<｜begin▁of▁sentence｜>### Instruction:
Imagine you're at the DJ booth, spinning tracks and setting up the perfect mix for the crowd. You’ve got a playlist that’s like a network of songs, where certain sets of tunes—let's call them trios—blend seamlessly into one another just like a trio of friends dancing to the beat. Now, let’s say you want your set list to have a special flow, where each song transitions into at least one other song in a way that each song pair is part of two other perfect trios.

That's like having a music graph, where the nodes are songs and the edges are flawless transitions, and you want to find the biggest possible playlist (subgraph) where each transition (edge) is shared by at least one other trio (k-2 triangles with k equal to 3 here). What tracks would you include to keep the night grooving without breaking the flow?
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()

# Add edges
G.add_edges_from([
    (1, 2), (1, 3), (1, 4),
    (2, 3), (2, 4),
    (3, 4), (4, 5)
])

# Find the k-truss
k = 3
H = nx.k_truss(G, k)

# Print nodes and edges of the k-truss
print('Nodes:', H.nodes())
print('Edges:', H.edges())
<|EOT|>
