# Apple App Store | Scrape App Store Search Results & Keywords (`johnvc/apple-app-store-search`) Actor Scrape Apple App Store search results for any keyword. Extract app titles, ratings, developer info, price, screenshots, genres, version, and bundle ID across 155+ country stores. Built for ASO research, app discovery, competitor tracking, and AI agent workflows. Pay only for the apps you receive. - **URL**: https://apify.com/johnvc/apple-app-store-search.md - **Developed by:** [John](https://apify.com/johnvc) (community) - **Categories:** SEO tools, Developer tools, E-commerce - **Stats:** 5 total users, 4 monthly users, 100.0% runs succeeded, 4 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $0.01 / 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 ## Apple App Store Search Scraper > **The fastest way to scrape Apple App Store search results for ASO research, app discovery, and AI agents.** Search any keyword in the App Store and get back rich, structured app data: titles, ratings, developer info, prices, screenshots, genres, versions, and bundle IDs. Works across 50+ country stores and 40+ languages. Built for App Store Optimization (ASO), competitor tracking, market research, and AI agent workflows. This actor is fully **MCP (Model Context Protocol) ready**, with one click setup for Claude Code, Claude Cowork, and Claude.ai Chat. --- ### AI Agent and MCP Integration The fastest path to use this actor is through the Apify MCP server. Once connected, Claude (or any MCP-compatible AI agent) can discover and invoke this actor directly from a natural language prompt. No glue code, no client SDK, no manual REST calls. The Apify MCP server hosts three discovery tools (`search-actors`, `fetch-actor-details`, `add-actor`) that let agents find and register this actor on the fly. Pick the setup that matches your Claude surface. #### Option 1: Claude Code (terminal CLI) The single-command setup. Open your terminal and run: ```bash claude mcp add apify -- npx -y @apify/actors-mcp-server ```` Then add your Apify API token (one time): ```bash claude mcp add apify -e APIFY_TOKEN=your_apify_token_here -- npx -y @apify/actors-mcp-server ``` Get your token at https://console.apify.com/account/integrations. Prefer to edit config by hand? Open `~/.claude.json` and add: ```json { "mcpServers": { "apify": { "command": "npx", "args": ["-y", "@apify/actors-mcp-server"], "env": { "APIFY_TOKEN": "your_apify_token_here" } } } } ``` Restart Claude Code, then try a prompt like: > *Find the top 50 meditation apps in the US App Store with their ratings and prices.* Claude will discover this actor via `search-actors`, register it as a tool, and run it. #### Option 2: Claude Cowork (web) Claude Cowork uses the hosted Apify MCP endpoint over HTTP. No local install required. 1. Open Cowork. 2. Go to **Settings** > **Connectors** > **Add custom connector**. 3. Fill in: - **Name:** `Apify` - **Remote MCP URL:** `https://mcp.apify.com` - **Authentication:** Bearer token (paste your Apify API token). 4. Save and enable the connector. Once connected, the Apify tools appear in the tool drawer. Try a prompt: > *Use Apify to scrape Apple App Store search results for "budget tracker" in the UK store and tell me which apps have the most ratings.* Cowork supports dynamic tool discovery, so once Claude finds this actor in a session, it stays registered as a named tool for the rest of the conversation. Subsequent prompts reuse it without re-discovery. #### Option 3: Claude.ai Chat (Connectors) Same hosted MCP endpoint, configured through the standard Claude.ai UI. 1. Open https://claude.ai. 2. Click your profile, then **Settings** > **Connectors** > **Add custom connector**. 3. Fill in: - **Name:** `Apify` - **Remote MCP URL:** `https://mcp.apify.com` - **Authentication:** Bearer token (your Apify API token). 4. Save. Toggle the connector on at the start of any chat where you want App Store data. Then prompt as normal: > *Search the App Store for "language learning" apps using Apify. Show me ratings and developers.