What are some Trie implementation strategies?

There are several strategies for implementing a Trie data structure:

Array-based Implementation

In this approach, each Trie node contains an array where each index corresponds to a character of the alphabet. For example, 0 stands for 'a', 1 for 'b', and so on. While simple to understand, this method can consume more memory, especially if many of the array elements are unused[1][4].

Here is the Python code for an array-based implementation:

class TrieNode:
    def __init__(self):
        # Array for 26 letters of the alphabet
        self.children = [None] * 26
        self.isEndOfWord = False

# Initialize the root node
root = TrieNode()

Linked List Approach

In this implementation, each node corresponds to a character, and the child attribute points to the head of another linked list, representing the next level of characters. This approach can save memory when the number of child nodes is significantly less than the array size of the previous method[1][4].

Here is the Python code for a linked list implementation:

class TrieNode:
    def __init__(self, key=None, value=None, parent=None, ...