x-build-id": "hbrr4XNddEfNWhIdT" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/memo23~harcourts-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-memo23-harcourts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/memo23~harcourts-scraper/runs": { "post": { "operationId": "runs-sync-memo23-harcourts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/memo23~harcourts-scraper/run-sync": { "post": { "operationId": "run-sync-memo23-harcourts-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "startUrls": { "title": "Harcourts property URLs", "type": "array", "description": "Full harcourts.com.au URLs. Search/listing URLs are paginated and fanned out to individual properties automatically until `Maximum items` is reached.", "items": { "type": "string" } }, "harvestEmails": { "title": "Harvest contact emails from the office website", "type": "boolean", "description": "When enabled (default), each row's office `websiteUrl` is followed and any contact emails found on that site are added to `harvestedEmails`. Per-URL deduped across the run.", "default": true }, "flatten": { "title": "Flatten nested fields for CSV-friendly output", "type": "boolean", "description": "When enabled (default), nested objects (`address`, `office`, `agents`) are expanded to underscore-separated top-level keys (e.g. `address_suburb`). Arrays of objects are JSON-stringified into `*_json` fields. Disable to keep the full nested JSON.", "default": true }, "maxItems": { "title": "Maximum items to scrape", "minimum": 1, "type": "integer", "description": "Hard cap on the number of properties collected. Harcourts search pages return 12 results each; use this cap to control billing.", "default": 10000 }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "type": "integer", "description": "Maximum number of detail pages fetched in parallel. 6-10 is the sweet spot.", "default": 8 }, "minConcurrency": { "title": "Min concurrency", "minimum": 1, "type": "integer", "description": "Minimum number of detail pages fetched in parallel.", "default": 1 }, "maxRequestRetries": { "title": "Max request retries", "minimum": 0, "type": "integer", "description": "Number of retries before a failed request is given up.", "default": 5 }, "proxy": { "title": "Proxy configuration", "type": "object", "description": "Defaults to Apify Residential with `country=AU` — the recommended pool for reliable Harcourts runs. Override with your own residential proxy provider if you prefer." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```