🍔 Uber Eats Scraper

Uber Eats Scraper is a free and open-source scraper that gets you unlimited detailed Uber Eats data for free.

✨ What Can I Get?

• 🍔 Full store details in 35 countries — phone, address, coordinates, hours, rating, cuisines & chain
• 📋 Complete menus — every item with price, photo, popularity & all customization options
• 🔎 80 stores per search — any address, with rating, price, delivery-time & offer filters
• 🗺️ The whole directory — every city, neighborhood and brand location Uber Eats lists

🍟 Example: A Full Uber Eats Store

{
  "id": "65686398-f585-439b-ae4c-dabe058a0a60",
  "name": "Five Guys (253 W. 42nd St.) NY - 1499",
  "link": "https://www.ubereats.com/store/five-guys-253-w-42nd-st-ny-1499/ZWhjmPWFQ5uuTNq-BYoKYA",
  "phone": "+12123982600",
  "merchant_type": "restaurant",
  "price_range": "$",
  "cuisines": ["American", "Burgers", "Hot Dog", "Family Meals", "Sandwich", "Fast Food", "Snacks"],
  "rating": 4.6,
  "review_count": 8000,
  "is_open": true,
  "status": "Open until 3:53 AM",
  "currency": "USD",
  "location": {
    "address": "253 W 42nd St, New York, NY 10036",
    "city": "New York",
    "region": "NY",
    "postal_code": "10036",
    "country": "US",
    "latitude": 40.7569903,
    "longitude": -73.9896063
  },
  "delivery": {
    "min_minutes": 11,
    "max_minutes": 23,
    "distance": { "value": 0.2, "unit": "mi" },
    "is_within_range": true
  },
  "hours": [
    {
      "days": "Every Day",
      "periods": [
        { "menu": "Menu", "opens_at": "06:30", "closes_at": "03:53", "closes_next_day": true }
      ]
    }
  ],
  "chain": { "id": "a32f0de2-ec42-44ee-965b-7b420b86e9f8", "name": "Five Guys" },
  "menus": [
    { "id": "a7abc1e5-7f23-5a76-ae26-32b76268deec", "title": "Menu", "hours_text": "6:30 AM – 3:53 AM", "item_count": 41 }
  ],
  "joined_at": "2020-02-04T01:22:17Z"
}

Trimmed for readability.

🚀 Unlimited Free Uber Eats Data — Get It in 60 Seconds

1️⃣ Clone and install:

git clone https://github.com/omkarcloud/uber-eats-scraper
cd uber-eats-scraper
python -m pip install -r requirements.txt

2️⃣ Start the API:

python run.py

3️⃣ Get your first data:

curl "http://localhost:8000/stores/details?store=ZWhjmPWFQ5uuTNq-BYoKYA"

{
  "location": null,
  "store": {
    "id": "65686398-f585-439b-ae4c-dabe058a0a60",
    "name": "Five Guys (253 W. 42nd St.) NY - 1499",
    "link": "https://www.ubereats.com/store/five-guys-253-w-42nd-st-ny-1499/ZWhjmPWFQ5uuTNq-BYoKYA",
    "phone": "+12123982600",
    "price_range": "$",
    "cuisines": ["American", "Burgers", "Hot Dog", "Family Meals", "Sandwich", "Fast Food", "Snacks"],
    "rating": 4.6,
    "review_count": 8000,
    "is_open": true,
    "status": "Open until 12:53 AM",
    "currency": "USD",
    "location": {
      "address": "253 W 42nd St, New York, NY 10036",
      "latitude": 40.7569903,
      "longitude": -73.9896063
    },
    "chain": { "id": "a32f0de2-ec42-44ee-965b-7b420b86e9f8", "name": "Five Guys" }
  }
}

All 20 endpoints are now live at http://localhost:8000.

Seeing 403 after a few hundred store or search calls? Uber Eats puts a reCAPTCHA wall in front of a busy IP. Set UBER_EATS_PROXY=http://user:pass@host:port (a residential proxy) before python run.py and keep going.

📚 Endpoints

20 endpoints cover everything you need.

Endpoint	Path	Returns
Store Details	/stores/details	Phone, address, hours, rating and delivery estimate in one call
Store Menu	/stores/menu	Every menu item with price, photo and popularity
Menu Item Details	/stores/menu/item	Every size, topping and side with its price
Store Reviews	/stores/reviews	Customer reviews with names and dates
Address Autocomplete	/locations/autocomplete	Address suggestions as you type
Resolve Location	/locations/details	Any address turned into a clean delivery point
Search Stores	/stores/search	80 stores per page for any dish or cuisine, filterable
Nearby Stores	/stores/nearby	Every store delivering to an address, filterable
Store Collections	/stores/collections	The home feed shelves: favorites, offers, popular
Search Store Menu	/stores/menu/search	Find any dish or product inside one store
Menu Section	/stores/menu/section	A full grocery aisle or menu section, paged
Search Suggestions	/search/suggestions	Search-box completions and matching stores
Popular Searches	/search/popular	Top cuisines and top grocery searches at an address
City Stores	/cities/stores	A city's stores, 20 per page, by cuisine if you like
City Details	/cities/details	A city's top cuisines, FAQ and nearby cities
Cities	/cities	Every city served in a country, grouped by state
Countries	/countries	Every country Uber Eats operates in
Neighborhood Stores	/neighborhoods/stores	Up to 80 stores of one neighborhood
Brand Stores	/brands/stores	Every location of a chain in a city, with coordinates
Brand Details	/brands/details	Every city a chain delivers in, with location counts

🔍 Exploring Parameters

The same API is published on RapidAPI, and its playground is the easiest place to try parameters and see raw responses. Once a request looks right, run it locally for unlimited free data.

1. Subscribe to the free plan — 1,000 calls/month, no credit card.
2. Try the endpoints in the playground — every param is pre-filled, so you see real data in one click.
3. Copy the generated code and replace https://best-uber-eats-scraper-free-1000-calls.p.rapidapi.com with http://localhost:8000. It will now run against your local API.

import requests

# generated by the playground, host swapped for the local API
response = requests.get(
    "http://localhost:8000/stores/search",
    params={"query": "sushi", "location": "Times Square, New York"},
)
print(response.json())

💬 Have Questions? We Have Answers.

You're a developer — we know how hard completing a project can be. So we offer full support: just message us and we'll reply ✅ with a solution within 1 working day.

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