# Gap Categories Spider (`getdataforme/gap-categories-spider`) Actor Gap Categories Spider extracts comprehensive product data from Gap's category pages, including IDs, names, prices, ratings, reviews, and images. It handles pagination, discounts, and multiple URLs for reliable, efficient e-commerce insights and analysis. - **URL**: https://apify.com/getdataforme/gap-categories-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, 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 Gap Categories Spider extracts comprehensive product data from Gap's category pages, including IDs, names, prices, ratings, reviews, and images. It handles pagination, discounts, and multiple URLs for reliable, efficient e-commerce insights and analysis. --- ## Gap Categories Spider ### Introduction The Gap Categories Spider is an Apify Actor designed to scrape detailed product information from Gap's category pages. It extracts comprehensive data such as product IDs, names, prices, ratings, reviews, and images, making it an essential tool for e-commerce data collection. This Actor ensures reliable, structured data output, enabling users to gather insights efficiently without manual browsing. ### Features - **Comprehensive Data Extraction**: Captures key product details including IDs, names, prices, ratings, reviews, availability, and images. - **Pagination Handling**: Automatically navigates through multiple pages in category listings for complete data retrieval. - **Discount and Pricing Insights**: Extracts original prices, discounted prices, and discount percentages for accurate pricing analysis. - **High Reliability**: Built with robust error handling to manage dynamic web content and ensure consistent scraping. - **Flexible Input**: Accepts multiple URLs for scraping various Gap categories simultaneously. - **Structured Output**: Delivers data in clean JSON format, ready for integration into databases or analysis tools. - **Performance Optimized**: Efficient scraping with minimal resource usage, supporting large-scale data collection. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|---------|----------|-------------|---------| | Urls | array | Yes | An array of URLs pointing to Gap category pages to scrape. Each URL must be a valid HTTP or HTTPS link. Minimum of 1 URL required. | ["https://www.gap.com/browse/men/t-shirts?cid=5225&mlink=1,1,M_DP_VCN_3_TEES_IMAGE#department=75"] | ### Example Usage #### Input JSON ```json { "Urls": [ "https://www.gap.com/browse/men/t-shirts?cid=5225&mlink=1,1,M_DP_VCN_3_TEES_IMAGE#department=75" ] } ```` #### Output JSON ```json [ { "product_id": "513718042", "style_id": "513718", "name": "Adult Heavyweight Relaxed Pocket T-Shirt", "product_url": "https://www.gap.com/browse/product.do?pid=513718042", "color": "Black", "price": "16.97", "original_price": "44.95", "discount_percent": "62", "rating": 4.6, "review_count": 395, "availability": "In Stock", "image": "https://www.gap.com/webcontent/0060/843/968/cn60843968.jpg", "actor_id": "cRqnK4PPxnCM8E44n", "run_id": "TkTigtqHSPyf9Rtq8" }, { "product_id": "513718132", "style_id": "513718", "name": "Adult Heavyweight Relaxed Pocket T-Shirt", "product_url": "https://www.gap.com/browse/product.do?pid=513718132", "color": "Green", "price": "14.97", "original_price": "44.95", "discount_percent": "67", "rating": 4.6, "review_count": 395, "availability": "In Stock", "image": "https://www.gap.com/webcontent/0056/987/339/cn56987339.jpg", "actor_id": "cRqnK4PPxnCM8E44n", "run_id": "TkTigtqHSPyf9Rtq8" }, { "product_id": "804453152", "style_id": "804453", "name": "Heavyweight Relaxed T-Shirt", "product_url": "https://www.gap.com/browse/product.do?pid=804453152", "color": "Green", "price": "19.99", "original_price": "49.95", "discount_percent": "60", "rating": 4.7, "review_count": 122, "availability": "In Stock", "image": "https://www.gap.com/webcontent/0060/391/417/cn60391417.jpg", "actor_id": "cRqnK4PPxnCM8E44n", "run_id": "TkTigtqHSPyf9Rtq8" } ] ``` ### Use Cases - **Market Research and Analysis**: Gather data on product trends, pricing strategies, and customer ratings to inform business decisions. - **Competitive Intelligence**: Compare Gap's offerings with competitors by analyzing product details and discounts. - **Price Monitoring**: Track price changes and discounts across categories for dynamic pricing strategies. - **Content Aggregation**: Collect product images and descriptions for content creation or e-commerce platforms. - **Academic Research**: Study consumer behavior through ratings, reviews, and availability data. - **Business Automation**: Automate data feeds for inventory management or sales forecasting tools. ### Installation and Usage 1. Search for "Gap Categories Spider" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters by providing the URLs of Gap category pages. 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 identifier for the product. - `style_id`: Style identifier. - `name`: Product name. - `product_url`: Direct link to the product page. - `color`: Product color variant. - `price`: Current selling price. - `original_price`: Original price before discount. - `discount_percent`: Percentage discount. - `rating`: Average customer rating. - `review_count`: Number of reviews. - `availability`: Stock status. - `image`: URL to product image. - `actor_id` and `run_id`: Metadata for tracking the Actor run. ### 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 ## `Urls` (type: `array`): The urls for the spider. ## Actor input object example ```json { "Urls": [ "https://www.gap.com/browse/men/t-shirts?cid=5225&mlink=1,1,M_DP_VCN_3_TEES_IMAGE#department=75" ] } ``` # 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/gap-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/gap-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/gap-categories-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/gap-categories-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Gap Categories Spider", "description": "Gap Categories Spider extracts comprehensive product data from Gap's category pages, including IDs, names, prices, ratings, reviews, and images. It handles pagination, discounts, and multiple URLs for reliable, efficient e-commerce insights and analysis.", "version": "0.0", "x-build-id": "o8kjC0DuYTNdPjRY1" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~gap-categories-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-gap-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~gap-categories-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-gap-categories-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~gap-categories-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-gap-categories-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Urls": { "title": "Urls", "minItems": 1, "type": "array", "description": "The urls for the spider.", "default": [ "https://www.gap.com/browse/men/t-shirts?cid=5225&mlink=1,1,M_DP_VCN_3_TEES_IMAGE#department=75" ], "items": { "type": "string" } } } }, "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 } } } } } } } } } } ```