<｜begin▁of▁sentence｜>### Instruction:
Imagine we're working with an organization that's looking to optimize their network structure, drawing inspiration from naturally occurring geometries. Specifically, we're examining an icosahedral-form network topology to understand its resilience and information flow capabilities. This topology consists of 12 interconnected nodes, resembling vertices, and 20 links, mirroring the edges of a Platonic icosahedron.

I'd like us to focus our analysis on the robustness of communication between two particular nodes within this network – node 0 and node 6. As an innovation consultant, my question to you is: How might we assess the resilience of the pathways between these two nodes? Could we, for instance, calculate the local edge connectivity in our model to evaluate the minimum number of links that would need to be removed to sever the communication line between these nodes, using NetworkX for the computations?

This assessment could provide valuable insight into the network's capability to maintain connectivity despite potential disruptions, thus informing our innovation strategy for network designs that emulate such robust structures.
### Response:
from networkx.algorithms.connectivity import local_edge_connectivity
import networkx as nx

# Create an undirected graph with 5 nodes
G = nx.icosahedral_graph()

# Compute local edge connectivity between node 0 and node 6
lec = local_edge_connectivity(G, 0, 6)

print('Local edge connectivity between node 0 and 6:', lec)
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