# TourRadar Reviews Scraper (`knagymate/tourradar-reviews-scraper`) Actor Extract reviews from TourRadar tour pages including ratings, comments, traveler data, and images. Supports sorting, date filtering, and bulk scraping from multiple URLs. - **URL**: https://apify.com/knagymate/tourradar-reviews-scraper.md - **Developed by:** [knagymate](https://apify.com/knagymate) (community) - **Categories:** Travel, Automation, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 3 bookmarks - **User rating**: 5.00 out of 5 stars ## Pricing from $3.00 / 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. 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 ## TourRadar Reviews Scraper | Extract Tour Reviews, Ratings & Traveler Feedback at Scale Scrape **TourRadar tour reviews** in seconds and turn them into structured datasets for **analytics, AI models, sentiment analysis, and travel market insights**. This actor extracts real traveler reviews including ratings, travel dates, operator responses, and user-uploaded images — ready for export to **JSON, CSV, Excel, or API pipelines**. --- ### 🔥 Why use this TourRadar scraper? - Extract **real TourRadar reviews at scale** - Capture **ratings, review text, and traveler insights** - Includes **tour operator responses and metadata** - Ideal for **AI training, analytics, dashboards, and competitor research** - Built for **fast, reliable, and scalable scraping** --- ### 🚀 Features - Scrape reviews from any **TourRadar tour URL** - Extract structured data including: - Review text and ratings - Travel date and traveler count - Author name - Operator name and responses - Review images - Sorting options: - Most recent - Most popular - Highest rating - Lowest rating - Incremental scraping via **cutoff date** - Export to **JSON, CSV, Excel, or integrate via API** --- ### 📥 Input ```json { "urls": [ { "url": "https://www.tourradar.com/t/258" } ], "max_review_per_page": 100, "sort_by": "recent", "cutoff_date": "2024-01-01" } ```` #### Input parameters - **urls** (required): List of TourRadar tour URLs - **max\_review\_per\_page**: Maximum number of reviews per URL (default: 1000) - **sort\_by**: - `recent` - `popular` - `highest` - `lowest` - **cutoff\_date**: Only return reviews newer than this date *** ### 📤 Output Each review is returned as structured data: ```json { "tourUrl": "https://www.tourradar.com/t/258", "tourId": "258", "id": "245656", "date": "2023-01-16 00:00:00", "dateTravel": "January 2023", "travellerCount": 0, "rating": 5.0, "authorName": "Evie", "comments": "This tour is 100% worth booking...", "operatorComment": "", "operatorName": "MacBackpackers", "images": [ "https://cdn.tourradar.com/s3/review/1440/245656_eb4b0837.jpg" ] } ``` *** ### 📊 Use cases #### 📈 Market research & analytics Analyze traveler sentiment, satisfaction trends, and review patterns across tours. #### 🧳 Tour operator benchmarking Compare tour operators based on ratings, feedback, and customer experience. #### 🤖 AI & data pipelines Use structured reviews for: - NLP models - Sentiment analysis - Recommendation systems #### 📉 Reputation monitoring Track how tour perception evolves over time. *** ### ⚠️ Notes - Some reviews may include **operator responses** - Not all reviews contain **images or traveler count** - Large tours can have **thousands of reviews** - Always comply with TourRadar Terms of Service *** ### 💡 Pro tips - Use `recent` + `cutoff_date` for **incremental scraping** - Run multiple jobs for **large-scale datasets** - Combine with other platforms for **multi-source analysis** - Store raw data for **future reprocessing and ML pipelines** *** ### ⚡ How it works - Extracts **tour ID from page HTML** - Fetches reviews via **TourRadar internal API** - Handles pagination automatically - Supports proxy rotation and retries for reliability *** ### 🧠 Built for scale This actor is designed with: - Retry logic & anti-bot handling - Proxy support - Clean structured outputs - Easy integration into data pipelines *** ### 🚀 Ready to scrape? Start extracting TourRadar reviews and unlock valuable travel insights today. # Actor input Schema ## `urls` (type: `array`): List of TourRadar tour URLs to scrape reviews from. ## `max_review_per_url` (type: `integer`): Maximum number of reviews to scrape per URL. ## `sort_by` (type: `string`): Sorting method for reviews. ## `cutoff_date` (type: `string`): Only reviews newer than this date will be returned. ## Actor input object example ```json { "urls": [ { "url": "https://www.tourradar.com/t/258" } ], "max_review_per_url": 200, "sort_by": "recent" } ``` # 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 = { "urls": [ { "url": "https://www.tourradar.com/t/258" } ], "max_review_per_url": 200, "sort_by": "recent", "cutoff_date": "" }; // Run the Actor and wait for it to finish const run = await client.actor("knagymate/tourradar-reviews-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 = { "urls": [{ "url": "https://www.tourradar.com/t/258" }], "max_review_per_url": 200, "sort_by": "recent", "cutoff_date": "", } # Run the Actor and wait for it to finish run = client.actor("knagymate/tourradar-reviews-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 '{ "urls": [ { "url": "https://www.tourradar.com/t/258" } ], "max_review_per_url": 200, "sort_by": "recent", "cutoff_date": "" }' | apify call knagymate/tourradar-reviews-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=knagymate/tourradar-reviews-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "TourRadar Reviews Scraper", "description": "Extract reviews from TourRadar tour pages including ratings, comments, traveler data, and images. Supports sorting, date filtering, and bulk scraping from multiple URLs.", "version": "0.0", "x-build-id": "Eq4ab01mGn2qp2ONf" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/knagymate~tourradar-reviews-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-knagymate-tourradar-reviews-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/knagymate~tourradar-reviews-scraper/runs": { "post": { "operationId": "runs-sync-knagymate-tourradar-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/knagymate~tourradar-reviews-scraper/run-sync": { "post": { "operationId": "run-sync-knagymate-tourradar-reviews-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "urls" ], "properties": { "urls": { "title": "Tour URLs", "type": "array", "description": "List of TourRadar tour URLs to scrape reviews from.", "items": { "type": "object", "required": [ "url" ], "properties": { "url": { "type": "string", "title": "URL of a web page", "format": "uri" } } } }, "max_review_per_url": { "title": "Maximum number of reviews per URL", "minimum": 1, "type": "integer", "description": "Maximum number of reviews to scrape per URL.", "default": 200 }, "sort_by": { "title": "Sort reviews by", "enum": [ "recent", "popular", "highest", "lowest" ], "type": "string", "description": "Sorting method for reviews.", "default": "recent" }, "cutoff_date": { "title": "Cutoff date", "type": "string", "description": "Only reviews newer than this date will be returned." } } }, "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 } } } } } } } } } } ```