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4e09889607
Co-authored-by: Superset Dev <dev@superset.apache.org> Co-authored-by: Claude Opus 4.7 <noreply@anthropic.com>
359 lines
10 KiB
Python
359 lines
10 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=import-outside-toplevel, unused-argument, unused-import
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from uuid import UUID
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import yaml
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from sqlalchemy.orm.session import Session
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from superset import db
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from superset.utils import json
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def test_export(session: Session) -> None:
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"""
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Test exporting a dataset.
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"""
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from superset.commands.dataset.export import ExportDatasetsCommand
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from superset.connectors.sqla.models import SqlaTable, SqlMetric, TableColumn
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from superset.models.core import Database
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engine = db.session.get_bind()
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SqlaTable.metadata.create_all(engine) # pylint: disable=no-member
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database = Database(database_name="my_database", sqlalchemy_uri="sqlite://")
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db.session.add(database)
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db.session.flush()
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columns = [
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TableColumn(column_name="ds", is_dttm=1, type="TIMESTAMP"),
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TableColumn(column_name="user_id", type="INTEGER"),
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TableColumn(column_name="revenue", type="INTEGER"),
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TableColumn(column_name="expenses", type="INTEGER"),
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TableColumn(
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column_name="profit",
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type="INTEGER",
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expression="revenue-expenses",
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extra=json.dumps({"certified_by": "User"}),
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uuid=UUID("00000000-0000-0000-0000-000000000005"),
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),
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]
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metrics = [
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SqlMetric(
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metric_name="cnt",
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expression="COUNT(*)",
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extra=json.dumps({"warning_markdown": None}),
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uuid=UUID("00000000-0000-0000-0000-000000000004"),
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),
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]
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sqla_table = SqlaTable(
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table_name="my_table",
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columns=columns,
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metrics=metrics,
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folders=[
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{
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"uuid": "00000000-0000-0000-0000-000000000000",
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"type": "folder",
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"name": "Engineering",
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"children": [
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{
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"uuid": "00000000-0000-0000-0000-000000000001",
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"type": "folder",
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"name": "Core",
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"children": [
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{
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"uuid": "00000000-0000-0000-0000-000000000004",
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"type": "metric",
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"name": "cnt",
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},
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],
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},
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],
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},
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{
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"uuid": "00000000-0000-0000-0000-000000000002",
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"type": "folder",
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"name": "Sales",
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"children": [
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{
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"uuid": "00000000-0000-0000-0000-000000000003",
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"type": "folder",
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"name": "Core",
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"children": [
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{
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"uuid": "00000000-0000-0000-0000-000000000005",
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"type": "column",
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"name": "profit",
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},
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],
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},
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],
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},
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],
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main_dttm_col="ds",
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database=database,
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offset=-8,
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description="This is the description",
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is_featured=1,
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cache_timeout=3600,
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catalog="public",
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schema="my_schema",
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sql=None,
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params=json.dumps(
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{
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"remote_id": 64,
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"database_name": "examples",
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"import_time": 1606677834,
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}
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),
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perm=None,
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filter_select_enabled=1,
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fetch_values_predicate="foo IN (1, 2)",
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is_sqllab_view=0, # no longer used?
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template_params=json.dumps({"answer": "42"}),
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schema_perm=None,
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normalize_columns=False,
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always_filter_main_dttm=False,
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extra=json.dumps({"warning_markdown": "*WARNING*"}),
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)
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# Add the table to the session and flush to get an ID
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db.session.add(sqla_table)
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db.session.flush()
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export = [
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(file[0], file[1]())
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for file in list(
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ExportDatasetsCommand._export(sqla_table) # pylint: disable=protected-access
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)
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]
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payload = sqla_table.export_to_dict(
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recursive=True,
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include_parent_ref=False,
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include_defaults=True,
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export_uuids=True,
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)
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assert export == [
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(
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f"datasets/my_database/my_table_{sqla_table.id}.yaml",
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f"""table_name: my_table
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main_dttm_col: ds
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currency_code_column: null
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description: This is the description
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default_endpoint: null
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offset: -8
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cache_timeout: 3600
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catalog: public
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schema: my_schema
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sql: null
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params:
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remote_id: 64
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database_name: examples
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import_time: 1606677834
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template_params:
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answer: '42'
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filter_select_enabled: 1
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fetch_values_predicate: foo IN (1, 2)
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extra:
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warning_markdown: '*WARNING*'
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normalize_columns: false
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always_filter_main_dttm: false
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folders:
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- uuid: 00000000-0000-0000-0000-000000000000
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type: folder
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name: Engineering
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children:
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- uuid: 00000000-0000-0000-0000-000000000001
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type: folder
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name: Core
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children:
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- uuid: 00000000-0000-0000-0000-000000000004
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type: metric
