Build a Graph Data Structure for Relationships

class Graph:
    def __init__(self):
        self.graph = {}

    def add_node(self, node):
        if node not in self.graph:
            self.graph[node] = set() # Use a set for efficient edge storage (no duplicates)

    def add_edge(self, node1, node2, directed=False):
        self.add_node(node1)
        self.add_node(node2)
        self.graph[node1].add(node2)
        if not directed:
            self.graph[node2].add(node1) # For undirected graphs

    def get_neighbors(self, node):
        return list(self.graph.get(node, []))

    def has_node(self, node):
        return node in self.graph

    def has_edge(self, node1, node2):
        return node2 in self.graph.get(node1, set())

    def __str__(self):
        nodes = sorted(list(self.graph.keys()))
        output = "Graph:
"
        for node in nodes:
            neighbors = sorted(list(self.graph[node]))
            output += f"  {node}: {', '.join(map(str, neighbors))}
"
        return output

# Example Usage: Social Network
social_graph = Graph()
social_graph.add_edge("Alice", "Bob")
social_graph.add_edge("Bob", "Charlie")
social_graph.add_edge("Alice", "David")
social_graph.add_edge("Charlie", "Eve")
social_graph.add_edge("David", "Eve")

print(social_graph)
# Output:
# Graph:
#   Alice: Bob, David
#   Bob: Alice, Charlie
#   Charlie: Bob, Eve
#   David: Alice, Eve
#   Eve: Charlie, David

print(f"Bob's friends: {social_graph.get_neighbors('Bob')}")
# Output: Bob's friends: ['Alice', 'Charlie']

print(f"Does Alice know Eve? {social_graph.has_edge('Alice', 'Eve')}")
# Output: Does Alice know Eve? False