2017-09-10 18:10:33 +00:00
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"""
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A Trie/Prefix Tree is a kind of search tree used to provide quick lookup
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of words/patterns in a set of words. A basic Trie however has O(n^2) space complexity
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making it impractical in practice. It however provides O(max(search_string, length of longest word)) lookup
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time making it an optimal approach when space is not an issue.
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"""
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class TrieNode:
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def __init__(self):
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self.nodes = dict() # Mapping from char to TrieNode
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self.is_leaf = False
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def insert_many(self, words: [str]):
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"""
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Inserts a list of words into the Trie
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:param words: list of string words
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:return: None
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"""
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for word in words:
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self.insert(word)
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2018-01-20 11:31:12 +00:00
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def insert(self, word: str): # noqa: F821 This syntax is Python 3 only
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2017-09-10 18:10:33 +00:00
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"""
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Inserts a word into the Trie
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:param word: word to be inserted
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:return: None
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"""
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curr = self
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for char in word:
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if char not in curr.nodes:
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curr.nodes[char] = TrieNode()
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curr = curr.nodes[char]
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curr.is_leaf = True
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def find(self, word: str) -> bool:
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"""
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Tries to find word in a Trie
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:param word: word to look for
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:return: Returns True if word is found, False otherwise
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"""
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curr = self
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for char in word:
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if char not in curr.nodes:
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return False
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curr = curr.nodes[char]
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return curr.is_leaf
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def print_words(node: TrieNode, word: str):
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"""
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Prints all the words in a Trie
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:param node: root node of Trie
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:param word: Word variable should be empty at start
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:return: None
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"""
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if node.is_leaf:
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print(word, end=' ')
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for key, value in node.nodes.items():
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print_words(value, word + key)
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def test():
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words = ['banana', 'bananas', 'bandana', 'band', 'apple', 'all', 'beast']
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root = TrieNode()
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root.insert_many(words)
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# print_words(root, '')
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assert root.find('banana')
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assert not root.find('bandanas')
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assert not root.find('apps')
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assert root.find('apple')
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test()
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