# Gymshark Product Details Ec Spider (`getdataforme/gymshark-product-details-ec-spider`) Actor Automate Gymshark product data extraction with Gymshark Product Details Ec Spider. Efficiently scrape names, descriptions, prices, and more from multiple URLs. Customize item limits for tailored insights.... - **URL**: https://apify.com/getdataforme/gymshark-product-details-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 --- ## Gymshark Product Details Ec Spider ### Introduction The Gymshark Product Details Ec Spider is a powerful web scraping tool designed to extract detailed product information from the Gymshark website. It automates data collection for product names, descriptions, prices, and more, providing valuable insights into Gymshark's offerings. ### Features - **Automated Data Extraction**: Efficiently scrapes multiple product details with minimal setup. - **High-Quality Data**: Ensures accurate and reliable information retrieval. - **Customizable Limits**: Allows setting item limits to control the scope of data extraction. - **Flexible URL Configuration**: Supports input of multiple URLs for comprehensive scraping. - **User-Friendly Interface**: Easy configuration through Apify Store with clear instructions. ### Input Parameters | Parameter | Type | Required | Description | Example | |-------------|----------|----------|-----------------------------------------------------------------------------|-------------------------------------------------------------------------| | `Urls` | array | Yes | The URLs for the spider to scrape. Must be valid HTTP/HTTPS links. | `["https://www.gymshark.com/products/gymshark-whitney-legging-leggings-pink-aw25"]` | | `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.gymshark.com/products/gymshark-whitney-legging-leggings-pink-aw25" ], "item_limit": 10 } ```` #### Output JSON ```json [ { "url": "https://www.gymshark.com/products/gymshark-whitney-legging-leggings-pink-aw25", "status": 200, "name": "Whitney Regular Legging", "description": "EVERY GYM GIRL’S FAVOURITE COLLECTIONThe Whitney leggings & shorts are every gym girl’s favourite for a reason. Stretchy, buttery soft, and squat-proof enough for leg day, they’re the perfect pick whatever your session. AND there’s a mix of high-waisted and mid-high rise options to suit your vibe.\nInvisible bum scrunch lifts and pops your glutes\nCinching, snatching, flattering waistband\nOur butteriest, softest material\nSIZE & FIT\nSuper high-rise waistband\nRegular length\nModel is 5’9” and wears S\nMATERIAL & CARE78% Nylon, 22% ElastaneSKU: B3C6K-KC2J", "brand": "Gymshark | We Do Gym", "sku": "B3C6K-KC2J", "price": 15, "price_currency": "USD", "availability": "https://schema.org/OutOfStock", "images": [ "https://cdn.shopify.com/s/files/1/0156/6146/files/images-WhitneyLeggingGSResetPinkB3C6K_KC2J_1013_V1a.jpg?v=1759312311" ], "product_group_id": "6806369730762", "color": "pink", "category": "leggings", "actor_id": "ZPSU4hlFPlqBFnDfF", "run_id": "As3GrCckcgGSX0oej" } ] ``` ### Use Cases - **Market Research and Analysis**: Gather data to understand market trends and consumer preferences. - **Competitive Intelligence**: Monitor competitor product offerings and pricing strategies. - **Price Monitoring**: Track changes in product prices over time for strategic decision-making. - **Content Aggregation**: Compile product information for content creation or marketing purposes. - **Academic Research**: Use scraped data for studies related to e-commerce, consumer behavior, or fashion trends. - **Business Automation**: Integrate with business processes for automated inventory updates and analysis. ### Installation and Usage 1. Search for "Gymshark Product Details 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 where each object represents a product with fields such as `url`, `status`, `name`, `description`, `brand`, `sku`, `price`, `price_currency`, `availability`, `images`, `product_group_id`, `color`, `category`, `actor_id`, and `run_id`. Each field provides specific details about the scraped products. ### Error Handling - **Invalid URLs**: The spider will skip any invalid or unreachable URLs. - **Rate Limiting**: If rate limits are encountered, the spider may pause or retry after a delay. - **Data Inconsistencies**: Any missing data fields will be returned as null or empty strings. ### Rate Limiting and Best Practices - Ensure compliance with Gymshark's terms of service to avoid IP bans. - Use appropriate delays between requests to mimic human browsing behavior. - Monitor logs for any rate limiting messages and adjust the frequency of requests accordingly. ### Limitations and Considerations - The spider is designed specifically for Gymshark URLs; it may not work with other websites. - Ensure that all required fields are filled before running the spider to avoid incomplete data extraction. - Be aware of potential changes in Gymshark's website structure, which could affect scraping 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.gymshark.com/products/gymshark-whitney-legging-leggings-pink-aw25" ], "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/gymshark-product-details-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/gymshark-product-details-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/gymshark-product-details-ec-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/gymshark-product-details-ec-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Gymshark Product Details Ec Spider", "description": "Automate Gymshark product data extraction with Gymshark Product Details Ec Spider. Efficiently scrape names, descriptions, prices, and more from multiple URLs. Customize item limits for tailored insights....", "version": "0.0", "x-build-id": "cgJAgnKVI0gs95keA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~gymshark-product-details-ec-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-gymshark-product-details-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~gymshark-product-details-ec-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-gymshark-product-details-ec-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~gymshark-product-details-ec-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-gymshark-product-details-ec-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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.gymshark.com/products/gymshark-whitney-legging-leggings-pink-aw25" ], "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 } } } } } } } } } } ```