Implement Trie (Prefix Tree)

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.

SOLUTION:

class Node:
    def __init__(self, val=None, children=[], end=False):
        self.val = val
        self.children = children
        self.end = end

class Trie:
    def __init__(self):
        self.root = Node(val=None, children=[])

    def insert(self, word: str) -> None:
        n = len(word)
        curr = self.root
        for i, c in enumerate(word):
            found = False
            for node in curr.children:
                if node.val == c:
                    curr = node
                    found = True
                    break
            if not found:
                newcurr = Node(val=c, children=[])
                curr.children.append(newcurr)
                curr = newcurr
        curr.end = True

    def search(self, word: str) -> bool:
        n = len(word)
        curr = self.root
        for i, c in enumerate(word):
            found = False
            for node in curr.children:
                if node.val == c:
                    curr = node
                    found = True
                    break
            if not found:
                return False
        return curr.end

    def startsWith(self, prefix: str) -> bool:
        n = len(prefix)
        curr = self.root
        for i, c in enumerate(prefix):
            found = False
            for node in curr.children:
                if node.val == c:
                    curr = node
                    found = True
                    break
            if not found:
                return False
        return True

# class Trie:

#     def __init__(self):
#         self.trie = {}

#     def insert(self, word: str) -> None:
#         word = list(word) + [-1]
#         n = len(word)
#         for i in range(n - 1):
#             if i not in self.trie:
#                 self.trie[i] = {}
#             if word[i] in self.trie[i]:
#                 self.trie[i][word[i]].add(word[i + 1])
#             else:
#                 self.trie[i][word[i]] = {word[i + 1]}

#     def search(self, word: str, isPartial = False) -> bool:
#         if not isPartial:
#             word = list(word) + [-1]
#         n = len(word)
#         if n == 1:
#             if word[0] in self.trie.get(0, {}):
#                 return True
#             else:
#                 return False
#         for i in range(n - 1):
#             if i not in self.trie or word[i] not in self.trie[i] or word[i + 1] not in self.trie[i][word[i]]:
#                 return False
#         return True

#     def startsWith(self, prefix: str) -> bool:
#         return self.search(prefix, isPartial = 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)

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Implement Trie (Prefix Tree)

Abhishek Chaudhary

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