# LinkedIn Profile Scraper — Experience & Skills ✅ No Cookies (`neuralverge/neuralverge-linkedin-person`) Actor
Extract LinkedIn profile data in bulk — experience, education, skills, connections, followers and posts — from a URL or username. Pay only for profiles found. No cookies or account required.
- **URL**: https://apify.com/neuralverge/neuralverge-linkedin-person.md
- **Developed by:** [NeuralVerge](https://apify.com/neuralverge) (community)
- **Categories:** Lead generation, Social media, Automation
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $5.00 / 1,000 results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js/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 Profile Scraper — Experience & Skills ✅ No Cookies
Extract structured **LinkedIn profile data** — name, headline, location,
connections, followers, about, full work experience, education, certifications,
languages and recent posts — from a profile URL or username. Powered by the
Neuralverge API. **No cookies or account required**, and **you only pay for
profiles we actually find**.
Ideal for recruiting and sourcing, lead enrichment, CRM hydration, and feeding
people data to AI agents.
### ✨ Why this Actor
- 💸 **Pay only for the profiles you get** — unresolved URLs are skipped and never
billed. Misses are free; no empty, billable rows.
- 🍪 **No cookies, login or account** — never share LinkedIn credentials or risk
account restrictions. Extraction runs on the Neuralverge backend.
- 👤 **Full profile** — experience, education, certifications, languages, top
skills, followers and posts as one structured object.
- ⚡ **Real-time & structured** — fresh data each run and one predictable JSON
schema, ready for a spreadsheet, ATS, CRM or AI pipeline.
### 🔧 How it works
1. **Provide a LinkedIn profile URL or username** — a full URL
(`https://www.linkedin.com/in/williamhgates`) or just the handle (`williamhgates`).
2. **Run the Actor.** Fetching and AI-structuring the profile happens on the
Neuralverge backend.
3. **Get one dataset row per person** — the source `url`, the extraction `settings`
(including the JSON schema) and the structured `machine` object. Export to CSV,
JSON or Excel, or pull it over the Apify API.
If the profile can't be resolved, it's logged and **skipped without charge**.
### Input
One profile per run.
| Field | Type | Notes |
|---|---|---|
| `profileUrl` | string | A LinkedIn profile URL or bare username. |
```json
{
"profileUrl": "https://www.linkedin.com/in/williamhgates"
}
````
### What you'll receive
Each dataset row mirrors the Neuralverge system output and has three top-level blocks:
- **`url`** — the profile URL you submitted (normalized from a username if you passed one).
- **`settings`** — the extraction settings, including the full JSON schema used, at
`settings.extract_schema_json`.
- **`machine`** — the structured result:
- `basic_info` — `fullname`, `first_name`, `last_name`, `headline`, `about`, `location`,
`connection_count`, `follower_count`, `current_company`, `top_skills`,
`top_education_school`, flags (`is_creator`, `is_premium`, `is_top_voice`,
`open_to_work`), `email` when present, and more.
- `experience`, `education`, `certifications`, `languages`, `causes`, `posts` — full arrays.
> **Nulls & empty arrays are normal.** Only fields present on the live profile are filled;
> anything not shown on LinkedIn (e.g. `top_skills`, `email`, `profile_picture_url`) comes
> back `null`, and `posts` / `certifications` may be empty. There is no single "current role"
> field — read it from `experience`, where the current role (if any) has `is_current: true`.
#### Example output (real run)
A real dataset row from `https://www.linkedin.com/in/jonathan-myrvik-3baa01109`, shown
**in full** — including the complete extraction **schema** (`settings.extract_schema_json`)
and the full **machine-readable result** (`machine`). The `human` markdown summary is
produced by the system but omitted from the dataset.
