Uber Eats Restaurant Scraper

Extract comprehensive restaurant data from Uber Eats — one of the largest food delivery platforms in the United States.

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Table of Contents

• Quick Start
• Features
• Use Cases
• How It Works
• Input Parameters
• Operation Modes
• Output Examples
• Data Fields
• Code Examples
• How to Get Coordinates
• Important Notes
• FAQ
• Support

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Quick Start

Get started in three simple steps:

Step 1: Find restaurants in Miami

{
  "mode": "search_stores",
  "latitude": "25.7617",
  "longitude": "-80.1918",
  "query": "Pizza",
  "max_results": 100
}

Step 2: Get restaurant details

{
  "mode": "store_info",
  "store_url": "https://www.ubereats.com/store/dominos-pizza/abc123-def456"
}

Step 3: Extract the menu

{
  "mode": "menu",
  "store_url": "https://www.ubereats.com/store/dominos-pizza/abc123-def456"
}

Tip: Start with categories mode to discover available food types in your target location.

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Features

Feature	Description
Search All Restaurants	Get hundreds of restaurants with full pagination support
Complete Menu Data	Full menus with prices, descriptions, and customization options
Detailed Store Profiles	Address, ratings, delivery info, and operating hours
Category Discovery	Find available food categories in any US location
Real-Time Data	Fresh data directly from Uber Eats platform
Structured JSON Output	Clean, validated data ready for analysis

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Use Cases

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How It Works

+------------------+    +------------------+    +------------------+    +------------------+
|     STEP 1       |    |     STEP 2       |    |     STEP 3       |    |     STEP 4       |
|   Categories     |--->|   Search         |--->|   Store Info     |--->|   Menu           |
|   Discovery      |    |   Stores         |    |   Details        |    |   Extraction     |
+------------------+    +------------------+    +------------------+    +------------------+
        |                      |                      |                      |
        v                      v                      v                      v
   Food types in          All restaurants        Complete store        Full menu with
   your location          matching query         information           prices and items

Step 1: Discover Categories

Find what food categories are available in your target location:

{
  "mode": "categories",
  "latitude": "25.7617",
  "longitude": "-80.1918"
}

Returns: Available food categories (Pizza, Sushi, Mexican, Chinese, etc.)

Step 2: Search All Restaurants

Get all restaurants matching your criteria with full pagination:

{
  "mode": "search_stores",
  "latitude": "25.7617",
  "longitude": "-80.1918",
  "query": "Pizza",
  "max_results": 500
}

Returns: Up to 500 restaurants with name, ratings, delivery fees, ETA, and coordinates.

Step 3: Get Restaurant Details

Use the store_id or store_url from Step 2 to get complete restaurant information:

{
  "mode": "store_info",
  "store_url": "https://www.ubereats.com/store/dominos-pizza/abc123-def456"
}

Returns: Full address, ratings, phone number, operating hours, and more.

Step 4: Get Complete Menu

Extract the full menu with all items and prices:

{
  "mode": "menu",
  "store_url": "https://www.ubereats.com/store/dominos-pizza/abc123-def456"
}

Returns: Categories, items, prices, descriptions, images, and availability.

---

Input Parameters

Required Parameters

Parameter	Type	Description
mode	string	Operation mode: categories, search_stores, stores, store_info, or menu

Mode-Specific Parameters

Parameter	Type	Required For	Description
latitude	string	categories, search_stores	Location latitude
longitude	string	categories, search_stores	Location longitude
query	string	stores, search_stores	Search term (e.g., "Pizza", "McDonald's")
store_url	string	store_info, menu	Full Uber Eats restaurant URL
store_id	string	store_info, menu	Restaurant UUID (alternative to store_url)

Optional Parameters

Parameter	Default	Description
max_results	1000	Maximum restaurants to extract (up to 5000)
request_waiting	5	Delay between requests in seconds (minimum: 3)

Proxy Configuration

Parameter	Default	Description
useApifyProxy	true	Enable Apify Proxy (required for production)
proxyGroups	["RESIDENTIAL"]	Proxy group - RESIDENTIAL recommended
proxyCountry	US	Proxy country code (US, CA, GB, DE, FR)

Important: This actor requires Residential proxy to work properly. The default configuration uses Apify's Residential proxy which is automatically enabled when running on the Apify platform.

