# Amazon Prouct Reviews (`happitap/amazon-prouct-reviews`) Actor \[UPDATED] Extract product reviews from Amazon including reviewer names, ratings, review text, customer photos, dates, and votes. āœ… Scrapes all reviews text, ratings, and dates šŸ“ø Extracts photos (both thumbnail and full-size URLs) šŸŽÆ Extracts helpful votes count āœ“ Identifies verified purchases - **URL**: https://apify.com/happitap/amazon-prouct-reviews.md - **Developed by:** [HappiTap](https://apify.com/happitap) (community) - **Categories:** E-commerce, Automation, Other - **Stats:** 77 total users, 2 monthly users, 100.0% runs succeeded, 1 bookmarks - **User rating**: 1.80 out of 5 stars ## Pricing from $1.00 / 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 ## Amazon Reviews Scraper Extract product reviews from Amazon including reviewer names, ratings, review text, customer photos, dates, and helpful votes. ### Features - āœ… Scrapes all review data including text, ratings, and dates - šŸ“ø Extracts customer photos (both thumbnail and full-size URLs) - šŸ”„ Automatic pagination through all review pages - āš” Rate limiting to respect Amazon's servers - šŸŖ Cookie support for logged-in sessions - šŸŽÆ Extracts helpful votes count - āœ“ Identifies verified purchases ### Input The Actor accepts the following input: - **Product Review URL** (required): Amazon product reviews URL (e.g., `https://www.amazon.com/product-reviews/B07S2DX7J9/`) - **Maximum Reviews**: Limit the number of reviews to scrape (default: 100, leave empty for unlimited) - **Max Requests Per Minute**: Rate limiting setting (default: 10) - **Proxy Configuration**: Proxy settings (Apify Proxy recommended) ### Output Each review is stored as a separate item in the dataset with the following fields: ```json { "reviewerName": "John Doe", "rating": "5.0", "reviewTitle": "Great product!", "reviewText": "This product exceeded my expectations...", "reviewDate": "Reviewed in the United States on January 15, 2024", "isVerified": true, "reviewImages": [ { "thumbnail": "https://m.media-amazon.com/images/I/71xM1a0eZCL._SY88.jpg", "large": "https://m.media-amazon.com/images/I/71xM1a0eZCL._SL1600_.jpg" } ], "helpfulVotes": "5 people found this helpful", "sourceUrl": "https://www.amazon.com/product-reviews/B07S2DX7J9/" } ```` ### Usage #### On Apify Platform 1. Go to the Actor's page 2. Click "Try for free" 3. Enter the Amazon product reviews URL 4. Configure optional settings 5. Click "Start" 6. Download results in JSON, CSV, or Excel format #### Via API ```javascript const { ApifyClient } = require('apify-client'); const client = new ApifyClient({ token: 'YOUR_API_TOKEN', }); const run = await client.actor('YOUR_USERNAME/amazon-reviews-scraper').call({ productUrl: 'https://www.amazon.com/product-reviews/B07S2DX7J9/', maxReviews: 100, }); const { items } = await client.dataset(run.defaultDatasetId).listItems(); console.log(items); ``` ### Tips - Use Apify Proxy to avoid getting blocked - Set appropriate rate limits to be respectful to Amazon's servers - For large scraping jobs, consider using residential proxies - The scraper automatically handles pagination ### Support For issues or questions, please contact support or open an issue on GitHub. # Actor input Schema ## `productUrl` (type: `string`): Amazon product reviews URL (e.g., https://www.amazon.com/product-reviews/PRODUCT\_ID/) ## `maxReviews` (type: `integer`): Maximum number of reviews to scrape. Leave empty for unlimited. ## `maxRequestsPerMinute` (type: `integer`): Rate limiting: maximum requests per minute ## `proxyConfiguration` (type: `object`): Proxy settings for the scraper ## Actor input object example ```json { "productUrl": "https://www.amazon.com/product-reviews/B07S2DX7J9/", "maxReviews": 100, "maxRequestsPerMinute": 10, "proxyConfiguration": { "useApifyProxy": true } } ``` # Actor output Schema ## `reviews` (type: `string`): All scraped reviews with complete details # 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 = { "productUrl": "https://www.amazon.com/product-reviews/B0FR9KVFQQ/", "proxyConfiguration": { "useApifyProxy": true } }; // Run the Actor and wait for it to finish const run = await client.actor("happitap/amazon-prouct-reviews").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`šŸ’¾ 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); }); // šŸ“š Want to learn more šŸ“–? Go to ā†’ 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 = { "productUrl": "https://www.amazon.com/product-reviews/B0FR9KVFQQ/", "proxyConfiguration": { "useApifyProxy": True }, } # Run the Actor and wait for it to finish run = client.actor("happitap/amazon-prouct-reviews").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("šŸ’¾ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # šŸ“š Want to learn more šŸ“–? Go to ā†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "productUrl": "https://www.amazon.com/product-reviews/B0FR9KVFQQ/", "proxyConfiguration": { "useApifyProxy": true } }' | apify call happitap/amazon-prouct-reviews --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=happitap/amazon-prouct-reviews", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon Prouct Reviews", "description": "[UPDATED] Extract product reviews from Amazon including reviewer names, ratings, review text, customer photos, dates, and votes.\n\nāœ… Scrapes all reviews text, ratings, and dates\nšŸ“ø Extracts photos (both thumbnail and full-size URLs)\nšŸŽÆ Extracts helpful votes count\nāœ“ Identifies verified purchases", "version": "0.0", "x-build-id": "mkg4SS0lPhHYQcQef" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/happitap~amazon-prouct-reviews/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-happitap-amazon-prouct-reviews", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/happitap~amazon-prouct-reviews/runs": { "post": { "operationId": "runs-sync-happitap-amazon-prouct-reviews", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/happitap~amazon-prouct-reviews/run-sync": { "post": { "operationId": "run-sync-happitap-amazon-prouct-reviews", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "productUrl" ], "properties": { "productUrl": { "title": "Product Review URL", "pattern": "^https://www\\.amazon\\.[a-z.]+/product-reviews/[^/]+/?(.*)$", "type": "string", "description": "Amazon product reviews URL (e.g., https://www.amazon.com/product-reviews/PRODUCT_ID/)" }, "maxReviews": { "title": "Maximum Reviews", "minimum": 1, "type": "integer", "description": "Maximum number of reviews to scrape. Leave empty for unlimited.", "default": 100 }, "maxRequestsPerMinute": { "title": "Max Requests Per Minute", "minimum": 1, "maximum": 60, "type": "integer", "description": "Rate limiting: maximum requests per minute", "default": 10 }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Proxy settings for the scraper" } } }, "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 } } } } } } } } } } ```