# Booking.com Hotel Price Tracker — Compare Hotel Prices (`apikiy/booking-price-tracker`) Actor An Apify Actor that scrapes hotel search results from [Booking.com](https://www.booking.com). Extract prices, ratings, reviews, amenities, and booking links for - **URL**: https://apify.com/apikiy/booking-price-tracker.md - **Developed by:** [Julien ApiKiy](https://apify.com/apikiy) (community) - **Categories:** Travel - **Stats:** 1 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 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 ## Booking.com Hotel Price Tracker An Apify Actor that scrapes hotel search results from [Booking.com](https://www.booking.com). Extract prices, ratings, reviews, amenities, and booking links for any destination and date range. ### Features - **Multi-destination search** — search multiple cities/destinations in one run - **Rich data extraction** — hotel name, price per night, total price, rating, review count, star rating, address, distance from center, image URL, booking URL, amenities - **Pagination support** — automatically navigates through result pages - **Anti-detection** — random delays, user-agent rotation, cookie consent dismissal, viewport randomization - **No proxy required** — works from datacenter IPs ### Input | Field | Type | Default | Description | |-------|------|---------|-------------| | `searchQueries` | `string[]` | *required* | List of destinations to search | | `checkIn` | `string` | *required* | Check-in date (YYYY-MM-DD) | | `checkOut` | `string` | *required* | Check-out date (YYYY-MM-DD) | | `guests` | `number` | `2` | Number of adult guests | | `maxResults` | `number` | `20` | Max results per destination | | `maxConcurrency` | `number` | `2` | Browser pages in parallel | #### Example Input ```json { "searchQueries": ["Paris", "London", "Barcelona"], "checkIn": "2026-09-01", "checkOut": "2026-09-05", "guests": 2, "maxResults": 10, "maxConcurrency": 2 } ```` ### Output Each item in the dataset: ```json { "hotelName": "Grand Hotel Paris", "pricePerNight": 189, "totalPrice": 756, "rating": 8.7, "reviewCount": 2345, "starRating": 4, "address": "15 Rue de Rivoli, Paris", "distanceFromCenter": "0.5 km from city centre", "imageUrl": "https://cf.bstatic.com/xdata/hotel.jpg", "bookingUrl": "https://www.booking.com/hotel/grand-hotel-paris.html", "amenities": ["WiFi", "Pool"], "destination": "Paris", "scrapedAt": "2026-09-01T12:00:00.000Z" } ``` ### How It Works 1. Builds Booking.com search URLs from your input parameters 2. Launches headless Chrome via PlaywrightCrawler 3. Dismisses cookie consent banners 4. Extracts hotel data from search result cards using multiple fallback selectors 5. Handles pagination to collect the requested number of results 6. Pushes all results to the default dataset ### Anti-Detection - Random user-agent rotation (8 real browser UAs) - Random viewport sizes (1280–1920 × 720–1080) - Random delays between actions (2–5 seconds) - Cookie consent auto-dismissal - WebDriver detection override ### Running Locally ```bash ## Install dependencies npm install ## Run tests npm test ## Run the actor (with Apify CLI) apify run ## Or run directly npm start ``` ### Running with Docker ```bash docker build -t booking-price-tracker . docker run -e APIFY_TOKEN=your_token booking-price-tracker ``` ### Testing ```bash npm test ``` Tests use ESM, `node:assert`, and Mocha. No proxy or external services needed. ### 💰 Pricing Pay-per-use, no monthly fees: | | Price | |---|---| | **Actor start** | $0.01 | | **Per result** | $0.01 | > 💡 Example: A run returning 500 results costs **$5.01** total ($0.01 start + 500 × $0.01). ### License MIT # Actor input Schema ## `searchQueries` (type: `array`): List of destinations or hotel names to search for on Booking.com ## `checkIn` (type: `string`): Check-in date in YYYY-MM-DD format ## `checkOut` (type: `string`): Check-out date in YYYY-MM-DD format ## `guests` (type: `integer`): Number of adult guests ## `maxResults` (type: `integer`): Maximum number of hotel results to extract per search query ## `maxConcurrency` (type: `integer`): Maximum number of browser pages to run in parallel ## Actor input object example ```json { "searchQueries": [ "Paris" ], "checkIn": "2026-08-01", "checkOut": "2026-08-02", "guests": 2, "maxResults": 20, "maxConcurrency": 2 } ``` # Actor output Schema ## `results` (type: `string`): No description # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "searchQueries": [ "Paris" ], "checkIn": "2026-08-01", "checkOut": "2026-08-02" }; // Run the Actor and wait for it to finish const run = await client.actor("apikiy/booking-price-tracker").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "searchQueries": ["Paris"], "checkIn": "2026-08-01", "checkOut": "2026-08-02", } # Run the Actor and wait for it to finish run = client.actor("apikiy/booking-price-tracker").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 '{ "searchQueries": [ "Paris" ], "checkIn": "2026-08-01", "checkOut": "2026-08-02" }' | apify call apikiy/booking-price-tracker --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=apikiy/booking-price-tracker", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Booking.com Hotel Price Tracker — Compare Hotel Prices", "description": "An Apify Actor that scrapes hotel search results from [Booking.com](https://www.booking.com). Extract prices, ratings, reviews, amenities, and booking links for", "version": "0.1", "x-build-id": "mHBjxqmWQFy03zhcj" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/apikiy~booking-price-tracker/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-apikiy-booking-price-tracker", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/apikiy~booking-price-tracker/runs": { "post": { "operationId": "runs-sync-apikiy-booking-price-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/apikiy~booking-price-tracker/run-sync": { "post": { "operationId": "run-sync-apikiy-booking-price-tracker", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "searchQueries": { "title": "Search Queries", "type": "array", "description": "List of destinations or hotel names to search for on Booking.com", "items": { "type": "string" }, "default": [ "Paris" ] }, "checkIn": { "title": "Check-in Date", "type": "string", "description": "Check-in date in YYYY-MM-DD format", "default": "2026-08-01" }, "checkOut": { "title": "Check-out Date", "type": "string", "description": "Check-out date in YYYY-MM-DD format", "default": "2026-08-02" }, "guests": { "title": "Number of Guests", "minimum": 1, "maximum": 30, "type": "integer", "description": "Number of adult guests", "default": 2 }, "maxResults": { "title": "Max Results per Query", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of hotel results to extract per search query", "default": 20 }, "maxConcurrency": { "title": "Max Concurrency", "minimum": 1, "maximum": 10, "type": "integer", "description": "Maximum number of browser pages to run in parallel", "default": 2 } } }, "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", 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