# Fab Discovery Scraper (`getdataforme/fab-discovery-scraper`) Actor The Fab Discovery Scraper extracts detailed product data from Fab.com, aiding market research, price monitoring, and competitive analysis. It features customizable searches, reliable outputs, and automated data collection, efficiently scraping up to 100 items per run with a user-friendly interface. - **URL**: https://apify.com/getdataforme/fab-discovery-scraper.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** Automation, Lead generation, Agents - **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 ## Fab Discovery Scraper The Fab Discovery Scraper is a powerful tool designed to extract detailed product information from Fab.com based on your specified search criteria. Whether you're conducting market research, monitoring prices, or gathering competitive intelligence, this actor provides reliable and comprehensive data to meet your needs. ### Features - **Comprehensive Data Extraction**: Retrieve detailed product information including title, price, ratings, and more. - **Customizable Search**: Tailor your search with specific queries and sorting options. - **High Performance**: Efficiently scrape up to 100 items per run. - **Reliable Output**: Consistent and structured data output for easy integration. - **Versatile Applications**: Suitable for market research, price monitoring, and more. - **User-Friendly Interface**: Simple setup and execution through the Apify platform. - **Automated Data Collection**: Schedule regular data extractions to keep your datasets up-to-date. ### Input Parameters | Parameter | Type | Required | Description | Example | |-------------|---------|----------|--------------------------------------------------|---------------| | searchQuery | String | Yes | The search term to look for on Fab.com. | "Vehicles" | | sortBy | String | No | Sort order for search results. | "-relevance" | | maxItems | Integer | No | Maximum number of items to fetch. | 100 | ### Example Usage #### Example Input ```json { "searchQuery": "Vehicles", "sortBy": "-relevance", "maxItems": 100 } ```` #### Example Output ```json [ { "uid": "2ef52723-be60-41b0-959b-47a96dc21ae4", "title": "Commercial Vehicles (Driveable)", "listingType": "3d-model", "price": 99.99, "averageRating": 0, "reviewCount": 0, "publishedAt": "2025-11-29T13:45:37.263030Z", "category": "Cars & Trucks", "tags": [ "Vehicle", "Videogame", "Blender", "Car", "Drivable", "Lowpoly", "Script", "Transport", "Truck", "Sport", "Passenger", "Cargo", "Load", "Blueprint", "Drive", "Van", "Pickup", "Racer" ], "thumbnailUrl": "https://media.fab.com/image_previews/gallery_images/0dcb1c98-63b3-49db-b9f0-412867b64821/ba6098a6-26d2-4cab-8bf2-926484b2028a.jpg", "seller": "Ozgur Saral", "isFree": false, "isDiscounted": false, "url": "https://www.fab.com/listings/2ef52723-be60-41b0-959b-47a96dc21ae4" } ] ``` ### Use Cases - **Market Research and Analysis**: Gather data on product trends and consumer preferences. - **Competitive Intelligence**: Monitor competitor offerings and pricing strategies. - **Price Monitoring**: Track price changes and discounts over time. - **Content Aggregation**: Compile product information for content creation. - **Academic Research**: Analyze market data for academic studies. - **Business Automation**: Automate data collection for business intelligence systems. ### Installation and Usage 1. Search for "Fab Discovery Scraper" 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 output is a JSON array where each object contains detailed information about a product, including: - `uid`: Unique identifier for the product. - `title`: Product title. - `price`: Product price. - `averageRating`: Average user rating. - `reviewCount`: Number of reviews. - `publishedAt`: Publication date. - `category`: Product category. - `tags`: Associated tags. - `thumbnailUrl`: URL to the product's thumbnail image. - `seller`: Seller's name. - `isFree`: Indicates if the product is free. - `isDiscounted`: Indicates if the product is discounted. - `url`: Direct URL to the product listing. ### 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 ## `searchQuery` (type: `string`): The search term to look for on Fab.com. ## `sortBy` (type: `string`): Sort order for search results. ## `maxItems` (type: `integer`): Maximum number of items to fetch. ## Actor input object example ```json { "searchQuery": "Vehicles", "sortBy": "-relevance", "maxItems": 100 } ``` # Actor output Schema ## `results` (type: `string`): No description # 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/fab-discovery-scraper").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/fab-discovery-scraper").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/fab-discovery-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/fab-discovery-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Fab Discovery Scraper", "description": "The Fab Discovery Scraper extracts detailed product data from Fab.com, aiding market research, price monitoring, and competitive analysis. It features customizable searches, reliable outputs, and automated data collection, efficiently scraping up to 100 items per run with a user-friendly interface.", "version": "0.0", "x-build-id": "Qbe308dmyktgcO9S1" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~fab-discovery-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-fab-discovery-scraper", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~fab-discovery-scraper/runs": { "post": { "operationId": "runs-sync-getdataforme-fab-discovery-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~fab-discovery-scraper/run-sync": { "post": { "operationId": "run-sync-getdataforme-fab-discovery-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchQuery": { "title": "Search Query", "type": "string", "description": "The search term to look for on Fab.com.", "default": "Vehicles" }, "sortBy": { "title": "Sort By", "enum": [ "-relevance", "-published_at", "price", "-price", "title", "-title" ], "type": "string", "description": "Sort order for search results.", "default": "-relevance" }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of items to fetch.", "default": 100 } } }, "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 } } } } } } } } } } ```