# Talent Category Scraper (`getdataforme/talent-category-scraper`) Actor The Talent Category Scraper extracts comprehensive job listings from Talent.com, delivering titles, companies, locations, descriptions, and timestamps.... - **URL**: https://apify.com/getdataforme/talent-category-scraper.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** Jobs, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 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 ## Talent Category Scraper ### Introduction The Talent Category Scraper is a powerful Apify Actor designed to extract job listings from Talent.com, providing structured data on job titles, companies, locations, descriptions, and more. It enables efficient scraping of job search results, making it ideal for market research, recruitment analytics, and data-driven insights into the job market. With reliable performance and customizable parameters, this Actor helps users gather high-quality job data quickly and effortlessly. ### Features - **Comprehensive Job Data Extraction**: Scrapes detailed job information including titles, companies, locations, descriptions, and update timestamps from Talent.com. - **Customizable Crawling**: Supports starting URLs and limits on the number of requests for targeted scraping. - **High Reliability**: Built on CheerioCrawler for fast, efficient web scraping with minimal errors. - **Structured Output**: Delivers clean JSON data, easily exportable to CSV, Excel, or other formats. - **Scalable and Performant**: Handles large volumes of job listings while respecting rate limits to avoid blocking. - **Easy Integration**: Seamlessly integrates with Apify's platform for automated workflows and data pipelines. - **Real-Time Insights**: Includes scraped timestamps and source URLs for tracking data freshness. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|------|----------|-------------|---------| | startUrls | array | Yes | An array of URLs to start the crawling process. Each URL should point to a Talent.com job search page. | `[{"url": "https://www.talent.com/jobs?l=United+States+of+America&radius=100&id=606156942807670413"}]` | | maxItems | integer | No | The maximum number of requests (job pages) to crawl. Limits the scope to prevent excessive usage. Default is 100. | `50` | ### Example Usage #### Input JSON ```json { "startUrls": [ { "url": "https://www.talent.com/jobs?l=United+States+of+America&radius=100&id=606156942807670413" } ], "maxItems": 10 } ```` #### Output JSON ```json [ { "jobId": "f21c63845340", "newId": "606156942807670413", "rank": 1, "title": "Conveyancing Solicitor - Remote, Remote", "company": "Ten-Percent.co.uk", "location": "Remote, Remote", "badges": [ "Remote", "Full-time" ], "description": "Conveyancing Solicitor (JO9997).A new vacancy has arisen with a law firm in London providing fully remote services and looking for a locum to cover from the 21st May 2026 to 25th June 2026 inclusiv...", "detailUrl": "https://www.talent.com/view?id=606156942807670413", "lastUpdatedIso": "2026-02-11T19:19:41Z", "lastUpdatedText": "Last updated: 30+ days ago", "scrapedAt": "2026-03-15T11:20:50.810Z", "sourcePage": 1, "sourceUrl": "https://www.talent.com/jobs?l=United+States+of+America&radius=100&id=606156942807670413" } ] ``` ### Use Cases - **Market Research and Analysis**: Analyze job market trends by scraping listings across regions and industries. - **Competitive Intelligence**: Monitor competitors' hiring patterns and job postings. - **Recruitment Automation**: Build databases of job opportunities for HR teams or job boards. - **Academic Research**: Collect data for studies on employment, salaries, and skill demands. - **Business Intelligence**: Track job availability in specific sectors for strategic planning. - **Content Aggregation**: Compile job data for newsletters, reports, or dashboards. ### Installation and Usage 1. Search for "Talent Category Scraper" in the Apify Store 2. Click "Try for free" or "Run" 3. Configure input parameters 4. Click "Start" to begin extraction 5. Monitor progress in the log 6. Export results in your preferred format (JSON, CSV, Excel) ### Output Format The Actor outputs an array of JSON objects, each representing a scraped job listing. Key fields include: - `jobId`: Unique identifier for the job. - `title`: Job title. - `company`: Hiring company name. - `location`: Job location. - `badges`: Array of tags like "Remote" or "Full-time". - `description`: Job description snippet. - `detailUrl`: Link to the full job page. - `lastUpdatedIso`: ISO timestamp of last update. - `scrapedAt`: Timestamp when the data was scraped. - `sourceUrl`: Original search URL. This structured format ensures easy parsing and integration into databases or analytics tools. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: https://getdataforme.com/contact/ We're here to help you get the most out of this Actor! *** # Actor input Schema ## `startUrls` (type: `array`): URLs to start with. ## `maxItems` (type: `integer`): Maximum number of requests that can be made by this crawler. ## Actor input object example ```json { "startUrls": [ { "url": "https://www.talent.com/jobs?l=United+States+of+America&radius=100&id=606156942807670413" } ], "maxItems": 100 } ``` # Actor output Schema ## `results` (type: `string`): No description # 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": [ { "url": "https://www.talent.com/jobs?l=United+States+of+America&radius=100&id=606156942807670413" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/talent-category-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": [{ "url": "https://www.talent.com/jobs?l=United+States+of+America&radius=100&id=606156942807670413" }] } # Run the Actor and wait for it to finish run = client.actor("getdataforme/talent-category-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": [ { "url": "https://www.talent.com/jobs?l=United+States+of+America&radius=100&id=606156942807670413" } ] }' | apify call getdataforme/talent-category-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/talent-category-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Talent Category Scraper", "description": "The Talent Category Scraper extracts comprehensive job listings from Talent.com, delivering titles, companies, locations, descriptions, and timestamps....", "version": "0.0", "x-build-id": "xq9zuT8KTx3PO3mWB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~talent-category-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-talent-category-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~talent-category-scraper/runs": { "post": { "operationId": "runs-sync-getdataforme-talent-category-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~talent-category-scraper/run-sync": { "post": { "operationId": "run-sync-getdataforme-talent-category-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Start URLs", "type": "array", "description": "URLs to start with.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxItems": { "title": "Max Requests per Crawl", "type": "integer", "description": "Maximum number of requests that can be made by this crawler.", "default": 100 } } }, "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 } } } } } } } } } } ```