Proxy Configuration Example

{
  "mode": "search_stores",
  "latitude": "25.7617",
  "longitude": "-80.1918",
  "query": "Pizza",
  "useApifyProxy": true,
  "proxyGroups": ["RESIDENTIAL"],
  "proxyCountry": "US"
}

---

Operation Modes

Mode	Description	Required Parameters	Output
categories	List available food categories	latitude, longitude	Food types in location
search_stores	Extract all restaurants (paginated)	latitude, longitude, query	Up to 5000 restaurants
stores	Quick search suggestions	query	Top 5 matching stores
store_info	Get restaurant details	store_url or store_id	Complete store profile
menu	Get menu items/products	store_url or store_id	Full menu with prices

---

Output Examples

Categories Mode

{
  "latitude": "25.7617",
  "longitude": "-80.1918",
  "total": 20,
  "categories": [
    {"title": "Pizza", "titleTerm": "Pizza", "type": "restaurant_category"},
    {"title": "Sushi", "titleTerm": "Sushi", "type": "restaurant_category"},
    {"title": "Mexican", "titleTerm": "Mexican", "type": "restaurant_category"},
    {"title": "Chinese", "titleTerm": "Chinese", "type": "restaurant_category"},
    {"title": "Italian", "titleTerm": "Italian", "type": "restaurant_category"}
  ]
}

Search Stores Mode

{
  "query": "Pizza",
  "latitude": "25.7617",
  "longitude": "-80.1918",
  "total": 374,
  "data": [
    {
      "store_id": "abc123-def456-...",
      "name": "Domino's (18505 S Dixie Hwy)",
      "slug": "dominos-18505-s-dixie-hwy",
      "rating": 3.9,
      "review_count": "500+",
      "eta_min": 15,
      "eta_max": 25,
      "delivery_fee": 149,
      "image_url": "https://tb-static.uber.com/prod/image.jpeg",
      "is_orderable": true,
      "latitude": 25.59,
      "longitude": -80.35,
      "url": "https://www.ubereats.com/store/dominos-18505-s-dixie-hwy/abc123"
    }
  ]
}

Stores Mode (Quick Search)

{
  "query": "McDonald's",
  "total": 5,
  "data": [
    {
      "store_id": "uuid",
      "name": "McDonald's (Palmetto Bay)",
      "slug": "mcdonalds-palmetto-bay",
      "categories": ["Fast Food", "American", "Burgers"],
      "image_url": "https://...",
      "is_orderable": true,
      "url": "https://www.ubereats.com/store/mcdonalds-palmetto-bay/uuid"
    }
  ]
}

Store Info Mode

{
  "name": "McDonald's",
  "store_id": "c13edd5e-4ad7-4a86-80f3-a8fc6f114a17",
  "slug": "mcdonalds-palmetto-bay",
  "rating": {
    "ratingValue": 4.5,
    "reviewCount": "1000+"
  },
  "location": {
    "address": "17255 S Dixie Hwy",
    "city": "Miami",
    "latitude": 25.5918,
    "longitude": -80.3536
  },
  "hours": ["6:00 AM - 11:00 PM"],
  "phone": "+1 (305) 555-0123"
}

Menu Mode

{
  "items": 45,
  "store_id": "c13edd5e-4ad7-4a86-80f3-a8fc6f114a17",
  "data": [
    {
      "name": "Big Mac",
      "description": "Two 100% beef patties, special sauce, lettuce, cheese...",
      "product_id": "uuid",
      "category": "Burgers",
      "price_to": 7.99,
      "price_from": 0.0,
      "discount": 0.0,
      "available": "Y",
      "has_customizations": "Y",
      "rating": 92,
      "num_ratings": 1250,
      "endorsement": "Y",
      "image": "https://tb-static.uber.com/prod/image.jpeg",
      "created_at": "2025-01-31"
    }
  ]
}

