# LinkedIn Jobs Scraper - No Cookies, Salary + Dedup, AI Ready (`entranced_gelato/linkedin-jobs-scraper-pro`) Actor Scrapes publicly accessible LinkedIn job listings via guest endpoints - no login, no cookies. Dedup/delta mode, normalized salary + posted date, GDPR-safe defaults, MCP/AI-agent ready. - **URL**: https://apify.com/entranced\_gelato/linkedin-jobs-scraper-pro.md - **Developed by:** [AIDevs](https://apify.com/entranced_gelato) (community) - **Categories:** Jobs, MCP servers, AI - **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.90 / 1,000 job scrapeds 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## LinkedIn Jobs Scraper — No Cookies, Dedup + Salary Normalization, AI/MCP Ready Collect **publicly available LinkedIn job listings** at scale — **no login, no cookies, no credentials, ever.** This Actor reads only the same public guest pages anyone can see logged-out, then cleans the data into structured records with normalized salary, ISO posting dates, cross-run deduplication, and an AI/MCP-friendly output mode. > This Actor is not affiliated with, endorsed by, or sponsored by LinkedIn Corporation. "LinkedIn" is used descriptively to indicate the public source of the data. ### What it does - Scrapes public LinkedIn job listings by **search URL** (paste from linkedin.com/jobs/search) or by **structured filters** (keywords, location, remote type, experience level, contract type, date posted, company). - Returns full job fields plus a **normalized salary object**, an **ISO posting date**, optional **public company enrichment**, and optional **delta mode** that emits only jobs you haven't seen before. - Never asks for your LinkedIn password or session cookies, so your account is never put at risk. ### Why this one is different | Capability | This Actor | Typical LinkedIn jobs scrapers | |---|---|---| | Login / cookies required | **Never** — public guest data only | "Advanced" tiers require your session cookies | | Machine-readable salary | **Yes** — `{min, max, currency, period}` | Raw text only, if at all | | ISO posting date | **Yes** — `"2 weeks ago"` → ISO + confidence flag | Raw relative text | | Pay only for **new** jobs | **Yes** — delta mode with per-user memory | Re-charges for the same jobs each run | | Recruiter PII default | **Off** (GDPR-safe gate) | Often scraped silently | | AI / MCP output mode | **Yes** — concise, token-friendly records | Not optimized | | Run transparency | **Yes** — `_stats` telemetry per run | Silent partial results | | Beat the 1,000-cap | **Yes** — split-by-country expansion + dedup | Sometimes | ### Quick start #### Apify Console (UI) 1. Open the Actor, paste a LinkedIn job search URL into **Search URLs**, or fill in **Keywords** + **Location**. 2. Set **Max items** and click **Start**. #### API ```bash curl -X POST "https://api.apify.com/v2/acts/YOUR_USERNAME~linkedin-jobs-scraper-pro/runs?token=YOUR_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "keywords": "python developer", "location": "Berlin", "remoteTypes": ["remote","hybrid"], "maxItems": 100 }' ```` #### n8n / Make / Zapier Use the generic **Apify** connector, pick this Actor, and map the input fields above. Schedule it to run daily with `onlyNewJobs: true` to receive only fresh postings. #### MCP (AI agents) This Actor exposes a clean, richly described input schema and supports **standby mode**, so it works well when called from Apify's MCP server. For agent use, set `"outputFormat": "concise"` to get compact, token-friendly records: ```json { "keywords": "data scientist", "location": "Remote", "maxItems": 25, "outputFormat": "concise" } ``` ### Input reference | Field | Type | Default | Notes | |---|---|---|---| | `searchUrls` | string\[] | `[]` | Paste from linkedin.com/jobs/search. Takes precedence over filters. | | `keywords` | string | — | Supports quoted phrases and OR / AND / NOT. | | `location` | string | — | City, region, or country. | | `remoteTypes` | string\[] | `[]` | `remote`, `hybrid`, `onsite`. | | `experienceLevels` | string\[] | `[]` | `internship`…`executive`. | | `contractTypes` | string\[] | `[]` | `full-time`…`volunteer`. | | `datePosted` | string | `any` | `24h`, `week`, `month`, `any`. | | `companyNames` / `companyIds` | string\[] | `[]` | Restrict to specific companies. | | `maxItems` | integer | `100` | 1–100000, after dedup. | | `splitByCountry` | string | — | e.g. `US`; expands per-city to beat the 1,000-cap. | | `scrapeJobDetails` | boolean | `true` | Off = faster/cheaper cards-only. | | `companyEnrichment` | boolean | `false` | Attach public company page data. | | `includePosterInfo` | boolean | `false` | **GDPR gate** — recruiter PII, off by default. | | `onlyNewJobs` | boolean | `false` | Delta mode; only jobs unseen in prior runs. | | `outputFormat` | string | `full` | `full` or `concise` (AI/MCP). | ### Output