# Leads Scraper βœ… $1/1k with EMAILS βœ… Apollo | ZoomInfo | Lusha (`lead_king/leads-finder`) Actor πŸ”₯ Cheap way to extract leads with verified ☎️ mobile numbers βœ… work & personal emails. Similar to Apollo, ZoomInfo, Lusha, Seamless. Target by location, job title, seniority, industry & company size. - **URL**: https://apify.com/lead\_king/leads-finder.md - **Developed by:** [Lead King](https://apify.com/lead_king) (community) - **Categories:** Lead generation, Automation, Agents - **Stats:** 6 total users, 3 monthly users, 57.9% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 1,000 leads fetcheds 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 ## Leads Scraper βœ… $1/1k with EMAILS β€” Apollo | ZoomInfo | Lusha alternative 🎯 The **cheap way to extract leads** with **verified ☎️ mobile numbers, βœ… work & personal emails** β€” similar to **Apollo, ZoomInfo, Lusha, Seamless, and Clearbit**, but with no subscription, no seats, and no export credits. Pick your filters, hit Start, and **pay only per lead you receive** β€” from **$1 per 1,000 leads**. ### πŸ§‘β€πŸ’Ό What does this Leads Scraper do? It turns simple targeting filters into a ready-to-use contact list. Choose **where** (state, city, ZIP), **who** (seniority, department, job title), and **what kind of company** (industry, employee count, revenue) β€” the Actor pulls matching people from a database of **hundreds of millions of profiles** and delivers full contact records, just like an Apollo or ZoomInfo export. No subscriptions, no API keys, no scraping setup. Export to **CSV, Excel, or JSON**, or push straight into your CRM. ### βš–οΈ Why use this instead of Apollo, ZoomInfo, or Lusha? | | This Actor | Apollo / ZoomInfo / Lusha | | --- | --- | --- | | **Pricing** | Pay per lead, from $1/1k | Monthly subscription + credits | | **Minimum spend** | Cents | $50–$15,000+/year | | **Setup** | Click Start | Sales calls, seats, contracts | | **Export limits** | None β€” it's your dataset | Credit-capped exports | ### πŸ•΅οΈ What data do I get for each lead? - πŸ‘€ **Full name** - πŸ“§ **Personal email(s)** - πŸ’Ό **Business email(s)** - πŸ“ž **Phone numbers** β€” personal, business, and **validated** numbers - 🏒 **Company** and company domain - 🎯 **Job title** Output sample: ```json { "fullName": "Jane Doe", "email": "jane.doe@example.com", "businessEmail": "jdoe@acmecorp.com", "phone": "+15550101234", "validPhones": "+15550101234", "jobTitle": "VP of Marketing", "company": "Acme Corp", "companyDomain": "acmecorp.com" } ```` ### πŸŽ›οΈ How do I target leads? Combine any of these filters: | Filter | Examples | | --- | --- | | **US state** | Texas, California, Florida… | | **City** | Austin, Miami, New York… | | **ZIP code** | 78701, 33101… | | **Seniority** | CXO, VP, Director, Manager | | **Department** | Sales, Engineering, Marketing, Finance… | | **Job title** | "Chief Executive Officer", "Head of Growth"… | | **Industry** | Software Development, Insurance, Real Estate… | | **Company size** | 1–10 up to 10,000+ employees | | **Company revenue** | Under $1M up to $1B+ | | **Age range** | e.g. 30–55 | | **Gender** | Male / Female | Turn on **"Only leads with an email"** (default) or **"Only leads with a phone"** to receive nothing but contactable records. ### πŸ’° How much does it cost? You pay a small fee per Actor start plus a **per-lead price** β€” you're only charged for lead records actually delivered to your dataset. Set **Max leads** to control your spend, or set a maximum cost per run in the run options; the Actor stops charging the moment the limit is reached. ### πŸ”₯ What can I use it for? - **Sales & outreach** β€” build call and email lists for exactly your ICP, like an Apollo or Seamless search without the subscription. - **Cold email & cold calling** β€” verified work emails and mobile numbers. - **Agencies** β€” generate targeted lead lists for clients in any niche + region. - **Recruiting** β€” find professionals by role, seniority, and location. - **Local marketing** β€” pull every decision-maker in a city or ZIP. - **Founders & growth** β€” fast, targeted prospecting without a data team. ### ▢️ How do I use it? 1. Click **Start** (or **Try for free**). 2. Pick your targeting filters and set **Max leads**. 3. Run β€” results stream into the dataset within seconds to a couple of minutes. 4. **Export** as CSV/Excel/JSON or connect via API. ### ❓ FAQ **Do I need an API key or account with a data provider?