# Accor Category Scraper (`getdataforme/accor-category-scraper`) Actor Effortlessly extract comprehensive hotel data from Accor, including pricing, availability, amenities, ratings, reviews, and eco-certifications. Perfect for market research, competitive analysis, and price monitoring. Reliable scraping with structured JSON output for seamless integration.... - **URL**: https://apify.com/getdataforme/accor-category-scraper.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** E-commerce, Lead generation, Agents - **Stats:** 3 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $0.05 / actor start 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 ## Accor Category Scraper The Accor Category Scraper is a powerful Apify Actor designed to extract detailed hotel information from the Accor hotel group's website. It allows users to search for hotels based on specific check-in and check-out dates and locations, providing comprehensive data on availability, pricing, amenities, and more. This tool is ideal for travel agencies, researchers, and businesses needing accurate, up-to-date hotel data for analysis and decision-making. ### Features - **Comprehensive Data Extraction**: Scrapes detailed hotel profiles including names, locations, ratings, reviews, amenities, certifications, and images. - **Pricing and Availability Insights**: Retrieves real-time pricing, promotions, meal plans, and availability status for specified dates. - **Flexible Location-Based Search**: Supports searches by country or city, with default to "United States" for broad coverage. - **High Reliability**: Built on CheerioCrawler for efficient, error-resistant web scraping with built-in retries. - **Structured JSON Output**: Delivers clean, machine-readable data suitable for integration with databases or analytics tools. - **Performance Optimized**: Handles large-scale extractions quickly, minimizing resource usage. - **Customizable Inputs**: Accepts future dates only, ensuring relevance and avoiding outdated information. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|--------|----------|-----------------------------------------------------------------------------|------------------| | dateIn | string | Yes | The check-in date in YYYY-MM-DD format. Must be a future date. | "2026-03-24" | | dateOut | string | Yes | The check-out date in YYYY-MM-DD format. Must be a future date. | "2026-03-31" | | location | string | Yes | The location to search for hotels (e.g., city or country). | "United States" | ### Example Usage To run the Actor, provide the following input JSON: ```json { "dateIn": "2026-03-24", "dateOut": "2026-03-31", "location": "United States" } ```` Example output JSON (truncated for brevity): ```json [ { "hotelId": "0937", "hotelName": "Sofitel Los Angeles at Beverly Hills", "hotelCrs": "TARS", "brandCode": "SOF", "brandLabel": "Sofitel", "brandDescription": "Hotel combining French-style luxury and refined local cuisine", "city": "Los Angeles", "country": "United States", "countryCode": "US", "street": "8555 Beverly Blvd., 90048 Los Angeles, California", "zipCode": "90048", "ratingScore": 4.5, "numberOfReviews": 2681, "ratingOrigin": "TRUST_YOU", "stars": 4, "lodgingCode": "HTL", "lodgingLabel": "Hotel", "topAmenities": ["POOL", "PARKING", "PET"], "certifications": [ { "code": "ECO_CERTIFIED", "label": "Ecocertified", "description": "# What is an ecocertified hotel ? \r\n\r\nThis hotel has been awarded an ecolabel by an external, independent organization. Accor has been working for several years with labels such as Green Key or Green Globe to certify its hotels' commitments to sustainable tourism. \r\n\r\nTo obtain this certification, the hotel must comply with an extensive and demanding set of criteria each year, such as: \r\n\r\n1. Measuring and reducing carbon footprint and energy consumption; \r\n2. Measuring and reducing water consumption; \r\n3. Eliminating single-use plastics; \r\n4. Providing organic, local and/or seasonal food