# Allegro.pl Product Scraper (`automation-lab/allegro-scraper`) Actor Scrape Allegro.pl product listings: prices, sellers, ratings, images, delivery info, and product parameters. Search by keyword or browse categories. Export to JSON, CSV, or Excel. - **URL**: https://apify.com/automation-lab/allegro-scraper.md - **Developed by:** [Stas Persiianenko](https://apify.com/automation-lab) (community) - **Categories:** E-commerce - **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Allegro.pl Product Scraper Scrape product listings from **[Allegro.pl](https://allegro.pl)** — Poland's #1 e-commerce marketplace with over 125 million active listings. Extract prices, sellers, ratings, images, parameters, and delivery info from any search or category. Export to JSON, CSV, or Excel in minutes. ### What does Allegro.pl Product Scraper do? Allegro.pl Product Scraper lets you **extract product listings at scale** from Poland's largest online marketplace. Just enter keywords or paste category URLs — the scraper handles pagination automatically and returns structured data for every product. - ✅ Search by keyword across all categories - ✅ Browse specific categories (e.g., laptops, shoes, electronics) - ✅ Filter by price range, product condition, and sort order - ✅ Extract complete product data: prices, sellers, images, ratings, shipping costs - ✅ Includes product parameters (brand, specs, dimensions) - ✅ Identifies sponsored vs. organic listings - ✅ No Allegro account or API key required Try it now: open the [Allegro.pl Product Scraper](https://apify.com/automation-lab/allegro-scraper) on Apify Store, enter a search keyword, and click Run. ### Who is Allegro.pl Product Scraper for? #### 📊 E-commerce Analysts & Researchers - Track competitor pricing across thousands of products - Monitor price fluctuations over time with scheduled runs - Research market positioning in specific product categories #### 🛍️ Procurement & Sourcing Teams - Compare supplier prices for bulk purchasing decisions - Find the best deals across millions of listings - Build supplier shortlists based on seller ratings and reviews #### 🤖 Developers & Data Engineers - Build price comparison platforms or shopping apps - Power recommendation engines with real product data - Feed business intelligence dashboards with fresh market data #### 📈 Marketing & SEO Teams - Analyze competitor product titles and descriptions - Track sponsored vs. organic product performance - Research consumer demand signals from sales volume ### Why use this Allegro.pl Scraper? - 🚀 **Fast extraction** — 60-75 products per page in under 30 seconds - 📦 **Rich data** — 20+ fields per product including parameters, images, shipping - 🔄 **Auto-pagination** — crawls as many pages as you need, up to 100 pages per query - 🎯 **Flexible input** — keyword search, category URLs, price filters, condition filter - 💾 **Multiple export formats** — JSON, CSV, Excel, XML via Apify's built-in tools - 🔗 **API-ready** — integrate with Google Sheets, Zapier, Make, and 5,000+ apps - 🛡️ **Resilient** — session rotation and retry logic handles bot detection automatically ### What data can you extract from Allegro.pl? | 🏷️ Product Info | 💰 Pricing | 👤 Seller Info | |---|---|---| | Product ID | Current price (PLN) | Seller login | | Title | Original/sale price | Seller URL | | Category path | Currency | Seller rating (%) | | Condition (new/used) | Delivery price | Super Seller badge | | Product images (up to 10) | Free delivery flag | Location | | Product parameters | | | | 📊 Engagement | 🏭 Logistics | 🔍 Search Context | |---|---|---| | Rating (0-5) | Delivery price | Search query | | Review count | Free delivery | Sponsored flag | | | | Scraped timestamp | ### How much does it cost to scrape Allegro.pl? This Actor uses **pay-per-event (PPE) pricing** — you pay only for products scraped, nothing for failed pages or overhead. | | Free plan | Starter ($29/mo) | Scale ($199/mo) | Business ($999/mo) | |---|---|---|---|---| | **Per product** | $0.00345 | $0.003 | $0.00234 | $0.0018 | | **1,000 products** | $3.45 | $3.00 | $2.34 | $1.80 | | **10,000 products** | $34.50 | $30.00 | $23.40 | $18.00 | Plus a one-time **$0.005 start fee** per run (covers browser startup cost). **Real-world cost examples:** | Query | Products | Duration | Cost (Free tier) | |---|---|---|---| | "laptop" (1 page) | ~74 | ~30s | ~$0.26 | | "iPhone" (3 pages) | ~200 | ~90s | ~$0.69 | | Category browse (5 pages) | ~350 | ~150s | ~$1.21 | 💡 Free plan users get **$5 credit** — enough for ~1,400 products. ### How to scrape Allegro.pl products 1. Open [Allegro.pl Product Scraper](https://apify.com/automation-lab/allegro-scraper) on