# Brno Menu Scraper (`padi142/brno-menu`) Actor Scrapes daily restaurant menus from various sources in Brno, Czech Republic. - **URL**: https://apify.com/padi142/brno-menu.md - **Developed by:** [Padak Padakovic](https://apify.com/padi142) (community) - **Categories:** Other, Travel - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ### What does Brno Menu Scraper do? **Brno Menu Scraper** collects daily lunch menus from restaurants in Brno, Czech Republic. Inspired by [https://github.com/jdobes/lunch] (https://github.com/jdobes/lunch). ### How to use Brno Menu Scraper 1. Open the actor in Apify Console. 2. Optionally choose restaurant IDs in the **Input** tab. 3. Optionally enter a reference date in `YYYY-MM-DD` format. 4. Start the run and open the Dataset when it finishes. 5. Download or consume the results through the Apify API. ### Input The **Restaurant IDs** field can limit a run to selected restaurants. Leave it empty to scrape all supported restaurants. The **Reference date** field determines the requested menu week when a source does not publish explicit dates. It defaults to today. Example: ```json { "restaurantIds": ["napurkynce"], "date": "2026-07-15" } ```` ### Supported restaurants | Restaurant ID | Restaurant | Menu URL | | ---------------------- | -------------------- | ----------------------------------------------------------- | | `nepal` | Nepal Brno | [Daily menu](https://nepalbrno.cz/NepalBrno/poledni.php) | | `napurkynce` | Na Purkyňce | [Daily menu](https://www.napurkynce.cz/denni-menu/) | | `ukarla` | U Karla | [Lunch menu](https://ukarlabrno.cz/menu/pages/poledni-menu) | | `u3opic` | U 3 Opic | [Restaurant website](https://www.u3opic.cz/) | | `charliesmill` | Charlie's Mill | [Menu](https://www.charliesmill.cz/menu/) | | `pivovarska-starobrno` | Pivovárská Starobrno | [Lunch menu](https://www.pivovarska-starobrno.cz/menu/) | | `uvozna` | Úvozna | [Daily menu](https://www.uvozna.cz/denni-menu/) | | `ubosenohy` | U Bosé nohy | [Lunch menu](https://www.ubosenohy.cz/poledni-menu.html) | Use these IDs in the `restaurantIds` input field to scrape selected restaurants. ### Output Each successful record contains the restaurant, source URL, date, and menu item names. Failed restaurant requests are represented with `status: "error"` and an error message. ```json { "restaurantId": "napurkyne", "restaurantName": "Na Purkyňce", "date": "2026-07-15", "menuItems": ["Polévka: Kuřecí vývar", "Smažený sýr, hranolky"], "status": "success" } ``` You can download the dataset in various formats such as JSON, HTML, CSV, or Excel. ### Data table | Field | Description | | ---------------- | ---------------------------- | | `restaurantId` | Stable restaurant identifier | | `restaurantName` | Restaurant name | | `url` | Official source page | | `date` | Menu date | | `menuItems` | Soup and main dish names | | `status` | `success` or `error` | | `scrapedAt` | Collection timestamp | # Actor input Schema ## `restaurantIds` (type: `array`): Optional list of restaurants to scrape. Leave empty to scrape all available restaurants. ## `date` (type: `string`): Date used to determine the menu week in YYYY-MM-DD format. Defaults to today. ## Actor input object example ```json { "restaurantIds": [], "date": "" } ``` # 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("padi142/brno-menu").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/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("padi142/brno-menu").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call padi142/brno-menu --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=padi142/brno-menu", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Brno Menu Scraper", "description": "Scrapes daily restaurant menus from various sources in Brno, Czech Republic.", "version": "0.0", "x-build-id": "8piT8n6rXB8R8lnrH" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/padi142~brno-menu/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-padi142-brno-menu", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/padi142~brno-menu/runs": { "post": { "operationId": "runs-sync-padi142-brno-menu", "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/padi142~brno-menu/run-sync": { "post": { "operationId": "run-sync-padi142-brno-menu", "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": { "restaurantIds": { "title": "Restaurant IDs", "type": "array", "description": "Optional list of restaurants to scrape. Leave empty to scrape all available restaurants.", "default": [], "items": { "type": "string" } }, "date": { "title": "Reference date", "type": "string", "description": "Date used to determine the menu week in YYYY-MM-DD format. Defaults to today.", "default": "" } } }, "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 } } } } } } } } } } ```