# Amazon Phone Number Scraper (`scraperoka/amazon-phone-number-scraper`) Actor 📞 Amazon Phone Number Scraper extracts phone numbers from Amazon listings fast and accurately. 🚀 Perfect for B2B lead gen, sales outreach & market research. Save time, boost response rates, and reach prospects efficiently. 🔍 - **URL**: https://apify.com/scraperoka/amazon-phone-number-scraper.md - **Developed by:** [Scraperoka](https://apify.com/scraperoka) (community) - **Categories:** Lead generation, E-commerce, Automation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.01 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ### Amazon Phone Number Scraper 🎯 Manually collecting phone numbers from Amazon bios, profiles, and posts is slow and hard to scale. **Amazon Phone Number Scraper** automates extraction of Amazon contact numbers using your keywords and a country dial code—ideal for marketers, recruiters, and growth teams. This Amazon phone number scraper is built for bulk lead generation phone number extraction and faster outreach list building, with the ability to collect up to thousands of candidates in a single run. --- ### What You Get: Sample Output Here's a sample record from a single run: ```json { "platform": "Amazon", "keyword": "marketing", "title": "Marketing Services", "description": "We help brands grow. WhatsApp us at +49 151 1234567.", "url": "https://www.amazon.com/some-profile-page", "phone_number": "+491511234567", "country": "Germany", "dial_code": "+49", "proxyGroups": [ "legacy" ] } ```` > Note: The actor writes results to the dataset as soon as each phone number is found (using `Actor.push_data` with `charged_event_name="result"`). **Output Fields** | Field | Type | What It Tells You | |---|---|---| | `platform` | string | Confirms the source platform for each record (`Amazon`). | | `keyword` | string | The keyword that led to this match, useful for auditing and filtering. | | `title` | string | The extracted result title (helpful context for lead review). | | `description` | string | The surrounding publicly available text where the phone number was detected. | | `url` | string | The URL where the phone number was found. | | `phone_number` | string | The normalized phone number in E.164 format (deduplicated). | | `country` | string | The selected country name used for targeting. | | `dial_code` | string | The selected country dial code used for targeting. | | `proxyGroups` | array | Indicates the proxy configuration used for the run (useful for troubleshooting and reproducibility). | Export your dataset as JSON, CSV, or Excel — straight from the Apify dashboard. *** ### Why Amazon Phone Number Scraper? There are a lot of ways to pull data from Amazon — here’s what sets **Amazon Phone Number Scraper** apart. #### Keyword-driven Amazon contact discovery You provide a list of `keywords`, and the scraper searches for phone numbers tied to Amazon bios, profiles, and posts related to those keywords. This makes the Amazon customer service phone number scraper workflow more targeted for your niche leads. #### Country dial code filtering for better relevance You choose a `country`, and the scraper uses the corresponding phone-number region rules so you don’t end up with irrelevant international numbers. This is especially useful for extracting Amazon seller contact details scraper leads by market. #### Deduplicated, integration-ready phone number output The actor deduplicates by phone number (it tracks `seen_numbers`) and outputs consistent records with fields like `phone_number`, `url`, and `description`. That means the Amazon phone number list scraper output is ready for enrichment and CRM import. #### Resilient scraping with retries and fallbacks When pages don’t return results as expected, the actor includes retry and fallback behavior to improve the chance of completing a run. This helps keep automated Amazon phone number scraping more dependable for larger batches. *** ### Configuring Your Run Drop this into your `input.json` to get started: ```json { "keywords": ["marketing", "founder"], "platform": "Amazon", "country": "United Kingdom (+44)", "maxPhoneNumbers": 20, "engine": "legacy", "proxyConfiguration": {} } ``` | Parameter | Required | What It Does | |---|---:|---| | `keywords` | ✅ | A list of keywords to search for (for example, “marketing”, “founder”, or a specific name). | | `platform` | ⬜ | Select platform. The only available option is `Amazon`. | | `country` | ✅ | Select a country to scrape related phone numbers from (also determines the target dial code). | | `maxPhoneNumbers` | ⬜ | Maximum number of phone numbers to collect. The scraper stops once this limit is reached to control runtime and cost. | | `engine` | ⬜ | Choose scraping engine: `cost-effective` (Cost Effective (New)) or `legacy` (Legacy). | | `proxyConfiguration` | ⬜ | Configure proxies for this Actor (advanced setup for improved reliability). | *** ### Core Capabilities #### Amazon phone number extraction from public profile text **Amazon Phone Number Scraper** finds phone numbers from Amazon bios, profiles, and posts related to your `keywords`. It’s designed for Amazon contact info scraper use cases where you want phone numbers plus the context needed to verify them. #### E.164 normalized phone numbers for clean lists Phone numbers are normalized to the E.164 format and stored in `phone_number`, which makes your Amazon business phone number extractor output consistent and easier to merge across systems. #### Stop-after-limit control for predictable runs Use `maxPhoneNumbers` to control how many phone numbers the scraper collects. This makes it practical for everything from quick tests to dedicated Amazon phone numbers extraction software runs. #### Built-in resilience for larger keyword sets The actor uses retries and fallbacks when results are missing or scraping is blocked, helping it complete more of your requested work. This supports automated Amazon phone number scraping workflows where you don’t want manual babysitting. #### Dataset-first results as they’re found Results are pushed to the Apify dataset as they’re discovered. That way, you can start exporting or processing immediately rather than waiting for everything to finish. *** ### Who Gets the Most Out of This Here’s how different teams put **Amazon Phone Number Scraper** to work: **Lead generation and outbound marketing teams** use it to quickly build an Amazon directory phone number scraper list for outreach. By pairing `keywords` with a specific `country` dial code, they can focus on the markets that matter most to their campaigns. **Sales development representatives** put the extracted `phone_number` plus the `url` and `description` into their workflow for faster prospecting and verification. This reduces the time spent searching manually and helps them scale Amazon seller contact scraper efforts. **Recruiters and talent sourcers** use it to find business contacts from Amazon bios and profile posts matching role-related keywords. The result is a cleaner list of phone numbers they can match to candidate organizations. **Data analysts and researchers** use the structured dataset to analyze contact coverage by keyword and country. The consistent fields (like `keyword`, `country`, `dial_code`, and `phone_number`) make it easier to filter, deduplicate, and join with existing datasets. **Automation and integration specialists** use the actor output to feed CRM enrichment pipelines. Because results land in the Apify dataset immediately, it’s straightforward to connect the scraper into scheduled jobs and downstream processing. *** ### Step-by-Step: How to Use It No coding needed. Here's how to run Amazon Phone Number Scraper from start to finish: 1. **Open the actor on Apify** — go to [console.apify.com](https://console.apify.com) and find **Amazon Phone Number Scraper**. 2. **Enter your inputs** — set `keywords` and `country` at minimum, and optionally tune `maxPhoneNumbers`, `engine`, and `proxyConfiguration`. 3. **Configure proxy settings (optional)** — if you want more reliability for larger runs, configure `proxyConfiguration` in Run Options. 4. **Hit Run and watch the live log** — track progress as results are discovered. 5. **View results in the dataset tab** — phone numbers appear as they’re pushed to the dataset. 