day_50

98. 所有可达路径

def dfs(graph, x, n, path, res):
    if x == n:
        res.append(path.copy())
        return
    for i in range(1, n + 1):
        if graph[x][i] == 1:
            path.append(i)
            dfs(graph, i, n, path, res)
            path.pop()

def main():
    n, m = map(int, input().split())
    graph = [[0] * (n + 1) for _ in range(n + 1)]
    for _ in range(m):
        s, t = map(int, input().split())
        graph[s][t] = 1 
        
    res = []
    dfs(graph, 1, n, [1], res)
    
    if not res:
        print(-1)
    else:
        for path in res:
            print(' '.join(map(str, path)))

if __name__ == '__main__':
    main()

邻接表方式

from collections import defaultdict

def dfs(graph, x, n, path, res):
    if x == n:
        res.append(path.copy())
        return
    for i in graph[x]:
        path.append(i)
        dfs(graph, i, n, path, res)
        path.pop()

def main():
    n, m = map(int, input().split())
    
    graph =defaultdict(list)
    for _ in range(m):
        s, t = map(int, input().split())
        graph[s].append(t)
    
    res = []
    dfs(graph, 1, n, [1], res)
    
    if not res:
        print(-1)
    else:
        for path in res:
            print(' '.join(map(str, path)))
    
if __name__ == '__main__':
    main()

就一深搜，虽然我不能自己写出来，但是这个不难。

邻接表和邻接矩阵都只是存储图的一种方式，在存储和遍历的时候有所不同，解题思路都是一样的。