# Amazon Deals Scraper (`codenest/amazon-deals-scraper`) Actor Extract over 100 of Amazon deals at once with ASIN, title, current price, original price, discount percentage, direct link, and product image. Filter by category or just insert the link and get your results. Get rocket speed and save usage cost. - **URL**: https://apify.com/codenest/amazon-deals-scraper.md - **Developed by:** [CodeNest](https://apify.com/codenest) (community) - **Categories:** E-commerce, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 scraped amazon deals 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 Deals Scraper - Smart Deal & Discount Tracker **Discover the hottest Amazon deals with our powerful **Amazon Deals Scraper**! This Apify actor extracts discounted products with original prices, savings percentages, and ASIN identifiers across any category.** --- ### 📋 Overview Need to track price drops, find bargain products, or monitor Amazon discounts? This **Amazon Deals Scraper** delivers: - 💰 **Instant Savings Detection** - See original vs discounted prices - 🎯 **Category Filtering** - Target books, electronics, fashion, and more - 📊 **Discount Percentages** - Sort by biggest deals instantly - 🔗 **Direct Product Links** - Click straight to purchase - 🖼️ **Product Images** - Visual confirmation of deals Perfect for deal hunters 🏷️, affiliate marketers 💹, price comparison sites 🔍, and bargain bloggers ✍️! --- ### ⭐ Core Capabilities of Amazon Deals Scraper #### 💵 Deal Intelligence - **Price Extraction** - Current selling price with precision - **Original Price Capture** - List price before discount - **Savings Calculation** - Automatic discount percentage - **Category Classification** - ABIS_BOOK, ABIS_EBOOKS, PAJAMAS, BLANK_BOOK #### 🏷️ Product Data Mastery - **ASIN Codes** - Amazon Standard Identification Numbers - **Product Titles** - Full descriptive names - **Direct URLs** - Clean Amazon product links - **High-Res Images** - Product thumbnail URLs #### 🔧 Advanced Features - **Category Targeting** - Focus on specific departments - **Bulk Extraction** - Thousands of deals per run - **Real-Time Data** - Current Amazon pricing - **Structured Output** - JSON-ready deal feed --- ### ⚙️ Input Configuration Simply select your target category and let the **Amazon Deals Scraper** work: ```json { "categories": [ "fashion" ], "links": [ "https://www.amazon.com/gp/goldbox?ref_=nav_cs_gb&bubble-id=Lowest%2520Price%2520in%2520365%2520Days", "https://www.amazon.com/gp/goldbox?ref_=nav_cs_gb&bubble-id=toys-games" ] } ```` #### 📝 Input Specifications | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `categories` | Array | ✅ Yes | - | Product categories to scrape (books, electronics, etc.) | **Supported Categories:** books, electronics, fashion, home, toys, beauty, sports, automotive, grocery, and more! *** ### 📤 Output Structure **Amazon Deals Scraper** produces comprehensive deal data: ```json [ { "asin": "0544445783", "title": "The Hobbit And The Lord Of The Rings: Deluxe Pocket Boxed Set", "link": "https://www.amazon.com/Hobbit-Lord-Rings-Deluxe-Pocket/dp/0544445783", "price": "24.92", "original_price": "75.0", "discount": "67% off", "image_url": "https://m.media-amazon.com/images/I/61f5qt8LhhL.jpg", "category": "ABIS_BOOK" } ] ``` #### 📖 Output Field Documentation **🔹 Product Identification** | Field | Description | |-------|-------------| | `asin` | Amazon's unique product identifier (10-characters) | | `title` | Complete product title/description | | `link` | Direct Amazon product purchase URL | | `image_url` | High-resolution product image | **🔹 Pricing Intelligence** | Field | Description | |-------|-------------| | `price` | Current discounted selling price (USD) | | `original_price` | List price before discount | | `discount` | Savings percentage or amount (e.g., "67% off") | **🔹 Classification** | Field | Description | |-------|-------------| | `category` | Amazon department code (ABIS\_BOOK, ABIS\_EBOOKS, etc.) | *** ### 💰 Deal Types Available The **Amazon Deals Scraper** automatically detects multiple discount patterns: #### Savings Categories: 1. **Deep Discounts (60%+ off)** - Clearance and flash sales 2. **Standard Deals (30-60% off)** - Regular promotions 3. **Light Savings (1-30% off)** - Minor price reductions 4. **Ebook Specials** - Digital books under $5 5. **Box Set Bundles** - Multi-item collections at savings #### Example Savings Found: | Product Type | Original | Deal Price | Savings | |--------------|----------|------------|---------| | Ebooks | $30.00 | $3.99 | 87% off | | Boxed Sets | $195.00 | $82.56 | 58% off | | Children's Books | $23.96 | $8.32 | 65% off | | Workbooks | $13.99 | $5.64 | 60% off | *** ### 🔧 Technical Features of This Amazon Deals Scraper #### 🚀 Performance Optimization - **Fast Category Navigation** - Direct department access - **Efficient Pagination** - Auto-scroll through deal listings - **Memory Optimized** - Handles thousands of products - **Rate Limit Respectful** - Avoids Amazon restrictions #### 🎯 Smart Detection - **Price Format Parsing** - Handles $, USD, and numeric formats - **Discount Calculation** - Automatic savings percentage - **Category Mapping** - Raw to readable category names - **ASIN Validation** - Ensures unique identifiers #### 📊 Complete Deal Extraction - **Real-Time Pricing** - Current Amazon discounts - **Historical Context** - Original vs deal prices - **Product Visuals** - Images for verification - **Direct Purchase Links** - One-click shopping *** ### 💡 Use Cases for Amazon Deals Scraper - **🏷️ Deal Hunters** - Never miss a bargain on favorite products - **📈 Affiliate Marketers** - Build deal websites with fresh discounts - **🛒 Price Comparison Sites** - Track Amazon against competitors - **✍️ Bargain Bloggers** - Create "Today's Best Deals" content - **📊 Market Researchers** - Analyze discount patterns by category - **🎁 Gift Shoppers** - Find presents within budget - **💼 Resellers** - Source inventory at discount prices *** ### ✨ Why Choose Our Amazon Deals Scraper? - **⚡ Lightning Fast** - Extracts 100+ deals per minute - **🎯 Precision Data** - Accurate prices, ASINs, and discounts - **🔄 Real-Time Updates** - Current Amazon pricing always - **📦 Complete Coverage** - All categories supported - **🛡️ Production Tested** - Thousands of successful scrapes - **💰 Maximize Savings** - Find the best discounts automatically *** ### ⚠️ Limitations - Requires valid Amazon category selection - Some products may not show original prices - Discounts change frequently (real-time data) - Geographic pricing may vary by region - Affiliate links need separate processing *** ### 📧 Need Custom Features for Your Amazon Deals Scraper? Want **specific category filters**, **price threshold alerts**, **email notifications**, or **custom discount calculations**? ✉️ Email **** for tailored enterprise deal scraping! *** *The **Amazon Deals Scraper** helps you find savings of 20-90% off across thousands of products. Start saving money today with automated deal discovery!* # Actor input Schema ## `categories` (type: `array`): Enter categories to filter by (e.g., electronics, beauty, fashion). If empty, all deals will be scraped. ## `links` (type: `array`): Enter specific Amazon Deals links to scrape. You can run the actor using categories, links, or both. ## Actor input object example ```json { "categories": [], "links": [] } ``` # 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-deals-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-deals-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-deals-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=codenest/amazon-deals-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon Deals Scraper", "description": "Extract over 100 of Amazon deals at once with ASIN, title, current price, original price, discount percentage, direct link, and product image. Filter by category or just insert the link and get your results. Get rocket speed and save usage cost.", "version": "0.0", "x-build-id": "NDIPaIN3TwSIswuAv" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/codenest~amazon-deals-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-codenest-amazon-deals-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/codenest~amazon-deals-scraper/runs": { "post": { "operationId": "runs-sync-codenest-amazon-deals-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/codenest~amazon-deals-scraper/run-sync": { "post": { "operationId": "run-sync-codenest-amazon-deals-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "categories": { "title": "Categories", "type": "array", "description": "Enter categories to filter by (e.g., electronics, beauty, fashion). If empty, all deals will be scraped.", "items": { "type": "string" }, "default": [] }, "links": { "title": "Deal Links", "type": "array", "description": "Enter specific Amazon Deals links to scrape. You can run the actor using categories, links, or both.", "items": { "type": "string" }, "default": [] } } }, "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 } } } } } } } } } } ```