# Wolt Scraper (`odaudlegur/wolt-scraper`) Actor Retrieves restaurant information on wolt.com. Checks which restaurant websites are alive, and crawls them for emails and social links. Filters common telemetry and template junk. - **URL**: https://apify.com/odaudlegur/wolt-scraper.md - **Developed by:** [SLASH](https://apify.com/odaudlegur) (community) - **Categories:** Lead generation, Automation, E-commerce - **Stats:** 42 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $1.50 / 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. Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have. 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 ## Wolt Scraper An Apify Actor that scrapes restaurant listings and detail pages from **wolt.com**, then optionally crawls each restaurantโ€™s own website to discover emails and social links. It uses HTTPX for fetching and BeautifulSoup for parsing. Wolt listings are client-rendered; the scraper extracts all restaurant links present in the initial HTML. To extend coverage, provide multiple listing URLs. ### Key Features - Listing to detail workflow - Start from listing pages like `https://wolt.com/en/nor/oslo/restaurants` - Extract restaurant detail URLs such as `https://wolt.com/en/nor/oslo/restaurant/chaiwala-oslo` - Restaurant details - name, address, phone, website - emails (email1..n) and social profiles (facebook, instagram, linkedin, x, youtube, tiktok, pinterest) - Same-domain contact crawl - For restaurants with a website, visit a small number of pages (default 3) to find additional emails and socials - Robust parsing - Parse HTML, JSON-LD, and Next.js `__NEXT_DATA__` for details ### Input Configuration Defined in `input_schema.json`. | Field | Type | Description | |------|------|-------------| | `start_urls` | array | Wolt listing pages to start from | | `max_results` | integer | Total restaurants to save across all listings (0 = no cap) | | `site_email_max_pages` | integer | Pages to visit on the restaurant website to discover contacts/socials (default 3) | | `timeout_seconds` | integer | Per-request read timeout (default 30) | Example: ```json { "start_urls": [ {"url": "https://wolt.com/en/nor/oslo/restaurants"} ], "max_results": 100, "site_email_max_pages": 3, "timeout_seconds": 30 } ```` ### How It Works 1. Enqueue listing URLs. 2. For each listing, parse the initial HTML to collect restaurant detail links. 3. For each restaurant detail page, extract core fields from JSON-LD, Next.js data, and visible HTML. 4. If a website exists, check availability and crawl a few internal pages to find emails and social links. 5. Push structured results to the default dataset. ### Output Example ```json { "source_url": "https://wolt.com/en/nor/oslo/restaurant/chaiwala-oslo", "name": "Chaiwala Oslo", "address": "Examplegata 1, 0150 Oslo", "phone": "+47 12 34 56 78", "website": "https://example-restaurant.no", "website_details": "ok", "email1": "post@example-restaurant.no", "social_facebook": "https://www.facebook.com/example", "social_instagram": "n/a", "social_linkedin": "n/a", "social_x": "n/a", "social_youtube": "n/a", "social_tiktok": "n/a", "social_pinterest": "n/a" } ``` *** ### Notes - Wolt listings use infinite scroll; HTTP fetch collects what is present in the initial HTML. Provide multiple listing pages if you need broader coverage. - Respect local laws and terms of service. Keep concurrency and request rates reasonable. ยฉ 2025 **SLSH**. All rights reserved. Copying or modifying the source code is prohibited. # Actor input Schema ## `start_urls` (type: `array`): Wolt listing pages to start from (e.g. https://wolt.com/en/nor/oslo/restaurants). The scraper follows restaurant detail links from these pages. ## `max_results` (type: `integer`): Total restaurants to save across all listings. 0 = no cap. Note: Wolt listing uses infinite scroll; HTTP fetch gets the initial set available in HTML. ## `site_email_max_pages` (type: `integer`): How many pages on the restaurant website to visit for emails and social links. ## `timeout_seconds` (type: `integer`): Read timeout per request. ## Actor input object example ```json { "start_urls": [ { "url": "https://wolt.com/en/nor/oslo/restaurants" } ], "max_results": 100, "site_email_max_pages": 3, "timeout_seconds": 30 } ``` # Actor output Schema ## `dataset` (type: `string`): No description ## `datasetCsv` (type: `string`): No description ## `datasetJsonl` (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 = { "start_urls": [ { "url": "https://wolt.com/en/nor/oslo/restaurants" } ] }; // Run the Actor and wait for it to finish const run = await client.actor("odaudlegur/wolt-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "start_urls": [{ "url": "https://wolt.com/en/nor/oslo/restaurants" }] } # Run the Actor and wait for it to finish run = client.actor("odaudlegur/wolt-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "start_urls": [ { "url": "https://wolt.com/en/nor/oslo/restaurants" } ] }' | apify call odaudlegur/wolt-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=odaudlegur/wolt-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Wolt Scraper", "description": "Retrieves restaurant information on wolt.com. Checks which restaurant websites are alive, and crawls them for emails and social links. Filters common telemetry and template junk.", "version": "1.1", "x-build-id": "RCrcdGNMxfLBaSXbv" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/odaudlegur~wolt-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-odaudlegur-wolt-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/odaudlegur~wolt-scraper/runs": { "post": { "operationId": "runs-sync-odaudlegur-wolt-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/odaudlegur~wolt-scraper/run-sync": { "post": { "operationId": "run-sync-odaudlegur-wolt-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "start_urls" ], "properties": { "start_urls": { "title": "Start URLs", "type": "array", "description": "Wolt listing pages to start from (e.g. https://wolt.com/en/nor/oslo/restaurants). The scraper follows restaurant detail links from these pages.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "max_results": { "title": "Maximum number of restaurants", "minimum": 0, "type": "integer", "description": "Total restaurants to save across all listings. 0 = no cap. Note: Wolt listing uses infinite scroll; HTTP fetch gets the initial set available in HTML.", "default": 100 }, "site_email_max_pages": { "title": "Same-domain pages to crawl for contacts", "minimum": 1, "maximum": 10, "type": "integer", "description": "How many pages on the restaurant website to visit for emails and social links.", "default": 3 }, "timeout_seconds": { "title": "HTTP timeout (seconds)", "minimum": 5, "type": "integer", "description": "Read timeout per request.", "default": 30 } } }, "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 } } } } } } } } } } ```