and beverage; \r\n5. Training hotel teams on environmental and social issues; \r\n6. Reducing food waste; \r\n7. Implementing initiatives to protect biodiversity around the hotel. \r\n\r\nWithin the Accor group, the aim is for all our hotels to obtain this type of label as a token of their environmental efforts. By August 2024, over 1,300 of the group's hotels had already obtained an ecolabel. \r\n" } ], "labels": [ { "code": "FAMILY_FRIENDLY", "label": "Family friendly", "description": "FAMILY_FRIENDLY" }, { "code": "FASTCOM", "label": "Fastcom", "description": "FASTCOM" }, { "code": "HIDDEN_MEMBER_RATE", "label": "", "description": "" } ], "totalImages": 71, "images": [ { "category": "HOTEL", "type": "IMAGE", "formats": [ { "url": "https://www.ahstatic.com/photos/0937_ho_00_p_120x90.jpg", "width": 120, "height": 90 }, { "url": "https://www.ahstatic.com/photos/0937_ho_00_p_346x260.jpg", "width": 346, "height": 260 }, { "url": "https://www.ahstatic.com/photos/0937_ho_00_p_1024x768.jpg", "width": 1024, "height": 768 }, { "url": "https://www.ahstatic.com/photos/0937_ho_00_p_2048x1536.jpg", "width": 2048, "height": 1536 }, { "url": "https://www.ahstatic.com/photos/0937_ho_00_p_3000x2250.jpg", "width": 3000, "height": 2250 } ] }, { "category": "HOTEL", "type": "IMAGE", "formats": [ { "url": "https://www.ahstatic.com/photos/0937_ho_01_p_120x90.jpg", "width": 120, "height": 90 }, { "url": "https://www.ahstatic.com/photos/0937_ho_01_p_346x260.jpg", "width": 346, "height": 260 }, { "url": "https://www.ahstatic.com/photos/0937_ho_01_p_1024x768.jpg", "width": 1024, "height": 768 }, { "url": "https://www.ahstatic.com/photos/0937_ho_01_p_2048x1536.jpg", "width": 2048, "height": 1536 }, { "url": "https://www.ahstatic.com/photos/0937_ho_01_p_3000x2250.jpg", "width": 3000, "height": 2250 } ] } ], "availabilityStatus": "AVAILABLE", "availabilityReasons": [], "distanceMeters": 1182276, "distanceFeet": 3878857, "dateIn": "2026-03-24", "rateId": "PROMRR", "rateLegacyId": "PROMRR-DR", "productId": "KGA", "productQuantity": 1, "adults": 1, "childrenAges": [], "babies": null, "lengthOfStayValue": 7, "lengthOfStayUnit": "NIGHT", "mealPlanCode": "EUROPEAN_PLAN", "mealPlanLabel": null, "currency": "EUR", "aggregationType": "TOTAL_STAY", "mainPrice": 2563.2, "mainPriceFormatted": "€2,564", "mainPriceLabel": "This accommodation also has a special offer", "mainPriceCategories": ["PROMOTION"], "referencePrice": "€2,775", "alternativePrice": 2390.36, "alternativePriceFormatted": "€2,391", "alternativePriceLabel": "This accommodation also has a special offer", "alternativePriceBookable": true, "deductionPercent": null, "deductionAmount": null, "deductionType": null, "offerCategories": [ { "code": "PROMOTION", "tag": "Discount -9%", "description": "Included: 9% discount.", "additionalTag": null } ], "loyaltyDinAndSpaRewardsAllowed": true, "loyaltyEarnAllowed": true, "loyaltyStatus": "PARTICIPATING_HOTEL", "paymentLabels": [], "remainingRooms": null, "offersCategories": [ { "code": "MEMBER_RATE", "label": null }, { "code": "DISABILITY_COMPLIANT", "label": null }, { "code": "STANDARD", "label": null } ], "scrapedAt": "2026-03-08T07:19:15.961Z", "searchDateIn": "2026-03-24", "searchDateOut": "2026-03-31", "searchLocation": "United States" } ] ``` ### Use Cases - **Market Research and Analysis**: Gather data on hotel offerings in specific regions to identify trends and opportunities. - **Competitive Intelligence**: Compare Accor hotels' pricing, amenities, and ratings against competitors. - **Price Monitoring**: Track promotional rates and availability for dynamic pricing strategies. - **Content Aggregation**: Build databases of hotel images, descriptions, and certifications for travel websites. - **Academic Research**: Study tourism patterns, sustainability certifications, and lodging preferences. - **Business Automation**: Integrate with travel booking systems for automated inventory checks and notifications. ### Installation and Usage 1. Search for "Accor