<｜begin▁of▁sentence｜>### Instruction:
Imagine you're a dynamic sales representative responsible for managing a network of clients and potential leads. Your client portfolio is structured much like a directed network, with four critical market segments labeled as 0, 1, 2, and 3. The interactions between these segments are akin to the flow of a sales cycle, represented by directed pathways: going from segment 0 to 1, then back to 0, onward to 2, circling back to 0, reaching back to 1, and finally connecting from an emerging market, segment 3, to 1.

You're tasked with a strategic approach to navigating these interactions, beginning with market segment 0, spreading the word about your products efficiently, and adhering to a methodical pattern akin to a breadth-first traversal of your market network. Your objective is to outline the sequence of interactions between market segments, specifically noting the order in which you'd engage each segment to maximize your sales outreach efforts. Could you arrange your client interaction itinerary reflecting this approach, given the directional flow among the market segments you handle? Remember, the goal is to sequence your visits without doubling back on any segment prematurely, as you would in a well-planned travel agenda.
### Response:
import networkx as nx

# Define the nodes of the graph
nodes = [0, 1, 2, 3]

# Define the directed edges of the graph
edges = [(0, 1), (1, 0), (1, 2), (2, 0), (2, 1), (3, 1)]

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

# Perform a breadth-first search of edges, starting from node 0
edges_bfs = list(nx.edge_bfs(G, 0))

# Output the edges visited in BFS order
print('Edges visited in BFS order:', edges_bfs)
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