Final Answer:
Here is an example code snippet to implement a Breadth-First Search (BFS) of your bucket list destinations, starting from Home (ORD). The function will print the order in which you visit the nodes (airport codes).
python:
from collections import deque
def bfs(bucket_list, start_node):
visited = set()
queue = deque([start_node])
while queue:
node = queue.popleft()
print(node)
if node not in visited:
visited.add(node)
neighbors = bucket_list[node]
for neighbor in neighbors:
if neighbor not in visited:
queue.append(neighbor)
Step-by-step explanation:
The code snippet above demonstrates how to implement a Breadth-First Search (BFS) algorithm to traverse a graph representing your bucket list destinations. The algorithm starts at the Home airport (ORD) and visits each node (airport code) in a breadth-first manner.
The function `bfs` takes two parameters: `bucket_list`, which is a dictionary representing the graph, and `start_node`, which is the starting point for the BFS traversal.
Inside the function, a set called `visited` is used to keep track of the nodes that have been visited. The `queue` is initialized with the start node. The algorithm then enters a while loop that continues until the queue is empty.
During each iteration of the loop, the node at the front of the queue is removed using the `popleft()` method from the `deque` data structure. This node is printed to the console, representing the order in which you visit the destinations.
If the node has not been visited before, it is added to the `visited` set. The neighbors of the current node are obtained from the `bucket_list` dictionary.
For each neighbor, if it has not been visited, it is added to the queue to be visited in the next iterations.
By using this BFS algorithm, you can traverse your bucket list destinations in a systematic manner, ensuring that you visit each destination in the order specified by the BFS traversal.