# Engineering Email Scraper (`contacts-api/engineering-email-scraper`) Actor Engineering email scraper to extract verified engineer and engineering company emails from business directories, firm websites, and industry listings πŸ“§βš™οΈ Perfect for B2B outreach, recruitment, and engineering lead generation. - **URL**: https://apify.com/contacts-api/engineering-email-scraper.md - **Developed by:** [Lead Heaven](https://apify.com/contacts-api) (community) - **Categories:** Lead generation, Automation, Jobs - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.99 / 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. 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› οΈ Engineering Email Scraper β€” Find Verified Leads In Minutes > The fastest way to build a targeted engineering list. This actor searches Google Maps for engineering firms and consultancies across any city, crawls their websites, and extracts verified engineering email addresses, phone numbers, and social profiles β€” all in one clean, export-ready dataset. With the engineering email scraper, you can go from query to outreach in minutes. --- #### πŸš€ Quick Start 1. Enter your search term β€” e.g., "Engineering", "Civil Engineering", "Mechanical Engineering" 2. Add one or more target locations β€” e.g., "New York", "San Francisco, California" 3. Set your desired number of businesses with emails 4. Hit Run and get your results in minutes No coding required. Export to CSV, JSON, or Excel instantly. --- #### πŸ’‘ What Is the Engineering Email Scraper? The Engineering Email Scraper is a purpose-built lead generation and contact discovery tool for: - Sales and marketing teams at SaaS and B2B services - Recruiters and staffing agencies - Business development and partnership managers - Researchers and data analysts It combines Google Maps discovery with deep website crawling to extract publicly available contact data β€” producing an accurate, deduplicated engineering list ready for immediate use and delivering qualified engineering leads straight to your CRM. Whether you need it as an engineering lead finder, an engineering lead scraper, an engineering email finder, an engineering email extractor, or an engineering contact finder β€” this actor covers all five in a single automated run. Target civil, structural, mechanical, electrical, environmental, MEP, industrial, manufacturing, robotics, and other engineering segments with consistent, CRM-ready results. --- #### πŸ“¦ What Data Does It Extract? | Field | Description | |---|---| | Business Name | Practice or company name from Google Maps | | Website | Official website URL | | Phone | Primary phone from the listing or website | | Full Address | Complete address as listed | | City / State / ZIP | Parsed location components | | Country Code | ISO country code where available | | Emails | All public engineering email addresses extracted from website pages | | Additional Phones | Extra phone numbers discovered during crawl | | Social Media Links | Facebook, Instagram, LinkedIn, Twitter, and more | | Email Count | Total unique emails found per business | | Pages Scraped | Number of website pages crawled per domain | | Rating | Average Google Maps star rating | | Reviews | Total number of Google reviews | | Latitude / Longitude | Geo-coordinates for mapping and filtering | | Place ID | Google Maps place identifier | | Scrape Status | Per-record status: `success`, `partial`, or `error` | --- #### βš™οΈ Input Configuration ##### Minimal Example ```json { "googleMapsSearchTerm": "Engineering", "googleMapsLocation": ["New York"], "maxBusinesses": 50 } ```` ##### Full Example with All Options ```json { "googleMapsSearchTerm": "Engineering", "googleMapsLocation": [ "New York", "San Francisco, California", "Chicago, Illinois" ], "maxBusinesses": 200, "scrapeMaxBusinessesPerLocation": true, "proxyConfiguration": { "useApifyProxy": true } } ``` ##### Input Parameters | Parameter | Type | Required | Description | |---|---|---|---| | `googleMapsSearchTerm` | String | βœ… Yes | Business type to search β€” e.g., "Engineering", "civil engineering", "mechanical engineering" | | `googleMapsLocation` | Array | βœ… Yes | One or more locations β€” e.g., `["New York", "Austin, Texas"]` | | `maxBusinesses` | Number | ❌ No | Max businesses with emails to return (1–1,000). The run stops once reached | | `scrapeMaxBusinessesPerLocation` | Boolean | ❌ No | If `true`, applies the cap per location. If `false`, it's a combined total across all locations | | `proxyConfiguration` | Object | ❌ No | Proxy settings. Strongly recommended for large runs | *** #### πŸ“€ Sample Output ```json [ { "name": "Apex Civil Engineering, LLC", "website": "https://www.apexcivileng.com", "phone": "+1 212-555-0148", "full_address": "450 7th Ave, New York, NY 10123, United States", "city": "New York", "state": "NY", "zip": "10123", "country_code": "US", "scraped_emails": [ "info@apexcivileng.com", "bids@apexcivileng.com" ], "scraped_phones": ["+1 212-555-0148", "+1 212-555-0177"], "scraped_social_media": [ "linkedin:https://www.linkedin.com/company/apex-civil-engineering", "facebook:https://www.facebook.com/apexcivileng" ], "emails_found": 2, "pages_scraped": 12, "avg_rating": 4.6, "total_reviews": 54, "lat": 40.7505, "long": -73.9922, "place_id": "ChIJ-EXAMPLEID1", "scrape_status": "success" }, { "name": "Vector Dynamics Engineering", "website": "https://www.vectordynamicseng.com", "phone": "+1 