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Migrates Superset's example data system from Python-based scripts to YAML configuration files, providing a cleaner, more maintainable approach to managing example datasets, charts, and dashboards. - Converted 9 Python example modules to YAML configurations - Exported existing examples from database and added as YAML files: - 11 dashboards (USA Births Names, World Bank's Data, etc.) - 115 charts - 25 datasets - Moved test-specific fixtures to `tests/fixtures/examples/` - Removed theme_id from dashboard exports for compatibility - **New command group**: `superset examples` with subcommands: - `load` - Load example data (replaces `load-examples`) - `clear-old` - Remove old Python-based examples - `clear` - Placeholder for future YAML clearing - `reload` - Clear and reload in one command - **Backwards compatibility**: `superset load-examples` still works with deprecation warning - **Safety mechanism**: Detects old examples and preserves them to avoid data loss - Fixed JSON data loading - examples can now load `.json.gz` files from CDN - Fixed Docker compose configuration for isolated development - Fixed webpack WebSocket configuration for different ports - Import operations now log what's being created vs updated: - "Creating new dashboard: Sales Dashboard" - "Updating existing chart: World's Population" - Provides clear visibility into the import process - Moved import logging to individual import functions (DRY principle) - Non-destructive migration approach - no user data is deleted - Deterministic UUID generation for consistent example data - Tested migration from old Python examples to new YAML format - Verified safety mechanism prevents accidental data overwrites - Confirmed backwards compatibility with deprecated command - All pre-commit checks pass - Updated installation docs to use new CLI commands - Added deprecation notice to UPDATING.md - Updated development documentation None - the old `load-examples` command continues to work with a deprecation warning. For users with existing Python-based examples: 1. Run `superset examples clear-old --confirm` to remove old examples 2. Run `superset examples load` to load new YAML-based examples
139 lines
5.0 KiB
Python
139 lines
5.0 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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"""Unit tests for Superset with caching"""
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import pytest
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from superset import app, db # noqa: F401
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from superset.common.db_query_status import QueryStatus
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from superset.connectors.sqla.models import SqlaTable
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from superset.extensions import cache_manager
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from tests.integration_tests.base_tests import SupersetTestCase
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from tests.integration_tests.constants import ADMIN_USERNAME
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from tests.integration_tests.fixtures.birth_names_dashboard import (
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load_birth_names_dashboard_with_slices, # noqa: F401
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load_birth_names_data, # noqa: F401
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)
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from tests.integration_tests.fixtures.query_context import get_query_context
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class TestCache(SupersetTestCase):
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def setUp(self):
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self.login(ADMIN_USERNAME)
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cache_manager.cache.clear()
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cache_manager.data_cache.clear()
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def tearDown(self):
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cache_manager.cache.clear()
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cache_manager.data_cache.clear()
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super().tearDown()
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@pytest.mark.usefixtures("load_birth_names_dashboard_with_slices")
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def test_no_data_cache(self):
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data_cache_config = app.config["DATA_CACHE_CONFIG"]
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app.config["DATA_CACHE_CONFIG"] = {"CACHE_TYPE": "NullCache"}
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cache_manager.init_app(app)
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slc = self.get_slice("Genders")
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# Get query context using the fixture
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query_context = get_query_context("birth_names")
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query_context["form_data"] = slc.form_data
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# Request chart for the first time
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resp = self.get_json_resp(
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"api/v1/chart/data",
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json_=query_context,
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)
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# Request chart for the second time
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resp_from_cache = self.get_json_resp(
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"api/v1/chart/data",
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json_=query_context,
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)
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# restore DATA_CACHE_CONFIG
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app.config["DATA_CACHE_CONFIG"] = data_cache_config
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assert resp.get("result")[0].get("cached_dttm") is None
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assert resp_from_cache.get("result")[0].get("cached_dttm") is None
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@pytest.mark.usefixtures("load_birth_names_dashboard_with_slices")
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def test_slice_data_cache(self):
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# Override cache config
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data_cache_config = app.config["DATA_CACHE_CONFIG"]
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cache_default_timeout = app.config["CACHE_DEFAULT_TIMEOUT"]
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app.config["CACHE_DEFAULT_TIMEOUT"] = 100
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app.config["DATA_CACHE_CONFIG"] = {
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"CACHE_TYPE": "SimpleCache",
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"CACHE_DEFAULT_TIMEOUT": 10,
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}
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cache_manager.init_app(app)
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slc = self.get_slice("Genders")
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# Clear the datasource cache timeout to test fallback to DATA_CACHE_CONFIG
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datasource = db.session.query(SqlaTable).filter_by(id=slc.datasource_id).one()
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original_cache_timeout = datasource.cache_timeout
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datasource.cache_timeout = None
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db.session.commit()
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# Get query context using the fixture
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query_context = get_query_context("birth_names")
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query_context["form_data"] = slc.form_data
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# Request chart for the first time
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resp = self.get_json_resp(
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"api/v1/chart/data",
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json_=query_context,
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)
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# Request chart for the second time
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resp_from_cache = self.get_json_resp(
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"api/v1/chart/data",
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json_=query_context,
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)
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result = resp.get("result")[0]
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cached_result = resp_from_cache.get("result")[0]
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assert result.get("cached_dttm") is None
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assert cached_result.get("cached_dttm") is not None
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# should fallback to default cache timeout
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assert cached_result["cache_timeout"] == 10
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assert cached_result["status"] == QueryStatus.SUCCESS
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assert result["data"] == cached_result["data"]
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assert result["query"] == cached_result["query"]
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# should exists in `data_cache`
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assert (
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cache_manager.data_cache.get(cached_result["cache_key"])["query"]
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== cached_result["query"]
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)
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# should not exists in `cache`
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assert cache_manager.cache.get(cached_result["cache_key"]) is None
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# reset datasource cache timeout
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datasource.cache_timeout = original_cache_timeout
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db.session.commit()
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# reset cache config
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app.config["DATA_CACHE_CONFIG"] = data_cache_config
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app.config["CACHE_DEFAULT_TIMEOUT"] = cache_default_timeout
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cache_manager.init_app(app)
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