# Facebook Profile Email Scraper (`scrapeflux/facebook-profile-email-scraper`) Actor Facebook Profile Email Scraper extracts publicly available email addresses and contact details from Facebook profiles at scale. Collect emails, profile information, usernames, locations, websites, and social data for lead generation, outreach, recruitment, market research, and business prospecting. - **URL**: https://apify.com/scrapeflux/facebook-profile-email-scraper.md - **Developed by:** [ScrapeFlux](https://apify.com/scrapeflux) (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 $3.99 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ### Facebook Profile Email Scraper 🚀 If you’re trying to get email addresses from Facebook profiles, doing it manually quickly becomes slow and inconsistent. **Facebook Profile Email Scraper** automates the collection of business and consumer emails from publicly available sources so you can build targeted lead lists faster—using your keywords, a country focus, and a chosen email type (B2B or B2C). It’s an excellent **facebook profile email scraper** and **facebook email scraper tool** for marketers, analysts, and researchers who need usable contact data at scale. Generate lead-focused results in a single run, without spending hours clicking through profiles one by one. --- ### See the Data: Sample Output Here's a real record from a single run: ```json { "keyword": "fitness", "title": "Personal Training — John Doe", "url": "https://www.facebook.com/johndoefitness/", "description": "Certified trainer • Email in bio • Coaching & programs", "email": "john.doe@fitnessdomain.com", "email_domain": "fitnessdomain.com", "email_type": "B2C", "country": "United States", "status": "success", "error_message": null } ```` | Field | Type | What It Tells You | |---|---|---| | `keyword` | string | The keyword that led to this result, so you can segment your lead list by theme (e.g., **facebook marketing email scraper** research). | | `title` | string | A human-readable label tied to the source content—useful for quick triage and validation. | | `url` | string | A direct link to the Facebook profile, so you can verify and reference the contact source. | | `description` | string | Extra context from the source content that helps you understand why this contact was found. | | `email` | string | The extracted email address you can use for outreach and list building. | | `email_domain` | string | The domain portion of the email, helpful for domain-level filtering and CRM enrichment. | | `email_type` | string | Indicates whether the result was collected for `B2B` or `B2C` audiences. | | `country` | string | The country selected for your run, useful for geography-based targeting. | | `status` | string | Indicates whether the record was collected successfully (useful when you need to handle partial results). | | `error_message` | string | null | Contains an error message when applicable; otherwise `null` for successful records. | Export your full dataset as JSON, CSV, or Excel from the Apify dashboard. *** ### Setting It Up Drop this into your `input.json` and you're ready to go: ```json { "keywords": ["fitness", "gym", "workout"], "country": "United States", "emailType": "B2C", "engine": "legacy", "maxEmails": 100 } ``` | Parameter | Required | What It Does | |---|---|---| | `keywords` | ✅ | Enter one or more keywords to search for on Facebook (for example: “fitness”, “marketing”). | | `country` | ✅ | Specifies the country to target for results. | | `emailType` | ✅ | Choose one — `B2C` or `B2B` to focus the email type you want. | | `engine` | ⬜ | Choose scraping engine: `cost-effective` (Cost Effective (New)) or `legacy` (Legacy). | | `maxEmails` | ✅ | Enter the maximum number of emails to collect (controls run size, time, and cost). | *** ### What It Does Facebook Profile Email Scraper extracts email addresses from relevant Facebook profile content and writes them into a structured dataset you can export and analyze. #### Uses your keywords and country focus 🎯 You provide `keywords` and a `country`, and the actor uses those inputs to guide what it collects. This makes it much easier to build a segmented **facebook lead email scraper** list by niche and geography. #### Supports B2B and B2C lead building 💼 With `emailType`, you can choose whether you want `B2B` or `B2C` email results. This lets your **facebook email list scraper** output match your outreach style and audience type. #### Produces clean, integration-ready records ✅ Each dataset record includes key fields like `email`, `email_domain`, `email_type`, `country`, and a `url` pointing to the Facebook profile. That structure is built to support downstream workflows like CRM import, spreadsheet analysis, and