# Tecnoempleo Scraper - Spain IT Jobs (`blackfalcondata/tecnoempleo-scraper`) Actor Scrape tecnoempleo.com - Spain's dedicated IT job board with 2,700+ active IT listings nationwide. Structured salary (min/max/period in EUR), skill taxonomy on every job, and incremental mode with repost detection for daily tracking. - **URL**: https://apify.com/blackfalcondata/tecnoempleo-scraper.md - **Developed by:** [Black Falcon Data](https://apify.com/blackfalcondata) (community) - **Categories:** Jobs, Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ### What does Tecnoempleo Scraper do? Tecnoempleo Scraper extracts structured job data from [tecnoempleo.com](https://tecnoempleo.com) — including salary data, contact details, company metadata, and full descriptions. It supports keyword search and controllable result limits, so you can run the same query consistently over time. The actor also offers detail enrichment (full descriptions and company metadata) where the source provides them. ### Key features - **Incremental mode** — recurring runs emit and charge only for listings that are new or whose tracked content changed. First run builds the baseline state; subsequent runs emit only new or changed records. - **Detail enrichment** — full descriptions and company metadata where the source provides them. - **Compact mode** — AI-agent and MCP-friendly payloads with core fields only. ### What data can you extract from tecnoempleo.com? Each result includes Core listing fields (`jobId`, `jobKey`, `title`, `location`, `province`, `country`, `workArrangement`, and `category`, and more), detail fields when enrichment is enabled (`description`, `descriptionText`, `descriptionHtml`, `descriptionMarkdown`, and `detailFetched`), contact and apply information (`directApply` and `applyUrl`), and company metadata (`company`, `companyUrl`, `companyLogo`, and `companyId`). In standard mode, all fields are always present — unavailable data points are returned as `null`, never omitted. In compact mode, only core fields are returned. Enable detail enrichment in the input to get richer fields such as full descriptions and company metadata where the source provides them. ### Input The main inputs are a search keyword and a result limit. Additional filters and options are available in the input schema. Key parameters: - **`query`** — Keyword or technology to search (e.g. 'python', 'sap', 'kubernetes'). Leave empty to browse all jobs. - **`province`** — Spanish province name (e.g. 'Madrid', 'Barcelona'). Leave empty for all provinces. - **`en_remoto`** — Filter by remote / hybrid / on-site. (default: `""`) - **`professionalSkill`** — Role category (e.g. 'Programador', 'Big Data', 'DevOps'). - **`experience`** — Minimum experience filter. - **`salary`** — Salary filter (site-specific value). - **`workday`** — Full-time / part-time / etc. - **`contractType`** — Indefinido / Temporal / Prácticas / etc. - **`date_start`** — Only return jobs posted on or after this date (YYYY-MM-DD). - **`maxResults`** — Maximum total results to return (0 = unlimited, up to ~2,700 active listings). (default: `100`) - **`includeDetails`** — Fetch full job details (HTML description, apply URL). Slower but richer output. (default: `true`) - **`descriptionMaxLength`** — Truncate description to N characters. 0 = no truncation. (default: `0`) - ...and 6 more parameters #### Input examples **Basic search** — Keyword-driven search with a result cap. → Full payload per result — all standard fields populated where the source provides them. ```json { "query": "python", "maxResults": 50 } ```` **Incremental tracking** — Only emit jobs that changed since the previous run with this `stateKey`. → First run builds the baseline state. Subsequent runs emit only records that are new or whose tracked content changed. Set `emitUnchanged: true` to include unchanged records as well. ```json { "query": "python", "maxResults": 200, "incrementalMode": true, "stateKey": "python-tracker" } ``` **Compact output for AI agents** — Return only core fields for AI-agent and MCP workflows. → Small payload with the most important fields — ideal for piping into LLMs without token overhead. ```json { "query": "python", "maxResults": 50, "compact": true } ``` ### Output Each run produces a dataset of structured job records. Results can be downloaded as JSON, CSV, or Excel from the Dataset tab in Apify Console. #### Example job record ```json { "jobId": "1461416ce80c343e6a9a2577766bb81aa315f9d2fb3eb47d23f066449b60ec14", "jobKey": "112c1f89c28ca30bce4f", "title": "Application Support Engineer", "company": "Geseme", "companyUrl": null, "companyLogo": "https://www.tecnoempleo.com/logotipos/203877.png", "companyId": null, "location": "Barcelona", "province": "Barcelona (Presencial)", "country": "España", "workArrangement": "ONSITE", "category": "Programador - Soporte Técnico", "technologies": [ "Transact SQL", "T SQL", ".Net Core", "C#" ], "description": "GESEME somos una consultoria de Salud laboral y Prevención de Riesgos Laborales. Nuestro objetivo es cuidar a las personas y mejorar las organizaciones. Estamos bucardo Application Support Engineer pa...", "descriptionText": "GESEME somos una consultoria de Salud laboral y Prevención de Riesgos Laborales. Nuestro objetivo es cuidar a las personas y mejorar las organizaciones. Estamos bucardo Application Support Engineer pa...", "descriptionHtml": "GESEME somos una consultoria de Salud laboral y Prevención de Riesgos Laborales. Nuestro objetivo es cuidar a las personas y mejorar las organizaciones. Estamos bucardo Application Support Engineer pa...", "descriptionMarkdown": "GESEME somos una consultoria de Salud laboral y Prevención de Riesgos Laborales. Nuestro objetivo es cuidar a las personas y mejorar las organizaciones. Estamos bucardo Application Support Engineer pa...", "summary": "GESEME somos una consultoria de Salud laboral y Prevención de Riesgos Laborales. Nuestro objetivo es cuidar a las personas y mejorar las organizaciones. Estamos bucardo Application Support Engineer p…", "salaryText": null, "salaryMin": null, "salaryMax": null, "salaryCurrency": null, "salaryPeriod": null, "employmentType": "FULL_TIME", "contractType": "Indefinido", "hoursPerWeek": "Jornada completa", "experienceLevel": "3-5 años", "educationLevel": "FP2/Grado Superior", "isUrgent": true, "isHighlighted": false, "isConfidential": null, "euWorkEligibilityRequired": null, "publishDate": "2026-04-16", "publishDateISO": "2026-04-16T00:00:00.000Z", "directApply": true, "url": "https://www.tecnoempleo.com/application-support-engineer-geseme/transact-sql-t-sql/rf-112c1f89c28ca30bce4f", "applyUrl": "https://www.tecnoempleo.com/application-support-engineer-geseme/transact-sql-t-sql/rf-112c1f89c28ca30bce4f", "portalUrl": "https://www.tecnoempleo.com/application-support-engineer-geseme/transact-sql-t-sql/rf-112c1f89c28ca30bce4f", "searchQuery": "", "contentQuality": "serp_only", "detailFetched": false, "scrapedAt": "2026-04-16T21:27:39.311Z", "source": "tecnoempleo.com", "contentHash": "6b601e59c9c45edb", "isRepost": false, "repostOfId": null, "repostDetectedAt": null, "originalPublishDate": null, "originalUrl": null, "changeType": "NEW" } ``` #### Incremental fields When `incremental: true`, each record also carries: - `changeType` — one of `NEW`, `UPDATED`, `UNCHANGED`, `REAPPEARED`, `EXPIRED`. Default output covers `NEW` / `UPDATED` / `REAPPEARED`; set `emitUnchanged: true` or `emitExpired: true` to opt into the others. - `firstSeenAt`, `lastSeenAt` — ISO-8601 timestamps tracking the listing across runs. - `isRepost`, `repostOfId`, `repostDetectedAt` — populated when a new listing matches the tracked content of a previously expired one. Set `skipReposts: true` to drop detected reposts from the output. ### How to scrape tecnoempleo.com 1. Go to [Tecnoempleo Scraper](https://apify.com/blackfalcondata/tecnoempleo-scraper?fpr=1h3gvi) in Apify Console. 2. Enter a search keyword. 3. Set `maxResults` to control how many results you need. 4. Enable `includeDetails` if you need full descriptions, contact info, or company data. 5. Click **Start** and wait for the run to finish. 