Speisekarte.de Restaurant Scraper: Extract German Restaurant Listings

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What Is Speisekarte.de?

Speisekarte.de is one of Germany's most popular restaurant discovery platforms, listing thousands of dining establishments across German cities with menus, reviews, and contact details. For food delivery aggregators, market researchers, or local business analysts, manually collecting this data is impractical. The Speisekarte.de Restaurant Scraper automates extraction from any restaurant listing page, delivering clean, structured records ready for analysis.

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Overview

This scraper targets Speisekarte.de's paginated restaurant search and category pages, extracting key business data per listing. It suits:

• Food tech developers building restaurant aggregators or delivery integrations
• Market researchers analyzing dining trends by city or cuisine type
• Sales teams prospecting restaurants for B2B outreach
• Data analysts studying pricing and cuisine distribution across German cities

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Input Format

{
  "ignore_url_failures": true,
  "max_items_per_url": 200,
  "urls": [
    "https://www.speisekarte.de/berlin/restaurants?page=3"
  ]
}

Field	Type	Default	Description
urls	array	—	Required. One or more Speisekarte.de restaurant listing URLs to scrape (e.g. city pages, cuisine filters, paginated results). Paste URLs one by one or use Bulk edit. Example: https://www.speisekarte.de/hamburg/restaurants
max_items_per_url	integer	20	Maximum number of restaurant records collected per URL. Increase up to 200 for full-page sweeps.
ignore_url_failures	boolean	true	If true, the scraper skips failed URLs and continues the run instead of stopping entirely. Recommended for bulk jobs.

Tip: To collect an entire city's listings, iterate through pages by incrementing the ?page= parameter across multiple URLs in the urls array.

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Output Format

Sample Record

{
  "name": "Weißes Röss’l",
  "image": "https://images.speisekarte.de/media/img/40fdf126-6a91-4a23-acc1-e16fb5621dad/6a173036-3439-4daf-be9d-6c22d194fa81.thumb.jpg",
  "address": {
    "@type": "PostalAddress",
    "address_locality": "Berlin",
    "postal_code": "12209",
    "street_address": "Heinersdorfer Str. 15",
    "address_country": "de"
  },
  "geo": {
    "@type": "GeoCoordinates",
    "latitude": 52.4183,
    "longitude": 13.3243
  },
  "telephone": "0307723030",
  "serves_cuisine": [
    "bayerisch"
  ],
  "price_range": "€€",
  "url": "https://www.speisekarte.de/berlin/restaurant/weisses_roessl",
  "from_url": "https://www.speisekarte.de/berlin/restaurants?page=2"
}

Each restaurant record returns up to 8 fields:

Field	Type	Meaning
Name	String	Restaurant name as listed on Speisekarte.de
Image	URL	Primary photo of the restaurant or its logo
Address	String	Full street address including city and postal code
Geo	Object	Geographic coordinates (latitude, longitude) for mapping or proximity analysis
Telephone	String	Public contact phone number
Serves Cuisine	String / Array	Cuisine type(s) offered (e.g. Italian, Sushi, Döner)
Price Range	String	Approximate price tier (e.g. €, €€, €€€)
URL	URL	Direct link to the restaurant's Speisekarte.de profile page

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How to Use

1. Find target pages — Browse Speisekarte.de, filter by city or cuisine, and copy the listing page URL (e.g. https://www.speisekarte.de/munich/restaurants).
2. Add URLs — Paste into the urls array. Add multiple pages for broader coverage.
3. Set item limit — Adjust max_items_per_url based on how many results the page contains (typically 20–30 per page).
4. Run and export — Download results as JSON, CSV, or Excel.

Common issues:

• Ensure URLs point to listing/search pages, not individual restaurant profiles.
• If results are fewer than expected, the page may have fewer listings than max_items_per_url — this is normal.
• Use ignore_url_failures: true when running multi-URL bulk jobs.

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Use Cases & Business Value

• Lead generation: Build outreach lists of restaurants in a target city with contact details
• Menu aggregation: Seed a food platform with verified restaurant data
• Geo-mapping: Plot restaurant density or cuisine distribution using the Geo field
• Competitive analysis: Track price ranges and cuisine trends across neighborhoods

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Conclusion

The Speisekarte.de Restaurant Scraper turns Germany's largest dining directory into a structured, queryable dataset. With coordinates, cuisine tags, pricing, and direct profile links included per record, it delivers everything needed for market research, business development, or platform integration — in one efficient run.