<｜begin▁of▁sentence｜>### Instruction:
Ah, imagine we're in the midst of a therapeutic dance session, where each movement represents a connection, a unique bond that tells us a storyÃ¢ÂÂsimilar to the nodes in a network graph. Each dance partners' interaction mirrors the edges that link the nodes, crafting a dancefloor-web, a visual and dynamic representation of complex relationships and interactions.

Now, let's translate this elegant interaction into our scientific work. We have a digital network, a choreography of its own weaved into data, stored in compact notation within a 'littleballoffur3.sparse6' file. It's a vast network, a grand ballroom of interactions, and we, as dance therapists, understand that sometimes we need to focus on a smaller group to see the individual movements more clearly.

So, here's what I'd love to pose to you, a challenge wrapped in our world's allegory: How might we extract, or better yet, sample a smaller dance troupe from our grand assembly held within 'littleballoffur3.sparse6'? Imagine we aimed to focus our therapeutic lens on just a circle of 10 dancers Ã¢ÂÂ or in the case of our data, 10 nodes. The SpikyBallSampler, a tool in our littleballoffur ensemble, is the method we'll employ to invite just a handful of nodes onto our intimate dance floor, ensuring their connections still reflect the larger story.

Thus, in the language of our technological craft, could you guide me on how to utilize the SpikyBallSampler to select a subgraph comprised of exactly 10 nodes from the graph outlined in the 'littleballoffur3.sparse6' file?
### Response:
import networkx as nx
from littleballoffur.exploration_sampling import SpikyBallSampler
G = nx.read_sparse6('littleballoffur3.sparse6')
sampler = SpikyBallSampler(number_of_nodes=10)
sampler_G = sampler.sample(G)
print(sampler_G.edges(), sampler_G.nodes())
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