<｜begin▁of▁sentence｜>### Instruction:
As a computer programmer tasked with testing a network simulation, let's say you need to create a test case to evaluate an algorithm's performance on networks that exhibit certain levels of randomness. You're interested in generating a sample network that mirrors the properties of an Erdős-Rényi model with a node count of `6`, where each possible edge appears independently with a probability of `0.5`. To ensure reproducibility, you're using a fixed `seed` value set to `42`.

Could you rephrase your requirement into code to construct this network using NetworkX? After doing so, how would you programmatically output the list of edges that this generated network comprises? Please ensure that the process is consistent each time it's executed by factoring in the seed value provided.
### Response:
import networkx as nx

# Create a random binomial graph
n = 6  # number of nodes
p = 0.5  # probability of edge creation
seed = 42  # seed for random number generator
directed = False  # if True, creates a directed graph

# Using the binomial graph function
g = nx.binomial_graph(n, p, seed=seed, directed=directed)

# Print the edges of the generated graph
print(g.edges())
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