<｜begin▁of▁sentence｜>### Instruction:
As a Sales Associate in a department store, your manager has asked you to use the Louvain community detection algorithm to identify groups of related products within the store's inventory. Once the communities are identified, you are tasked with computing and printing the cut ratio for each community. This cut ratio will indicate the fraction of existing product connections leaving the community, helping the store understand how products are related and how they may be marketed together to increase sales. To complete this task, you will need to use the cdlib library to run the Louvain algorithm and calculate the cut ratio for each community.
### Response:
import networkx as nx
from cdlib import algorithms, evaluation

# Create a graph from the polblogs dataset
G = nx.read_gml('polblogs.gml')

# Perform community detection using the Louvain method
communities = algorithms.louvain(G)

# Compute the cut ratio for the detected communities
cut_ratio = evaluation.cut_ratio(G, communities)

# Print the overall cut ratio of the graph partitioning
print(cut_ratio.score)
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