# Allergist Email Scraper (`scraperoka/allergist-email-scraper`) Actor 🧑‍⚕️ Allergist Email Scraper finds allergist email addresses from targeted profiles/pages for fast B2B outreach. ✅ Cleaner lists, higher deliverability & lead generation. 🚀 Perfect for marketing, sales, and recruitment campaigns. - **URL**: https://apify.com/scraperoka/allergist-email-scraper.md - **Developed by:** [Scraperoka](https://apify.com/scraperoka) (community) - **Categories:** Lead generation, Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 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 ### Allergist Email Scraper 📬 **Allergist Email Scraper** is an actor that helps you scrape allergist business listings and extract their contact information from publicly available sources—especially email addresses—so you can quickly build a targeted **allergist email list scraper** for outreach, research, or analysis. It supports both a **find allergist emails** workflow and broader **medical specialty email scraper** use cases, including building an **allergy clinic email scraper** style dataset by location. Whether you're a marketer, recruiter, or data enthusiast, this **doctor email extraction tool** streamlines the manual work of collecting specialist practice contact details at scale, saving you hours of manual work. --- ### Why choose Allergist Email Scraper? ✅ | Feature | Benefit | | --- | --- | | ✅ **All-in-one business + website contact enrichment** | Extracts business details plus scraped contact emails, phone numbers, and social media profiles in one run | | ✅ **Reliability with built-in resilience** | Includes retries and fallbacks for more consistent results when sites are difficult to access | | ✅ **Structured, dataset-ready output** | Saves results to an Apify dataset with consistent fields for easy export and downstream use | | ✅ **Built for scale across multiple locations** | Use multi-location input and limits to control how many businesses you collect | | ✅ **Proxy support for smoother scraping** | Includes **proxyConfiguration** support to help reduce scraping interruptions at higher volumes | | ✅ **Progressive saving to reduce data loss** | Pushes results to the dataset as it processes businesses so you don’t lose everything if a run stops | --- ### Key features 🔑 - 📌 **Allergist-focused lead discovery**: Uses your search term and geographic location(s) to target allergist businesses for contact extraction. - 🌐 **Website contact extraction**: Scrapes each business website to collect **scraped_emails**, **scraped_phones**, and **scraped_social_media**. - 🧠 **Email-only dataset control**: When enabled, it can save only businesses that actually have emails (great for **allergist marketing email list** building). - 🛡️ **ProxyConfiguration support**: Helps improve reliability during large-scale scraping. - 🔄 **Resilient scraping behavior**: Includes resilience patterns so the run can keep going when individual sites fail. - 💾 **Real-time dataset saving**: Results are pushed to the Apify dataset immediately while businesses are processed. - 📊 **Detailed contact + location fields**: Produces records with name, website, phone, full address, city/state/zip/country code, and coordinates when available. - 🧾 **Email-level rows**: If emails are found, the dataset can contain one row per email via the flattened output approach (useful for CRM import and validation workflows). --- ### Input Provide input via an `input.json` file. Example structure: ```json { "googleMapsSearchTerm": "Allergist", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "scrapeMaxBusinessesPerLocation": false, "proxyConfiguration": { "useApifyProxy": true } } ```` #### Input Fields | Field | Required | Description | | --- | --- | --- | | `googleMapsSearchTerm` | Yes | The business type or niche you want to scrape (for example, `Allergist`, or any other niche you’d like to convert into an **allergist lead email scraper** style list). | | `googleMapsLocation` | Yes | Target geographic location(s) you want to scrape for (for example, `["Miami, Florida"]`). You can pass multiple locations. | | `maxBusinesses` | No | Maximum number of businesses to find (range: `1-1000`). The scraper stops when this target is reached. | | `scrapeMaxBusinessesPerLocation` | No | Controls whether the actor collects up to `maxBusinesses` results **per location** (`true`) or combines all locations up to a **single total limit** (`false`). | | `proxyConfiguration` | No | Proxy settings for scraping. Recommended for larger runs. Includes an option `proxy