How do you solve Distribute Candies on LeetCode?

Distribute Candies (LeetCode #575) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: To maximize unique types, focus on the number of distinct candies available.

What is the brute force solution for Distribute Candies?

The brute force approach for Distribute Candies is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach involves checking all possible combinations of candies Alice can eat. This is straightforward but inefficient, as it doesn't leverage any patterns in the data. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Distribute Candies?

Distribute Candies uses the following concepts: Array, Hash Table. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Distribute Candies?

Always think about the properties of the data (like uniqueness) before diving into complex algorithms. Consider edge cases, such as all candies being the same type. Practice explaining your thought process clearly, as communication is key in interviews.

What are common mistakes when solving Distribute Candies?

Confusing the number of candies Alice can eat with the number of unique types. Overcomplicating the problem by trying to generate combinations instead of using sets.

#575

Distribute Candies

Easy

ArrayHash TableHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(n)

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Intuition

Time O(n)Space O(n)

The optimal solution leverages the properties of sets to count unique candy types directly, avoiding the need for combinations. This is efficient and straightforward.

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Algorithm

3 steps

1Step 1: Create a set from the candyType array to get unique candy types.
2Step 2: Calculate the maximum number of candies Alice can eat, which is n / 2.
3Step 3: Return the minimum of the size of the unique types set and n / 2.

solution.py3 lines

1def maxUniqueCandies(candyType):
2    unique_types = set(candyType)
3    return min(len(unique_types), len(candyType) // 2)

ℹ

Complexity note: This complexity is linear because we traverse the candyType array once to create the set of unique types, and the space complexity is also linear due to storing the unique types.

1To maximize unique types, focus on the number of distinct candies available.
2The limit of unique types Alice can eat is constrained by both the number of unique candies and n / 2.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.