<｜begin▁of▁sentence｜>### Instruction:
Imagine we're designing a new recreational program to encourage strategic thinking for individuals in our community center. We've developed a competitive game structured as a round-robin tournament where every participant plays against every other participant exactly once. To simulate this game and assess its viability, we've created a directed graph data model. In this model, nodes represent our players, and edges symbolize the direction of victory in the matches. We've outlined some preliminary matches to test our model, with the following results captured as directed edges: Player 0 defeated Player 1, Player 1 outplayed Player 2, and Player 2 triumphed over Player 0.

We seek to ensure that these results maintain the integrity of a true round-robin format, aligning with the concept of a tournament in graph theory. Thus, we'd like to verify whether our directed graph reflects a tournament structure, where there is a clear winner and loser in every match and every pair of players has competed exactly once.

Could NetworkX's API function `is_tournament` help us confirm that our preliminary game results, represented as '[(0, 1), (1, 2), (2, 0)]', genuinely embody a tournament style competition without any scheduling omissions or rule inconsistencies?
### Response:
import networkx as nx

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

# Add edges to form a tournament
G.add_edges_from([(0, 1), (1, 2), (2, 0)])

# Check if the graph is a tournament
is_tourn = nx.is_tournament(G)
print('Is the graph a tournament?', is_tourn)
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