Random Graph Properties Extraction

This function accepts a NetworkX graph object and returns a dictionary containing randomly selected node, edge, node degree, number of connected components, average path length, and degree distribution.

Technology Stack : NetworkX

Code Type : Function

Code Difficulty : Intermediate

                
                    
import networkx as nx
import random

def random_graph_properties(G):
    """
    Generate random properties for a given graph G using NetworkX.

    :param G: A networkx.Graph object.
    :return: A dictionary with random graph properties.
    """
    # Randomly choose a node from the graph
    node = random.choice(list(G.nodes()))
    
    # Randomly choose an edge from the graph
    edge = random.choice(list(G.edges()))
    
    # Calculate the degree of the chosen node
    degree = G.degree(node)
    
    # Calculate the number of connected components
    connected_components = len(list(nx.connected_components(G)))
    
    # Calculate the average path length of the graph
    average_path_length = nx.average_shortest_path_length(G)
    
    # Randomly choose a node's degree distribution
    degree_distribution = nx.degree_distribution(G)
    
    # Generate the result dictionary
    result = {
        "node": node,
        "edge": edge,
        "degree": degree,
        "connected_components": connected_components,
        "average_path_length": average_path_length,
        "degree_distribution": degree_distribution
    }
    
    return result

# Example usage:
# G = nx.erdos_renyi_graph(10, 0.5)
# properties = random_graph_properties(G)
# print(properties)