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288 lines
9.0 KiB
Python
288 lines
9.0 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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# pylint: disable=line-too-long, import-outside-toplevel, protected-access, invalid-name
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import json
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from pytest_mock import MockFixture
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from sqlalchemy import select
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from sqlalchemy.sql import sqltypes
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from sqlalchemy_bigquery import BigQueryDialect
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def test_get_fields() -> None:
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"""
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Test the custom ``_get_fields`` method.
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The method adds custom labels (aliases) to the columns to prevent
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collision when referencing record fields. Eg, if we had these two
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columns:
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name STRING
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project STRUCT<name STRING>
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One could write this query:
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SELECT
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`name`,
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`project`.`name`
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FROM
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the_table
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But then both columns would get aliased as "name".
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The custom method will replace the fields so that the final query
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looks like this:
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SELECT
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`name` AS `name`,
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`project`.`name` AS project__name
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FROM
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the_table
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"""
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from superset.db_engine_specs.bigquery import BigQueryEngineSpec
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columns = [{"name": "limit"}, {"name": "name"}, {"name": "project.name"}]
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fields = BigQueryEngineSpec._get_fields(columns)
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query = select(fields)
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assert str(query.compile(dialect=BigQueryDialect())) == (
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"SELECT `limit` AS `limit`, `name` AS `name`, "
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"`project`.`name` AS `project__name`"
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)
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def test_select_star(mocker: MockFixture) -> None:
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"""
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Test the ``select_star`` method.
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The method removes pseudo-columns from structures inside arrays. While these
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pseudo-columns show up as "columns" for metadata reasons, we can't select them
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in the query, as opposed to fields from non-array structures.
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"""
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from superset.db_engine_specs.bigquery import BigQueryEngineSpec
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cols = [
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{
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"name": "trailer",
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"type": sqltypes.ARRAY(sqltypes.JSON()),
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"nullable": True,
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"comment": None,
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"default": None,
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"precision": None,
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"scale": None,
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"max_length": None,
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},
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{
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"name": "trailer.key",
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"type": sqltypes.String(),
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"nullable": True,
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"comment": None,
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"default": None,
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"precision": None,
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"scale": None,
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"max_length": None,
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},
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{
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"name": "trailer.value",
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"type": sqltypes.String(),
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"nullable": True,
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"comment": None,
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"default": None,
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"precision": None,
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"scale": None,
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"max_length": None,
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},
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{
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"name": "trailer.email",
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"type": sqltypes.String(),
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"nullable": True,
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"comment": None,
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"default": None,
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"precision": None,
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"scale": None,
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"max_length": None,
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},
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]
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# mock the database so we can compile the query
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database = mocker.MagicMock()
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database.compile_sqla_query = lambda query: str(
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query.compile(dialect=BigQueryDialect())
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)
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engine = mocker.MagicMock()
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engine.dialect = BigQueryDialect()
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sql = BigQueryEngineSpec.select_star(
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database=database,
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table_name="my_table",
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engine=engine,
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schema=None,
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limit=100,
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show_cols=True,
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indent=True,
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latest_partition=False,
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cols=cols,
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)
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assert (
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sql
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== """SELECT `trailer` AS `trailer`
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FROM `my_table`
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LIMIT :param_1"""
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)
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def test_get_parameters_from_uri_serializable() -> None:
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"""
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Test that the result from ``get_parameters_from_uri`` is JSON serializable.
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"""
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from superset.db_engine_specs.bigquery import BigQueryEngineSpec
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parameters = BigQueryEngineSpec.get_parameters_from_uri(
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"bigquery://dbt-tutorial-347100/",
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{"access_token": "TOP_SECRET"},
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)
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assert parameters == {"access_token": "TOP_SECRET", "query": {}}
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assert json.loads(json.dumps(parameters)) == parameters
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def test_unmask_encrypted_extra() -> None:
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"""
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Test that the private key can be reused from the previous ``encrypted_extra``.
