# Food Stores Email Scraper (`contacts-api/food-stores-email-scraper`) Actor Food stores email scraper to extract verified emails from grocery stores, supermarkets, and food retail businesses πŸ“§πŸ›’ Perfect for supplier outreach, partnerships, and food industry lead generation. - **URL**: https://apify.com/contacts-api/food-stores-email-scraper.md - **Developed by:** [Lead Heaven](https://apify.com/contacts-api) (community) - **Categories:** Lead generation, Automation, E-commerce - **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›’ Food Stores Email Scraper β€” Find Verified Leads in Minutes > The fastest way to build a targeted food stores email database. This actor searches Google Maps for Food Stores and related categories in any location, crawls their websites, and extracts verified emails, phone numbers, and social media profiles β€” all in one clean, export-ready dataset. --- #### πŸš€ Quick Start With Food Stores Email Scraper 1. Enter your search term β€” e.g., "Food Stores", "grocery stores", "organic markets" 2. Add one or more locations β€” e.g., "New York", "Austin, Texas" 3. Set your desired number of businesses with emails 4. Hit Run and get results in minutes No coding required. Export to CSV, JSON, or Excel instantly. --- #### πŸ’‘ What Is The Food Stores Email Scraper? The Food Stores Email Scraper is a purpose-built lead generation and contact discovery tool for: - Consumer brand sales and distribution teams - Wholesale suppliers and brokers - B2B outreach and agency lead gen - Market researchers and analysts It combines Google Maps listing discovery with deep website crawling to extract publicly available contact data β€” producing accurate, deduplicated food stores email lists. Whether you need a food stores lead finder, a food stores lead scraper, or a food stores email finder, this actor covers all three in a single automated run. Use it as your food stores contact scraper and food stores contact finder to enrich records at scale, or as a food stores email extractor and food stores data scraper to build a fresh food stores list in minutes. --- #### πŸ“¦ What Data Does It Extract? | Field | Description | |---|---| | Business Name | Store 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 food stores 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 | This dataset structure makes it easy to build a high-quality food stores list, prioritize food stores leads by rating/review volume, and push contacts into your CRM. --- #### βš™οΈ Input Configuration For Food Stores Email Scraper ##### Minimal Example ```json { "googleMapsSearchTerm": "Food Stores", "googleMapsLocation": ["New York"], "maxBusinesses": 50 } ```` ##### Full Example with All Options ```json { "googleMapsSearchTerm": "Food Stores", "googleMapsLocation": [ "New York", "Boston, Massachusetts", "Philadelphia, Pennsylvania" ], "maxBusinesses": 200, "scrapeMaxBusinessesPerLocation": true, "proxyConfiguration": { "useApifyProxy": true } } ``` ##### Input Parameters | Parameter | Type | Required | Description | |---|---|---|---| | googleMapsSearchTerm | String | Yes | Business type to search β€” e.g., "Food Stores", "grocery store", "organic market". | | googleMapsLocation | Array | Yes | One or more target locations β€” e.g., \["New York", "Austin, Texas"]. | | maxBusinesses | Number | No | Maximum businesses with emails to return (1–1,000). The run stops when this target is reached. | | scrapeMaxBusinessesPerLocation | Boolean | No | If true, applies the cap per location. If false, uses a combined total across all locations. | | proxyConfiguration | Object | No | Proxy settings. Strongly recommended for large or multi-location runs. | *** #### πŸ“€ Sample Output ```json [ { "name": "Green Market Grocers", "website": "https://www.greenmarketgrocers.com", "phone": "+1 212-555-0174", "full_address": "145 W 72nd St, New York, NY 10023, United States", "city": "New York", "state": "NY", "zip": "10023", "country_code": "US", "scraped_emails": [ "info@greenmarketgrocers.com", "orders@greenmarketgrocers.com" ], "scraped_phones": ["+1 212-555-0174", "+1 212-555-0129"], "scraped_social_media": [ "facebook:https://facebook.com/greenmarketgrocers", "instagram:https://instagram.com/greenmarketgrocers" ], "emails_found": 2, "pages_scraped": 12, "avg_rating": 4.6, "total_reviews": 264, "lat": 40.7789, "long": -73.9801, "place_id": "ChIJZ-EXAMPLEID", "scrape_status": "success" }, { "name": "Hudson Fresh Foods", "website": "https://www.hudsonfreshfoods.com", "phone": "+1 646-555-0110", "full_address": "88 Hudson St, New York, NY 10013, United States", "city": "New York", "state": "NY", "zip": "10013", "country_code": "US", "scraped_emails": [ "contact@hudsonfreshfoods.com" ], "scraped_phones": ["+1 646-555-0110"], "scraped_social_media": [ "linkedin:https://linkedin.com/company/hudsonfreshfoods" ], "emails_found": 1, "pages_scraped": 7, "avg_rating": 4.2, "total_reviews": 98, "lat": 40.7194, "long": -74.0064, "place_id": "ChIJP-EXAMPLEID2", "scrape_status": "success" } ] ``` *** #### πŸ”§ How It Works β€” Under The Hood Of Food Stores Email Scraper Step 1 β†’ Discover Google Maps listings using your search term and locations\ Step 2 β†’ Collect store name, address, phone, website, geo-coordinates, and rating data\ Step 3 β†’ Visit each website and crawl key pages (Home, Contact, About, Footer, Careers, etc.)