# Builtwith Discovery Parser Spider (`getdataforme/builtwith-discovery-parser-spider`) Actor The Builtwith Discovery Parser Spider extracts detailed platform and technology data from BuiltWith's discovery platform, offering customizable search parameters and scalable performance.... - **URL**: https://apify.com/getdataforme/builtwith-discovery-parser-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 --- ## Builtwith Discovery Parser Spider ### Introduction The Builtwith Discovery Parser Spider is a powerful tool designed to extract detailed information from BuiltWith's discovery platform. It enables users to gather insights on various platforms and technologies used by websites, providing valuable data for market research, competitive analysis, and more. ### Features - **Comprehensive Data Extraction**: Extracts detailed information about platforms and technologies. - **Customizable Search Parameters**: Allows configuration of search keys and item limits. - **High-Quality Data Output**: Provides reliable and structured output in JSON format. - **Scalable Performance**: Efficiently handles large datasets with adjustable item limits. - **User-Friendly Interface**: Easy setup and execution within the Apify platform. ### Input Parameters Table | Parameter | Type | Required | Description | Example | |-------------|---------|----------|-----------------------------------------------------------------------------|------------------| | SearchKey | string | No | The search key for the spider. | "Platform" | | item_limit | integer | No | Maximum items to scrape per actor run. Set to 0 for no limit. | 10 | ### Example Usage #### Input JSON ```json { "SearchKey": "Platform", "item_limit": 10 } ```` #### Output JSON ```json [ { "name": "Platform Media", "detail_url": "https://trends.builtwith.com/agency/Platform-Media", "description": "Platform Media is a Belfast-based marketing agency that goes beyond traditional services and helps extend clients' reach.", "categories": [ "Agency", "UK Agency" ], "total_live": 5, "live_and_expired": 54, "expired": 49, "actor_id": "1HTY4SdsH74meN2aB", "run_id": "eRiJRthUVYZ7WgK4U" }, { "name": "Acadaca Platform", "detail_url": "https://trends.builtwith.com/shop/Acadaca-Platform", "description": "Enterprise eCommerce platform.", "categories": [ "eCommerce", "Enterprise", "Online Store Builder", "Hosted Solution", "Agency", "B2B eCommerce", "Cross-Border eCommerce", "Custom Commerce Solution", "Digital Experience Platform", "Direct-to-Consumer eCommerce", "eCommerce Enabler", "eCommerce Marketing", "Fashion eCommerce", "Industry-Specific eCommerce", "Mobile Commerce Platform", "Omnichannel Commerce", "Order Management System", "Social Commerce" ], "total_live": 14, "american_live_sites": 6, "live_and_expired": 136, "expired": 122, "actor_id": "1HTY4SdsH74meN2aB", "run_id": "eRiJRthUVYZ7WgK4U" }, { "name": "Leaflet Platform", "detail_url": "https://trends.builtwith.com/shop/Leaflet-Platform", "description": "Price testing platform for Shopify.", "categories": [ "eCommerce", "Non Platform", "Shopify App", "Conversion Rate Optimization", "Hosted Solution", "SMB Solution", "eCommerce Marketing", "Merchandising Platform", "Pre-Purchase Solutions" ], "total_live": 13, "american_live_sites": 10, "live_and_expired": 154, "expired": 141, "actor_id": "1HTY4SdsH74meN2aB", "run_id": "eRiJRthUVYZ7WgK4U" } ] ``` ### Use Cases - **Market Research and Analysis**: Gain insights into market trends and competitor technologies. - **Competitive Intelligence**: Understand the technological stack of competitors. - **Price Monitoring**: Track pricing strategies across different platforms. - **Content Aggregation**: Collect data for content creation and analysis. - **Academic Research**: Support studies in technology adoption and digital marketing. - **Business Automation**: Integrate with business processes for automated insights. ### Installation and Usage 1. Search for "Builtwith Discovery Parser 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 platform with fields such as `name`, `detail_url`, `description`, `categories`, `total_live`, `live_and_expired`, `expired`, `actor_id`, and `run_id`. This structured data format allows for easy integration into various applications. ### Error Handling The actor is designed to handle common errors gracefully. If an error occurs, it will be logged in the Apify console with details on how to resolve it. Users are encouraged to check the log for any issues during execution. ### Rate Limiting and Best Practices - **Rate Limiting**: Ensure compliance with BuiltWith's terms of service by adhering to rate limits. - **Best Practices**: Use appropriate item limits to optimize performance and avoid unnecessary data retrieval. ### Limitations and Considerations - The actor relies on the availability and structure of BuiltWith's discovery platform, which may change over time. - Users should verify that their use case complies with BuiltWith's terms of service. ### 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 ## `SearchKey` (type: `string`): The search key 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 { "SearchKey": "Platform", "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/builtwith-discovery-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/builtwith-discovery-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/builtwith-discovery-parser-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/builtwith-discovery-parser-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Builtwith Discovery Parser Spider", "description": "The Builtwith Discovery Parser Spider extracts detailed platform and technology data from BuiltWith's discovery platform, offering customizable search parameters and scalable performance....", "version": "0.0", "x-build-id": "TLlKzeKl5cCa9ElZJ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~builtwith-discovery-parser-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-builtwith-discovery-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~builtwith-discovery-parser-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-builtwith-discovery-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~builtwith-discovery-parser-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-builtwith-discovery-parser-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "SearchKey": { "title": "Search Key", "type": "string", "description": "The search key for the spider.", "default": "Platform" }, "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 } } } } } } } } } } ```