# Booking.com Hotels Listing Scraper (`parseforge/booking-com-hotels-scraper`) Actor Turn Booking.com search results into clean, structured hotel datasets. Capture pricing, ratings, reviews, room signals, cancellation flags, and location details to power travel analytics, competitive tracking, pricing intelligence, and recurring market research workflows.. - **URL**: https://apify.com/parseforge/booking-com-hotels-scraper.md - **Developed by:** [ParseForge](https://apify.com/parseforge) (community) - **Categories:** Travel, Developer tools, Automation - **Stats:** 31 total users, 17 monthly users, 97.7% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event 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 ![ParseForge Banner](https://github.com/ParseForge/apify-assets/blob/ad35ccc13ddd068b9d6cba33f323962e39aed5b2/banner.jpg?raw=true) ## 🏨 Booking.com Hotels Listing Scraper > πŸ•’ **Last updated:** 2026-05-05
Pull structured records from Booking.com Hotels Listing β€” clean fields ready as CSV, JSON, JSONL, Excel, or XML for downstream pipelines.
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Booking.com travel search
##### Copy to your AI assistant Copy this block into ChatGPT, Claude, Cursor, or any LLM to start using this actor. ```` parseforge/booking-com-hotels-scraper on Apify. Call: ApifyClient("TOKEN").actor("parseforge/booking-com-hotels-scraper").call(run\_input={...}), then client.dataset(run\["defaultDatasetId"]).list\_items().items for results. Key inputs: startUrl (string, default "https://www.booking.com/searchresults.en-gb.html?ss=Paris\&c), maxItems (integer, default 10), search (string), destination (string), propertyType (string), sortBy (string). Full actor spec: fetch build via GET https://api.apify.com/v2/acts/parseforge~booking-com-hotels-scraper (Bearer TOKEN). Get token: https://console.apify.com/account/integrations ```` Collect structured Booking.com hotel listing data from destination searches or direct Booking search URLs in minutes. This actor is built for travel analysts, pricing teams, market researchers, and operations teams that need clean listing data without manual browsing. Use it to track hotel prices, compare ratings, monitor review volumes, analyze cancellation policies, and export listing data for reporting, benchmarking, and travel market research. > **The Booking.com Hotels Listing Scraper returns 60+ structured output fields, including pricing, ratings, reviews, room offerings, policy flags, and listing-enriched metadata from Booking listing results.** ### ✨ What Does It Do - 🧭 Collect listings using either destination search inputs or a direct Booking search URL (`startUrl`). - πŸ’΅ Capture displayed price, original price, numeric price, currency, and pricing badges. - ⭐ Extract ratings, rating labels, review counts, star ratings, and external review signals. - πŸ›οΈ Parse room offering signals such as room type, occupancy, bed hints, and block pricing. - πŸ“ Capture address, city, coordinates, and distance-related fields for mapping and location analysis. - βœ… Extract policy fields like free cancellation, no prepayment, and sold-out indicators. - 🧩 Return listing-enriched fields directly from Booking listing results without requiring hotel page scraping. - πŸ“… Use check-in and check-out dates so Booking returns more realistic pricing for your stay window. ### πŸ”§ Input - **Start URL**: Paste one Booking search result URL. - **Max Items**: Maximum total listings to collect across the run. - **Destination**: Search by destination using `search` (or legacy `destination`) when not using `startUrl`. - **Property Type**: Filter by hotels, apartments, hostels, and more. - **Min Score / Stars / Price Range**: Filter by review score, star count, and price range. - **Sort By**: Choose Booking listing sort order. - **Check-in / Check-out**: Provide stay dates for realistic listing prices. - **Adults / Children / Rooms / Children Ages**: Adjust result set for your target traveler profile. - **Language / Currency / Flex Window**: Control localization and date flexibility behavior. - **Include Filter Metadata**: Include Booking filter/sorter metadata in output. - **Proxy Configuration**: Configure networking behavior for larger runs. Important mode rule: - Use `startUrl` **or** destination/filter inputs. - If both are provided, the actor returns an input error by design. Example JSON input: ```json { "startUrl": "https://www.booking.com/searchresults.en-gb.html?ss=Paris&checkin=2026-04-01&checkout=2026-04-04&group_adults=2&no_rooms=1&group_children=0", "maxItems": 50 } ```` ```json { "search": "Paris", "checkIn": "2026-04-01", "checkOut": "2026-04-04", "adults": 2, "rooms": 1, "maxItems": 100, "minScore": "8.5", "starsCountFilter": "4", "currency": "USD", "language": "en-gb" } ``` ### πŸ“Š Output Download your results in CSV, Excel, or JSON. | πŸ–ΌοΈ Image URL | πŸ†” Hotel ID | 🏨 Hotel Name | |---|---|---| | πŸ”— URL | πŸ’΅ Price | πŸ’± Currency | | ⭐ Rating | πŸ“ Reviews | 🏷️ Stars | | πŸ“ Location | πŸ™οΈ City | 🌍 Country | | 🧭 Coordinates | βœ… Free Cancellation | πŸ’³ No Prepayment | | πŸ›οΈ Room Offerings | 🧩 Listing-Enriched Fields | ⏱️ Scraped At | When available, the actor also returns richer listing fields such as distance metrics, discount/tax summaries, genius flags, sustainability hints, and room configuration metadata. ### πŸ’Ž Why Choose the Booking.com Hotels Listing Scraper? This actor combines destination search mode and direct search URL mode in one flow, so you can collect both broad market snapshots and reproducible URL-based datasets without switching tools. It also includes listing-enriched fields from Booking listing results, giving you deeper output than basic title/price scrapers. It is built for practical business workflows. You can filter by score, stars, price range, property type, date window, and guest profile, then export a flat dataset ready for pricing analysis, competitive benchmarking, destination intelligence, or travel reporting. ### πŸ“‹ How to Use No technical skills required. 1. **Sign Up**: [Create a free account w/ $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) 2. **Open the Actor**: Find the Booking.com Hotels Listing Scraper in the Apify Store. 3. **Set Your Input**: Use `startUrl` or destination/filter mode (not both). 4. **Run the Actor**: Start the run and let it collect listing data. 5. **Download the Results**: Export your dataset in CSV, Excel, or JSON. ### 🎯 Business Use Cases - **Travel Market Researchers** - Track hotel pricing shifts by destination and date windows. - Compare rating distributions and review counts by property type. - Build benchmark datasets for hotel demand and positioning analysis. - Monitor cancellation and prepayment trends across destinations. - **Revenue and Pricing Teams** - Compare competitor rate movements by neighborhood and stay period. - Analyze listing-level discounts, badges, and policy signals. - Export normalized datasets for BI dashboards and pricing models. - Run recurring snapshots for trend detection and alerts. *** *** ### ✨ Why choose this Actor | | Capability | |---|---| | 🎯 | **Built for the job.** Scoped specifically to this data source so you skip the parser engineering entirely. | | πŸ”– | **Structured output.** Clean, typed fields ready for analysis, dashboards, or downstream pipelines. | | ⚑ | **Fast.** Optimized request patterns return results in seconds, not minutes. | | πŸ” | **Always fresh.** Every run pulls live data, so the dataset reflects the source as of run time. | | 🌐 | **No infra to manage.** Apify handles proxies, retries, scaling, scheduling, and storage. | | πŸ›‘οΈ | **Reliable.** Battle-tested across many runs and edge cases, with graceful error handling. | | 🚫 | **No code required.** Configure in the UI, run from CLI, schedule via cron, or call from any language with the Apify SDK. | > πŸ“Š Production-grade structured data without the engineering overhead of building and maintaining your own scraper. *** ### πŸ“ˆ How it compares to alternatives | Approach | Cost | Coverage | Refresh | Filters | Setup | |---|---|---|---|---|---| | **⭐ Booking.com Hotels Listing Scraper** *(this Actor)* | $5 free credit, then pay-per-use | Full source coverage | **Live per run** | Source-native filters supported | ⚑ 2 min | | Build your own scraper | Engineering hours | Full once built | Whenever you maintain it | Custom code | 🐒 Days to weeks | | Paid managed APIs | $$$ monthly | Vendor-defined | Live | Vendor-defined | ⏳ Hours | | Third-party data dumps | Varies | Subset, often stale | Periodic | None | πŸ•’ Variable | Pick this Actor when you want broad coverage, server-side filtering, and no pipeline maintenance. *** ### πŸš€ How to use 1. πŸ“ **Sign up.