diff --git a/graphs/johnson_graph.py b/graphs/johnson_graph.py
index af9ed6c76..6328cd3f4 100644
--- a/graphs/johnson_graph.py
+++ b/graphs/johnson_graph.py
@@ -8,19 +8,19 @@ import sys
 class JohnsonGraph:
     def __init__(self) -> None:
         self.edges: list[str] = []
-        self.graph: dict[str, int] = {}
+        self.graph: dict[str, list] = {}
 
     # add vertices for a graph
-    def add_vertices(self, u) -> None:
+    def add_vertices(self, u:int) -> None:
         self.graph[u] = []
 
     # assign weights for each edges formed of the directed graph
-    def add_edge(self, u, v, w) -> None:
+    def add_edge(self, u:str, v:str, w:int) -> None:
         self.edges.append((u, v, w))
         self.graph[u].append((v, w))
 
     # perform a dijkstra algorithm on a directed graph
-    def dijkstra(self, s) -> dict:
+    def dijkstra(self, s:str) -> dict:
         distances = {vertex: sys.maxsize - 1 for vertex in self.graph}
         pq = [(0, s)]
         distances[s] = 0
@@ -37,7 +37,7 @@ class JohnsonGraph:
         return distances
 
     # carry out the bellman ford algorithm for a node and estimate its distance vector
-    def bellman_ford(self, s) -> dict:
+    def bellman_ford(self, s:str) -> dict:
         distances = {vertex: sys.maxsize - 1 for vertex in self.graph}
         distances[s] = 0
 
@@ -51,7 +51,7 @@ class JohnsonGraph:
     # perform the johnson algorithm to handle the negative weights that
     # could not be handled by either the dijkstra
     # or the bellman ford algorithm efficiently
-    def johnson_algo(self) -> dict:
+    def johnson_algo(self) -> list[dict]:
         self.add_vertices("#")
         for v in self.graph:
             if v != "#":