# Linkedin Lead Scraper (`scraper-engine/linkedin-lead-scraper`) Actor Extract high-quality professional leads using the LinkedIn Lead Scraper. Collect names, job titles, company names, locations, and profile links automatically. Ideal for B2B prospecting, recruitment research, and building targeted outreach lists. - **URL**: https://apify.com/scraper-engine/linkedin-lead-scraper.md - **Developed by:** [Scraper Engine](https://apify.com/scraper-engine) (community) - **Categories:** Lead generation, Automation, Jobs - **Stats:** 26 total users, 3 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing $19.99/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 ### **LinkedIn** Lead Scraper πŸ“± LinkedIn Lead Scraper is a powerful Direct Tool Keyword (Exact Intent) built for efficient LinkedIn scraping to extract verified lead addresses and contact details. As a LinkedIn Lead Scraper tool, it supports Bulk / Automation Intent keywords by enabling bulk LinkedIn scraping and scalable data extraction from multiple profiles. With automated LinkedIn scraping, users can collect names, job titles, company details, and other profile data in a structured format. This LinkedIn scraping tool ensures accurate LinkedIn data scraping for lead generation, marketing, and recruitment, while automated LinkedIn lead scraper capabilities help scale operations without compromising quality or efficiency. ### Support and feedback - **Bug reports**: Open a ticket in the repository Issues section - **Custom features**: Contact our enterprise support team *Lead: dev.scraperengine@gmail.com * ### πŸ“Š Extractable Data Table – LinkedIn Lead Scraper | Data Type | Description | | --- | --- | | Lead Address | Extract verified lead addresses from LinkedIn profiles using a Direct Tool Keyword (LinkedIn Lead Scraper) for accurate outreach and LinkedIn scraping. | | Full Name | Retrieve full names of profile owners for personalized communication through LinkedIn data scraping. | | Job Title | Capture current job titles to identify decision-makers via LinkedIn Lead Scraper tool. | | Company Name | Extract company details for B2B targeting using bulk LinkedIn scraping workflows. | | Location | Gather geographic data for region-based targeting through automated LinkedIn scraping. | | Profile URL | Retrieve direct LinkedIn profile links for reference and tracking in LinkedIn scraping automation. | | Industry | Identify industry classification for better segmentation using LinkedIn scraping tools. | | Connections Count | Extract network size to evaluate lead strength through LinkedIn data scraping at scale. | ### Key Features of **LinkedIn** Lead Scraper Here are the standout features that make the **LinkedIn Lead Scraper (Direct Tool Keyword)** a top-tier solution for marketers, agencies, and researchers working with **LinkedIn scraping** and **LinkedIn lead generation automation**: ⭐ **Automated LinkedIn Lead Scraper** for fast and accurate **LinkedIn data scraping** at scale ⭐ Extract leads from LinkedIn profiles securely using a reliable **LinkedIn scraping tool** ⭐ Supports **bulk LinkedIn scraping** for names, job titles, company details, and contact information ⭐ Customizable filters to target specific industries, locations, or roles for precise **LinkedIn lead scraping** ⭐ User-friendly interface for smooth **LinkedIn scraping automation** and data management ⭐ High accuracy in extracting verified lead addresses from public LinkedIn profiles ⭐ Scalable system designed for large-scale **LinkedIn B2B Lead Scraper** workflows ⭐ Ensures compliance with LinkedIn policies and ethical **LinkedIn scraping practices** ⭐ Structured output for easy integration into CRM and marketing systems ⭐ Advanced algorithms to reduce duplication and improve **LinkedIn data extraction quality** ⭐ Regular updates to maintain compatibility with LinkedIn platform changes ⭐ Full documentation and support for smooth usage and troubleshooting ### How to use **LinkedIn** Lead Scraper πŸš€ Follow this **simple, step-by-step guide** to start extracting **LinkedIn** leads today: #### Step-by-Step Guide * πŸ”‘ **Create account on Apify** – Sign up or log in to Apify to access the **LinkedIn Lead Scraper tool** * 🧠 **Open Apify dashboard** – Go to your workspace and search for the LinkedIn scraper in the Actor library * πŸ“₯ **Enter search criteria** – Add keywords such as job titles, industries, companies, or locations for **LinkedIn scraping** * βš™οΈ **Select data types** – Choose what you want to extract like profiles, names, job roles, and company details * 