# Booking.com Scraper (`nexgendata/booking-com-scraper`) Actor Extract hotel listings from Booking.com with prices, ratings, amenities, and availability. Power travel market research and competitive analysis. - **URL**: https://apify.com/nexgendata/booking-com-scraper.md - **Developed by:** [Stephan Corbeil](https://apify.com/nexgendata) (community) - **Categories:** Travel - **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $5.00 / 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 Scraper by nexgendata Scrape Booking.com for hotel listings with prices, review scores, availability, and property details. Search any destination worldwide with optional check-in and check-out dates to get real-time pricing data. Built for hotel revenue managers, travel industry analysts, and anyone who needs structured accommodation pricing data at scale. Booking.com lists over 28 million accommodation options across 226 countries and territories, making it the largest online travel agency by room count. The platform's pricing data reflects real-time market rates that hotels, vacation rentals, and alternative accommodations are actually charging. This makes Booking.com data uniquely valuable for pricing intelligence — unlike list prices or rack rates, these are the prices travelers actually see and book at. This actor extracts that pricing data into structured JSON for analysis. ### How It Works Enter a destination — a city name, region, or specific location — and optionally provide check-in and check-out dates. The actor searches Booking.com and extracts property data from the search results. Each listing includes the property name, nightly price, review score, review count, distance from center, and a direct URL to the property page. When dates are provided, prices reflect actual availability and rate for those specific dates. The actor first attempts to extract data from structured JSON-LD embedded in the page source, which provides the most reliable and consistent data format. When structured data is unavailable, it falls back to parsing the property card elements directly from the HTML. Both methods return the same standardized output format. ### Who Uses This Revenue managers at hotel chains and independent properties use Booking.com pricing data to set competitive rates. When a revenue manager can see what every competing hotel within a two-mile radius charges for a Tuesday night in April, they can position their own pricing with precision rather than guesswork. This actor enables daily or weekly rate audits across hundreds of competitive properties simultaneously. Online travel agencies and metasearch engines monitor Booking.com pricing to ensure their own rates are competitive. Travel industry analysts track accommodation pricing trends across markets to advise hospitality investors and operators. Short-term rental operators on platforms like Airbnb and Vrbo use hotel pricing data as a benchmark for their own rate strategies. Real estate investors evaluating hotel acquisition targets use Booking.com data to assess market positioning, pricing power, and competitive density. Destination marketing organizations monitor accommodation pricing to understand tourism economics in their region. Corporate travel managers track hotel rates across their commonly booked destinations to negotiate better corporate rates. ### Pricing This actor costs $5 per 1,000 results. Monitoring 200 hotels in a single city costs $1 per run. A weekly competitive audit across 20 cities (4,000 properties) costs $20/week. Monthly rate monitoring for a hotel chain tracking 500 competitor properties runs $2.50/month. Commercial hotel rate intelligence services charge $500-5,000/month for similar data — this delivers the same information at a fraction of the cost. # Actor input Schema ## `destination` (type: `string`): City, region, or hotel name to search for on Booking.com. ## `checkin` (type: `string`): Check-in date in YYYY-MM-DD format. Leave empty for default dates. ## `checkout` (type: `string`): Check-out date in YYYY-MM-DD format. Leave empty for default dates. ## `maxResults` (type: `integer`): Maximum number of hotels to return (1-100). ## Actor input object example ```json { "destination": "New York", "maxResults": 20 } ```` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "destination": "New York" }; // Run the Actor and wait for it to finish const run = await client.actor("nexgendata/booking-com-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "destination": "New York" } # Run the Actor and wait for it to finish run = client.actor("nexgendata/booking-com-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 '{ "destination": "New York" }' | apify call nexgendata/booking-com-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nexgendata/booking-com-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Booking.com Scraper", "description": "Extract hotel listings from Booking.com with prices, ratings, amenities, and availability. Power travel market research and competitive analysis.", "version": "0.0", "x-build-id": "MiNHd057epG8Tcvht" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nexgendata~booking-com-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nexgendata-booking-com-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nexgendata~booking-com-scraper/runs": { "post": { "operationId": "runs-sync-nexgendata-booking-com-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nexgendata~booking-com-scraper/run-sync": { "post": { "operationId": "run-sync-nexgendata-booking-com-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "destination" ], "properties": { "destination": { "title": "Destination", "type": "string", "description": "City, region, or hotel name to search for on Booking.com." }, "checkin": { "title": "Check-in Date", "type": "string", "description": "Check-in date in YYYY-MM-DD format. Leave empty for default dates." }, "checkout": { "title": "Check-out Date", "type": "string", "description": "Check-out date in YYYY-MM-DD format. Leave empty for default dates." }, "maxResults": { "title": "Max Results", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of hotels to return (1-100).", "default": 20 } } }, "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 } } } } } } } } } } ```