<｜begin▁of▁sentence｜>### Instruction:
Given a directed graph with nodes x, a, b, c, d, e, y and edges with capacities as follows: ('x', 'a', 3), ('x', 'b', 1), ('a', 'c', 3), ('b', 'c', 5), ('b', 'd', 4), ('d', 'e', 2), ('c', 'y', 2), ('e', 'y', 3), can you compute the maximum flow from node 'x' to node 'y' and provide the value of the flow as well as a dictionary showing the flow through each edge using NetworkX?
### Response:
import networkx as nx

# Create a directed graph
G = nx.DiGraph()

# Add edges with capacities
G.add_edge('x', 'a', capacity=3)
G.add_edge('x', 'b', capacity=1)
G.add_edge('a', 'c', capacity=3)
G.add_edge('b', 'c', capacity=5)
G.add_edge('b', 'd', capacity=4)
G.add_edge('d', 'e', capacity=2)
G.add_edge('c', 'y', capacity=2)
G.add_edge('e', 'y', capacity=3)

# Compute the maximum flow between 'x' (source) and 'y' (sink)
flow_value, flow_dict = nx.maximum_flow(G, 'x', 'y')

print('Flow value:', flow_value)
print('Flow dict:', flow_dict)
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