# Tripadvisor Hotels Scraper (`cryptosignals/tripadvisor-hotels-scraper`) Actor Scrape TripAdvisor hotel listings with ratings, prices, and amenities - **URL**: https://apify.com/cryptosignals/tripadvisor-hotels-scraper.md - **Developed by:** [Web Data Labs](https://apify.com/cryptosignals) (community) - **Categories:** Travel - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, NaN 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 ## TripAdvisor Hotels Scraper Extract structured hotel data from TripAdvisor at scale — name, rating, review count, price per night, address, coordinates, and direct URL. No login, no API keys, no manual work. Just give it a city. ### What it does Given a city or region, this actor returns a clean JSON dataset of hotels listed on TripAdvisor for that location. Each record includes review-aggregated rating, review count, indicative nightly price, address, country, geo-coordinates, image URL and the canonical TripAdvisor URL — ready to drop into a database, spreadsheet or BI tool. It handles the messy parts for you: location-name normalization, listing pagination, rating extraction from multiple page layouts, and graceful retries when TripAdvisor throttles. You don't write a single selector. ### Who it's for - **Travel agencies & OTAs** building destination pages or comparison tools - **Price-comparison & meta-search** products that need TripAdvisor's review data alongside other sources - **Market research & consultancies** analyzing hospitality supply, pricing distribution, or rating sentiment per city - **Hotel chains & revenue managers** benchmarking against competitors in a market - **Data teams** that need a reliable hotel feed without owning the scraping infrastructure ### Inputs | Field | Type | Required | Default | Description | |-------|------|----------|---------|-------------| | `location` | string | Yes | `New York City` | City name. Common cities (50+) resolve instantly. Anything else is auto-resolved. | | `maxResults` | integer | No | `30` | Maximum number of hotels to return (1–100 recommended). | #### Example input ```json { "location": "Barcelona", "maxResults": 25 } ```` ### Outputs Each item in the dataset has the following shape: | Field | Type | Description | |-------|------|-------------| | `name` | string | Hotel name | | `url` | string | Canonical TripAdvisor hotel page URL | | `location` | string | City passed in the input | | `ratingScore` | number | Aggregate rating (0–5) | | `reviewCount` | integer | Number of reviews | | `pricePerNight` | integer | Indicative nightly price (in TripAdvisor's displayed currency) — may be null if not displayed | | `priceRange` | string | Price band when available (e.g. "$$$") | | `address` | string | Street address | | `addressLocality` | string | City / locality | | `addressCountry` | string | Country | | `latitude` | number | Geo latitude | | `longitude` | number | Geo longitude | | `imageUrl` | string | Lead image URL | | `telephone` | string | Phone number when listed | | `scrapedAt` | string | ISO 8601 timestamp of when the record was captured | #### Example output ```json { "name": "Hotel Casa Fuster", "url": "https://www.tripadvisor.com/Hotel_Review-g187497-d228719-Reviews-Hotel_Casa_Fuster.html", "location": "Barcelona", "ratingScore": 4.5, "reviewCount": 3812, "pricePerNight": 412, "priceRange": "$$$$", "address": "Passeig de Gracia 132", "addressLocality": "Barcelona", "addressCountry": "ES", "latitude": 41.398, "longitude": 2.161, "imageUrl": "https://media-cdn.tripadvisor.com/.../casa-fuster.jpg", "telephone": "+34 932 55 30 00", "scrapedAt": "2026-04-30T09:14:22.117Z" } ``` ### Pricing — Pay Per Event This actor uses **Pay Per Event (PPE)** billing: **$0.01 per hotel scraped**. You only pay for results — failed runs and partial pages are free. A 30-hotel run = **$0.30**. A 100-hotel run = **$1.00**. Predictable, transparent, no surprise compute bills. ### Free vs Paid Apify plans To protect new users from accidental over-runs, the actor caps **Free Apify plan** users at **5 hotels per run**. Paid Apify plans (Starter and above) get the full `maxResults` you request. Run it locally with the Apify CLI and there is no cap. ### How to use 1. Click **Start** with a `location` (any major city works — try "Tokyo", "Miami", "Barcelona"). 2. Set `maxResults` to how many hotels you want. 3. Get a clean JSON / CSV / Excel dataset within minutes. Export from the dataset tab or pull it via the Apify API. ### Tips - **Specific cities work best.** "Las Vegas" beats "Nevada". "Barcelona" beats "Spain". - **Run multiple cities in parallel** by triggering the actor several times — Apify queues them automatically. - **Schedule a daily run** to track price and rating changes over time. - **Pipe results into Google Sheets, Airtable, Snowflake, or anywhere else** via Apify integrations (Zapier, Make, webhooks). ### Reliability The actor uses Apify's residential proxy network and rotating browser fingerprints to behave like a real user. Rating, review count and address come from structured page metadata where present, with DOM fallbacks for pages that don't expose it. Pagination is handled automatically up to your `maxResults` cap. If you hit any issue, contact the maintainer through the actor's Issues tab — replies usually within 24 hours. ### Legal & ethics This actor scrapes only **publicly visible** information from TripAdvisor's listing pages — the same data any visitor sees in their browser. Use the resulting data responsibly and in line with TripAdvisor's Terms of Service for your jurisdiction. The actor does not bypass logins, paywalls or CAPTCHAs and does not harvest personal user data. # Actor input Schema ## `location` (type: `string`): City or destination to search for hotels (e.g. 'New York City', 'Paris, France') ## `maxResults` (type: `integer`): Maximum number of hotels to scrape ## Actor input object example ```json { "maxResults": 30 } ``` # 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("cryptosignals/tripadvisor-hotels-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 = {} # Run the Actor and wait for it to finish run = client.actor("cryptosignals/tripadvisor-hotels-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 '{}' | apify call cryptosignals/tripadvisor-hotels-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=cryptosignals/tripadvisor-hotels-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Tripadvisor Hotels Scraper", "description": "Scrape TripAdvisor hotel listings with ratings, prices, and amenities", "version": "0.1", "x-build-id": "JAmLotOmLadiYdvHc" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/cryptosignals~tripadvisor-hotels-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-cryptosignals-tripadvisor-hotels-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/cryptosignals~tripadvisor-hotels-scraper/runs": { "post": { "operationId": "runs-sync-cryptosignals-tripadvisor-hotels-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/cryptosignals~tripadvisor-hotels-scraper/run-sync": { "post": { "operationId": "run-sync-cryptosignals-tripadvisor-hotels-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "location" ], "properties": { "location": { "title": "Location", "type": "string", "description": "City or destination to search for hotels (e.g. 'New York City', 'Paris, France')" }, "maxResults": { "title": "Max Results", "maximum": 500, "type": "integer", "description": "Maximum number of hotels to scrape", "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 } } } } } } } } } } ```