support` (prefilled to `true`). | *** ### Output After execution, the actor saves results in the Apify dataset **as JSON records** (pushed via `Actor.push_data`). Each dataset row represents a business enriched with scraped contact info, and when emails are present it can also be flattened to one row per email. #### Example output ```json { "name": "Sample Allergist Clinic", "website": "https://example.com", "phone": "+1-555-555-5555", "full_address": "123 Main St New York NY 10001 US", "city": "New York", "state": "NY", "zip": "10001", "country_code": "US", "scraped_emails": [ "contact@example.com", "info@example.com" ], "scraped_phones": [ "+1-555-000-0000" ], "scraped_social_media": [ "https://www.facebook.com/exampleclinic" ], "emails_found": 2, "pages_scraped": 5, "avg_rating": 4.6, "total_reviews": 128, "lat": 40.7128, "long": -74.006, "place_id": "ChIJN1t_tDeuEmsRUsoU7Y9sVtQ", "scrape_status": "success", "email_found": "contact@example.com" } ``` #### Output Fields | Field | Type | Description | | --- | --- | --- | | `name` | string | Business name for the allergist listing. | | `website` | string | Business website URL (used as the starting point for contact extraction). | | `phone` | string | Phone number from the business listing (not necessarily the phone found on the website). | | `full_address` | string | Full address combined from the available address parts. | | `city` | string | City component of the address. | | `state` | string | State component of the address. | | `zip` | string | Postal/ZIP code component. | | `country_code` | string | Country code component of the address. | | `scraped_emails` | array | Emails extracted from the business website. | | `scraped_phones` | array | Phone numbers extracted from the business website. | | `scraped_social_media` | array | Social media profile links extracted from the business website. | | `emails_found` | number | Count of emails found for the business. | | `pages_scraped` | number | Number of processed URLs/pages during the website scraping phase. | | `avg_rating` | number | Average rating value from the business listing (when available). | | `total_reviews` | number | Total review count from the business listing (when available). | | `lat` | number | Latitude coordinate (when available). | | `long` | number | Longitude coordinate (when available). | | `place_id` | string | Place identifier from the listing (used internally for uniqueness). | | `scrape_status` | string | Status of the website scraping step (e.g. `success`, `failed`, `no_website`, `error`). | | `email_found` | string | Present when emails are flattened into email-level rows; contains the email for that specific row. May be empty when no emails are saved in non-email-only mode. | | `scrape_error` | string | Present when scraping fails; contains the error message (as pushed into the dataset). | You can export the dataset from Apify to JSON (and typically also CSV from the dashboard), then plug it directly into your outreach workflows or analysis. *** ### How to use Allergist Email Scraper (via Apify Console) 🚀 1. **Open Apify Console** Go to [console.apify.com](https://console.apify.com) and sign in. 2. **Find the actor** Search for **Allergist Email Scraper** in the Actors marketplace. 3. **Configure input** In the **INPUT** section, fill in: `googleMapsSearchTerm` (for example, `Allergist`) and one or more `googleMapsLocation` values. Optionally set `maxBusinesses`, `scrapeMaxBusinessesPerLocation`, and `proxyConfiguration`. 4. **Choose proxy settings (optional)** If you’re running larger batches, enable proxy support via `proxyConfiguration` (the form is prefilled with `proxy support: true`). 5. **Run the actor** Click **Run** to start. During the run, you’ll see logs showing progress per location and per business. 6. **Monitor progress** Watch the logs for progress updates (including how many businesses are found) and status outcomes like success or failed website scrapes. 7. **Open the dataset** After completion, go to the **OUTPUT** tab and open the dataset (Business Contact Data). 