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109 lines
3.3 KiB
Plaintext
109 lines
3.3 KiB
Plaintext
---
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title: '211. Design Add and Search Words Data Structure'
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description: Design a data structure that supports adding new words and finding if a string matches any previously added string
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icon: dot
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topics:
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- { name: "String", slug: "string" }
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- { name: "Depth-First Search", slug: "depth-first-search" }
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- { name: "Design", slug: "design" }
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- { name: "Trie", slug: "trie" }
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video: "BTf05gs_8iU"
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issue: "https://github.com/prdlk/leetcode/issues/128"
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sidebar:
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label: 'Design Add and Search Words Data Structure'
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badge: 'Medium'
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---
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### Constraints:
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- `1 <= word.length <= 25`
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- `word` in addWord consists of lowercase English letters.
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- `word` in search consist of '.' or lowercase English letters.
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- There will be at most 2 dots in `word` for search queries.
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- At most 10^4 calls will be made to addWord and search.
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## Approach
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```mermaid
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flowchart TD
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subgraph state["state — root TrieNode; every node holds a children dict and an endOfWord flag"]
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R["root"] --- C["... children[c] ..."] --- L["endOfWord = True — a word ends here"]
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end
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subgraph addWord["addWord(word)"]
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A1["cur = root"] --> A2{"more c in word?"}
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A2 -- yes --> A3{"c not in cur.children?"}
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A3 -- yes --> A4["cur.children[c] = TrieNode()"]
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A4 --> A5["cur = cur.children[c]"]
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A3 -- no --> A5
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A5 --> A2
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A2 -- no --> A6["cur.endOfWord = True"]
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A6 --> A7(["done"])
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end
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subgraph search["search(word)"]
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S1["dfs(0, root) — match from index 0 at the root"] --> S2["cur = root"]
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S2 --> S3{"more i in range(j, len(word))?"}
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S3 -- no --> S4(["return cur.endOfWord"])
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S3 -- yes --> S5["c = word[i]"]
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S5 --> S6{"c == '.'?"}
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S6 -- yes --> S7{"more child in cur.children.values()?"}
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S7 -- yes --> S8{"dfs(i + 1, child)? — try the rest of the word from this child"}
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S8 -- yes --> S9(["return True"])
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S8 -- no --> S7
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S7 -- no --> S10(["return False — no child matched the wildcard"])
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S6 -- no --> S11{"c not in cur.children?"}
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S11 -- yes --> S12(["return False"])
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S11 -- no --> S13["cur = cur.children[c]"]
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S13 --> S3
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end
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state --> addWord
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state --> search
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```
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## Solution
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```py
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class TrieNode:
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def __init__(self):
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self.children = {}
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self.endOfWord = False
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class WordDictionary:
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def __init__(self):
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self.root = TrieNode()
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def addWord(self, word: str) -> None:
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cur = self.root
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for c in word:
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if c not in cur.children:
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cur.children[c] = TrieNode()
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cur = cur.children[c]
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cur.endOfWord = True
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# Leverage Recursion
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def search(self, word: str) -> bool:
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def dfs(j, root):
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cur = root
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for i in range(j, len(word)):
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c = word[i]
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if c == ".":
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for child in cur.children.values():
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if dfs(i + 1, child):
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return True
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return False
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else:
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if c not in cur.children:
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return False
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cur = cur.children[c]
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return cur.endOfWord
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return dfs(0, self.root)
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# Your WordDictionary object will be instantiated and called as such:
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# obj = WordDictionary()
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# obj.addWord(word)
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# param_3 = obj.search(word)
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```
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