<｜begin▁of▁sentence｜>### Instruction:
You know how it is in the studio, right? You're laying tracks, dialing in the mix, getting everything sounding just perfect. That's how it is when I'm doing my thing with audio Ã¢ÂÂ a little tweak here, a little adjustment there, until everything fits into place. But today, it's like I'm remixing, but with data, not sound. I've got this raw recording of sorts Ã¢ÂÂ it's a graph, but it's stored in this sparse6 format in a file named 'littleballoffur4.sparse6'. What I'm jamming on is pulling a solid sample out of this graph, you know? Like, I need to isolate a piece of it, just like I would with a killer drum break or a guitar riff. 

I need this sample to be exactly 10 nodes, keeping the vibe of the original. Think of it like I need a submix from a massive multitrack recording. So, if we were to switch the studio for a data lab for a sec, how would I use something called the CirculatedNeighborsRandomWalkSampler to extract that 10-node subset sample from our graph track? And let's keep it on-brand for our data mixing session, if this was a GML file instead, what would its name be?
### Response:
import networkx as nx
from littleballoffur import CirculatedNeighborsRandomWalkSampler
G = nx.read_sparse6('littleballoffur4.sparse6')
sampler = CirculatedNeighborsRandomWalkSampler(number_of_nodes=10)
sample_G = sampler.sample(G)
print(sample_G.edges(), sample_G.nodes())
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