## Topological sort use case.

In Computer Sciense a topological sort of a directed graph (Directed Acyclic Graph - DAG) is a linear ordering of its vertices such that for every directed edge uv from vertex u to vertex v, u comes before v in the ordering. The method applicable for graphs that have no directed cycles - directed acyclic graphs. Topological sort is a graph bypassing mode in which each node v is visited only after all its dependencies are visited.

The typical use case of topological sorting is a tasks scheduling based on their relations. The Python code can be implemented in recursive and non-recursive way, below recursive code is presented.

## Topological sorting Algorithm Python code:

```
from collections import defaultdict
#Class for a graph
class Graph:
def __init__(self,vertices):
self.graph = defaultdict(list)
self.V = vertices
# add an edge to graph
def addEdge(self,u,v):
self.graph[u].append(v)
# A recursive function used by Main function
def TopologicalSortUtil(self,v,visited,stack):
visited[v] = True
# adjacent vertices recursion
for i in self.graph[v]:
if visited[i] == False:
self.TopologicalSortUtil(i,visited,stack)
stack.insert(0,v)
# Main function
def TopologicalSort(self):
visited = [False]*self.V
stack =[]
for i in range(self.V):
if visited[i] == False:
self.TopologicalSortUtil(i,visited,stack)
print (stack)
g = Graph(6)
g.addEdge(2,0)
g.addEdge(1,2)
g.addEdge(5,3)
g.addEdge(1,5)
g.addEdge(3,4)
g.addEdge(0,4)
print ("Topological Sort:")
g.TopologicalSort()
```

OUT: Topological Sort:

[1, 5, 3, 2, 0, 4]