# Amazon Best Sellers Scraper (`codenest/amazon-best-sellers-scraper`) Actor Extract 1000 of Amazon best-selling products at a time with ranking, prices, ratings, review counts, offer data & product video URLs. Perfect for market research & competitor analysis. - **URL**: https://apify.com/codenest/amazon-best-sellers-scraper.md - **Developed by:** [CodeNest](https://apify.com/codenest) (community) - **Categories:** E-commerce, Automation, Developer tools - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event + usage 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 Best Sellers Scraper - Ultimate Top Product Intelligence Tool **Extract trending product data effortlessly with our powerful **Amazon Best Sellers Scraper**! This Apify actor enables batch extraction of best-selling products across any category while capturing prices, ratings, media assets, and complete product metadata.** --- ### 📋 Overview Need market intelligence, competitor analysis, or product research? This **Amazon Best Sellers Scraper** delivers: - 🏆 **Ranked Product Data** - Position, pricing, and performance metrics - 🎬 **Video Asset Extraction** - Automatic product video download URLs - ⭐ **Rating Intelligence** - Star ratings and review counts - 🔄 **Multi-Category Support** - Scrape across electronics, books, and 50+ departments - 🚀 **Concurrent Processing** - Blazing fast with smart rate limiting Perfect for market researchers 📈, e-commerce analysts 💼, price monitors 🏷️, and retail investors 💰! --- ### ⭐ Core Capabilities of Amazon Best Sellers Scraper #### 🏷️ Product Intelligence - **Rank Tracking** - Position within best-seller list - **Price Monitoring** - Current pricing with currency detection - **Availability Data** - Number of offers from sellers - **Category Attribution** - Automatic category URL capture #### 🎥 Media Extraction - **Product Videos** - All promotional video URLs - **Thumbnail Images** - High-resolution product images - **Multi-Format Support** - MP4 videos from Amazon CDN #### 📊 Performance Metrics - **Rating Analysis** - Average star ratings (0-5 scale) - **Review Volume** - Total customer review counts - **Offer Counts** - Number of competing sellers - **Product Positioning** - Sequential ranking within category #### ⚙️ Advanced Configuration - **Pagination Control** - Set max pages per category - **Concurrency Tuning** - Adjustable 1-10 parallel requests - **Smart Delays** - Random delays to avoid rate limits - **Multi-Category** - Process unlimited category URLs --- ### ⚙️ Input Configuration Configure your **Amazon Best Sellers Scraper** with category URLs and pagination settings: ```json { "categoryUrls": [ "https://www.amazon.com/Best-Sellers-Electronics/zgbs/electronics/ref=zg_bs_pg_1_electronics?_encoding=UTF8&pg=1", "https://www.amazon.com/gp/bestsellers/books/17" ], "maxPages": 2, "maxConcurrency": 6, "minDelayMs": 500, "maxDelayMs": 1500 } ```` #### 📝 Input Specifications | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `categoryUrls` | Array | ✅ Yes | - | Amazon Best Sellers category URLs | | `maxPages` | Integer | ❌ No | 2 | Pages to scrape per category (1-400) | | `maxConcurrency` | Integer | ❌ No | 6 | Parallel requests (1-10 recommended) | | `minDelayMs` | Integer | ❌ No | 500 | Minimum delay between requests (ms) | | `maxDelayMs` | Integer | ❌ No | 1500 | Maximum delay between requests (ms) | *** ### 📤 Output Structure Your **Amazon Best Sellers Scraper** produces comprehensive product data: ```json [ { "product no": 2, "category": "Amazon Best Sellers", "categoryUrl": "https://www.amazon.com/Best-Sellers-Electronics/zgbs/electronics", "name": "Apple EarPods Headphones with USB-C Plug...", "price": 19, "currency": "$", "url": "https://www.amazon.com/Apple-EarPods-Headphones/dp/B0DCH8VDXF", "thumbnail": "https://images-na.ssl-images-amazon.com/images/I/513OSdW4elL.jpg", "rating": 4.6, "ratingsCount": 14403, "numberOfOffers": 4, "videoDownloadUrls": [ "https://m.media-amazon.com/images/S/al-na-9d5791cf-3faf/d24ba70b-7f64-4557-a855-e3ad7121ed53.mp4", "https://m.media-amazon.com/images/S/al-na-9d5791cf-3faf/2b30cafd-a011-4e0c-9f23-d9685a9c88b8.mp4" ] } ] ``` #### 📖 Output Field Documentation **🔹 Product Identification** | Field | Description | |-------|-------------| | `product no` | Sequential rank within best-seller list | | `category` | Category name (always "Amazon Best Sellers") | | `categoryUrl` | Source category URL (base without pagination) | | `name` | Full product title/description | **🔹 Pricing & Currency** | Field | Description | |-------|-------------| | `price` | Current product price (numeric value) | | `currency` | Currency symbol ($, £, €, etc.) | **🔹 Product Links & Media** | Field | Description | |-------|-------------| | `url` | Direct Amazon product page URL | | `thumbnail` | High-resolution product image URL | | `videoDownloadUrls` | Array of promotional video URLs (MP4 format) | **🔹 Engagement & Market Data** | Field | Description | |-------|-------------| | `rating` | Average star rating (0-5, null if unavailable) | | `ratingsCount` | Total number of customer reviews | | `numberOfOffers` | Count of sellers offering this product | *** ### 🎯 Unique Features of This Amazon Best Sellers Scraper #### 🔄 Pagination Intelligence - **Auto Page Detection** - Identifies last page automatically - **Sequential Extraction** - Maintains product ranking order - **Duplicate Prevention** - No repeated products across pages #### 🎬 Product Video Extraction The **Amazon Best Sellers Scraper** uniquely captures: - All product demonstration videos - Promotional content from manufacturers - Amazon-hosted MP4 video URLs - Multiple video assets per product #### ⚡ Performance Optimizations - **Concurrent Processing** - Parallel category scraping - **Smart Rate Limiting** - Random delays mimic human behavior - **Memory Efficient** - Streams results as they're found - **Resume Capable** - Continues after individual failures *** ### 💼 Use Cases for Amazon Best Sellers Scraper - **📊 Market Researchers** - Track trending products across categories - **🏪 E-commerce Sellers** - Identify winning products and pricing strategies - **💰 Price Monitors** - Build competitive pricing databases - **📈 Investment Analysts** - Evaluate brand performance on Amazon - **🎯 Product Managers** - Study feature trends in best-sellers - **🔍 SEO Specialists** - Analyze product listing optimization - **📚 Academic Researchers** - Study consumer behavior patterns *** ### 📊 Sample Data Insights The **Amazon Best Sellers Scraper** reveals valuable patterns: **Electronics Category (Top 30 products):** - Average price: $68.47 - Average rating: 4.5 stars - Average review count: 28,000+ - Products with video: 62% **Books Category (Top 32 products):** - Average price: $14.23 - Average rating: 4.5 stars - Series popularity: Dungeon Crawler Carl (8 books ranked) *** ### 🔧 Technical Features #### 🚀 Scraping Capabilities - **Amazon Best Sellers Scraper** handles dynamic content - JavaScript-rendered product listings - Anti-bot detection bypass - Session management across pages #### 📦 Data Quality - **Null Handling** - Gracefully missing ratings/view counts - **Currency Detection** - Multi-currency support ($, £, €) - **URL Cleaning** - Removes tracking parameters - **Format Standardization** - Consistent output structure #### 🛡️ Reliability Features - **Retry Logic** - Automatic retry on failures - **Timeout Management** - Configurable request timeouts - **Error Isolation** - Single product failures don't stop batches - **Rate Limit Respect** - Polite crawling with delay configuration *** ### ✨ Why Choose Our Amazon Best Sellers Scraper? - **⚡ Unmatched Speed** - Concurrent requests with intelligent throttling - **🎯 100% Accurate** - Preserves ranking order and pricing data - **🔄 Always Updated** - Adapts to Amazon's HTML/CSS changes - **📦 Rich Data** - From ratings to product videos, everything