# Best Amazon Email Scraper (`scraper-mind/best-amazon-email-scraper`) Actor \[๐—•๐Ÿฎ๐—• ๐—˜๐— ๐—”๐—œ๐—Ÿ ๐—”๐—ฉ๐—”๐—œ๐—Ÿ๐—”๐—•๐—Ÿ๐—˜] Extract Amazon leads fast with this powerful Amazon Email Scraper ๐Ÿ”๐Ÿ“ง. Extract verified B2B/B2C emails, domains, and contact insights by keyword and country. Perfect for outreach, eCommerce, and growth teams. Generate targeted Amazon emails in seconds. - **URL**: https://apify.com/scraper-mind/best-amazon-email-scraper.md - **Developed by:** [Scraper Mind](https://apify.com/scraper-mind) (community) - **Categories:** Lead generation, Social media - **Stats:** 39 total users, 2 monthly users, 100.0% runs succeeded, 2 bookmarks - **User rating**: No ratings yet ## Pricing $19.99/month + usage To use this Actor, you pay a monthly rental fee to the developer. The rent is subtracted from your prepaid usage every month after the free trial period.You also pay for the Apify platform usage, which gets cheaper the higher Apify subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#rental-actors ## 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 ### Amazon Email Scraper โ€” Scrape Leads from Amazon using the Lead Generation Tool ๐Ÿš€ An **Amazon Email Scraper** is a powerful tool designed to extract **Amazon emails**, contact details, and lead information from product pages, Q&A sections, reviews, and brand interactions. With this scraper, you can quickly collect **B2B and B2C Amazon leads** from any regional Amazon marketplace โ€” perfect for sales teams, eCommerce brands, and marketers targeting niche audiences. By automating the process of finding **Amazon lead data**, you skip hours of manual research and instantly uncover real, verified contact points. This boosts **SEO**, **outreach efficiency**, and **audience targeting** by helping you gather high-intent leads based on keywords like *โ€œjuicer,โ€ โ€œfitness,โ€ โ€œprinter,โ€* and more. If youโ€™re looking to scale your Amazon prospecting with accuracy, speed, and cost efficiency, this **Amazon contact scraper** is the ideal solution. ๐Ÿš€ --- ### ๐Ÿ“ฆ What data can the **Amazon Email Scraper** extract? Below is a breakdown of the key information you can extract when searching for Amazon leads using this tool: | Data Type ๐Ÿ“Š | Description | | ----------------------- | ----------------------------------------------------------------------- | | **Email Address** | Extract B2C or B2B Amazon emails from Q&A pages, reviews & public text. | | **Email Domain** | Identify whether the lead uses Gmail, company domain, etc. | | **Lead Type** | Categorized as **B2B** or **B2C** depending on your selection. | | **Title / Page Name** | Title of the Amazon page where the email was found. | | **Description Snippet** | The sentence or text section containing the email. | | **Keyword Matched** | The keyword used for the Amazon search (e.g., *juicer*). | | **Source URL** | Direct link to the Amazon page containing the lead. | | **Country** | Country you selected (e.g., United States, UK). | This structured data makes it incredibly easy to build segmented lead lists, enrich CRM datasets, and fuel marketing campaigns with real customer contact points. --- ### ๐Ÿ”ง Input Parameters #### ๐Ÿ“Œ Example Input (JSON) ```json { "keywords": ["juicer"], "maxEmails": 20, "country": "United States", "scrapeFrom": "Amazon US", "emailType": "B2C", "engine": "cost-effective" } ```` #### ๐Ÿ“‹ Input Parameter Table | Field | Description | | -------------- | ------------------------------------------------ | | **keywords** | List of keywords to search for on Amazon. | | **country** | Target region for search results. | | **scrapeFrom** | Amazon marketplace to extract data from. | | **emailType** | Choose between **B2C** or **B2B** emails. | | **engine** | Select cost-effective or legacy scraping engine. | | **maxEmails** | Maximum number of emails to collect. | *** ### ๐Ÿ“ค Output Format #### ๐Ÿ“Œ Example Output (JSON) ```json [ { "keyword": "juicer", "title": "Amazon.com: Customer Questions & Answers", "url": "https://www.amazon.com/ask/questions/Tx10RKZLFZ50Q3A/%3F", "description": "Hello Laura, please send your shipping address to our company email...", "email": "juicepressousa@gmail.com", "email_domain": "gmail.com", "email_type": "B2C" } ] ``` #### ๐Ÿ“‹ Output Field Table | Field | Description | | ---------------- | -------------------------------------- | | **keyword** | Keyword that produced the result. | | **title** | Page title where the email was found. | | **url** | Amazon source URL. | | **description** | Text snippet