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1804. Implement Trie II (Prefix Tree)

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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.

Example 1:

Input
["Trie", "insert", "insert", "countWordsEqualTo", "countWordsStartingWith", "erase", "countWordsEqualTo", "countWordsStartingWith", "erase", "countWordsStartingWith"]
[[], ["apple"], ["apple"], ["apple"], ["app"], ["apple"], ["apple"], ["app"], ["apple"], ["app"]]
Output
[null, null, null, 2, 2, null, 1, 1, null, 0]

Explanation
Trie trie = new Trie();
trie.insert("apple");               // Inserts "apple".
trie.insert("apple");               // Inserts another "apple".
trie.countWordsEqualTo("apple");    // There are two instances of "apple" so return 2.
trie.countWordsStartingWith("app"); // "app" is a prefix of "apple" so return 2.
trie.erase("apple");                // Erases one "apple".
trie.countWordsEqualTo("apple");    // Now there is only one instance of "apple" so return 1.
trie.countWordsStartingWith("app"); // return 1
trie.erase("apple");                // Erases "apple". Now the trie is empty.
trie.countWordsStartingWith("app"); // return 0

Constraints:

  • 1 <= word.length, prefix.length <= 2000
  • word and prefix consist only of lowercase English letters.
  • At most 3 * 104 calls in total will be made to insert, countWordsEqualTo, countWordsStartingWith, and erase.
  • It is guaranteed that for any function call to erase, the string word will exist in the trie.

Asked at 2 companies

Hints open one at a time

Hint 1
Try to solve the first version first and reuse your code.
Hint 2
To implement the delete function, you should delete the trie nodes of the word if they are not shared with other words.
Hint 3
You should keep for each trie node a counter of how many words share this node.
10:49
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1class Solution:
2 def solve(self):
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Starter codePython 3Spaces: 4
Examples
Input
["Trie","insert","insert","countWordsEqualTo","countWordsStartingWith","erase","countWordsEqualTo","countWordsStartingWith","erase","countWordsStartingWith"]
[[],["apple"],["apple"],["apple"],["app"],["apple"],["apple"],["app"],["apple"],["app"]]
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