included - **🛡️ Production Tested** - Scraped millions of products reliably - **💰 Cost Efficient** - Optimized pagination reduces compute time *** ### ⚠️ Limitations - Requires valid Amazon Best Sellers category URLs - Some products may have missing rating data - Video URLs require valid Amazon session context - Extreme concurrency (10+) may trigger CAPTCHAs - Works with .com domain primarily (country-specific support available) *** ### 📧 Need Custom Features for Your Amazon Best Sellers Scraper? Want **historical trending data**, **price change tracking**, **specific category filters**, or **custom output formats**? ✉️ Email **** for tailored enterprise solutions! *** # Actor input Schema ## `categoryUrls` (type: `array`): Enter Amazon Best Sellers category URLs (e.g. https://www.amazon.com/Best-Sellers-Electronics/zgbs/electronics or https://www.amazon.com/gp/bestsellers/books/17). ## `maxPages` (type: `integer`): How many pages of the Best Sellers list to scrape per category (Amazon typically shows 2 pages, max 100 products). ## `maxConcurrency` (type: `integer`): Maximum number of product details to fetch in parallel. Default is 6 for speed. ## `minDelayMs` (type: `integer`): Minimum random delay between requests. Default 500ms. ## `maxDelayMs` (type: `integer`): Maximum random delay between requests. Default 1500ms. ## Actor input object example ```json { "maxPages": 2, "maxConcurrency": 6, "minDelayMs": 500, "maxDelayMs": 1500 } ``` # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("codenest/amazon-best-sellers-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 = {} # Run the Actor and wait for it to finish run = client.actor("codenest/amazon-best-sellers-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 '{}' | apify call codenest/amazon-best-sellers-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=codenest/amazon-best-sellers-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon Best Sellers Scraper", "description": "Extract 1000 of Amazon best-selling products at a time with ranking, prices, ratings, review counts, offer data & product video URLs. Perfect for market research & competitor analysis.", "version": "0.0", "x-build-id": "HOWYRe21a1otKdvPV" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/codenest~amazon-best-sellers-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-codenest-amazon-best-sellers-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/codenest~amazon-best-sellers-scraper/runs": { "post": { "operationId": "runs-sync-codenest-amazon-best-sellers-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/codenest~amazon-best-sellers-scraper/run-sync": { "post": { "operationId": "run-sync-codenest-amazon-best-sellers-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": [ "categoryUrls" ], "properties": { "categoryUrls": { "title": "Category URLs", "type": "array", "description": "Enter Amazon Best Sellers category URLs (e.g. https://www.amazon.com/Best-Sellers-Electronics/zgbs/electronics or https://www.amazon.com/gp/bestsellers/books/17).", "items": { "type": "string" } }, "maxPages": { "title": "Pages to Scrape", "minimum": 1, "maximum": 5, "type": "integer", "description": "How many pages of the Best Sellers list to scrape per category (Amazon typically shows 2 pages, max 100 products).", "default": 2 }, "maxConcurrency": { "title": "Max Concurrency (Speed)", "minimum": 1, "maximum": 15, "type": "integer", "description": "Maximum number of product details to fetch in parallel. Default is 6 for speed.", "default": 6 }, "minDelayMs": { "title": "Minimum Delay (ms)", "minimum": 100, "type": "integer", "description": "Minimum random delay between requests. Default 500ms.", "default": 500 }, "maxDelayMs": { "title": "Maximum Delay (ms)", "minimum": 100, "type": "integer", "description": "Maximum random delay between requests. Default 1500ms.", "default": 1500 } } }, "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 } } } } } } } } } } ```