Our Uber Eats Scraper and Uber Eats Scraper API provide real-time data extraction for Uber Eats. Covering USA, UK, UAE, India, Canada, France, Germany, Spain, Italy, and Mexico, this Uber Eats Scraper ensures access to restaurant, menu, and pricing data for businesses.
Uber Eats is an online food delivery platform that connects users with local restaurants. Customers can order meals through the app or website, with options for delivery or pickup, offering convenience and diverse dining choices.
What is Uber Eats Scraper?
Uber Eats Scraper is a tool or API designed to extract data from Uber Eats, including restaurant details, menus, prices, and ratings. It provides businesses with real-time insights for market analysis, competition tracking, and decision-making.
Input Example of Uber Eats Scraper
{"location":"London","limit":5}
Output Example of Uber Eats Scraper
{"restaurant_name": "The Burger Joint","cuisines": "Burgers, Fast Food","delivery_time": "30-40 minutes","establishments": [{"id": 12345,"name": "The Burger Joint"}],"features": {"vegan_options": true,"gluten_free_options": true,"delivery_available": true,"pickup_available": true},"id": 987654,"images": [{"thumbnail": "https://www.ubereats.com/images/restaurant1-thumbnail.jpg","full_image": "https://www.ubereats.com/images/restaurant1-full.jpg"},{"thumbnail": "https://www.ubereats.com/images/restaurant2-thumbnail.jpg","full_image": "https://www.ubereats.com/images/restaurant2-full.jpg"}],"location": {"address": "123 Main St","city": "New York","latitude": "40.712776","longitude": "-74.005974","map_url": "https://www.ubereats.com/maps/restaurant1"},"menu_texts": [{"categories": [{"dishes": [{"dish_id": 101,"name": "Classic Cheeseburger","description": "A juicy beef patty with melted cheese, lettuce, tomato, and special sauce.","price": "$8.99"},{"dish_id": 102,"name": "Veggie Burger","description": "A delicious vegetarian patty with all the fixings.","price": "$7.99"}],"id": 111,"name": "Burgers"},{"dishes": [{"dish_id": 103,"name": "French Fries","description": "Crispy golden fries served with ketchup.","price": "$2.99"}],"id": 112,"name": "Sides"}]}],"phone": "+1-800-123-4567","payment_methods": "Cash, Credit Card, PayPal","ratings": {"average": 4.5,"total_votes": 200},"reviews": {"count": 50,"feedback": ["Great food! Fast delivery.","The burger was amazing, will order again."]},"social": {"twitter": "https://twitter.com/TheBurgerJoint","facebook": "https://facebook.com/TheBurgerJoint"},"status": "Open Now","timing": "9am - 11pm (Mon-Sun)","type": "restaurant","url": "https://www.ubereats.com/restaurant/the-burger-joint"}
Optional Parameters for Uber Eats Data Scraper
Parameter
Description
Example
Location
Specifies the city or area to search for restaurants.
"London"
Cuisine Type
Filters restaurants based on cuisine (e.g., pizza, sushi).
"Pizza", "Sushi", "Mexican"
Price Range
Filters restaurants based on price range (e.g., $, $$, $$$).
"$", "$$", "$$$"
Rating Threshold
Filters restaurants based on a minimum rating.
4.0, 4.5
Delivery Time
Filters restaurants based on estimated delivery time (in minutes).
30 minutes, 45 minutes
Restaurant Features
Filters based on specific restaurant features (e.g., "Delivery", "Pickup").
"Delivery", "Pickup"
Sort By
Sorts restaurants based on criteria like "Best Match", "Rating", or "Price".
"Best Match", "Rating"
Menu Items Filter
Filters menu items based on specific types (e.g., vegetarian, vegan).
"Vegetarian", "Vegan"
Distance from Location
Limits search results to a specific distance from a location (e.g., miles/km).
5 miles, 10 kilometers
Restaurant Status
Filters restaurants based on whether they are open or closed.
"Open", "Closed"
Required Parameters for Uber Eats Restaurant Data Scraper
Parameter
Description
Example
Location
Specifies the city or area to search for restaurants.
"London"
Restaurant Name
The name of the restaurant to serach for.
"Joe's Pizza", "Sushi Express"
API Key
Required if using an API to access Uber Eats data.
"your-api-key"
Category
Specifies the category of restaurants (e.g. "Pizza", "Sushi")
"Pizza", "Mexican"
Delivery Method
Specifies the delivery method (e.g. "Delivery", "Pickup").
"Delivery", "Pickup"
Sort Criteria
Specifies the sorting method (e.g. "Best Match", "Rating", or "Delivery Time").
"Best Match", "Rating"
Pagination
Parameter
Description
Example
Page Number
Specifies the page number to scrape (useful for navigating through multiple pages of results).
"1","2","3", etc.
Results Per Page
Define the number of restaurant results to return per page.
20, 50, 100
Next Page URL
The URL to the next page of restaurant listing (used to navigate to the next set of results).
"https://ubereats.com/page/2"
Has Next Page
A boolean value indicating whether there is a next page of results.
True, False
Total Pages
The total number of pages available for the search query.
5, 10, 15
Classification
Parameter
Description
Example
Cuisine Type
Classifies restaurants based on the type of cuisine.
"Pizza","Sushi","Mexican"
Restaurant Rating
Classifies restaurants based on their user rating.
4.0, 4.5, 5.0
Price Range
Classifies restaurants based on their price range.
"$", "$$", "$$$"
Delivery Method
Classifies restaurants based on their delivery method (e.g. delivery, pickup).
"Delivery", "Pickup"
Restaurant Status
Classifies restaurants based on their operational status (e.g., open or closed).
