# Swiggy Restaurant Scraper - Listings, Ratings & Delivery Data (`fascinating_lentil/swiggy-restaurant-scraper`) Actor Scrape public Swiggy restaurant listings with names, cuisines, ratings, delivery time, cost for two, offers, locality, image URLs, and restaurant URLs. - **URL**: https://apify.com/fascinating\_lentil/swiggy-restaurant-scraper.md - **Developed by:** [Md Jakaria Mirza](https://apify.com/fascinating_lentil) (community) - **Categories:** Other, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 restaurant scrapeds 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 ## Swiggy Restaurant Scraper - Listings, Ratings & Delivery Data Scrape public Swiggy restaurant listing data by city, locality, and cuisine. This Actor collects restaurant names, cuisine types, ratings, rating counts, cost for two, delivery time, distance, visible offers, vegetarian status, locality, image URLs, and Swiggy restaurant URLs. It is designed for food delivery research, restaurant market analysis, competitor monitoring, pricing intelligence, and local restaurant discovery datasets. The scraper uses Swiggy's public web JSON responses with optional Apify Proxy routing, retries, and random waits for stable public listing collection. This Actor extracts public business listing facts only. It does not collect phone numbers, emails, customer data, private account data, or personal profiles. ### Use Cases - Food delivery market research by city and cuisine. - Restaurant competitor tracking across local Swiggy listings. - Rating, delivery time, and visible offer analysis. - Local restaurant discovery for BI dashboards and maps. - Food-tech datasets for pricing, cuisine, and availability trends. ### Input ```json { "cities": ["Bangalore"], "localities": [], "cuisines": ["Chinese"], "sortBy": "RELEVANCE", "maxResults": 10, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "IN" } } ```` ### Output ```json { "source": "swiggy", "imageUrl": "https://media-assets.swiggy.com/swiggy/image/upload/...", "searchCity": "Bangalore", "searchLocality": null, "searchCuisine": "Chinese", "position": 1, "restaurantId": "123456", "restaurantName": "Example Kitchen", "cuisineTypes": ["Chinese", "Asian"], "costForTwo": "₹500 for two", "priceForTwo": 500, "overallRating": 4.2, "totalRatingsCount": 1200, "deliveryTimeEstimate": 32, "distance": "2.1 km", "offersAndDiscounts": ["20% off"], "pureVeg": false, "openClosedStatus": true, "locality": "Indiranagar", "city": "Bangalore", "promotedSponsored": false, "restaurantUrl": "https://www.swiggy.com/restaurants/example-kitchen-123456", "scrapedAt": "2026-06-13T12:00:00.000Z" } ``` ### How to Scrape Swiggy Restaurants 1. Enter one or more Indian cities, for example `Bangalore`, `Mumbai`, `Delhi`, `Pune`, or `Hyderabad`. 2. Optionally add localities or cuisine filters. 3. Set `maxResults` to control how many unique restaurants are saved. 4. Run the Actor. 5. Export results as JSON, CSV, Excel, or via API. ### Pricing | Event | Price | When charged | | --- | ---: | --- | | `restaurant-scraped` | `$0.003` | Once per clean restaurant record saved to the dataset | The Actor charges only after a restaurant record is successfully saved. ### Notes - Swiggy pages can vary by city, locality, and region. - Some fields may be `null` when Swiggy does not show them on the listing page. - India residential proxies are recommended for reliable regional access. ### Responsible Use This Actor is intended for lawful collection of publicly available information only. Users are responsible for ensuring their use complies with the source website's terms, robots.txt, applicable privacy laws, including India's DPDP Act, and all local regulations. Do not use this Actor to collect, store, sell, or misuse personal data without a lawful basis. The Actor author is not responsible for misuse by end users. ### License Apache-2.0 # Actor input Schema ## `cities` (type: `array`): Cities to scrape, for example Bangalore, Mumbai, Delhi, Pune, Hyderabad, Chennai, Kolkata, or Ahmedabad. ## `localities` (type: `array`): Optional areas within the city. Leave empty to search the city page. ## `cuisines` (type: `array`): Optional cuisine filters such as Chinese, North Indian, Italian, Biryani, or South Indian. ## `sortBy` (type: `string`): Preferred result sorting when Swiggy exposes sorting controls. ## `maxResults` (type: `integer`): Maximum unique restaurant records to save across selected cities and filters. ## `proxyConfiguration` (type: `object`): India residential proxies are recommended for reliable regional access. ## Actor input object example ```json { "cities": [ "Bangalore" ], "localities": [], "cuisines": [], "sortBy": "RELEVANCE", "maxResults": 10, "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "IN" } } ``` # 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 = { "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "IN" } }; // Run the Actor and wait for it to finish const run = await client.actor("fascinating_lentil/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 = { "proxyConfiguration": { "useApifyProxy": True, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "IN", } } # Run the Actor and wait for it to finish run = client.actor("fascinating_lentil/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 '{ "proxyConfiguration": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "IN" } }' | apify call fascinating_lentil/swiggy-restaurant-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=fascinating_lentil/swiggy-restaurant-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Swiggy Restaurant Scraper - Listings, Ratings & Delivery Data", "description": "Scrape public Swiggy restaurant listings with names, cuisines, ratings, delivery time, cost for two, offers, locality, image URLs, and restaurant URLs.", "version": "1.0", "x-build-id": "LqCPcPq7db4s52yKM" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/fascinating_lentil~swiggy-restaurant-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-fascinating_lentil-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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/fascinating_lentil~swiggy-restaurant-scraper/runs": { "post": { "operationId": "runs-sync-fascinating_lentil-swiggy-restaurant-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/fascinating_lentil~swiggy-restaurant-scraper/run-sync": { "post": { "operationId": "run-sync-fascinating_lentil-swiggy-restaurant-scraper", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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", "required": [ "cities" ], "properties": { "cities": { "title": "Cities", "minItems": 1, "type": "array", "description": "Cities to scrape, for example Bangalore, Mumbai, Delhi, Pune, Hyderabad, Chennai, Kolkata, or Ahmedabad.", "default": [ "Bangalore" ], "items": { "type": "string" } }, "localities": { "title": "Localities / Areas", "type": "array", "description": "Optional areas within the city. Leave empty to search the city page.", "default": [], "items": { "type": "string" } }, "cuisines": { "title": "Cuisine filters", "type": "array", "description": "Optional cuisine filters such as Chinese, North Indian, Italian, Biryani, or South Indian.", "default": [], "items": { "type": "string" } }, "sortBy": { "title": "Sort order", "enum": [ "RELEVANCE", "RATING", "DELIVERY_TIME", "COST_LOW_TO_HIGH", "COST_HIGH_TO_LOW" ], "type": "string", "description": "Preferred result sorting when Swiggy exposes sorting controls.", "default": "RELEVANCE" }, "maxResults": { "title": "Maximum restaurants", "minimum": 1, "maximum": 300, "type": "integer", "description": "Maximum unique restaurant records to save across selected cities and filters.", "default": 10 }, "proxyConfiguration": { "title": "Proxy configuration", "type": "object", "description": "India residential proxies are recommended for reliable regional access.", "default": { "useApifyProxy": true, "apifyProxyGroups": [ "RESIDENTIAL" ], "apifyProxyCountry": "IN" } } } }, "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 } } } } } } } } } } ```