<｜begin▁of▁sentence｜>### Instruction:
Imagine you are a veterinary surgeon and you're faced with a complex network of blood vessels in a patient during surgery. You need to maneuver through these vessels in such a way that you traverse each section of vessels only once before returning to the starting point, ensuring there's no need for a second incision. Think of this network as a map with pathways defined by the flows from one organ to another: from the heart (0) to the lungs (3), from the liver (1) to the kidneys (2), from the kidneys (2) to the lungs (3), and from the lungs (3) back to the heart (0) and liver (1).

You've got this map sketched in the patient's surgery records as data points that resemble the following: {0: [3], 1: [2], 2: [3], 3: [0, 1]}. Based on your medical knowledge and the patterns of circulation, can you determine whether it's possible to perform the surgery with the single incision technique by following this map? Specifically, we need to know if this circulatory map is analogous to what is known in another field as an Eulerian graph, where a closed circuit can be created without retracing any steps. This efficiency would be ideal for the patient, ensuring a quicker surgery and recovery time.
### Response:
import networkx as nx

# Create a directed graph
G = nx.DiGraph({0: [3], 1: [2], 2: [3], 3: [0, 1]})

# Check if the graph is Eulerian
is_eulerian = nx.is_eulerian(G)

# Print the result
print('The directed graph is Eulerian:', is_eulerian)
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