Apify Store 2. Click **Try for free** 3. In **Search Queries**, enter keywords (e.g., `laptop gaming`, `iPhone 15`) 4. Set **Max Products per Search** (start with 20-50 to test) 5. Optionally filter by price range, condition, or sort order 6. Click **Start** and wait ~30 seconds 7. Download results in JSON, CSV, or Excel from the **Dataset** tab #### Input examples **Keyword search (most common):** ```json { "searchQueries": ["laptop gaming", "tablet samsung"], "maxItemsPerQuery": 100, "sortBy": "relevance" } ```` **Price-filtered search:** ```json { "searchQueries": ["buty sportowe"], "maxItemsPerQuery": 200, "minPrice": 100, "maxPrice": 500, "condition": "new", "sortBy": "price-asc" } ``` **Category URL scraping:** ```json { "startUrls": [ {"url": "https://allegro.pl/kategoria/laptopy-491"}, {"url": "https://allegro.pl/kategoria/smartfony-i-telefony-komorkowe-165"} ], "maxItemsPerQuery": 300 } ``` ### Input parameters | Parameter | Type | Default | Description | |---|---|---|---| | `searchQueries` | string\[] | — | Keywords to search on Allegro.pl | | `startUrls` | URL\[] | — | Direct Allegro listing or category URLs | | `maxItemsPerQuery` | integer | 100 | Max products per query/URL | | `minPrice` | integer | — | Min price filter in PLN | | `maxPrice` | integer | — | Max price filter in PLN | | `condition` | string | `all` | Product condition: `all`, `new`, `used` | | `sortBy` | string | `relevance` | Sort: `relevance`, `price-asc`, `price-desc`, `newest` | ### Output examples Each product is saved as a JSON object: ```json { "id": "17808132516", "url": "https://allegro.pl/oferta/hp-victus-15-gaming-ryzen-7-17808132516", "title": "Laptop HP Victus 15 15,6\" AMD Ryzen 7 16 GB / 512 GB szary", "price": 3551, "priceOriginal": null, "currency": "PLN", "seller": "INFLOO", "sellerUrl": "https://allegro.pl/uzytkownik/INFLOO", "sellerRating": 98.6, "imageUrl": "https://a.allegroimg.com/s720/11a3b1/...", "images": [ "https://a.allegroimg.com/s720/11a3b1/...", "https://a.allegroimg.com/s360/11b9d1/..." ], "condition": "new", "isSponsored": false, "isSuperSeller": true, "reviewCount": 24, "rating": 4.8, "deliveryPrice": 10.49, "deliveryFree": false, "category": "Elektronika > Komputery > Laptopy", "location": "", "parameters": { "Marka": "HP", "System operacyjny": "Windows 11 Home", "Wielkość pamięci RAM": "16 GB", "Pojemność dysku": "512 GB", "Seria procesora": "AMD Ryzen 7", "Przekątna ekranu": "15.6\"" }, "searchQuery": "laptop gaming", "scrapedAt": "2026-04-03T02:41:01.609Z" } ``` ### Tips for best results - 🔢 **Start small** — test with 20-50 products first to verify the data meets your needs - 🌍 **Polish keywords work better** — use Polish terms (e.g., "buty sportowe" instead of "sport shoes") for more relevant results - 📋 **Use category URLs** for comprehensive category coverage (up to 100 pages × 74 items) - ⏱️ **Schedule runs** for price monitoring — Apify's scheduler runs actors automatically - 💰 **Filter by price** to focus on the exact range you care about - 🔄 **Sort by newest** to track new listings in a category - 📊 **Export to Google Sheets** via Apify's built-in integration for team access ### Integrations **Allegro.pl Product Scraper → Google Sheets** Schedule daily runs and append new products to a Google Sheet for team price monitoring. Connect via Apify's Google Sheets integration in the actor settings. **Allegro.pl Product Scraper → Slack/Discord** Set up a webhook to alert your team when prices drop below a threshold. Combine with Make or Zapier to filter and format the notifications. **Allegro.pl Product Scraper → Price Comparison Database** Run the scraper for multiple product categories and store results in Apify Dataset or export to a database. Use the `id` field to track product changes over time. **Allegro.pl Product Scraper → Make/Zapier Automation** Trigger automated workflows from new product listings — email alerts, CRM updates, inventory management. **Scheduled Price Monitoring** Use Apify's scheduler (cron `0 9 * * *`) to run the scraper daily and track price trends over weeks or months. ### Using the Apify API #### Node.js ```javascript import { ApifyClient } from 'apify-client'; const client = new ApifyClient({ token: 'YOUR_API_TOKEN' }); const run = await client.actor('automation-lab/allegro-scraper').call({ searchQueries: ['laptop gaming'], maxItemsPerQuery: 100, sortBy: 'price-asc', }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(`Scraped ${items.length} products`); ``` #### Python ```python from apify_client import ApifyClient client = ApifyClient(token='YOUR_API_TOKEN') run = client.actor('automation-lab/allegro-scraper').call(run_input={ 