```json
{
"url": "https://www.linkedin.com/in/jonathan-myrvik-3baa01109",
"settings": {
"has_schema": true,
"country_code": "us",
"extract_schema_json": {
"type": "object",
"properties": {
"basic_info": {
"type": "object",
"properties": {
"fullname": {
"type": "string"
},
"first_name": {
"type": "string"
},
"last_name": {
"type": "string"
},
"headline": {
"type": "string"
},
"public_identifier": {
"type": "string"
},
"profile_url": {
"type": "string",
"format": "uri"
},
"profile_picture_url": {
"type": "string",
"format": "uri"
},
"background_picture_url": {
"type": "string",
"format": "uri"
},
"about": {
"type": "string"
},
"location": {
"type": "object",
"properties": {
"country": {
"type": "string"
},
"city": {
"type": "string"
},
"full": {
"type": "string"
},
"postal_code": {
"type": "string"
},
"country_code": {
"type": "string"
}
}
},
"creator_hashtags": {
"type": "array",
"items": {
"type": "string"
}
},
"is_creator": {
"type": "boolean"
},
"is_influencer": {
"type": "boolean"
},
"is_premium": {
"type": "boolean"
},
"open_to_work": {
"type": "boolean"
},
"created_timestamp": {
"type": "integer"
},
"show_follower_count": {
"type": "boolean"
},
"memorialized": {
"type": "boolean"
},
"is_top_voice": {
"type": "boolean"
},
"primary_locale": {
"type": "string"
},
"urn": {
"type": "string"
},
"follower_count": {
"type": "integer"
},
"connection_count": {
"type": "integer"
},
"current_company": {
"type": "string"
},
"current_company_urn": {
"type": "string"
},
"current_company_url": {
"type": "string",
"format": "uri"
},
"current_company_logo_url": {
"type": "string",
"format": "uri"
},
"top_education_school": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"urn": {
"type": "string"
},
"url": {
"type": "string",
"format": "uri"
},
"logo_url": {
"type": "string",
"format": "uri"
}
}
},
"top_skills": {
"type": "array",
"items": {
"type": "string"
}
},
"email": {
"type": [
"string",
"null"
]
}
}
},
"experience": {
"type": "array",
"items": {
"type": "object",
"properties": {
"title": {
"type": "string"
},
"company": {
"type": "string"
},
"location": {
"type": "string"
},
"description": {
"type": "string"
},
"duration": {
"type": "string"
},
"start_date": {
"type": "object",
"properties": {
"year": {
"type": "integer"
},
"month": {
"type": "string"
}
}
},
"end_date": {
"type": "object",
"properties": {
"year": {
"type": "integer"
},
"month": {
"type": "string"
}
}
},
"is_current": {
"type": "boolean"
},
"company_linkedin_url": {
"type": "string",
"format": "uri"
},
"company_logo_url": {
"type": "string",
"format": "uri"
},
"employment_type": {
"type": "string"
},
"company_id": {
"type": "string"
}
}
}
},
"education": {
"type": "array",
"items": {
"type": "object",
"properties": {
"school": {
"type": "string"
},
"duration": {
"type": "string"
},
"school_linkedin_url": {
"type": "string",
"format": "uri"
},
"school_logo_url": {
"type": "string",
"format": "uri"
},
"school_id": {
"type": "string"
},
"start_date": {
"type": "object",
"properties": {
"year": {
"type": "integer"
}
}
},
"end_date": {
"type": "object",
"properties": {
"year": {
"type": "integer"
}
}
}
}
}
},
"certifications": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"issuer": {
"type": "string"
},
"issueDate": {
"type": "string"
}
}
}
},
"languages": {
"type": "array",
"items": {
"type": "object",
"properties": {
"language": {
"type": "string"
},
"proficiency": {
"type": "string"
}
}
}
},
"causes": {
"type": "array",
"items": {
"type": "string"
}
},
"posts": {
"type": "array",
"items": {
"type": "object",
"properties": {
"post_id": {
"type": "string"
},
"urn": {
"type": "string"
},
"text": {
"type": "string"
},
"content_type": {
"type": "string",
"enum": [
"text",
"image",
"video",
"document",
"poll",
"article"
]
},
"published_at": {
"type": "string",
"format": "date-time"
},
"post_url": {
"type": "string",
"format": "uri"
},
"hashtags": {
"type": "array",
"items": {
"type": "string"
}
},
"mentions": {
"type": "array",
"items": {
"type": "object",
"properties": {
"name": {
"type": "string"
},
"urn": {
"type": "string"
},
"profile_url": {
"type": "string",
"format": "uri"
}
}
}
},
"media": {
"type": "array",
"items": {
"type": "object",
"properties": {
"type": {
"type": "string",
"enum": [
"image",
"video",
"document",
"link"
]
},
"url": {
"type": "string",
"format": "uri"
},
"thumbnail_url": {
"type": "string",
"format": "uri"
},
"title": {
"type": "string"
}
}
}
},
"engagement": {
"type": "object",
"properties": {
"reactions_count": {
"type": "integer"
},
"likes_count": {
"type": "integer"
},
"comments_count": {
"type": "integer"
},
"shares_count": {
"type": "integer"
},
"impressions_count": {
"type": "integer"
}
}
}
}
}
}
},
"required": [
"basic_info",
"experience",
"education"
]
}
},
"machine": {
"basic_info": {
"fullname": "Jonathan Myrvik",
"first_name": "Jonathan",
"last_name": "Myrvik",
"headline": "Department Manager at The Fresh Market",
"public_identifier": "jonathan-myrvik-3baa01109",
"profile_url": "https://www.linkedin.com/in/jonathan-myrvik-3baa01109",
"profile_picture_url": null,
"background_picture_url": null,
"about": "I am a highly driven and organized individual. I possess a strong ability to multi task and lead team with great leadership skills.
