# Uber Eats Sushi Restaurant Scraper, US Cities

**Use case:** 

Compare sushi delivery supply across four major US metros in one Uber Eats run. For strategy and site-selection teams making data-backed expansion decisions.

## Input

```json
{
  "locations": [
    "1600 Pennsylvania Ave NW, Washington, DC 20500, USA",
    "233 S Wacker Dr, Chicago, IL 60606, USA",
    "1 Ferry Building, San Francisco, CA 94111, USA",
    "700 Biscayne Blvd, Miami, FL 33132, USA"
  ],
  "search_keyword": "Sushi",
  "max_search_results": 10
}
```

## Output

```json
{
  "store_uuid": {
    "label": "Store UUID",
    "format": "string"
  },
  "name": {
    "label": "Store Name",
    "format": "string"
  },
  "url": {
    "label": "Store URL",
    "format": "url"
  },
  "city": {
    "label": "City",
    "format": "string"
  },
  "country_code": {
    "label": "Country Code",
    "format": "string"
  },
  "estimated_time_to_delivery": {
    "label": "Estimated Time to Delivery",
    "format": "string"
  },
  "rating": {
    "label": "Rating",
    "format": "number"
  },
  "rating_count": {
    "label": "Rating Count",
    "format": "string"
  },
  "images": {
    "label": "Store Images",
    "format": "array"
  },
  "extraction_date": {
    "label": "Extraction Date",
    "format": "string"
  },
  "extraction_datetime": {
    "label": "Extraction Datetime",
    "format": "string"
  },
  "input": {
    "label": "Input",
    "format": "object"
  }
}
```

## About this Actor

This example demonstrates how to use [Ubereats Stores Search By Location And Keyword](https://apify.com/datacach/ubereats-stores-search-by-location-and-keyword) with a specific input configuration. Visit the [Actor detail page](https://apify.com/datacach/ubereats-stores-search-by-location-and-keyword) to learn more, explore other use cases, and run it yourself.