Trie
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- 500 solutions for LeetCode problems in Python and Java
- 17 notes on essential concepts related to data structures and algorithms
- 130 patterns for solving LeetCode problems
trie
intro
class TrieNode:
def __init__(self):
self.children = {}
self.is_word = False
class Trie:
def __init__(self):
self.root = TrieNode()
def insert(self, word: str) -> None:
node = self.root
for c in word:
if c not in node.children:
node.children[c] = TrieNode()
node = node.children[c]
node.is_word = True
def search(self, word: str) -> bool:
node = self.root
for c in word:
if c not in node.children:
return False
node = node.children[c]
return node.is_word
def startsWith(self, prefix: str) -> bool:
node = self.root
for c in prefix:
if c not in node.children:
return False
node = node.children[c]
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)
# time O(L) for insert(), search(), startsWith(), L is the word's length
# space O(nL), n is the number of words, L is the max len
- concepts
- trie is a prefix tree
- can insert word, search word, and search prefix efficiently in
O(L)
- a tree of character nodes
- every node has a hashmap for children nodes
- can insert word, search word, and search prefix efficiently in
- prune
- think about when we can stop finding deeper nodes
- think about remove certain node which no longer need to be considered
- trie’s variation can happen in
- trie node
- inserting way
- searching way
- trie is a prefix tree
pattern
- standard trie
- insert word, search word, and search prefix
- custom trie node
- the information to store in TrieNode can be different, depends on different problems
- like store a list, boolean, string inside each trie node
- notice the space complexity could increase
- when disucss about complexity need to mention that only count for number of nodes or consider the content inside
- notice the space complexity could increase
- store more info can improve time complexity sometimes
- perform dfs inside trie
- can use dfs as assistance for searching (eg. args: node, idx)
- could increase the time complexity for searching