<｜begin▁of▁sentence｜>### Instruction:
Welcome to Graph Theory Associates! Oh, I see that you're inquiring about a very specific task involving our graph management software, how fascinating! You want to understand how to merge two distinct networks in a unique manner—by computing the lexicographic product, right?

Let me put that in context for you. Imagine you're handling the network system for a large conference center. Within this center, we have two separate networks: Network G, which represents the main conference hall connections, and Network H, for the breakout session rooms. Now, Network G is quite simple, with just one connection between Room 1 and Room 2, and this connection has a significance score, sort of like a weight, which is 4. Meanwhile, Network H connects two discussion spaces, 'a' and 'b', and this link has a higher score of 7.

You're looking to create a new comprehensive network that combines these two in a systematic way that captures all possible connections, considering their respective weights. To visualize this combined network, you’re considering using the power of our graph software and want to see the result, am I correct? The data you provided will be seamlessly integrated into the program, and the lexicographic product you’re after will be a new network with its own set of rooms and connections based on the rules you've described. 

This will give you a richer understanding of how these spaces can interact during the event, magnifying the possibilities for planning and optimization! Now, I won't be able to generate this for you right here at the reception desk, but I can certainly direct you to our graph technology specialists who can take it from here. Shall I do that for you?
### Response:
import networkx as nx

# Create two graphs, G and H
G = nx.Graph()
H = nx.Graph()

# Add nodes and edges to G
G.add_edge(1, 2, weight=4)

# Add nodes and edges to H
H.add_edge('a', 'b', weight=7)

# Compute the lexicographic product P of G and H
P = nx.lexicographic_product(G, H)

# Print the nodes and edges of the product graph
print('Nodes of P:', list(P.nodes))
print('Edges of P:', list(P.edges))
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