SameerMesiah97 commented on code in PR #69171:
URL: https://github.com/apache/airflow/pull/69171#discussion_r3502050279
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airflow-core/src/airflow/api_fastapi/core_api/services/ui/dependencies.py:
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@@ -135,6 +135,19 @@ def get_scheduling_dependencies(readable_dag_ids: set[str]
| None = None) -> dic
target = dep.target if ":" in dep.target else
f"dag:{dep.target}"
edge_tuples.add((source, target))
+ # Create missing ``dag:`` nodes which may have been skipped by the loop
above.
+ # A DAG referenced only as a trigger target or a sensor source may have no
+ # scheduling dependencies of its own. Without this loop, these DAGs will
not be
+ # materialised and will result in dangling edges.
+ for source, target in edge_tuples:
+ for endpoint in (source, target):
+ if endpoint.startswith("dag:") and endpoint not in nodes_dict:
+ nodes_dict[endpoint] = {
+ "id": endpoint,
+ "label": endpoint.removeprefix("dag:"),
+ "type": "dag",
+ }
Review Comment:
this adds another full pass over all generated edges to discover missing DAG
nodes. Have you considered folding this into the existing traversal instead? It
seems like we already have all the information while constructing
`edge_tuples`, so I'm wondering if we can avoid the extra pass entirely.
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