# Advanced LinkedIn Job Scraper (`api-empire/advanced-linkedin-job-scraper`) Actor - **URL**: https://apify.com/api-empire/advanced-linkedin-job-scraper.md - **Developed by:** [API Empire](https://apify.com/api-empire) (community) - **Categories:** Jobs, Automation, Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $4.99 / 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 ## 🚀 Advanced LinkedIn Job Scraper **Scrape thousands of LinkedIn jobs with rich, normalized output — keyword + location + company + industry + salary filters, full company profiles, and apply URLs.** Built for recruiters, talent intelligence teams, market researchers and engineers who need clean, structured LinkedIn job data without writing or maintaining their own scraper. --- ### ✨ Why choose this Actor? - ⚡ **Fast, async, autoscaling** — built on `aiohttp` with adaptive retries and per-item live saving so a crash never loses already-scraped jobs. - 🛡️ **Smart proxy fallback** — defaults to **no proxy**, automatically escalates to **Apify datacenter** then **residential** proxies the moment LinkedIn pushes back. - 🏢 **Full company enrichment** — every job includes company name, logo, website, employee count, follower count, industries, locations, and background cover. - 💰 **Salary, applicants, experience level, workplace type** — every field you'd see on a job card, normalized into one consistent JSON shape. - 🎯 **Powerful filters** — job title, location, company, workplace type (remote/hybrid/onsite), employment type, experience, salary band, posting recency, industry, easy-apply, early-applicant. - 📦 **Bulk-friendly** — supply lists of keywords, locations and companies; every combination is searched and de-duplicated. --- ### 🔑 Key features - 🔍 Search by **keyword + location + company** in one run - 🌍 Filter by **on-site / hybrid / remote** - 💼 Filter by **employment type** (full-time, part-time, contract, temporary, internship) - 🎯 Filter by **experience level** (intern → executive) - 💵 Filter by **minimum salary** ($40K → $200K+) - ⏰ Filter by **posting recency** (past hour / 24h / week / month) - 🏭 Filter by **industry IDs** - 🥇 Filter to **less-than-10-applicants** jobs (early-bird hiring) - ✅ Filter to **Easy Apply** only - 🔃 Sort by **relevance** or **date** - 📊 Per-job dataset row saved **incrementally** — no work lost on a crash - 🖥️ **Multiple table views** in the Apify Console: Overview, Company Profiles, Salary & Apply Info, Descriptions --- ### 📥 Input ```json { "searchKeywords": ["software engineer", "data scientist"], "locations": ["California", "New York"], "companyUrls": [ "https://www.linkedin.com/company/google", "Netflix" ], "maxItems": 50, "workplaceType": ["remote", "hybrid"], "employmentType": ["full_time", "contract"], "experienceLevel": ["mid-senior", "director"], "salary": ["120k+"], "postedLimit": "week", "sortBy": "date", "easyApply": false, "under10Applicants": false, "industryIds": ["4", "5", "6"], "geoIds": [], "page": 1, "li_at": "AQED...YOUR_COOKIE_HERE...", "requestDelaySeconds": 1, "proxyConfiguration": { "useApifyProxy": false } } ```` | Field | Type | Description | |---|---|---| | `searchKeywords` | array (required) | Job titles or keywords to search | | `locations` | array | Cities, states, countries to search in | | `companyUrls` | array | LinkedIn company URLs or names to filter by | | `maxItems` | integer | Max jobs per `keyword × location` combo (0 = unlimited) | | `workplaceType` | array | `on_site`, `remote`, `hybrid` | | `employmentType` | array | `full_time`, `part_time`, `contract`, `temporary`, `internship` | | `experienceLevel` | array | `internship`, `entry`, `associate`, `mid-senior`, `director`, `executive` | | `salary` | array | Minimum salary tier: `40k+` through `200k+` | | `postedLimit` | string | `""`, `1h`, `24h`, `week`, `month` | | `sortBy` | string | `relevance` (default) or `date` | | `easyApply` | boolean | Restrict to Easy Apply jobs only | | `under10Applicants` | boolean | Restrict to jobs with <10 applicants | | `industryIds` | array | LinkedIn industry IDs (e.g. `4` Software Dev) | | `geoIds` | array | LinkedIn geo IDs — overrides `locations` | | `page` | integer | Start page (each page = 25 jobs) | | `li_at` | string (required, secret) | Your LinkedIn `li_at` session cookie | | `requestDelaySeconds` | integer | Base delay between job-detail requests | | `proxyConfiguration` | object | Proxy config — default is **no proxy** with auto-fallback | *** ### 📤 Output Each job is pushed to the default dataset as a row with this shape: ```json { "id": "4406580591", "title": "Software Engineer, ML Fleet Intelligence", "linkedinUrl": "https://www.linkedin.com/jobs/view/4406580591/", "jobState": "LISTED", "postedDate": "2026-05-20T11:53:33.000Z", "headerCaptionText": "Google\nSunnyvale, CA\n2 days ago\nBe among the first 25 applicants\nSee who Google has hired for this role", "descriptionText": "Minimum qualifications: ...", "descriptionHtml": "Minimum qualifications:\n\n...", "location": { "linkedinText": "Sunnyvale, CA", "countryCode": "us", "parsed": { "text": "Sunnyvale, CA, United States", "countryCode": "US", "country": "United States", "state": "California", "city": "Sunnyvale" } }, "employmentType": "full_time", "workplaceType": "on_site", "easyApplyUrl": null, "applyMethod": { "companyApplyUrl": "https://careers.google.com/...", "type": "OffsiteApply" }, "applicants": 0, "company": { "id": "1441", "universalName": "google", "name": "Google", "logo": "https://media.licdn.com/...", "employeeCount": 342897, "followerCount": 41681887, "industries": [{ "name": "Software Development" }], "locations": [...] }, "salary": { "text": null, "min": null, "max": null }, "industries": ["Information Services", "Technology, Information and Internet"], "experienceLevel": "", "benefits": [], "query": { ... }, "_meta": { "pagination": { ... } } } ``` The dataset comes with four prebuilt views in the Apify Console: 1. 📋 **Overview** — id, title, company, location, salary, applicants, posted date 2. 🏢 **Company Profiles** — id, title, full company object 3. 💰 **Salary & Apply Info** — id, title, salary, apply URLs, applicant counts 4. 📝 **Job Descriptions** — id, title, full description text, industries, benefits *** ### 🚀 How to use the Actor (via Apify Console) 1. Log in at **[console.apify.com](https://console.apify.com)** → **Actors**. 2. Open **Advanced LinkedIn Job Scraper**. 3. Paste your `li_at` cookie (get it from DevTools → Application → Cookies on `linkedin.com`). 4. Add **search keywords** (e.g. `software engineer`) and **locations** (e.g. `California`). 5. Optionally narrow with **workplace type**, **employment type**, **salary**, **experience**, **company**, **industry**, etc. 6. Click **Start**. 7. Watch live progress in the **Log** tab — jobs stream to the **Dataset** tab as they're scraped. 8. Export to **JSON / CSV / Excel / XML / RSS** from the dataset, or pull them via the [Apify API](https://docs.apify.com/api/v2). *** ### 🛡️ Proxy strategy By default the scraper runs with **no proxy** (your run IP). When LinkedIn returns a block-style response (HTTP 401/403/429), the scraper: 1. 🔁 **Falls back to Apify datacenter proxy**, retries the same request. 2. 🏠 If datacenter is still blocked, **falls back to Apify residential proxy**, with up to **3 retries**. 3. 🔒 Once a fallback occurs, the new proxy is **sticky for the rest of the run** so you don't keep paying datacenter cost when datacenter is blocked. Every fallback is logged so you can see exactly what happened in the **Log** tab. *** ### 💡 Best use cases - 📈 Track open roles at competitor companies - 🧑‍💼 Build a recruiting pipeline of warm leads - 🔬 Salary & compensation research - 📊 Hiring-trends analysis by industry / region - 🤖 Feed structured job data into your own ATS or AI pipeline *** ### ❓ Frequently asked questions **Do I need a LinkedIn premium account?