** [Create a free account with $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) (takes 2 minutes). 2. 🌐 **Open the Actor.** Go to the Booking.com Hotels Listing Scraper page on the Apify Store. 3. 🎯 **Set input.** Configure the input fields in the form (or paste a JSON), then set `maxItems`. 4. πŸš€ **Run it.** Click **Start** and let the Actor collect your data. 5. πŸ“₯ **Download.** Grab your results in the **Dataset** tab as CSV, Excel, JSON, or XML. > ⏱️ Total time from signup to downloaded dataset: **3-5 minutes.** No coding required. *** ### πŸ’Ό Business use cases
#### πŸ“Š Data & Analytics - Build trend reports and dashboards from live source data - Feed BI tools, warehouses, and ML pipelines with structured records - Run periodic snapshots to track changes over time - Compare segments, regions, or categories with consistent fields #### 🏒 Operations & Strategy - Monitor competitor moves, pricing, and inventory shifts - Build internal directories and lookup tools backed by current data - Power workflows that depend on fresh source records - Cut manual data-gathering time from hours to minutes
#### 🎯 Marketing & Growth - Identify market opportunities and trending topics - Research target audiences and customer personas at scale - Power lead-generation pipelines with verified records - Track sentiment, reviews, or social signals over time #### πŸ› οΈ Engineering & Product - Prototype features that need real-world data without owning a crawler - Replace fragile in-house scrapers with a managed Actor - Wire datasets into your apps via the Apify API or webhooks - Skip the proxy, retry, and parsing maintenance entirely
*** ### 🌟 Beyond business use cases Data like this powers more than commercial workflows. The same structured records support research, education, civic projects, and personal initiatives.
#### πŸŽ“ Research and academia - Empirical datasets for papers, thesis work, and coursework - Longitudinal studies tracking changes across snapshots - Reproducible research with cited, versioned data pulls - Classroom exercises on data analysis and ethical scraping #### 🎨 Personal and creative - Side projects, portfolio demos, and indie app launches - Data visualizations, dashboards, and infographics - Content research for bloggers, YouTubers, and podcasters - Hobbyist collections and personal trackers
#### 🀝 Non-profit and civic - Transparency reporting and accountability projects - Advocacy campaigns backed by public-interest data - Community-run databases for local issues - Investigative journalism on public records #### πŸ§ͺ Experimentation - Prototype AI and machine-learning pipelines with real data - Validate product-market hypotheses before engineering spend - Train small domain-specific models on niche corpora - Test dashboard concepts with live input
### πŸ€– Ask an AI assistant about this scraper Open a ready-to-send prompt about this ParseForge actor in the AI of your choice: - πŸ’¬ [**ChatGPT**](https://chat.openai.com/?q=How%20do%20I%20use%20the%20Booking.com%20Hotels%20Listing%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - 🧠 [**Claude**](https://claude.ai/new?q=How%20do%20I%20use%20the%20Booking.com%20Hotels%20Listing%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - πŸ” [**Perplexity**](https://perplexity.ai/search?q=How%20do%20I%20use%20the%20Booking.com%20Hotels%20Listing%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) - πŸ…’ [**Copilot**](https://copilot.microsoft.com/?q=How%20do%20I%20use%20the%20Booking.com%20Hotels%20Listing%20Scraper%20by%20ParseForge%20on%20Apify%3F%20Show%20me%20input%20examples%2C%20output%20fields%2C%20common%20use%20cases%2C%20and%20how%20to%20integrate%20it%20into%20a%20workflow.) ### ❓ Frequently Asked Questions #### πŸ’³ Do I need a paid Apify plan to run this actor? No. You can start right now on the free Apify plan, which includes **$5 in free monthly credit**. That is enough to run this actor several times and explore the output before committing to anything. Paid plans unlock higher limits, more concurrent runs, and larger datasets. [Create a free Apify account