<｜begin▁of▁sentence｜>### Instruction:
Imagine we are studying an urban road network shaped in a circular pattern, much like a cycle, with 9 interconnected checkpoints. This network can be visualized using a cycle graph where each junction point is considered a node. As a geographer, you would be interested in identifying which streets (edges) act as unique connections between different neighborhoods – these are known in graph theory as local bridges. The span of each local bridge reflects the number of steps it would take to find an alternative route between the neighborhoods should the street (bridge) be temporarily closed. 

Could you, leveraging NetworkX, conduct a survey through the cycle graph of our urban model to locate these local bridges and evaluate the span for each? This comprehensive analysis could provide valuable insights for city planners to understand the vulnerability of certain routes and potentially improve the resilience of our urban transportation network.
### Response:
import networkx as nx

# Create an undirected graph
G = nx.cycle_graph(9)

# Use local_bridges to find edges that are not part of any triangle
# and compute the span of each bridge
for bridge in nx.local_bridges(G, with_span=True):
    print(bridge)
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