<｜begin▁of▁sentence｜>### Instruction:
Given a directed graph with nodes {x, a, b, c, d, e, y} and edge capacities {('x','a'):3, ('x','b'):1, ('a','c'):3, ('b','c'):5, ('b','d'):4, ('d','e'):2, ('c','y'):2, ('e','y'):3}, how can we use the Edmonds-Karp algorithm to find the maximum flow from node 'x' to node 'y' and what is the value of this maximum flow?
### Response:
import networkx as nx
from networkx.algorithms.flow import edmonds_karp

# Create a DiGraph and add edges with capacity
G = nx.DiGraph()
G.add_edge('x', 'a', capacity=3.0)
G.add_edge('x', 'b', capacity=1.0)
G.add_edge('a', 'c', capacity=3.0)
G.add_edge('b', 'c', capacity=5.0)
G.add_edge('b', 'd', capacity=4.0)
G.add_edge('d', 'e', capacity=2.0)
G.add_edge('c', 'y', capacity=2.0)
G.add_edge('e', 'y', capacity=3.0)

# Apply Edmonds-Karp algorithm to find the maximum flow from 'x' to 'y'
R = edmonds_karp(G, 'x', 'y')

# The flow value is the total flow into the sink 'y'
flow_value = R.graph['flow_value']
print('Maximum flow from node x to node y:', flow_value)
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