# Expedia Hotel Scraper (`jungle_synthesizer/expedia-scraper`) Actor Extract hotel listings from Expedia including property name, star rating, guest reviews, price per night, amenities, and location. Filter by destination, check-in/check-out dates, and guest count. - **URL**: https://apify.com/jungle\_synthesizer/expedia-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Travel, Lead generation - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $2.40 / 1,000 record scrapeds 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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows. 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/docs.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python/docs.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/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 ## Expedia Hotel Scraper Extract hotel listings from **Expedia** — property name, star rating, guest review score, price per night, total stay price, location, and image. Search any destination with your own check-in / check-out dates and guest count. --- ### What you get Each hotel record contains: | Field | Description | |-------|-------------| | `hotelId` | Expedia property ID | | `name` | Hotel name | | `link` | Expedia hotel listing URL | | `starRating` | Star rating (1–5) | | `guestRating` | Guest review score (e.g. `8.4/10 Excellent`) | | `reviewCount` | Number of guest reviews | | `pricePerNight` | Price per night for the selected dates | | `totalPrice` | Total price for the stay | | `neighborhood` | Neighborhood or area within the destination | | `distanceFromCenter` | Distance from city center or landmark | | `imageUrl` | URL of the hotel's main image | | `destination` / `checkIn` / `checkOut` | The search parameters used for this record | | `scrapedAt` | ISO-8601 timestamp of extraction | --- ### Input | Parameter | Type | Default | Description | |-----------|------|---------|-------------| | `destination` | string | — | City, region, or destination (e.g. `New York`, `Paris`, `Las Vegas`). | | `checkIn` | string | +30 days | Check-in date `YYYY-MM-DD`. Defaults to 30 days out. | | `checkOut` | string | checkIn +2 | Check-out date `YYYY-MM-DD`. Defaults to check-in + 2 nights. | | `adults` | integer | `2` | Number of adult guests per room. | | `rooms` | integer | `1` | Number of rooms. | | `maxItems` | integer | `10` | Maximum number of hotels to return. | #### Example ```json { "destination": "Las Vegas", "checkIn": "2026-09-01", "checkOut": "2026-09-04", "adults": 2, "rooms": 1, "maxItems": 50 } ```` *** ### How it works 1. Builds the Expedia search for your destination and dates. 2. Fetches the results through a hardened unblocking layer that clears Expedia's bot protection. 3. Parses each property card — name, rating, review score, nightly and total price, location, image. 4. Returns up to `maxItems` hotels. *** ### Who it's for - **Travel & OTA analysts** tracking hotel rates and availability across destinations. - **Revenue managers** benchmarking competitor pricing by date and market. - **Deal & metasearch sites** enriching hotel inventory with live Expedia prices and review scores. *** ### Notes - Prices reflect the selected dates and guest/room count at scrape time and can change frequently. - Provide precise `checkIn` / `checkOut` dates for accurate nightly and total pricing. # Actor input Schema ## `sp_intended_usage` (type: `string`): What will this data feed? E.g. lead lists, KYB checks, price tracking. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): We'll personally help with your use case. No spam. ## `resumeCursor` (type: `string`): Leave empty for a fresh crawl. To CONTINUE a previous run where it stopped — without paying again for records you already received — paste the `resumeCursor` value from that run's Output (the run's OUTPUT key). Resume promptly: the previous run's data expires with your account's retention window (free tier: your ~10 most recent runs). ## `destination` (type: `string`): City, region, or destination to search for hotels (e.g. 'New York', 'Paris', 'Las Vegas') ## `checkIn` (type: `string`): Check-in date in YYYY-MM-DD format. Defaults to 30 days from today. ## `checkOut` (type: `string`): Check-out date in YYYY-MM-DD format. Defaults to check-in + 2 nights. ## `adults` (type: `integer`): Number of adult guests per room ## `rooms` (type: `integer`): Number of rooms ## `minStarRating` (type: `integer`): Filter results to this minimum star rating (1-5) ## `maxItems` (type: `integer`): Maximum number of hotel listings to return ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "destination": "New York", "adults": 2, "rooms": 1, "minStarRating": 1, "maxItems": 15 } ``` # 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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "destination": "New York", "checkIn": "", "checkOut": "", "adults": 2, "rooms": 1, "minStarRating": 1, "maxItems": 15 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/expedia-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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "destination": "New York", "checkIn": "", "checkOut": "", "adults": 2, "rooms": 1, "minStarRating": 1, "maxItems": 15, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/expedia-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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "destination": "New York", "checkIn": "", "checkOut": "", "adults": 2, "rooms": 1, "minStarRating": 1, "maxItems": 15 }' | apify call jungle_synthesizer/expedia-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/expedia-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Expedia Hotel Scraper", "description": "Extract hotel listings from Expedia including property name, star rating, guest reviews, price per night, amenities, and location. Filter by destination, check-in/check-out dates, and guest count.", "version": "0.1", "x-build-id": "QJDBK45cXXP91a9Al" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~expedia-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-expedia-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jungle_synthesizer~expedia-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-expedia-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jungle_synthesizer~expedia-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-expedia-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "What will this data feed? E.g. lead lists, KYB checks, price tracking." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact email (optional)", "minLength": 1, "type": "string", "description": "We'll personally help with your use case. No spam." }, "resumeCursor": { "title": "Resume cursor (continue a previous run)", "type": "string", "description": "Leave empty for a fresh crawl. To CONTINUE a previous run where it stopped — without paying again for records you already received — paste the `resumeCursor` value from that run's Output (the run's OUTPUT key). Resume promptly: the previous run's data expires with your account's retention window (free tier: your ~10 most recent runs)." }, "destination": { "title": "Destination", "type": "string", "description": "City, region, or destination to search for hotels (e.g. 'New York', 'Paris', 'Las Vegas')" }, "checkIn": { "title": "Check-in Date", "type": "string", "description": "Check-in date in YYYY-MM-DD format. Defaults to 30 days from today." }, "checkOut": { "title": "Check-out Date", "type": "string", "description": "Check-out date in YYYY-MM-DD format. Defaults to check-in + 2 nights." }, "adults": { "title": "Number of Adults", "minimum": 1, "maximum": 8, "type": "integer", "description": "Number of adult guests per room" }, "rooms": { "title": "Number of Rooms", "minimum": 1, "maximum": 8, "type": "integer", "description": "Number of rooms" }, "minStarRating": { "title": "Minimum Star Rating", "minimum": 1, "maximum": 5, "type": "integer", "description": "Filter results to this minimum star rating (1-5)" }, "maxItems": { "title": "Max Items", "minimum": 1, "type": "integer", "description": "Maximum number of hotel listings to return", "default": 15 } } }, "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 } } } } } } } } } } ```