839.Similar String Groups === ###### tags: `Hard`,`Array`,`String`,`DFS`,`BFS` [839. Similar String Groups](https://leetcode.com/problems/similar-string-groups/) ### 題目描述 Two strings `X` and `Y` are similar if we can swap two letters (in different positions) of `X`, so that it equals `Y`. Also two strings `X` and `Y` are similar if they are equal. For example, `"tars"` and `"rats"` are similar (swapping at positions 0 and 2), and `"rats"` and `"arts"` are similar, but `"star"` is not similar to `"tars"`, `"rats"`, or `"arts"`. Together, these form two connected groups by similarity: `{"tars", "rats", "arts"}` and `{"star"}`. Notice that `"tars"` and `"arts"` are in the same group even though they are not similar. Formally, each group is such that a word is in the group if and only if it is similar to at least one other word in the group. We are given a list `strs` of strings where every string in `strs` is an anagram of every other string in `strs`. How many groups are there? ### 範例 **Example 1:** ``` Input: strs = ["tars","rats","arts","star"] Output: 2 ``` **Example 2:** ``` Input: strs = ["omv","ovm"] Output: 1 ``` **Constraints**: * 1 <= `strs.length` <= 300 * 1 <= `strs[i].length` <= 300 * `strs[i]` consists of lowercase letters only. * All words in `strs` have the same length and are anagrams of each other. ### 解答 #### Python ```python= class Solution: def numSimilarGroups(self, strs: List[str]) -> int: n = len(strs) parents = list(range(n)) def find(x): if parents[x] != x: parents[x] = find(parents[x]) return parents[x] def union(x, y): xr, yr = find(x), find(y) if xr != yr: parents[xr] = yr def similar(s1, s2): diff = 0 for c1, c2 in zip(s1, s2): if c1 != c2: diff += 1 if diff > 2: return False return diff == 0 or diff == 2 for i, j in combinations(range(n), 2): if similar(strs[i], strs[j]): union(i, j) return len(set(find(i) for i in range(n))) ``` > [name=Yen-Chi Chen][time=Fri, Apr 28, 2023] ### ChatGPT ![](https://i.imgur.com/Isi2yzR.png) To solve this problem, you can use the Disjoint Set Union (DSU) data structure. It's a data structure that allows you to efficiently group elements into disjoint sets and check which set an element belongs to. Here's a Python implementation to solve the problem: ```python= class DSU: def __init__(self, n): self.parent = list(range(n)) def find(self, x): if self.parent[x] != x: self.parent[x] = self.find(self.parent[x]) return self.parent[x] def union(self, x, y): xr, yr = self.find(x), self.find(y) if xr != yr: self.parent[xr] = yr def are_similar(s1, s2): diff_count = 0 for i in range(len(s1)): if s1[i] != s2[i]: diff_count += 1 if diff_count > 2: return False return diff_count == 2 or diff_count == 0 def count_groups(strs): n = len(strs) dsu = DSU(n) for i in range(n): for j in range(i + 1, n): if are_similar(strs[i], strs[j]): dsu.union(i, j) return len(set(dsu.find(i) for i in range(n))) # Example usage strs = ["tars", "rats", "arts", "star"] print(count_groups(strs)) # Output: 2 ``` This implementation defines a DSU class with the basic functionality for union and find operations. The `are_similar` function checks if two strings are similar, and the `count_groups` function counts the number of groups in the input list of strings using the DSU class. ### Reference [回到題目列表](https://hackmd.io/@Marsgoat/leetcode_every_day)