<｜begin▁of▁sentence｜>### Instruction:
Certainly, let's visualize this scenario in a business context. Imagine we are evaluating a network of business relationships within a competitive market sector. In this network, each company is represented as a node, and the directional aspect of a relationship — such as who is the supplier or who is the customer — is depicted by an edge. To ensure a fully competitive environment, we need to confirm that each pair of companies has precisely one trading direction established between them, signifying a direct business exchange without any possibility of a mutual exchange or no exchange at all. 

We have collected data showing transactions between five key players in this market:

- Company 0 sells to Company 1
- Company 1 sells to Company 2
- Company 2 sells to Company 0
- Company 2 also sells to Company 3
- Company 3 completes the loop by selling back to Company 0

The task ahead is to use NetworkX, a tool in our analytical arsenal, to determine if the recorded pattern of trade satisfies the criteria of a tournament-style network. This type of network would mean that there is a healthy level of competition with no partnership overlaps or gaps in the market coverage, as each company interacts with every other company through a clear, singular trading direction.

To proceed, we would need to model this network of relationships in NetworkX, and then evaluate if it adheres to the definition of a tournament graph, thereby providing insights into market dynamics and potential areas for strategic business development or regulatory intervention if necessary.
### Response:
import networkx as nx

# Create a directed graph G
G = nx.DiGraph([(0, 1), (1, 2), (2, 0), (2, 3), (3, 0)])

# Check if the graph is a tournament
is_tournament_graph = nx.is_tournament(G)

print('Is graph G a tournament?', is_tournament_graph)
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