diff --git a/algorithms/Python/README.md b/algorithms/Python/README.md
index 3d4a1271..2fe7de1a 100644
--- a/algorithms/Python/README.md
+++ b/algorithms/Python/README.md
@@ -35,6 +35,7 @@
 - [Linear Search](searching/linear_search.py)
 - [Ternary Search](searching/ternary_search.py)
 - [Interpolation Search](searching/interpolation_search.py)
+- [Uniform Cost Search](searching/uniform_cost_search.py)
 
 ## Sorting
 - [Bubble Sort](sorting/bubble_sort.py)
diff --git a/algorithms/Python/searching/uniform_cost_search.py b/algorithms/Python/searching/uniform_cost_search.py
new file mode 100644
index 00000000..02e10365
--- /dev/null
+++ b/algorithms/Python/searching/uniform_cost_search.py
@@ -0,0 +1,44 @@
+# this graph to check the algorithm
+graph={
+  'S':[('A',2),('B',3),('D',5)],
+  'A':[('C',4)],
+  'B':[('D',4)],
+  'C':[('D',1),('G',2)],
+  'D':[('G',5)],
+  'G':[],
+    }
+
+#to calculate the total cost of path
+def path_cost(path):
+    total_cost=0
+    for (node, cost) in path:
+        total_cost+=cost
+    return total_cost , path[-1][0]
+# well sort queue items based on total path
+#if two items have the same total_cost then sort by node name (alphabetically)
+
+# uniform cost search
+def UCS(graph, start, goal):
+    visited=[]
+    queue=[[(start,0)]]
+    while queue:
+        queue.sort(key=path_cost)#sorting by cost
+        path=queue.pop(0)#choosing least cost
+        node=path[-1][0]
+        if node in visited:
+            continue
+        visited.append(node)
+        if node==goal:
+            return path
+        else:
+            adjacent_nodes=graph.get(node,[])
+            for(node2,cost)in adjacent_nodes:
+                new_path=path.copy()
+                new_path.append((node2,cost))
+                queue.append(new_path)
+
+
+solution= UCS(graph,'S','G')
+print('solution is ' , solution)
+print ('cost of solution is ',path_cost(solution)[0])
+