reference (sample) ```json { "id": "3812345678", "url": "https://www.linkedin.com/jobs/view/3812345678/", "title": "Senior Python Developer", "companyName": "Acme Corp", "companyUrl": "https://www.linkedin.com/company/acme", "companyLogo": "https://media.licdn.com/logo1.png", "location": "Berlin, Germany", "salaryText": "€70,000 - €90,000/year", "salaryNormalized": { "min": 70000, "max": 90000, "currency": "EUR", "period": "year", "source": "€70,000 - €90,000/year" }, "postedText": "1 week ago", "postedAtISO": "2026-06-28T00:00:00.000Z", "postedAtResolved": true, "seniority": "Mid-Senior level", "employmentType": "Full-time", "jobFunction": "Engineering and Information Technology", "industries": "Software Development", "descriptionText": "We are looking for a Senior Python Developer…", "applicantsCount": 200, "applyUrl": "https://acme.example.com/careers/apply/123", "applyType": "external", "isNew": true, "scrapedAt": "2026-07-05T12:00:00.000Z" } ``` Every run also pushes a final `_stats` record and sets it as the run status message: ```json { "_stats": { "requested": 100, "scraped": 98, "duplicates": 2, "failed": 0, "blockRate": 0.0, "companiesEnriched": 0, "durationSeconds": 74, "stoppedReason": null } } ``` ### Pricing — pay per event You pay only for what you get. No monthly rental, no subscription. | Event | Price | |---|---| | Actor start | **$0.00** | | Each job scraped | **$0.0009** — that's **$0.90 per 1,000 jobs** (only unique, successfully scraped jobs; never duplicates or failures) | | Each company enriched | **$0.0015** ($1.50 per 1,000) | At **$0.90 / 1,000 jobs**, this Actor undercuts the most widely used LinkedIn jobs scrapers while adding normalized salary, ISO dates, delta mode, and GDPR-safe defaults on top. **Intro offer:** the first **200 jobs per user are free.** Cost examples (jobs only, after the free tier): - **100 jobs** → $0.09 - **1,000 jobs** → $0.90 - **10,000 jobs** → $9.00 With `onlyNewJobs: true`, a daily scheduled run charges only for genuinely new postings — often a handful of cents per day. ### Legality & compliance - **Public data only.** This Actor fetches only pages reachable while logged out. It never logs in, never sends cookies or credentials, and never attempts to bypass an authwall or CAPTCHA. In *hiQ v. LinkedIn*, scraping public data was held not to violate the CFAA; hiQ's loss turned on the User Agreement it had accepted through accounts — an agreement this Actor never accepts or uses. - **No circumvention.** This Actor collects publicly available listings. It does not bypass LinkedIn security or limits. - **Personal data (GDPR).** Job postings are largely non-personal. Recruiter / job-poster fields are personal data and are **off by default**. If you enable `includePosterInfo`, **you become the data controller** responsible for a lawful basis (e.g. Art. 6(1)(f) legitimate interest for recruitment research) and for honoring erasure requests. - **Your data stays yours.** Results are written only to your own Apify storage. This Actor does not build or redistribute a central database of job descriptions. - **Trademark.** "LinkedIn" is used only descriptively; no LinkedIn logo is used as the Actor icon. #### Data removal requests To request removal of personal data that may appear in results, please open a request on this Actor's **Issues tab** on Apify Store. We respond within 24 hours. ### FAQ **Why do big searches stop around 1,000 results?** That's LinkedIn's own per-search cap on public results. Set `splitByCountry` (e.g. `US`) and the Actor expands the search into per-city queries and de-duplicates across them. **How do I get only new jobs each day?** Schedule the Actor (free platform feature) and set `onlyNewJobs: true`. It remembers job IDs it has already returned for you and emits only new ones — so you also pay only for new items. **Can I export to CSV / Excel / JSON?** Yes — every run's dataset can be exported as JSON, CSV, or XLSX, and accessed via the API. Scheduling and webhooks are supported (all free platform features). **Does it need my LinkedIn login?** No — and it never will. That's the point. ### Support Found a problem or a markup change? Open an issue on the Actor's **Issues** tab. We aim to respond within **24 hours** and to fix selector breakages within 48 hours. # Actor input Schema ## `searchUrls` (type: `array`): One or more LinkedIn job search URLs copied from linkedin.com/jobs/search. Takes precedence over the structured filters below. Example: https://www.linkedin.com/jobs/search/?keywords=python%20developer\&location=Berlin ## `keywords` (type: `string`): Job search keywords. Supports quoted phrases and boolean operators (OR, AND, NOT) which are translated to guest search params where possible. Ignored if Search URLs are provided. ## `location` (type: `string`): Location