Category Scraper" in the Apify Store 2. Click "Try for free" or "Run" 3. Configure input parameters 4. Click "Start" to begin extraction 5. Monitor progress in the log 6. Export results in your preferred format (JSON, CSV, Excel) ### Output Format The Actor outputs an array of JSON objects, each representing a hotel. Key fields include: - **hotelId**: Unique identifier for the hotel. - **hotelName**: Name of the hotel. - **city/country**: Location details. - **ratingScore/numberOfReviews**: Guest ratings and review counts. - **topAmenities/certifications**: Lists of amenities and eco-certifications. - **images**: Array of image URLs in various sizes. - **availabilityStatus/mainPrice**: Availability and pricing information, including promotions. - **scrapedAt**: Timestamp of data extraction. Data is structured for easy parsing and integration. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: https://getdataforme.com/contact/ We're here to help you get the most out of this Actor! *** Extract comprehensive hotel data from Accor with ease. Features include detailed pricing, availability, amenities, and eco-certifications. Perfect for market research, price monitoring, and competitive analysis. Try it now on Apify Store! (148 characters) # Actor input Schema ## `dateIn` (type: `string`): The date to start the crawl (YYYY-MM-DD). Must be a future date. ## `dateOut` (type: `string`): The date to end the crawl (YYYY-MM-DD). Must be a future date. ## `location` (type: `string`): Enter the Location ## Actor input object example ```json { "dateIn": "2026-03-24", "dateOut": "2026-03-31", "location": "United States" } ``` # 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 = { "dateIn": "2026-03-24", "dateOut": "2026-03-31" }; // Run the Actor and wait for it to finish const run = await client.actor("getdataforme/accor-category-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 = { "dateIn": "2026-03-24", "dateOut": "2026-03-31", } # Run the Actor and wait for it to finish run = client.actor("getdataforme/accor-category-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 '{ "dateIn": "2026-03-24", "dateOut": "2026-03-31" }' | apify call getdataforme/accor-category-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/accor-category-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Accor Category Scraper", "description": "Effortlessly extract comprehensive hotel data from Accor, including pricing, availability, amenities, ratings, reviews, and eco-certifications. Perfect for market research, competitive analysis, and price monitoring. Reliable scraping with structured JSON output for seamless integration....", "version": "0.0", "x-build-id": "RD6KTenNmffI4CQYA" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~accor-category-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-accor-category-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~accor-category-scraper/runs": { "post": { "operationId": "runs-sync-getdataforme-accor-category-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~accor-category-scraper/run-sync": { "post": { "operationId": "run-sync-getdataforme-accor-category-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": [ "dateIn", "dateOut", "location" ], "properties": { "dateIn": { "title": "Date In Must be a future date.", "pattern": "^(202[6-9]|20[3-9]\\d)-(0[1-9]|1[0-2])-(0[1-9]|[12]\\d|3[01])$", "type": "string", "description": "The date to start the crawl (YYYY-MM-DD). Must be a future date.", "default": "2026-03-24" }, "dateOut": { "title": "Date Out Must be a future date.", "pattern": "^(202[6-9]|20[3-9]\\d)-(0[1-9]|1[0-2])-(0[1-9]|[12]\\d|3[01])$", "type": "string", "description": "The date to end the crawl (YYYY-MM-DD). Must be a future date.", "default": "2026-03-31" }, "location": { "title": "Enter the Location ", "type": "string", "description": "Enter the Location", "default": "United States" } } }, "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 } } } } } } } } } } ```