# Amazon Products Scraper (Brasil) (`citrine_osmosis/amazon-products-scraper-brasil`) Actor Um aplicativo que coleta automaticamente (faz scraping) e estrutura dados de produtos disponíveis publicamente a partir de anúncios da Amazon para análise e monitoramento. - **URL**: https://apify.com/citrine\_osmosis/amazon-products-scraper-brasil.md - **Developed by:** [Lucas Missalia](https://apify.com/citrine_osmosis) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 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. 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 Product Scraper (Optimized) — Apify Actor An Apify Actor that extracts structured product data from Amazon search result pages using **Playwright (async Chromium)**, with a focus on **high performance and stability** on the Apify platform. citeturn4search1turn3file4 > **Performance-first version:** this iteration adds **concurrency**, **resource blocking**, and **single-pass DOM extraction** to reduce Playwright overhead and prevent slowdowns/freezes under load. citeturn3file4 --- ### 📦 Features - Scrapes Amazon search result pages for product listings. citeturn4search1 - Extracts rich product data including prices, ratings, delivery info, stock hints, and optional specs. citeturn4search1turn3file4 - Automatically handles cookie consent banners (best-effort). citeturn4search1turn3file4 - Triggers lazy-loaded content with a lightweight scroll. citeturn4search1turn3file4 - **Optimized for Apify performance**: - **Concurrent workers** (multiple pages in parallel). citeturn3file4 - **Blocks heavy resources** (images/fonts/styles/media) to reduce CPU/RAM and speed navigation. citeturn3file4 - **Single `page.evaluate()` extraction** to avoid hundreds of Playwright round-trips per page. citeturn3file4 - Detects Kindle Unlimited info (when present) and flags international purchase availability (best-effort). citeturn4search1turn3file4 - Outputs clean, structured JSON data via Apify's dataset. citeturn4search1turn3file4 --- ### 🗂️ Output #### Output model This optimized version pushes **one dataset item per product** (in batches) and includes the originating search URL in `sourceUrl`. citeturn3file4 #### Example item ```json { "sourceUrl": "https://www.amazon.com/s?k=laptop", "name": "Product Title", "asin": "B09XYZ1234", "rate": "4.5 out of 5 stars", "rateCount": "12,345 ratings", "description": "Short editorial or badge description", "price": "$499.99", "delivery": "Monday, Apr 22", "shippingInformation": "Free delivery Monday, Apr 22", "fastestDelivery": "Fastest delivery: Tomorrow", "internationalPurchase": false, "thumbnail": "https://m.media-amazon.com/images/...", "link": "https://www.amazon.com/dp/B09XYZ1234", "stockDetails": "Only 20 left in stock - order soon.", "details": { "screenSize": "15.6 Inches", "ram": "16 GB", "kindleUnlimited": "https://www.amazon.com/...", "message": "Read for free with Kindle Unlimited" } } ```` **Notes** - `stockDetails` and `details` are **optional** and appear only when the product listing includes those blocks. citeturn4search1turn3file4 - Only products that have **both a name and a price** are included in the output. citeturn4search1turn3file4 *** ### ⚙️ Input Configuration Configure the Actor via the Apify input UI or by passing JSON. #### Fields - `start_urls` *(array)* — List of Amazon search URLs to scrape. - Default: `[{"url": "https://www.amazon.com/s?k=spider+man+comics"}]` citeturn3file4 - `max_concurrency` *(number)* — Number of parallel workers/pages. - Default: `4` citeturn3file4 - `max_retries` *(number)* — Retries per URL on timeout/error. - Default: `2` citeturn3file4 - `navigation_timeout_ms` *(number)* — Navigation timeout in milliseconds. - Default: `30000` citeturn3file4 #### Example Input ```json { "start_urls": [ { "url": "https://www.amazon.com/s?k=mechanical+keyboard" }, { "url": "https://www.amazon.com/s?k=gaming+headset" } ], "max_concurrency": 4, "max_retries": 2, "navigation_timeout_ms": 30000 } ``` *** ### 🛠️ Tech Stack - **Apify SDK (Python)** — Actor lifecycle, request queue, dataset output. citeturn4search1 - **Playwright (async)** — Headless Chromium browser automation. citeturn4search1 *** ### 🔍 How It Works 1. **Initialization** — The Actor reads `start_urls` from the input and seeds a request queue. citeturn4search1turn3file4 2. **Browser + Context** — A headless Chromium browser is launched with a realistic user-agent and viewport. citeturn4search1turn3file4 3. **Performance routing** — Requests are intercepted and heavy resources are blocked (fonts, stylesheets, media, images). citeturn3file4 4. **Concurrent processing** — Multiple workers reuse pages and pull URLs from the queue concurrently. citeturn3file4 5. **Page processing** — For each URL, the Actor: - Navigates to the page and accepts cookie banners if present (best-effort). citeturn4search1turn3file4 - Waits