to search in, e.g. a city, region, or country. Ignored if Search URLs are provided. ## `remoteTypes` (type: `array`): Filter by workplace type. Empty = any. ## `experienceLevels` (type: `array`): Filter by seniority. Empty = any. ## `contractTypes` (type: `array`): Filter by employment type. Empty = any. ## `datePosted` (type: `string`): Only include jobs posted within this window. ## `companyNames` (type: `array`): Restrict results to these company names (resolved to LinkedIn company filters where possible). ## `companyIds` (type: `array`): Restrict results to these numeric LinkedIn company IDs (f\_C filter). ## `maxItems` (type: `integer`): Maximum number of jobs to scrape across all search URLs (after dedup). LinkedIn caps a single search at ~1000 results — use Split by country to exceed that. ## `splitByCountry` (type: `string`): Country code (e.g. US, GB, IN, DE). When set, a single search is expanded into multiple per-city searches to collect more than LinkedIn's 1000-results-per-search cap, with cross-URL deduplication. Leave empty to disable. ## `scrapeJobDetails` (type: `boolean`): Fetch each job's detail page for full description, criteria (seniority, employment type, job function, industries) and applicant count. Turn off for a faster, cheaper cards-only run. ## `companyEnrichment` (type: `boolean`): Attach public company page data (description, website, employee count, industry, HQ). Charged separately per enriched company. ## `includePosterInfo` (type: `boolean`): When on, includes the job poster / recruiter's name, photo and profile URL. This is PERSONAL DATA — enabling it makes YOU the data controller responsible for a lawful basis (e.g. GDPR Art. 6(1)(f) legitimate interest) and for honoring erasure requests. Off by default. ## `onlyNewJobs` (type: `boolean`): Remember job IDs seen in previous runs (in a per-user named key-value store) and emit only jobs not seen before. Ideal for scheduled runs — you pay only for genuinely new postings. ## `outputFormat` (type: `string`): 'full' returns all fields; 'concise' returns a compact, token-friendly subset ideal for AI agents / MCP. ## `maxConcurrency` (type: `integer`): Maximum parallel requests. Kept low by default for rate discipline and to avoid blocks. ## `proxyConfiguration` (type: `object`): Proxy settings. Apify Proxy (datacenter group) is strongly recommended; the actor auto-escalates individual requests to residential only after repeated blocks, to control cost. ## Actor input object example ```json { "searchUrls": [ "https://www.linkedin.com/jobs/search/?keywords=python%20developer&location=Berlin" ], "keywords": "\"python developer\" OR \"backend engineer\" NOT senior", "location": "New York, NY", "remoteTypes": [ "remote", "hybrid" ], "datePosted": "any", "companyNames": [], "companyIds": [], "maxItems": 100, "splitByCountry": "US", "scrapeJobDetails": true, "companyEnrichment": false, "includePosterInfo": false, "onlyNewJobs": false, "outputFormat": "full", "maxConcurrency": 5, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [] } } ``` # 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 = { "searchUrls": [], "companyNames": [], "companyIds": [] }; // Run the Actor and wait for it to finish const run = await client.actor("entranced_gelato/linkedin-jobs-scraper-pro").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 = { "searchUrls": [], "companyNames": [], "companyIds": [], } # Run the Actor and wait for it to finish run = client.actor("entranced_gelato/linkedin-jobs-scraper-pro").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 '{ "searchUrls": [], "companyNames": [], "companyIds": [] }' | apify call entranced_gelato/linkedin-jobs-scraper-pro --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=entranced_gelato/linkedin-jobs-scraper-pro", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "LinkedIn Jobs Scraper - No Cookies, Salary + Dedup, AI Ready", "description": "Scrapes publicly accessible LinkedIn job listings via guest endpoints - no login, no cookies. Dedup/delta mode, normalized salary + posted date, GDPR-safe defaults, MCP/AI-agent ready.", "version": "1.0", "x-build-id": "lkeE10p5an1As2ZbB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/entranced_gelato~linkedin-jobs-scraper-pro/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-entranced_gelato-linkedin-jobs-scraper-pro", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/entranced_gelato~linkedin-jobs-scraper-pro/runs": { "post": { "operationId": "runs-sync-entranced_gelato-linkedin-jobs-scraper-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/entranced_gelato~linkedin-jobs-scraper-pro/run-sync": { "post": { "operationId": "run-sync-entranced_gelato-linkedin-jobs-scraper-pro", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchUrls": { "title": "Search URLs", "type": "array", "description": "One