containing the email. | | **email** | Extracted email address. | | **email\_domain** | Domain of the email address. | | **email\_type** | B2B or B2C classification. | | **scrape\_from** | Marketplace scraped (e.g., Amazon US). | | **country** | Country targeted. | *** #### ๐Ÿ”‘ Key Features of the **Amazon Email Scraper** - โšก **Smart Keyword Targeting** โ€” Add any keyword (e.g., *juicer, fitness, skincare*) to find highly relevant Amazon emails. - ๐ŸŒ **Multi-country Support** โ€” Extract Amazon leads from the US, UK, India, Canada, Germany, France, and dozens more. - ๐Ÿ›’ **Amazon Marketplace Selector** โ€” Scrape from Amazon US, Amazon India, Amazon UK, and more. - ๐ŸŽฏ **B2B or B2C Email Targeting** โ€” Choose exactly the type of email you need. - ๐Ÿš€ **Cost-Effective Engine** โ€” Uses lightweight, fast, and affordable scraping mode to reduce cost while increasing speed. - ๐Ÿ—๏ธ **Legacy Engine Option** โ€” More traditional and highly reliable scraping mode for deep search tasks. - ๐Ÿ“ง **Max Email Limit Control** โ€” Gather anywhere from 1 to 10,000 emails depending on your needs. - ๐Ÿ“Ž **Direct Dataset Export** โ€” Easily download your results in JSON, CSV, or Excel. - ๐Ÿ” **Real-time Amazon Data Discovery** โ€” Extract live emails from Amazon Q\&A, brand replies, product descriptions, and more. - ๐Ÿ”„ **Automated Crawling** โ€” The scraper handles everything start to finishโ€”no manual navigation required. This makes the tool perfect for generating **Amazon lead lists**, **market insights**, or **B2C outreach campaigns**. *** ### ๐Ÿ› ๏ธ How to use the **Amazon Email Scraper** Follow this simple step-by-step guide to extract Amazon emails effortlessly: 1. **Log in to Apify** Create a free account or sign in to your existing one. 2. **Select the Actor** Search for **โ€œAmazon Email Scraperโ€** in the Apify Store and open the actor page. 3. **Enter Input Data** Paste your keyword(s) into the `keywords` field. Example: `"juicer"`, `"fitness"`, `"hair dryer"` 4. **Choose Options** - Select **Country:** e.g., *United States* - Select **Scrape From:** e.g., *Amazon US* - Pick **Email Type:** *B2C* or *B2B* - Choose **Engine:** cost-effective or legacy 5. **Run the Actor** Click **Start** โ€” the scraper automatically crawls relevant Amazon pages and extracts emails. 6. **Download Results** Export as **CSV, JSON, XLSX**, or connect the dataset directly to your CRM or Google Sheets. This workflow ensures you gather high-quality **Amazon leads** quickly and efficiently. *** ### ๐ŸŽฏ Use Cases The **Amazon Email Scraper** unlocks powerful real-world applications, including: - **E-commerce lead generation** โ€” Find customers already engaged with products related to your niche. - **Brand outreach campaigns** โ€” Reach out to consumers asking questions or engaging with Amazon listings. - **Influencer & seller discovery** โ€” Identify individuals who leave emails in Amazon Q\&A or review sections. - **Market research** โ€” Analyze consumer interests based on queries and communication patterns. - **Competitor lead harvesting** โ€” Gather contact details from competing brands or related product categories. - **Email list building** โ€” Create segmented lists for remarketing and personalized campaigns. - **Product development insights** โ€” Understand pain points from Q\&A emails and feedback messages. If you run ads, build funnels, or conduct outreach, this scraper becomes a high-value lead generator. ๐Ÿ’ฐโœจ *** ### ๐Ÿ’Ž Why choose us? - ๐Ÿ”ฅ **High-speed crawling** powered by optimized async requests. - ๐Ÿ’ฐ **Cost-effective scraping** for large-scale email extraction. - ๐ŸŒ **Global Amazon support** with dozens of marketplace regions. - ๐Ÿค **Reliable & accurate** results with optimized selectors and logic behind the scenes. - ๐Ÿง  **Smart search capabilities** that match keywords with the most relevant Amazon content. - ๐Ÿ“ฆ **Clean JSON output** ready for automation and integration. - ๐Ÿ›ก๏ธ **Safe & controlled scraping** โ€” limits and filters ensure stable performance. - ๐Ÿ’ฌ **Dedicated support** via . Choosing this scraper means choosing precision, reliability, and scale for your **Amazon lead generation strategy**. *** ### ๐Ÿš€ How many results can you scrape with the **Amazon Email Scraper**? The scraper is built for **scalability** and can extract anywhere from a few emails to **thousands** depending on your configuration. You can set `maxEmails` anywhere between **1 and 10,000**, giving you full control over output size. Key factors influencing the number of emails you can