LeetCode 1971. Find if Path Exists in Graph Solution in Java, C++, Python & More | Explanation + Code

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1971. Find if Path Exists in Graph

Description

There is a bi-directional graph with n vertices, where each vertex is labeled from 0 to n - 1 (inclusive). The edges in the graph are represented as a 2D integer array edges, where each edges[i] = [ui, vi] denotes a bi-directional edge between vertex ui and vertex vi. Every vertex pair is connected by at most one edge, and no vertex has an edge to itself.

You want to determine if there is a valid path that exists from vertex source to vertex destination.

Given edges and the integers n, source, and destination, return true if there is a valid path from source to destination, or false otherwise.

 

Example 1:

Input: n = 3, edges = [[0,1],[1,2],[2,0]], source = 0, destination = 2
Output: true
Explanation: There are two paths from vertex 0 to vertex 2:
- 0 → 1 → 2
- 0 → 2

Example 2:

Input: n = 6, edges = [[0,1],[0,2],[3,5],[5,4],[4,3]], source = 0, destination = 5
Output: false
Explanation: There is no path from vertex 0 to vertex 5.

 

Constraints:

  • 1 <= n <= 2 * 105
  • 0 <= edges.length <= 2 * 105
  • edges[i].length == 2
  • 0 <= ui, vi <= n - 1
  • ui != vi
  • 0 <= source, destination <= n - 1
  • There are no duplicate edges.
  • There are no self edges.

Solutions

Solution 1: DFS

We first convert edges into an adjacency list g, then use DFS to determine whether there is a path from source to destination.

During the process, we use an array vis to record the vertices that have already been visited to avoid revisiting them.

The time complexity is O(n + m), and the space complexity is O(n + m). Here, n and m are the number of nodes and edges, respectively.

PythonJavaC++GoTypeScriptRust
class Solution: def validPath( self, n: int, edges: List[List[int]], source: int, destination: int ) -> bool: def dfs(i: int) -> bool: if i == destination: return True vis.add(i) for j in g[i]: if j not in vis and dfs(j): return True return False g = [[] for _ in range(n)] for u, v in edges: g[u].append(v) g[v].append(u) vis = set() return dfs(source)(code-box)

Solution 2: BFS

We can also use BFS to determine whether there is a path from source to destination.

Specifically, we define a queue q, initially adding source to the queue. Additionally, we use a set vis to record the vertices that have already been visited to avoid revisiting them.

Next, we continuously take vertices i from the queue. If i = destination, it means there is a path from source to destination, and we return true. Otherwise, we traverse all adjacent vertices j of i. If j has not been visited, we add j to the queue q and mark j as visited.

Finally, if the queue is empty, it means there is no path from source to destination, and we return false.

The time complexity is O(n + m), and the space complexity is O(n + m). Here, n and m are the number of nodes and edges, respectively.

PythonJavaC++GoTypeScriptRust
class Solution: def validPath( self, n: int, edges: List[List[int]], source: int, destination: int ) -> bool: g = [[] for _ in range(n)] for u, v in edges: g[u].append(v) g[v].append(u) q = deque([source]) vis = {source} while q: i = q.popleft() if i == destination: return True for j in g[i]: if j not in vis: vis.add(j) q.append(j) return False(code-box)

Solution 3: Union-Find

Union-Find is a tree-like data structure that, as the name suggests, is used to handle some disjoint set merge and query problems. It supports two operations:

  1. Find: Determine which subset an element belongs to. The time complexity of a single operation is O(α(n)).
  2. Union: Merge two subsets into one set. The time complexity of a single operation is O(α(n)).

For this problem, we can use the Union-Find set to merge the edges in edges, and then determine whether source and destination are in the same set.

The time complexity is O(n log n + m) or O(n α(n) + m), and the space complexity is O(n). Where n and m are the number of nodes and edges, respectively.

PythonJavaC++GoTypeScriptRust
class UnionFind: def __init__(self, n): self.p = list(range(n)) self.size = [1] * n def find(self, x): if self.p[x] != x: self.p[x] = self.find(self.p[x]) return self.p[x] def union(self, a, b): pa, pb = self.find(a), self.find(b) if pa == pb: return False if self.size[pa] > self.size[pb]: self.p[pb] = pa self.size[pa] += self.size[pb] else: self.p[pa] = pb self.size[pb] += self.size[pa] return True class Solution: def validPath( self, n: int, edges: List[List[int]], source: int, destination: int ) -> bool: uf = UnionFind(n) for u, v in edges: uf.union(u, v) return uf.find(source) == uf.find(destination)(code-box)

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