codeant-ai-for-open-source[bot] commented on code in PR #43490:
URL: https://github.com/apache/superset/pull/43490#discussion_r3864763006
##########
superset/initialization/__init__.py:
##########
@@ -1002,11 +1005,14 @@ def _warn_if_retention_beat_missing(self) -> None:
"CeleryConfig or add the module to your override.",
self._RETENTION_TASK_MODULE,
)
- default_flags = self.config.get("DEFAULT_FEATURE_FLAGS", {})
- configured_flags = self.config.get("FEATURE_FLAGS", {})
- soft_delete_enabled = bool(
+ default_flags: dict[str, Any] =
self.config.get("DEFAULT_FEATURE_FLAGS", {})
+ configured_flags: dict[str, Any] = self.config.get("FEATURE_FLAGS", {})
+ soft_delete_enabled: bool = bool(
configured_flags.get("SOFT_DELETE",
default_flags.get("SOFT_DELETE", False))
)
+ audit_pruning_enabled: bool = (
+ self.config.get("PURGE_AUDIT_PRUNING_ENABLED", False) is True
+ )
Review Comment:
The comment is valid. `is True` correctly prevents invalid values from
enabling pruning, but it also collapses invalid values into the legitimate
`False` state, so startup provides no actionable warning.
Keep the fail-closed behavior, but validate the type separately:
```python
audit_pruning_config: Any = self.config.get(
"PURGE_AUDIT_PRUNING_ENABLED", False
)
if not isinstance(audit_pruning_config, bool):
logger.warning(
"deletion-retention: invalid PURGE_AUDIT_PRUNING_ENABLED=%r; "
"audit pruning remains disabled",
audit_pruning_config,
)
audit_pruning_enabled = False
else:
audit_pruning_enabled = audit_pruning_config
```
Then retain the existing schedule/import checks based on
`audit_pruning_enabled`. This preserves the task’s strict behavior while making
values such as `"true"` and `1` visible during initialization. A focused test
should assert that an invalid value logs a warning and does not trigger the
schedule check.
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