<｜begin▁of▁sentence｜>### Instruction:
In the dynamic realm of data analytics, where the interconnectedness of digital systems can be represented by intricate web-like structures, I'm following an intriguing story about a highly specialized algorithm developed for a unique class of networks. This algorithm, which is akin to a digital detective that dissects the directional flows of information, is specifically tailored to dissect directed graphs—those which traffic in one-way streets of data.

However, intrigue arises when this meticulous mechanism must avoid entangling itself in a more complex subset of these networks—those known as multigraphs, which feature multiple data lanes intersecting at single points, creating a chaotic crisscross of information pathways.

As a diligent reporter delving into the narrative of this algorithm, I'm seeking to unravel how the algorithm's creators ensure it stays its course, meticulously analyzing only the directed graphs it's been designed to decode, and steering clear of the convoluted multigraphs. A practical scenario of this could involve a dataset from a "traffic_flow_analysis.gml" file representing the one-way streets and intersections of an urban traffic network, and the importance of applying this algorithm solely to the directed, non-multilayered routes.

The question at the heart of this investigation, then, is how do the algorithm's architects program it to distinguish between these types and execute its function exclusively on the directed graphs, thereby maintaining the integrity of their sophisticated digital detective?
### Response:
import networkx as nx

@nx.utils.not_implemented_for('multigraph')
def example_function(G):
    # This function is not allowed for multigraphs
    if not G.is_directed():
        raise nx.NetworkXError('This function is only for directed graphs')
    return 'Function can be executed'

# Create a directed graph
DG = nx.DiGraph()
DG.add_edges_from([(1, 2), (2, 3)])

# Try executing the function on a directed graph
try:
    result = example_function(DG)
    print(result)
except nx.NetworkXNotImplemented as e:
    print(e)

# Create a multigraph
MG = nx.MultiDiGraph()
MG.add_edges_from([(1, 2, {'weight': 1}), (1, 2, {'weight': 2}), (2, 3)])

# Try executing the function on a multigraph
try:
    result = example_function(MG)
    print(result)
except nx.NetworkXNotImplemented as e:
    print(e)
<|EOT|>
