'''
https://leetcode.com/problems/implement-trie-prefix-tree/
208. Implement Trie (Prefix Tree)
Medium

5780

82

Add to List

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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.
boolean search(String word) Returns true if the string word is in the trie (i.e., was inserted before), and false otherwise.
boolean startsWith(String prefix) Returns true if there is a previously inserted string word that has the prefix prefix, and false otherwise.
 

Example 1:

Input
["Trie", "insert", "search", "search", "startsWith", "insert", "search"]
[[], ["apple"], ["apple"], ["app"], ["app"], ["app"], ["app"]]
Output
[null, null, true, false, true, null, true]

Explanation
Trie trie = new Trie();
trie.insert("apple");
trie.search("apple");   // return True
trie.search("app");     // return False
trie.startsWith("app"); // return True
trie.insert("app");
trie.search("app");     // return True
 

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, search, and startsWith.'''


class Trie:

    def __init__(self):
        """
        Initialize your data structure here.
        """
        self.trie = {}

    def insert(self, word: str) -> None:
        """
        Inserts a word into the trie.
        """
        t = self.trie
        for i in word:
            if i not in t:
                t[i] = {}
            t = t[i]
        t['is_word'] = 1

    def search(self, word: str) -> bool:
        """
        Returns if the word is in the trie.
        """
        t = self.trie
        for i in word:
            if i not in t:
                return False
            t = t[i]
        if 'is_word' not in t:
            return False
        return True

    def startsWith(self, prefix: str) -> bool:
        """
        Returns if there is any word in the trie that starts with the given prefix.
        """
        t = self.trie
        for i in prefix:
            if i not in t:
                return False
            t = t[i]
        return True


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

'''
https://leetcode.com/problems/implement-trie-prefix-tree/
208. Implement Trie (Prefix Tree)
Medium

5780

82

Add to List

Share
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.
boolean search(String word) Returns true if the string word is in the trie (i.e., was inserted before), and false otherwise.
boolean startsWith(String prefix) Returns true if there is a previously inserted string word that has the prefix prefix, and false otherwise.
 

Example 1:

Input
["Trie", "insert", "search", "search", "startsWith", "insert", "search"]
[[], ["apple"], ["apple"], ["app"], ["app"], ["app"], ["app"]]
Output
[null, null, true, false, true, null, true]

Explanation
Trie trie = new Trie();
trie.insert("apple");
trie.search("apple");   // return True
trie.search("app");     // return False
trie.startsWith("app"); // return True
trie.insert("app");
trie.search("app");     // return True
 

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, search, and startsWith.'''


class Trie:

    def __init__(self):
        """
        Initialize your data structure here.
        """
        self.trie = {}

    def insert(self, word: str) -> None:
        """
        Inserts a word into the trie.
        """
        t = self.trie
        for i in word:
            if i not in t:
                t[i] = {}
            t = t[i]
        t['is_word'] = 1

    def search(self, word: str) -> bool:
        """
        Returns if the word is in the trie.
        """
        t = self.trie
        for i in word:
            if i not in t:
                return False
            t = t[i]
        if 'is_word' not in t:
            return False
        return True

    def startsWith(self, prefix: str) -> bool:
        """
        Returns if there is any word in the trie that starts with the given prefix.
        """
        t = self.trie
        for i in prefix:
            if i not in t:
                return False
            t = t[i]
        return True


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

https://leetcode.com/problems/implement-trie-prefix-tree/ 208. Implement Trie (Prefix Tree) Medium  5780  82  Add to List  Share 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. boolean search(String word) Returns true if the string word is in the trie (i.e., was inserted before), and false otherwise. boolean startsWith(String prefix) Returns true if there is a previously inserted string word that has the prefix prefix, and false otherwise.    Example 1:  Input ["Trie", "insert", "search", "search", "startsWith", "insert", "search"] [[], ["apple"], ["apple"], ["app"], ["app"], ["app"], ["app"]] Output [null, null, true, false, true, null, true]  Explanation Trie trie = new Trie(); trie.insert("apple"); trie.search("apple");   // return True trie.search("app");     // return False trie.startsWith("app"); // return True trie.insert("app"); trie.search("app");     // return True    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, search, and startsWith. Initialize your data structure here. Inserts a word into the trie. Returns if the word is in the trie. Returns if there is any word in the trie that starts with the given prefix. # Your Trie object will be instantiated and called as such: # obj = Trie() # obj.insert(word) # param_2 = obj.search(word) # param_3 = obj.startsWith(prefix)