* #### Option 4: ChatGPT, n8n, Zapier, custom GPTs (direct REST) Skip MCP entirely with a single REST call. Useful for custom GPTs, Zapier flows, n8n pipelines, or any HTTP client. ```bash curl -X POST \ "https://api.apify.com/v2/acts/YOUR_USERNAME~apple-app-store-search/runs?token=YOUR_APIFY_TOKEN" \ -H "Content-Type: application/json" \ -d '{"term": "meditation", "country": "us", "num": 50}' ``` For ChatGPT custom GPT Actions, import the [Apify OpenAPI spec](https://docs.apify.com/api/v2) as a custom action. Once added, ChatGPT can call this actor as a function from any custom GPT. [Full Apify MCP documentation](https://docs.apify.com/platform/integrations/mcp) *** ### The Apple App Store API Family This actor is the **search** link in a three-API family, all keyed on the same `app_id`: | API | Purpose | Input | Output | | --- | ------- | ----- | ------ | | **Apple App Store Search API (this actor)** | Find apps by keyword. | Search term + country | Many apps (search results). | | Apple App Store Product API | Get full details for one app: description, version history, screenshots, IAPs, privacy cards, sample reviews. | One or more App Store IDs + country | One full product record per ID. | | Apple App Store Reviews API (coming soon) | Get paginated reviews for one app. | App Store ID + country + sort | Many reviews per app. | ``` Search API ──► app_id ──► Product API ──► full product details └──► Reviews API ──► paginated reviews ``` Agents typically chain them: search here for candidates, pick the IDs they care about, then fan out to the Product API and the Reviews API. Each API is pay-per-record across the family, so you only pay for what you actually fetch. *** ### What You Can Extract | Field | Description | | ----- | ----------- | | App title | Official name shown on the App Store | | App ID and bundle ID | Stable identifiers for cross-referencing | | Developer info | Name, developer ID, and link to the developer page | | Ratings | Average rating (0 to 5) and total rating count | | Price | Type (Free, Paid, Free Trial), amount, currency, and symbol | | Description and release notes | Full app description and latest version notes | | Screenshots | URLs and sizes for iPhone, iPad, Mac, and other device classes | | Logos | Multiple resolutions (60x60, 100x100, 512x512) | | Genres | Primary and secondary App Store categories with IDs | | Version info | Current version, release date, and latest version release date | | Compatibility | Minimum OS version, supported devices, and supported languages | | Age rating and advisories | Content rating plus any content warnings | | Search context | The originating query, country store, language, and ranking position | Every dataset item is one app, flat and ready for analysis. Each row also carries the search query and country code, so multi-keyword runs stay self-contained. *** ### Use Cases - **App Store Optimization (ASO):** Track keyword rankings, monitor competitor apps, and benchmark category leaders. - **App discovery and market research:** Identify trending apps in any country store or category. - **Competitor tracking:** Watch a rival developer's portfolio, version history, and ratings over time. - **Pricing and price-tier analysis:** Compare paid vs free vs freemium distribution in a category. - **AI agent context:** Feed real App Store data into LLM prompts for grounded answers about iOS apps. - **Trend monitoring:** Detect new entrants and rapid risers in specific genres. - **Multi-country comparison:** Run the same query across US, UK, JP, DE, and BR to compare regional app catalogs. *** ### Input Parameters | Parameter | Type | Required | Default | Description | | --------- | ---- | -------- | ------- | ----------- | | `term` | string | yes | (none) | Search query, e.g. `coffee`, `fitness tracker`, `meditation`. | | `country` | string | no | `us` | Two-letter country code (ISO 3166-1 alpha-2, lowercase). 