# πŸ“© Google Maps Email Extractor (`poidata/google-maps-email-extractor`) Actor Quickly collect all business details, including emails, phone numbers, and social media links from Google Maps listings and their websites. Export data as JSON or CSV. Run via API, schedule runs, or integrate with your tools. - **URL**: https://apify.com/poidata/google-maps-email-extractor.md - **Developed by:** [Poidata](https://apify.com/poidata) (community) - **Categories:** Lead generation, Social media, Automation - **Stats:** 2,225 total users, 38 monthly users, 100.0% runs succeeded, 32 bookmarks - **User rating**: 1.89 out of 5 stars ## Pricing from $6.00 / 1,000 results This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## πŸ’Œ Google Maps Email Extractor **What is Google Maps Email Extractor?** Google Maps Email Extractor is a fast web scraping tool that finds businesses on Google Maps and transforms them into actionable **google map leads** by gathering email addresses, phone numbers and social media links along with other key business details. **Supports coordinate radius and GeoJSON polygon searches** for precise geographic targeting. Simply specify your search keywords and location, and it does all the workβ€”saving the results directly to an downloadable Apify Dataset. --- ### πŸ€” What can this Email Extractor do? * **Find Businesses:** Use keywords (`terms`) and a location to discover **google map leads** on Google Maps. * **Advanced Search Methods:** - **Location-based:** Traditional city/address searches - **Coordinate Radius:** Search within a specific radius around latitude/longitude - **GeoJSON Polygon:** Search within custom polygon boundaries * **Extract Emails:** Automatically visit each business's website and collect any listed email addresses. * **Gather Social Links:** Capture social media URLs (Facebook, Instagram, LinkedIn, YouTube) from each site. * **Refine Your Search:** Apply filters (`min_rating`, `min_reviews`, `min_photos`, `has_website`, `categories_filter`) to focus on the most relevant leads. * **Save & Export:** All dataβ€”including contacts, ratings, addresses, and metadataβ€”is saved in your Dataset and can be exported as JSON, CSV, Excel, or HTML. --- ### 🎯 Advanced Search Methods #### **Location-based Search (Traditional)** Use city names or addresses for broad area searches. #### **Coordinate Radius Search** Search within a specific radius around exact coordinates: - **`latitude`**: Decimal latitude coordinate - **`longitude`**: Decimal longitude coordinate - **`radius`**: Search radius in miles - **`totalAroundCoordinate`**: Maximum results within the radius #### **GeoJSON Polygon Search** Search within custom polygon boundaries: - **`polygon`**: GeoJSON polygon coordinates defining the search area - **`totalAroundCoordinate`**: Maximum results within the polygon **Search Priority:** Polygon > Geocoordinate > Location --- ### οΏ½οΏ½ Input Parameters Provide a JSON input to configure your run: #### **Basic Parameters** | Parameter | Type | Description | Default | | ------------------- | --------- | --------------------------------------------------------- | ------------ | | `terms` | `array` | Keywords to search (e.g., `["cafe","bakery"]`). | **required** | | `term` | `string` | Single keyword for quick tests (alias for `terms`). | β€” | | `location` | `string` | City or address (e.g., "New York, USA"). | β€” | | `total` | `integer` | Max number of listings to fetch (max 300). | `20` | #### **Advanced Search Parameters** | Parameter | Type | Description | Default | | ---------------------- | --------- | --------------------------------------------------------- | ------------ | | `latitude` | `number` | Decimal latitude for coordinate search. | β€” | | `longitude` | `number` | Decimal longitude for coordinate search. | β€” | | `radius` | `number` | Search radius in miles for coordinate search. | `1.0` | | `polygon` | `string` | GeoJSON polygon coordinates for polygon search. | β€” | | `totalAroundCoordinate`| `integer` | Max results for coordinate/polygon searches (max 300). | `20` | #### **Email Options** | Parameter | Type | Description | Default | | ---------------- | --------- | --------------------------------------------------------- | ------------ | | `has_email` | `boolean` | Only include businesses with extracted emails. | `false` | | `tech_enabled` | `boolean` | Enable advanced email extraction techniques. | `true` | | `social_enabled` | `boolean` | Extract social media links from websites. | `true` | #### **Filters** | Parameter | Type | Description | Default | | ------------------- | --------- | --------------------------------------------------------- | ------------ | | `min_rating` | `number` | Minimum star rating (0–5). | `0` | | `min_reviews` | `integer` | Minimum number of reviews. | `0` | | `min_photos` | `integer` | Minimum number of photos. | `0` | | `name_filter` | `array` | Matches and filters specific name (e.g., `["KFC"]`). | `[]` | | `has_website` | `boolean` | Only include businesses with a website. | `false` | | `categories_filter` | `array` | Filter by business categories. | `[]` | --- ### 🎯 Filters Explained * **`min_rating` (0–5):** Exclude lower-rated businesses. * **`min_reviews` (integer):** Ensure listings have sufficient review volume. * **`min_photos` (integer):** Only include listings with a minimum number of photos. * **`has_website` (boolean):** Skip businesses that don't list a website. * **`categories_filter` (array):** Narrow results to specific business categories. Use these filters alone or combined to target precise **google map leads**. --- ### οΏ½οΏ½ Output Structure Each record in your Apify Dataset contains: * **Business Details:** `name`, `address`, `city`, `state`, `zip`, `country`, `latitude`, `longitude` * **Contact Info:** `phone`, `website`, `emails` (array), `social` (object) * **Metrics:** `rating`, `reviewCount` * **Metadata:** `original_rank`, `display_rank`, `distance_miles`, `searchTerm`, `searchLocation`, `timestamp` View your **google map leads** in the **Overview** tab as a simple, ready-to-use table. google maps email lead extractor scraper --- Each Dataset record contains: * **Business Details:** `name`, `address`, `city`, `state`, `zip`, `country`, `latitude`, `longitude` * **Contact Info:** `phone`, `website`, `emails` (array), `social` (object) * **Metrics:** `rating`, `reviewCount` * **Metadata:** `original_rank`, `display_rank`, `distance_miles`, `searchTerm`, `searchLocation`, `timestamp` View your results in the **Overview** tab as a clean table of **Google Maps** leads with emails. --- ### πŸ’‘ Quick Start 1. Open **Google Maps Email Extractor** in the Apify Store. 2. Paste your JSON input into the Input tab. 3. Click **Run**. 4. Explore or download data under **Dataset β†’ Overview**. #### Example Inputs ##### **Location-based Search** ```json { "terms": ["school"], "location": "New York, USA", "total": 20, "min_rating": 4, "has_website": true } ```` ##### **Coordinate Radius Search** ```json { "terms": ["restaurant"], "latitude": 40.7128, "longitude": -74.0060, "radius": 2.0, "totalAroundCoordinate": 50, "has_website": true } ``` ##### **GeoJSON Polygon Search** ```json { "terms": ["hotel"], "polygon": { "type": "Polygon", "coordinates": [[ [-74.0060, 40.7128], [-74.0060, 40.7228], [-73.9960, 40.7228], [-73.9960, 40.7128], [-74.0060, 40.7128] ]] }, "totalAroundCoordinate": 100, "has_website": true } ``` *** ### πŸ“˜ Full JSON Example ```json { "emails": [ "arroyo@***boss.org", "maria.casiano@nyc****.org", "palexander@sch**ls.nyc.gov" ], "social": { "facebook": ["https://www.facebook.com/nycboss.org"], "instagram": ["https://www.instagram.com/businessofsportsschool/"], "linkedin": ["https://www.linkedin.com/school/10808989/"], "youtube": ["https://www.youtube.com/channel/.../featured"] }, "searchTerm": "School", "searchLocation": "New York, USA", "original_rank": 83, "display_rank": 3, "distance_miles": 0.5, "name": "M393 The Business of Sports School", "address": "439 W 49th St, New York, NY 10019", "street": "439 W 49th St", "neighborhood": "Manhattan", "city": "New York", "state": "New York", "zip": "10019", "country": "US", "country_code": "us", "country_name": "United States", "latitude": 40.7635391, "longitude": -73.9907469, "rating": 4.3, "reviewCount": 16, "phone": "(212) 246-2183", "phoneIsd": "+1 212-246-2183", "website": "nycboss.org", "url": "https://www.google.com/maps?cid=11138179353395429176", "placeId": "XE8aaKuDCfmNi-gPhtzNmAU", "cid": "11138179353395429176", "gid": "0x89c258510299fb27:0x9a92c31bfbb97f38", "photo": "https://lh3.googleusercontent.com/...", "photoCount": 14, "additionalInfo": { "info": { "Accessibility": [ "Wheelchair accessible parking lot", "Wheelchair accessible entrance" ] } }, "timestamp": "2025-05-06T20:05:17Z" } ``` *** ### ⚑ Performance & Processing #### **Incremental Saving** - Results are saved to the dataset as they're processed - Real-time progress tracking - No waiting until the end to see results #### **Deduplication** - Unique businesses collected by `gid` (Google ID) - Prevents duplicate entries across multiple search terms - Prioritizes records with more complete data #### **Processing Flow** 1. **Collect Unique Businesses:** Gather all unique businesses by `gid` first 2. **Extract Emails:** Process unique websites concurrently at 5 