<｜begin▁of▁sentence｜>### Instruction:
Imagine you've got a floorplan of a barbershop where each seat and workstation is marked out, kind of like a map of who can easily chat with who while they're enjoying a trim. This map is tucked away in an old-fashioned file titled 'path_to_file.adjlist', each pairing of seats laid out one by one, much like you'd jot down which friends live next door to each other.

Now, picture you wanted to bring that old-school setup into the digital age, translating the neighbors into a modern system, a network if we want to sound fancy, with every chair number turned into a clean-cut integer for simplicity's sake. So, what I'm looking to do here is to get that whole community of seats from 'path_to_file.adjlist', spruce it up with a digital twist, and then have a gander at who can talk to who – but with all the names turned into numbers, mind you. How would one go about giving that seat-to-seat chit-chat scenario a good trim using NetworkX?
### Response:
import networkx as nx

# Read the adjacency list from a file
G = nx.read_adjlist('path_to_file.adjlist', nodetype=int)

# Display the graph
print(G.edges())
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