Swiggy Menu Scraper

Extract complete restaurant menus from Swiggy with flattened, CSV-friendly output.

Features

Easy Input

• Search by restaurant name (e.g., "ITC", "Pizza Hut")
• OR provide restaurant IDs if you have them
• No manual ID lookup required!

Complete Data

• Restaurant info (name, rating, location)
• All menu categories
• Item details (name, price, description)
• Veg/non-veg indicators
• Ratings and images
• Stock status

Input Examples

Example 1: Search by Name (Recommended)

{
  "restaurantName": "YouMee",
  "Locality": "Express Avenue",
  "city": "Chennai"
}

Example 2: Multiple Chains

{
  "restaurantName": "Pizza Hut",
  "Locality": "Perungudi",
  "city": "Chennai"
}

Example 3: Using IDs (if you have them)

{
  "restaurantIds": ["925755", "16227"],
  "city": "Chennai"
}

Output Format

Each row contains:

• restaurantId - Swiggy restaurant ID
• restaurantName - Restaurant name
• city - City
• location - Area/locality
• rating - Restaurant rating
• totalRatings - Number of ratings
• cuisines - Cuisine types
• costForTwo - Cost for two people
• deliveryTime - Delivery time
• categoryName - Menu category
• itemId - Item ID
• itemName - Item name
• itemDescription - Item description
• price - Price in ₹
• finalPrice - Final price (after discounts)
• isVeg - Yes/No
• inStock - Yes/No
• itemRating - Item rating
• itemRatingCount - Item rating count
• imageUrl - Image URL

How to Use

1. Simple Search

Input: Restaurant name + City

{
  "restaurantName": "McDonald's",
  "city": "Bangalore"
}

2. Download as CSV

After run completes:

• Go to Dataset tab
• Click Export → CSV
• Open in Excel/Google Sheets

3. Analyze Data

Perfect for:

• Price comparison
• Menu analysis
• Item tracking
• Restaurant research

Supported Cities

Chennai, Mumbai, Delhi, Bangalore, Hyderabad, Pune, Kolkata, Ahmedabad, Jaipur

Performance

• Speed: ~18 seconds per restaurant
• Cost: ~$0.50 per 100 restaurants
• Success Rate: 95%+

Use Cases

📊 Price Monitoring

• Track price changes over time
• Compare prices across locations
• Identify patterns

🍽️ Menu Analysis

• Popular items by rating
• Veg vs non-veg distribution
• Category breakdown

💼 Business Intelligence

• Competitive analysis
• Market research
• Pricing strategy

Tips

1. Search by name - Easier than finding IDs
2. Export to CSV - Best way to view data
3. Use Excel pivot tables - Great for analysis
4. Filter by isVeg - Easy veg/non-veg filtering

Example Workflow

1. Input: "KFC" + "Chennai"
2. Actor finds 3 KFC locations
3. Scrapes all menus
4. Outputs 200+ rows (flat)
5. Export CSV
6. Analyze in Excel

Limitations

• Requires valid city name
• Some restaurants may not have menus
• Rate-limited (3 sec between requests)

---