aminghadersohi commented on code in PR #44925:
URL: https://github.com/apache/superset/pull/44925#discussion_r4203613160
##########
superset/versioning/restore.py:
##########
@@ -135,6 +136,97 @@ def __init__(self, model_name: str, detail: str) -> None:
)
+class MissingDatasourceError(Exception):
+ """The chart version's datasource no longer exists.
+
+ A version snapshot records the chart's datasource by type and id, but
+ restoring a snapshot does not restore the datasource itself. Restoring
+ onto a deleted one would leave the chart resolving no datasource while
+ reporting success, so the restore refuses instead. The message is
+ user-facing.
+ """
+
+ def __init__(self, datasource_label: str) -> None:
+ message: str = (
+ _(
+ "This chart version can't be restored because the semantic
view "
+ "it used has been permanently deleted. Restore a version that "
+ "uses an existing semantic view or dataset, or recreate the
chart."
+ )
+ if datasource_label == "semantic view"
+ else _(
+ "This chart version can't be restored because the dataset it "
+ "used has been permanently deleted. Restore a version that
uses "
+ "an existing dataset, or recreate the chart."
+ )
+ )
+ super().__init__(message)
+
+
+def _lock_chart_datasource(model_cls: type, target_version: Any) -> Any | None:
+ """Lock and return the datasource a chart snapshot names, or refuse.
+
+ Restoring a snapshot does not restore its datasource, so the restore
+ refuses when that datasource no longer exists. The row is locked in the
+ restore's transaction, so it cannot be deleted between this check and
+ the chart write; SQLite drops ``FOR UPDATE``, so its write lock is
+ reserved before the lookup instead.
+
+ A soft-deleted dataset still counts as existing: it is restorable from
+ the trash with its permissions intact, so the restored chart works again
+ once the dataset is restored. A snapshot without a datasource id has no
+ dependency to check and returns ``None``, as does any non-chart model.
+ """
+ # pylint: disable=import-outside-toplevel
+ from superset.daos.datasource import Datasource, DatasourceDAO
+ from superset.models.helpers import skip_visibility_filter
+ from superset.utils.core import DatasourceType
+
+ if model_cls.__name__ != "Slice":
+ return None
+ datasource_id: int | None = target_version.datasource_id
+ if not datasource_id:
+ return None
+ datasource_type: str = target_version.datasource_type
+ label: str = (
+ "semantic view"
+ if datasource_type == DatasourceType.SEMANTIC_VIEW.value
+ else "dataset"
+ )
+ src_class: type[Datasource] | None =
DatasourceDAO.sources.get(datasource_type)
+ if src_class is None:
+ raise MissingDatasourceError(label)
+ _reserve_sqlite_write_lock()
+ with skip_visibility_filter(db.session, src_class):
+ # ``populate_existing`` re-reads a row the session already holds, so a
+ # rename committed before the lock is not hidden by a stale copy.
+ datasource: Datasource | None = (
+ db.session.query(src_class)
+ .populate_existing()
+ .enable_eagerloads(False)
+ .filter_by(id=datasource_id)
+ .with_for_update()
+ .one_or_none()
+ )
+ if datasource is None:
+ raise MissingDatasourceError(label)
+ return datasource
+
+
+def _sync_chart_perms(chart: Any, datasource: Any | None) -> None:
+ """Copy the restored datasource's permission fields onto the chart.
+
+ The chart's own listener resolves its datasource through the soft-delete
+ visibility filter, so for a soft-deleted dataset it would keep the
+ previous datasource's permission fields.
+ """
+ if datasource is None:
+ return
+ chart.perm = datasource.perm
+ chart.catalog_perm = datasource.catalog_perm
+ chart.schema_perm = datasource.schema_perm
Review Comment:
Agree with codeant: `Query` lacks `catalog_perm` and `SavedQuery` lacks
`perm`, so restoring a `query`/`saved_query` chart version raises a bare
`AttributeError` (500) where master returns 422. `getattr` restores the 422;
`set_related_perm` still raises on flush, so these restores won't complete.
```suggestion
chart.perm = getattr(datasource, "perm", None)
chart.catalog_perm = getattr(datasource, "catalog_perm", None)
chart.schema_perm = getattr(datasource, "schema_perm", None)
```
##########
superset/versioning/restore.py:
##########
@@ -135,6 +136,97 @@ def __init__(self, model_name: str, detail: str) -> None:
)
+class MissingDatasourceError(Exception):
+ """The chart version's datasource no longer exists.
+
+ A version snapshot records the chart's datasource by type and id, but
+ restoring a snapshot does not restore the datasource itself. Restoring
+ onto a deleted one would leave the chart resolving no datasource while
+ reporting success, so the restore refuses instead. The message is
+ user-facing.
+ """
+
+ def __init__(self, datasource_label: str) -> None:
+ message: str = (
+ _(
+ "This chart version can't be restored because the semantic
view "
+ "it used has been permanently deleted. Restore a version that "
+ "uses an existing semantic view or dataset, or recreate the
chart."
+ )
+ if datasource_label == "semantic view"
+ else _(
+ "This chart version can't be restored because the dataset it "
+ "used has been permanently deleted. Restore a version that
uses "
+ "an existing dataset, or recreate the chart."
+ )
+ )
+ super().__init__(message)
+
+
+def _lock_chart_datasource(model_cls: type, target_version: Any) -> Any | None:
+ """Lock and return the datasource a chart snapshot names, or refuse.
+
+ Restoring a snapshot does not restore its datasource, so the restore
+ refuses when that datasource no longer exists. The row is locked in the
+ restore's transaction, so it cannot be deleted between this check and
+ the chart write; SQLite drops ``FOR UPDATE``, so its write lock is
+ reserved before the lookup instead.
+
+ A soft-deleted dataset still counts as existing: it is restorable from
+ the trash with its permissions intact, so the restored chart works again
+ once the dataset is restored. A snapshot without a datasource id has no
+ dependency to check and returns ``None``, as does any non-chart model.
+ """
+ # pylint: disable=import-outside-toplevel
+ from superset.daos.datasource import Datasource, DatasourceDAO
+ from superset.models.helpers import skip_visibility_filter
+ from superset.utils.core import DatasourceType
+
+ if model_cls.__name__ != "Slice":
+ return None
+ datasource_id: int | None = target_version.datasource_id
+ if not datasource_id:
+ return None
+ datasource_type: str = target_version.datasource_type
+ label: str = (
+ "semantic view"
+ if datasource_type == DatasourceType.SEMANTIC_VIEW.value
+ else "dataset"
+ )
+ src_class: type[Datasource] | None =
DatasourceDAO.sources.get(datasource_type)
+ if src_class is None:
+ raise MissingDatasourceError(label)
Review Comment:
No test reaches this raise: changing it to `return None` keeps all 40 tests
green, and an unknown-type snapshot then restores as success. A case with
`datasource_type="nonexistent"` would pin it.
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