Breadth first search

Author: ivanmmarkovic

.idea/Problem-Solving-with-Algorithms-and-Data-Structures-using-Python.iml

@@ -12,7 +12,7 @@ def addVertex(self, label: str):
         self.colors[label] = "white"
         self.previous[label] = None
 
-    def addEdge(self, label1: str, label2: str):
+    def add_edge(self, label1: str, label2: str):
         self.adjacencyList[label1].append(label2)
 
     def dfs(self, label: str):

Ch07. Graphs and Graph Algorithms/cycle-detection/cycle-detection-directed-graph/graph.py

@@ -7,10 +7,9 @@
 for vertex in vertices:
     graph.addVertex(vertex)
 
-
-graph.addEdge("a", "b")
-graph.addEdge("b", "c")
-graph.addEdge("c", "d")
-graph.addEdge("d", "b")
+graph.add_edge("a", "b")
+graph.add_edge("b", "c")
+graph.add_edge("c", "d")
+graph.add_edge("d", "b")
 
 graph.dfs("a")

Ch07. Graphs and Graph Algorithms/cycle-detection/cycle-detection-directed-graph/main.py

@@ -96,6 +96,7 @@ but it also contains other data structures, algorithms and problems.
 - [Quicksort - return new array](https://github.com/ivanmmarkovic/Problem-Solving-with-Algorithms-and-Data-Structures-using-Python/blob/master/sorting/quicksort-return-new-array.py)
 
 ### [Graphs](https://github.com/ivanmmarkovic/Problem-Solving-with-Algorithms-and-Data-Structures-using-Python/tree/master/graphs)
+- [Breadth first search]()
 - [Dijkstra algorithm - Shortest path](https://github.com/ivanmmarkovic/Problem-Solving-with-Algorithms-and-Data-Structures-using-Python/tree/master/graphs/dijkstra)
     - [Priority Queue implementation](https://github.com/ivanmmarkovic/Problem-Solving-with-Algorithms-and-Data-Structures-using-Python/tree/master/graphs/dijkstra/priority-queue-impl-adjacency-map)
     - [Matrix implementation](https://github.com/ivanmmarkovic/Problem-Solving-with-Algorithms-and-Data-Structures-using-Python/tree/master/graphs/dijkstra/matrix-impl)

README.md

@@ -0,0 +1,41 @@
+from queue import Queue
+
+
+class Graph:
+    def __init__(self):
+        self.vertices: list = []
+        self.adjacency_list: dict = {}
+        self.prev: dict = {}
+        self.distance: dict = {}
+        self.colors: dict = {}
+
+    def add_vertex(self, label: str):
+        self.vertices.append(label)
+        self.adjacency_list[label]: list = []
+        self.prev[label] = None
+        self.distance[label] = 0
+        self.colors[label] = "white"
+
+    def add_edge(self, label1: str, label2: str):
+        self.adjacency_list[label1].append(label2)
+        self.adjacency_list[label2].append(label1)
+
+    def bfs(self, label: str):
+        q: Queue = Queue()
+        q.enqueue(label)
+        self.colors[label] = "gray"
+        while not q.is_empty():
+            tmp: str = q.dequeue()
+            for neighbour in self.adjacency_list[tmp]:
+                if self.colors[neighbour] == "white":
+                    self.prev[neighbour] = tmp
+                    self.distance[neighbour] = self.distance[tmp] + 1
+                    self.colors[neighbour] = "gray"
+                    q.enqueue(neighbour)
+            self.colors[tmp] = "black"
+
+    def return_path(self, label: str) -> str:
+        if self.prev[label] is None:
+            return label
+        else:
+            return self.return_path(self.prev[label]) + " -> " + label

graphs/breadth-first-search/__pycache__/graph.cpython-39.pyc

@@ -0,0 +1,22 @@
+from graph import Graph
+
+graph = Graph()
+
+my_vertices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I']
+# add vertices
+for i in range(len(my_vertices)):
+    graph.add_vertex(my_vertices[i])
+
+graph.add_edge('A', 'B')
+graph.add_edge('A', 'C')
+graph.add_edge('A', 'D')
+graph.add_edge('C', 'D')
+graph.add_edge('C', 'G')
+graph.add_edge('D', 'G')
+graph.add_edge('D', 'H')
+graph.add_edge('B', 'E')
+graph.add_edge('B', 'F')
+graph.add_edge('E', 'I')
+
+graph.bfs("A")
+print(graph.return_path("H"))

graphs/breadth-first-search/__pycache__/queue.cpython-39.pyc

@@ -0,0 +1,15 @@
+class Queue:
+    def __init__(self):
+        self.queue = []
+
+    def enqueue(self, item):
+        self.queue.insert(0, item)
+
+    def dequeue(self):
+        return self.queue.pop()
+
+    def size(self):
+        return len(self.queue)
+
+    def is_empty(self):
+        return self.queue == []