<｜begin▁of▁sentence｜>### Instruction:
Imagine we're examining the stability and interconnectedness of political coalitions within a theoretical framework that mirrors the structure of the Petersen graph, an exemplar of robust tripartite agreement. This graph is acknowledged for its resiliency due to triconnectivity—a measure of non-breakability even after the removal of two nodes or parties. Within this political model, how might we investigate the coalition substructure, identifying those groups of nodes—similar to political factions or cliques—that remain tightly interconnected at various levels of k-connectivity, ensuring the alliance's overall coherence? This analysis would be like uncovering the core alliances that sustain the coalition's integrity under stress. Could we delineate these subgroups to understand the coalition's depth and resistance to political fracturing?
### Response:
import networkx as nx

# Petersen graph has 10 nodes and it is triconnected, thus all
# nodes are in a single component on all three connectivity levels
G = nx.petersen_graph()
k_components = nx.k_components(G)

print(k_components)
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