<｜begin▁of▁sentence｜>### Instruction:
Given a weighted graph with edges [('A', 'B', 4), ('B', 'C', 2), ('A', 'C', 5), ('C', 'D', 1)], how can you compute the current flow closeness centrality for nodes in the graph using NetworkX?
### Response:
import networkx as nx

# Create a weighted graph
G = nx.Graph()
G.add_edge('A', 'B', weight=4)
G.add_edge('B', 'C', weight=2)
G.add_edge('A', 'C', weight=5)
G.add_edge('C', 'D', weight=1)

# Compute the current flow closeness centrality
centrality = nx.current_flow_closeness_centrality(G, weight='weight', dtype=float, solver='lu')

print(centrality)
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