<｜begin▁of▁sentence｜>### Instruction:
Alright, picture this: you're working on a documentary about the intricate networks of the film industry Ã¢ÂÂ it's all about who knows who, right? Imagine the network of actors, directors, and producers as a complex web connecting Hollywood's finest. Now, we've mapped out this network into an extensive graph that looks as convoluted as a studio's wiring. It's our job as filmmakers to edit this down into an insightful substory, showcasing the most connected individuals, akin to highlighting the stars who really shine in terms of collaborations and influence.

To craft this narrative, we're looking to extract just a snippet - a subgraph of 10 key players that best represent the big picture. Think of it as casting for the most pivotal roles in our screening, excising the most integral nodes based on the weight of their connections in the grand scheme of Tinseltown.

Could you dive in with the DegreeBasedSampler tool, it's like your camera lens focusing on the most prominent characters in a frame, zooming into those whose degree of centrality stands out. They're the ones who would make it to the posters - their names pull the crowds. We want the subgraph to reflect this star-studded prominence. Now, our graph's details are stored in a digital format akin to a script, specifically named "littleballoffur2.sparse6". Consider this the raw footage we need to refine.

So, could you direct this sequence by using the DegreeBasedSampler, keeping in mind that I'm looking for a premier cast of 10 from this digital narrative? Let's make this subgraph sampling as top-billed as an A-list gala, shall we? And just to stick with protocol, if we were working with a ".gml" file, I'd say we name our file after the project, perhaps "HollywoodNetwork.gml," for the sake of this script. But, alas, we're working from "littleballoffur2.sparse6".
### Response:
import networkx as nx
from littleballoffur import DegreeBasedSampler
G = nx.read_sparse6('littleballoffur2.sparse6')
sampler = DegreeBasedSampler(number_of_nodes=10, seed=42)
sampler_G = sampler.sample(G)
print(sampler_G.edges())
print(sampler_G.nodes());
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