- Give each element a component representative.
- Merge representatives when a connection is accepted.
- Answer connectivity or component queries from the compressed representatives.
Code notes
- 132 lines of Python from the credited upstream file abc350_d.py.
- The implementation visibly relies on sequence storage, ordered lookup.
- No explicit loop blocks detected.
Complexity
Account for every find and union operation; with path compression and ranked merging, the amortized cost is nearly constant per operation.
Check the problem constraints before deciding whether this complexity will pass.
Use this to learn the idea, then write your own version.
12 3 4from typing import List5 6 7class UnionFind:8 """Represents a data structure that tracks a set of elements partitioned9 into a number of disjoint (non-overlapping) subsets.10 11 Landau notation: O(α(n)), where α(n) is the inverse Ackermann function.12 13 See:14 https:www.youtube.com/watch?v=zV3Ul2pA2Fw15 https:en.wikipedia.org/wiki/Disjoint-set_data_structure16 https:atcoder.jp/contests/abc120/submissions/444494217 https:atcoder.jp/contests/abc292/submissions/3941007518 """19 20 def __init__(self, number_count: int) -> None:21 """22 Args:23 number_count: The size of elements (greater than 2).24 """25 self.parent_numbers = [-1 for _ in range(number_count)]26 self.edge_count = [0 for _ in range(number_count)]27 self.group_count = number_count28 29 def find_root(self, number: int) -> int:30 """Follows the chain of parent pointers from number up the tree until31 it reaches a root element, whose parent is itself.32 Args:33 number: The trees id (0-index).34 35 Returns:36 The index of a root element.37 """38 if self.parent_numbers[number] < 0:39 return number40 41 self.parent_numbers[number] = self.find_root(self.parent_numbers[number])42 return self.parent_numbers[number]43 44 def get_group_size(self, number: int) -> int:45 """46 Args:47 number: The trees id (0-index).48 49 Returns:50 The size of group.51 """52 return -self.parent_numbers[self.find_root(number)]53 54 def is_same_group(self, number_x: int, number_y: int) -> bool:55 """Represents the roots of tree number_x and number_y are in the same56 group.57 Args:58 number_x: The trees x (0-index).59 number_y: The trees y (0-index).60 """61 return self.find_root(number_x) == self.find_root(number_y)62 63 def merge_if_needs(self, number_x: int, number_y: int) -> bool:64 """Uses find_root to determine the roots of the tree number_x and65 number_y belong to. If the roots are distinct, the trees are combined66 by attaching the roots of one to the root of the other.67 Args:68 number_x: The trees x (0-index).69 number_y: The trees y (0-index).70 """71 x = self.find_root(number_x)72 y = self.find_root(number_y)73 74 self.edge_count[x] += 175 76 if x == y:77 return False78 79 self.group_count -= 180 81 if self.parent_numbers[x] > self.parent_numbers[y]:82 x, y = y, x83 84 self.parent_numbers[x] += self.parent_numbers[y]85 self.parent_numbers[y] = x86 self.edge_count[x] += self.edge_count[y]87 return True88 89 def get_roots(self) -> List[int]:90 return [i for i, x in enumerate(self.parent_numbers) if x < 0]91 92 def get_edge_count(self, number: int) -> int:93 return self.edge_count[number]94 95 def get_group_count(self) -> int:96 return self.group_count97 98 99def main():100 import sys101 102 input = sys.stdin.readline103 104 n, m = map(int, input().split())105 graph = [[] for _ in range(n)]106 uf = UnionFind(n)107 108 109 for _ in range(m):110 ai, bi = map(int, input().split())111 ai -= 1112 bi -= 1113 114 graph[ai].append(bi)115 graph[bi].append(ai)116 117 if not uf.is_same_group(ai, bi):118 uf.merge_if_needs(ai, bi)119 120 ans = 0121 122 for root in uf.get_roots():123 size = uf.get_group_size(root)124 count = size * (size - 1) 2 125 ans += count126 127 print(ans - m)128 129 130if __name__ == "__main__":131 main()132