🎯 **Apply filters** – Refine targeting for accurate **LinkedIn lead scraping automation** results * πŸš€ **Run the Actor** – Click β€œStart” to begin **automated LinkedIn scraping** * πŸ“Š **Download results** – Export your data in CSV, Excel, or JSON format after completion * πŸ”— **Integrate data** – Use extracted leads in CRM or outreach tools for **LinkedIn lead generation workflows** * πŸ“š **Check documentation** – Follow Apify guides for advanced **LinkedIn data scraping setup** ### Use Cases 🎯 #### πŸš€ Lead Generation πŸš€ Extract leads from LinkedIn profiles to build highly targeted B2B lists using LinkedIn scraping tools πŸ“‘ Automate LinkedIn contact scraping for faster and more efficient outreach campaigns through LinkedIn lead scraping automation #### πŸ§‘β€πŸ’Ό Recruitment πŸ§‘β€πŸ’Ό Gather candidate contact information from LinkedIn profiles using LinkedIn data scraping πŸ’Ό Streamline hiring workflows with a LinkedIn Lead Scraper tool for faster talent sourcing #### πŸ“Š Market Research πŸ“Š Analyze industry trends by extracting LinkedIn profile data through LinkedIn scraping 🌍 Collect company and location insights for regional analysis using bulk LinkedIn scraping #### 🀝 Networking 🀝 Connect with professionals by extracting verified leads using a LinkedIn Lead Scraper (Direct Tool Keyword) πŸ”— Build meaningful business connections through automated LinkedIn scraping tools for targeted outreach ### Why choose us? πŸ’Ž #### ⚑ Advanced LinkedIn Lead Scraper Tool Β Our LinkedIn Lead Scraper (Direct Tool Keyword) is a powerful LinkedIn scraping tool built for businesses, recruiters, and marketers who need accurate and scalable LinkedIn lead scraping solutions. #### πŸš€ Automated Lead Extraction Β It enables automated LinkedIn scraping to extract leads from LinkedIn profiles efficiently, saving time, effort, and operational costs while ensuring structured LinkedIn data scraping. #### 🎯 Smart Targeting & Filters Β With advanced filters and keyword-based targeting, you can refine bulk LinkedIn scraping by industries, locations, job titles, or search intent for highly relevant leads. #### πŸ“Š Structured & CRM-Ready Data Β The tool delivers clean, structured output for seamless integration into CRMs and marketing systems, supporting LinkedIn lead scraping automation workflows. #### πŸ›‘οΈ Safe & Compliant Usage Β We prioritize ethical data practices and compliance-focused LinkedIn scraping to ensure responsible and reliable usage. #### 🀝 Simple Interface & Support Β Designed for ease of use, the platform includes a user-friendly interface and dedicated support to help you scale LinkedIn lead generation automation effectively. #### πŸ’Ό Built for Every Use Case Β Whether for sales, recruitment, or marketing, this LinkedIn Lead Scraper tool delivers consistent and reliable results tailored to your business needs. ### **LinkedIn** Lead Scraper Scalability πŸ“ˆ #### ⚑ Scalable LinkedIn Lead Scraper Solution Β The LinkedIn Lead Scraper (Direct Tool Keyword) is designed for both small and large-scale LinkedIn scraping projects, ensuring consistent performance and accurate LinkedIn data scraping results. #### 🎯 Flexible Targeting System Β With advanced filters and keyword-based targeting, users can refine LinkedIn lead scraping automation by industry, job role, or company for highly relevant data collection. #### πŸ“¦ Batch & Bulk Processing Β Supports bulk LinkedIn scraping and batch extraction, allowing thousands of profiles to be processed simultaneously without reducing data quality or speed. #### πŸš€ Automated High-Volume Scraping Β The system enables automated LinkedIn scraping workflows, making it easy to scale lead generation without manual effort. #### 🏒 Built for All Business Sizes Β From startups to enterprises, the LinkedIn scraping tool adapts to growing data needs and expanding outreach strategies. #### πŸ“Š Growth-Ready Lead Generation Tool Β Ideal for LinkedIn lead generation automation, helping businesses continuously expand their prospecting and marketing operations efficiently. ### **LinkedIn** Lead Scraper Legal Guidelines βš–οΈ Yes β€” LinkedIn scraping can be used responsibly when applied with ethical practices and proper compliance. The LinkedIn Lead Scraper (Direct Tool Keyword) is designed to extract only publicly available information from LinkedIn profiles, making it suitable for research, marketing, and LinkedIn data scraping analysis when used correctly. #### Legal & Ethical Guidelines * βš–οΈ Ensure compliance with LinkedIn terms of service when using any LinkedIn