<｜begin▁of▁sentence｜>### Instruction:
Scenario: As an automotive engineer, you're accustomed to designing and ensuring the reliability of complex systems, such as those found in vehicles. Now, consider the intricate web of roads and traffic flow within a city as a network where intersections serve as nodes and streets as edges. Just as each component of a vehicle must work smoothly for a successful journey, each path in this network must be traversable in a way that allows one to travel each road exactly once without lifting their foot from the accelerator – a so-called "Eulerian" tour, named after the legendary mathematician Euler.

You've been presented with the blueprints of two conceptual city designs. The first one, resembling a harmonious and fully connected community (akin to a 'complete graph' with 5 intersections), while the second one is more unconventional and resembles the 'Petersen graph', known for its non-intuitive pathways.

Employing NetworkX, a powerful tool much like the diagnostic software we use in perfecting vehicle systems, could you analyze these city road networks to verify if a vehicle can take a seamless tour through each intersection exactly once without retraveling any street? This assessment will be crucial in understanding the practicality of these designs before any real-world implementation takes place.
### Response:
import networkx as nx

def check_eulerian(G):
    return nx.is_eulerian(G)

# Example usage:
# Create a complete graph with 5 nodes
G = nx.complete_graph(5)
print(check_eulerian(G))  # Output: True

# Create a graph that is not Eulerian
H = nx.petersen_graph()
print(check_eulerian(H))  # Output: False
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