6. Export the dataset as JSON, CSV, or Excel. ### Use cases - Extract job data from tecnoempleo.com for market research and competitive analysis. - Track salary trends across regions and categories over time. - Monitor new and changed listings on scheduled runs without processing the full dataset every time. - Build outreach lists using contact details and apply URLs from listings. - Research company hiring patterns, employer profiles, and industry distribution. - Feed structured data into AI agents, MCP tools, and automated pipelines using compact mode. - Export clean, structured data to dashboards, spreadsheets, or data warehouses. ### How much does it cost to scrape tecnoempleo.com? Tecnoempleo Scraper uses [pay-per-event](https://apify.com/pricing?fpr=1h3gvi) pricing. You pay a small fee when the run starts and then for each result that is actually produced. - **Run start:** $0.01 per run - **Per result:** $0.0015 per job record Example costs: - 10 results: **$0.03** - 100 results: **$0.16** - 500 results: **$0.76** #### Example: recurring monitoring savings These examples compare full re-scrapes with incremental runs at different churn rates. Churn is the share of listings that are new or whose tracked content changed since the previous run. Actual churn depends on your query breadth, source activity, and polling frequency — the scenarios below are examples, not predictions. Example setup: 250 results per run, daily polling (30 runs/month). Event-pricing examples scale linearly with result count. | Churn rate | Full re-scrape run cost | Incremental run cost | Savings vs full re-scrape | Monthly cost after baseline | |---|---:|---:|---:|---:| | 5% — stable niche query | $0.39 | $0.03 | $0.36 (93%) | $0.86 | | 15% — moderate broad query | $0.39 | $0.07 | $0.32 (83%) | $1.99 | | 30% — high-volume aggregator | $0.39 | $0.12 | $0.26 (68%) | $3.67 | Full re-scrape monthly cost at daily polling: $11.55. First month with incremental costs $1.22 / $2.31 / $3.94 for the 5% / 15% / 30% scenarios because the first run builds baseline state at full cost before incremental savings apply. Platform usage (compute and proxies) is billed separately by Apify based on actual consumption. Incremental runs consume less on result processing, though fixed per-run overhead stays the same. ### FAQ #### How many results can I get from tecnoempleo.com? The number of results depends on the search query and available listings on tecnoempleo.com. Use the `maxResults` parameter to control how many results are returned per run. #### Does Tecnoempleo Scraper support recurring monitoring? Yes. Enable incremental mode to only receive new or changed listings on subsequent runs. This is ideal for scheduled monitoring where you want to track changes over time without re-processing the full dataset. #### Can I integrate Tecnoempleo Scraper with other apps? Yes. Tecnoempleo Scraper works with Apify's [integrations](https://apify.com/integrations?fpr=1h3gvi) to connect with tools like Zapier, Make, Google Sheets, Slack, and more. You can also use webhooks to trigger actions when a run completes. #### Can I use Tecnoempleo Scraper with the Apify API? Yes. You can start runs, manage inputs, and retrieve results programmatically through the Apify API. Client libraries are available for JavaScript, Python, and other languages. #### Can I use Tecnoempleo Scraper through an MCP Server? Yes. Apify provides an [MCP Server](https://apify.com/apify/actors-mcp-server?fpr=1h3gvi) that lets AI assistants and agents call this actor directly. Use compact mode and `descriptionMaxLength` to keep payloads manageable for LLM context windows. #### Is it legal to scrape tecnoempleo.com? This actor extracts publicly available data from tecnoempleo.com. Web scraping of public information is generally considered legal, but you should always review the target site's terms of service and ensure your use case complies with applicable laws and regulations, including GDPR where relevant. #### Your feedback If you have questions, need a feature, or found a bug, please [open an issue](https://apify.com/blackfalcondata/tecnoempleo-scraper/issues?fpr=1h3gvi) on the actor's page in Apify Console. Your feedback helps us improve. ### You might also like - [Adzuna Job Scraper](https://apify.com/blackfalcondata/adzuna-scraper?fpr=1h3gvi) — Scrape adzuna.com - the global