<｜begin▁of▁sentence｜>### Instruction:
Oh, I see we're in the midst of a bit of a conundrum here. Imagine you're in the laboratory, and you've been given two sets of patient blood sample sequences for testing. These sequences for testing are like the different paths the blood will travel, right? So, here you have sequence one, labeled as edges1, which goes from vial 1 to 2, then 2 to 3, and finally from 3 to 4. Then, sequence two, or edges2 as it's been noted, seems suspiciously similar, traveling from vial 3 to 4, then retracing back to 1 to 2, and again 2 to 3.

Now, as someone who values accuracy and precision in the lab, don't you think we need to figure out if these two sequences are in fact the same, just mixed up a bit in their order? It's imperative for the integrity of our records and testing protocols, wouldn't you agree? If these sample sequences are indeed identical, despite their different order, that's one less discrepancy we need to worry about. But how might we go about confirming this with the tools at our disposal, like a statistical analysis? Could we treat these paths as a network of connected points and analyze them that way? What are your thoughts on this approach?
### Response:
import networkx as nx

# Define two sets of edges
edges1 = [(1, 2), (2, 3), (3, 4)]
edges2 = [(3, 4), (1, 2), (2, 3)]

# use the edges_equal function to check if edges1 and edges2 are equal
are_equal = nx.utils.edges_equal(edges1, edges2)

print('Are the two edge sets equal?', are_equal)
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