# InfoJobs Spain Job Scraper — Empleo España (`nomad-agent/infojobs-scraper`) Actor Extract live openings from InfoJobs.net, Spain's largest job board. Filter by keyword and province; each record includes title, company, location, salary band, contract type and apply URL. Built for Spanish job boards, recruiting agencies and labour-market analysis. - **URL**: https://apify.com/nomad-agent/infojobs-scraper.md - **Developed by:** [Nomad.Dev](https://apify.com/nomad-agent) (community) - **Categories:** Jobs - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## InfoJobs Spain Job Scraper — Empleo España Scrape current vacancies from InfoJobs.net, the biggest job board in Spain, with keyword and province filtering. ### What InfoJobs data does this scraper extract? Each result is one flat JSON record per job posting: | Field | Meaning | |---|---| | `title` | Job title as posted | | `company` | Hiring company / organisation | | `location` | Location / duty station (may include remote hints) | | `url` | Direct link to the posting | | `postedAt` | Posting date where the source provides it | | `salary` | Salary text where the source provides it | | `snippet` | Short description excerpt | | `id` | Stable source-side identifier | | `source` | Always `"infojobs"` — handy when merging datasets from several job scrapers | ### How to scrape InfoJobs with this Actor 1. Click **Try for free** / **Run** — no login to the target site, no cookies, no proxies to configure. 2. Adjust the input (keyword, filters, `maxItems`) or keep the defaults. 3. Run it and export the dataset as JSON, CSV or Excel, or read it over the [API](https://docs.apify.com/api/v2). Run it from your own code: ```python from apify_client import ApifyClient client = ApifyClient("") run = client.actor("nomad-agent/infojobs-scraper").call(run_input={"maxItems": 50}) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item["title"], "—", item["company"], item["url"]) ```` Or a single HTTP call that runs the Actor and returns items in one response: ```bash curl -X POST \ "https://api.apify.com/v2/acts/nomad-agent~infojobs-scraper/run-sync-get-dataset-items?token=" \ -H "Content-Type: application/json" \ -d '{"maxItems": 50}' ``` ### Input | Field | Type | Default | Notes | |---|---|---|---| | `keyword` | string | `""` | Free-text search query (e.g. "data engineer", "marketing"). Leave empty to return the latest postings across all categories. | | `province` | string (select) | `""` | Restrict results to a single Spanish province (e.g. Madrid, Barcelona). Leave as "All provinces" to search nationwide. | | `postedSince` | integer | `0` | Only return listings posted within this many days. See "Freshness filtering" below. Set 0 to disable. | | `titleExclude` | array of strings | `[]` | Skip listings whose title contains any of these case-insensitive terms. | | `companyExclude` | array of strings | `[]` | Skip listings whose company name contains any of these case-insensitive terms. | | `maxItems` | integer | `15` | Maximum number of postings to return. InfoJobs returns roughly 10–15 cards per page; set 0 for no additional cap. | | `timeoutSecs` | integer | `25` | How long to wait for InfoJobs to respond before giving up, in seconds. *(Advanced)* | | `cacheTtlSeconds` | integer | `1800` | Reuses the last fetch for this many seconds so rapid re-runs don't hit InfoJobs again. Set 0 to always fetch live. *(Advanced)* | #### Freshness filtering (`postedSince`) InfoJobs shows posting dates as relative Spanish text on the search page, not an ISO date — typically a compact badge like `"Hace 14m"` (minutes), `"Hace 2h"` (hours) or `"Hace 6d"` (days), occasionally a spelled-out form like `"Hace 2 semanas"` or `"Hace 3 meses"`. When `postedSince` is set, this text is parsed into an approximate age in days *for filtering only* — the `postedAt` field in the output always keeps the original, unmodified text. Listings whose date text doesn't match a known pattern are always kept, since their age can't be judged. ### Output example ```json { "id": "if-9982314", "title": "Desarrollador/a Full Stack", "company": "Indra", "location": "Madrid (Híbrido)", "url": "https://www.infojobs.net/madrid/desarrollador-full-stack/of-i9982314", "postedAt": "Hace 2h", "salary": "35.000–45.000 €", "snippet": "Buscamos desarrollador/a full stack...", "source": "infojobs" } ``` ### Integrations Export results as JSON, CSV or Excel; connect via Make, Zapier or n8n; call directly with `run-sync-get-dataset-items`; or plug into AI agents through the Apify MCP server. ### Pricing Pay per event: **$0.05 per Actor start** and **$0.004 per job returned**. 100 jobs ≈ $0.45. No subscription, no rental — you pay only for what you fetch. ### Use cases - Spanish job boards and alert bots (empleo en España) - Recruiting agencies sourcing Spain-based talent - Salary benchmarking for the Spanish market - Regional labour-market dashboards ### FAQ **Is it legal to scrape InfoJobs?** This Actor reads only publicly available job postings — data any visitor can see without logging in. No personal data behind authentication is touched. Review the target site's terms and your local regulations for your specific use case. **Do I need an account on the target site?** No. Postings are fetched from public pages/APIs — no login, cookies or session tokens. **How fresh is the data?** Every run fetches live listings. Results are cached for `cacheTtlSeconds` (default 30 min, set 0 to always hit the source live). **How many jobs can I get?** `maxItems` caps the run (set 0 where supported for no cap). Most sources paginate from newest to oldest. **Something broken or missing?