class DisjointSet:def __init__(self, n):# Args:#   n (int): Number of vertices in the graph
self.parent = [None] * n  # Contains which node is the parent of the node at poisition <i>self.size = [1] * n  # Contains size of node at index <i>, used to optimize mergefor i in range(n):self.parent[i] = i  # Make all nodes his own parent, creating n sets.def find_set(self, a):if self.parent[a] != a: # Very important, memoize result of the recursion in the list to optimize next# calls and make this operation practically constant, O(1)self.parent[a] = find_set(self.parent[a])# node <a> it's the set root, so we can return that indexreturn self.parent[a]def find_set2(self, a):parent_n = aparent_n1 = self.parent[parent_n]while parent_n1 != parent_n: time.sleep(2)parent_n = parent_n1parent_n1 = self.parent[parent_n]print(parent_n1, parent_n, a)return parent_n1def find_set3(self, a):visited, que = set(), [a]u = self.parent[a]while que: time.sleep(2)u = que.pop()if u not in visited:print(f"u={u} was visited")visited.add(u)que.append(self.parent[u])return udef find_set4(self, a):parent_n1 = awhile 1: time.sleep(2)parent_n = parent_n1parent_n1 = self.parent[parent_n]if parent_n1 == parent_n:breakprint(parent_n1, parent_n, a)return parent_n1def find_set5(self, a):parent_n = awhile 1: time.sleep(2)parent_n1 = self.parent[parent_n]if parent_n1 == parent_n:breakparent_n = parent_n1print(parent_n1, parent_n, a)return parent_n1def find_set6(self, a):parent_n = aparent_n1 = self.parent[parent_n]while 1: if parent_n1 != parent_n:  # 收敛条件breaktime.sleep(2)parent_n = parent_n1parent_n1 = self.parent[parent_n]print(parent_n1, parent_n, a)return parent_n1