50+ stores supported. | | `lang` | string | no | `en-us` | Language code in `xx-yy` form (e.g. `en-us`, `fr-fr`, `ja-jp`). | | `num` | integer | no | `10` | Apps per page, 1 to 200. Default 10 keeps first runs cheap; raise to scan more apps per page. | | `device` | string | no | `desktop` | Device class to emulate: `desktop`, `tablet`, or `mobile`. | | `disallow_explicit` | boolean | no | `false` | Set true to filter out apps flagged as explicit. | | `property` | string | no | `""` | `""` for app-name search (default) or `developer` to search developer names. | | `category_id` | integer | no | (none) | Filter by App Store category ID. Examples: 6014 Games, 6017 Education, 6005 Social Networking, 6013 Health and Fitness. | | `max_pages` | integer | no | `1` | Maximum pages to fetch. Set to 0 for unlimited. | | `output_file` | string | no | auto | Optional local JSON filename. Useful for local testing only. | *** ### Example Inputs #### Basic search ```json { "term": "coffee", "max_pages": 1 } ``` #### Localized search (UK store, English) ```json { "term": "budget tracker", "country": "gb", "lang": "en-gb", "num": 50, "max_pages": 1 } ``` #### Filtered by category (Games only, family safe) ```json { "term": "puzzle", "country": "us", "category_id": 6014, "disallow_explicit": true, "num": 100, "max_pages": 2 } ``` #### Developer portfolio search ```json { "term": "King", "property": "developer", "country": "us", "max_pages": 1 } ``` #### International store (Japan) ```json { "term": "manga", "country": "jp", "lang": "ja-jp", "num": 100, "max_pages": 1 } ``` *** ### Example Output Each dataset item is one app: ```json { "position": 1, "app_id": 1429637763, "title": "Calm", "bundle_id": "com.calm.app", "developer_name": "Calm.com, Inc.", "developer_id": 469307675, "developer_link": "https://apps.apple.com/us/developer/calm-com-inc/id469307675", "version": "8.21", "age_rating": "4+", "release_date": "2015-08-27T07:00:00Z", "latest_version_release_date": "2026-04-30T10:14:21Z", "price_type": "Free", "price_amount": null, "price_currency": "USD", "price_symbol": "$", "rating_average": 4.8, "rating_count": 1814237, "genres": [ {"name": "Health & Fitness", "id": 6013, "primary": true}, {"name": "Lifestyle", "id": 6012, "primary": false} ], "size_in_bytes": 312456789, "minimum_os_version": "15.0", "description_text": "Calm is the #1 app for sleep, meditation, and relaxation...", "release_notes": "We update Calm every two weeks with new content and improvements.", "screenshots": [ {"link": "https://...screen1.png", "size": "1284x2778", "device": "iphone"}, {"link": "https://...screen2.png", "size": "1284x2778", "device": "iphone"}, {"link": "https://...ipad1.png", "size": "2048x2732", "device": "ipad"} ], "logos": [ {"size": "60x60", "link": "https://...60x60.png"}, {"size": "512x512", "link": "https://...512x512.png"} ], "supported_languages": ["en-US", "es-MX", "fr-FR", "de-DE", "ja-JP", "ko-KR"], "supported_devices": ["iPhone5s-iPhone5s", "iPadAir-iPadAir", "..."], "features": ["iosUniversal"], "advisories": [], "link": "https://apps.apple.com/us/app/calm/id1429637763", "game_center_enabled": false, "search_term": "meditation", "search_country": "us", "search_lang": "en-us", "search_page": 1, "search_position_global": 1, "search_timestamp": "2026-05-11T10:30:00" } ``` *** ### Pricing Transparent pay-per-event pricing. You only pay for what you get. | Event | Cost | When charged | | ----- | ---- | ------------ | | `setup` | `$0.02` | Once at the start of each run. | | `result` | `$0.0015` | Per app returned in the dataset. | #### Cost estimates | Use case | Apps returned | Approx. cost | | -------- | ------------- | ------------ | | Quick keyword check (1 page, 10 apps) | 10 | `$0.035` | | Standard keyword scan (1 page, 200 apps) | 200 | `$0.32` | | Deep keyword crawl (5 pages, 200 each) | 1,000 | `$1.52` | | Bulk ASO sweep (50 keywords, 200 apps each) | 10,000 | `$15.02` (one run per keyword) | No monthly subscription. No hidden fees. Stop the run at any time and pay only for what was already returned. *** ### How to Get Started 1. **Create an Apify account** at https://apify.com if you do not have one. 2. **Open the actor page** in the Apify store and click **Try for free**. 3. **Set the input** (only `term` is required) and click **Start**. 4. **Watch the run live** in the Apify console, then download results as JSON, CSV, Excel, or RSS once it finishes. 