lead enrichment. #### Includes an engine choice for different run tradeoffs ⚡ You can select `engine` as either `cost-effective` or `legacy` depending on your priorities. For larger jobs, use `maxEmails` thoughtfully to manage scraping time and cost. #### Handles run sizing with `maxEmails` (fast iteration) 🔁 Setting `maxEmails` helps you control how many emails you collect per run. If you’re building a **facebook profile email harvesting** pipeline, you can start small to validate quality, then scale up. Overall, Facebook Profile Email Scraper helps you get actionable email leads tied to Facebook profile sources—without manual list building. *** ### Why Facebook Profile Email Scraper? There are plenty of ways to pull contact data from Facebook—here’s why Facebook Profile Email Scraper stands out. #### Built for keyword-driven lead list building Instead of random scraping, you drive discovery with `keywords` and `country`. That’s how a **facebook contact email finder** becomes a practical lead-generation workflow rather than a one-off data grab. #### Output is structured for immediate use The dataset fields are designed for lead operations: you get the `email`, `email_domain`, `email_type`, `country`, and the profile `url` for reference. This makes it easier to go from scrape → review → import. #### Engine flexibility for different priorities You can choose between `cost-effective` and `legacy` via the `engine` input. If you’re doing bulk outreach, this helps you align **facebook email scraper tool** performance with your time and budget constraints. *** ### Real-World Use Cases Here's how different teams put Facebook Profile Email Scraper to work: **Sales Teams**\ A sales team needs fast, targeted prospects for a specific niche in a specific country. They run the actor with niche keywords and `emailType` set to match their ICP, then import the dataset into their CRM and start outreach sooner—cutting prospecting time from hours to minutes. **Marketing Agencies**\ An agency running multiple campaigns across industries wants clean segmentation without manual extraction. They use `keywords` for campaign themes, filter by `email_domain` and `email_type`, and export results to spreadsheets for campaign QA and segmentation. **Freelance Researchers**\ A researcher building a list of organizations and individuals tied to certain topics wants evidence-backed sources. They review the `url` and `description` fields for context, keep the dataset structured, and export for reporting and follow-up analysis. **Data Analysts & Enrichment Workflows**\ An analyst wants to study lead coverage and domain patterns. They use `country`, group by `email_domain`, and compare B2B vs B2C distributions across keyword clusters to guide next steps in outreach strategy. **Automation Specialists (Technical Workflow)**\ A developer runs Facebook Profile Email Scraper on a schedule and feeds the resulting dataset into an internal pipeline. With consistent dataset fields (like `email`, `email_domain`, `email_type`, and `country`), they can automate validation, deduplication, and downstream enrichment. *** ### How to Run It No code required. Here's how to get your first results in under 5 minutes: 1. **Open the actor page on Apify**\ Go to the actor listing on [console.apify.com](https://console.apify.com). 2. **Enter your inputs**\ Set `keywords`, choose a `country`, select `emailType` (B2C or B2B), and set `maxEmails` to control how many results you want. 3. **Select your engine (optional)**\ If you need a different run tradeoff, set `engine` to `cost-effective` or `legacy`. 4. **Start the run and watch the live log**\ Monitor progress in real time to confirm it’s behaving as expected. 5. **Open the Dataset tab to see results instantly**\ Your dataset records will include fields like `email`, `email_domain`, `email_type`, `country`, and the Facebook profile `url`. 6. **Export in your preferred format**\ Download your results as JSON, CSV, or Excel from the Apify dashboard. The whole setup takes under 5 minutes — results start appearing within seconds of launch. *** ### Export & Integration Options Once your data is collected, Facebook Profile Email Scraper fits directly into your existing workflow. You can download the dataset from the Apify dashboard in common formats such as JSON, CSV, or Excel. This makes it straightforward to share results with teammates or import into a spreadsheet-based workflow. For automation, you can integrate the actor via Apify’s API and connect it to downstream steps like CRM import or lead enrichment systems. If you use no-code automation tools (for example, Zapier or Make), you can also push results into other tools when runs complete. *** ### Pricing Facebook