<｜begin▁of▁sentence｜>### Instruction:
Envision yourself preparing for a beautifully choreographed dance, where you and your fellow dancers represent nodes in a network, each of you interconnected by potential dance sequences depicted as edges between you. Now, the sequence in which you all move is vital, as it should be efficient, flowing gracefully from one move to the next. Just like in a dance, where you would find the most graceful path from one position to another, imagine this network of dance moves with connections having different complexities, symbolized as weights.

In our dance ensemble, there is a specific set of dance sequences: between Dancer 1 and Dancer 2, Dancer 1 and Dancer 3, Dancer 2 and Dancer 3, Dancer 3 and Dancer 4, and finally between Dancer 4 and Dancer 5. These sequences are fluid, with each transition having the same level of complexity, or 'weight,' in our performance.

Your challenge, akin to orchestrating a dance to perfection, is to determine the most efficient sequence of movements, ensuring the overall dance routine connects each pair of dancers with the smoothest transition – the shortest 'weighted path' in our analogy. You'd aim to transform this into a complete dance where every dancer is connected with the most graceful move, creating a seamless performance.

This is analogous to finding the metric closure of a network in the realm of a dance performance, translating the original set of connections into a network where every dancer has a direct sequence to every other, each 'weight' illustrating the shortest dance from one to another. How would you re-choreograph this dance to achieve such a harmonious flow?
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edges_from([(1, 2, {'weight': 1}), (1, 3, {'weight': 1}), (2, 3, {'weight': 1}), (3, 4, {'weight': 1}), (4, 5, {'weight': 1})])

# Compute the metric closure
mc = nx.metric_closure(G)

# Print edges with weights from the metric closure
for u, v, weight in mc.edges(data='weight'):
    print(f"({u}, {v}, {weight})")
<|EOT|>
