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This repository was archived by the owner on Nov 1, 2024. It is now read-only.
Use a similar method in a related PR, to support LabGraph topology in LabGraph Monitor. This will be a function that looks something like: def generate_labgraph_monitor(graph: df.Graph) -> None:
The graph topology itself consists of the following:
Methods (these are the nodes in the graph)
Publishers (these are directed edges leaving a method)
Subscribers (these are directed edges entering a method)
Nodes (these are logical groupings of methods which always share the same process – technically not part of the topology, but the grouping may be useful to call out)
Topics
Topics determine what the directed edges are. Any two connected topics will back the same stream. Each stream will have one publisher and one or more subscribers; the edges are all from that publisher to each subscriber.
We can inspect these properties of a graph by looking at these private attributes: __topics__: The topics __streams__: The streams __methods__: The methods (publishers, subscribers, and "transformers" which are just methods with both @publisher and @subscriber decorators)