# Rappi Restaurants Scraper - Cheap ๐Ÿšด๐Ÿ”๐ŸŒŽ (`scrapestorm/rappi-restaurants-scraper-cheap`) Actor Easily gather restaurant listings from Rappi. This tool automates restaurant data extraction, providing details like restaurant names, ratings โญ, delivery fees ๐Ÿšด, delivery times โฐ, images ๐Ÿ“ธ, and URLs ๐Ÿ”—. Ideal for market research, competitor tracking, and lead generation. - **URL**: https://apify.com/scrapestorm/rappi-restaurants-scraper-cheap.md - **Developed by:** [Storm\_Scraper](https://apify.com/scrapestorm) (community) - **Categories:** E-commerce, Lead generation, Travel - **Stats:** 9 total users, 0 monthly users, 0.0% runs succeeded, 1 bookmarks - **User rating**: No ratings yet ## Pricing $1.99 / 1,000 comments 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 ## ๐Ÿ” Rappi Restaurants Scraper ๐Ÿšด๐Ÿ“Š๐ŸŒŽ - Fast Restaurant Data Extraction The Rappi Restaurants Scraper is a fast, reliable, and powerful tool that extracts structured restaurant listings from Rappi, one of the largest food delivery platforms in Latin America. Whether you're monitoring restaurant listings, analyzing competitors, building lead databases, or tracking delivery marketplaces, this scraper delivers clean and structured Rappi restaurant data at scale โ€” instantly and with no coding required. --- ### ๐Ÿ” What This Scraper Does Simply provide one or multiple Rappi restaurant category/search URLs, and the scraper will return: โœ… All available restaurants matching your search (up to your selected limit) โœ… Clean, structured restaurant data including ratings, delivery information, images, and more | Field | Description | | ---------------- | ------------------------------------- | | `store_id` | Unique restaurant identifier on Rappi | | `name` | Restaurant name | | `rating` | Average customer rating | | `eta` | Estimated delivery time | | `delivery_price` | Delivery fee | | `image` | Main restaurant image URL | | `logo` | Restaurant logo URL | | `url` | Restaurant page URL | | `source_url` | Source search/category URL | โšก Average performance: Extracting 100โ€“200 restaurants usually takes 30โ€“60 seconds depending on category size and available listings. --- ### ๐Ÿ›  How to Use the Scraper #### 1๏ธโƒฃ Enter one or more Rappi restaurant URLs Examples: ```` urls = \[ "https://www.rappi.com.co/bello/restaurantes", "https://www.rappi.com.co/restaurantes" ] ``` #### 2๏ธโƒฃ Set your maximum items per URL ``` maxItems = 100 ``` #### 3๏ธโƒฃ Run the scraper Export your results in: * JSON * CSV * Excel * XML * HTML --- ### ๐Ÿ’ฐ Pricing This scraper uses a pay-per-event model. You are only charged for successful results. **Price: $1.99 per 1,000 results** --- ### ๐ŸŒŸ Why Use This Scraper? * ๐Ÿ• Restaurant Discovery โ€” Collect restaurant listings across cities and categories * ๐Ÿ“ˆ Lead Generation โ€” Build restaurant databases and contact datasets * ๐Ÿ”Ž Competitor Analysis โ€” Track restaurant visibility, ratings, and delivery metrics * ๐Ÿš€ Fast & Reliable โ€” Handles large restaurant listings smoothly * ๐ŸŒŽ Latin America Focused โ€” Optimized for Rappi marketplace data * ๐Ÿ“Š Marketplace Intelligence โ€” Analyze delivery trends and restaurant performance --- ### ๐Ÿ“ฅ Input Schema Input example: ``` { "urls": \[ "https://www.rappi.com.co/bello/restaurantes", "https://www.rappi.com.co/restaurantes" ], "maxItems": 100 } ``` Input fields: | Field | Type | Description | | ---------- | ------- | -------------------------------------------------------------- | | `urls` | array | List of Rappi restaurant category/search URLs | | `maxItems` | integer | Maximum number of restaurants to scrape per URL (default: 100) | --- ### ๐Ÿ“ค Output Example ``` { "store\_id": "900021278", "name": "Mis Carnes Parrilla", "rating": "4.5", "eta": "29 min", "delivery\_price": "$ 1.800", "image": "https://images.rappi.com/restaurants\_background/mscarnes1-1746742717044.jpg?e=webp\&q=40\&d=300x300", "logo": "https://images.rappi.com/restaurants\_logo/900010377-1516053536.png?d=10x10\&q=10\&e=webp", "url": "https://www.rappi.com.co/restaurantes/900021278-mis-carnes-parrilla", "source\_url": "https://www.rappi.com.co/bello/restaurantes" } ```` --- ### ๐Ÿงพ Output Explanation The output is a list of