8. **Export your results** Export your dataset records for use in tools like spreadsheets, CRMs, or your **allergy clinic email scraper** pipelines. No coding required—get targeted allergist contact data in minutes with this **allergist email list scraper**. *** ### Advanced features & SEO optimization ✨ - 🧾 **Engineered for allergist email lists**: Built specifically for **Allergist Email Scraper** lead generation patterns—turning a specialist niche + location into a ready-to-use **allergist contact email finder** dataset. - 🔄 **Email-only quality mode (email-first)**: When email-only mode is enabled in the workflow, it focuses the output on businesses that have emails—ideal for a cleaner **custom allergist email outreach list**. - 🌐 **Rich contact enrichment**: Not only emails—also extracts phones and social profiles, which helps you verify and enrich a **medical directory email scraper** output. - 🛡️ **Proxy support for stability**: Helps improve reliability when scraping at higher volumes, especially when you’re building an **allergist marketing email list** across multiple cities. *** ### Best use cases 📌 - 📈 **Lead generation for allergist practices**: Build a ready-to-import **allergist email list scraper** dataset by city for outreach campaigns. - 🔬 **Market research by location**: Compare allergist clinics across multiple `googleMapsLocation` inputs and analyze availability of contact details. - 🧠 **Healthcare sales prospecting**: Enrich CRM records with emails and additional contact channels for **healthcare lead generation email scraper** workflows. - 🗂️ **Data enrichment for specialist programs**: Create a **specialist practice email database** including websites, phone(s), and social links. - 🧾 **Email outreach verification prep**: Use extracted email domains to support **verify doctor email addresses** steps downstream. - 💻 **Automation pipeline ingestion**: Feed dataset rows into your scripts for segmentation, deduplication, and **doctor email extraction tool** workflows. - 📊 **Analyst-friendly datasets**: Use consistent fields like `avg_rating`, `total_reviews`, coordinates (`lat`, `long`), and `place_id` to drive reporting. *** ### Technical specifications #### Supported Input Formats ✅ `googleMapsSearchTerm` as a string (e.g., `Allergist`)\ ✅ `googleMapsLocation` as an array of locations (each location is a string) #### Proxy Support ✅ `proxyConfiguration` (includes `proxy support` in the provided schema) #### Retry Mechanism ✅ Includes resilience patterns and fallback logic during scraping to improve success rates when individual sites fail. #### Dataset Structure ✅ Uses the Apify dataset named **Business Contact Data** with the listed fields: `name`, `website`, `phone`, `full_address`, `city`, `state`, `zip`, `country_code`, `scraped_emails`, `scraped_phones`, `scraped_social_media`, `emails_found`, `pages_scraped`, `avg_rating`, `total_reviews`, `lat`, `long`, `place_id`, `scrape_status` #### Rate Limits & Performance ✅ Designed for multi-location collection with limits controlled by `maxBusinesses` and (optionally) per-location limits via `scrapeMaxBusinessesPerLocation`. #### Limitations ❌ Output quality depends on whether businesses have accessible websites and whether the emails are publicly present on those sites.\ ❌ Some entries may be returned with `scrape_status` such as `no_website`, `failed`, or `error` if enrichment can’t complete. *** ### FAQ #### Can I scrape more than one location at a time? ✅ Yes. Provide multiple values in `googleMapsLocation` as an array. You can also control whether `maxBusinesses` is applied per location (`scrapeMaxBusinessesPerLocation: true`) or as one global cap. #### How many businesses will it collect? You can set `maxBusinesses` (range `1-1000`). The actor stops when it reaches the target based on whether you enable `scrapeMaxBusinessesPerLocation`. #### Does it extract emails only, or more contact fields too? It extracts emails (`scraped_emails`) and also gathers `scraped_phones` and `scraped_social_media` from the business website where available. #### What does `scrape_status` mean? `score_status` is a text field indicating the outcome of the website scraping step. Values pushed into the dataset include `success`, `failed`, `no_website`, and `error` depending on what happened during extraction. #### Will the dataset include one row per business or per email? When emails are found, the actor pushes a flattened email-level row using `email_found` (and removes `scraped_emails` from that flattened row). If no emails are found, behavior depends on whether email-only mode is active; otherwise it can push a business row with `email_found` empty. #### Do I need to use proxies? No. Proxy support is optional via `proxyConfiguration`. For larger-scale scraping, proxies are recommended for reliability and to reduce interruptions. #### What if a business has no website? In that case, the actor sets `scraped_emails` to an empty list, sets `scrape_status` to `no_website`, and (in non-email-only mode) can still push the business record