'searchQueries': ['laptop gaming'], 'maxItemsPerQuery': 100, 'sortBy': 'price-asc', }) dataset = client.dataset(run['defaultDatasetId']) for item in dataset.iterate_items(): print(f"{item['title']}: {item['price']} PLN") ``` #### cURL ```bash curl -X POST "https://api.apify.com/v2/acts/automation-lab~allegro-scraper/runs?token=YOUR_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{ "searchQueries": ["laptop gaming"], "maxItemsPerQuery": 100, "sortBy": "price-asc" }' ``` ### Use with AI agents via MCP Allegro.pl Product Scraper is available as a tool for AI assistants that support the [Model Context Protocol (MCP)](https://docs.apify.com/platform/integrations/mcp). Add the Apify MCP server to your AI client — this gives you access to all Apify actors, including this one: #### Setup for Claude Code ```bash claude mcp add --transport http apify "https://mcp.apify.com?tools=automation-lab/allegro-scraper" ``` #### Setup for Claude Desktop, Cursor, or VS Code Add this to your MCP config file: ```json { "mcpServers": { "apify": { "url": "https://mcp.apify.com?tools=automation-lab/allegro-scraper" } } } ``` Your AI assistant will use OAuth to authenticate with your Apify account on first use. #### Example prompts Once connected, try asking your AI assistant: - "Use automation-lab/allegro-scraper to find the 50 cheapest new iPhone 15 listings on Allegro.pl and give me a price analysis" - "Scrape 200 laptop products from Allegro.pl category for laptops, then identify the top 10 sellers by rating" - "Get Allegro.pl gaming accessories priced between 50-300 PLN and export them to a spreadsheet" Learn more in the [Apify MCP documentation](https://docs.apify.com/platform/integrations/mcp). ### Is it legal to scrape Allegro.pl? Allegro.pl's product listings are publicly accessible to anyone browsing the web without authentication. This scraper only collects publicly visible data — the same information any visitor would see. Web scraping public data is generally permissible under: - The **CJEU Ryanair v. PR Aviation ruling** — public data scraping for legitimate business purposes is generally lawful - **GDPR** — we collect only publicly visible product and seller data, not personal user information - Standard **fair use principles** — data is used for analysis, not reproduction We recommend: - Using the data for legitimate business purposes (price research, market analysis) - Not reproducing entire product listings verbatim without adding value - Respecting Allegro's rate limits (built into the actor automatically) - Reviewing [Allegro's Terms of Service](https://allegro.pl/regulaminy) for your specific use case **This tool is provided for legitimate research and business intelligence use.** Apify's platform complies with ethical scraping standards and proxy rotation to minimize impact on target servers. ### FAQ **How many products can I scrape from Allegro.pl?** Allegro's search returns up to 100 pages × ~74 products = ~7,400 results per query. For comprehensive category coverage, use category URLs with `maxItemsPerQuery` set to 7400 or higher. **How fast is the scraper?** Each page takes approximately 15-30 seconds including browser startup. Rate: ~150-250 products per minute depending on query complexity. **How much does it cost to scrape 10,000 Allegro products?** At Free tier: ~$34.50. At Starter plan: ~$30.00. Higher-tier subscribers get volume discounts. **Why are some products showing without a price?** This typically means the listing has variable pricing (e.g., the price depends on selected variants like size/color). The `price` field shows the main price; check the product URL for full details. **Why is the category field sometimes empty?** Category information is derived from Allegro's internal category mapping. Some broad search queries may not associate products with a specific category path. **Why do I get "Bot detection triggered" errors?** This happens when Allegro's Cloudflare protection blocks the initial request. The actor automatically retries with session rotation — typically 2-3 retries are needed. If this happens frequently, try using fewer concurrent requests (already set to 1) or contact support. **Can I scrape used items only?** Yes! Set `condition` to `"used"` in the input. This applies the `stan=used` filter to Allegro's search. **Why are some URLs redirecting through allegro.pl/events/clicks?