<｜begin▁of▁sentence｜>### Instruction:
As a technology consultant specializing in graph analysis, I can help with that. Imagine you're analyzing the flow of information within a large network of interconnected devices in a smart city. You have collected data on the network's edges, representing the connections between devices. By using the `igraph` library, you can leverage the `Cover` class to obtain a community edge betweenness cover of the network. Now, you need to use the `__len__` method of the `Cover` class to determine the number of clusters in the cover. This will allow you to gain insights into how the network is organized and identify potential areas of interest for further analysis.
### Response:
import igraph as ig

# Create a graph
edges = [(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 0)]
g = ig.Graph(edges=edges)

# Perform community detection to get a cover
cover = g.community_edge_betweenness().as_cover()

# Get the number of clusters in the cover
num_clusters = len(cover)

# Print the number of clusters
print('Number of clusters in the cover:', num_clusters)
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