\ Step 4 β†’ Extract public emails, phone numbers, and social media links\ Step 5 β†’ Deduplicate, normalize, and score contacts for clean export\ Step 6 β†’ Return structured results ready for CSV/JSON export or API consumption Use it as an always-on food stores lead finder and food stores email extractor to automate discovery plus enrichment in one pass. *** #### ✨ Key Features ##### 🎯 Precise Location Targeting For Food Stores Leads Pinpoint stores by city, state, or region. Run multiple locations at once and cap results per location for well-distributed food stores leads. ##### πŸ” Deep Website Crawl And Food Stores Email Extraction Goes beyond the listing page. Crawls contact, about, and high-signal pages to surface every available public food stores email and phone number. Operates as a food stores email finder and food stores contact scraper in one. ##### 🌎 Multi-Location Scaling Launch campaigns across dozens of cities. Choose a combined cap or a per-location cap β€” ideal for building a robust food stores list for regional or national coverage. ##### 🧹 Smart De-Duplication Automatically de-duplicates emails per domain and normalizes formats so your exported food stores leads are clean and CRM-ready. ##### πŸ“Š Structured Output For CRMs Consistent field names and contact arrays let you push data directly into HubSpot, Salesforce, Apollo, or outreach tools β€” perfect for a food stores data scraper workflow. ##### πŸ›‘οΈ Proxy-Ready For Reliability Built-in proxy support enables stable, large-scale runs without rate-limiting β€” essential when using the tool as a food stores lead scraper or food stores contact finder. ##### ⏱️ Stop At Your Target The actor halts as soon as your maxBusinesses limit is reached β€” saving compute and keeping budgets predictable. ##### πŸ”„ Schedulable & Repeatable Run daily, weekly, or monthly to maintain an up-to-date food stores list and continuously capture new food stores leads. *** #### 🎯 Use Cases ##### πŸ’Ό B2B Outreach & Sales Build pitch lists for grocery chains, indie markets, co-ops, and specialty stores. Use the tool as your food stores lead scraper and food stores email finder to power cold email sequences. ##### πŸ›’ Brand Distribution & Wholesale Identify stores to carry your CPG products. The food stores lead finder highlights prospects by city and niche, while the food stores contact scraper collects emails for category managers or store inboxes. ##### πŸ“£ Local & Regional Marketing Create geo-targeted campaigns with verified food stores email contacts and phone numbers pulled from official websites. ##### 🀝 Partnerships & Vendor Onboarding Find complementary stores for partnerships, sampling, or local promotions. Use the food stores contact finder and food stores email extractor to speed up outreach. ##### πŸ“š Market Research & Competitor Mapping Map store density, ratings, and review counts. Export via API to integrate with your BI stack using this food stores data scraper. ##### πŸ—ƒοΈ CRM Enrichment Fill missing emails, phones, and social links for your existing store records and keep your food stores list fresh. *** #### πŸ“ˆ How Many Results Can You Get? Output depends on: - Number of locations - Breadth of your search terms (e.g., β€œFood Stores” vs β€œorganic grocery”) - Website density and the visibility of contact emails - maxBusinesses and per-location vs combined cap - Proxy configuration and run timeout Typical Ranges: - Small (1–3 cities): 30–120 businesses with emails - Medium (5–15 cities): 200–600 businesses with emails - Large (20+ cities/states): 800–1,000+ per run Run multiple campaigns to expand your regional or national food stores list, and iterate queries to capture more food stores leads over time. *** #### πŸ”Œ Integrations & Export Options Once your run completes, you can: - JSON: Download full structured data - CSV / Excel: Import directly into spreadsheets - Apify API: Stream results into your apps and workflows - Zapier / Make: Trigger automations when new food stores leads are found - Webhooks: Push results to your CRM or pipeline on run completion Plug into Instantly, Smartlead, Apollo, HubSpot, Salesforce, or any outreach platform that accepts CSV/JSON imports. *** #### πŸ› οΈ Step-By-Step Usage Guide For Food Stores Email Scraper 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 β€œFood Stores Email Scraper” in the Apify Store and click Try for free. Step 3 β€” Set Your Search Term\ Enter "Food Stores" or a niche alternative like "grocery stores", "Asian supermarket", or "organic market". Step 4 β€” Add Target Locations\ Enter one or more city/state combos β€” e.g., "New York", "Austin, Texas". Step 5 β€” Set Your Limit\ Choose how many businesses with emails you want β€” start small to test, scale up to 1,000. Step 6 β€” Choose Scaling Strategy - Combined cap: One total across all locations - Per-location cap: Applies your limit independently to each location Step 7 β€” Enable Proxies\ Turn on Apify Proxy for stability and scale. Step 8 β€” Run πŸš€\ Click Start and let the Food Stores 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 outreach - Follow applicable laws in your jurisdiction Relevant regulations to be aware of: - GDPR (EU) - CAN-SPAM Act (US) - CASL (Canada) - PECR (UK) This tool is intended for ethical business prospecting only. You are responsible for how you use the data collected when building a food stores list or contacting food stores leads. *** #### ❓ 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 like info@, contact@, orders@ commonly used for food stores email communication. Q: Can I search multiple cities in one run?\ A: Yes. Add as many locations as needed. Use the per-location cap for even geographic distribution of food stores leads. Q: Does it deduplicate emails and results?\ A: Yes. Emails are deduplicated per domain, ensuring a clean food stores list ready for upload. Q: Is a proxy required?\ A: Not for small tests, but strongly recommended for 200+ businesses or multi-location runs to avoid rate limits β€” especially when operating as a food stores lead scraper or food stores data scraper. Q: What types of stores can it find?\ A: Any Google Maps-searchable β€œFood Stores” category β€” grocery stores, specialty markets, ethnic supermarkets, organic shops, and convenience stores. Q: Can I use this as a food stores lead finder for distributors and brands?\ A: Absolutely. Many use it as a food stores contact scraper and food stores email extractor to build outreach pipelines for wholesale and brand partnerships. Q: What export formats are available?\ A: JSON, CSV, and Excel. You can also consume results via the Apify API, webhooks, or automation platforms. *** #### πŸ§‘β€πŸ’» Support & Custom Solutions Have a question, feature request, or need a custom build tailored to your niche? Email: scrapermindapi@gmail.com We can help with: - Custom input/output formats for your CRM - Niche-specific tuning (e.g., chains vs independents) - Large or scheduled runs across many regions - Integration assistance for Zapier/Make, APIs, and webhooks *** Built for brands, wholesalers, agencies, and researchers who need accurate food stores leads at scale β€” fast. Use it as your food stores email finder, food stores lead finder, and food stores contact finder to build a high-quality food stores list with verified food stores email contacts. 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": "Food Stores", "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": "Food Stores", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("contacts-api/food-stores-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": "Food Stores", "googleMapsLocation": ["New York"], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("contacts-api/food-stores-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": "Food Stores", "googleMapsLocation": [ "New York" ], "maxBusinesses": 5, "proxyConfiguration": { "useApifyProxy": true } }' | apify call contacts-api/food-stores-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=contacts-api/food-stores-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Food Stores Email Scraper", "description": "Food stores email scraper to extract verified emails from grocery stores, supermarkets, and food retail businesses πŸ“§πŸ›’ Perfect for supplier outreach, partnerships, and food industry lead generation.", "version": "1.0", "x-build-id": "VLeCZy6I6T0PcUcXA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/contacts-api~food-stores-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-contacts-api-food-stores-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~food-stores-email-scraper/runs": { "post": { "operationId": "runs-sync-contacts-api-food-stores-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~food-stores-email-scraper/run-sync": { "post": { "operationId": "run-sync-contacts-api-food-stores-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": "Food Stores" }, "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 } } } } } } } } } } ```