collect: - **Keyword breadth** โ€” Broad keywords (e.g., *fitness*) produce more results than narrow ones (e.g., *ceramic lemon juicer*). - **Marketplace size** โ€” Amazon US, India, and Germany have the largest data pools. - **Email Type** โ€” B2C emails are more common; B2B may yield fewer but higher-value addresses. - **Regions selected** โ€” Scraping from additional Amazon sites expands possible lead counts. - **Search depth** โ€” Larger keyword lists lead to more page coverage and more extracted emails. With the **cost-effective engine**, you can scrape larger volumes faster and at lower cost. The **legacy engine** trades speed for reliability in complex markets. Whether you need 20 emails or 5,000+, the scraper is built to scale. *** ### โš–๏ธ Is it legal to scrape **Amazon Email** data? Scraping publicly available data is generally legal when done ethically and responsibly. The **Amazon Email Scraper** only extracts information already visible to the public, such as emails shared in Amazon Q\&A or review text. However, users should keep in mind: - Always respect **Amazonโ€™s terms of use**. - Do not collect sensitive personal data. - Use scraped emails responsibly and comply with **GDPR**, **CAN-SPAM**, and other email regulations. - Only use data for legitimate business or research purposes. This scraper is designed for ethical, compliant, and transparent data gathering. *** ## Related Scrapers Check out these other scrapers that make it easy to collect emails, phone numbers, and content from popular platforms. - [Best LinkedIn Email Scraper](https://console.apify.com/actors/UO6op1saiCrlaeMEK/) - [Best Instagram Email Scraper](https://console.apify.com/actors/4bYhKqb1HakSE4nbL/) - [Best TikTok Email Scraper](https://console.apify.com/actors/HeNp9ZCxCBlPmmunu/) - [Best YouTube Email Scraper](https://console.apify.com/actors/q17EHOm8wTqQAAMyN/) - [Best Crunchbase Email Scraper](https://console.apify.com/actors/U7Ym7iG6ShP8wVbNY/) - [Best Twitter Email Scraper](https://console.apify.com/actors/vnKPDUudjE4wjv4Ad/) - [Best Etsy Email Scraper](https://console.apify.com/actors/YZv6xVnTSvYtzBhau/) - [Best Zillow Email Scraper](https://console.apify.com/actors/vS5OGfUhguSVcm2L2/) - [Best Facebook Email Scraper](https://console.apify.com/actors/xt9dRXomhQkoDhQGp/) ### โ“ FAQ **1. Can this Amazon Email Scraper extract both B2B and B2C emails?** Yes! You can choose the email type before running the scraper. **2. Does it work on all Amazon marketplaces?** It supports major regions including the US, UK, India, Germany, Canada, and more. **3. How many Amazon emails can I scrape per run?** Anywhere from 1 to 10,000 depending on keyword volume and settings. **4. Is the tool beginner-friendly?** Absolutely โ€” just enter your keywords, choose a country, and run. **5. What types of Amazon leads can I extract?** Consumers, product owners, reviewers, and anyone who publicly posts an email. **6. Can I export results to CSV or Excel?** Yes โ€” export options include JSON, CSV, and XLSX. **7. Is this scraper safe to use?** Yes โ€” it extracts only publicly visible data and offers compliance-friendly output. *** If youโ€™d like any edits, enhancements, or additional SEO optimization, just let me know! ๐Ÿš€ # Actor input Schema ## `keywords` (type: `array`): Enter one or more keywords to search for on Amazon. ## `country` (type: `string`): Specify the country to target for Google search results. ## `scrapeFrom` (type: `string`): Choose which regional Amazon site to scrape. ## `emailType` (type: `string`): Choose one โ€” B2C or B2B. ## `engine` (type: `string`): Choose scraping engine. ๐Ÿš€ Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. ๐Ÿ”ง Legacy: Uses GOOGLE\_SERP proxy with traditional selectors - more reliable but slower and more expensive. ## `maxEmails` (type: `integer`): Enter the maximum number of emails to collect. ## Actor input object example ```json { "keywords": [ "fitness", "gym", "workout" ], "country": "United States", "scrapeFrom": "Amazon US", "emailType": "B2C", "engine": "legacy", "maxEmails": 20 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "keywords": [ "fitness", "gym", "workout" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scraper-mind/best-amazon-email-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keywords": [ "fitness", "gym", "workout", ] } # Run the Actor and wait for it to finish run = client.actor("scraper-mind/best-amazon-email-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "fitness", "gym", "workout" ] }' | apify call