Profile Email Scraper runs on Apify, which includes a **free tier** — no credit card needed to start. Free tier usage is typically enough for several real test runs so you can validate lead quality before scaling. For larger jobs, pricing is based on Apify’s compute model (billed per Actor compute unit), and you can choose from Apify subscription plans for heavier workloads. There’s no per-row markup—you pay for platform compute rather than charging based on the number of emails exported. Start free at [apify.com](https://apify.com) — scale up when you need to. *** ### Reliability & Limitations | What We Handle | How | |---|---| | Rate limiting resilience | Includes logic to handle throttling conditions and continue scraping with controlled pacing. | | Engine tradeoffs | You can choose `engine` between `cost-effective` and `legacy` to match your run needs. | | Run size control | `maxEmails` caps how many emails are collected, helping you manage time and cost. | | Partial outcomes | You still get dataset records for what’s found within the run constraints. | Limitations: The actor works with publicly available profile information and cannot access private or login-gated content. If a profile doesn’t include an email in the accessible content, it may not return an email for that profile. For enterprise-scale needs or custom configurations, reach out and we'll help. *** ### Frequently Asked Questions #### Is there a free plan? Yes. Apify provides a free tier for starting out, so you can run Facebook Profile Email Scraper without committing immediately to paid usage. #### Do I need to log in or create an account on Facebook? No login is required from your side to run Facebook Profile Email Scraper. The actor is designed to work with publicly available data. #### How accurate is the extracted data? Accuracy depends on what’s actually published in the accessible Facebook profile content. The dataset includes `email` and related fields such as `email_domain`, plus reference fields like `url` and `description` to support validation. #### How many results can I get per run? You control the number of collected emails using `maxEmails`. If you set a higher `maxEmails`, you’re allowing the actor to collect more results, but it’s still bounded by run constraints. #### How fresh is the data? The data freshness depends on when the actor accesses the publicly available information during the run. For best results, run the actor closer to when you plan to start outreach. #### Is this legal? Does it comply with GDPR / CCPA? You are responsible for compliance with GDPR, CCPA, and applicable platform rules. Facebook Profile Email Scraper is built to extract **publicly available data**, but you must ensure your usage and storage of that data is lawful for your context. #### Can I export to Google Sheets or Excel? Yes. You can export your dataset from the Apify dashboard in formats such as JSON, CSV, or Excel, and then import into Google Sheets or your spreadsheet tool. #### Can I schedule this to run automatically? Yes. You can schedule actor runs using Apify’s scheduling features so Facebook Profile Email Scraper can run automatically on a cadence you choose. #### Can I access results via the API? Yes. You can trigger runs and retrieve dataset results programmatically using the Apify API. #### What happens when the actor encounters an error? If an issue occurs, you’ll still see results written to the dataset for successful records within the run constraints. Error details are available in the dataset through fields such as `error_message` when applicable. *** ### Get Help & Use Responsibly Got a question about Facebook Profile Email Scraper or a feature you'd like added? Reach out at . We welcome suggestions like improving CSV-friendly formatting for exports or adding better filtering options for `email_type` and `email_domain` workflows. **publicly available data**\ The actor collects **publicly available data** on Facebook profiles. It does not access private accounts, login-gated pages, or password-protected content. You’re responsible for complying with GDPR, CCPA, and the platform’s Terms of Service when using or storing the results. For data-removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `keywords` (type: `array`): Enter one or more keywords to search for on Facebook. ## `country` (type: `string`): Specify the country to target for Google search results. ## `emailType` (type: `string`): Choose one — B2C or B2B. ## `engine` (type: `string`): Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE\_SERP proxy with traditional selectors - more reliable but slower and more expensive. ## `maxEmails` (type: `integer`): Enter the maximum number of emails to collect. ## Actor