<｜begin▁of▁sentence｜>### Instruction:
In the context of preparing transcripts for a legal case involving analysis of traffic patterns within a complex network infrastructure, imagine we are examining a diagram representing various points of data exchange. This diagram is essentially a map detailing the connections between different nodes in the network, which for the purposes of record, include links such as (0, 1), (1, 2), (2, 0), (2, 3), (4, 5), (3, 4), (5, 6), (6, 3), and (6, 7).

For the proceedings, we need to ascertain the number of distinct, self-sufficient clusters within this network, where data can seamlessly circulate among the nodes in that cluster but not necessarily to or from nodes of other clusters. In other words, how many separate groups are there where information is able to flow freely in all directions within each group?

Could you provide this information for the court's records, maintaining the accuracy and precision required for legal documentation?
### Response:
import networkx as nx

# Create a directed graph
G = nx.DiGraph()
# Add edges
e = [(0, 1), (1, 2), (2, 0), (2, 3), (4, 5), (3, 4), (5, 6), (6, 3), (6, 7)]
G.add_edges_from(e)

# Compute the number of strongly connected components
num_scc = nx.number_strongly_connected_components(G)

print('Number of strongly connected components:', num_scc)
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