RPS 3. **Save Incrementally:** Push results to dataset as they're processed *** ### πŸ’° Pricing Google Maps Email Extractor uses a clear, pay-as-you-go model: - **$8 per 1,000 results** ($0.008 per business record). - **No setup fees** or subscriptions. For example, fetching 1,000 google map leads costs $8, and pulling 625 free leads with the trial plans credit. Your bill reflects the exact number of records saved to the Dataset. *** ### 🀝 Integrations & Support - **API & Webhooks:** Automate via Apify's REST API. - **Connect:** Zapier, Make, Slack, Google Sheets, and more. - **Support:** Open a GitHub issue or message us on the Apify Store. *** ### πŸ”‘ Keywords Google Maps Email Extractor, google map leads, email scraping, lead generation, Apify Actor, Google map social media, coordinate search, polygon search, GeoJSON *** ### πŸ› οΈ Tools & Resources #### πŸ—ΊοΈ **GeoJSON Polygon Creation** Need to create custom geographic boundaries for polygon searches? Use this free tool: **[Keene College Polyline Tool](https://www.keene.edu/campus/maps/tool/)** - Create and generate GeoJSON polygons for precise geographic targeting. **Features:** - **Interactive Map**: Click on the map to create polygon vertices - **GeoJSON Export**: Generate properly formatted GeoJSON coordinates - **Right-Hand Rule**: Automatically conforms to proper coordinate ordering - **Free to Use**: No registration required - **Simple Interface**: Easy-to-use polygon drawing tool **How to Use:** 1. Visit the [Polyline Tool](https://www.keene.edu/campus/maps/tool/) 2. Right-click on the map to begin drawing 3. Click to add vertices and create your polygon 4. Use the "Close Shape" button to complete your polygon 5. Copy the generated GeoJSON coordinates 6. Use the coordinates in your polygon search parameters **Perfect for:** - Creating custom search areas for polygon-based searches - Defining precise geographic boundaries - Targeting specific neighborhoods or regions - Complex area coverage requirements *** ### πŸ“© Need Custom Data? For bulk datasets by city, country, or global coverage, contact us at [Poidata.io](https://poidata.io/contact-us). # Actor input Schema ## `term` (type: `array`): The term or search terms to look for (e.g. restaurant, cafe, dentist, etc). Must be 25 characters or less. ## `location` (type: `string`): The location to search in (e.g. New York, Paris). Must be 50 characters or less. ## `language` (type: `string`): Language for search results ## `country` (type: `string`): Country context for search results ## `total` (type: `integer`): Up to 300 results per term, max 4,500 for 50 terms ## `coordinateSection` (type: `string`): Scrape with geo-coordinates ## `latitude` (type: `string`): Latitude of the location (optional if location is provided). ## `longitude` (type: `string`): Longitude of the location (optional if location is provided). ## `radius` (type: `integer`): Set radius to scrape around the geocoordinate location. ## `polygon` (type: `string`): Polygon of the location (optional if location is provided). ## `totalAroundCoordinate` (type: `integer`): Set total results to scrape around the geocoordinate location per term. ## `advanceOptionSection` (type: `string`): Filters ## `min_rating` (type: `string`): Minimum star rating (0–5, decimals allowed) ## `min_reviews` (type: `integer`): Minimum number of reviews ## `min_photos` (type: `integer`): Minimum number of photos ## `has_website` (type: `boolean`): Filter to only businesses with websites (checked) or without websites (unchecked) ## `name_filter` (type: `string`): Filter businesses by name (case-insensitive substring match) ## `categories_filter` (type: `array`): Filter businesses by category (comma-separated, case-insensitive) ## `tech_enabled` (type: `boolean`): Enable detection of technologies used on the website (may slow down scraping). ## `social_enabled` (type: `boolean`): Enable detection of social media links from the website. ## `has_email` (type: `boolean`): If checked, only keep businesses where at least one email address was found. ## Actor input object example ```json { "term": [ "Restaurant" ], "location": "New York, USA", "language": "en", "country": "us", "total": 20, "radius": 1, "totalAroundCoordinate": 20, "min_rating": "0", "min_reviews": 0, "min_photos": 0, "tech_enabled": false, "social_enabled": true, "has_email": 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("poidata/google-maps-email-extractor").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 = {} # Run the Actor and wait for it to finish run = client.actor("poidata/google-maps-email-extractor").