Update queue implementation (#5388)

* Update queue implementation

Popping the first element of a list takes O(n) time.
Using a cyclic queue takes O(1) time.

* Add queue changes from extra files

* Update indentation

* Add empty line between imports

* Fix lines

* Apply suggestions from code review

Co-authored-by: John Law <[email protected]>

Co-authored-by: John Law <[email protected]>

Author: Crowton

graphs/breadth_first_search.py

@@ -3,6 +3,8 @@
 """ Author: OMKAR PATHAK """
 from __future__ import annotations
 
+from queue import Queue
+
 
 class Graph:
     def __init__(self) -> None:
@@ -51,19 +53,19 @@ def bfs(self, start_vertex: int) -> set[int]:
         visited = set()
 
         # create a first in first out queue to store all the vertices for BFS
-        queue = []
+        queue = Queue()
 
         # mark the source node as visited and enqueue it
         visited.add(start_vertex)
-        queue.append(start_vertex)
+        queue.put(start_vertex)
 
-        while queue:
-            vertex = queue.pop(0)
+        while not queue.empty():
+            vertex = queue.get()
 
             # loop through all adjacent vertex and enqueue it if not yet visited
             for adjacent_vertex in self.vertices[vertex]:
                 if adjacent_vertex not in visited:
-                    queue.append(adjacent_vertex)
+                    queue.put(adjacent_vertex)
                     visited.add(adjacent_vertex)
         return visited
 

graphs/breadth_first_search_2.py

@@ -14,6 +14,8 @@
 """
 from __future__ import annotations
 
+from queue import Queue
+
 G = {
     "A": ["B", "C"],
     "B": ["A", "D", "E"],
@@ -30,13 +32,14 @@ def breadth_first_search(graph: dict, start: str) -> set[str]:
     'ABCDEF'
     """
     explored = {start}
-    queue = [start]
-    while queue:
-        v = queue.pop(0)  # queue.popleft()
+    queue = Queue()
+    queue.put(start)
+    while not queue.empty():
+        v = queue.get()
         for w in graph[v]:
             if w not in explored:
                 explored.add(w)
-                queue.append(w)
+                queue.put(w)
     return explored
 
 

graphs/check_bipartite_graph_bfs.py

@@ -6,14 +6,17 @@
 # from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
 # or u belongs to V and v to U. We can also say that there is no edge that connects
 # vertices of same set.
+from queue import Queue
+
+
 def checkBipartite(graph):
-    queue = []
+    queue = Queue()
     visited = [False] * len(graph)
     color = [-1] * len(graph)
 
     def bfs():
-        while queue:
-            u = queue.pop(0)
+        while not queue.empty():
+            u = queue.get()
             visited[u] = True
 
             for neighbour in graph[u]:
@@ -23,7 +26,7 @@ def bfs():
 
                 if color[neighbour] == -1:
                     color[neighbour] = 1 - color[u]
-                    queue.append(neighbour)
+                    queue.put(neighbour)
 
                 elif color[neighbour] == color[u]:
                     return False
@@ -32,7 +35,7 @@ def bfs():
 
     for i in range(len(graph)):
         if not visited[i]:
-            queue.append(i)
+            queue.put(i)
             color[i] = 0
             if bfs() is False:
                 return False