<｜begin▁of▁sentence｜>### Instruction:
Given a graph with 5 vertices and the following edges: [(0, 1), (1, 2), (2, 3), (3, 4)], can you use the as_clustering method from the VertexDendrogram class in igraph to find the optimal clustering of the vertices? Note: Also print the summary of the dendrogram.
### Response:
from igraph import Graph

# Create a simple graph with 5 vertices and 4 edges
edges = [(0, 1), (1, 2), (2, 3), (3, 4)]
g = Graph(edges=edges)

# Run a community detection algorithm to get the dendrogram
vdendrogram = g.community_fastgreedy().as_clustering()

# Now we can use methods of VertexDendrogram like .as_clustering()
clusters = vdendrogram.as_clustering()

# Print a summary of the resulting clustering
count = vdendrogram.optimal_count
print(f'Optimal cluster count: {count}')
print(clusters)

# Get a summary of the dendrogram itself
print(vdendrogram.summary())
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