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Flatten Nested List Iterator

You are given a nested list of integers nestedList. Each element is either an integer or a list whose elements may also be integers or other lists. Implement an iterator to flatten it.

Implement the NestedIterator class:

  • NestedIterator(List<NestedInteger> nestedList) Initializes the iterator with the nested list nestedList.
  • int next() Returns the next integer in the nested list.
  • boolean hasNext() Returns true if there are still some integers in the nested list and false otherwise.

Your code will be tested with the following pseudocode:

initialize iterator with nestedList
res = []
while iterator.hasNext()
    append iterator.next() to the end of res
return res

If res matches the expected flattened list, then your code will be judged as correct.

 

Example 1:

Input: nestedList = [[1,1],2,[1,1]]
Output: [1,1,2,1,1]
Explanation: By calling next repeatedly until hasNext returns false, the order of elements returned by next should be: [1,1,2,1,1].

Example 2:

Input: nestedList = [1,[4,[6]]]
Output: [1,4,6]
Explanation: By calling next repeatedly until hasNext returns false, the order of elements returned by next should be: [1,4,6].

 

Constraints:

  • 1 <= nestedList.length <= 500
  • The values of the integers in the nested list is in the range [-106, 106].

Solution Explanation:

This problem requires creating an iterator that flattens a nested list of integers. The solution uses a depth-first search (DFS) approach to traverse the nested structure and collect all integers into a single list. This list is then used by the iterator to provide the next() and hasNext() functionality.

Approach:

  1. Depth-First Search (DFS): A recursive helper function dfs is used to traverse the nested list. It checks each element:

    • If the element is an integer, it's added to the nums list.
    • If the element is a nested list, the dfs function is called recursively on that sublist.

  2. Iterator Implementation: The NestedIterator class implements the iterator interface.

    • __init__(nestedList): Initializes the iterator by calling dfs to flatten the input list.
    • next(): Returns the next integer from the flattened nums list. It increments the internal index i.
    • hasNext(): Checks if there are more integers remaining in the nums list by comparing the index i with the list's length.

Time and Space Complexity Analysis:

  • Time Complexity: O(N), where N is the total number of integers in the nested list. The DFS traversal visits each integer exactly once.

  • Space Complexity: O(N) in the worst case, where the nested list is a deeply nested structure with many integers. This space is used to store the flattened list nums and the recursion stack during the DFS traversal. In the best case (a flat list), the space complexity is O(1) excluding the input list.

Code Explanation (Python):

The Python code directly implements the described approach. The dfs function is a helper function that recursively traverses the nested lists. The NestedIterator class then uses this flattened list to implement the iterator. Note that the problem definition includes a NestedInteger class definition, which is used in the code but is not fully implemented as it is part of the problem's interface and would require custom implementation based on the specific environment (LeetCode, etc.)

Code Explanation (Other Languages):

The Java, C++, Go, TypeScript, and Rust code examples follow the same overall approach. They differ in syntax and specific features of each language, but the core logic of the DFS and iterator implementation remains consistent. For example:

  • Java: Uses an ArrayList for nums and implements the Iterator interface.
  • C++: Uses a vector for nums and implements the iterator functionality explicitly.
  • Go: Uses a slice ([]int) for nums. The constructor is explicitly named Constructor.
  • TypeScript: Uses a number[] for nums and directly implements hasNext() and next().
  • Rust: Uses a Vec<i32> for nums and implements the iterator using the Iterator trait.

The provided code examples demonstrate a clear, efficient, and well-structured solution to the nested list iterator problem. The use of recursion through DFS simplifies the flattening process, and the separate iterator class provides a clean and organized implementation.