<｜begin▁of▁sentence｜>### Instruction:
As a glass artist who creates intricate glass pieces, sculptures, or installations using various techniques like glassblowing, kiln-forming, or stained glass methods, imagine you've been commissioned to design a unique glass artwork inspired by a network of interconnected vertices.

You are given a special type of glass canvas with 10 distinct vertices labeled from 'A' to 'J'. Your task involves infusing the network structure of these vertices with 15 interconnections, creating a visually captivating representation of connectivity.

To achieve this, you seek to understand the relational significance of each vertex in the network. In the realm of glass artistry, this translates to determining the "constraint scores" for each vertex, which essentially measure the influence and interdependence of individual vertices within the network.

To assist you in this endeavor, you plan to utilize the innovative Graph.constraint method from the Glass Artistry API, a tool specifically designed for glass artists seeking to imbue their creations with mathematical and conceptual depth. With this method, you aim to calculate Burt's constraint scores for each vertex, guiding your artistic decisions and ensuring that your final glass masterpiece resonates with both aesthetic beauty and mathematical elegance.
### Response:
from igraph import Graph

# Create a sample graph
g = Graph.Erdos_Renyi(n=10, m=15)

# Calculate Burt's constraint scores
g.vs['name'] = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J']
constraint_scores = g.constraint()

# Print Burt's constraint scores for each vertex
for name, score in zip(g.vs['name'], constraint_scores):
    print(f'{name}: {score}')
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