scraping tool * 🌐 Only extract publicly available data from LinkedIn profiles via LinkedIn scraping * πŸ”’ Avoid collecting private, restricted, or sensitive profile information * 🧠 Use LinkedIn lead scraping automation responsibly with respect for user privacy * 🚫 Do not use extracted data for spam or unsolicited outreach campaigns * πŸ“œ Follow applicable data protection laws such as GDPR and regional regulations * βœ‹ Obtain proper consent when required before using extracted contact data * πŸ“š Regularly review LinkedIn policies to ensure compliant LinkedIn data scraping practices ### Input Parameters 🧩 πŸ“¦ Example Input (JSON) ```json { "keywords": ["Linkedin Lead Scraper"], "country": "Global", "maxLeadNumbers": 20, "platform": "LinkedIn", "engine": "legacy" } ```` ### Input Table | Data Type | Description | | --- | --- | | keywords | Keywords to find relevant profiles | | country | Country setting (Global) | | maxLeadNumbers | Maximum leads to collect (default 20) | | platform | Platform to scrape (LinkedIn) | | engine | Engine type (legacy) | | proxyConfiguration | Optional proxy settings | ### Output Format πŸ“€ πŸ“ Example Output (JSON) ```json [ { "network": "LinkedIn", "keyword": "Linkedin Lead Scraper", "title": "Google's Single-Benefit Marketing Strategy for Chrome ...", "description": "βœ“For years, once we created a Gmail account, we couldn't change the username (the part before @ gmail.com ). ... Grand Rapids Marketing Co. Read more", "url": "https://www.linkedin.com/posts/phill-agnew_heres-how-google-marketed-chrome-browser-activity-7404878510214914048-dLxI", "lead": "before@gmail.com" } ] ``` ### Output Table | Data Type | Description | | --- | --- | | network | Identifies LinkedIn as the source | | keyword | Keyword that triggered the result (Linkedin Lead Scraper) | | title | Profile title or username | | description | Public bio snippet with contact info | | url | Direct LinkedIn profile link | | lead | Extracted lead address | ### FAQ ❓ #### πŸ€” What is LinkedIn Lead Scraper? LinkedIn Lead Scraper (Direct Tool Keyword) is a LinkedIn scraping tool designed to extract lead addresses and profile data efficiently from publicly available LinkedIn profiles for LinkedIn data scraping use cases. #### βš–οΈ Is it legal to scrape LinkedIn leads? Yes, when used responsibly. The tool focuses on publicly available data and should comply with LinkedIn terms and applicable data protection laws during LinkedIn scraping. #### 🎯 Can I use this tool for lead generation? Yes, it is built for LinkedIn lead generation automation, helping users build targeted lists through LinkedIn lead scraping. #### πŸ“Š What data can I extract using this tool? You can extract leads, names, job titles, company names, locations, profile URLs, industries, and connections count through LinkedIn data scraping. #### βœ… Is the extracted data accurate? Yes, advanced algorithms improve accuracy and reduce errors in LinkedIn scraping automation results. #### πŸ”— How do I integrate the data into my CRM? You can export data in CSV, Excel, or JSON formats compatible with most CRM systems for seamless LinkedIn lead scraping workflows. #### πŸ›‘οΈ Does the tool comply with LinkedIn policies? Yes, it is designed for responsible LinkedIn scraping of publicly available data in compliance with platform guidelines. #### 🚫 Can I scrape private LinkedIn profiles? No, the tool only supports LinkedIn scraping of publicly accessible profile information. #### πŸ“ˆ Is the tool scalable for large projects? Yes, the LinkedIn Lead Scraper tool supports bulk LinkedIn scraping and is suitable for both small and enterprise-level projects. ### 🧾 Conclusion LinkedIn Lead Scraper is a powerful LinkedIn scraping tool designed to simplify and scale LinkedIn data scraping for lead generation, recruitment, and market research. With support for LinkedIn lead scraping automation and bulk LinkedIn scraping, it enables users to collect structured, accurate, and actionable data from LinkedIn profiles efficiently. By combining speed, scalability, and responsible data practices, this tool helps businesses improve outreach and build high-quality B2B pipelines while maintaining compliance with platform guidelines and data protection standards. # Actor input Schema ## `keywords` (type: `array`): List of keywords to search for on Linkedin (e.g., \['marketing', 'founder', 'business']). The actor will search Google for Linkedin profiles/posts containing these keywords and extract email addresses. ## `platform` (type: `string`): Select platform. ## `location` (type: `string`): Optional: Add location to search query (e.g., 'London', 'New York'). Leave empty to search globally. ## `emailDomains` (type: `array`): Optional: Filter results to only include emails from specific domains (e.g., \['@gmail.com', '@outlook.com']). Leave empty to collect all email domains. ## `maxEmails` (type: `integer`): Maximum number of emails to collect per keyword (default: 20). ## `engine` (type: `string`): Choose scraping engine. πŸš€ Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. πŸ”§ Legacy: Uses GOOGLE\_SERP proxy with traditional selectors - more reliable but slower and more expensive. ## `proxyConfiguration` (type: `object`): Choose which proxies to use. By default, no proxy is used. If Google rejects or blocks the request, the actor will automatically fallback to datacenter proxy, then residential proxy with 3 retries. ## Actor input object example ```json { "keywords": [ "marketing" ], "platform": "Linkedin", "location": "", "emailDomains": [ "@gmail.com" ], "maxEmails": 20, "engine": "legacy", "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 = { "keywords": [ "marketing" ], "emailDomains": [ "@gmail.com" ], "proxyConfiguration": { "useApifyProxy": false } }; // Run the Actor and wait for it to finish const run = await client.actor("scraper-engine/linkedin-lead-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "keywords": ["marketing"], "emailDomains": ["@gmail.com"], "proxyConfiguration": { "useApifyProxy": False }, } # Run the Actor and wait for it to finish run = client.actor("scraper-engine/linkedin-lead-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "marketing" ], "emailDomains": [ "@gmail.com" ], "proxyConfiguration": { "useApifyProxy": false } }' | apify call scraper-engine/linkedin-lead-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraper-engine/linkedin-lead-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Linkedin Lead Scraper", "description": "Extract high-quality professional leads using the LinkedIn Lead Scraper. Collect names, job titles, company names, locations, and profile links automatically. Ideal for B2B prospecting, recruitment research, and building targeted outreach lists.", "version": "0.1", "x-build-id": "p1JWlLzCuhPqGb0VP" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraper-engine~linkedin-lead-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraper-engine-linkedin-lead-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/scraper-engine~linkedin-lead-scraper/runs": { "post": { "operationId": "runs-sync-scraper-engine-linkedin-lead-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/scraper-engine~linkedin-lead-scraper/run-sync": { "post": { "operationId": "run-sync-scraper-engine-linkedin-lead-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": [ "keywords" ], "properties": { "keywords": { "title": "Keywords", "type": "array", "description": "List of keywords to search for on Linkedin (e.g., ['marketing', 'founder', 'business']). The actor will search Google for Linkedin profiles/posts containing these keywords and extract email addresses.", "items": { "type": "string" } }, "platform": { "title": "Platform", "enum": [ "Linkedin" ], "type": "string", "description": "Select platform.", "default": "Linkedin" }, "location": { "title": "Location Filter", "type": "string", "description": "Optional: Add location to search query (e.g., 'London', 'New York'). Leave empty to search globally.", "default": "" }, "emailDomains": { "title": "Email Domains Filter", "type": "array", "description": "Optional: Filter results to only include emails from specific domains (e.g., ['@gmail.com', '@outlook.com']). Leave empty to collect all email domains.", "items": { "type": "string" } }, "maxEmails": { "title": "Maximum Emails per Keyword", "minimum": 1, "maximum": 5000, "type": "integer", "description": "Maximum number of emails to collect per keyword (default: 20).", "default": 20 }, "engine": { "title": "Engine", "enum": [ "legacy" ], "type": "string", "description": "Choose scraping engine. πŸš€ Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. πŸ”§ Legacy: Uses GOOGLE_SERP proxy with traditional selectors - more reliable but slower and more expensive.", "default": "legacy" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Choose which proxies to use. By default, no proxy is used. If Google rejects or blocks the request, the actor will automatically fallback to datacenter proxy, then residential proxy with 3 retries." } } }, "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 } } } } } } } } } } ```