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Design A Food Rating System - Leetcode Solution

Companies:

  • amazon

LeetCode:  Design A Food Rating System Leetcode Solution

Difficulty: Medium

Topics: design heap-priority-queue hash-table  

The "Design A Food Rating System" problem on LeetCode can be solved using the Object-Oriented Programming (OOP) concept. In this problem, we need to design a system for rating food items based on user reviews.

Approach:

We can create two classes for this problem:

  1. Food: This class will store the information about the food item's name, type (cuisine), and the average rating. It will also have a method to update the average rating based on new reviews.

  2. Review: This class will store the information about user reviews. It will have attributes like username, rating, and comments.

The system can be designed as follows:

  1. Create a Food class with the following attributes:
  • name: string
  • type: string
  • rating: float
  1. Create a Review class with the following attributes:
  • username: string
  • rating: float
  • comment: string
  1. Create a method in the Food class to add a new Review:
  • def add_review(self, review: Review) -> None:
  • """
  • Add a new review to the food item
  • """
  • self.reviews.append(review)
  • self.recalculate_rating()
  1. Create a method in the Food class to calculate the average rating:
  • def recalculate_rating(self):
  • """
  • Recalculate the average rating based on all reviews
  • """
  • if len(self.reviews) == 0:
  • self.rating = 0
  • else:
  • self.rating = sum([r.rating for r in self.reviews])/len(self.reviews)
  1. Create a FoodRatingSystem class to manage the food items and reviews:
  • def init(self):
  • self.foods = []
  1. Create a method in the FoodRatingSystem class to add a new food item:
  • def add_food(self, food: Food) -> None:
  • """
  • Add a new food item to the system
  • """
  • self.foods.append(food)
  1. Create a method in the FoodRatingSystem class to get the top N (N is given as input) food items by average rating:
  • def get_top_n_foods(self, n: int) -> List[str]:
  • """
  • Get the top N food items by average rating
  • """
  • sorted_foods = sorted(self.foods, key=lambda f: f.rating, reverse=True)
  • top_n_foods = [f.name for f in sorted_foods[:n]]
  • return top_n_foods
  1. Create a method in the FoodRatingSystem class to add a new review for a food item:
  • def add_review_for_food(self, food_name: str, review: Review) -> None:
  • """
  • Add a review for a food item
  • """
  • for food in self.foods:
  • if food.name == food_name:
  • food.add_review(review)
  • break
  1. Create a method in the FoodRatingSystem class to get the average rating of a food item:
  • def get_average_rating_for_food(self, food_name: str) -> float:
  • """
  • Get the average rating for a food item
  • """
  • for food in self.foods:
  • if food.name == food_name:
  • return food.rating
  • return None
  1. Create a method in the FoodRatingSystem class to get all the reviews for a food item:
  • def get_reviews_for_food(self, food_name: str) -> List[Review]:
  • """
  • Get all reviews for a food item
  • """
  • for food in self.foods:
  • if food.name == food_name:
  • return food.reviews
  • return []

Once we have implemented the above classes and methods, we can use them to manage food items and reviews. We can add new food items, add reviews for existing food items, and get the top N food items by average rating.

Time Complexity:

The time complexity of adding a food item is O(1).

The time complexity of adding a new review to a food item is O(N), where N is the number of reviews for the food item.

The time complexity of calculating the average rating for a food item is O(N), where N is the number of reviews for the food item.

The time complexity of getting the top N food items by average rating is O(N log N), where N is the number of food items.

The time complexity of getting the average rating for a food item is O(N), where N is the number of reviews for the food item.

The time complexity of getting all reviews for a food item is O(N), where N is the number of reviews for the food item.

Therefore, we can conclude that the overall time complexity of this approach is O(N log N).

Design A Food Rating System Solution Code

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