SIENTIAPDE-1712

Remove `query_to_minio` method from Storage class and update worker activities to eliminate its usage. This change streamlines the codebase by removing unused functionality related to MinIO queries.

laborious/activities/storage.py

@@ -206,75 +206,6 @@ class Storage(Postgres, MinioManager):
 
         return report
 
-    @activity.defn(name='query_to_minio')
-    async def query_to_minio(self, input_data: dict[str, Any]) -> dict[str, Any]:
-        """
-        Execute SQL query, write result as Parquet to MinIO, and return object name.
-
-        Args (input_data):
-            metadata (dict): Workflow metadata
-            query (str): SQL query
-            model_name (str): Model name for object naming
-            object_prefix (str, optional): Prefix inside bucket (default: datasets/retrain)
-
-        Returns:
-            dict: { success: bool, object_name: str, uri: str }
-        """
-
-        if self.minio_repository is None:
-            raise ValueError('Minio repository not initialized')
-
-        metadata = input_data.get('metadata', {})
-        model_name = input_data.get('model_name') or metadata.get('model_name') or 'unknown'
-        object_prefix = input_data.get('object_prefix', 'datasets/retrain')
-
-        timestamp = now().strftime(DATETIME_FORMAT_FILENAME)
-        # Keep a stable model-level layout for minimal_retrain:
-        #   training_datasets/<model_name>/<filename>
-        # Sanitize object_prefix to avoid extra subdirectories in the relative key.
-        safe_prefix = str(object_prefix).strip().strip('/').replace('/', '_')
-        filename = f'{safe_prefix}_{timestamp}.parquet'
-        relative_key = f'training_datasets/{model_name}/{filename}'
-        bucket = getattr(self.minio_repository, 'bucket', 'streamlit-connectors')
-        uri = f's3://{bucket}/{relative_key}'
-
-        try:
-            data = await self.load_custom_query(input_data)
-            if not data:
-                self.error('query_to_minio failed: No data returned from query', metadata)
-                return {'success': False, 'message': 'No data returned from query'}
-
-            # Ensure we have a DataFrame
-            data = pd.DataFrame(data)
-
-            # Convert DataFrame -> parquet bytes, then upload using the new MinIO interface.
-            parquet_buffer = BytesIO()
-            data.to_parquet(parquet_buffer, engine='pyarrow', index=True)
-            file_bytes = parquet_buffer.getvalue()
-
-            upload_result = await self.minio_repository.upload_file(
-                file_bytes=file_bytes,
-                relative_key=relative_key,
-                metadata=metadata,
-            )
-
-            object_key_full = upload_result.get('minio_object_name', relative_key)
-            uri = f's3://{bucket}/{object_key_full}'
-            return {'success': True, 'object_key': object_key_full, 'uri': uri}
-        except Exception as e:
-            trace = traceback.format_exc()
-            await self.send_notification_async(
-                metadata=metadata,
-                notification_id='ERROR_STORING_QUERY_TO_MINIO',
-                message=f'Error storing query to MinIO: {e}',
-                block='query_to_minio',
-                level=NotificationLevel.ERROR,
-                attachment_content=trace,
-            )
-
-            self.error(trace, metadata)
-
-            return {'success': False, 'message': str(e)}
 
     def close(self) -> None:
         """Close Storage resources (MinIO client and Postgres engine)."""