henry3260 commented on code in PR #72036:
URL: https://github.com/apache/airflow/pull/72036#discussion_r4027870108
##########
airflow-core/src/airflow/cli/commands/team_command.py:
##########
@@ -303,3 +303,45 @@ def team_verify(args, *, session=NEW_SESSION):
raise SystemExit(1)
print("Verification succeeded.")
+
+
+@cli_utils.action_cli
+@providers_configuration_loaded
+@provide_session
+def team_inspect(args, *, session=NEW_SESSION):
+ """Inspect resources belonging to a team."""
+ team_name = _extract_team_name(args)
Review Comment:
Should we check multi_team first?
```
if not conf.getboolean("core", "multi_team"):
print("Multi-team is not enabled.")
return
```
##########
airflow-core/src/airflow/cli/commands/team_command.py:
##########
@@ -303,3 +303,45 @@ def team_verify(args, *, session=NEW_SESSION):
raise SystemExit(1)
print("Verification succeeded.")
+
+
+@cli_utils.action_cli
+@providers_configuration_loaded
+@provide_session
+def team_inspect(args, *, session=NEW_SESSION):
+ """Inspect resources belonging to a team."""
+ team_name = _extract_team_name(args)
+
+ team = session.scalar(select(Team).where(Team.name == team_name))
+ if team is None:
+ raise SystemExit(f"Team '{team_name}' does not exist")
+
+ bundle_names = session.scalars(
+ select(dag_bundle_team_association_table.c.dag_bundle_name)
+ .where(dag_bundle_team_association_table.c.team_name == team_name)
+ .order_by(dag_bundle_team_association_table.c.dag_bundle_name)
+ ).all()
+
+ pool_names = session.scalars(
+ select(Pool.pool).where(Pool.team_name ==
team_name).order_by(Pool.pool)
+ ).all()
+
+ connection_ids = session.scalars(
+ select(Connection.conn_id).where(Connection.team_name ==
team_name).order_by(Connection.conn_id)
+ ).all()
+
+ variable_keys = session.scalars(
+ select(Variable.key).where(Variable.team_name ==
team_name).order_by(Variable.key)
+ ).all()
+
+ AirflowConsole().print_as(
+ data=[team],
+ output=args.output,
+ mapper=lambda x: {
+ "name": x.name,
+ "dag_bundles": bundle_names,
+ "pools": pool_names,
+ "connections": connection_ids,
+ "variables": variable_keys,
Review Comment:
`print_as` calls mapper once per element in data, so the mapper is expected
to derive the whole row from x. Here only name does — the other four keys close
over `bundle_names / pool_names / connection_ids / variable_keys`, which are
computed once outside for a single team_name.
It's correct today only because data has exactly one element. If data ever
grows to more than one team, every row would silently repeat the first team's
resources while name varies.
Since there's only one row anyway, dropping the mapper and passing the dict
directly would sidestep this `print_as` accepts a dict sequence via
is_data_sequence:
```
AirflowConsole().print_as(
data=[
{
"name": team.name,
"dag_bundles": bundle_names,
"pools": pool_names,
"connections": connection_ids,
"variables": variable_keys,
}
],
output=args.output,
)
```
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