5. Optional: connect via MCP (see top of this README) to call the actor directly from Claude or any AI agent. *** ### FAQ **Q: Why am I getting 0 apps?** A: Check that the `term` is spelled correctly and matches keywords actual users would type. Try removing filters like `category_id` or `disallow_explicit`. If `country` is unusual, also confirm that store has apps matching the query. **Q: How many apps does one page return?** A: Up to 200. Set `num` to control this. The actor charges per app actually returned, not per page, so picking a high `num` is the most efficient way to scan a keyword. **Q: Can I get full app details or reviews with this actor?** A: Not directly. This actor focuses on search and discovery. For full per-app details (description, version history, screenshots, in-app purchases, privacy cards, sample reviews) use the companion **Apple App Store Product API**. For paginated reviews, use the dedicated **Apple App Store Reviews API** (coming soon). All three actors share the same App Store `app_id`, so you can chain them: search this actor for candidates, then fan out to the Product API and Reviews API for the IDs you care about. **Q: Can I search by developer name instead of app name?** A: Yes. Set `property` to `developer` and put the developer name in `term`. **Q: Which country stores are supported?** A: 50+ stores including US, UK, CA, AU, DE, FR, JP, KR, BR, MX, IN, and more. See the `country` parameter dropdown for the full list. **Q: Does this work with AI agents and MCP?** A: Yes. Setup instructions for Claude Code, Claude Cowork, and Claude.ai Chat are at the top of this README. *** Last Updated: 2026.05.11 # Actor input Schema ## `term` (type: `string`): Search query for the App Store (e.g. 'coffee', 'fitness tracker', 'meditation'). Required. ## `country` (type: `string`): Two-letter country code (ISO 3166-1 alpha-2, lowercase) selecting which App Store region to search. Defaults to 'us'. ## `lang` (type: `string`): Language code in the form 'xx-yy' (e.g. 'en-us', 'fr-fr', 'ja-jp'). Defaults to 'en-us'. ## `num` (type: `integer`): Number of app results to request per page. Range 1 to 200. Default 10 keeps the first run cheap. Raise it to scan more apps per page (each app returned is charged separately). ## `device` (type: `string`): Browser device class to emulate when requesting search results. Defaults to 'desktop'. ## `disallow_explicit` (type: `boolean`): Set true to exclude apps flagged as explicit. Default false. ## `property` (type: `string`): Scope the search. Leave empty (default) to search app names. Use 'developer' to search developer names instead. ## `category_id` (type: `integer`): Filter results by App Store category (genre) ID. Examples: 6014 Games, 6017 Education, 6005 Social Networking, 6007 Productivity, 6013 Health & Fitness. Leave blank for no category filter. ## `max_pages` (type: `integer`): Maximum number of pages to fetch. Set to 0 for unlimited (fetch all available pages). Default 1. Each page returns up to 'num' apps. ## `output_file` (type: `string`): Optional filename to save a local JSON copy of the raw search results. Used for local testing only. Auto-generated if blank. ## Actor input object example ```json { "term": "coffee", "country": "us", "lang": "en-us", "num": 10, "device": "desktop", "disallow_explicit": false, "property": "", "max_pages": 1 } ``` # Actor output Schema ## `results` (type: `string`): Complete list of apps returned by the search. Each dataset item contains app metadata: title, developer, ratings, price, screenshots, version, bundle ID, supported devices, plus the originating search query and country. # 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 = { "term": "coffee" }; // Run the Actor and wait for it to finish const run = await client.actor("johnvc/apple-app-store-search").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 = { "term": "coffee" } # Run the Actor and wait for it to finish run = client.actor("johnvc/apple-app-store-search").