job board with 20+ country markets. Structured salary. - [APEC.fr Scraper - French Executive Jobs](https://apify.com/blackfalcondata/apec-scraper?fpr=1h3gvi) — Scrape apec.fr - French executive job listings with salary ranges, company, location, skills,. - [Arbeitsagentur Scraper - German Jobs](https://apify.com/blackfalcondata/arbeitsagentur-scraper?fpr=1h3gvi) — Scrape arbeitsagentur.de - Germany’s official employment portal with 1M+ listings. Contact data,. - [AutoScout24 Scraper](https://apify.com/blackfalcondata/autoscout24-scraper?fpr=1h3gvi) — Scrape autoscout24.com - Europe's largest used car marketplace with 770K+ listings. Structured. - [Bayt.com Scraper - Jobs from the Middle East](https://apify.com/blackfalcondata/bayt-scraper?fpr=1h3gvi) — Scrape bayt.com - the leading Middle East job board. Salary data, experience requirements. - [Bilbasen Scraper - Denmark’s Car Marketplace](https://apify.com/blackfalcondata/bilbasen-scraper?fpr=1h3gvi) — Scrape bilbasen.dk - Denmark’s largest car marketplace. Full vehicle specifications, seller. - [Bumeran Scraper](https://apify.com/blackfalcondata/bumeran-scraper?fpr=1h3gvi) — Scrape bumeran.com.ar - the largest job board across 8 LATAM countries. Work modality, contract. - [Cadremploi Job Scraper](https://apify.com/blackfalcondata/cadremploi-scraper?fpr=1h3gvi) — Scrape cadremploi.fr - French management and executive jobs. Salary ranges, apply links. ### Getting started with Apify New to Apify? [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=1h3gvi) — no credit card required. 1. Sign up — $5 platform credit included 2. Open this actor and configure your input 3. Click **Start** — export results as JSON, CSV, or Excel Need more later? [See Apify pricing](https://apify.com/pricing?fpr=1h3gvi). # Actor input Schema ## `query` (type: `string`): Keyword or technology to search (e.g. 'python', 'sap', 'kubernetes'). Leave empty to browse all jobs. ## `province` (type: `string`): Spanish province name (e.g. 'Madrid', 'Barcelona'). Leave empty for all provinces. ## `en_remoto` (type: `string`): Filter by remote / hybrid / on-site. ## `professionalSkill` (type: `string`): Role category (e.g. 'Programador', 'Big Data', 'DevOps'). ## `experience` (type: `string`): Minimum experience filter. ## `salary` (type: `string`): Salary filter (site-specific value). ## `workday` (type: `string`): Full-time / part-time / etc. ## `contractType` (type: `string`): Indefinido / Temporal / Prácticas / etc. ## `date_start` (type: `string`): Only return jobs posted on or after this date (YYYY-MM-DD). ## `maxResults` (type: `integer`): Maximum total results to return (0 = unlimited, up to ~2,700 active listings). ## `includeDetails` (type: `boolean`): Fetch full job details (HTML description, apply URL). Slower but richer output. ## `descriptionMaxLength` (type: `integer`): Truncate description to N characters. 0 = no truncation. ## `compact` (type: `boolean`): Core fields only — useful for AI-agent / MCP workflows. ## `incrementalMode` (type: `boolean`): Compare against previous run state. Emits NEW/UPDATED jobs; suppresses UNCHANGED/EXPIRED unless enabled. ## `stateKey` (type: `string`): Stable identifier for the tracked universe (required when incrementalMode is on). ## `emitUnchanged` (type: `boolean`): Also emit jobs that have not changed since the last run. ## `emitExpired` (type: `boolean`): Also emit jobs that have disappeared since the last run. ## `skipReposts` (type: `boolean`): When incremental, skip jobs whose content matches an expired job from a prior run (cross-run repost detection). ## Actor input object example ```json { "query": "python", "en_remoto": "", "maxResults": 25, "includeDetails": true, "descriptionMaxLength": 0, "compact": false, "incrementalMode": false, "emitUnchanged": false, "emitExpired": false, "skipReposts": false } ``` # 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 = { "query": "python", "maxResults": 25 }; // Run the Actor and wait for it to finish const run = await client.actor("blackfalcondata/tecnoempleo-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 = { "query": "python", "maxResults": 25, } # Run the Actor and