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 '{}' | apify call poidata/google-maps-email-extractor --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=poidata/google-maps-email-extractor", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "πŸ“© Google Maps Email Extractor", "description": "Quickly collect all business details, including emails, phone numbers, and social media links from Google Maps listings and their websites. Export data as JSON or CSV. Run via API, schedule runs, or integrate with your tools.", "version": "0.0", "x-build-id": "0OggDXSl5xnKudivd" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/poidata~google-maps-email-extractor/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-poidata-google-maps-email-extractor", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/poidata~google-maps-email-extractor/runs": { "post": { "operationId": "runs-sync-poidata-google-maps-email-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/poidata~google-maps-email-extractor/run-sync": { "post": { "operationId": "run-sync-poidata-google-maps-email-extractor", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "term" ], "properties": { "term": { "title": "πŸ‘‰ Search Term", "maxItems": 50, "type": "array", "description": "The term or search terms to look for (e.g. restaurant, cafe, dentist, etc). Must be 25 characters or less.", "default": [ "Restaurant" ], "items": { "type": "string" } }, "location": { "title": "🌍 Location", "maxLength": 50, "type": "string", "description": "The location to search in (e.g. New York, Paris). Must be 50 characters or less.", "default": "New York, USA" }, "language": { "title": "πŸ”  Language", "enum": [ "en" ], "type": "string", "description": "Language for search results", "default": "en" }, "country": { "title": "Country Context", "enum": [ "us" ], "type": "string", "description": "Country context for search results", "default": "us" }, "total": { "title": "πŸ”’ Total Results", "minimum": 20, "maximum": 300, "type": "integer", "description": "Up to 300 results per term, max 4,500 for 50 terms", "default": 20 }, "coordinateSection": { "title": "Scrape with Geo-coordinates", "type": "string", "description": "Scrape with geo-coordinates" }, "latitude": { "title": "Latitude", "type": "string", "description": "Latitude of the location (optional if location is provided)." }, "longitude": { "title": "Longitude", "type": "string", "description": "Longitude of the location (optional if location is provided)." }, "radius": { "title": "Radius", "minimum": 1, "maximum": 100, "type": "integer", "description": "Set radius to scrape around the geocoordinate location.", "default": 1 }, "polygon": { "title": "Polygon", "type": "string", "description": "Polygon of the location (optional if location is provided)." }, "totalAroundCoordinate": { "title": "Total Results Around Coordinate", "minimum": 20, "maximum": 100000, "type": "integer", "description": "Set total results to scrape around the geocoordinate location per term.", "default": 20 }, "advanceOptionSection": { "title": "βš™οΈ Filters", "type": "string", "description": "Filters" }, "min_rating": { "title": "Minimum Rating", "pattern": "^(?:[0-4](?:\\.\\d+)?|5(?:\\.0+)?)$", "type": "string", "description": "Minimum star rating (0–5, decimals allowed)", "default": "0" }, "min_reviews": { "title": "Minimum Reviews", "minimum": 0, "type": "integer", "description": "Minimum number of reviews", "default": 0 }, "min_photos": { "title": "Minimum Photos", "minimum": 0, "type": "integer", "description": "Minimum number of photos", "default": 0 }, "has_website": { "title": "Has Website", "type": "boolean", "description": "Filter to only businesses with websites (checked) or without websites (unchecked)" }, "name_filter": { "title": "Business Name Filter", "type": "string", "description": "Filter businesses by name (case-insensitive substring match)" }, "categories_filter": { "title": "Multiple Categories Filter", "type": "array", "description": "Filter businesses by category (comma-separated, case-insensitive)", "items": { "type": "string" } }, "tech_enabled": { "title": "Detect Website Tech Stack", "type": "boolean", "description": "Enable detection of technologies used on the website (may slow down scraping).", "default": false }, "social_enabled": { "title": "Detect Social Profiles", "type": "boolean", "description": "Enable detection of social media links from the website.", "default": true }, "has_email": { "title": "Only Keep Results With Emails", "type": "boolean", "description": "If checked, only keep businesses where at least one email address was found.", "default": false } } }, "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 } } } } } } } } } } ```