415-555-0262", "full_address": "88 Market St, San Francisco, CA 94104, United States", "city": "San Francisco", "state": "CA", "zip": "94104", "country_code": "US", "scraped_emails": [ "contact@vectordynamicseng.com", "rfq@vectordynamicseng.com" ], "scraped_phones": ["+1 415-555-0262"], "scraped_social_media": [ "linkedin:https://www.linkedin.com/company/vector-dynamics", "twitter:https://twitter.com/vectordynamics" ], "emails_found": 2, "pages_scraped": 9, "avg_rating": 4.9, "total_reviews": 21, "lat": 37.7891, "long": -122.4011, "place_id": "ChIJ-EXAMPLEID2", "scrape_status": "success" } ] ``` *** #### πŸ”§ How It Works β€” Under the Hood ``` Step 1 β†’ Search Google Maps using your term + location Step 2 β†’ Collect business listings (name, address, phone, website) Step 3 β†’ Visit each website and crawl key pages (Home, Contact, About, etc.) Step 4 β†’ Extract public emails, phone numbers, and social media links Step 5 β†’ Deduplicate and normalize all contact data Step 6 β†’ Return structured results ready for export or API consumption ``` This pipeline enables the Engineering Email Scraper to function as both an engineering lead finder and an engineering contact scraper, while also serving as a reliable engineering data scraper for market mapping and enrichment. *** #### ✨ Key Features ##### 🎯 Precise Location Targeting Enter any city, state, or region. The actor pinpoints engineering firms in your exact target areas β€” delivering hyper-local engineering leads. ##### πŸ” Deep Website Crawl Goes beyond listings. Crawls homepages, contact pages, about pages, and footers to surface every available public email and phone number. ##### 🌎 Multi-Location Scaling Run across dozens of cities at once. Choose a combined cap or a per-location cap β€” perfect for building a large, multi-market engineering list. ##### 🧭 Broad Contact Discovery Collect general inboxes (info@, contact@), bids/procurement emails, and department mailboxes. Use it as an engineering contact scraper or engineering contact finder to capture the widest range of public touchpoints. ##### 🧹 Smart De-Duplication Automatically removes duplicate emails per domain so your lists stay clean and accurate β€” no messy cleanup required after export. ##### πŸ“Š Structured, CRM-Ready Output Normalized fields across every record. Push straight into HubSpot, Salesforce, Apollo, Instantly, or Make/Zapier β€” it doubles as an engineering data scraper to power analytics and territory planning. ##### πŸ›‘οΈ Proxy-Ready for Reliability Built-in proxy support enables stable, large-scale runs without rate-limiting or IP blocks β€” ideal for agency-level campaigns. ##### ⏱️ Stop at Your Target The actor halts as soon as your `maxBusinesses` limit is reached β€” no wasted compute, no overage. ##### πŸ”„ Schedulable & Repeatable Set it to run daily, weekly, or monthly to continuously grow and refresh your contact data. *** #### 🎯 Use Cases ##### πŸ’Ό B2B Outreach & Sales Build pitch lists targeting civil, structural, MEP, and mechanical firms. Use this as your engineering lead scraper to generate pipeline, and as an engineering email finder to fuel cold email sequences. ##### πŸ§‘β€πŸ’Ό Recruiting & Staffing Identify firms hiring across specialties and regions. The built-in engineering contact finder surfaces public inboxes you can’t reach via job boards. ##### 🀝 Partnerships & Vendor Sourcing Find potential partners across EPCs, integrators, and consultants. Treat the actor as an engineering contact scraper to compile procurement and vendor-relations emails. ##### 🧭 Market Mapping & Competitive Intel Map regional density by niche and size, then track changes over time. Results from this engineering data scraper can feed dashboards and territory designs. ##### πŸ—ƒοΈ CRM Enrichment & RevOps Backfill missing emails, phones, and social links on your accounts and prospects using the engineering email extractor. ##### 🏒 Agency Client Delivery Run repeatable weekly scrapes and deliver fresh segments to clients β€” a hands-off way to maintain prospect lists using a battle-tested engineering lead scraper. *** #### πŸ“ˆ How Many Results Can You Get? Scale from a small prospect list to a massive regional database β€” results depend on: - Number of locations added - Search term breadth (narrow vs. broad niche) - Website density and email visibility in each market - `maxBusinesses` setting and per-location vs. combined mode - Proxy configuration and run timeout ##### Typical Output Ranges | Campaign Size | Businesses with Emails | |---|---| | Small (1–3 cities) | 20 – 100 | | Medium (5–15 cities) | 200 – 600 | | Large (20+ cities / states) | 800 – 1,000+ per run | Run multiple times across different regions and niches to grow your dataset without hitting hard platform limits. *** #### πŸ”Œ Integrations & Export Options Once your run with the Engineering Email Scraper completes, you can: | Option | Details | |---|---| | JSON | Full structured data download | | CSV / Excel | Import directly into spreadsheets | | Apify API | Stream results into your own apps or workflows | | Zapier / Make | Trigger automations when new records are found | | Webhooks | Push results to your CRM or pipeline on run completion | Plug directly into Instantly, Smartlead, Apollo, HubSpot, Salesforce, or any outreach platform that accepts CSV/JSON imports. *** #### πŸ› οΈ Step-by-Step Usage Guide Step 1 β€” Log in to Apify\ Create a free account or sign