Michelin Guide Restaurant Scraper

Extract comprehensive restaurant data from the Michelin Guide across 47+ countries worldwide. Get detailed information about Michelin-starred restaurants, Bib Gourmand establishments, and other recommended dining venues.

🌟 What You Get

This scraper extracts detailed information for each restaurant including:

• Restaurant Details: Name, full description, chef information
• Location Data: Complete address, city, country, geographic coordinates
• Michelin Recognition: Star ratings (1-3 stars), Bib Gourmand, Green Star status
• Cuisine Information: Cuisine types and specialties
• Pricing: Price category indicators
• Contact Information: Phone numbers, website links, booking links
• Facilities: Features, accepted credit cards, opening hours
• Direct Links: URL to the restaurant's Michelin Guide page

🌍 Global Coverage

Scrape restaurants from 47+ countries including:

• Europe: France, Italy, Spain, Germany, UK, Netherlands, Belgium, Switzerland, Austria, Portugal, Sweden, Norway, Denmark, Finland, Iceland, Poland, Czech Republic, Greece, Croatia, Serbia, Hungary, Slovenia, Estonia, Latvia, Lithuania, Luxembourg, Malta, and more
• Asia: Japan, China, Hong Kong, Singapore, Thailand, South Korea, Taiwan, Vietnam, Malaysia, Macau, Philippines
• Americas: USA, Canada, Mexico, Brazil, Argentina
• Middle East: UAE, Qatar, Turkey, Saudi Arabia

Or scrape all countries at once with a single run!

⚙️ Key Features

• Fast & Efficient: Scrapes up to 2 restaurants per second with detail page information
• Reliable: Built-in retry logic and timeout handling for stable runs
• Flexible: Choose specific countries or get global data
• Complete Data: Always includes full detail page information
• Smart Stopping: Automatically detects when all data has been scraped
• State Persistence: Can resume from interruptions
• Timeout Protection: Multiple layers of timeout handling to prevent hung runs

📊 Use Cases

Perfect for:

• Restaurant Discovery Platforms: Build comprehensive dining databases
• Food & Travel Apps: Enrich your app with Michelin Guide data
• Market Research: Analyze culinary trends and Michelin star distributions
• Travel Planning: Create curated lists of top restaurants by region
• Data Analysis: Study pricing, cuisine types, and geographic patterns
• Content Creation: Generate content about fine dining destinations
• Business Intelligence: Track restaurant industry trends and prestigious establishments

🚀 How to Use

Basic Usage

1. Select Your Coverage: Choose a specific country or select "All Countries"
2. Configure Pages (Optional): Set start/end pages if you want partial data
3. Adjust Performance (Optional): Modify concurrency and delays as needed
4. Run: The scraper will collect all available data within the 1-hour default timeout

Input Parameters

• Country (default: "All Countries"): Select a specific country or scrape all countries

  • Supports 47+ countries across Europe, Asia, Americas, and Middle East

• Start Page (default: 1): The page number to start scraping from

  • Useful for resuming interrupted scrapes or scraping specific sections

• End Page (optional): The page number to stop at

  • Leave empty to scrape all available pages
  • Each page contains approximately 48 restaurants

• Max Concurrency (default: 3): Number of concurrent detail page requests

  • Higher values = faster scraping but more resource intensive
  • Recommended: 3-5 for optimal balance

• Delay Between Pages (default: 1 second): Delay between scraping each page

  • Helps avoid overwhelming the server
  • Can be reduced to 0 for faster scraping

• Skip Detail Scraping (default: false): Skip fetching restaurant detail pages

  • Enable for faster scraping with less comprehensive data
  • Disable (default) for complete restaurant information

• Output Format (default: "Full"): Choose between full or simplified output

  • Full: All available fields
  • Simplified: Key fields only (name, address, phone, description, etc.)

• Debug Mode (default: false): Enable verbose logging for troubleshooting

⏱️ Performance

• Speed: ~1-2 restaurants per second with full detail scraping
• Timeout: 1 hour default (configurable in run options)
• Memory: 1 GB default (sufficient for most runs)
• Data Volume: Can scrape thousands of restaurants in a single run
• Typical Run Times:
  • Single country (100-200 restaurants): 2-5 minutes
  • Multiple countries (1000+ restaurants): 15-30 minutes
  • All countries (10,000+ restaurants): 45-60 minutes

📝 Output Format

Data is exported in JSON format with all fields clearly labeled. You can download the results as JSON, CSV, Excel, or other formats directly from Apify.