6. **Export your data** — download as JSON, CSV, or Excel from the Apify dashboard. The whole process takes under 5 minutes to set up. *** ### Integrations & Export Options Once your data is collected, **Amazon Phone Number Scraper** plugs directly into your existing workflow. You can download your results in common formats like JSON, CSV, or Excel straight from the Apify dataset tab. This works well for Amazon phone number data scraper projects where you want an immediate export for spreadsheets and BI tools. For automation and orchestration, you can use Apify’s API to pull results programmatically, and connect downstream systems using webhooks. Many teams also use no-code automation tools (like Zapier or Make) to route leads directly into CRMs, lead routers, and enrichment steps—check Apify docs for setup details: https://apify.com/docs/api. *** ### Pricing & Free Trial Amazon Phone Number Scraper runs on the Apify platform, which offers a **free tier** — no credit card required to get started. You can run smaller tests using the free allowance and scale when your use case is proven. For exact pricing, refer to Apify’s pricing page and plan details on https://apify.com. Since results are pushed with `charged_event_name="result"`, your cost is tied to the run’s actual produced results under Apify’s standard billing model. Start for free at [apify.com](https://apify.com) and scale when you’re ready. *** ### Reliability & Performance | What We Handle | How | |---|---| | Rate-limiting and blocks | Includes retries and fallbacks, improving completion for larger keyword runs. | | Proxy reliability | Supports proxy configuration for more dependable scraping runs. | | Output consistency | Deduplicates phone numbers and outputs structured fields suitable for analysis and CRM import. | | Runtime control | Uses `maxPhoneNumbers` to cap results and stop once the target is reached. | | Large searches | Offers an engine selection and allows you to adjust runtime-related settings via Run Options. | **Limitations:** The actor collects phone numbers from publicly available sources on Amazon bios, profiles, and posts. It cannot access login-gated or private content, and results depend on what phone numbers are actually present in those public texts. For enterprise-scale runs, contact us to discuss custom configurations. *** ### Frequently Asked Questions #### Is there a free plan or trial? Yes. Apify provides a free tier you can use to test **Amazon Phone Number Scraper**. For current free-tier credit amounts and eligibility, check the pricing details on Apify. #### Do I need to log in to Amazon to use this? No. This actor is designed to work with publicly available data from Amazon profiles and related pages, so a login is not required. #### How accurate is the data? The scraper extracts phone numbers that appear in publicly available Amazon profile text and normalizes them to E.164 in `phone_number`. Accuracy therefore depends on what phone numbers are actually present in the source text. #### How many results can I get per run? You control that with `maxPhoneNumbers`. The actor stops once it reaches the specified limit, so you can plan quick tests or larger collection runs. #### How often is the data updated / how fresh is it? Data freshness depends on when you run the actor. Each run collects phone numbers from the public pages at the time of scraping, so the output reflects that moment’s available content. #### Is this legal? Does it comply with GDPR / CCPA? The actor only accesses **publicly available data** visible without login. You are responsible for complying with GDPR, CCPA, and any applicable laws and platform Terms of Service when you store and use the data. #### Can I export results to Google Sheets or Excel? Yes. You can export your Apify dataset results as JSON, CSV, or Excel. From there, it’s straightforward to load into Google Sheets or other spreadsheet tools. #### Can I run this on a schedule automatically? Yes. You can schedule Apify runs and automate lead collection workflows via Apify’s scheduling features. This is helpful if you want ongoing Amazon lead generation phone number scraper updates. #### Can I access this via API? Yes. You can access Apify runs and datasets programmatically via the Apify API. See https://apify.com/docs/api for details. #### What happens if the actor hits an error? The actor includes resilience behavior (retries and fallbacks) and pushes results as they’re found. If a run doesn’t complete as expected, you can still use the dataset records produced up to that point. *** ### Need Help or Have a Request? Got a question about **Amazon Phone Number Scraper** or want a new feature added? Reach out at . We welcome requests and help you get the most from your Amazon seller contact details scraper workflow—especially for custom lead-generation needs like webhook notifications and batch-friendly setups. *** ### Disclaimer & Responsible Use *Amazon Phone Number Scraper is the fastest, most reliable way to extract phone numbers from Amazon public profiles—start your free run today.