# Sephora Categories Spider (`getdataforme/sephora-categories-spider`) Actor This Apify actor efficiently scrapes comprehensive product data from Sephora category pages, including IDs, brands, prices, ratings, and reviews.... - **URL**: https://apify.com/getdataforme/sephora-categories-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 2 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 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 ### Description This Apify actor efficiently scrapes comprehensive product data from Sephora category pages, including IDs, brands, prices, ratings, and reviews.... --- ## Sephora Categories Spider This Apify Actor efficiently scrapes product data from Sephora's category pages, extracting detailed information such as product IDs, brand names, prices, ratings, and reviews. It provides structured, reliable data for e-commerce analysis, making it an essential tool for businesses and researchers. With built-in optimizations, it ensures high-quality results while handling dynamic web content seamlessly. ### Features - **Comprehensive Data Extraction**: Captures key product details including IDs, names, prices, ratings, and reviews from specified Sephora categories. - **High-Speed and Reliable Scraping**: Utilizes advanced web scraping techniques for fast, dependable performance with minimal downtime. - **Customizable Category Selection**: Allows targeting specific categories via slugs for focused data collection. - **Structured Output Formats**: Supports JSON, CSV, and Excel exports for easy integration into workflows. - **Error Handling and Monitoring**: Includes robust error recovery and progress tracking through Apify's logging system. - **Data Quality Assurance**: Ensures accurate, up-to-date information with built-in validations. - **Scalable for Automation**: Ideal for recurring tasks like price monitoring and competitive intelligence. ### Input Parameters | Parameter | Type | Required | Description | Example | |--------------|--------|----------|--------------------------------------|-------------| | CategorySlug | string | No | The category slug for the spider. | "skincare" | ### Example Usage #### Input Configuration ```json { "CategorySlug": "skincare" } ```` #### Example Output ```json [ { "product_id": "P519160", "brand_name": "rhode", "display_name": "Glazing Milk Ceramide Facial Essence", "current_sku": "2898419", "price": "$20.00 - $32.00", "rating": "3.8306", "reviews": "2036", "product_url": "/product/glazing-milk-P519160?skuId=2898419", "actor_id": "y8xLpYiM3B2ZazRfa", "run_id": "5BBveljIWF2sDY5xi" }, { "product_id": "P427406", "brand_name": "The Ordinary", "display_name": "Glycolic Acid 7% Exfoliating and Brightening Daily Toner", "current_sku": "2031508", "price": "$9.00 - $13.50", "rating": "4.3555", "reviews": "4566", "product_url": "/product/the-ordinary-deciem-glycolic-acid-7-toning-solution-P427406?skuId=2031508", "actor_id": "y8xLpYiM3B2ZazRfa", "run_id": "5BBveljIWF2sDY5xi" }, { "product_id": "P517678", "brand_name": "Beauty of Joseon", "display_name": "Day Dew Sunscreen Lightweight SPF 50", "current_sku": "2893485", "price": "$18.00", "rating": "4.0135", "reviews": "371", "product_url": "/product/day-dew-sunscreen-exclusive-50ml-P517678?skuId=2893485", "actor_id": "y8xLpYiM3B2ZazRfa", "run_id": "5BBveljIWF2sDY5xi" } ] ``` ### Use Cases - **Market Research and Analysis**: Gather data on product trends, pricing, and consumer ratings to inform business strategies. - **Competitive Intelligence**: Monitor competitors' offerings in specific categories like skincare or makeup. - **Price Monitoring**: Track price fluctuations and availability for dynamic pricing models. - **Content Aggregation**: Collect product details for blogs, reviews, or e-commerce platforms. - **Academic Research**: Analyze consumer behavior and product popularity in beauty markets. - **Business Automation**: Automate data feeds for inventory management or marketing campaigns. ### Installation and Usage 1. Search for "Sephora Categories Spider" in the Apify Store 2. Click "Try for free" or "Run" 3. Configure input parameters 4. Click "Start" to begin extraction 5. Monitor progress in the log 6. Export results in your preferred format (JSON, CSV, Excel) ### Output Format The Actor outputs data as a JSON array of objects, each representing a product. Key fields include: - `product_id`: Unique Sephora product identifier. - `brand_name`: The product's brand. - `display_name`: Full product name. - `current_sku`: Current stock-keeping unit. - `price`: Price range or single price. - `rating`: Average customer rating. - `reviews`: Number of reviews. - `product_url`: Relative URL to the product page. - `actor_id` and `run_id`: Apify tracking identifiers for the extraction run. This structure ensures easy parsing and integration into databases or analysis tools. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: https://getdataforme.com/contact/ We're here to help you get the most out of this Actor! *** # Actor input Schema ## `CategorySlug` (type: `string`): The category slug for the spider. ## Actor input object example ```json { "CategorySlug": "skincare" } ``` # 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("getdataforme/sephora-categories-spider").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("getdataforme/sephora-categories-spider").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 getdataforme/sephora-categories-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/sephora-categories-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Sephora Categories Spider", "description": "This Apify actor efficiently scrapes comprehensive product data from Sephora category pages, including IDs, brands, prices, ratings, and reviews....", "version": "0.0", "x-build-id": "gRk9dnVJs8oC5i3IB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~sephora-categories-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-sephora-categories-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~sephora-categories-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-sephora-categories-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~sephora-categories-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-sephora-categories-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "CategorySlug": { "title": "Category Slug", "type": "string", "description": "The category slug for the spider.", "default": "skincare" } } }, "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 } } } } } } } } } } ```