Sample Output

{
  "name": "Le Bernardin",
  "description": "A temple to seafood in all its guises...",
  "address": "155 West 51st Street, New York, NY 10019",
  "phone": "+1 212-554-1515",
  "website": "https://le-bernardin.com",
  "city": {
    "name": "New York"
  },
  "country": {
    "name": "United States",
    "slug": "united-states"
  },
  "michelin_award": "3 Stars",
  "green_star": false,
  "cuisines": [
    {
      "name": "Seafood",
      "slug": "seafood"
    },
    {
      "name": "French",
      "slug": "french"
    }
  ],
  "price_category": "$$$",
  "chef": "Eric Ripert",
  "features": [
    "Great wine list",
    "Counter dining"
  ],
  "credit_cards": [
    "American Express",
    "Visa",
    "Mastercard"
  ],
  "opening_hours": "Monday-Thursday: 5:00 PM - 10:00 PM...",
  "booking_link": "https://...",
  "url": "https://guide.michelin.com/us/en/new-york-state/new-york/restaurant/le-bernardin",
  "_geoloc": {
    "lat": 40.761868,
    "lng": -73.981363
  }
}

💡 Tips

• Start with a single country to test the output format and understand the data structure
• Use the default settings for optimal balance of speed and reliability
• For large global scrapes, consider breaking into multiple runs by region if you need faster results
• Monitor the logs to track scraping progress and identify any issues
• The scraper automatically retries failed pages to ensure data completeness
• Empty page handling: The scraper intelligently detects the end of results vs. temporary page load failures

🔧 Advanced Configuration

Resuming Interrupted Runs

The scraper automatically saves its state and can resume from where it left off if interrupted. The state includes:

• Current page number
• Total restaurants scraped
• Timestamp of last update

Timeout Handling

The scraper includes multiple layers of timeout protection:

• Page fetch timeout: 30 seconds per page
• Detail scraping timeout: 15 seconds per restaurant
• Batch timeout: 60 seconds per batch
• Global runtime limit: Automatically stops 5 minutes before platform timeout

Error Recovery

• Automatic retry for failed requests (up to 3 attempts with exponential backoff)
• Failed URLs are tracked and skipped to prevent repeated failures
• Empty page retry logic (2 attempts before considering truly empty)
• Comprehensive error logging for debugging

📋 Data Fields

Basic Information

• name: Restaurant name
• description / full_description: Full restaurant description from detail page
• chef: Head chef name
• url: Link to Michelin Guide page

Location

• address / detailed_address: Complete street address
• city: City information (name, slug)
• country: Country information (name, slug, code)
• region: Regional information
• _geoloc: Geographic coordinates (lat, lng)

Michelin Recognition

• michelin_award: Star rating (1 Star, 2 Stars, 3 Stars, Bib Gourmand, etc.)
• green_star: Boolean for Green Star sustainability award
• new_table: Boolean for newly added restaurants

Cuisine & Pricing

• cuisines: Array of cuisine types
• price_category: Price indicator (€, €€, €€€, €€€€)
• currency: Local currency code
• currency_symbol: Currency symbol

Contact & Booking

• phone / phone_number: Contact phone number
• website: Restaurant website
• booking_link: Online booking link
• online_booking: Boolean for online booking availability

Facilities & Services

• features: Array of restaurant features/facilities
• credit_cards: Accepted credit card types
• opening_hours: Operating hours
• take_away: Boolean for takeaway service
• delivery: Boolean for delivery service

Images

• main_image: Main restaurant image
• images: Array of additional images
• image: Featured image

🛟 Support

• All configuration options include helpful descriptions in the input form
• Built-in state persistence for interrupted runs
• Detailed logging to track scraping progress
• Automatic empty page detection to know when scraping is complete
• Comprehensive error messages for troubleshooting

⚠️ Important Notes

• This scraper is designed for legitimate data collection purposes
• Please respect the Michelin Guide's terms of service
• Use the data responsibly and in compliance with applicable laws
• The scraper includes polite delays and rate limiting to avoid overwhelming servers
• Consider the ethical implications of web scraping and use the data appropriately

🔄 Updates & Maintenance

This scraper is actively maintained and updated to handle:

• Changes to the Michelin Guide website structure
• New countries added to the Michelin Guide
• Performance optimizations
• Bug fixes and stability improvements

📞 Getting Help

If you encounter any issues:

1. Check the logs: The scraper provides detailed logging of its operations
2. Verify your input: Ensure country codes and page numbers are valid
3. Review the output: Check if partial data was collected before the error
4. Enable debug mode: Turn on debug logging for more detailed information
5. Contact support: Reach out through the Apify platform for assistance

🎯 Performance Benchmarks

Based on typical usage:

• Austria (~200 restaurants): 3-4 minutes
• France (~600 restaurants): 8-12 minutes
• USA (~400 restaurants): 6-10 minutes
• All Countries (~15,000 restaurants): 50-60 minutes

Note: Times may vary based on network conditions and server response times.

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Technical Details

How It Works

1. Configuration Extraction: Automatically extracts Algolia API configuration from Michelin Guide pages
2. API Integration: Uses the Algolia search API to efficiently retrieve restaurant listings
3. Detail Scraping: Fetches comprehensive information from individual restaurant pages
4. Data Processing: Structures and formats data for easy consumption
5. State Management: Tracks progress and handles interruptions gracefully

Architecture

• Built with Python 3.11 and the Apify SDK
• Asynchronous requests using aiohttp for optimal performance
• BeautifulSoup for HTML parsing
• Implements connection pooling and timeout management
• Event-driven state persistence for reliability

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Ready to start? Simply configure your desired settings and click Run! The scraper will handle the rest, providing you with comprehensive Michelin Guide restaurant data in a clean, structured format.