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Best First Search

def bfs(graph, start_node):
    queue = [start_node]  # Use a list as a queue
    visited = []  # Keep track of visited nodes

    while queue:
        current_node = queue.pop(0)  # Remove the first node from the queue
        if current_node not in visited:
            visited.append(current_node)  # Mark the node as visited
            queue.extend(graph[current_node])  # Add neighbors to the queue
    print("BFS Traversal:", visited)
# Example graph
graph = {
    'P': ['Q', 'R'],
    'Q': ['S', 'T'],
    'R': ['U', 'V'],
    'S': [],
    'T': [],
    'U': [],
    'V': []
}
# Start BFS from node 'A'
bfs(graph, 'P')



Depth First Search

def dfs(graph, start_node, visited=None):
    if visited is None:
        visited = []  # Initialize the visited list for the first call
    visited.append(start_node)  # Mark the current node as visited
    print(start_node, end=" ")  # Print the visited node
    # Recursively visit all unvisited neighbors
    for neighbor in graph[start_node]:
        if neighbor not in visited:
            dfs(graph, neighbor, visited)

# Example graph
graph = {
    'P': ['Q', 'R'],
    'Q': ['S', 'T'],
    'R': ['U', 'V'],
    'S': [],
    'T': [],
    'U': [],
    'V': []
}
# Start DFS from node 'P'
print("DFS Traversal:")
dfs(graph, 'P')