# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. import logging from functools import partial from typing import Any from flask_appbuilder.models.sqla import Model from flask_babel import gettext as __ from marshmallow import ValidationError from superset.commands.base import BaseCommand, CreateMixin from superset.commands.dataset.exceptions import ( DatasetDuplicateFailedError, DatasetExistsValidationError, DatasetInvalidError, DatasetNotFoundError, ) from superset.commands.exceptions import DatasourceTypeInvalidError from superset.connectors.sqla.models import SqlaTable, SqlMetric, TableColumn from superset.daos.dataset import DatasetDAO from superset.errors import ErrorLevel, SupersetError, SupersetErrorType from superset.exceptions import SupersetErrorException from superset.extensions import db from superset.models.core import Database from superset.sql.parse import Table from superset.utils.decorators import on_error, transaction logger = logging.getLogger(__name__) class DuplicateDatasetCommand(CreateMixin, BaseCommand): def __init__(self, data: dict[str, Any]) -> None: self._base_model: SqlaTable = SqlaTable() self._properties = data.copy() @transaction(on_error=partial(on_error, reraise=DatasetDuplicateFailedError)) def run(self) -> Model: self.validate() database_id = self._base_model.database_id table_name = self._properties["table_name"] owners = self._properties["owners"] database = db.session.query(Database).get(database_id) if not database: raise SupersetErrorException( SupersetError( message=__("The database was not found."), error_type=SupersetErrorType.DATABASE_NOT_FOUND_ERROR, level=ErrorLevel.ERROR, ), status=404, ) table = SqlaTable(table_name=table_name, owners=owners) table.database = database table.schema = self._base_model.schema table.template_params = self._base_model.template_params table.normalize_columns = self._base_model.normalize_columns table.always_filter_main_dttm = self._base_model.always_filter_main_dttm table.is_sqllab_view = True table.sql = self._base_model.sql.strip().strip(";") db.session.add(table) cols = [] for config_ in self._base_model.columns: column_name = config_.column_name col = TableColumn( column_name=column_name, verbose_name=config_.verbose_name, expression=config_.expression, filterable=True, groupby=True, is_dttm=config_.is_dttm, type=config_.type, description=config_.description, ) cols.append(col) table.columns = cols mets = [] for config_ in self._base_model.metrics: metric_name = config_.metric_name met = SqlMetric( metric_name=metric_name, verbose_name=config_.verbose_name, expression=config_.expression, metric_type=config_.metric_type, description=config_.description, ) mets.append(met) table.metrics = mets return table def validate(self) -> None: exceptions: list[ValidationError] = [] base_model_id = self._properties["base_model_id"] duplicate_name = self._properties["table_name"] base_model = DatasetDAO.find_by_id(base_model_id) if not base_model: exceptions.append(DatasetNotFoundError()) else: self._base_model = base_model if self._base_model and self._base_model.kind != "virtual": exceptions.append(DatasourceTypeInvalidError()) if DatasetDAO.find_one_or_none(table_name=duplicate_name): exceptions.append(DatasetExistsValidationError(table=Table(duplicate_name))) try: owners = self.populate_owners() self._properties["owners"] = owners except ValidationError as ex: exceptions.append(ex) if exceptions: raise DatasetInvalidError(exceptions=exceptions)