Randomly Select Nodes Using NDLib Library and NetworkX

I am trying to randomly select nodes using NDLib and Network X. Instead I am coming up with the same number repeated throughout the list. Is there anyway to adjust this code to randomly choose a number

import networkx as nx
import numpy as np
from networkx.drawing.nx_pydot import graphviz_layout
import ndlib.models.ModelConfig as mc
import ndlib.models.epidemics as ep
import operator
import random

G= nx.erdos_renyi_graph(1000, 0.1)##This might be a bad example

def simulate_threshold(G, importance_measure=None, iterate=50, n=1, threshold=0.25):
    if importance_measure:
        # select seed nodes
        sorted_node = sorted(importance_measure(G).items(), key=operator.itemgetter(1))[::-1]
        
        highest_nodes = [n for n, _ in sorted_node[:n]]
        infected_nodes=highest_nodes
        config = mc.Configuration()
        config.add_model_initial_configuration("Infected", infected_nodes)
    else:
        fraction=float(n)/len(G.nodes)
        fraction = random.uniform(0,fraction)
        config = mc.Configuration()
        config.add_model_parameter('fraction_infected', float(n)/len(G.nodes))
        

    # Model selection
    model = ep.ThresholdModel(G, seed = 42)
   
    
    
    for i in G.nodes:
        config.add_node_configuration("threshold",i,threshold)
    model.set_initial_status(config)

    # Simulation execution
    iterations = model.iteration_bunch(iterate)
    return [it['node_count'][1] for it in iterations]


I=50
N=5
T=0.3
random.seed(42)


node_count_random = simulate_threshold(G, importance_measure=None, iterate=I, n=N, threshold=T)