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179 lines
5.3 KiB
Python
179 lines
5.3 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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import copy
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from datetime import datetime
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from typing import Any
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from unittest.mock import MagicMock, patch
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import pytest
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from freezegun import freeze_time
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from sqlalchemy.orm.session import Session
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from superset.daos.base import BaseDAO
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from superset.daos.dataset import DatasetDAO
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from superset.sql.parse import Table
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def test_validate_update_uniqueness(session: Session) -> None:
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"""
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Test the `validate_update_uniqueness` static method.
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In particular, allow datasets with the same name in the same database as long as they
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are in different schemas
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""" # noqa: E501
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from superset import db
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from superset.connectors.sqla.models import SqlaTable
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from superset.models.core import Database
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SqlaTable.metadata.create_all(session.get_bind())
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database = Database(
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database_name="my_db",
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sqlalchemy_uri="sqlite://",
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)
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dataset1 = SqlaTable(
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table_name="my_dataset",
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schema="main",
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database=database,
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)
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dataset2 = SqlaTable(
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table_name="my_dataset",
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schema="dev",
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database=database,
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)
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db.session.add_all([database, dataset1, dataset2])
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db.session.flush()
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assert (
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DatasetDAO.validate_update_uniqueness(
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database=database,
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table=Table(dataset1.table_name, dataset1.schema),
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dataset_id=dataset1.id,
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)
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is True
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)
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assert (
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DatasetDAO.validate_update_uniqueness(
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database=database,
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table=Table(dataset1.table_name, dataset2.schema),
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dataset_id=dataset1.id,
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)
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is False
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)
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assert (
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DatasetDAO.validate_update_uniqueness(
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database=database,
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table=Table(dataset1.table_name),
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dataset_id=dataset1.id,
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)
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is True
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)
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@freeze_time("2025-01-01 00:00:00")
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@patch.object(DatasetDAO, "update_columns")
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@patch.object(DatasetDAO, "update_metrics")
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@patch.object(BaseDAO, "update")
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@pytest.mark.parametrize(
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"attributes,expected_attributes",
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[
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(
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{
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"columns": [{"id": 1, "name": "col1"}],
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"metrics": [{"id": 1, "name": "metric1"}],
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},
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{"changed_on": datetime(2025, 1, 1, 0, 0, 0)},
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),
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(
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{
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"columns": [{"id": 1, "name": "col1"}],
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"metrics": [{"id": 1, "name": "metric1"}],
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"description": "test description",
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},
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{
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"description": "test description",
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"changed_on": datetime(2025, 1, 1, 0, 0, 0),
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},
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),
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(
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{
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"columns": [{"id": 1, "name": "col1"}],
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},
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{"changed_on": datetime(2025, 1, 1, 0, 0, 0)},
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),
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(
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{
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"columns": [{"id": 1, "name": "col1"}],
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"description": "test description",
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},
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{
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"description": "test description",
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"changed_on": datetime(2025, 1, 1, 0, 0, 0),
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},
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),
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(
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{
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"metrics": [{"id": 1, "name": "metric1"}],
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},
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{"changed_on": datetime(2025, 1, 1, 0, 0, 0)},
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),
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(
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{
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"metrics": [{"id": 1, "name": "metric1"}],
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"description": "test description",
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},
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{
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"description": "test description",
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"changed_on": datetime(2025, 1, 1, 0, 0, 0),
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},
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),
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(
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{"description": "test description"},
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{"description": "test description"},
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),
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],
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)
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def test_update_dataset_related_metadata_updates_changed_on(
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base_update_mock: MagicMock,
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update_metrics_mock: MagicMock,
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update_columns_mock: MagicMock,
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attributes: dict[str, Any],
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expected_attributes: dict[str, Any],
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) -> None:
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"""
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Test that the changed_on property is updated when a metric or column is updated.
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"""
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item = MagicMock()
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DatasetDAO.update(item, copy.deepcopy(attributes))
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if "columns" in attributes:
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update_columns_mock.assert_called_once_with(
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item, attributes["columns"], override_columns=False
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)
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else:
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update_columns_mock.assert_not_called()
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if "metrics" in attributes:
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update_metrics_mock.assert_called_once_with(item, attributes["metrics"])
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else:
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update_metrics_mock.assert_not_called()
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base_update_mock.assert_called_once_with(item, expected_attributes)
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