<｜begin▁of▁sentence｜>### Instruction:
Imagine you're analyzing the infrastructure of a secure network to identify potential single points of failure in the architecture. You're using a directed graph model to represent the network flow between different nodes, where each node represents a server or network device and each directed edge represents communication from one node to another. Your task is to enhance your understanding of the network by identifying all servers in the system that would be affected in the second degree of separation should the primary node (identified as node 0) experience an issue.

Using your cybersecurity analysis tools, you're particularly interested in a specific subset of the network topology. The connectivity data you've obtained so far includes the following communication paths: server 0 connects to servers 1 and 2, server 1 connects to servers 3 and 4, and server 2 connects to servers 5 and 6.

Can you determine which servers would be exactly two steps away from the primary server 0 within this network schematic, using NetworkX to visualize and calculate the distances in this directed graph? This information will be critical for understanding the ripple effect of a potential issue originating at server 0 and for preparing a robust security protocol accordingly.
### Response:
import networkx as nx

# Create a directed graph
H = nx.DiGraph()
H.add_edges_from([(0,1), (0,2), (1,3), (1,4), (2,5), (2,6)])

# Get all nodes at distance 2 from the source node 0
nodes_at_distance_2 = nx.descendants_at_distance(H, 0, 2)

print('Nodes at distance 2 from node 0:', nodes_at_distance_2)
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