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name: cnt
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- uuid: 00000000-0000-0000-0000-000000000002
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type: folder
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name: Sales
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children:
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- uuid: 00000000-0000-0000-0000-000000000003
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type: folder
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name: Core
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children:
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- uuid: 00000000-0000-0000-0000-000000000005
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type: column
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name: profit
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uuid: {payload["uuid"]}
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metrics:
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- metric_name: cnt
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verbose_name: null
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metric_type: null
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expression: COUNT(*)
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description: null
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d3format: null
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currency: null
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extra:
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warning_markdown: null
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warning_text: null
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columns:
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- column_name: profit
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verbose_name: null
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is_dttm: false
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is_active: true
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type: INTEGER
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advanced_data_type: null
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groupby: true
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filterable: true
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expression: revenue-expenses
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description: null
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python_date_format: null
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datetime_format: null
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extra:
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certified_by: User
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- column_name: ds
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verbose_name: null
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is_dttm: 1
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is_active: true
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type: TIMESTAMP
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advanced_data_type: null
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groupby: true
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filterable: true
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expression: null
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description: null
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python_date_format: null
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datetime_format: null
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extra: null
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- column_name: user_id
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verbose_name: null
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is_dttm: false
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is_active: true
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type: INTEGER
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advanced_data_type: null
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groupby: true
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filterable: true
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expression: null
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description: null
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python_date_format: null
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datetime_format: null
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extra: null
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- column_name: expenses
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verbose_name: null
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is_dttm: false
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is_active: true
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type: INTEGER
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advanced_data_type: null
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groupby: true
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filterable: true
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expression: null
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description: null
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python_date_format: null
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datetime_format: null
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extra: null
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- column_name: revenue
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verbose_name: null
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is_dttm: false
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is_active: true
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type: INTEGER
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advanced_data_type: null
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groupby: true
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filterable: true
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expression: null
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description: null
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python_date_format: null
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datetime_format: null
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extra: null
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version: 1.0.0
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database_uuid: {database.uuid}
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""",
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),
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(
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"databases/my_database.yaml",
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f"""database_name: my_database
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sqlalchemy_uri: sqlite://
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cache_timeout: null
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expose_in_sqllab: true
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allow_run_async: false
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allow_ctas: false
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allow_cvas: false
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allow_dml: false
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allow_file_upload: false
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extra:
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metadata_params: {{}}
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engine_params: {{}}
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metadata_cache_timeout: {{}}
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schemas_allowed_for_file_upload: []
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impersonate_user: false
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configuration_method: sqlalchemy_form
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uuid: {database.uuid}
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version: 1.0.0
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""",
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),
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]
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def test_export_two_datasets_same_table_name_different_schema(
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session: Session,
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) -> None:
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"""
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Regression coverage for GitHub issue #16141.
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Exporting two datasets that share a `table_name` but live in
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different schemas (e.g. prod.users + dev.users) must produce two
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distinct entries in the export. Historically the pair could collide
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onto a single filename — the export filename is now disambiguated by
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dataset id, so this test pins that behavior so it can't silently
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regress.
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"""
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from superset.commands.dataset.export import ExportDatasetsCommand
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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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engine = db.session.get_bind()
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SqlaTable.metadata.create_all(engine) # pylint: disable=no-member
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database = Database(database_name="my_database", sqlalchemy_uri="sqlite://")
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db.session.add(database)
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db.session.flush()
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prod = SqlaTable(table_name="users", schema="prod", database=database)
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dev = SqlaTable(table_name="users", schema="dev", database=database)
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db.session.add_all([prod, dev])
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db.session.flush()
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paths: list[str] = []
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contents: list[str] = []
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for ds in (prod, dev):
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for path, content_fn in ExportDatasetsCommand._export( # pylint: disable=protected-access
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ds, export_related=False
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):
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paths.append(path)
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contents.append(content_fn())
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# Both datasets must produce distinct export paths — no collision.
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assert len(paths) == len(set(paths)), (
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f"Export filenames collided for same-table-name datasets: {paths}"
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)
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# And both YAML payloads must reflect their own schema, not be
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# silently merged or overwritten.
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schemas_in_yaml = {yaml.safe_load(c)["schema"] for c in contents}
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assert schemas_in_yaml == {"prod", "dev"}, (
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f"Expected both prod and dev schemas in export, got {schemas_in_yaml}"
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)
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