Fixed

sorts/topological_sort.py

@@ -1,22 +1,52 @@
+"""Topological Sort on Directed Acyclic Graph(DAG)"""
+
+#     a
+#    / \
+#   b   c
+#  / \
+# d   e
+
 edges: dict[str, list[str]] = {
     "a": ["c", "b"],
     "b": ["d", "e"],
     "c": [],
     "d": [],
     "e": [],
 }
+
 vertices: list[str] = ["a", "b", "c", "d", "e"]
 
+"""Perform topological sort on a directed acyclic graph(DAG) starting from the specified node"""
 def topological_sort(start: str, visited: list[str], sort: list[str]) -> list[str]:
-    visited.append(start)
     current = start
-    for neighbor in edges[start]:
+    # Mark the current node as visited
+    visited.append(current)
+    # List of all neighbours of current node
+    neighbors = edges[current]
+
+    # Traverse all neighbours of the current node
+    for neighbor in neighbors:
+        # Recursively visit each unvisited neighbour
         if neighbor not in visited:
-            topological_sort(neighbor, visited, sort)
+            sort = topological_sort(neighbor, visited, sort)
+
+    # After visiting all neigbours, add the current node to the sorted list
     sort.append(current)
+
+    # If there are some nodes that were not visited (disconnected components)
+    if len(visited) != len(vertices):
+        for vertice in vertices:
+            if vertice not in visited:
+                sort = topological_sort(vertice, visited, sort)
+
+    # Return sorted list
     return sort
 
 if __name__ == "__main__":
+    # Topological Sorting from node "a" (Returns the order in bottom up approach)
     sort = topological_sort("a", [], [])
-    sort.reverse() #Top down approach
+
+    # Reversing the list to get the correct topological order (Top down approach)
+    sort.reverse()  
+
     print(sort)