<｜begin▁of▁sentence｜>### Instruction:
As a data scientist working for a political research agency, you have been tasked with using the Eva algorithm from the Community Discovery Library (cdlib) to perform attributed community detection on a graph representing relationships between various US political books. Each book is associated with a random political view attribute, which can be categorized as Liberal, Conservative, or Neutral. The graph data is accessible from a GML file named polbooks.gml. Your goal is to generate a JSON representation of the resulting clustering based on the attributed community detection utilizing the cdlib API.
### Response:
import networkx as nx
from cdlib import algorithms
import random

# Creating a sample graph with attributes
G = nx.read_gml('polbooks.gml')

# Assign random attributes to each node
labels = {}
attributes = ['Liberal', 'Conservative', 'Neutral']
for node in G.nodes():
    labels[node] = {'political_view': random.choice(attributes)}

# Apply the Eva algorithm for community detection considering node attributes
communities = algorithms.eva(G, labels, alpha=0.8)

# Generate JSON representation of the clustering
json_repr = communities.to_json()

print(json_repr)
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