<｜begin▁of▁sentence｜>### Instruction:
In the harmonious world of music therapy, where each connection we foster can be seen as a duet between individuals, imagine you're composing a piece where every interaction comes with a varying degree of resonance, represented by numeric values. However, in your latest symphony of connections—a network of passages among individuals 'A', 'B', 'C', and 'D'—you have musical phrases that carry different strengths, akin to weights: a gentle legato between 'A' and 'B' with a weight of 0.6, a more pronounced motif connecting 'B' and 'C' with a weight of 7, and a discordant section from 'C' to 'D', which has been accidentally marked 'not numeric' instead of having a tangible measure of intensity.

As you strive for a therapeutic session that flows smoothly and predictably like a well-orchestrated piece, you must ensure all interactions are quantifiable. How would you examine, using the is_real_weighted function from graspologic, if every melodic line in this network is indeed composed with real, numerical weights? This check is essential to maintaining the structure and balance in the therapeutic environment much like maintaining harmony in a composition.
### Response:
import networkx as nx
from graspologic.preconditions import is_real_weighted

G = nx.Graph()
G.add_edge('A', 'B', weight=0.6)
G.add_edge('B', 'C', weight=7)
G.add_edge('C', 'D', weight='not numeric') # This will cause the function to return False

# Check if the graph is weighted with all real (numeric) weights
is_real_weighted_graph = is_real_weighted(G, 'weight')
print('Graph has all real weighted edges:', is_real_weighted_graph)
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