** No. Everything runs on Apify credits β€” one click and you get data. **Are the emails verified?** Records include validation status from the data provider; enable "Only leads with an email" to skip records without one. **Is this GDPR/CCPA relevant?** The data covers US-based profiles from a licensed B2B/B2C data provider. You are responsible for using the data in compliance with applicable laws and opt-out obligations in your jurisdiction. **Can I get more than 10,000 leads?** Yes β€” run the Actor multiple times with different filters (e.g. state by state) to segment your pulls. # Actor input Schema ## `maxLeads` (type: `integer`): Maximum number of leads to fetch. You are charged per lead actually returned. ## `requireEmail` (type: `boolean`): Skip records that have no personal or business email. ## `requirePhone` (type: `boolean`): Skip records that have no personal or business phone. ## `states` (type: `array`): Target leads in these US states (2-letter codes). ## `cities` (type: `array`): Target leads in these cities, e.g. "Austin", "Miami". ## `zips` (type: `array`): Target leads in these ZIP codes. ## `companyDescriptions` (type: `array`): Keywords describing what the company does, e.g. "boutique hotel", "HR software", "organic skincare". Matched against the company description β€” useful when the industry list is too broad or too coarse. ## `seniority` (type: `array`): Target professionals at these seniority levels. ## `departments` (type: `array`): Target professionals working in these departments. ## `jobTitles` (type: `array`): Target these job titles, e.g. "Chief Executive Officer". ## `industries` (type: `array`): Target companies in these industries. ## `employeeCounts` (type: `array`): Target companies with this many employees. ## `companyRevenues` (type: `array`): Target companies with this annual revenue. ## `gender` (type: `string`): Optionally target a single gender. ## `ageMin` (type: `integer`): Only include people at least this old. ## `ageMax` (type: `integer`): Only include people at most this old. ## Actor input object example ```json { "maxLeads": 100, "requireEmail": true, "requirePhone": false, "cities": [] } ``` # Actor output Schema ## `results` (type: `string`): Open the dataset of lead records. ## `resultsConsole` (type: `string`): Browse the leads in the Apify Console. # 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 = { "maxLeads": 100, "cities": [] }; // Run the Actor and wait for it to finish const run = await client.actor("lead_king/leads-finder").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 = { "maxLeads": 100, "cities": [], } # Run the Actor and wait for it to finish run = client.actor("lead_king/leads-finder").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 '{ "maxLeads": 100, "cities": [] }' | apify call lead_king/leads-finder --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=lead_king/leads-finder", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Leads Scraper βœ… $1/1k with EMAILS βœ… Apollo | ZoomInfo | Lusha", "description": "πŸ”₯ Cheap way to extract leads with verified ☎️ mobile numbers βœ… work & personal emails. Similar to Apollo, ZoomInfo, Lusha, Seamless. Target by location, job title, seniority, industry & company size.", "version": "0.0", "x-build-id": "QTn6uLgVtTbxLAVco" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/lead_king~leads-finder/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-lead_king-leads-finder", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/lead_king~leads-finder/runs": { "post": { "operationId": "runs-sync-lead_king-leads-finder", "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/lead_king~leads-finder/run-sync": { "post": { "operationId": "run-sync-lead_king-leads-finder", "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": { "maxLeads": { "title": "Max leads", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of leads to fetch. You are charged per lead actually returned.", "default": 100 }, "requireEmail": { "title": "Only leads with an email", "type": "boolean", "description": "Skip records that have no personal or business email.", "default": true }, "requirePhone": { "title": "Only leads with a phone number", "type": "boolean", "description": "Skip records that have no personal or business phone.", "default": false }, "states": { "title": "US states", "type": "array", "description": "Target leads in these US states (2-letter