<｜begin▁of▁sentence｜>### Instruction:
As a biologist, let's say you're exploring a vast ecosystem represented by an intricate network of interactions among 500 species. This network mirrors the complex web of relationships within the ecosystem, with each species connected to others based on shared interactions. Now, imagine you want to study a subset of this network, focusing on a community of 150 species and their immediate connections.

To accomplish this, you can utilize a sampling technique called RandomNodeNeighborSampler. This technique allows you to randomly select a starting species and then expand your selection by including its neighboring species, gradually forming a subgraph. By repeating this process, you can construct a representative subset of the larger network, providing valuable insights into the local dynamics of species interactions within the ecosystem.

So, in essence, you're employing RandomNodeNeighborSampler from the networkx library to sample a subgraph comprising 150 species from the larger network, thereby enabling you to analyze the interconnected relationships within this selected community of organisms.
### Response:
import networkx as nx
from littleballoffur import RandomNodeNeighborSampler

G = nx.gnp_random_graph(n=500, p=0.25)

sampler = RandomNodeNeighborSampler(number_of_nodes=150, seed=42)

sampler_G = sampler.sample(G)

print(sampler_G.nodes())
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