My tenure in the service and hospitality industry has been defined by driving my business, training and recruiting top talent, along with maintaining a level and standard of excellence.",
"location": {
"country": "United States",
"city": "Tampa",
"full": "Tampa, Florida, United States",
"postal_code": null,
"country_code": "US"
},
"creator_hashtags": [],
"is_creator": null,
"is_influencer": null,
"is_premium": null,
"open_to_work": null,
"created_timestamp": null,
"show_follower_count": null,
"memorialized": null,
"is_top_voice": null,
"primary_locale": null,
"urn": null,
"follower_count": 90,
"connection_count": 87,
"current_company": null,
"current_company_urn": null,
"current_company_url": null,
"current_company_logo_url": null,
"top_education_school": null,
"top_skills": null,
"email": null
},
"experience": [
{
"title": "Restaurant and Culinary Manager",
"company": "Bahama Breeze",
"location": null,
"description": null,
"duration": null,
"start_date": {
"year": 2018,
"month": "4"
},
"end_date": {
"year": 2023,
"month": "1"
},
"is_current": false,
"company_linkedin_url": null,
"company_logo_url": null,
"employment_type": null,
"company_id": "3860789"
},
{
"title": "Chef",
"company": "Nordstrom",
"location": "Tampa/St. Petersburg, Florida Area",
"description": "Relocated to assist with remodel of full service operation. Assisted with developing menu ideas and concepts. Maintained an excellence in food costs, quality, and standards.",
"duration": null,
"start_date": {
"year": 2013,
"month": "3"
},
"end_date": {
"year": 2015,
"month": "7"
},
"is_current": false,
"company_linkedin_url": null,
"company_logo_url": null,
"employment_type": "Full-time",
"company_id": "3379"
},
{
"title": "Chef/Manager",
"company": "Nordstrom",
"location": null,
"description": "Training and developing staff and team members.\nManaging food and labor costs\nDeveloping menu items and specifications\nEnsuring recipe adherence\nAssisted with training and opening of numerous concepts",
"duration": null,
"start_date": {
"year": 2004,
"month": "11"
},
"end_date": {
"year": 2018,
"month": "4"
},
"is_current": false,
"company_linkedin_url": null,
"company_logo_url": null,
"employment_type": "Full-time",
"company_id": "3379"
},
{
"title": "Chef",
"company": "Nordstrom",
"location": "Greater Atlanta Area",
"description": "Successfully managed two operations while upholding the standard and level of excellence. Increased both operations by 12% in annual sales.",
"duration": null,
"start_date": {
"year": 2010,
"month": "5"
},
"end_date": {
"year": 2013,
"month": "3"
},
"is_current": false,
"company_linkedin_url": null,
"company_logo_url": null,
"employment_type": "Full-time",
"company_id": "3379"
},
{
"title": "Executive Chef",
"company": "Aramark Business Dining",
"location": "Tampa/St. Petersburg, Florida Area",
"description": null,
"duration": null,
"start_date": {
"year": 2015,
"month": "12"
},
"end_date": {
"year": 2017,
"month": "4"
},
"is_current": false,
"company_linkedin_url": null,
"company_logo_url": null,
"employment_type": "Full-time",
"company_id": null
}
],
"education": [
{
"school": "Tampa Bay Culinary Academy",
"duration": null,
"school_linkedin_url": null,
"school_logo_url": null,
"school_id": null,
"start_date": {
"year": 2002
},
"end_date": {
"year": 2004
}
},
{
"school": "University of Memphis",
"duration": null,
"school_linkedin_url": null,
"school_logo_url": null,
"school_id": null,
"start_date": {
"year": 1999
},
"end_date": {
"year": 2001
}
}
],
"certifications": [
{
"name": "Serv Safe Certified",
"issuer": "FoodHandler",
"issueDate": null
}
],
"languages": [
{
"language": "English",
"proficiency": null
}
],
"causes": [],
"posts": []
}
}
```
> Genuine output from a live run. Note the real-world gaps: no `experience` row is flagged
> `is_current: true`, and `top_skills`, `email` and `posts` came back empty — while all five
> roles, both schools, one certification and one language are populated.