in at apify.com. Step 2 β€” Open the Actor\ Search for "Engineering Email Scraper" in the Apify Store and click Try for free. Step 3 β€” Set Your Search Term\ Enter "Engineering" or a niche variant like "civil engineering", "MEP engineering", "structural engineering", or "industrial engineering". Step 4 β€” Add Target Locations\ Enter one or more city/state combos β€” e.g., "New York", "Austin, Texas", "Seattle, Washington". Step 5 β€” Set Your Limit\ Choose how many businesses with emails you want β€” 20 for a quick test, up to 1,000 for a full campaign. Step 6 β€” Choose Scaling Strategy - Combined cap: The total across all locations combined - Per-location cap: Applies your limit independently to each city Step 7 β€” Enable Proxies\ Turn on Apify Proxy for stable, uninterrupted crawling at scale. Step 8 β€” Run πŸš€\ Click Start and let the Engineering Email Scraper do the work. Step 9 β€” Export\ Download as JSON, CSV, or Excel β€” or pull via API straight into your stack. *** #### βš–οΈ Legal & Compliance This actor collects only publicly available business contact information β€” emails and phone numbers published openly on websites. Best practices to stay compliant: - Only use publicly visible contact data - Do not bypass login walls or paywalls - Respect each website’s robots.txt and Terms of Service - Include an unsubscribe option in all outreach - Follow applicable laws in your jurisdiction Relevant regulations to be aware of: | Regulation | Region | |---|---| | GDPR | European Union | | CAN-SPAM Act | United States | | CASL | Canada | | PECR | United Kingdom | This tool is intended for ethical business prospecting only. You are responsible for how you use the data collected. *** #### ❓ Frequently Asked Questions Q: Does this scrape private or personal emails?\ A: No. The actor only extracts emails that are publicly visible on business websites β€” general inboxes, procurement/bids, and department mailboxes. Q: Can I search multiple cities in one run?\ A: Yes. Add as many locations as needed. Use per-location capping for even geographic distribution. Q: Does it deduplicate results?\ A: Yes. Emails are deduplicated per domain to keep your lists accurate and tidy. Q: Can I schedule recurring runs?\ A: Absolutely. Use Apify’s built-in scheduler to run weekly or monthly and keep your data fresh. Q: What engineering niches does the search term support?\ A: Any Google Maps searchable term β€” try "civil engineering", "structural engineering", "MEP engineering", "mechanical engineering", "environmental engineering", "industrial engineering", or "engineering consultants". Q: Are proxies required?\ A: Not for small runs, but strongly recommended for 200+ business runs to avoid rate limits and maintain reliability. Q: What export formats are available?\ A: JSON, CSV, and Excel. You can also consume results via the Apify API or webhook. Q: How is this different from manual research?\ A: Manual search is slow and inconsistent. This automated workflow acts as an engineering lead finder and pipeline builder β€” from discovery to contact extraction β€” in minutes. Q: Can agencies white-label or resell this?\ A: Yes. Run it on behalf of clients and deliver fresh segments on a recurring basis. *** #### πŸ§‘β€πŸ’» Support & Custom Solutions Have a question, feature request, or need a custom build? Email: scrapermindapi@gmail.com We’re happy to help with: - Custom input/output configurations - Niche-specific adaptations - Bulk or enterprise run support - Integration assistance Built for marketers, recruiters, and operations teams who need accurate engineering leads at scale β€” fast, powered by the engineering email scraper. For any help or custom solution, contact via this mail: scrapermindapi@gmail.com # 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": "Engineering", "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": "Engineering", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("contacts-api/engineering-email-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "googleMapsSearchTerm": "Engineering", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("contacts-api/engineering-email-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "googleMapsSearchTerm": "Engineering", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }' | apify call contacts-api/engineering-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=contacts-api/engineering-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Engineering Email Scraper", "description": "Engineering email scraper to extract verified engineer and engineering company emails from business directories, firm websites, and industry listings πŸ“§βš™οΈ Perfect for B2B outreach, recruitment, and engineering lead generation.", "version": "1.0", "x-build-id": "QNfvkzgcezzbgnDxg" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/contacts-api~engineering-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-contacts-api-engineering-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/contacts-api~engineering-email-scraper/runs": { "post": { "operationId": "runs-sync-contacts-api-engineering-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/contacts-api~engineering-email-scraper/run-sync": { "post": { "operationId": "run-sync-contacts-api-engineering-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": "Engineering" }, "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 } } } } } } } } } } ```