<｜begin▁of▁sentence｜>### Instruction:
Given a weighted directed graph with edge set [('A', 'B', 3), ('A', 'C', 2), ('B', 'C', 5), ('C', 'A', 1), ('C', 'B', 4)], how can you obtain a branching through a greedy algorithm using NetworkX, considering maximum weights, with a consistent random state?
### Response:
import networkx as nx

# Create a directed graph
G = nx.DiGraph()
G.add_weighted_edges_from([
    ('A', 'B', 3),
    ('A', 'C', 2),
    ('B', 'C', 5),
    ('C', 'A', 1),
    ('C', 'B', 4)
])

# Perform the greedy branching
B = nx.greedy_branching(G, attr='weight', default=1, kind='max', seed=42)

print('Edges of the greedy branching:', B.edges(data=True))
<|EOT|>
