<｜begin▁of▁sentence｜>### Instruction:
Imagine you're assisting a team of mental health professionals in examining the structure of support within a community, where individuals are represented as nodes and the support direction as edges in a directed graph. To understand the clustering of support networks, you're working with a digital map saved as "community_support.gml". Could you help the team understand how many isolated support clusters exist within this community by finding out the quantity of weakly connected components in this map using NetworkX?
### Response:
import networkx as nx

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

# Add edges to the graph (nodes are added automatically)
G.add_edges_from([(0, 1), (2, 1), (3, 4), (4, 5)])

# Use the function to find the number of weakly connected components
num_components = nx.number_weakly_connected_components(G)

print('Number of weakly connected components:', num_components)
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