"Open", "Closed"
Menu Type
Classifies restaurants based on menu offerings (e.g., vegetarian, vegan, gluten-free).
"Vegetarian", "Vegan", "Gluten-Free"
Restaurant Features
Classifies restaurants based on specific features (e.g., "Offers Delivery", "Top Rated").
"Top Rated", "Offers Delivery"
Location
Classifies restaurants based on their geographical location (e.g., city, neighborhood).
"New York", "London"
Pricing
Parameter
Description
Example
Price Range
Specifies the price level of the restaurant typically represented by symbols ($, $$, $$$).
"$","$$","$$$"
Average Meal Price
Specifies the average cost for a meal at the restaurant.
"20 USD", "30 EUR"
Min Delivery Fee
Specifies the minimum delivery fee for the restaurant.
"2 USD", "5 EUR"
Max Delivery Fee
Specifies the maximum delivery fee for the restaurant.
"5 USD", "7 EUR"
Discounts available
Filters restaurants that offers discounts, like "free delivery" or "10% off".
"10% off", "Free Delivery"
Minimum Order Price
Specifies the minimum order price required for delivery.
"10 USD", "15 EUR"
Features
Parameter
Description
Example
Delivery Availability
Specifies whether a restaurant offers delivery.
"Delivery","Pickup"
Open Now
Filter restaurants that are currently open.
"Open", "Closed"
Offers Discounts
Filters restaurants that are offering discounts or promotions (e.g., free delivery, 10% off).
"10% off", "Free Delivery"
Top Rated
Filters restaurants that have high user ratings.
"Top Rated", "Highly Rated"
Vegetarian Options
Filters restaurants that offer vegetarian menu items.
"Vegetarian", "Vegan"
Gluten-Free Options
Filters restaurants that offer gluten-free menu items.
"Gluten-Free", "Allergy Friendly"
Late Night
Filters restaurants that are open late at night.
"Late Night", "Night Owl"
Family-Friendly
Filters restaurants that are suitable for families or offer kid-friendly options.
"Family-Friendly", "Kid-Friendly"
Pickup Options
Filters restaurants that offer pickup as an option.
"Pickup", "Takeout"
Alcohol Available
Filters restaurants that offer alcoholic beverages.
"Alcohol Available", "No Alcohol"
Is it Legal to Scrape Uber Eats?
Scraping Uber Eats, like scraping any website or app, falls into a complex legal area. Whether it is legal to scrape Uber Eats Food Delivery Data Scraping depends on several factors, including the website’s terms of service, the methods used for scraping, and the type of data being collected.
Uber Eats, like most companies, has specific Uber Eats Restaurant Menu Data Collection guidelines outlined in its terms of service. These terms typically prohibit data scraping or unauthorized access to their platform. If you use an Uber Eats Scraper to collect data without permission, you may be violating their terms of service. This could result in legal consequences, including the suspension of accounts or legal action.
However, Web Scraping Uber Eats Food Delivery Data is commonly done by businesses for legitimate purposes, such as market research or data analysis, but they often do so by utilizing official APIs or obtaining explicit permission. For example, using the Uber Eats Scraper API or the Uber Eats Menu API can provide structured data access within the boundaries of their terms.
If you choose to Scrape Uber Eats Food Delivery App Data without permission, you may be infringing on intellectual property rights. This can lead to lawsuits, as scraping can be seen as unauthorized access to Uber Eats' platform. Additionally, scraping sensitive data, such as Extract Uber Eats Restaurant Reviews and Ratings, or Scraping Uber Eats for Food Deals and Offers, might violate privacy laws.
Legal risks also increase when scraping large amounts of data, such as Uber Eats Restaurant Listings Extraction and Extract Popular Dishes on Uber Eats, or collecting Uber Eats Food Delivery Time Data Extraction. Furthermore, Uber Eats Location-based Restaurant Scraping can raise location privacy concerns.
In conclusion, to avoid legal issues, it’s advised to thoroughly review Uber Eats’ terms of service or to use their official APIs for legitimate data extraction. Always ensure compliance with legal regulations and obtain necessary permissions before scraping.
Industries
Check out how industries use Uber Eats Scraper worldwide.
You should have a Real Data API account to execute the program examples. Replace
< YOUR_API_TOKEN>
in the program using the token of your scraper. Read about the live APIs with Real Data API docs for more explanation.
import{ RealdataAPIClient }from'RealdataAPI-Client';// Initialize the RealdataAPIClient with API tokenconst client =newRealdataAPIClient({token:'<YOUR_API_TOKEN>',});// Prepare actor inputconst input ={"location":"London"};(async()=>{// Run the actor and wait for it to finishconst run =await client.actor("jupri/zomato").call(input);// Fetch and print actor results from the run's dataset (if any)
console.log('Results from dataset');const{ items }=await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item)=>{
console.dir(item);});})();
from RealdataAPI_client import RealdataAPIClient
# Initialize the RealdataAPIClient with your API token
client = RealdataAPIClient("<YOUR_API_TOKEN>")# Prepare the actor input
run_input ={"location":"London"}# Run the actor and wait for it to finish
run = client.actor("jupri/zomato").call(run_input=run_input)# Fetch and print actor results from the run's dataset (if there are any)for item in client.dataset(run["defaultDatasetId"]).iterate_items():print(item)
# Set API tokenAPI_TOKEN=<YOUR_API_TOKEN># Prepare actor inputcat> input.json <<'EOF'
{
"location": "London"
}
EOF# Run the actorcurl"https://api.RealdataAPI.com/v2/acts/jupri~zomato/runs?token=$API_TOKEN"/-X POST /-d @input.json /-H'Content-Type: application/json'
Disclaimer : Real Data API only extracts publicly available data while maintaining a strict policy against collecting any personal or identity-related information.
