# Rappi Perú (`diegomedflo/rappi-peru`) Actor Extrae restaurantes y menús completos de Rappi Peru. Soporta 7 ciudades: Lima, Arequipa, Trujillo, Chiclayo, Piura, Cusco e Iquitos. Obtén nombre, dirección, rating, precio de delivery, horarios y menú con precios por producto. Sin login requerido. $0.001 por resultado. - **URL**: https://apify.com/diegomedflo/rappi-peru.md - **Developed by:** [Diego](https://apify.com/diegomedflo) (community) - **Categories:** E-commerce - **Stats:** 2 total users, 1 monthly users, 88.9% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $1.00 / 1,000 results This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. 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 ## Rappi Peru — Scraper de Restaurantes y Menús Extrae restaurantes y menús completos de **Rappi Peru** usando la plataforma [Apify](https://apify.com). No requiere login ni cuenta en Rappi. Disponible en el Apify Store: [diegomedflo/rappi-apify](https://apify.com/diegomedflo/rappi-apify) --- ### ¿Qué hace? - Obtiene todos los restaurantes disponibles en una ciudad peruana desde Rappi - Extrae el detalle completo de cada restaurante: nombre, dirección, rating, precio de delivery, tiempo estimado, horario - Opcionalmente descarga el menú completo por restaurante: categorías, productos, descripciones, precios e imágenes - Guarda los datos como registros JSON en el dataset de Apify — descargables en JSON, CSV o Excel --- ### Ciudades disponibles | Slug | Ciudad | |---|---| | `lima` | Lima | | `arequipa` | Arequipa | | `trujillo` | Trujillo | | `chiclayo` | Chiclayo | | `piura` | Piura | | `cusco` | Cusco | | `iquitos` | Iquitos | --- ### Parámetros de entrada | Campo | Tipo | Requerido | Descripción | |---|---|---|---| | `city` | string | ✅ | Slug de la ciudad (ej. `lima`) | | `mode` | string | ✅ | `restaurants` solo restaurantes, `restaurants_and_menu` incluye menú | | `lat` | number | ❌ | Latitud de entrega — afecta el ETA y precio de delivery. Por defecto usa el centro de la ciudad. | | `lng` | number | ❌ | Longitud de entrega | | `max_restaurants` | integer | ❌ | Límite de restaurantes a procesar | #### Ejemplo de entrada ```json { "city": "lima", "mode": "restaurants_and_menu", "lat": -12.097, "lng": -77.048, "max_restaurants": 20 } ```` *** ### Datos de salida Se generan dos tipos de registros en el dataset, identificados por el campo `record_type`. #### Registro de restaurante ```json { "record_type": "restaurant", "store_id": 4, "name": "Primos Chicken Bar Armendariz", "brand_name": "Primos Chicken Bar", "address": "Armendariz 546, Miraflores", "city": "lima", "location_lat": -12.1348, "location_lng": -77.0259, "rating_score": 3.7, "rating_reviews": 249, "delivery_price_soles": 1.9, "eta_minutes": 14, "eta_text": "14 min", "open_time": "11:30:00", "close_time": "23:00:00", "is_open_today": true, "menu_categories": 15, "menu_products": 80, "scraped_at": "2026-06-05T20:00:00Z" } ``` #### Registro de producto del menú (solo en modo `restaurants_and_menu`) ```json { "record_type": "menu_item", "store_id": 4, "restaurant_name": "Primos Chicken Bar Armendariz", "city": "lima", "category": "Combos", "product_name": "Pollo a la Brasa más Papas", "description": "Porción de pollo a la brasa con papas fritas", "price_soles": 95.0, "image_url": "https://images.rappi.pe/products/abc123.png", "scraped_at": "2026-06-05T20:00:00Z" } ``` *** ### Precios | Evento | Costo | Descripción | |---|---|---| | Inicio del actor | $0.05 | Cargo único por ejecución | | Por resultado | $0.001 | Por cada restaurante o producto extraído | | Escenario | Costo estimado | |---|---| | Lima, solo restaurantes (~52 tiendas) | ~$0.10 | | Arequipa, solo restaurantes (~30 tiendas) | ~$0.08 | | Lima, restaurantes + menú completo (~3500 items) | ~$3.60 | *** ### ¿Cómo usarlo? #### Desde la consola de Apify 1. Abre la [página del Actor](https://apify.com/diegomedflo/rappi-apify) 2. Completa el formulario de entrada (ciudad, modo) 3. Haz clic en **Start** 4. Descarga los resultados desde la pestaña **Dataset** en JSON, CSV o Excel #### Vía API REST ```bash curl -X POST "https://api.apify.com/v2/acts/diegomedflo~rappi-apify/runs" \ -H "Authorization: Bearer TU_API_TOKEN" \ -H "Content-Type: application/json" \ -d '{"city": "lima", "mode": "restaurants"}' ``` #### Vía SDK de Python ```python from apify_client import ApifyClient client = ApifyClient("TU_API_TOKEN") run = client.actor("diegomedflo/rappi-apify").call(run_input={ "city": "lima", "mode": "restaurants_and_menu", "max_restaurants": 10 }) dataset = client.dataset(run["defaultDatasetId"]).list_items().items ``` *** ### Uso local (CLI — genera archivos Excel) ```bash pip install requests beautifulsoup4 lxml pandas openpyxl python main.py ``` Sigue las instrucciones en consola para elegir ciudad y modo. Los archivos Excel se guardan en la misma carpeta del proyecto. *** ### Autor **Diego Medina** — [diegomedflo](https://github.com/diegomedflo) > Este Actor no está afiliado ni respaldado por Rappi. Solo accede a información públicamente disponible. # Actor input Schema ## `city` (type: `string`): Peruvian city to scrape restaurants from. ## `mode` (type: `string`): Choose what data to return. 'restaurants' returns store info only (fast). 'restaurants\_and\_menu' adds all menu items per restaurant (slower, costs more). ## `lat` (type: `number`): Optional. Latitude of the delivery address (affects delivery price and ETA estimates). If omitted, the city center coordinates are used. ## `lng` (type: `number`): Optional. Longitude of the delivery address (affects delivery price and ETA estimates). If omitted, the city center coordinates are used. ## `max_restaurants` (type: `integer`): Maximum number of restaurants to scrape. Leave empty to scrape all found on the city page (typically 30-60). ## Actor input object example ```json { "city": "lima", "mode": "restaurants", "lat": -12.097, "lng": -77.048 } ``` # Actor output Schema ## `restaurantes` (type: `string`): Dataset con todos los registros extraídos: restaurantes (record\_type='restaurant') y productos del menú (record\_type='menu\_item'). Descargable en JSON, CSV o Excel. # 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 = {}; // Run the Actor and wait for it to finish const run = await client.actor("diegomedflo/rappi-peru").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 = {} # Run the Actor and wait for it to finish run = client.actor("diegomedflo/rappi-peru").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 '{}' | apify call diegomedflo/rappi-peru --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=diegomedflo/rappi-peru", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Rappi Perú", "description": "Extrae restaurantes y menús completos de Rappi Peru. Soporta 7 ciudades: Lima, Arequipa, Trujillo, Chiclayo, Piura, Cusco e Iquitos. Obtén nombre, dirección, rating, precio de delivery, horarios y menú con precios por producto. Sin login requerido. $0.001 por resultado.", "version": "0.0", "x-build-id": "1zMg8Ics9IGz9gvlX" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/diegomedflo~rappi-peru/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-diegomedflo-rappi-peru", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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/diegomedflo~rappi-peru/runs": { "post": { "operationId": "runs-sync-diegomedflo-rappi-peru", "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/diegomedflo~rappi-peru/run-sync": { "post": { "operationId": "run-sync-diegomedflo-rappi-peru", "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": [ "city", "mode" ], "properties": { "city": { "title": "City", "enum": [ "lima", "arequipa", "trujillo", "chiclayo", "piura", "cusco", "iquitos" ], "type": "string", "description": "Peruvian city to scrape restaurants from.", "default": "lima" }, "mode": { "title": "Scrape Mode", "enum": [ "restaurants", "restaurants_and_menu" ], "type": "string", "description": "Choose what data to return. 'restaurants' returns store info only (fast). 'restaurants_and_menu' adds all menu items per restaurant (slower, costs more).", "default": "restaurants" }, "lat": { "title": "Delivery Latitude", "type": "number", "description": "Optional. Latitude of the delivery address (affects delivery price and ETA estimates). If omitted, the city center coordinates are used." }, "lng": { "title": "Delivery Longitude", "type": "number", "description": "Optional. Longitude of the delivery address (affects delivery price and ETA estimates). If omitted, the city center coordinates are used." }, "max_restaurants": { "title": "Max Restaurants", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of restaurants to scrape. Leave empty to scrape all found on the city page (typically 30-60)." } } }, "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 } } } } } } } } } } ```