Trie (Prefix Tree) is a data structure that is used to store a dynamic set of strings, and provides an efficient way to query for words with a given prefix. It is used in many applications such as spell-checkers, autocomplete, and text-parsing. In this article, we will discuss how to implement a Trie (Prefix Tree) and how it can be used to solve 75 Leetcode questions.
Implementing Trie (Prefix Tree)
A Trie (Prefix Tree) is a tree-like data structure that is used to store a collection of strings. It consists of nodes that contain a character and a pointer to the next node. The root node is empty and each node can have up to 26 children. The number of children depends on the number of characters in a string. The leaves of the tree represent the strings stored in the Trie.
To implement a Trie, we need to define the Node class which will represent each node in the tree. The Node class should contain a character, a pointer to the next node in the tree, and a boolean value that indicates if the node is a leaf or not. We can also add a dictionary of the children nodes, so that we can quickly access any child node.
We also need to define the Trie class which will contain the root node and the methods to add a string to the Trie and to search for a string in the Trie. The add() method should traverse the Trie and add the characters of the string to the tree. The search() method should traverse the Trie and search for the string.
Blind 75 Leetcode Questions
Trie (Prefix Tree) can be used to solve a wide range of problems related to strings. For example, it can be used to solve the Blind 75 Leetcode questions. These questions require you to find the longest prefix of a given string that is a valid word in a dictionary. To solve these questions, we can use a Trie to store the dictionary of valid words and then search for the longest prefix of the given string.
Another use of Trie (Prefix Tree) is to find all the words in a given dictionary that start with a given prefix. To solve this problem, we can use the search() method of the Trie to search for the prefix and then traverse the Trie to find all the words that start with the given prefix.
Finally, Trie (Prefix Tree) can also be used to find all the words in a given dictionary that contain a given pattern. To solve this problem, we can use the search() method of the Trie to search for the pattern and then traverse the Trie to find all the words that contain the given pattern.
In conclusion, Trie (Prefix Tree) is a powerful data structure that can be used to solve a wide range of problems related to strings. It can be used to solve the Blind 75 Leetcode questions, to find all the words in a given dictionary that start with a given prefix, and to find all the words in a given dictionary that contain a given pattern.