# Zalando Product Detail Ec Spider (`getdataforme/zalando-product-detail-ec-spider`) Actor The Zalando Product Detail Ec Spider efficiently extracts comprehensive product data from Zalando's website, including images, attributes, pricing, and stock availability.... - **URL**: https://apify.com/getdataforme/zalando-product-detail-ec-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 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 --- ## Zalando Product Detail Ec Spider ### Introduction The Zalando Product Detail Ec Spider is a powerful tool designed to extract detailed product information from Zalando's website. It efficiently gathers data such as images, attributes, pricing, and stock availability, providing comprehensive insights into each product. ### Features - **Comprehensive Data Extraction**: Captures detailed product information including images, attributes, prices, and stock status. - **High-Quality Data**: Ensures reliable and accurate data extraction for informed decision-making. - **Flexible Configuration**: Allows customization of URLs and item limits to suit specific needs. - **Efficient Performance**: Optimized for speed and efficiency in data scraping. - **User-Friendly Setup**: Easy configuration with clear input parameters. ### Input Parameters | Parameter | Type | Required | Description | Example | |------------|----------|----------|-----------------------------------------------------------------------------|-------------------------------------------------------------------------| | Urls | array | Yes | The URLs for the spider to scrape. | `["https://www.zalando.co.uk/redefined-rebel-fabian-boxy-fit-shirt-turkish-coffee-r0622d06m-o11.html"]` | | item_limit | integer | No | Maximum items to scrape per actor run. Set to 0 for no limit. | `10` | ### Example Usage #### Input JSON ```json { "Urls": [ "https://www.zalando.co.uk/redefined-rebel-fabian-boxy-fit-shirt-turkish-coffee-r0622d06m-o11.html" ], "item_limit": 10 } ```` #### Output JSON ```json [ { "productUrl": "https://www.zalando.co.uk/redefined-rebel-fabian-boxy-fit-shirt-turkish-coffee-r0622d06m-o11.html", "images": [ "https://img01.ztat.net/article/spp-media-p1/57ec33df4a39446a9b4389fbab0c6f41/6fdf98905ea0440699ecdf8a8e28c2fe.jpg?imwidth=300", "https://img01.ztat.net/article/spp-media-p1/a2570262a19841bf83e3b4f821daf4b9/a711ccd3262247a784dfa528defd65f0.jpg?imwidth=300", "https://img01.ztat.net/article/spp-media-p1/fa0677094ff3422faf7ea6991bdeba30/6dd350763680491ab9fe6e64e809a44e.jpg?imwidth=300" ], "attributes": { "brand": "Redefined Rebel", "color": "turkish coffee", "targetGroup": "MEN", "productGroup": "CLOTHING", "availableSizes": ["L", "M", "S", "XL", "XS", "XXL"] }, "scraperVersion": "1.0.0", "productId": "ern:product::R0622D06M-O11", "title": "FABIAN BOXY FIT - Shirt - turkish coffee", "description": null, "category": "Casual Shirts", "brand": "Redefined Rebel", "currency": "GBP", "salePrice": 31, "listPrice": 34.99, "discountPercentage": 11, "isInStock": true, "stockQuantity": null, "sku": "R0622D06M-O11", "upc": null, "actor_id": "jEKiUxk44SrYh9YgG", "run_id": "rtfZFkrkWGmcnhTVB" } ] ``` ### Use Cases - **Market Research and Analysis**: Gain insights into product offerings and market trends. - **Competitive Intelligence**: Monitor competitor pricing and product availability. - **Price Monitoring**: Track price changes over time for strategic decision-making. - **Content Aggregation**: Aggregate product data for marketing or sales purposes. - **Academic Research**: Use detailed product information for research projects. - **Business Automation**: Automate data collection processes to enhance efficiency. ### Installation and Usage 1. Search for "Zalando Product Detail Ec Spider" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters as needed. 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 output is a JSON array containing objects with detailed product information: - **productUrl**: The URL of the scraped product page. - **images**: An array of image URLs. - **attributes**: A dictionary of product attributes such as brand, color, and sizes. - **scraperVersion**: Version of the scraper used. - **productId**: Unique identifier for the product. - **title**: Product title. - **description**: Product description (if available). - **category**: Product category. - **brand**: Brand name. - **currency**: Currency code. - **salePrice**: Current sale price. - **listPrice**: Original list price. - **discountPercentage**: Discount percentage if applicable. - **isInStock**: Boolean indicating stock availability. - **stockQuantity**: Available stock quantity (if available). - **sku**: Stock Keeping Unit. - **upc**: Universal Product Code (if available). - **actor\_id**: Unique identifier for the actor run. - **run\_id**: Unique identifier for the specific run. ### Error Handling The spider includes error handling to manage common issues such as network errors, invalid URLs, and data parsing errors. If an error occurs, it will be logged in the Apify console, allowing you to review and address any issues promptly. ### Rate Limiting and Best Practices To ensure optimal performance and avoid being blocked by Zalando's servers: - **Respect Rate Limits**: Configure delays between requests if necessary. - **Use Multiple Actor Runs**: For large datasets, consider running multiple instances with different URL sets. - **Monitor Logs**: Regularly check logs for any rate limiting warnings or errors. ### Limitations and Considerations - **Dynamic Content**: Some product details may be loaded dynamically via JavaScript, which might not be captured if the page structure changes. - **URL Validity**: Ensure URLs are valid and accessible to avoid extraction failures. - **Data Changes**: Zalando's website layout or data presentation may change, potentially affecting data accuracy. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: [Contact Us](https://getdataforme.com/contact/) We're here to help you get the most out of this Actor! # Actor input Schema ## `Urls` (type: `array`): The urls for the spider. ## `item_limit` (type: `integer`): Maximum items to scrape per actor run. Set to 0 for no limit. ## Actor input object example ```json { "Urls": [ "https://www.zalando.co.uk/redefined-rebel-fabian-boxy-fit-shirt-turkish-coffee-r0622d06m-o11.html" ], "item_limit": 10 } ``` # Actor output Schema ## `results` (type: `string`): Scraped data items from dataset # 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/zalando-product-detail-ec-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/zalando-product-detail-ec-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/zalando-product-detail-ec-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/zalando-product-detail-ec-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Zalando Product Detail Ec Spider", "description": "The Zalando Product Detail Ec Spider efficiently extracts comprehensive product data from Zalando's website, including images, attributes, pricing, and stock availability....", "version": "0.0", "x-build-id": "sQ7vw6vHzYxsPKFZz" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~zalando-product-detail-ec-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-zalando-product-detail-ec-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~zalando-product-detail-ec-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-zalando-product-detail-ec-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~zalando-product-detail-ec-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-zalando-product-detail-ec-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Urls": { "title": "Urls", "minItems": 1, "type": "array", "description": "The urls for the spider.", "default": [ "https://www.zalando.co.uk/redefined-rebel-fabian-boxy-fit-shirt-turkish-coffee-r0622d06m-o11.html" ], "items": { "type": "string" } }, "item_limit": { "title": "Item limit", "minimum": 0, "type": "integer", "description": "Maximum items to scrape per actor run. Set to 0 for no limit.", "default": 10 } } }, "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 } } } } } } } } } } ```