# Swiggy Restaurant / Dish Extractor (`smacient/swiggy-restaurant-dish-extractor`) Actor

Effortlessly get the various restaurants or dishes data from Swiggy within seconds.

- **URL**: https://apify.com/smacient/swiggy-restaurant-dish-extractor.md
- **Developed by:** [Smacient](https://apify.com/smacient) (community)
- **Categories:** Automation, E-commerce, AI
- **Stats:** 16 total users, 0 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: 5.00 out of 5 stars

## Pricing

from $4.00 / 1,000 results

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 web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
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.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — 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 🍽️

Effortlessly extract restaurant data from Swiggy with our powerful scraper. Get restaurants URL, their ratings, offers, cuisines, and more in few seconds.

### ✨ Features

- 🏪 **Comprehensive Data**: Extract restaurant names, ratings, cuisines, prices, and more
- 🎯 **Smart Search**: Search by cuisine type or restaurant name
- 📍 **Location-Based**: Support for almost all cities
- 📊 **Structured Output**: Clean JSON format ready for analysis
- 💰 **Offer Detection**: Automatically extracts current promotional offers
- 🏆 **Rating & Reviews**: Get detailed rating information and review counts
- 🖼️ **Restaurant Images**: Direct links to high-quality restaurant images

### 📋 Input Configuration

#### Required Fields

- **Delivery Location**: City name or delivery location (e.g., Chennai, Mumbai, Bangalore)
- **Search Term**: Cuisine type or restaurant name (e.g., Pizza, Biryani, KFC)

#### Optional Fields

- **Maximum Results**: Number of restaurants to scrape (Default: 99999 for unlimited)

### 🔍 Example Input

```json
{
  "location": "Chennai",
  "searchTerm": "Biryani",
  "maxResults": 50
}
```

### 📊 Output Data

Each restaurant entry includes:

```json
{
  "restaurantName": "Paradise Biryani",
  "restaurantId": "12345",
  "rating": 4.3,
  "ratingCount": "10K+ ratings",
  "cuisines": "Biryani, North Indian, Chinese",
  "cuisinesList": ["Biryani", "North Indian", "Chinese"],
  "areaName": "T Nagar",
  "locality": "Pondy Bazaar",
  "deliveryTime": "30-35 mins",
  "deliveryTimeMinutes": 32,
  "price": "₹400 for two",
  "costForTwoMessage": "₹400 for two",
  "distance": "3.5 km",
  "offer": "50% OFF UPTO ₹100",
  "promoted": false,
  "isOpen": true,
  "badges": ["Bestseller"],
  "restaurantUrl": "https://www.swiggy.com/city/chennai/paradise-biryani-rest12345",
  "imageUrl": "https://media-assets.swiggy.com/swiggy/image/upload/...",
  "veg": false,
  "location": "Chennai",
  "searchTerm": "Biryani"
}
```

### 🎯 Use Cases

- **Market Research**: Analyze restaurant offerings and pricing in different cities
- **Price Monitoring**: Track restaurant prices and offers over time
- **Competitive Analysis**: Compare restaurants by ratings, and cuisines
- **Location Intelligence**: Understand restaurant density and distribution
- **Offer Tracking**: Monitor promotional campaigns and discounts
- **Menu Analysis**: Study cuisine trends and popular food categories
- **Delivery Optimization**: Analyze delivery times and service areas
- **Business Intelligence**: Generate insights for restaurant industry analysis

### 🌆 Supported Cities (50+)

Almost any City!

### 💡 Tips for Best Results

1. **Use Specific Search Terms**: Instead of "food", try "North Indian" or "Chinese"
2. **Popular Locations**: Major cities have more comprehensive data
3. **Reasonable Limits**: Set maxResults to avoid unnecessarily long runs
4. **Monitor Offers**: Offers change frequently - run regularly for updates
5. **Combine with Other Tools**: Export data to spreadsheets for analysis

### 🔐 Privacy & Compliance

- Scrapes only publicly available data
- No login or authentication required
- Respects Swiggy's public API structure
- Does not access user accounts or private information

### 📞 Support & Feedback

- Found a bug? Please report it! @support@smacient.com
- Have suggestions? We'd love to hear them!
- Need custom features? Contact us for enterprise solutions

### 🔄 Updates & Maintenance

This actor is actively maintained and updated regularly to ensure:

- Compatibility with Swiggy's latest API changes
- Bug fixes and performance improvements
- New features based on user feedback

### 📈 Performance

- **Speed**: ~10 seconds for 50 restaurants
- **Accuracy**: 99%+ data extraction accuracy
- **Reliability**: Built-in error handling and retry logic
- **Scalability**: Handles large-scale extractions efficiently

### 🏆 Why Choose This Actor?

✅ **Most Comprehensive Data**: Extracts 20+ fields per restaurant
✅ **Production Ready**: Built with enterprise-grade error handling
✅ **Fast & Efficient**: Optimized for speed and resource usage
✅ **Well Documented**: Clear examples and detailed output schema
✅ **Actively Maintained**: Regular updates and improvements
✅ **Great Support**: Responsive to issues and feature requests

***

# Actor input Schema

## `location` (type: `string`):

Pincode (515001), city name (Bangalore), or address

## `searchTerm` (type: `string`):

Cuisine or dish (e.g., 'Japanese', 'Pizza', 'Biryani', 'Sushi')

## `resultType` (type: `string`):

What to return

## `maxResults` (type: `integer`):

Maximum number of results to return

## Actor input object example

```json
{
  "location": "Chennai",
  "searchTerm": "Pizza",
  "resultType": "restaurants",
  "maxResults": 50
}
```

# 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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "location": "Chennai",
    "searchTerm": "Pizza"
};

// Run the Actor and wait for it to finish
const run = await client.actor("smacient/swiggy-restaurant-dish-extractor").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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "location": "Chennai",
    "searchTerm": "Pizza",
}

# Run the Actor and wait for it to finish
run = client.actor("smacient/swiggy-restaurant-dish-extractor").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 '{
  "location": "Chennai",
  "searchTerm": "Pizza"
}' |
apify call smacient/swiggy-restaurant-dish-extractor --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=smacient/swiggy-restaurant-dish-extractor",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/o3RAUYKa7aJ30XRrL/builds/ax5GW1RApxjecfXcf/openapi.json