to the dataset. #### Is it legal to use this for healthcare lead generation? ✅ This tool reads **publicly accessible sources**. Compliance with GDPR/CCPA, spam regulations, and each website’s terms of service is your responsibility. *** ### Support & feature requests 🤝 If you’re using **Allergist Email Scraper** for an **allergist lead email scraper** workflow and you’d like improvements, we’d love to hear from you. - 💡 **Feature Requests**: CSV export enhancements, custom output shaping for your **allergist email list scraper** pipelines, and CRM-ready formatting are great examples. - 📧 **Contact**: email us at Your feedback helps shape the roadmap for this **doctor email extraction tool**. *** ### Final thoughts on Allergist Email Scraper 💬 *Allergist Email Scraper*\* gives you an SEO-friendly, structured way to build an allergist email list scraper for location-based outreach.\* Run it at scale, export the results, and turn your contact research into action. # Actor input Schema ## `googleMapsSearchTerm` (type: `string`): Enter the business type or niche for email scraper (e.g., 'coffee shops', 'dentists'). ## `googleMapsLocation` (type: `array`): Target geographic location for the email scraper (e.g., 'Miami, Florida'). ## `maxBusinesses` (type: `integer`): Target number of businesses to find (1-1000). The scraper will stop when this target is reached. ## `scrapeMaxBusinessesPerLocation` (type: `boolean`): If enabled, the scraper will collect up to `maxBusinesses` results per location. If disabled, it combines all locations up to a single total limit. ## `proxyConfiguration` (type: `object`): Proxy settings for scraping. Recommended for large-scale scraping. ## Actor input object example ```json { "googleMapsSearchTerm": "Allergist", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "scrapeMaxBusinessesPerLocation": false, "proxyConfiguration": { "useApifyProxy": true } } ``` # 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 = { "googleMapsSearchTerm": "Allergist", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("scraperoka/allergist-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 = { "googleMapsSearchTerm": "Allergist", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("scraperoka/allergist-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 '{ "googleMapsSearchTerm": "Allergist", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }' | apify call scraperoka/allergist-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraperoka/allergist-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Allergist Email Scraper", "description": "🧑‍⚕️ Allergist Email Scraper finds allergist email addresses from targeted profiles/pages for fast B2B outreach. ✅ Cleaner lists, higher deliverability & lead generation. 🚀 Perfect for marketing, sales, and recruitment campaigns.", "version": "1.0", "x-build-id": "CfFETHRbL2WH5oFLJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraperoka~allergist-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraperoka-allergist-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraperoka~allergist-email-scraper/runs": { "post": { "operationId": "runs-sync-scraperoka-allergist-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraperoka~allergist-email-scraper/run-sync": { "post": { "operationId": "run-sync-scraperoka-allergist-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "googleMapsLocation", "googleMapsSearchTerm" ], "properties": { "googleMapsSearchTerm": { "title": "Search Term", "type": "string", "description": "Enter the business type or niche for email scraper (e.g., 'coffee shops', 'dentists').", "default": "Allergist" }, "googleMapsLocation": { "title": "Location", "type": "array", "description": "Target geographic location for the email scraper (e.g., 'Miami, Florida').", "default": [ "New York" ], "items": { "type": "string" } }, "maxBusinesses": { "title": "Maximum Businesses With Emails", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Target number of businesses to find (1-1000). The scraper will stop when this target is reached.", "default": 5 }, "scrapeMaxBusinessesPerLocation": { "title": "Scrape Max Businesses Per Location", "type": "boolean", "description": "If enabled, the scraper will collect up to `maxBusinesses` results per location. If disabled, it combines all locations up to a single total limit.", "default": false }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for scraping. Recommended for large-scale scraping." } } }, "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 } } } } } } } } } } ```