** The scraper automatically strips Allegro's tracking redirect wrappers to return clean, direct product URLs. ### Other e-commerce scrapers Check out our other automation-lab scrapers for related platforms: - 🛒 [Amazon Scraper](https://apify.com/automation-lab/amazon-scraper) — products, prices, reviews from Amazon - 🏪 [eBay Scraper](https://apify.com/automation-lab/ebay-scraper) — listings from eBay marketplace - 🎨 [Etsy Scraper](https://apify.com/automation-lab/etsy-scraper) — handmade products from Etsy - 🏬 [Walmart Scraper](https://apify.com/automation-lab/walmart-scraper) — products from Walmart.com - 🛍️ [Best Buy Scraper](https://apify.com/automation-lab/bestbuy-scraper) — electronics from Best Buy # Actor input Schema ## `searchQueries` (type: `array`): Enter keywords to search on Allegro.pl. Each keyword runs a separate search. Example: "laptop gaming", "iPhone 15". ## `startUrls` (type: `array`): Alternatively, paste direct Allegro.pl listing or category URLs. Overrides search queries if provided. ## `maxItemsPerQuery` (type: `integer`): Maximum number of products to extract per search query or URL. Increase for larger datasets. ## `minPrice` (type: `integer`): Filter products: only return items priced at or above this value (in PLN). ## `maxPrice` (type: `integer`): Filter products: only return items priced at or below this value (in PLN). ## `condition` (type: `string`): Filter by product condition. ## `sortBy` (type: `string`): Choose how to sort search results. ## Actor input object example ```json { "searchQueries": [ "laptop gaming" ], "startUrls": [], "maxItemsPerQuery": 20, "condition": "all", "sortBy": "relevance" } ``` # Actor output Schema ## `overview` (type: `string`): No description # 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 = { "searchQueries": [ "laptop gaming" ], "startUrls": [], "maxItemsPerQuery": 20, "condition": "all", "sortBy": "relevance" }; // Run the Actor and wait for it to finish const run = await client.actor("automation-lab/allegro-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 = { "searchQueries": ["laptop gaming"], "startUrls": [], "maxItemsPerQuery": 20, "condition": "all", "sortBy": "relevance", } # Run the Actor and wait for it to finish run = client.actor("automation-lab/allegro-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 '{ "searchQueries": [ "laptop gaming" ], "startUrls": [], "maxItemsPerQuery": 20, "condition": "all", "sortBy": "relevance" }' | apify call automation-lab/allegro-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=automation-lab/allegro-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Allegro.pl Product Scraper", "description": "Scrape Allegro.pl product listings: prices, sellers, ratings, images, delivery info, and product parameters. Search by keyword or browse categories. Export to JSON, CSV, or Excel.", "version": "0.1", "x-build-id": "Cg6aZomCYFXxhRmOA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/automation-lab~allegro-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-automation-lab-allegro-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/automation-lab~allegro-scraper/runs": { "post": { "operationId": "runs-sync-automation-lab-allegro-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/automation-lab~allegro-scraper/run-sync": { "post": { "operationId": "run-sync-automation-lab-allegro-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "searchQueries": { "title": "🔍 Search Queries", "type": "array", "description": "Enter keywords to search on Allegro.pl. Each keyword runs a separate search. Example: \"laptop gaming\", \"iPhone 15\".", "items": { "type": "string" } }, "startUrls": { "title": "📎 Start URLs (optional)", "type": "array", "description": "Alternatively, paste direct Allegro.pl listing or category URLs. Overrides search queries if provided.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "maxItemsPerQuery": { "title": "Max Products per Search", "minimum": 1, "maximum": 10000, "type": "integer", "description": "Maximum number of products to extract per search query or URL. Increase for larger datasets.", "default": 100 }, "minPrice": { "title": "Min Price (PLN)", "minimum": 0, "type": "integer", "description": "Filter products: only return items priced at or above this value (in PLN)." }, "maxPrice": { "title": "Max Price (PLN)", "minimum": 1, "type": "integer", "description": "Filter products: only return items priced at or below this value (in PLN)." }, "condition": { "title": "Condition", "enum": [ "all", "new", "used" ], "type": "string", "description": "Filter by product condition.", "default": "all" }, "sortBy": { "title": "Sort Results By", "enum": [ "relevance", "price-asc", "price-desc", "newest" ], "type": "string", "description": "Choose how to sort search results.", "default": "relevance" } } }, "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 } } } } } } } } } } ```