# LeetCode 797. All Paths From Source to Target

## Description

https://leetcode.com/problems/all-paths-from-source-to-target/

Given a directed acyclic graph (DAG) of `n` nodes labeled from 0 to n – 1, find all possible paths from node `0` to node `n - 1`, and return them in any order.

The graph is given as follows: `graph[i]` is a list of all nodes you can visit from node `i` (i.e., there is a directed edge from node `i` to node `graph[i][j]`).

Example 1:

```Input: graph = [[1,2],,,[]]
Output: [[0,1,3],[0,2,3]]
Explanation: There are two paths: 0 -> 1 -> 3 and 0 -> 2 -> 3.
```

Example 2:

```Input: graph = [[4,3,1],[3,2,4],,,[]]
Output: [[0,4],[0,3,4],[0,1,3,4],[0,1,2,3,4],[0,1,4]]
```

Example 3:

```Input: graph = [,[]]
Output: [[0,1]]
```

Example 4:

```Input: graph = [[1,2,3],,,[]]
Output: [[0,1,2,3],[0,2,3],[0,3]]
```

Example 5:

```Input: graph = [[1,3],,,[]]
Output: [[0,1,2,3],[0,3]]
```

Constraints:

• `n == graph.length`
• `2 <= n <= 15`
• `0 <= graph[i][j] < n`
• `graph[i][j] != i` (i.e., there will be no self-loops).
• The input graph is guaranteed to be a DAG.

## Explanation

Build an adjacency list representing the relationship between nodes and edges. Then conduct a depth-first search to find all the paths from source to target.

## Python Solution

``````class Solution:
def allPathsSourceTarget(self, graph: List[List[int]]) -> List[List[int]]:

results = []

for i in graph:

for i in range(len(graph)):
edges = graph[i]

for edge in edges:

return results

def helper(self, results, adjacency_list, current, target, path):
if current == target:
results.append(list(path))
return