<｜begin▁of▁sentence｜>### Instruction:
As a real estate agent facilitating the buying, selling, or renting of properties on behalf of clients, imagine you have access to a detailed blueprint of a community's layout – 'community_graph.gml'. Now, to effectively evaluate the cohesive structure and interconnectedness within the community, could you leverage networkx tools, maintaining each property's community assignment based on its location and attributes? Aim to calculate the modularity score of the community graph, considering that each property is assigned to a specific community corresponding to its distance from a central hub.
### Response:
import igraph as ig

# Read a graph from file
g = ig.read('community_graph.gml')

# Assume that we have precomputed a community structure
# For simplicity, we assign each node to a community equal to its id modulo 3
membership = [v.index % 3 for v in g.vs]

# Calculate the modularity
modularity_score = g.modularity(membership)

# Print the modularity score
print(modularity_score)
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