scraper-mind/best-amazon-email-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraper-mind/best-amazon-email-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Best Amazon Email Scraper", "description": "[๐—•๐Ÿฎ๐—• ๐—˜๐— ๐—”๐—œ๐—Ÿ ๐—”๐—ฉ๐—”๐—œ๐—Ÿ๐—”๐—•๐—Ÿ๐—˜] Extract Amazon leads fast with this powerful Amazon Email Scraper ๐Ÿ”๐Ÿ“ง. Extract verified B2B/B2C emails, domains, and contact insights by keyword and country. Perfect for outreach, eCommerce, and growth teams. Generate targeted Amazon emails in seconds.", "version": "1.0", "x-build-id": "UJn8HkBhmn1osbHN0" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraper-mind~best-amazon-email-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraper-mind-best-amazon-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraper-mind~best-amazon-email-scraper/runs": { "post": { "operationId": "runs-sync-scraper-mind-best-amazon-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraper-mind~best-amazon-email-scraper/run-sync": { "post": { "operationId": "run-sync-scraper-mind-best-amazon-email-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "keywords", "country", "scrapeFrom", "emailType", "maxEmails" ], "properties": { "keywords": { "title": "Keywords", "type": "array", "description": "Enter one or more keywords to search for on Amazon.", "items": { "type": "string" } }, "country": { "title": "Country", "enum": [ "United States", "United Kingdom", "Canada", "Australia", "Germany", "France", "India", "Japan", "Brazil", "Italy", "Spain", "Netherlands", "Sweden", "Norway", "Denmark", "Finland", "Poland", "Czech Republic", "Hungary", "Romania", "Bulgaria", "Croatia", "Slovenia", "Slovakia", "Estonia", "Latvia", "Lithuania", "Portugal", "Greece", "Cyprus", "Malta", "Luxembourg", "Ireland", "Belgium", "Austria", "Switzerland", "Liechtenstein", "Iceland", "South Korea", "China", "Mexico", "Argentina", "Chile", "Colombia", "Peru", "Venezuela", "Ecuador", "Uruguay", "Paraguay", "Bolivia", "Guyana", "Suriname", "French Guiana", "Falkland Islands (Malvinas)", "South Georgia and the South Sandwich Islands", "Bonaire, Sint Eustatius and Saba", "Curaรงao", "Aruba", "Sint Maarten (Dutch part)", "Turks and Caicos Islands", "British Virgin Islands", "Anguilla", "Montserrat", "Antigua and Barbuda", "Barbados", "Dominica", "Grenada", "Saint Kitts and Nevis", "Saint Lucia", "Saint Vincent and the Grenadines", "Trinidad and Tobago", "Jamaica", "Bahamas", "Belize", "Costa Rica", "Guatemala", "Honduras", "Nicaragua", "Panama", "El Salvador", "Cuba", "Dominican Republic", "Haiti", "Puerto Rico", "U.S. Virgin Islands", "American Samoa", "Guam", "Northern Mariana Islands", "Saudi Arabia", "United Arab Emirates", "Bahrain", "Iraq", "Iran, Islamic Republic of", "Israel", "Jordan", "Kuwait", "Lebanon", "Oman", "Qatar", "Syrian Arab Republic", "Yemen", "Afghanistan", "Bangladesh", "Bhutan", "Maldives", "Nepal", "Pakistan", "Sri Lanka", "Myanmar", "Cambodia", "Lao People's Democratic Republic", "Thailand", "Viet Nam", "Malaysia", "Singapore", "Brunei Darussalam", "Philippines", "Indonesia", "Timor-Leste", "Papua New Guinea", "Fiji", "New Zealand", "Solomon Islands", "Vanuatu", "New Caledonia", "French Polynesia", "Wallis and Futuna", "Samoa", "Tonga", "Tuvalu", "Kiribati", "Nauru", "Federated States of Micronesia", "Marshall Islands", "Palau", "Cook Islands", "Niue", "Tokelau" ], "type": "string", "description": "Specify the country to target for Google search results.", "default": "United States" }, "scrapeFrom": { "title": "Scrape From", "enum": [ "Amazon US", "Amazon India", "Amazon Germany", "Amazon UK", "Amazon Japan", "Amazon Canada", "Amazon France", "Amazon Italy", "Amazon Spain", "Amazon Brazil", "Amazon Australia", "Amazon Mexico", "Amazon UAE", "Amazon Saudi Arabia", "Amazon Netherlands" ], "type": "string", "description": "Choose which regional Amazon site to scrape.", "default": "Amazon US" }, "emailType": { "title": "Email Type", "enum": [ "B2C", "B2B" ], "type": "string", "description": "Choose one โ€” B2C or B2B.", "default": "B2C" }, "engine": { "title": "Engine", "enum": [ "cost-effective", "legacy" ], "type": "string", "description": "Choose scraping engine. ๐Ÿš€ Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. ๐Ÿ”ง Legacy: Uses GOOGLE_SERP proxy with traditional selectors - more reliable but slower and more expensive.", "default": "legacy" }, "maxEmails": { "title": "Max Emails", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Enter the maximum number of emails to collect.", "default": 20 } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```