input object example ```json { "keywords": [ "fitness", "gym", "workout" ], "country": "United States", "emailType": "B2C", "engine": "legacy", "maxEmails": 20 } ``` # 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": [ "fitness", "gym", "workout" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scrapeflux/facebook-profile-email-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keywords": [ "fitness", "gym", "workout", ] } # Run the Actor and wait for it to finish run = client.actor("scrapeflux/facebook-profile-email-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "fitness", "gym", "workout" ] }' | apify call scrapeflux/facebook-profile-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapeflux/facebook-profile-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Facebook Profile Email Scraper", "description": "Facebook Profile Email Scraper extracts publicly available email addresses and contact details from Facebook profiles at scale. Collect emails, profile information, usernames, locations, websites, and social data for lead generation, outreach, recruitment, market research, and business prospecting.", "version": "1.0", "x-build-id": "aWK0O9uaUJVSURW9w" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapeflux~facebook-profile-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapeflux-facebook-profile-email-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scrapeflux~facebook-profile-email-scraper/runs": { "post": { "operationId": "runs-sync-scrapeflux-facebook-profile-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scrapeflux~facebook-profile-email-scraper/run-sync": { "post": { "operationId": "run-sync-scrapeflux-facebook-profile-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "country", "emailType", "maxEmails" ], "properties": { "keywords": { "title": "Keywords", "type": "array", "description": "Enter one or more keywords to search for on Facebook.", "items": { "type": "string" } }, "country": { "title": "Country", "enum": [ "United States", "United Kingdom", "Canada", "Australia", "Germany", "France", "India", "Japan", "Brazil", "Italy", "Spain", "Netherlands", "Sweden", "Norway", "Denmark", "Finland", "Poland", "Czech Republic", "Hungary", "Romania", "Bulgaria", "Croatia", "Slovenia", "Slovakia", "Estonia", "Latvia", "Lithuania", "Portugal", "Greece", "Cyprus", "Malta", "Luxembourg", "Ireland", "Belgium", "Austria", "Switzerland", "Liechtenstein", "Iceland", "South Korea", "China", "Mexico", "Argentina", "Chile", "Colombia", "Peru", "Venezuela", "Ecuador", "Uruguay", "Paraguay", "Bolivia", "Guyana", "Suriname", "French Guiana", "Falkland Islands (Malvinas)", "South Georgia and the South Sandwich Islands", "Bonaire, Sint Eustatius and Saba", "Curaçao", "Aruba", "Sint Maarten (Dutch part)", "Turks and Caicos Islands", "British Virgin Islands", "Anguilla", "Montserrat", "Antigua and Barbuda", "Barbados", "Dominica", "Grenada", "Saint Kitts and Nevis", "Saint Lucia", "Saint Vincent and the Grenadines", "Trinidad and Tobago", "Jamaica", "Bahamas", "Belize", "Costa Rica", "Guatemala", "Honduras", "Nicaragua", "Panama", "El Salvador", "Cuba", "Dominican Republic", "Haiti", "Puerto Rico", "U.S. Virgin Islands", "American Samoa", "Guam", "Northern Mariana Islands", "Saudi Arabia", "United Arab Emirates", "Bahrain", "Iraq", "Iran, Islamic Republic of", "Israel", "Jordan", "Kuwait", "Lebanon", "Oman", "Qatar", "Syrian Arab Republic", "Yemen", "Afghanistan", "Bangladesh", "Bhutan", "Maldives", "Nepal", "Pakistan", "Sri Lanka", "Myanmar", "Cambodia", "Lao People's Democratic Republic", "Thailand", "Viet Nam", "Malaysia", "Singapore", "Brunei Darussalam", "Philippines", "Indonesia", "Timor-Leste", "Papua New Guinea", "Fiji", "New Zealand", "Solomon Islands", "Vanuatu", "New Caledonia", "French Polynesia", "Wallis and Futuna", "Samoa", "Tonga", "Tuvalu", "Kiribati", "Nauru", "Federated States of Micronesia", "Marshall Islands", "Palau", "Cook Islands", "Niue", "Tokelau" ], "type": "string", "description": "Specify the country to target for Google search results.", "default": "United States" }, "emailType": { "title": "Email Type", "enum": [ "B2C", "B2B" ], "type": "string", "description": "Choose one — B2C or B2B.", "default": "B2C" }, "engine": { "title": "Engine", "enum": [ "cost-effective", "legacy" ], "type": "string", "description": "Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE_SERP proxy with traditional selectors - more reliable but slower and more expensive.", "default": "legacy" }, "maxEmails": { "title": "Max Emails", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Enter the maximum number of emails to collect.", "default": 20 } } }, "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 } } } } } } } } } } ```