here](https://console.apify.com/sign-up?fpr=vmoqkp) to get started. #### 🚨 What happens if my run fails or returns no results? Failed runs are not charged. If the source site changes, proxies get rate-limited, or a specific input matches nothing, re-run the actor or open our [contact form](https://tally.so/r/BzdKgA) and we will investigate. You can also check the run log in the Apify console to see why the run stopped. #### πŸ“ How many items can I scrape per run? Free users are limited to **10 items per run** so you can preview the output and confirm the actor works for your use case. Paid users can raise `maxItems` up to **1,000,000** per run. [Upgrade here](https://console.apify.com/sign-up?fpr=vmoqkp) if you need full scale. #### πŸ•’ How fresh is the data? Every run fetches live data at the moment of execution. There is no cache or delay: the records you get reflect what the source returned at that moment. Schedule the actor to maintain a rolling snapshot of the data you need. #### πŸ§‘β€πŸ’» Can I call this actor from my own code? Yes. Apify exposes every actor as a REST endpoint and ships first-class SDKs for [Node.js](https://docs.apify.com/sdk/js) and [Python](https://docs.apify.com/sdk/python). You can start a run, read the dataset, and handle webhooks from your own app in a few lines. All you need is your Apify API token. #### πŸ“€ How do I export the data? Every Apify dataset can be downloaded in one click from the console as CSV, JSON, JSONL, Excel, HTML, XML, or RSS. You can also pull results programmatically via the [Apify API](https://docs.apify.com/api/v2) or stream them into BigQuery, S3, and other destinations through built-in integrations. #### πŸ“… Can I schedule the actor to run automatically? Yes. Use the Apify scheduler to run the actor on any cadence, from hourly to monthly. Results are saved to your dataset and can be delivered to webhooks, email, Slack, cloud storage, or automation tools such as Zapier and Make. *** ### πŸ”Œ Integrate with any app Booking.com Hotels Listing Scraper connects to any cloud service via [Apify integrations](https://apify.com/integrations): - [**Make**](https://docs.apify.com/platform/integrations/make) - Automate multi-step workflows - [**Zapier**](https://docs.apify.com/platform/integrations/zapier) - Connect with 5,000+ apps - [**Slack**](https://docs.apify.com/platform/integrations/slack) - Get run notifications in your channels - [**Airbyte**](https://docs.apify.com/platform/integrations/airbyte) - Pipe results into your warehouse - [**GitHub**](https://docs.apify.com/platform/integrations/github) - Trigger runs from commits and releases - [**Google Drive**](https://docs.apify.com/platform/integrations/drive) - Export datasets straight to Sheets You can also use webhooks to trigger downstream actions when a run finishes. Push fresh data into your product backend, or alert your team in Slack. *** ### πŸ’‘ More ParseForge Actors - [Google Maps Scraper](https://apify.com/parseforge/google-maps-scraper) - Collect business data, coordinates, and location metadata. - [GovernmentJobs Scraper](https://apify.com/parseforge/governmentjobs-scraper) - Extract public-sector job listings and details. - [Dice Jobs Scraper](https://apify.com/parseforge/dice-jobs-scraper) - Scrape US tech job listings with filters and details. - [Airbnb Scraper](https://apify.com/parseforge/airbnb-scraper) - Collect rental listings, pricing, amenities, and host data. Browse our [complete collection of data extraction tools](https://apify.com/parseforge) for more. ### πŸš€ Ready to Start? [Create a free account w/ $5 credit](https://console.apify.com/sign-up?fpr=vmoqkp) and start collecting Booking listing data in minutes. ### πŸ†˜ Need Help? - Check the FAQ section above for common questions. - Visit the [Apify support page](https://docs.apify.com) for platform help and tutorials. - Use our [Tally contact form](https://tally.so/r/BzdKgA) for custom solutions, requests, or issue reporting. ### πŸ”— Recommended Actors - [**πŸ” Google Search Scraper**](https://apify.com/parseforge/google-search-scraper) - Multi-engine SERP results with country and language targeting - [**πŸ—ΊοΈ Nominatim OSM Scraper**](https://apify.com/parseforge/nominatim-osm-scraper) - Geocode addresses via OpenStreetMap - [**πŸ“Š Indexmundi