<｜begin▁of▁sentence｜>### Instruction:
Certainly, let's reframe this scenario with a tone and relevance suitable for a Network Security Engineer.

Imagine you're analyzing a simplified model of a network security system where resources ('u1', 'u2', 'u3') need to be matched with security protocols ('v1', 'v2', 'v3') to ensure robust protection. The current configuration links each resource to a dedicated protocol forming pairs—('u1', 'v1'), ('u2', 'v2'), ('u3', 'v3')—with additional redundancy in place, where 'u1' is also linked to an alternate protocol 'v2', and 'u2' has a fallback protocol 'v3'.

In this context, we're interested in understanding the system's resilience. Specifically, we would like to determine the maximal extendability of this network representation, which essentially asks: How effectively can our protocols be reallocated while still maintaining a one-to-one correspondence between every resource and a security protocol, assuming there exists an initial perfect matching?

This analysis is crucial for ensuring the security framework is both robust and adaptable to potential threats or failures that might disrupt the current configuration. Could you compute this using NetworkX, taking into account the existing connections within our cybersecurity model?
### Response:
import networkx as nx
from networkx.algorithms.matching import maximal_extendability

# Create a bipartite graph with a perfect matching
B = nx.Graph()
B.add_nodes_from(['u1', 'u2', 'u3'], bipartite=0)
B.add_nodes_from(['v1', 'v2', 'v3'], bipartite=1)
B.add_edges_from([('u1', 'v1'), ('u2', 'v2'), ('u3', 'v3'), ('u1', 'v2'), ('u2', 'v3')])

# Compute the maximal extendability
extendability = maximal_extendability(B)

print('The maximal extendability of the graph is:', extendability)
<|EOT|>