** No, a regular free LinkedIn account works. You just need the `li_at` cookie from a logged-in browser session. **Why is `li_at` required?** LinkedIn's full job API requires a session. The `li_at` cookie identifies your session. It's stored encrypted by Apify and never logged. **How many jobs can I scrape per run?** LinkedIn caps search results at around **1000 per query**. Use `maxItems` plus narrow filters (location, industry, salary) to stay within healthy limits. **Will my LinkedIn account get banned?** The scraper uses jittered delays, retries with backoff, and proxy fallback to stay polite. Risk is low at default settings but never zero — use a non-primary account for heavy scraping. **Can I scrape specific company pages?** Yes — pass full LinkedIn company URLs (or plain names) in `companyUrls`. Results are filtered to those employers. **What if a location returns no jobs?** Try the country name instead of a city (e.g. `United States` rather than `San Francisco`), or use a numeric `geoId` from a LinkedIn job-search URL. *** ### 🛟 Support and feedback Issues, feature requests and dataset samples — please file via the Actor's **Issues** tab on the Apify Store, or contact support through your Apify Console account. *** ### ⚠️ Legal & ethical notes - This Actor only retrieves **publicly listed jobs**. - You are responsible for complying with LinkedIn's Terms of Service, GDPR/CCPA, and any applicable scraping or data-protection laws in your jurisdiction. - Do not use scraped data for spam, harassment, or unauthorized outreach. # Actor input Schema ## `searchKeywords` (type: `array`): List one or more job titles or keywords to search on LinkedIn (e.g. `software engineer`, `data scientist`, `product manager`). Each entry runs as a separate search and the results are merged. ## `locations` (type: `array`): Locations to search in (e.g. `California`, `New York`, `United Kingdom`, `Remote`). Each entry runs as a separate search. Leave empty for worldwide. ## `li_at` (type: `string`): Your LinkedIn `li_at` cookie value. Required to access full job details. To get it: log in to LinkedIn → DevTools → Application → Cookies → `li_at`. Stored encrypted. ## `maxItems` (type: `integer`): Caps the number of jobs returned for every `keyword × location` combination. Set `0` for unlimited (capped internally at ~1000 to prevent runaway runs). ## `companyUrls` (type: `array`): Filter jobs to specific employers. Accepts LinkedIn company URLs (`https://www.linkedin.com/company/google`) or plain names (`Netflix`). Leave empty to include all employers. ## `workplaceType` (type: `array`): Filter by where the work is performed. ## `employmentType` (type: `array`): Filter by the type of employment offered. ## `experienceLevel` (type: `array`): Filter jobs by required experience level. ## `salary` (type: `array`): Filter by minimum annual base salary in USD. ## `under10Applicants` (type: `boolean`): Only include jobs with fewer than 10 applicants — early-bird hiring. ## `easyApply` (type: `boolean`): Only include jobs that support LinkedIn's one-click Easy Apply flow. ## `postedLimit` (type: `string`): Only return jobs posted within this time window. ## `industryIds` (type: `array`): LinkedIn industry IDs to filter by (e.g. `4` Software Development, `5` Computer Networking, `6` Internet, `96` IT Services). Leave empty for all industries. ## `sortBy` (type: `string`): Sort jobs by keyword relevance, or by most recent first. ## `geoIds` (type: `array`): Pre-resolved LinkedIn geo IDs (e.g. `103644278` USA, `101174742` Canada). When provided, overrides the `Locations Filter` above. ## `page` (type: `integer`): Page number to start from (each page = 25 jobs). Use `1` for first page. ## `requestDelaySeconds` (type: `integer`): Base delay between job-detail requests. A small random jitter is added automatically to reduce blocking risk. ## `userAgent` (type: `string`): Override the User-Agent header. Leave empty to use the default Chrome on Windows UA. ## `proxyConfiguration` (type: `object`): Proxy settings. By default the scraper runs **without a proxy**. If LinkedIn rejects the request, it automatically falls back to a **datacenter** proxy, and then to a **residential** proxy (with up to 3 retries). Once a fallback occurs, the new proxy is reused for the rest of the run. ## Actor input object example ```json { "searchKeywords": [ "software engineer" ], "locations": [ "New York", "California" ], "maxItems": 10, "companyUrls": [], "workplaceType": [], "employmentType": [], "experienceLevel": [], "salary": [], "under10Applicants": false, "easyApply": false, "postedLimit": "", "industryIds": [], "sortBy": "date", "geoIds": [], "page": 1, "requestDelaySeconds": 1, "userAgent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36", "proxyConfiguration": { "useApifyProxy": false } } ``` # 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 = { "searchKeywords": [ "software engineer" ], "locations": [ "New York", "California" ], "companyUrls": [], "proxyConfiguration": { "useApifyProxy": false } }; // Run the Actor and wait for it to finish const run = await client.actor("api-empire/advanced-linkedin-job-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 = { "searchKeywords": ["software engineer"], "locations": [ "New York", "California", ], "companyUrls": [], "proxyConfiguration": { "useApifyProxy": False }, } # Run the Actor and wait for it to finish run = client.actor("api-empire/advanced-linkedin-job-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 '{ "searchKeywords": [ "software engineer" ], "locations": [ "New York", "California" ], "companyUrls": [], "proxyConfiguration": { "useApifyProxy": false } }' | apify call api-empire/advanced-linkedin-job-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=api-empire/advanced-linkedin-job-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Advanced LinkedIn Job Scraper", "description": null, "version": "0.1", "x-build-id": "YFralXBsq5ktuk7Xi" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/api-empire~advanced-linkedin-job-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-api-empire-advanced-linkedin-job-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/api-empire~advanced-linkedin-job-scraper/runs": { "post": { "operationId": "runs-sync-api-empire-advanced-linkedin-job-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/api-empire~advanced-linkedin-job-scraper/run-sync": { "post": { "operationId": "run-sync-api-empire-advanced-linkedin-job-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "searchKeywords", "li_at" ], "properties": { "searchKeywords": { "title": "🔍 Search queries", "type": "array", "description": "List one or more job titles or keywords to search on LinkedIn (e.g. `software engineer`, `data scientist`, `product manager`). Each entry runs as a separate search and the results are merged.", "items": { "type": "string" } }, "locations": { "title": "📍 Locations Filter", "type": "array", "description": "Locations to search in (e.g. `California`, `New York`, `United Kingdom`, `Remote`). Each entry runs as a separate search. Leave empty for worldwide.", "items": { "type": "string" } }, "li_at": { "title": "🔐 LinkedIn Session Cookie (li_at)", "type": "string", "description": "Your LinkedIn `li_at` cookie value. Required to access full job details. To get it: log in to LinkedIn → DevTools → Application → Cookies → `li_at`. Stored encrypted." }, "maxItems": { "title": "📦 Maximum number of jobs to scrape per each job title and location input", "minimum": 0, "maximum": 100000, "type": "integer", "description": "Caps the number of jobs returned for every `keyword × location` combination. Set `0` for unlimited (capped internally at ~1000 to prevent runaway runs).", "default": 10 }, "companyUrls": { "title": "🏢 Company Filter", "type": "array", "description": "Filter jobs to specific employers. Accepts LinkedIn company URLs (`https://www.linkedin.com/company/google`) or plain names (`Netflix`). Leave empty to include all employers.", "items": { "type": "string" } }, "workplaceType": { "title": "🏠 Workplace Type", "uniqueItems": true, "type": "array", "description": "Filter by where the work is performed.", "items": { "type": "string", "enum": [ "on_site", "remote", "hybrid" ], "enumTitles": [ "🏢 On-site", "🌍 Remote", "🔀 Hybrid" ] }, "default": [] }, "employmentType": { "title": "💼 Employment Type", "uniqueItems": true, "type": "array", "description": "Filter by the type of employment offered.", "items": { "type": "string", "enum": [ "full_time", "part_time", "contract", "temporary", "internship" ], "enumTitles": [ "🕘 Full-time", "⏱️ Part-time", "📝 Contract", "📅 Temporary", "🎓 Internship" ] }, "default": [] }, "experienceLevel": { "title": "🎯 Experience Level", "uniqueItems": true, "type": "array", "description": "Filter jobs by required experience level.", "items": { "type": "string", "enum": [ "internship", "entry", "associate", "mid-senior", "director", "executive" ], "enumTitles": [ "🎓 Internship", "🌱 Entry-level", "👥 Associate", "🚀 Mid-Senior", "🧭 Director", "👑 Executive" ] }, "default": [] }, "salary": { "title": "💰 Salary Filter", "uniqueItems": true, "type": "array", "description": "Filter by minimum annual base salary in USD.", "items": { "type": "string", "enum": [ "40k+", "60k+", "80k+", "100k+", "120k+", "140k+", "160k+", "180k+", "200k+" ], "enumTitles": [ "💵 $40K+", "💵 $60K+", "💵 $80K+", "💵 $100K+", "💵 $120K+", "💵 $140K+", "💵 $160K+", "💵 $180K+", "💵 $200K+" ] }, "default": [] }, "under10Applicants": { "title": "🥇 Under 10 Applicants", "type": "boolean", "description": "Only include jobs with fewer than 10 applicants — early-bird hiring.", "default": false }, "easyApply": { "title": "✅ LinkedIn Easy Apply", "type": "boolean", "description": "Only include jobs that support LinkedIn's one-click Easy Apply flow.", "default": false }, "postedLimit": { "title": "⏰ Posted Limit", "enum": [ "", "1h", "24h", "week", "month" ], "type": "string", "description": "Only return jobs posted within this time window.", "default": "" }, "industryIds": { "title": "🏭 Industry IDs Filter", "type": "array", "description": "LinkedIn industry IDs to filter by (e.g. `4` Software Development, `5` Computer Networking, `6` Internet, `96` IT Services). Leave empty for all industries.", "default": [], "items": { "type": "string" } }, "sortBy": { "title": "🔃 Sort By", "enum": [ "relevance", "date" ], "type": "string", "description": "Sort jobs by keyword relevance, or by most recent first.", "default": "date" }, "geoIds": { "title": "🌐 LinkedIn Geo IDs", "type": "array", "description": "Pre-resolved LinkedIn geo IDs (e.g. `103644278` USA, `101174742` Canada). When provided, overrides the `Locations Filter` above.", "default": [], "items": { "type": "string" } }, "page": { "title": "📄 Start Page", "minimum": 1, "maximum": 100, "type": "integer", "description": "Page number to start from (each page = 25 jobs). Use `1` for first page.", "default": 1 }, "requestDelaySeconds": { "title": "⏳ Delay Between Requests (seconds)", "minimum": 0, "maximum": 30, "type": "integer", "description": "Base delay between job-detail requests. A small random jitter is added automatically to reduce blocking risk.", "default": 1 }, "userAgent": { "title": "🖥️ User Agent", "type": "string", "description": "Override the User-Agent header. Leave empty to use the default Chrome on Windows UA.", "default": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/120.0.0.0 Safari/537.36" }, "proxyConfiguration": { "title": "🛡️ Proxy Configuration", "type": "object", "description": "Proxy settings. By default the scraper runs **without a proxy**. If LinkedIn rejects the request, it automatically falls back to a **datacenter** proxy, and then to a **residential** proxy (with up to 3 retries). Once a fallback occurs, the new proxy is reused for the rest of the run.", "default": { "useApifyProxy": 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 } } } } } } } } } } ```