<｜begin▁of▁sentence｜>### Instruction:
As a Smart Home Designer, I often find myself in the world of complex systems and intricate network designs. Just last week, I had a client who wanted an automated system that could optimally connect all his smart devices while maintaining a minimalist design. Picture the task at hand like an elaborate network of devices, where each device represents a node in a graph, and the connections between them are the edges. My goal is to create a manageable sample of this network to prototype, without overwhelming the simplicity of the design or missing out on the functionality.

Imagine I've mapped out the entire network of the client's smart home devices, and it's as intricate as a piece of modern art. Now, I need to extract just a portion of it Ã¢ÂÂ a subgraph Ã¢ÂÂ to focus on. In tech speak, we could liken this to needing to sample a subgraph with 10 nodes from a larger graph that's been read from a 'littleballoffur7.sparse6' file, using something like the BreadthFirstSearchSampler in a graph processing toolkit.

In practical terms, think of it as if I'm selecting a representative set of devices out of all the smart devices connected in the home, to demonstrate a streamlined connectivity path. This subset is vital to avoid clutter and focus on the most efficient communication between devices. So, the question at hand: How can one take advantage from the BreadthFirstSearchSampler to create such a focused, 10-node subgraph for the prototype? Just to clarify, if it were a gml file instead, we'd be asking for the specific file name in our query.
### Response:
import networkx as nx
from littleballoffur import BreadthFirstSearchSampler
G = nx.read_sparse6('littleballoffur7.sparse6')
sampler = BreadthFirstSearchSampler(number_of_nodes=10)
sampler_G = sampler.sample(G)
print(sampler_G.edges(), sampler_G.nodes())
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