# Toctoc Property Search Scraper (`stealth_mode/toctoc-property-search-scraper`) Actor Scrape property listings from Toctoc.com with comprehensive real estate data. Collect 19+ fields including prices, location, images, property type, and operation details — perfect for market analysis, investment research, and real estate aggregation. - **URL**: https://apify.com/stealth\_mode/toctoc-property-search-scraper.md - **Developed by:** [Stealth mode](https://apify.com/stealth_mode) (community) - **Categories:** Automation, Developer tools, Real estate - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Toctoc Property Search Scraper: Extract Real Estate Listings at Scale --- ### What Is Toctoc.com? Toctoc.com is a prominent Latin American real estate platform, particularly dominant in Chile, offering thousands of property listings for sale and rent. It provides property seekers with detailed information across residential, commercial, and mixed-use properties. For investors, developers, and market researchers, manually extracting this data is inefficient and error-prone — the **Toctoc Property Search Scraper** automates the extraction process, delivering structured property records ready for analysis and integration. --- ### Overview The **Toctoc Property Search Scraper** extracts detailed property listings from Toctoc.com search results, converting unstructured web pages into clean, machine-readable datasets. It is designed for: - **Real estate investors** tracking market trends and pricing across regions - **Property developers** monitoring competitor listings and market demand - **Market researchers** analyzing the Latin American real estate landscape - **Aggregator platforms** integrating property data from multiple sources - **Data analysts** building dashboards and reports on property availability Key strengths include flexible URL targeting (search pages by property type, operation, or region), configurable item limits, and built-in error handling via `ignore_url_failures` to ensure uninterrupted collection across large datasets. --- ### Input Format The scraper accepts a JSON configuration object specifying search URLs and extraction parameters: ```json { "urls": [ "https://www.toctoc.com/venta/casa?o=ficha&d=venta" ], "ignore_url_failures": true, "max_items_per_url": 200 } ```` | Field | Description | Example | |---|---|---| | `urls` | Array of Toctoc search page URLs to scrape | `["https://www.toctoc.com/venta/casa"]` | | `max_items_per_url` | Maximum properties extracted per URL (1-200+) | `200` | | `ignore_url_failures` | If `true`, continues if some URLs fail; if `false`, stops on error | `true` | **Constructing URLs:** Use Toctoc search filters to target specific markets: - Property type: `/casa` (house), `/departamento` (apartment), `/comercial` (commercial) - Operation: `/venta` (sale), `/arriendo` (rent) - Region or commune filters automatically apply via URL parameters > **Tip:** Start with `max_items_per_url: 50-100` for testing, then scale to `200+` for bulk collection. *** ### Output Format **Sample output** ```json { "titulo": "Barrio Encanto de Molina", "comuna": "Molina", "region": "Maule", "imagen_principal": { "alt": "", "src": "https://d1cfu8v5n1wsm.cloudfront.net/toctoc/fotos/20230516/2572698/2026033152365970780.jpg" }, "imagen_inmobiliaria": { "alt": "", "src": "https://d1cfu8v5n1wsm.cloudfront.net/toctoc/logos/empresa/4042/2019111259179610434.jpg" }, "url_ficha": "https://www.toctoc.com/propiedades/compranuevo/casa/molina/barrio-encanto-de-molina/2572698", "url_ficha_itau": "", "es_destacada": false, "es_favorita": false, "es_oferta": false, "tipo_propiedad": "Casas", "tipo_operacion": "Venta Nuevo", "precios": [ { "order": 0, "prefix": "UF", "value": "2.350" }, { "order": 1, "prefix": "$", "value": "95.793.661" } ], "superficie": [ "65,89", "67,86" ], "dormitorios": [ "3", "3" ], "bannos": [ "2", "2" ], "badge": { "visible": false, "text": "", "text_color": "", "background_color": "" }, "oferta": { "precios": [ { "order": 0, "prefix": "", "value": "" }, { "order": 1, "prefix": "", "value": "" } ], "dscto_titulo": "", "dscto_porcentaje": 0, "dscto_monto": { "order": 0, "prefix": "", "value": "" } }, "horas_publicado": 26889, "card_wide": false, "beneficio_cliente": null, "client_id": 4042, "id_property": 2572698, "id_estado_propiedad": 1, "from_url": "https://www.toctoc.com/venta/casa?o=ficha&d=venta" } ``` Each property listing returns a structured record with 19 key fields: #### Property Identification & Location | Field | Description | Use Case | |---|---|---| | `ID Property` | Unique Toctoc identifier for the property | Database primary key | | `Título` | Property title/headline as shown on listing | Display and searching | | `Comuna` | Local municipality or district | Geographic filtering | | `Región` | Region or state (e.g., Metropolitana) | Regional analysis | | `URL Ficha` | Direct link to the property detail page | Source tracking, revisiting | | `URL Ficha Itaú` | Bank partner (Itaú) property detail link | Alternative access path | #### Property Details & Specifications | Field | Description | Use Case | |---|---|---| | `Tipo Propiedad` | Property category (house, apartment, etc.) | Filtering and segmentation | | `Tipo Operación` | Transaction type (sale, rent) | Market segment analysis | | `Superficie` | Total area in square meters | Size-based comparison | | `Dormitorios` | Number of bedrooms | Property classification | | `Baños` | Number of bathrooms | Amenity analysis | | `Precios` | Listed price in local currency | Price analytics | #### Listing Metadata & Images | Field | Description | Use Case | |---|---|---| | `Imagen Principal` | Main property photo URL | Visual database, thumbnails | | `Imagen Inmobiliaria` | Real estate professional photo | Brand/agency tracking | | `Horas Publicado` | Time since listing published | Freshness indicator | #### Flags & Promotion Status | Field | Description | Use Case | |---|---|---| | `Es Destacada` | Featured/promoted listing flag | Premium listing analysis | | `Es Favorita` | User-favorited listing indicator | Popularity metrics | | `Es Oferta` | Special offer or discount flag | Deal identification | | `Badge` | Promotional badge (e.g., "New", "Hot Deal") | Marketing effectiveness | | `Oferta` | Offer/discount details | Competitive pricing analysis | | `Card Wide` | Extended listing card format flag | Display format tracking | | `Beneficio Cliente` | Client benefit or bonus description | Marketing copy analysis | #### System Fields | Field | Description | |---|---| | `Client ID` | Toctoc client/seller identifier | | `ID Estado Propiedad` | Property status code (active, pending, sold) | *** ### How to Use 1. **Identify target URLs** — Browse Toctoc.com and find search results matching your criteria (e.g., houses for sale in Metropolitana, apartments for rent in a specific commune). 2. **Copy search URLs** — Grab the full URL from your browser. You can add multiple URLs to capture different markets simultaneously. 3. **Configure parameters** — Set `max_items_per_url` based on page depth (typically 20-50 listings per page; use `200` to capture multiple pages). 4. **Set error handling** — Keep `ignore_url_failures: true` for large runs to prevent interruption if a page temporarily fails. 5. **Run and export** — Start the scraper, monitor the log, and download results as JSON, CSV, or Excel. **Best practices:** - Use property-specific URLs (e.g., `/venta/casa`) to isolate market segments for cleaner analysis. - Start with `max_items_per_url: 50` to test URL structure before scaling. - Schedule regular scrapes to track price changes and new listings over time. *** ### Use Cases & Business Value - **Investment analysis:** Track pricing trends, rental yields, and market heat by region - **Competitive intelligence:** Monitor developer and broker listings to identify activity patterns - **Market reports:** Generate data-driven insights on supply, demand, and pricing - **Property aggregation:** Feed Toctoc data into custom portals or comparative property tools - **Lead generation:** Build prospect lists from newly listed properties matching investment criteria The Toctoc Property Scraper transforms market research from hours of manual browsing into minutes of automated extraction, enabling faster decisions and deeper market insights. *** ### Conclusion The **Toctoc Property Search Scraper** is an essential tool for anyone seeking structured real estate data from Latin America's leading platforms. With 19 detailed fields covering location, pricing, images, and promotion status, it delivers the complete dataset needed for investment analysis, market research, and property aggregation at scale. # Actor input Schema ## `urls` (type: `array`): Add the URLs of the property list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list. ## `ignore_url_failures` (type: `boolean`): If true, the scraper will continue running even if some URLs fail to be scraped. ## `max_items_per_url` (type: `integer`): The maximum number of items to scrape per URL. ## Actor input object example ```json { "urls": [ "https://www.toctoc.com/venta/casa?o=ficha&d=venta" ], "ignore_url_failures": true, "max_items_per_url": 20 } ``` # 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 = { "urls": [ "https://www.toctoc.com/venta/casa?o=ficha&d=venta" ], "ignore_url_failures": true, "max_items_per_url": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("stealth_mode/toctoc-property-search-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 = { "urls": ["https://www.toctoc.com/venta/casa?o=ficha&d=venta"], "ignore_url_failures": True, "max_items_per_url": 20, } # Run the Actor and wait for it to finish run = client.actor("stealth_mode/toctoc-property-search-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 '{ "urls": [ "https://www.toctoc.com/venta/casa?o=ficha&d=venta" ], "ignore_url_failures": true, "max_items_per_url": 20 }' | apify call stealth_mode/toctoc-property-search-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=stealth_mode/toctoc-property-search-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Toctoc Property Search Scraper", "description": "Scrape property listings from Toctoc.com with comprehensive real estate data. Collect 19+ fields including prices, location, images, property type, and operation details — perfect for market analysis, investment research, and real estate aggregation.", "version": "0.0", "x-build-id": "ebXnfRq1nTc9Tj0fZ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/stealth_mode~toctoc-property-search-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-stealth_mode-toctoc-property-search-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/stealth_mode~toctoc-property-search-scraper/runs": { "post": { "operationId": "runs-sync-stealth_mode-toctoc-property-search-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/stealth_mode~toctoc-property-search-scraper/run-sync": { "post": { "operationId": "run-sync-stealth_mode-toctoc-property-search-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": { "urls": { "title": "URLs of the property list urls to scrape", "type": "array", "description": "Add the URLs of the property list urls you want to scrape. You can paste URLs one by one, or use the Bulk edit section to add a prepared list.", "items": { "type": "string" } }, "ignore_url_failures": { "title": "Continue running even if some URLs fail to be scraped", "type": "boolean", "description": "If true, the scraper will continue running even if some URLs fail to be scraped." }, "max_items_per_url": { "title": "Max items per URL", "type": "integer", "description": "The maximum number of items to scrape per URL." } } }, "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 } } } } } } } } } } ```