wait for it to finish run = client.actor("blackfalcondata/tecnoempleo-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 '{ "query": "python", "maxResults": 25 }' | apify call blackfalcondata/tecnoempleo-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=blackfalcondata/tecnoempleo-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tecnoempleo Scraper - Spain IT Jobs", "description": "Scrape tecnoempleo.com - Spain's dedicated IT job board with 2,700+ active IT listings nationwide. Structured salary (min/max/period in EUR), skill taxonomy on every job, and incremental mode with repost detection for daily tracking.", "version": "0.1", "x-build-id": "xbQ36gpRlPGCSDdn3" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/blackfalcondata~tecnoempleo-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-blackfalcondata-tecnoempleo-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/blackfalcondata~tecnoempleo-scraper/runs": { "post": { "operationId": "runs-sync-blackfalcondata-tecnoempleo-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/blackfalcondata~tecnoempleo-scraper/run-sync": { "post": { "operationId": "run-sync-blackfalcondata-tecnoempleo-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "query": { "title": "Search Query", "type": "string", "description": "Keyword or technology to search (e.g. 'python', 'sap', 'kubernetes'). Leave empty to browse all jobs." }, "province": { "title": "Province", "type": "string", "description": "Spanish province name (e.g. 'Madrid', 'Barcelona'). Leave empty for all provinces." }, "en_remoto": { "title": "Work Arrangement", "enum": [ "", "1", "2", "3" ], "type": "string", "description": "Filter by remote / hybrid / on-site.", "default": "" }, "professionalSkill": { "title": "Professional Function", "type": "string", "description": "Role category (e.g. 'Programador', 'Big Data', 'DevOps')." }, "experience": { "title": "Experience Level", "type": "string", "description": "Minimum experience filter." }, "salary": { "title": "Salary Range", "type": "string", "description": "Salary filter (site-specific value)." }, "workday": { "title": "Work Schedule", "type": "string", "description": "Full-time / part-time / etc." }, "contractType": { "title": "Contract Type", "type": "string", "description": "Indefinido / Temporal / Prácticas / etc." }, "date_start": { "title": "Posted Since", "type": "string", "description": "Only return jobs posted on or after this date (YYYY-MM-DD)." }, "maxResults": { "title": "Max Results", "minimum": 0, "maximum": 50000, "type": "integer", "description": "Maximum total results to return (0 = unlimited, up to ~2,700 active listings).", "default": 100 }, "includeDetails": { "title": "Include Job Details", "type": "boolean", "description": "Fetch full job details (HTML description, apply URL). Slower but richer output.", "default": true }, "descriptionMaxLength": { "title": "Description Max Length", "minimum": 0, "type": "integer", "description": "Truncate description to N characters. 0 = no truncation.", "default": 0 }, "compact": { "title": "Compact Output", "type": "boolean", "description": "Core fields only — useful for AI-agent / MCP workflows.", "default": false }, "incrementalMode": { "title": "Incremental Mode", "type": "boolean", "description": "Compare against previous run state. Emits NEW/UPDATED jobs; suppresses UNCHANGED/EXPIRED unless enabled.", "default": false }, "stateKey": { "title": "State Key", "type": "string", "description": "Stable identifier for the tracked universe (required when incrementalMode is on)." }, "emitUnchanged": { "title": "Emit Unchanged", "type": "boolean", "description": "Also emit jobs that have not changed since the last run.", "default": false }, "emitExpired": { "title": "Emit Expired", "type": "boolean", "description": "Also emit jobs that have disappeared since the last run.", "default": false }, "skipReposts": { "title": "Skip Reposts", "type": "boolean", "description": "When incremental, skip jobs whose content matches an expired job from a prior run (cross-run repost detection).", "default": false } } }, "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 } } } } } } } } } } ```