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"""
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from superset.db_engine_specs.bigquery import BigQueryEngineSpec
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old = json.dumps(
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{
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"credentials_info": {
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"project_id": "black-sanctum-314419",
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"private_key": "SECRET",
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},
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}
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)
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new = json.dumps(
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{
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"credentials_info": {
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"project_id": "yellow-unicorn-314419",
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"private_key": "XXXXXXXXXX",
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},
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}
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)
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assert json.loads(str(BigQueryEngineSpec.unmask_encrypted_extra(old, new))) == {
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"credentials_info": {
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"project_id": "yellow-unicorn-314419",
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"private_key": "SECRET",
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},
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}
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def test_unmask_encrypted_extra_when_empty() -> None:
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"""
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Test that a None value works for ``encrypted_extra``.
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"""
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from superset.db_engine_specs.bigquery import BigQueryEngineSpec
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old = None
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new = json.dumps(
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{
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"credentials_info": {
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"project_id": "yellow-unicorn-314419",
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"private_key": "XXXXXXXXXX",
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},
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}
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)
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assert json.loads(str(BigQueryEngineSpec.unmask_encrypted_extra(old, new))) == {
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"credentials_info": {
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"project_id": "yellow-unicorn-314419",
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"private_key": "XXXXXXXXXX",
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},
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}
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def test_unmask_encrypted_extra_when_new_is_empty() -> None:
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"""
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Test that a None value works for ``encrypted_extra``.
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"""
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from superset.db_engine_specs.bigquery import BigQueryEngineSpec
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old = json.dumps(
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{
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"credentials_info": {
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"project_id": "black-sanctum-314419",
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"private_key": "SECRET",
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},
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}
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)
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new = None
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assert BigQueryEngineSpec.unmask_encrypted_extra(old, new) is None
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def test_mask_encrypted_extra_when_empty() -> None:
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"""
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Test that the encrypted extra will return a none value if the field is empty.
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"""
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from superset.db_engine_specs.bigquery import BigQueryEngineSpec
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assert BigQueryEngineSpec.mask_encrypted_extra(None) is None
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def test_parse_error_message() -> None:
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"""
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Test that we parse a received message and just extract the useful information.
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Example errors:
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bigquery error: 400 Syntax error: Table \"case_detail_all_suites\" must be qualified with a dataset (e.g. dataset.table).
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(job ID: ddf30b05-44e8-4fbf-aa29-40bfccaed886)
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-----Query Job SQL Follows-----
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| . | . | . |\n 1:select * from case_detail_all_suites\n 2:LIMIT 1001\n | . | . | . |
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"""
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from superset.db_engine_specs.bigquery import BigQueryEngineSpec
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message = 'bigquery error: 400 Syntax error: Table "case_detail_all_suites" must be qualified with a dataset (e.g. dataset.table).\n\n(job ID: ddf30b05-44e8-4fbf-aa29-40bfccaed886)\n\n -----Query Job SQL Follows----- \n\n | . | . | . |\n 1:select * from case_detail_all_suites\n 2:LIMIT 1001\n | . | . | . |'
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expected_result = 'bigquery error: 400 Syntax error: Table "case_detail_all_suites" must be qualified with a dataset (e.g. dataset.table).'
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assert (
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str(BigQueryEngineSpec.parse_error_exception(Exception(message)))
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== expected_result
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)
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def test_parse_error_raises_exception() -> None:
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"""
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Test that we handle any exception we might get from calling the parse_error_exception method.
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Example errors:
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400 Syntax error: Expected "(" or keyword UNNEST but got "@" at [4:80]
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bigquery error: 400 Table \"case_detail_all_suites\" must be qualified with a dataset (e.g. dataset.table).
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"""
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from superset.db_engine_specs.bigquery import BigQueryEngineSpec
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message = 'bigquery error: 400 Syntax error: Table "case_detail_all_suites" must be qualified with a dataset (e.g. dataset.table).'
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message_2 = "6"
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expected_result = 'bigquery error: 400 Syntax error: Table "case_detail_all_suites" must be qualified with a dataset (e.g. dataset.table).'
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assert (
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str(BigQueryEngineSpec.parse_error_exception(Exception(message)))
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== expected_result
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)
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assert str(BigQueryEngineSpec.parse_error_exception(Exception(message_2))) == "6"
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