restaurant objects, each containing: **store_id** Unique restaurant identifier on Rappi **name** Restaurant name **rating** Average customer rating **eta** Estimated delivery time **delivery_price** Delivery fee for orders **image** Main restaurant image URL **logo** Restaurant logo image URL **url** Direct restaurant page URL **source_url** Original search/category URL used to collect the restaurant --- ### ๐Ÿ”ฅ Common Use Cases * Restaurant market research * Delivery platform monitoring * Competitor tracking * Restaurant lead generation * Food delivery analytics * Marketplace intelligence dashboards --- ### ๐Ÿ”Ž Powered by ScrapeStorm โœจ Start scraping Rappi restaurants like a pro โ€” no coding required! --- ### ๐Ÿ“ซ Support ๐Ÿ˜Š Leave us a star โญโญโญโญโญ if you are satisfied with the product! ๐ŸŒ For questions, feature requests, customizations, or issues, please reach out through Apify's platform or contact: **Storm_Scraper ๐ŸŒช๏ธ๐ŸŒฉ๏ธ** # Actor input Schema ## `urls` (type: `array`): List of Rappi restaurant page URLs to scrape. Example: https://www.rappi.com.co/bello/restaurantes or https://www.rappi.com.co/restaurantes ## `maxItems` (type: `integer`): Maximum number of restaurants to scrape per URL ## Actor input object example ```json { "urls": [ "https://www.rappi.com.co/bello/restaurantes", "https://www.rappi.com.co/restaurantes" ], "maxItems": 100 } ```` # 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 = { "urls": [ "https://www.rappi.com.co/bello/restaurantes", "https://www.rappi.com.co/restaurantes" ], "maxItems": 100 }; // Run the Actor and wait for it to finish const run = await client.actor("scrapestorm/rappi-restaurants-scraper-cheap").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`๐Ÿ’พ 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); }); // ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ 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 = { "urls": [ "https://www.rappi.com.co/bello/restaurantes", "https://www.rappi.com.co/restaurantes", ], "maxItems": 100, } # Run the Actor and wait for it to finish run = client.actor("scrapestorm/rappi-restaurants-scraper-cheap").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("๐Ÿ’พ Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # ๐Ÿ“š Want to learn more ๐Ÿ“–? Go to โ†’ https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{ "urls": [ "https://www.rappi.com.co/bello/restaurantes", "https://www.rappi.com.co/restaurantes" ], "maxItems": 100 }' | apify call scrapestorm/rappi-restaurants-scraper-cheap --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=scrapestorm/rappi-restaurants-scraper-cheap", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Rappi Restaurants Scraper - Cheap ๐Ÿšด๐Ÿ”๐ŸŒŽ", "description": "Easily gather restaurant listings from Rappi. This tool automates restaurant data extraction, providing details like restaurant names, ratings โญ, delivery fees ๐Ÿšด, delivery times โฐ, images ๐Ÿ“ธ, and URLs ๐Ÿ”—. Ideal for market research, competitor tracking, and lead generation.", "version": "0.0", "x-build-id": "7I18tQUoYSep1EUsQ" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/scrapestorm~rappi-restaurants-scraper-cheap/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-scrapestorm-rappi-restaurants-scraper-cheap", "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/scrapestorm~rappi-restaurants-scraper-cheap/runs": { "post": { "operationId": "runs-sync-scrapestorm-rappi-restaurants-scraper-cheap", "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/scrapestorm~rappi-restaurants-scraper-cheap/run-sync": { "post": { "operationId": "run-sync-scrapestorm-rappi-restaurants-scraper-cheap", "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": [ "urls" ], "properties": { "urls": { "title": "Rappi Search URLs", "type": "array", "description": "List of Rappi restaurant page URLs to scrape. Example: https://www.rappi.com.co/bello/restaurantes or https://www.rappi.com.co/restaurantes", "items": { "type": "string" } }, "maxItems": { "title": "Maximum items per URL", "type": "integer", "description": "Maximum number of restaurants to scrape per URL", "default": 100 } } }, "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 } } } } } } } } } } ```