for the Amazon search result grid to appear. - Performs a light scroll to trigger lazy-loaded product cards. citeturn4search1turn3file4 6. **Data extraction** — Extracts all product cards in a **single `page.evaluate()`** call and post-processes fields (e.g., Kindle Unlimited link). citeturn3file4 7. **Output** — Structured product items are pushed to the Apify dataset (batched). citeturn3file4 *** ### 🚀 Performance Tips - Start with `max_concurrency = 2–4` and increase gradually based on your Actor’s CPU/RAM. citeturn3file4 - If you observe timeouts, increase `navigation_timeout_ms` and/or reduce concurrency. citeturn3file4 - Blocking heavy resources improves speed, but if you need higher fidelity (e.g., guaranteed thumbnails), consider allowing images by removing `image` from the blocked types. citeturn3file4 *** ### ⚠️ Limitations & Notes - Amazon actively detects and blocks scrapers. This Actor uses a realistic user-agent and scroll behavior to mitigate this, but results may vary depending on the region and Amazon's current anti-bot policies. citeturn4search1turn3file4 - Amazon page layout and selectors change frequently; you may need to update selectors inside the extraction script. citeturn3file4 - Intended for **search result pages** (e.g., `/s?k=...`), not product detail pages. citeturn3file4 *** ### 📄 License / Compliance This project is intended for personal and educational use. Always comply with Amazon’s Terms of Service and applicable laws when scraping. citeturn4search1 # Actor input Schema ## `start_urls` (type: `array`): URLs to start with ## `max_concurrency` (type: `integer`): defines the maximum number of pages or browser contexts crawled simultaneously ## `max_retries` (type: `integer`): configuration option that defines the maximum number of times a failed test will be automatically re-executed before being marked as finally failed ## `navigation_timeout_ms` (type: `integer`): the maximum time (in milliseconds) the framework will wait for a page navigation event to complete before throwing a TimeoutError ## Actor input object example ```json { "start_urls": [ { "url": "https://www.amazon.com/s?k=laptop" } ], "max_concurrency": 4, "max_retries": 2, "navigation_timeout_ms": 30000 } ``` # 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 = { "start_urls": [ { "url": "https://www.amazon.com/s?k=laptop" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("citrine_osmosis/amazon-products-scraper-brasil").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 = { "start_urls": [{ "url": "https://www.amazon.com/s?k=laptop" }] } # Run the Actor and wait for it to finish run = client.actor("citrine_osmosis/amazon-products-scraper-brasil").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 '{ "start_urls": [ { "url": "https://www.amazon.com/s?k=laptop" } ] }' | apify call citrine_osmosis/amazon-products-scraper-brasil --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=citrine_osmosis/amazon-products-scraper-brasil", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Amazon Products Scraper (Brasil)", "description": "Um aplicativo que coleta automaticamente (faz scraping) e estrutura dados de produtos disponíveis publicamente a partir de anúncios da Amazon para análise e monitoramento.", "version": "0.1", "x-build-id": "ZNAPKXQpWuhZnNqZR" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/citrine_osmosis~amazon-products-scraper-brasil/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-citrine_osmosis-amazon-products-scraper-brasil", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/citrine_osmosis~amazon-products-scraper-brasil/runs": { "post": { "operationId": "runs-sync-citrine_osmosis-amazon-products-scraper-brasil", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/citrine_osmosis~amazon-products-scraper-brasil/run-sync": { "post": { "operationId": "run-sync-citrine_osmosis-amazon-products-scraper-brasil", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "start_urls" ], "properties": { "start_urls": { "title": "Start URLs", "type": "array", "description": "URLs to start with", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "max_concurrency": { "title": "max_concurrency", "type": "integer", "description": "defines the maximum number of pages or browser contexts crawled simultaneously", "default": 4 }, "max_retries": { "title": "max_retries", "type": "integer", "description": "configuration option that defines the maximum number of times a failed test will be automatically re-executed before being marked as finally failed", "default": 2 }, "navigation_timeout_ms": { "title": "navigation_timeout_ms", "type": "integer", "description": "the maximum time (in milliseconds) the framework will wait for a page navigation event to complete before throwing a TimeoutError", "default": 30000 } } }, "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 } } } } } } } } } } ```