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import graphinate
N: int = 8
# First Define a GraphModel instance.
# It will be used to hold the graph definitions
graph_model: graphinate.GraphModel = graphinate.model(name="Octagonal Graph")
# Register in the Graph Model the edges' supplier generator function
@graph_model.edge()
def edge():
for i in range(N):
yield {'source': i, 'target': i + 1}
yield {'source': N, 'target': 0}
# Use the NetworkX Builder
builder = graphinate.builders.NetworkxBuilder(graph_model)
# build the NetworkX GraphRepresentation
# the output in this case is a nx.Graph instance
graph = builder.build()
# this supplied plot method uses matplotlib to display the graph
graphinate.matplotlib.plot(graph, with_edge_labels=True)
# or use the Mermaid Builder
builder = graphinate.builders.MermaidBuilder(graph_model)
# to create a Mermaid diagram
diagram: str = builder.build()
# and get Markdown or single page HTML to display it
mermaid_markdown: str = graphinate.mermaid.markdown(diagram)
mermaid_html: str = graphinate.mermaid.html(diagram, title=graph_model.name)
# or use the GraphQL Builder
builder = graphinate.builders.GraphQLBuilder(graph_model)
# to create a Strawberry GraphQL schema
schema = builder.build()
# and serve it using Uvicorn web server
graphinate.graphql.server(schema)
erivlis /
graphinate
