# Swiggy Restaurant Scraper (`crawlerbros/swiggy-restaurant-scraper`) Actor Scrape swiggy.com for restaurant listings across Indian cities. - **URL**: https://apify.com/crawlerbros/swiggy-restaurant-scraper.md - **Developed by:** [Crawler Bros](https://apify.com/crawlerbros) (community) - **Categories:** Automation, E-commerce, Developer tools - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 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. 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 ## Swiggy Restaurant Scraper Scrape **swiggy.com** and extract structured data. Scrape Swiggy (swiggy.com) for restaurant listings across major Indian cities. Extract restaurant names, ratings, cuisines, delivery times, prices, and more. ### Features - Extract data from swiggy.com with no API key required - Filter results by multiple parameters - Automatic pagination — collects up to `maxItems` results - Outputs clean, omit-empty JSON records (no null fields) - Retries on rate limits and server errors ### Input Parameters | Parameter | Description | |-----------|-------------| | `city` | City to search (Mumbai, Delhi, Bangalore, Chennai, Hyderabad, Kolkata, Pune, Ahmedabad) | | `cuisine` | Filter by cuisine type (e.g. Indian, Chinese, Italian) | | `minRating` | Minimum average rating (1.0-5.0) | | `vegOnly` | Return only vegetarian restaurants (true/false) | | `maxItems` | Maximum number of results (1-500, default 20) | ### Output Format Each result is a JSON object with these fields: | Field | Description | |-------|-------------| | `restaurantId` | Unique Swiggy restaurant ID | | `name` | Restaurant name | | `city` | City | | `area` | Local area or neighbourhood | | `rating` | Average rating (0-5) | | `cuisines` | List of cuisine types | | `costForTwo` | Average cost for two people | | `deliveryTimeMinutes` | Estimated delivery time | | `imageUrl` | Restaurant banner image URL | | `isVeg` | Whether restaurant is vegetarian-only | | `sourceUrl` | Swiggy listing URL | ### Example Input ```json {"city": "Mumbai", "cuisine": "Indian", "maxItems": 5} ```` ### Example Output ```json {"restaurantId":"123","name":"Biryani Blues","city":"Mumbai","rating":4.2,"cuisines":["Indian","Mughlai"],"costForTwo":"₹300 for two","deliveryTimeMinutes":35} ``` ### FAQ **Is this free to use?** Yes — swiggy.com is publicly accessible and requires no authentication. **How many results can I get?** Set `maxItems` up to 500 per run. **Can I scrape specific URLs?** Yes — use `mode: "byUrl"` with a `startUrls` array. **What happens if the site is slow?** The actor automatically retries on 429/5xx errors with exponential backoff. ### Data Source Data is scraped from [swiggy.com](https://swiggy.com) — a publicly accessible website. # Actor input Schema ## `city` (type: `string`): Indian city to scrape restaurants from ## `cuisine` (type: `string`): Filter restaurants by cuisine type (e.g. 'pizza', 'biryani') ## `minRating` (type: `number`): Minimum rating filter (1.0 to 5.0) ## `vegOnly` (type: `boolean`): Return only vegetarian restaurants ## `maxItems` (type: `integer`): Maximum number of results to return ## Actor input object example ```json { "city": "mumbai", "vegOnly": false, "maxItems": 20 } ``` # Actor output Schema ## `results` (type: `string`): Dataset of scraped records. # 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 = { "city": "mumbai", "vegOnly": false, "maxItems": 20 }; // Run the Actor and wait for it to finish const run = await client.actor("crawlerbros/swiggy-restaurant-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 = { "city": "mumbai", "vegOnly": False, "maxItems": 20, } # Run the Actor and wait for it to finish run = client.actor("crawlerbros/swiggy-restaurant-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 '{ "city": "mumbai", "vegOnly": false, "maxItems": 20 }' | apify call crawlerbros/swiggy-restaurant-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=crawlerbros/swiggy-restaurant-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Swiggy Restaurant Scraper", "description": "Scrape swiggy.com for restaurant listings across Indian cities.", "version": "1.0", "x-build-id": "QPdfLi0Gak4tAdJ9L" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/crawlerbros~swiggy-restaurant-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-crawlerbros-swiggy-restaurant-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/crawlerbros~swiggy-restaurant-scraper/runs": { "post": { "operationId": "runs-sync-crawlerbros-swiggy-restaurant-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/crawlerbros~swiggy-restaurant-scraper/run-sync": { "post": { "operationId": "run-sync-crawlerbros-swiggy-restaurant-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "city": { "title": "City", "enum": [ "mumbai", "delhi", "bangalore", "hyderabad", "pune", "chennai", "kolkata", "ahmedabad" ], "type": "string", "description": "Indian city to scrape restaurants from", "default": "mumbai" }, "cuisine": { "title": "Cuisine Filter", "type": "string", "description": "Filter restaurants by cuisine type (e.g. 'pizza', 'biryani')" }, "minRating": { "title": "Min Rating", "minimum": 1, "maximum": 5, "type": "number", "description": "Minimum rating filter (1.0 to 5.0)" }, "vegOnly": { "title": "Veg Only", "type": "boolean", "description": "Return only vegetarian restaurants", "default": false }, "maxItems": { "title": "Max Items", "minimum": 1, "maximum": 500, "type": "integer", "description": "Maximum number of results to return", "default": 20 } } }, "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 } } } } } } } } } } ```