<｜begin▁of▁sentence｜>### Instruction:
As a Reiki practitioner, I can understand the importance of balance and structure in our daily lives. Imagine that you are leading a wellness retreat, and you have a group of attendees who are interested in exploring their connections and forming supportive communities. You decide to represent their relationships and connections through a network graph, with each individual being a node and the connections between them being the edges.

Now, you wish to understand the patterns of connection within the group, and you've defined a clustering (community structure) system to categorize them into three distinct clusters. You want to calculate and display the size of each cluster, allowing you to gain insights into the distribution of these supportive communities within the group.

In this scenario, you are looking for a method or tool, similar to the "sizes" function in the VertexClustering of the igraph API, to help you obtain and display the size of each cluster formed within the network graph of your wellness retreat attendees.
### Response:
import igraph as ig

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

# Define a clustering (community structure)
# Let's say we found three clusters: {0,1}, {2,3}, and {4,5}
membership = [0, 0, 1, 1, 2, 2]

# Create a VertexClustering object
clustering = ig.VertexClustering(g, membership)

# Get sizes of the clusters
cluster_sizes = clustering.sizes()

# Print the cluster sizes
print(cluster_sizes)
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