codes).", "items": { "type": "string", "enum": [ "AL", "AK", "AZ", "AR", "CA", "CO", "CT", "DE", "FL", "GA", "HI", "ID", "IL", "IN", "IA", "KS", "KY", "LA", "ME", "MD", "MA", "MI", "MN", "MS", "MO", "MT", "NE", "NV", "NH", "NJ", "NM", "NY", "NC", "ND", "OH", "OK", "OR", "PA", "RI", "SC", "SD", "TN", "TX", "UT", "VT", "VA", "WA", "WV", "WI", "WY" ], "enumTitles": [ "Alabama", "Alaska", "Arizona", "Arkansas", "California", "Colorado", "Connecticut", "Delaware", "Florida", "Georgia", "Hawaii", "Idaho", "Illinois", "Indiana", "Iowa", "Kansas", "Kentucky", "Louisiana", "Maine", "Maryland", "Massachusetts", "Michigan", "Minnesota", "Mississippi", "Missouri", "Montana", "Nebraska", "Nevada", "New Hampshire", "New Jersey", "New Mexico", "New York", "North Carolina", "North Dakota", "Ohio", "Oklahoma", "Oregon", "Pennsylvania", "Rhode Island", "South Carolina", "South Dakota", "Tennessee", "Texas", "Utah", "Vermont", "Virginia", "Washington", "West Virginia", "Wisconsin", "Wyoming" ] } }, "cities": { "title": "Cities", "type": "array", "description": "Target leads in these cities, e.g. \"Austin\", \"Miami\".", "items": { "type": "string" } }, "zips": { "title": "ZIP codes", "type": "array", "description": "Target leads in these ZIP codes.", "items": { "type": "string" } }, "companyDescriptions": { "title": "Business keywords", "type": "array", "description": "Keywords describing what the company does, e.g. \"boutique hotel\", \"HR software\", \"organic skincare\". Matched against the company description β€” useful when the industry list is too broad or too coarse.", "items": { "type": "string" } }, "seniority": { "title": "Seniority", "type": "array", "description": "Target professionals at these seniority levels.", "items": { "type": "string", "enum": [ "cxo", "vp", "director", "manager", "staff" ], "enumTitles": [ "CXO", "VP", "Director", "Manager", "Staff" ] } }, "departments": { "title": "Departments", "type": "array", "description": "Target professionals working in these departments.", "items": { "type": "string", "enum": [ "administrative", "community and social services", "education", "engineering", "executive", "finance", "government", "health services", "human resources", "information technology", "legal", "media and communications", "military and protective services", "marketing", "operations", "product management", "real estate", "sales" ], "enumTitles": [ "Administrative", "Community and Social Services", "Education", "Engineering", "Executive", "Finance", "Government", "Health Services", "Human Resources", "Information Technology", "Legal", "Media and Communications", "Military and Protective Services", "Marketing", "Operations", "Product Management", "Real Estate", "Sales" ] } }, "jobTitles": { "title": "Job titles", "type": "array", "description": "Target these job titles, e.g. \"Chief Executive Officer\".", "items": { "type": "string" } }, "industries": { "title": "Industries", "type": "array", "description": "Target companies in these industries.", "items": { "type": "string", "enum": [ "Accounting", "Administration Of Justice", "Advertising Services", "Airlines And Aviation", "Alternative Dispute Resolution", "Alternative Medicine", "Animation And Post-Production", "Appliances, Electrical, And Electronics Manufacturing", "Architecture And Planning", "Armed Forces", "Artists And Writers", "Automation Machinery Manufacturing", "Automotive", "Aviation And Aerospace Component Manufacturing", "Banking", "Beverage Manufacturing", "Biotechnology Research", "Book And Periodical Publishing", "Broadcast Media Production And Distribution", "Building Construction", "Business Consulting And Services", "Business Skills Training", "Capital Markets", "Chemical Manufacturing", "Civic And Social Organizations", "Civil Engineering", "Commercial Real Estate", "Computer And Network Security", "Computer Games", "Computer Hardware Manufacturing", "Computer Networking", "Computers And Electronics Manufacturing", "Consumer Electronics", "Consumer Goods", "Consumer Services", "Cosmetics", "Dairy Product Manufacturing", "Defense And Space Manufacturing", "Design Services", "E-Learning Providers", "Education Administration Programs", "Entertainment Providers", "Environmental Services", "Events Services", "Executive Offices", "Facilities Services", "Farming", "Financial Services", "Fine Art", "Fisheries", "Food And Beverage Services", "Freight And Package Transportation", "Fundraising", "Furniture