Scraper**](https://apify.com/parseforge/indexmundi-scraper) - Global demographic and economic indicators - [**πŸ“° RAG Web Browser**](https://apify.com/parseforge/rag-web-browser) - Crawl and extract clean text from any URL for AI retrieval - [**🌐 Website Content Crawler**](https://apify.com/parseforge/website-content-crawler) - Crawl entire sites and export structured content > πŸ’‘ **Pro Tip:** browse the complete [ParseForge collection](https://apify.com/parseforge) for more reference-data scrapers. *** ### ❌ Disclaimer > **This Actor is an independent tool and is not affiliated with, endorsed by, or sponsored by Booking.com or any of its subsidiaries. All trademarks mentioned are the property of their respective owners.** # Actor input Schema ## `startUrl` (type: `string`): Optional Booking search URL to start from. ## `maxItems` (type: `integer`): Maximum number of hotels to scrape. ## `search` (type: `string`): Destination query, for example Paris or New York. ## `destination` (type: `string`): Legacy field kept for backward compatibility. ## `propertyType` (type: `string`): Filter by property type. ## `sortBy` (type: `string`): Booking sorter key. ## `minScore` (type: `string`): Minimum hotel rating in format like 8.4. ## `starsCountFilter` (type: `string`): Filter by stars count. ## `minMaxPrice` (type: `string`): Price filter format: 100-150 or 100+. ## `currency` (type: `string`): Currency code sent to Booking URL params. ## `language` (type: `string`): Language sent to Booking endpoints. ## `checkIn` (type: `string`): YYYY-MM-DD or relative format like 3 days. ## `checkOut` (type: `string`): YYYY-MM-DD or relative format like 5 days. ## `checkinDate` (type: `string`): Legacy date field in YYYY-MM-DD format. ## `checkoutDate` (type: `string`): Legacy date field in YYYY-MM-DD format. ## `flexWindow` (type: `string`): Accepted values: 0,1,2,3,7. ## `adults` (type: `integer`): Number of adults for the stay. ## `children` (type: `integer`): Number of children for the stay. ## `rooms` (type: `integer`): Number of rooms to request in search. ## `childrenAges` (type: `string`): Optional children ages as comma-separated values, for example 4,7. ## `includeFilterMetadata` (type: `boolean`): Include available filter and sorter metadata in the first output item. ## `proxyConfiguration` (type: `object`): Residential proxies are recommended for Booking.com. ## Actor input object example ```json { "startUrl": "https://www.booking.com/searchresults.en-gb.html?ss=Paris&checkin=2026-04-01&checkout=2026-04-04&group_adults=2&no_rooms=1&group_children=0", "maxItems": 10, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } } ``` # Actor output Schema ## `overview` (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 = { "startUrl": "https://www.booking.com/searchresults.en-gb.html?ss=Paris&checkin=2026-04-01&checkout=2026-04-04&group_adults=2&no_rooms=1&group_children=0", "maxItems": 10, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }; // Run the Actor and wait for it to finish const run = await client.actor("parseforge/booking-com-hotels-scraper").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`πŸ’Ύ 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); }); // πŸ“š Want to learn more πŸ“–? Go to β†’ 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 = { "startUrl": "https://www.booking.com/searchresults.en-gb.html?ss=Paris&checkin=2026-04-01&checkout=2026-04-04&group_adults=2&no_rooms=1&group_children=0", "maxItems": 10, "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], }, } # Run the Actor and wait for it to finish run = client.actor("parseforge/booking-com-hotels-scraper").