# UK GDC Scraper (`bigboring/uk-gdc-scraper`) Actor Extracts registered dental professionals from the UK General Dental Council. - **URL**: https://apify.com/bigboring/uk-gdc-scraper.md - **Developed by:** [Big Boring](https://apify.com/bigboring) (community) - **Categories:** Lead generation, Business - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Uk Gdc Scraper ### What does this scraper do? The **Uk Gdc Scraper** is a highly efficient and fast data extraction tool designed to scrape gdc directories and websites across UK. It extracts essential information such as business names, addresses, phone numbers, email addresses, websites, and social media links. It relies on a universal heuristic engine, making it capable of scraping thousands of standard directory websites without relying on fragile, site-specific CSS selectors. ### Why scrape gdc data in UK? - **Lead Generation:** Build a targeted B2B list of gdc for sales outreach and marketing campaigns. - **Market Research:** Understand the distribution and density of gdc across different regions in UK. - **Competitor Analysis:** Keep track of the local gdc landscape and monitor their digital presence. - **Data Enrichment:** Update your existing CRM with fresh, accurate contact details of gdc. ### Input Parameters The scraper accepts various input parameters to customize your scraping jobs. The primary input is an array of start URLs. | Field | Type | Description | | ----- | ---- | ----------- | | `startUrls` | Array | List of URLs to start scraping from. These should ideally be directory search result pages or list pages for gdc. | | `maxRunTimeMinutes` | Integer | Maximum execution time for the scraper in minutes. Defaults to 1440 (24 hours). Acts as a graceful kill switch to protect your budget. | *Example Input:* ```json { "startUrls": [ { "url": "https://example-directory.com/uk/gdc" } ], "maxRunTimeMinutes": 60 } ```` ### Output Example The extracted data is stored in the Apify Dataset in JSON format. Here is a typical example of an extracted item: ```json { "url": "https://example-directory.com/listing/123", "name": "Example Gdc Services", "phone": "+1 234 567 8900", "email": "contact@example.com", "website": "https://www.example.com", "address": "123 Main St, City, UK", "social": { "facebook": "https://facebook.com/example", "linkedin": "https://linkedin.com/company/example" } } ``` ### Universal DOM Heuristics Unlike traditional scrapers that break when a website changes its design, the **Uk Gdc Scraper** uses a Universal DOM Heuristic Engine. It scans the page for semantic patterns, neighboring text nodes, and regex matches to find contact information organically. This makes it incredibly resilient and capable of working out-of-the-box on the vast majority of local business directories. ### Pricing This actor is monetized using a **Pay-Per-Result** (PPE) pricing model. You only pay for the successful records extracted, ensuring cost-efficiency. - **Price:** $0.005 per dataset item. ### Graceful Kill Switch To prevent runaway costs, this scraper is equipped with a graceful kill switch. If the run time exceeds the `maxRunTimeMinutes` input parameter, the scraper will safely finalize the current pages, save the dataset, and shut down gracefully without losing any data. # Actor input Schema ## `maxItems` (type: `integer`): Maximum number of items to scrape. ## `maxRunTimeMinutes` (type: `integer`): Gracefully kills the scraper after this many minutes to prevent runaway costs. ## Actor input object example ```json { "maxItems": 100, "maxRunTimeMinutes": 5 } ``` # Actor output Schema ## `results` (type: `string`): Extracted business listings and contact information. # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "maxItems": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("bigboring/uk-gdc-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "maxItems": 100 } # Run the Actor and wait for it to finish run = client.actor("bigboring/uk-gdc-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 '{ "maxItems": 100 }' | apify call bigboring/uk-gdc-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=bigboring/uk-gdc-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "UK GDC Scraper", "description": "Extracts registered dental professionals from the UK General Dental Council.", "version": "1.0", "x-build-id": "q9wgrrUpSCokUy0gB" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/bigboring~uk-gdc-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-bigboring-uk-gdc-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/bigboring~uk-gdc-scraper/runs": { "post": { "operationId": "runs-sync-bigboring-uk-gdc-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/bigboring~uk-gdc-scraper/run-sync": { "post": { "operationId": "run-sync-bigboring-uk-gdc-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "maxItems": { "title": "Max items", "type": "integer", "description": "Maximum number of items to scrape." }, "maxRunTimeMinutes": { "title": "Max Run Time (Minutes)", "minimum": 1, "type": "integer", "description": "Gracefully kills the scraper after this many minutes to prevent runaway costs.", "default": 5 } } }, "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 } } } } } } } } } } ```