### Pricing
Pay per result — **$0.005 per profile** ($5 per 1,000) returned to the dataset. **You
pay only for rows returned — misses are free.**
| Event | Price |
|---|---|
| Actor start | Free |
| Profile returned (per dataset row) | **$0.005** |
Profiles that can't be resolved are **not billed**. Pricing is on top of your Apify
platform usage.
### Integrations & API
Results are stored in a standard Apify dataset — export as CSV, JSON, XML or Excel,
or fetch on demand through the [Apify API](https://docs.apify.com/api). The Actor
also plugs into Apify's integrations (Make, Zapier, n8n, webhooks) and can be called
from any [MCP](https://mcp.apify.com/) client to give an AI agent live people data.
### FAQ
**Do I need a LinkedIn account or cookies?** No. Extraction runs on the Neuralverge
backend — you never provide credentials or a session.
**Can I pass a username instead of a URL?** Yes — a bare handle like `williamhgates`
works as well as a full profile URL.
**Does it return emails?** An `email` is included only when present in the profile
data. A dedicated LinkedIn email actor is available separately.
**Am I charged if a profile isn't found?** No. You're billed only for rows returned
to the dataset.
***
**Disclaimer:** This Actor is an independent tool and is not affiliated with, endorsed
by, or sponsored by LinkedIn Corporation. LinkedIn® is a registered trademark of
LinkedIn Corporation. All trademarks are property of their respective owners.
# Actor input Schema
## `profileUrl` (type: `string`):
A LinkedIn profile URL or bare username (e.g. williamhgates) — one per run.
## Actor input object example
```json
{
"profileUrl": "https://www.linkedin.com/in/jonathan-myrvik-3baa01109"
}
```
# Actor output Schema
## `results` (type: `string`):
Structured LinkedIn people data (name, headline, current/latest role, location, skills, experience, education), one row per matched URL.
# 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 = {
"profileUrl": "https://www.linkedin.com/in/jonathan-myrvik-3baa01109"
};
// Run the Actor and wait for it to finish
const run = await client.actor("neuralverge/neuralverge-linkedin-person").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 = { "profileUrl": "https://www.linkedin.com/in/jonathan-myrvik-3baa01109" }
# Run the Actor and wait for it to finish
run = client.actor("neuralverge/neuralverge-linkedin-person").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 '{
"profileUrl": "https://www.linkedin.com/in/jonathan-myrvik-3baa01109"
}' |
apify call neuralverge/neuralverge-linkedin-person --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=neuralverge/neuralverge-linkedin-person",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "LinkedIn Profile Scraper — Experience & Skills ✅ No Cookies",
"description": "Extract LinkedIn profile data in bulk — experience, education, skills, connections, followers and posts — from a URL or username. Pay only for profiles found. No cookies or account required.",
"version": "0.1",
"x-build-id": "KgJaVdHOHauXEVpQK"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/neuralverge~neuralverge-linkedin-person/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-neuralverge-neuralverge-linkedin-person",
"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": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/neuralverge~neuralverge-linkedin-person/runs": {
"post": {
"operationId": "runs-sync-neuralverge-neuralverge-linkedin-person",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/neuralverge~neuralverge-linkedin-person/run-sync": {
"post": {
"operationId": "run-sync-neuralverge-neuralverge-linkedin-person",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$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": {
"profileUrl": {
"title": "LinkedIn profile URL or username",
"type": "string",
"description": "A LinkedIn profile URL or bare username (e.g. williamhgates) — one per run."
}
}
},
"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
}
}
}
}
}
}
}
}
}
}
```