or more LinkedIn job search URLs copied from linkedin.com/jobs/search. Takes precedence over the structured filters below. Example: https://www.linkedin.com/jobs/search/?keywords=python%20developer&location=Berlin", "items": { "type": "string" } }, "keywords": { "title": "Keywords", "type": "string", "description": "Job search keywords. Supports quoted phrases and boolean operators (OR, AND, NOT) which are translated to guest search params where possible. Ignored if Search URLs are provided." }, "location": { "title": "Location", "type": "string", "description": "Location to search in, e.g. a city, region, or country. Ignored if Search URLs are provided." }, "remoteTypes": { "title": "Remote types", "type": "array", "description": "Filter by workplace type. Empty = any.", "items": { "type": "string", "enum": [ "remote", "hybrid", "onsite" ], "enumTitles": [ "Remote", "Hybrid", "On-site" ] } }, "experienceLevels": { "title": "Experience levels", "type": "array", "description": "Filter by seniority. Empty = any.", "items": { "type": "string", "enum": [ "internship", "entry", "associate", "mid-senior", "director", "executive" ], "enumTitles": [ "Internship", "Entry level", "Associate", "Mid-Senior level", "Director", "Executive" ] } }, "contractTypes": { "title": "Contract types", "type": "array", "description": "Filter by employment type. Empty = any.", "items": { "type": "string", "enum": [ "full-time", "part-time", "contract", "temporary", "internship", "volunteer" ], "enumTitles": [ "Full-time", "Part-time", "Contract", "Temporary", "Internship", "Volunteer" ] } }, "datePosted": { "title": "Date posted", "enum": [ "24h", "week", "month", "any" ], "type": "string", "description": "Only include jobs posted within this window.", "default": "any" }, "companyNames": { "title": "Company names", "type": "array", "description": "Restrict results to these company names (resolved to LinkedIn company filters where possible).", "items": { "type": "string" } }, "companyIds": { "title": "Company IDs", "type": "array", "description": "Restrict results to these numeric LinkedIn company IDs (f_C filter).", "items": { "type": "string" } }, "maxItems": { "title": "Max items", "minimum": 1, "maximum": 100000, "type": "integer", "description": "Maximum number of jobs to scrape across all search URLs (after dedup). LinkedIn caps a single search at ~1000 results — use Split by country to exceed that.", "default": 100 }, "splitByCountry": { "title": "Split by country (beat the 1000-cap)", "type": "string", "description": "Country code (e.g. US, GB, IN, DE). When set, a single search is expanded into multiple per-city searches to collect more than LinkedIn's 1000-results-per-search cap, with cross-URL deduplication. Leave empty to disable." }, "scrapeJobDetails": { "title": "Scrape job details", "type": "boolean", "description": "Fetch each job's detail page for full description, criteria (seniority, employment type, job function, industries) and applicant count. Turn off for a faster, cheaper cards-only run.", "default": true }, "companyEnrichment": { "title": "Company enrichment", "type": "boolean", "description": "Attach public company page data (description, website, employee count, industry, HQ). Charged separately per enriched company.", "default": false }, "includePosterInfo": { "title": "Include job poster info (GDPR gate)", "type": "boolean", "description": "When on, includes the job poster / recruiter's name, photo and profile URL. This is PERSONAL DATA — enabling it makes YOU the data controller responsible for a lawful basis (e.g. GDPR Art. 6(1)(f) legitimate interest) and for honoring erasure requests. Off by default.", "default": false }, "onlyNewJobs": { "title": "Only new jobs (delta mode)", "type": "boolean", "description": "Remember job IDs seen in previous runs (in a per-user named key-value store) and emit only jobs not seen before. Ideal for scheduled runs — you pay only for genuinely new postings.", "default": false }, "outputFormat": { "title": "Output format", "enum": [ "full", "concise" ], "type": "string", "description": "'full' returns all fields; 'concise' returns a compact, token-friendly subset ideal for AI agents / MCP.", "default": "full" }, "maxConcurrency": { "title": "Max concurrency", "minimum": 1, "maximum": 20, "type": "integer", "description": "Maximum parallel requests. Kept low by default for rate discipline and to avoid blocks.", "default": 5 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "Proxy settings. Apify Proxy (datacenter group) is strongly recommended; the actor auto-escalates individual requests to residential only after repeated blocks, to control cost.", "default": { "useApifyProxy": true, "apifyProxyGroups": [] } } } }, "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 } } } } } } } } } } ```