* By using this actor, you agree that it accesses **publicly available data** and does not access private accounts, login-gated content, or password-protected pages. You are responsible for complying with GDPR, CCPA, applicable laws, and platform Terms of Service. For data removal requests, contact . Use responsibly, ethically, and only for lawful purposes. # Actor input Schema ## `keywords` (type: `array`): A list of keywords to search for. (Example: John, marketing, etc.) ## `platform` (type: `string`): Select platform. ## `country` (type: `string`): Select a country to scrape related phone numbers. ## `maxPhoneNumbers` (type: `integer`): Maximum number of phone numbers to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time. ## `engine` (type: `string`): Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE\_SERP proxy with traditional selectors - more reliable but slower and more expensive. ## `proxyConfiguration` (type: `object`): Configure proxies for this Actor. ## Actor input object example ```json { "keywords": [ "marketing", "founder" ], "platform": "Amazon", "country": "United Kingdom (+44)", "maxPhoneNumbers": 20, "engine": "legacy" } ``` # 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": [ "marketing", "founder" ] }; // Run the Actor and wait for it to finish const run = await client.actor("scraperoka/amazon-phone-number-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = { "keywords": [ "marketing", "founder", ] } # Run the Actor and wait for it to finish run = client.actor("scraperoka/amazon-phone-number-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "keywords": [ "marketing", "founder" ] }' | apify call scraperoka/amazon-phone-number-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scraperoka/amazon-phone-number-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon Phone Number Scraper", "description": "📞 Amazon Phone Number Scraper extracts phone numbers from Amazon listings fast and accurately. 🚀 Perfect for B2B lead gen, sales outreach & market research. Save time, boost response rates, and reach prospects efficiently. 🔍", "version": "0.1", "x-build-id": "0PEtdl5e9GhXtzmOW" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scraperoka~amazon-phone-number-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scraperoka-amazon-phone-number-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/scraperoka~amazon-phone-number-scraper/runs": { "post": { "operationId": "runs-sync-scraperoka-amazon-phone-number-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/scraperoka~amazon-phone-number-scraper/run-sync": { "post": { "operationId": "run-sync-scraperoka-amazon-phone-number-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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" ], "properties": { "keywords": { "title": "Keywords", "type": "array", "description": "A list of keywords to search for. (Example: John, marketing, etc.)", "default": [ "marketing", "founder" ], "items": { "type": "string" } }, "platform": { "title": "Platform", "enum": [ "Amazon" ], "type": "string", "description": "Select platform.", "default": "Amazon" }, "country": { "title": "Country", "enum": [ "Afghanistan (+93)", "Albania (+355)", "Algeria (+213)", "Andorra (+376)", "Angola (+244)", "Antigua And Barbuda (+1-268)", "Argentina (+54)", "Armenia (+374)", "Australia (+61)", "Austria (+43)", "Azerbaijan (+994)", "Bahamas (+1-242)", "Bahrain (+973)", "Bangladesh (+880)", "Barbados (+1-246)", "Belarus (+375)", "Belgium (+32)", "Belize (+501)", "Benin (+229)", "Bhutan (+975)", "Bolivia (+591)", "Bosnia And Herzegovina (+387)", "Botswana (+267)", "Brazil (+55)", "Brunei (+673)", "Bulgaria (+359)", "Burkina Faso (+226)", "Burundi (+257)", "Cambodia (+855)", "Cameroon (+237)", "Canada (+1)", "Cape Verde (+238)", "Central African Republic (+236)", "Chad (+235)", "Chile (+56)", "China (+86)", "Colombia (+57)", "Comoros (+269)", "Congo (Democratic Republic) (+243)", "Congo (Republic) (+242)", "Costa Rica (+506)", "Croatia (+385)", "Cuba (+53)", "Cyprus (+357)", "Czech Republic (+420)", "Denmark (+45)", "Djibouti (+253)", "Dominica (+1-767)", "Dominican Republic (+1-809)", "East Timor (+670)", "Ecuador (+593)", "Egypt (+20)", "El Salvador (+503)", "Equatorial Guinea (+240)", "Eritrea (+291)", "Estonia (+372)", "Eswatini (+268)", "Ethiopia (+251)", "Fiji (+679)", "Finland (+358)", "France (+33)", "Gabon (+241)", "Gambia (+220)", "Georgia (+995)", "Germany (+49)", "Ghana (+233)", "Greece (+30)", "Grenada (+1-473)", "Guatemala (+502)", "Guinea (+224)", "Guinea-Bissau (+245)", "Guyana (+592)", "Haiti (+509)", "Honduras (+504)", "Hungary (+36)", "Iceland (+354)", "India (+91)", "Indonesia (+62)", "Iran (+98)", "Iraq (+964)", "Ireland (+353)", "Israel (+972)", "Italy (+39)", "Jamaica (+1-876)", "Japan (+81)", "Jordan (+962)", "Kazakhstan (+7)", "Kenya (+254)", "Kiribati (+686)", "Korea, North (+850)", "Korea, South (+82)", "Kuwait (+965)", "Kyrgyzstan (+996)", "Laos (+856)", "Latvia (+371)", "Lebanon (+961)", "Lesotho (+266)", "Liberia (+231)", "Libya (+218)", "Liechtenstein (+423)", "Lithuania (+370)", "Luxembourg (+352)", "Madagascar (+261)", "Malawi (+265)", "Malaysia (+60)", "Maldives (+960)", "Mali (+223)", "Malta (+356)", "Marshall Islands (+692)", "Mauritania (+222)", "Mauritius (+230)", "Mexico (+52)", "Micronesia (+691)", "Moldova (+373)", "Monaco (+377)", "Mongolia (+976)", "Montenegro (+382)", "Morocco (+212)", "Mozambique (+258)", "Myanmar (+95)", "Namibia (+264)", "Nauru (+674)", "Nepal (+977)", "Netherlands (+31)", "New Zealand (+64)", "Nicaragua (+505)", "Niger (+227)", "Nigeria (+234)", "North Macedonia (+389)", "Norway (+47)", "Oman (+968)", "Pakistan (+92)", "Palau (+680)", "Panama (+507)", "Papua New Guinea (+675)", "Paraguay (+595)", "Peru (+51)", "Philippines (+63)", "Poland (+48)", "Portugal (+351)", "Qatar (+974)", "Romania (+40)", "Russia (+7)", "Rwanda (+250)", "Saint Kitts And Nevis (+1-869)", "Saint Lucia (+1-758)", "Saint Vincent And The Grenadines (+1-784)", "Samoa (+685)", "San Marino (+378)", "Sao Tome And Principe (+239)", "Saudi Arabia (+966)", "Senegal (+221)", "Serbia (+381)", "Seychelles (+248)", "Sierra Leone (+232)", "Singapore (+65)", "Slovakia (+421)", "Slovenia (+386)", "Solomon Islands (+677)", "Somalia (+252)", "South Africa (+27)", "South Sudan (+211)", "Spain (+34)", "Sri Lanka (+94)", "Sudan (+249)", "Suriname (+597)", "Sweden (+46)", "Switzerland (+41)", "Syria (+963)", "Taiwan (+886)", "Tajikistan (+992)", "Tanzania (+255)", "Thailand (+66)", "Togo (+228)", "Tonga (+676)", "Trinidad And Tobago (+1-868)", "Tunisia (+216)", "Turkey (+90)", "Turkmenistan (+993)", "Tuvalu (+688)", "Uganda (+256)", "Ukraine (+380)", "United Arab Emirates (+971)", "United Kingdom (+44)", "United States (+1)", "Uruguay (+598)", "Uzbekistan (+998)", "Vanuatu (+678)", "Vatican City (+39-06)", "Venezuela (+58)", "Vietnam (+84)", "Yemen (+967)", "Zambia (+260)", "Zimbabwe (+263)" ], "type": "string", "description": "Select a country to scrape related phone numbers.", "default": "United Kingdom (+44)" }, "maxPhoneNumbers": { "title": "Max Phone Numbers", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of phone numbers to collect. The scraper will stop once this limit is reached. Setting a higher limit allows for more potential results but doesn't guarantee reaching that number. This helps save costs by controlling scraping time.", "default": 20 }, "engine": { "title": "Engine", "enum": [ "cost-effective", "legacy" ], "type": "string", "description": "Choose scraping engine. 🚀 Cost Effective (New): Uses residential proxies with async requests for faster, cheaper scraping. 🔧 Legacy: Uses GOOGLE_SERP proxy with traditional selectors - more reliable but slower and more expensive.", "default": "legacy" }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Configure proxies for this Actor." } } }, "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 } } } } } } } } } } ```