---

Data Fields

Search Stores Mode

Field	Type	Description
store_id	string	Unique restaurant identifier (UUID)
name	string	Restaurant name with location
slug	string	URL-friendly name
rating	number	Average rating (0-5 stars)
review_count	string	Number of reviews (e.g., "500+")
eta_min	number	Minimum delivery time (minutes)
eta_max	number	Maximum delivery time (minutes)
delivery_fee	number	Delivery fee in cents (149 = $1.49)
image_url	string	Restaurant image URL
is_orderable	boolean	Currently accepting orders
latitude	number	Restaurant latitude
longitude	number	Restaurant longitude
url	string	Direct link to restaurant page

Menu Mode

Field	Type	Description
name	string	Menu item name
description	string	Item description
product_id	string	Unique item identifier
category	string	Menu category (e.g., "Burgers")
price_to	number	Current price in USD
price_from	number	Original price if discounted
discount	number	Discount percentage (0-100)
available	string	"Y" = Available, "N" = Unavailable
has_customizations	string	"Y" = Has options, "N" = No options
rating	number	Positive ratings percentage (0-100)
num_ratings	number	Total number of ratings
endorsement	string	"Y" = Popular item, "N" = Regular
image	string	Item image URL
created_at	string	Extraction date (YYYY-MM-DD)

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Code Examples

Python Integration

from apify_client import ApifyClient

# Initialize the Apify client
client = ApifyClient("your_apify_token")

# Search for Pizza restaurants in Miami
run = client.actor("YOUR_USERNAME/uber-eats-restaurant-scraper").call(run_input={
    "mode": "search_stores",
    "latitude": "25.7617",
    "longitude": "-80.1918",
    "query": "Pizza",
    "max_results": 100,
    "useApifyProxy": True,
    "proxyGroups": ["RESIDENTIAL"],
    "proxyCountry": "US"
})

# Get results from dataset
items = client.dataset(run["defaultDatasetId"]).list_items().items
restaurants = items[0]["data"]

print(f"Found {len(restaurants)} Pizza restaurants in Miami")

# Display top 5 restaurants
for restaurant in restaurants[:5]:
    print(f"- {restaurant['name']}")
    print(f"  Rating: {restaurant['rating']} | ETA: {restaurant['eta_min']}-{restaurant['eta_max']} min")
    print(f"  Delivery Fee: ${restaurant['delivery_fee']/100:.2f}")
    print()

JavaScript / Node.js Integration

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'your_apify_token' });

const run = await client.actor('YOUR_USERNAME/uber-eats-restaurant-scraper').call({
    mode: 'search_stores',
    latitude: '25.7617',
    longitude: '-80.1918',
    query: 'Pizza',
    max_results: 100
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Found ${items[0].data.length} restaurants`);

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How to Get Coordinates

Option 1: Google Maps

1. Open Google Maps
2. Right-click on any location in the United States
3. Click on the coordinates to copy them
4. Use the first number as latitude and second as longitude

Option 2: Use Common City Coordinates

City	Latitude	Longitude
Miami, FL	25.7617	-80.1918
New York, NY	40.7128	-74.0060
Los Angeles, CA	34.0522	-118.2437
Chicago, IL	41.8781	-87.6298
Houston, TX	29.7604	-95.3698
San Francisco, CA	37.7749	-122.4194
Las Vegas, NV	36.1699	-115.1398
Phoenix, AZ	33.4484	-112.0740
Dallas, TX	32.7767	-96.7970
Nashville, TN	36.1627	-86.7816

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Important Notes

Topic	Details
Region	United States only - Uber Eats US market
Proxy	Residential proxy required (auto-configured on Apify)
Pagination	search_stores handles pagination automatically (80 stores/page)
Rate Limiting	Minimum 3-second delay between requests
Store Identification	Use either store_url OR store_id (not both)
Coordinates	Required for categories and search_stores modes

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FAQ

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Support

Having issues? Here is how to get help:

1. Check the FAQ above for common solutions
2. Review your input parameters to ensure they match the required format
3. Test with default values to ensure the actor is working
4. Contact support through Apify for additional assistance