# Gap Search Results Parser Spider (`getdataforme/gap-search-results-parser-spider`) Actor This Apify Actor scrapes and parses product data from Gap's search results, extracting prices, reviews, colors, sizes, and vendor details for valuable e-commerce insights. Ideal for market research, competitive analysis, and price monitoring.... - **URL**: https://apify.com/getdataforme/gap-search-results-parser-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 1 total users, 0 monthly users, 0.0% 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 scrapes and parses product data from Gap's search results, extracting prices, reviews, colors, sizes, and vendor details for valuable e-commerce insights. Ideal for market research, competitive analysis, and price monitoring.... --- ## Gap Search Results Parser Spider ### Introduction The Gap Search Results Parser Spider is a powerful Apify Actor designed to scrape and parse product data from Gap's search results pages. It extracts comprehensive details about products, including pricing, reviews, colors, sizes, and vendor information, enabling users to gather valuable e-commerce insights efficiently. This tool is ideal for businesses and researchers needing structured data from Gap's online catalog without manual effort. ### Features - **Comprehensive Data Extraction**: Captures key product attributes such as name, price ranges, sale prices, review scores, colors, sizes, and vendor details. - **High Reliability**: Built with robust error handling to ensure consistent data retrieval from Gap's dynamic web pages. - **Flexible Query Support**: Allows custom search queries to target specific product categories or keywords. - **Structured JSON Output**: Delivers clean, machine-readable data in JSON format, ready for integration into databases or analytics tools. - **Scalable Performance**: Optimized for handling multiple products per run, with efficient scraping to minimize resource usage. - **No Coding Required**: User-friendly interface on Apify Store for easy configuration and execution. - **Real-Time Insights**: Provides up-to-date information on promotions, discounts, and availability. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|--------|----------|-----------------------------------------------------------------------------|------------------| | Query | string | No | The search query to use for finding products on Gap's website. Defaults to a general term if not specified. | "girls t-shirts" | ### Example Usage To run the actor, provide the input in JSON format: ```json { "Query": "girls" } ```` Example output in JSON format: ```json [ { "id": "894335", "name": "Kids Care Bears Graphic Tunic T-Shirt", "web_product_type": "girls short-sleeved tees", "price_range": ["24.95", "34.95"], "sale_price_range": ["11.0", "23.0"], "review_score": null, "review_count": null, "vendor": "HYBRID PROMOTIONS, LLC", "free_shipping": "false", "default_thumb_image": "/webcontent/0061/870/059/cn61870059.jpg", "excluded_from_promo": "false", "colors": [ { "id": "894335012", "short_description": "Bainbridge blue", "name": "Blue", "effective_price": "20.0", "regular_price": "34.95", "percentage_off": "43", "default_size_variant_id": "REGULAR", "sku_sizes": ["regular|tops|size|6/7|s", "regular|tops|size|12|xl", "regular|tops|size|8|m", "regular|tops|size|10|l", "regular|tops|size|14/16|xxl"] } // Additional colors omitted for brevity ], "actor_id": "3ndsEFkgy8v0ChYOG", "run_id": "kVOe0aiTwCYa8Xgdi" } // Additional products omitted for brevity ] ``` ### Use Cases - **Market Research**: Analyze product trends, pricing strategies, and consumer preferences on Gap's platform. - **Competitive Intelligence**: Compare Gap's offerings with competitors by extracting detailed product catalogs. - **Price Monitoring**: Track price changes, sales, and discounts for inventory management or retail arbitrage. - **Content Aggregation**: Build databases of fashion products for blogs, apps, or e-commerce sites. - **Academic Research**: Study consumer behavior, fashion trends, or supply chain data from retail sources. - **Business Automation**: Automate data collection for reporting, dashboards, or integration with CRM systems. ### Installation and Usage 1. Search for "Gap Search Results Parser Spider" in the Apify Store. 2. Click "Try for free" or "Run". 3. Configure input parameters (e.g., set your desired query). 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 a JSON array of product objects. Each object includes fields like `id`, `name`, `web_product_type`, `price_range`, `sale_price_range`, `review_score`, `review_count`, `vendor`, `free_shipping`, `default_thumb_image`, `excluded_from_promo`, and a `colors` array. The `colors` array contains sub-objects with details on color variants, including `id`, `name`, `effective_price`, `regular_price`, `percentage_off`, and `sku_sizes` for available sizes. This structure ensures all relevant product data is captured for easy parsing and analysis. ### Error Handling The actor includes built-in error handling for common issues such as network timeouts, invalid queries, or changes in Gap's website structure. If an error occurs, it will be logged, and the run may retry automatically. For persistent issues, check the Apify console for details and ensure your query is valid. ### Rate Limiting and Best Practices Apify enforces rate limits to comply with website policies; avoid excessive runs to prevent blocks. Best practices include using specific queries to reduce load, running during off-peak hours, and exporting data promptly. Limit concurrent runs and monitor usage to stay within Apify's guidelines. ### Limitations and Considerations Data accuracy depends on Gap's website updates; the actor may not capture real-time changes immediately. It focuses on search results and may not include all product pages. Ensure compliance with Gap's terms of service and legal regulations when using scraped data. ### 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 ## `Query` (type: `string`): The query for the spider. ## Actor input object example ```json { "Query": "girls" } ``` # 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-search-results-parser-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-search-results-parser-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-search-results-parser-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/gap-search-results-parser-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Gap Search Results Parser Spider", "description": "This Apify Actor scrapes and parses product data from Gap's search results, extracting prices, reviews, colors, sizes, and vendor details for valuable e-commerce insights. Ideal for market research, competitive analysis, and price monitoring....", "version": "0.0", "x-build-id": "HJhQDaJLtQEgqmSR1" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~gap-search-results-parser-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-gap-search-results-parser-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~gap-search-results-parser-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-gap-search-results-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~gap-search-results-parser-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-gap-search-results-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Query": { "title": "Query", "type": "string", "description": "The query for the spider.", "default": "girls" } } }, "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 } } } } } } } } } } ```