<｜begin▁of▁sentence｜>### Instruction:
Alrighty, let's imagine we're out here at the crack of dawn, just like we check on our fish in the ponds, ensuring they're healthy and thriving in the environment we've carefully crafted for 'em. Now, instead of fish, think of data points in a graph. Just like we select the best breeders to ensure a good stock, we want to sample a portion of the data to analyze further.

You see, this task is like when we need to check a sample of the water for quality, but here we've got a digital 'pond' of data. Got this file, 'littleballoffur7.sparse6', it's like a map of how all the data pointsÃ¢ÂÂor in our case, fishÃ¢ÂÂare interconnected. Now, we've got a specific net for the job, called the DiffusionSampler, fancy name, but it's just a tool in our toolbox.

Our goal is simple: we need to cast this net and bring up a sample, but we don't want the whole pond, just a manageable bit to look at, like 10 nodes that are well connected, giving us an idea of the overall health of the system.

So, how do we go about dipping our net in with the DiffusionSampler to pull out a subgraph of 10 nodes from that 'littleballoffur7.sparse6' file? It's gonna help us understand our digital ecosystem just like we do with our aquatic friends.
### Response:
import networkx as nx
from littleballoffur import DiffusionSampler
G = nx.read_sparse6('littleballoffur7.sparse6')
sampler = DiffusionSampler(number_of_nodes=10)
sampler_G = sampler.sample(G)
print(sampler_G.edges(), sampler_G.nodes())
<|EOT|>
