<｜begin▁of▁sentence｜>### Instruction:
Imagine we're in the midst of sketching out a disaster recovery simulation, focusing on how communication networks might be affected by a catastrophic event. We've got our hands on a crucial piece of data, a file named 'path_to_file.edgelist', which details the infrastructure of our communications network. This file is formatted as a weighted edge list, with each connection delineated by commas to indicate not only the link but the capacity or strength of each line, likely representing bandwidth or some other pivotal metric for our planning purposes.

Could you illustrate how we might feed this information into a NetworkX graph to fully visualize the current layout and capacities? Specifically, we're interested in transferring the intricate web of connections along with their associated weights from the 'path_to_file.edgelist' into a digestible graphical format. This will enable us to pinpoint weaknesses in the network and develop a robust strategy for maintaining communications during a disaster recovery operation.
### Response:
import networkx as nx

# Read the weighted edge list from a file
G = nx.read_weighted_edgelist('path_to_file.edgelist', delimiter=',', nodetype=int)

# Display the edges with weights
for u, v, weight in G.edges(data='weight'):
    print(f'({u}, {v}, {weight})')
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