And Home Furnishings Manufacturing", "Gambling Facilities And Casinos", "Glass, Ceramics And Concrete Manufacturing", "Government Administration", "Government Relations Services", "Health, Wellness And Fitness", "Higher Education", "Hospitality", "Hospitals And Health Care", "Human Resources Services", "Individual And Family Services", "Industrial Machinery Manufacturing", "Insurance", "International Affairs", "International Trade And Development", "Internet", "Internet Publishing", "Investment Banking", "Investment Management", "It Services And It Consulting", "Judiciary", "Law Enforcement", "Law Practice", "Leasing Real Estate", "Legal Services", "Legislative Offices", "Leisure, Travel & Tourism", "Libraries", "Logistics And Supply Chain", "Machinery Manufacturing", "Manufacturing", "Maritime Transportation", "Market Research", "Marketing Services", "Mechanical Or Industrial Engineering", "Medical Equipment Manufacturing", "Medical Practices", "Mental Health Care", "Military", "Mining", "Mobile Gaming Apps", "Motion Pictures And Film", "Motor Vehicle Manufacturing", "Movies, Videos, And Sound", "Museums, Historical Sites, And Zoos", "Musicians", "Nanotechnology Research", "Newspaper Publishing", "Newspapers", "Non-Profit Organizations", "Oil And Gas", "Online Audio And Video Media", "Outsourcing And Offshoring Consulting", "Packaging And Containers Manufacturing", "Paper And Forest Product Manufacturing", "Personal Care Product Manufacturing", "Pharmaceutical Manufacturing", "Philanthropic Fundraising Services", "Photography", "Plastics Manufacturing", "Political Organizations", "Primary And Secondary Education", "Printing Services", "Professional Training And Coaching", "Program Development", "Public Policy Offices", "Public Relations And Communications Services", "Public Safety", "Railroad Equipment Manufacturing", "Ranching", "Recreational Facilities", "Religious Institutions", "Renewable Energy Semiconductor Manufacturing", "Renewables & Environment", "Research", "Research Services", "Restaurants", "Retail", "Retail Apparel And Fashion", "Retail Art Supplies", "Retail Groceries", "Retail Luxury Goods And Jewelry", "Retail Office Equipment", "Security And Investigations", "Semiconductor Manufacturing", "Shipbuilding", "Spectator Sports", "Sporting Goods Manufacturing", "Sports", "Strategic Management Services", "Supermarkets", "Technology, Information And Internet", "Telecommunications", "Textile Manufacturing", "Think Tanks", "Tobacco Manufacturing", "Translation And Localization", "Transportation, Logistics, Supply Chain And Storage", "Travel Arrangements", "Truck Transportation", "Utilities", "Venture Capital And Private Equity Principals", "Veterinary Services", "Warehousing And Storage", "Wellness And Fitness Services", "Wholesale", "Wholesale Building Materials", "Wholesale Import And Export", "Wine And Spirits", "Wireless Services", "Writing And Editing" ] } }, "employeeCounts": { "title": "Company size (employees)", "type": "array", "description": "Target companies with this many employees.", "items": { "type": "string", "enum": [ "1 to 10", "11 to 25", "26 to 50", "51 to 100", "101 to 250", "251 to 500", "501 to 1000", "1001 to 5000", "5001 to 10000", "10000+" ], "enumTitles": [ "1–10", "11–25", "26–50", "51–100", "101–250", "251–500", "501–1,000", "1,001–5,000", "5,001–10,000", "10,000+" ] } }, "companyRevenues": { "title": "Company revenue", "type": "array", "description": "Target companies with this annual revenue.", "items": { "type": "string", "enum": [ "Under 1 Million", "1 Million to 5 Million", "5 Million to 10 Million", "10 Million to 25 Million", "25 Million to 50 Million", "50 Million to 100 Million", "100 Million to 250 Million", "250 Million to 500 Million", "500 Million to 1 Billion", "1 Billion and Over" ], "enumTitles": [ "Under $1M", "$1M–$5M", "$5M–$10M", "$10M–$25M", "$25M–$50M", "$50M–$100M", "$100M–$250M", "$250M–$500M", "$500M–$1B", "$1B+" ] } }, "gender": { "title": "Gender", "enum": [ "male", "female" ], "type": "string", "description": "Optionally target a single gender." }, "ageMin": { "title": "Minimum age", "minimum": 18, "maximum": 99, "type": "integer", "description": "Only include people at least this old." }, "ageMax": { "title": "Maximum age", "minimum": 18, "maximum": 99, "type": "integer", "description": "Only include people at most this old." } } }, "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 } } } } } } } } } } ```