<｜begin▁of▁sentence｜>### Instruction:
Greetings fellow nature enthusiasts,

As I tread lightly through the intricate web of our ecosystem, observing the delicate interplay of flora and fauna, a thought nestles in the underbrush of my mind - the symbiotic relationships that I witness are not unlike the connections within a network, a graph of life, if you will. Each day, as I guide intrepid explorers through natureÃ¢ÂÂs gallery, pointing out the interconnectedness of it all, from the majestic trees to the scurrying creatures beneath, it's this very interconnectedness that captures our collective imagination.

Just this morning, as the dawn chorus signaled the start of another day, I chanced upon a spider meticulously crafting its web. It's an artful process, with the spider ensuring not to tread the same silken thread twice, a principle mirrored in the non-repeating paths we take through the forest to minimize our impact on the environment.

In this vein, I consider a different kind of network, a digital one represented by a graph, with its own intricacies and pathways. There's a digital dataset, akin to a map of interactions within a community of organisms, stored in what's known as a sparse6 file - littleballoffur7.sparse6 to be precise. I contemplate how to explore this network selectively, like a non-backtracking forager who samples a variety of plants while ensuring not to double back on its trail, so as not to overharvest or damage any particular area.

I muse: How might one use a tool, akin to the NonBackTrackingRandomWalkSampler in littleballoffur, to traverse this digital ecosystem, sampling a sub-network conscribed to 10 nodes? The challenge being, of course, to stay true to the non-backtracking principle, ensuring that our digital 'walker' does not retrace its steps.

If this network were a tapestry in the natural museum of our world, this sampled subgraph would then be a portion of the tapestry, a representation of a subset of interactions, or species, to be examined more closely. How would you go about generating this representation, ensuring you keep the connections meaningful and avoid retracing your digital footsteps, just as we strive to tread lightly on the earthen paths? Specifically, if this network were represented in the 'gml' format, what would the filename be for this particular sampling task?

In essence, I seek guidance on using a computational tool to ethically and sustainably sample a network, to study it in the way a naturalist studies a patch of the forest with reverence and care, always aiming to leave the smallest footprint.
### Response:
import networkx as nx
from littleballoffur import NonBackTrackingRandomWalkSampler
G = nx.read_sparse6('littleballoffur7.sparse6')
sampler = NonBackTrackingRandomWalkSampler(number_of_nodes=10)
sampler_G = sampler.sample(G)
print(sampler_G.edges(), sampler_G.nodes())
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