# Amazon Best Sellers Scraper (`jungle_synthesizer/amazon-bestsellers-scraper`) Actor Track Amazon Best Sellers rankings across any category. Collects product name, rank, ASIN, price, rating, review count, and image URL from any bestsellers category page. - **URL**: https://apify.com/jungle\_synthesizer/amazon-bestsellers-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** E-commerce, Lead generation, News - **Stats:** 2 total users, 1 monthly users, 66.7% 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 ## Amazon Best Sellers Scraper Track Amazon Best Sellers rankings across any category. For each product the actor collects rank, ASIN, title, price, rating, review count, image URL, and the category it came from. ### What it does The actor opens any Amazon Best Sellers category page with a real Chromium browser (Playwright) behind a US residential proxy. Amazon serves bestseller data client-side via React — a plain HTTP request returns a bot-wall shell with no product data. The browser renders the full page, extracts all product cards in a single `page.evaluate()` call, and saves the results. Each category shows up to 50 products per page across two pages (`?pg=2`). The actor scrapes both pages and stops as soon as `maxItems` is reached. ### Output fields | Field | Type | Description | |-------|------|-------------| | `rank` | integer | Bestseller rank within the category (1 = #1) | | `asin` | string | Amazon Standard Identification Number | | `title` | string | Product title | | `url` | string | Canonical product page URL | | `imageUrl` | string | Product image URL | | `price` | string | Current price as displayed (e.g. `$24.99`) | | `rating` | number | Average customer rating (0-5) | | `reviewCount` | integer | Number of customer reviews | | `categoryName` | string | Human-readable category name | | `categoryUrl` | string | URL of the category page scraped | | `scrapedAt` | string | ISO-8601 timestamp | ### Input | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `categoryUrl` | string | `https://www.amazon.com/gp/bestsellers/` | Amazon Best Sellers category URL | | `maxItems` | integer | — | Maximum number of products to collect | #### Examples **Top-level bestsellers (all categories):** ```json { "categoryUrl": "https://www.amazon.com/gp/bestsellers/", "maxItems": 50 } ```` **Electronics bestsellers:** ```json { "categoryUrl": "https://www.amazon.com/gp/bestsellers/electronics/", "maxItems": 50 } ``` **Books bestsellers:** ```json { "categoryUrl": "https://www.amazon.com/gp/bestsellers/books/", "maxItems": 50 } ``` You can use any Amazon bestsellers URL — navigate to the category you want on Amazon and paste the URL. ### Technical notes - **Browser:** Playwright (Chromium) — required because Amazon renders bestseller content client-side - **Proxy:** US residential (DataImpulse) — Amazon blocks datacenter IPs - **Memory:** 2 GB recommended; minimum 1 GB - **Rate limiting:** Concurrency is kept low (2 parallel pages) with 1-second delays to reduce detection risk - **Deduplication:** Results are deduplicated by ASIN within a run ### Limitations - Scrapes one category URL per run (v0.1). Run the actor multiple times to collect data across categories. - Amazon shows at most 100 products per category (50 per page x 2 pages). Set `maxItems` accordingly. - Prices, ratings, and rankings change frequently — re-run regularly for fresh data. - Amazon.com (US) only. International domains require a separate configuration. # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `categoryUrl` (type: `string`): Amazon Best Sellers category URL (e.g. https://www.amazon.com/gp/bestsellers/electronics). Defaults to top-level bestsellers. ## `maxItems` (type: `integer`): Maximum number of products to scrape (up to 100 per page; Amazon shows 50 per page) ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "categoryUrl": "https://www.amazon.com/gp/bestsellers/", "maxItems": 10 } ``` # Actor output Schema ## `results` (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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "categoryUrl": "https://www.amazon.com/gp/bestsellers/", "maxItems": 10 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/amazon-bestsellers-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "categoryUrl": "https://www.amazon.com/gp/bestsellers/", "maxItems": 10, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/amazon-bestsellers-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "categoryUrl": "https://www.amazon.com/gp/bestsellers/", "maxItems": 10 }' | apify call jungle_synthesizer/amazon-bestsellers-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/amazon-bestsellers-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon Best Sellers Scraper", "description": "Track Amazon Best Sellers rankings across any category. Collects product name, rank, ASIN, price, rating, review count, and image URL from any bestsellers category page.", "version": "0.1", "x-build-id": "vN9Un3mBRiJTIdSCi" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~amazon-bestsellers-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-amazon-bestsellers-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jungle_synthesizer~amazon-bestsellers-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-amazon-bestsellers-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jungle_synthesizer~amazon-bestsellers-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-amazon-bestsellers-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "maxItems" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "categoryUrl": { "title": "Category URL", "type": "string", "description": "Amazon Best Sellers category URL (e.g. https://www.amazon.com/gp/bestsellers/electronics). Defaults to top-level bestsellers." }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of products to scrape (up to 100 per page; Amazon shows 50 per page)" } } }, "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 } } } } } } } } } } ```