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 '{ "term": "coffee" }' | apify call johnvc/apple-app-store-search --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=johnvc/apple-app-store-search", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Apple App Store | Scrape App Store Search Results & Keywords", "description": "Scrape Apple App Store search results for any keyword. Extract app titles, ratings, developer info, price, screenshots, genres, version, and bundle ID across 155+ country stores. Built for ASO research, app discovery, competitor tracking, and AI agent workflows. Pay only for the apps you receive.", "version": "0.1", "x-build-id": "vhmjK69IK7A0fZOyY" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/johnvc~apple-app-store-search/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-johnvc-apple-app-store-search", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/johnvc~apple-app-store-search/runs": { "post": { "operationId": "runs-sync-johnvc-apple-app-store-search", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/johnvc~apple-app-store-search/run-sync": { "post": { "operationId": "run-sync-johnvc-apple-app-store-search", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "required": [ "term" ], "properties": { "term": { "title": "Search Term", "minLength": 1, "type": "string", "description": "Search query for the App Store (e.g. 'coffee', 'fitness tracker', 'meditation'). Required." }, "country": { "title": "Country Store", "enum": [ "us", "gb", "ca", "au", "nz", "ie", "in", "sg", "ph", "my", "de", "fr", "es", "it", "nl", "be", "at", "ch", "se", "no", "dk", "fi", "pt", "pl", "cz", "gr", "hu", "ro", "tr", "ru", "ua", "il", "ae", "sa", "eg", "za", "ng", "ke", "jp", "kr", "cn", "tw", "hk", "th", "id", "vn", "br", "mx", "ar", "cl", "co", "pe" ], "type": "string", "description": "Two-letter country code (ISO 3166-1 alpha-2, lowercase) selecting which App Store region to search. Defaults to 'us'.", "default": "us" }, "lang": { "title": "Language", "enum": [ "en-us", "en-gb", "en-au", "en-ca", "en-ie", "en-nz", "en-in", "en-sg", "fr-fr", "fr-ca", "fr-ch", "fr-be", "de-de", "de-at", "de-ch", "es-es", "es-mx", "es-ar", "es-cl", "es-co", "it-it", "pt-pt", "pt-br", "nl-nl", "nl-be", "ja-jp", "ko-kr", "zh-cn", "zh-tw", "zh-hk", "ru-ru", "uk-ua", "pl-pl", "tr-tr", "ar-sa", "he-il", "sv-se", "no-no", "da-dk", "fi-fi", "el-gr", "th-th", "vi-vn", "id-id", "ms-my" ], "type": "string", "description": "Language code in the form 'xx-yy' (e.g. 'en-us', 'fr-fr', 'ja-jp'). Defaults to 'en-us'.", "default": "en-us" }, "num": { "title": "Results Per Page", "minimum": 1, "maximum": 200, "type": "integer", "description": "Number of app results to request per page. Range 1 to 200. Default 10 keeps the first run cheap. Raise it to scan more apps per page (each app returned is charged separately).", "default": 10 }, "device": { "title": "Device Class", "enum": [ "desktop", "tablet", "mobile" ], "type": "string", "description": "Browser device class to emulate when requesting search results. Defaults to 'desktop'.", "default": "desktop" }, "disallow_explicit": { "title": "Filter Explicit Apps", "type": "boolean", "description": "Set true to exclude apps flagged as explicit. Default false.", "default": false }, "property": { "title": "Search Scope", "enum": [ "", "developer" ], "type": "string", "description": "Scope the search. Leave empty (default) to search app names. Use 'developer' to search developer names instead.", "default": "" }, "category_id": { "title": "Category ID", "minimum": 0, "type": "integer", "description": "Filter results by App Store category (genre) ID. Examples: 6014 Games, 6017 Education, 6005 Social Networking, 6007 Productivity, 6013 Health & Fitness. Leave blank for no category filter." }, "max_pages": { "title": "Maximum Pages", "minimum": 0, "maximum": 100, "type": "integer", "description": "Maximum number of pages to fetch. Set to 0 for unlimited (fetch all available pages). Default 1. Each page returns up to 'num' apps.", "default": 1 }, "output_file": { "title": "Local Output File", "type": "string", "description": "Optional filename to save a local JSON copy of the raw search results. Used for local testing only. Auto-generated if blank." } } }, "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 } } } } } } } } } } ```