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("πŸ’Ύ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # πŸ“š Want to learn more πŸ“–? Go to β†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "startUrl": "https://www.booking.com/searchresults.en-gb.html?ss=Paris&checkin=2026-04-01&checkout=2026-04-04&group_adults=2&no_rooms=1&group_children=0", "maxItems": 10, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ] } }' | apify call parseforge/booking-com-hotels-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=parseforge/booking-com-hotels-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Booking.com Hotels Listing Scraper", "description": "Turn Booking.com search results into clean, structured hotel datasets. Capture pricing, ratings, reviews, room signals, cancellation flags, and location details to power travel analytics, competitive tracking, pricing intelligence, and recurring market research workflows..", "version": "1.0", "x-build-id": "wFvJpw519inEstPxX" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/parseforge~booking-com-hotels-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-parseforge-booking-com-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/parseforge~booking-com-hotels-scraper/runs": { "post": { "operationId": "runs-sync-parseforge-booking-com-hotels-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/parseforge~booking-com-hotels-scraper/run-sync": { "post": { "operationId": "run-sync-parseforge-booking-com-hotels-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "properties": { "startUrl": { "title": "Start URL", "type": "string", "description": "Optional Booking search URL to start from." }, "maxItems": { "title": "Max results", "minimum": 1, "maximum": 1000000, "type": "integer", "description": "Maximum number of hotels to scrape." }, "search": { "title": "Destination", "type": "string", "description": "Destination query, for example Paris or New York." }, "destination": { "title": "Destination (Legacy)", "type": "string", "description": "Legacy field kept for backward compatibility." }, "propertyType": { "title": "Property type", "enum": [ "none", "Hotels", "Apartments", "Hostels", "Guest houses", "Homestays", "Bed and breakfasts", "Holiday homes", "Boats", "Villas", "Motels", "Resorts", "Holiday parks", "Campsites", "Luxury tents" ], "type": "string", "description": "Filter by property type." }, "sortBy": { "title": "Order results by", "enum": [ "bayesian_review_score", "distance_from_search", "class_asc", "price", "review_score_and_price", "class_and_price" ], "type": "string", "description": "Booking sorter key." }, "minScore": { "title": "Minimum rating", "type": "string", "description": "Minimum hotel rating in format like 8.4." }, "starsCountFilter": { "title": "Stars count", "enum": [ "any", "1", "2", "3", "4", "5", "unrated" ], "type": "string", "description": "Filter by stars count." }, "minMaxPrice": { "title": "Price range", "type": "string", "description": "Price filter format: 100-150 or 100+." }, "currency": { "title": "Preferred currency", "type": "string", "description": "Currency code sent to Booking URL params." }, "language": { "title": "Language", "type": "string", "description": "Language sent to Booking endpoints." }, "checkIn": { "title": "Check-in date", "type": "string", "description": "YYYY-MM-DD or relative format like 3 days." }, "checkOut": { "title": "Check-out date", "type": "string", "description": "YYYY-MM-DD or relative format like 5 days." }, "checkinDate": { "title": "Check-in Date (Legacy)", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "Legacy date field in YYYY-MM-DD format." }, "checkoutDate": { "title": "Check-out Date (Legacy)", "pattern": "^\\d{4}-\\d{2}-\\d{2}$", "type": "string", "description": "Legacy date field in YYYY-MM-DD format." }, "flexWindow": { "title": "Stay date flexibility (days)", "enum": [ "0", "1", "2", "3", "7" ], "type": "string", "description": "Accepted values: 0,1,2,3,7." }, "adults": { "title": "Adults", "minimum": 1, "maximum": 50, "type": "integer", "description": "Number of adults for the stay." }, "children": { "title": "Children", "minimum": 0, "maximum": 50, "type": "integer", "description": "Number of children for the stay." }, "rooms": { "title": "Rooms", "minimum": 1, "maximum": 50, "type": "integer", "description": "Number of rooms to request in search." }, "childrenAges": { "title": "Children Ages", "type": "string", "description": "Optional children ages as comma-separated values, for example 4,7." }, "includeFilterMetadata": { "title": "Include available filters metadata", "type": "boolean", "description": "Include available filter and sorter metadata in the first output item." }, "proxyConfiguration": { "title": "Proxy Configuration", "type": "object", "description": "Residential proxies are recommended for Booking.com." } } }, "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 } } } } } } } } } } ```