# Hansard DebateInfo Scraper (`getdataforme/hansard-debateinfo-scraper`) Actor The Hansard DebateInfo Scraper extracts structured data from UK parliamentary debates, capturing details like titles, dates, and speaker contributions.... - **URL**: https://apify.com/getdataforme/hansard-debateinfo-scraper.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 1 monthly users, 33.3% 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 ## README.md ### Hansard DebateInfo Scraper #### Introduction The Hansard DebateInfo Scraper is an advanced tool designed to extract detailed information from UK parliamentary debates. It provides structured data on debate topics, speakers, and their contributions, enabling users to analyze political discourse efficiently. #### Features - **Comprehensive Data Extraction**: Captures detailed information about debates, including titles, dates, and speaker contributions. - **High-Quality Data**: Ensures reliable and accurate extraction from the Hansard website. - **Performance Efficiency**: Fast processing with minimal resource usage. - **Customizable Output**: Supports multiple formats like JSON, CSV, and Excel for easy integration. - **User-Friendly Interface**: Simple configuration and execution process. #### Input Parameters | Parameter | Type | Required | Description | Example | |-----------------|---------|----------|-----------------------------------------------------------------------------|------------------------------| | `country` | String | Yes | The country code (e.g., "GB" for the UK). | `"GB"` | | `debateType` | String | No | Type of debate to extract (e.g., "House of Commons"). | `"House of Commons"` | | `startDate` | Date | No | Start date for filtering debates. | `"2023-01-01T00:00:00Z"` | | `endDate` | Date | No | End date for filtering debates. | `"2023-12-31T23:59:59Z"` | | `outputFormat` | String | No | Desired output format (e.g., "JSON", "CSV"). | `"JSON"` | #### Example Usage ##### Input JSON ```json { "country": "GB", "debateType": "House of Commons", "startDate": "2023-01-01T00:00:00Z", "endDate": "2023-12-31T23:59:59Z", "outputFormat": "JSON" } ```` ##### Output JSON ```json { "data": { "debateInfo": [ { "title": "Debate on the Middle East and International Relations", "date": "2023-10-05T12:00:00Z", "speakers": [ {"name": "Lord Ahmad of Wimbledon", "contribution": "..."}, {"name": "Baroness Anelay of St Johns", "contribution": "..."} ] } ] } } ``` #### Use Cases - **Market Research and Analysis**: Understand political trends and public policy discussions. - **Competitive Intelligence**: Monitor legislative changes affecting industries. - **Price Monitoring**: Track debates on economic policies impacting pricing strategies. - **Content Aggregation**: Compile comprehensive reports on parliamentary activities. - **Academic Research**: Analyze historical and current political discourse. - **Business Automation**: Automate data collection for strategic decision-making. #### Installation and Usage 1. Search for "Hansard DebateInfo Scraper" 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 data is structured with key fields such as `debateInfo`, which includes debate titles, dates, and speaker contributions. Each entry provides detailed insights into parliamentary discussions. ### 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! *** ## Description Unlock insights from UK parliamentary debates with the Hansard DebateInfo Scraper. Extract detailed data on debate topics, speakers, and contributions efficiently. Ideal for market research, competitive intelligence, and academic analysis. Try it now in the Apify Store! # Actor input Schema ## `startUrls` (type: `array`): URLs to start with. ## Actor input object example ```json { "startUrls": [ { "url": "https://hansard.parliament.uk/Lords/2026-05-21/debates/754C80AD-6B54-43D1-A5F9-7E46D44B4690/King%E2%80%99SSpeech" } ] } ``` # 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 = { "startUrls": [ { "url": "https://hansard.parliament.uk/Lords/2026-05-21/debates/754C80AD-6B54-43D1-A5F9-7E46D44B4690/King%E2%80%99SSpeech" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/hansard-debateinfo-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 = { "startUrls": [{ "url": "https://hansard.parliament.uk/Lords/2026-05-21/debates/754C80AD-6B54-43D1-A5F9-7E46D44B4690/King%E2%80%99SSpeech" }] } # Run the Actor and wait for it to finish run = client.actor("getdataforme/hansard-debateinfo-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 '{ "startUrls": [ { "url": "https://hansard.parliament.uk/Lords/2026-05-21/debates/754C80AD-6B54-43D1-A5F9-7E46D44B4690/King%E2%80%99SSpeech" } ] }' | apify call getdataforme/hansard-debateinfo-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/hansard-debateinfo-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Hansard DebateInfo Scraper", "description": "The Hansard DebateInfo Scraper extracts structured data from UK parliamentary debates, capturing details like titles, dates, and speaker contributions....", "version": "0.0", "x-build-id": "WXimxSWsZsBelAx1u" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~hansard-debateinfo-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-hansard-debateinfo-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~hansard-debateinfo-scraper/runs": { "post": { "operationId": "runs-sync-getdataforme-hansard-debateinfo-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~hansard-debateinfo-scraper/run-sync": { "post": { "operationId": "run-sync-getdataforme-hansard-debateinfo-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "startUrls": { "title": "Start URLs", "type": "array", "description": "URLs to start with.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } } } }, "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": 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