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Update README.md
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@ -26,7 +26,7 @@ class Trie:
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def __init__(self):
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def __init__(self):
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self.root = {}
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self.root = {}
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def insert(self, word: str) -> None:
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def insert(self, word: str)L
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node = self.root
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node = self.root
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for c in word:
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for c in word:
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if c not in node:
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if c not in node:
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@ -58,6 +58,7 @@ class Trie:
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<br>
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<br>
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* similar to a bst, when we insert a value to a trie, we need to decide which path to go depending on the target value we insert.
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* similar to a bst, when we insert a value to a trie, we need to decide which path to go depending on the target value we insert.
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* the root node needs to be initialized before you insert strings.
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* the root node needs to be initialized before you insert strings.
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@ -71,10 +72,13 @@ class Trie:
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<br>
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<br>
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* all the descendants of a node have a common prefix of the string associated with that node, so it should be easy to search if there are any words in the trie that starts with the given prefix.
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* all the descendants of a node have a common prefix of the string associated with that node, so it should be easy to search if there are any words in the trie that starts with the given prefix.
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* we go down the tree depending on the given prefix, once we cannot find the child node, the search fails.
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* we go down the tree depending on the given prefix, once we cannot find the child node, the search fails.
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* we can also search for a specific word rather than a prefix, treating this word as a prefix and searching in the same way as above.
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* we can also search for a specific word rather than a prefix, treating this word as a prefix and searching in the same way as above.
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* if the search succeeds, we need to check if the target word is only a prefix of words in the trie or if it's exactly a word (for example, by adding a boolean flag).
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* if the search succeeds, we need to check if the target word is only a prefix of words in the trie or if it's exactly a word (for example, by adding a boolean flag).
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