** Open an issue on the Actor's **Issues** tab — it is monitored and reliability fixes ship fast. ### Related Actors - [Web Developer Jobs Scraper — 10 Boards in One](https://apify.com/nomad-agent/web-dev-bundle) - [Tecnoempleo Scraper — Spain IT & Tech Jobs](https://apify.com/nomad-agent/tecnoempleo-scraper) - [EURES Job Scraper — EU Job Mobility Portal](https://apify.com/nomad-agent/eures-scraper) # Actor input Schema ## `keyword` (type: `string`): Free-text search query (e.g. "data engineer", "marketing"). Leave empty to return the latest postings across all categories. ## `province` (type: `string`): Restrict results to a single Spanish province. Leave as "All provinces" to search nationwide. ## `postedSince` (type: `integer`): Only return listings posted within this many days. InfoJobs shows posting dates as relative Spanish text (e.g. "Hace 14m", "Hace 2h", "Hace 6d", or spelled out as "Hace 2 semanas"), which is parsed into an approximate age for this filter only — the `postedAt` output field always keeps the original text. Listings whose date text doesn't match a known pattern are always kept (can't be judged, so they're not dropped). Set 0 (default) to disable and return all fetched listings regardless of age. ## `titleExclude` (type: `array`): Skip listings whose title contains any of these case-insensitive terms. ## `companyExclude` (type: `array`): Skip listings whose company name contains any of these case-insensitive terms. ## `maxItems` (type: `integer`): Maximum number of postings to return. InfoJobs returns roughly 10–15 cards per page; set 0 for no additional cap. ## `timeoutSecs` (type: `integer`): How long to wait for InfoJobs to respond before giving up, in seconds. ## `cacheTtlSeconds` (type: `integer`): Reuses the last fetch for this many seconds so rapid re-runs don't hit InfoJobs again. Set 0 to always fetch live. ## Actor input object example ```json { "keyword": "software engineer", "province": "", "postedSince": 0, "titleExclude": [ "becario", "practicas" ], "companyExclude": [], "maxItems": 15, "timeoutSecs": 25, "cacheTtlSeconds": 1800 } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("nomad-agent/infojobs-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 = {} # Run the Actor and wait for it to finish run = client.actor("nomad-agent/infojobs-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 '{}' | apify call nomad-agent/infojobs-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nomad-agent/infojobs-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "InfoJobs Spain Job Scraper — Empleo España", "description": "Extract live openings from InfoJobs.net, Spain's largest job board. Filter by keyword and province; each record includes title, company, location, salary band, contract type and apply URL. Built for Spanish job boards, recruiting agencies and labour-market analysis.", "version": "0.1", "x-build-id": "NCKAQgbaUsX4v6Hjz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nomad-agent~infojobs-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nomad-agent-infojobs-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nomad-agent~infojobs-scraper/runs": { "post": { "operationId": "runs-sync-nomad-agent-infojobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nomad-agent~infojobs-scraper/run-sync": { "post": { "operationId": "run-sync-nomad-agent-infojobs-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "keyword": { "title": "Keyword", "type": "string", "description": "Free-text search query (e.g. \"data engineer\", \"marketing\"). Leave empty to return the latest postings across all categories." }, "province": { "title": "Province", "enum": [ "", "28", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", "21", "22", "23", "24", "25", "26", "27", "29", "20", "30", "31", "32", "33", "34", "35", "36", "37", "38", "39", "40", "41", "46", "42", "43", "44", "45", "47", "48", "49", "50", "51", "52", "53" ], "type": "string", "description": "Restrict results to a single Spanish province. Leave as \"All provinces\" to search nationwide.", "default": "" }, "postedSince": { "title": "Posted within last N days", "minimum": 0, "type": "integer", "description": "Only return listings posted within this many days. InfoJobs shows posting dates as relative Spanish text (e.g. \"Hace 14m\", \"Hace 2h\", \"Hace 6d\", or spelled out as \"Hace 2 semanas\"), which is parsed into an approximate age for this filter only — the `postedAt` output field always keeps the original text. Listings whose date text doesn't match a known pattern are always kept (can't be judged, so they're not dropped). Set 0 (default) to disable and return all fetched listings regardless of age.", "default": 0 }, "titleExclude": { "title": "Title must NOT contain", "type": "array", "description": "Skip listings whose title contains any of these case-insensitive terms.", "default": [], "items": { "type": "string" } }, "companyExclude": { "title": "Company must NOT contain", "type": "array", "description": "Skip listings whose company name contains any of these case-insensitive terms.", "default": [], "items": { "type": "string" } }, "maxItems": { "title": "Max items", "minimum": 0, "type": "integer", "description": "Maximum number of postings to return. InfoJobs returns roughly 10–15 cards per page; set 0 for no additional cap.", "default": 15 }, "timeoutSecs": { "title": "Request timeout (seconds)", "minimum": 5, "type": "integer", "description": "How long to wait for InfoJobs to respond before giving up, in seconds.", "default": 25 }, "cacheTtlSeconds": { "title": "Cache TTL (seconds)", "minimum": 0, "type": "integer", "description": "Reuses the last fetch for this many seconds so rapid re-runs don't hit InfoJobs again. Set 0 to always fetch live.", "default": 1800 } } }, "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 } } } } } } } } } } ```