<｜begin▁of▁sentence｜>### Instruction:
Suppose you're navigating a case involving a family's immigration process, wherein the 'root' represents the primary applicant, and 'child 1' and 'child 2' signify the applicant's dependents. The connections between the root and each child symbolize the dependencies in their application procedures. To efficiently organize and manage the sequence in which each dependent's paperwork should be processed, you're considering utilizing a strategy analogous to the breadth-first search method.

How might you adapt the concept of the bfs_edges function from network analysis to map out the procedural links starting from the primary applicant ('root') and subsequently progressing through each dependent ('child 1' and 'child 2'), thereby establishing a systematic approach to tackle the family's immigration applications? Your objective is to derive an ordered list of these procedural steps, mirroring the edges traversed during the search.
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()

# Add nodes and edges to the graph
G.add_nodes_from([(0, {'label': 'root'}), (1, {'label': 'child 1'}), (2, {'label': 'child 2'})])
G.add_edges_from([(0, 1, {'label': 'edge 0-1'}), (0, 2, {'label': 'edge 0-2'})])

# Perform a breadth-first search starting from the root node (0)
edges_bfs = list(nx.bfs_edges(G, source=0))

# Print the edges traversed in BFS
print('BFS Edges:', edges_bfs)
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