Problem description:

A trie (pronounced as “try”) or prefix tree is a tree data structure used to efficiently store and retrieve keys in a dataset of strings. There are various applications of this data structure, such as autocomplete and spellchecker.

Implement the Trie class:

  • Trie() Initializes the trie object.
  • void insert(String word) Inserts the string word into the trie.
  • int countWordsEqualTo(String word) Returns the number of instances of the string word in the trie.
  • int countWordsStartingWith(String prefix) Returns the number of strings in the trie that have the string prefix as a prefix.
  • void erase(String word) Erases the string word from the trie.

Solution:

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class TrieNode:
    def __init__(self):
        self.child = defaultdict(TrieNode)
        self.count = 0
        self.tail = 0

class Trie:
    def __init__(self):
        self.root = TrieNode()

    def insert(self, word: str) -> None:
        p = self.root
        for c in word:
            p = p.child[c]
            p.count += 1
        p.tail += 1

    def countWordsEqualTo(self, word: str) -> int:
        p = self.root
        for c in word:
            if c in p.child:
                p = p.child[c]
            else:
                return 0
        return p.tail

    def countWordsStartingWith(self, prefix: str) -> int:
        p = self.root
        for c in prefix:
            if c in p.child:
                p = p.child[c]
            else:
                return 0
        return p.count

    def erase(self, word: str) -> None:
        p = self.root
        for c in word:
            if c in p.child:
                p = p.child[c]
                p.count -= 1
        p.tail -= 1


# Your Trie object will be instantiated and called as such:
# obj = Trie()
# obj.insert(word)
# param_2 = obj.countWordsEqualTo(word)
# param_3 = obj.countWordsStartingWith(prefix)
# obj.erase(word)

time complexity: $O()$
space complexity: $O()$
reference:
related problem: