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Posted to commits@superset.apache.org by ru...@apache.org on 2026/07/03 15:43:51 UTC
(superset) branch legacy-viz-phase2-removal created (now 01ab3dd078b)
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rusackas pushed a change to branch legacy-viz-phase2-removal
in repository https://gitbox.apache.org/repos/asf/superset.git
at 01ab3dd078b chore(viz)!: remove explore_json endpoints, viz.py and the legacy chart data pipeline
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new 01ab3dd078b chore(viz)!: remove explore_json endpoints, viz.py and the legacy chart data pipeline
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(superset) 01/01: chore(viz)!: remove explore_json endpoints, viz.py and the legacy chart data pipeline
Posted by ru...@apache.org.
This is an automated email from the ASF dual-hosted git repository.
rusackas pushed a commit to branch legacy-viz-phase2-removal
in repository https://gitbox.apache.org/repos/asf/superset.git
commit 01ab3dd078b9286db8c8f2d4021f6671c33961c4
Author: Claude Code <no...@anthropic.com>
AuthorDate: Fri Jul 3 08:41:59 2026 -0700
chore(viz)!: remove explore_json endpoints, viz.py and the legacy chart data pipeline
With every legacy chart migrated to /api/v1/chart/data, this removes
the deprecated pipeline at its declared 5.0.0 EOL:
Backend:
- /superset/explore_json/ and /superset/explore_json/data/<cache_key>
routes plus their viz-only helpers (generate_json, CSV/XLSX/query/
results/samples responses) and the CSRF exemption
- superset/viz.py and all remaining importers: the get_viz factory and
explore-cache permission checkers in views/utils, the Slice.viz
property and explore_json_url, the legacy warm-up-cache path, the
legacy annotation-data path in the query context processor, and the
BaseViz overload of security_manager.raise_for_access
- the load_explore_json_into_cache celery task and the async query
manager's explore_json job plumbing
- the can_explore_json permission grant for the public role and the
legacy-prefix redirect entries for the removed routes
Frontend:
- the useLegacyApi flag on ChartMetadata and every branch keyed on it:
chartAction's legacy request/response handling, exportChart's legacy
endpoint, ChartClient and StatefulChart explore_json endpoints,
DrillBy legacy handling, and the explore panel's dataset-required
alert for legacy charts on non-table datasources
- getURIDirectory now always resolves to /explore/ and the legacy
endpoint-type helpers are gone
Tests covering the removed pipeline are removed or retargeted; the
LegacyPrefixRedirectMiddleware itself remains for the other legacy
prefixes.
Co-Authored-By: Claude Fable 5 <no...@anthropic.com>
---
.../src/chart/clients/ChartClient.ts | 23 +-
.../src/chart/components/StatefulChart.test.tsx | 4 +-
.../src/chart/components/StatefulChart.tsx | 30 +-
.../src/chart/models/ChartMetadata.ts | 5 -
.../test/chart/clients/ChartClient.test.ts | 36 -
.../src/vendor/superset/exploreUtils.ts | 69 -
.../preset-chart-deckgl/src/utils/explore.ts | 68 -
.../src/components/Chart/ChartRenderer.test.tsx | 1 -
.../src/components/Chart/DrillBy/DrillByModal.tsx | 13 +-
.../Chart/DrillBy/DrillBySubmenu.test.tsx | 1 -
.../src/components/Chart/chartAction.ts | 89 +-
.../src/components/Chart/chartActions.test.ts | 222 +-
.../ExploreChartPanel/ExploreChartPanel.test.tsx | 1 -
.../explore/components/ExploreChartPanel/index.tsx | 48 -
.../ExploreViewContainer.test.tsx | 2 -
.../src/explore/exploreUtils/exploreUtils.test.tsx | 57 +-
.../src/explore/exploreUtils/exportChart.test.ts | 133 -
.../src/explore/exploreUtils/getExploreUrl.test.ts | 28 +-
.../exploreUtils/getLegacyEndpointType.test.ts | 40 -
.../explore/exploreUtils/getURIDirectory.test.ts | 14 +-
.../src/explore/exploreUtils/index.ts | 77 +-
.../exploreUtils/shouldUseLegacyApi.test.ts | 59 -
superset/async_events/async_query_manager.py | 30 +-
superset/charts/api.py | 2 +-
superset/commands/chart/warm_up_cache.py | 33 +-
superset/common/query_context_processor.py | 25 -
superset/config.py | 1 -
superset/datasets/api.py | 2 +-
superset/mcp_service/utils/permissions_utils.py | 2 +-
superset/middleware/legacy_prefix_redirect.py | 4 +-
superset/models/slice.py | 18 +-
superset/security/manager.py | 9 +-
superset/tasks/async_queries.py | 81 +-
superset/views/core.py | 258 +-
superset/views/utils.py | 103 +-
superset/viz.py | 2742 --------------------
tests/integration_tests/core_tests.py | 103 +-
tests/integration_tests/security_tests.py | 22 +-
.../integration_tests/tasks/async_queries_tests.py | 118 -
tests/integration_tests/utils_tests.py | 33 +-
tests/integration_tests/viz_tests.py | 2453 -----------------
.../async_events/async_query_manager_tests.py | 51 -
.../commands/chart/warm_up_cache_test.py | 342 +--
.../middleware/test_legacy_prefix_redirect.py | 8 -
tests/unit_tests/tasks/test_async_queries.py | 169 --
tests/unit_tests/test_subdirectory_url_for.py | 13 -
tests/unit_tests/test_viz_cache_key.py | 111 -
tests/unit_tests/test_viz_get_df_payload.py | 244 --
48 files changed, 172 insertions(+), 7825 deletions(-)
diff --git a/superset-frontend/packages/superset-ui-core/src/chart/clients/ChartClient.ts b/superset-frontend/packages/superset-ui-core/src/chart/clients/ChartClient.ts
index 397a854a2a5..52c8d76c6e4 100644
--- a/superset-frontend/packages/superset-ui-core/src/chart/clients/ChartClient.ts
+++ b/superset-frontend/packages/superset-ui-core/src/chart/clients/ChartClient.ts
@@ -104,24 +104,15 @@ export default class ChartClient {
const buildQueryRegistry = getChartBuildQueryRegistry();
if (metaDataRegistry.has(visType)) {
- const { useLegacyApi } = metaDataRegistry.get(visType)!;
const buildQuery =
(await buildQueryRegistry.get(visType)) ?? (() => formData);
- const requestConfig: RequestConfig = useLegacyApi
- ? {
- endpoint: '/explore_json/',
- postPayload: {
- form_data: buildQuery(formData),
- },
- ...options,
- }
- : {
- endpoint: '/api/v1/chart/data',
- jsonPayload: {
- query_context: buildQuery(formData),
- },
- ...options,
- };
+ const requestConfig: RequestConfig = {
+ endpoint: '/api/v1/chart/data',
+ jsonPayload: {
+ query_context: buildQuery(formData),
+ },
+ ...options,
+ };
return this.client
.post(requestConfig)
diff --git a/superset-frontend/packages/superset-ui-core/src/chart/components/StatefulChart.test.tsx b/superset-frontend/packages/superset-ui-core/src/chart/components/StatefulChart.test.tsx
index 3d73326b45e..8cb4c2b2f25 100644
--- a/superset-frontend/packages/superset-ui-core/src/chart/components/StatefulChart.test.tsx
+++ b/superset-frontend/packages/superset-ui-core/src/chart/components/StatefulChart.test.tsx
@@ -68,9 +68,7 @@ beforeEach(() => {
// Setup default registry mocks
(getChartMetadataRegistry as any).mockReturnValue({
- get: jest.fn().mockReturnValue({
- useLegacyApi: false,
- }),
+ get: jest.fn().mockReturnValue({}),
});
(getChartBuildQueryRegistry as any).mockReturnValue({
diff --git a/superset-frontend/packages/superset-ui-core/src/chart/components/StatefulChart.tsx b/superset-frontend/packages/superset-ui-core/src/chart/components/StatefulChart.tsx
index baae1ae2ce4..9e77e75c33d 100644
--- a/superset-frontend/packages/superset-ui-core/src/chart/components/StatefulChart.tsx
+++ b/superset-frontend/packages/superset-ui-core/src/chart/components/StatefulChart.tsx
@@ -245,9 +245,6 @@ export default function StatefulChart(props: StatefulChartProps) {
}
finalFormData.viz_type = vizType;
- // Get chart metadata
- const { useLegacyApi } = getChartMetadataRegistry().get(vizType) || {};
-
// Build query using the chart's buildQuery function
const buildQuery = await getChartBuildQueryRegistry().get(vizType);
let queryContext;
@@ -259,39 +256,28 @@ export default function StatefulChart(props: StatefulChartProps) {
queryContext = buildQueryContext(finalFormData);
}
- // Ensure query_context is properly formatted for new API
- if (!useLegacyApi && !queryContext.queries) {
+ // Ensure query_context is properly formatted for the API
+ if (!queryContext.queries) {
queryContext = { queries: [queryContext] };
}
- const endpoint = useLegacyApi ? '/explore_json/' : '/api/v1/chart/data';
const requestConfig: RequestConfig = {
- endpoint,
+ endpoint: '/api/v1/chart/data',
signal: abortControllerRef.current.signal,
...(timeout && { timeout: timeout * 1000 }),
- };
-
- if (useLegacyApi) {
- requestConfig.postPayload = {
- form_data: {
- ...finalFormData,
- ...(force && { force: true }),
- },
- };
- } else {
- requestConfig.jsonPayload = {
+ jsonPayload: {
...queryContext,
...(force && { force: true }),
- };
- }
+ },
+ };
const response = await chartClientRef.current!.client.post(requestConfig);
let responseData = Array.isArray(response.json)
? response.json
: [response.json];
- // Handle the nested result structure from the new API
- if (!useLegacyApi && responseData[0]?.result) {
+ // Handle the nested result structure from the API
+ if (responseData[0]?.result) {
responseData = responseData[0].result;
}
diff --git a/superset-frontend/packages/superset-ui-core/src/chart/models/ChartMetadata.ts b/superset-frontend/packages/superset-ui-core/src/chart/models/ChartMetadata.ts
index 3b5073f02b3..f8bd22d4fb2 100644
--- a/superset-frontend/packages/superset-ui-core/src/chart/models/ChartMetadata.ts
+++ b/superset-frontend/packages/superset-ui-core/src/chart/models/ChartMetadata.ts
@@ -40,7 +40,6 @@ export interface ChartMetadataConfig {
supportedAnnotationTypes?: string[];
thumbnail: string;
thumbnailDark?: string;
- useLegacyApi?: boolean;
behaviors?: Behavior[];
exampleGallery?: ExampleImage[];
tags?: string[];
@@ -75,8 +74,6 @@ export default class ChartMetadata {
thumbnailDark?: string;
- useLegacyApi: boolean;
-
behaviors: Behavior[];
datasourceCount: number;
@@ -112,7 +109,6 @@ export default class ChartMetadata {
supportedAnnotationTypes = [],
thumbnail,
thumbnailDark,
- useLegacyApi = false,
behaviors = [],
datasourceCount = 1,
enableNoResults = true,
@@ -144,7 +140,6 @@ export default class ChartMetadata {
this.supportedAnnotationTypes = supportedAnnotationTypes;
this.thumbnail = thumbnail;
this.thumbnailDark = thumbnailDark;
- this.useLegacyApi = useLegacyApi;
this.behaviors = behaviors;
this.datasourceCount = datasourceCount;
this.enableNoResults = enableNoResults;
diff --git a/superset-frontend/packages/superset-ui-core/test/chart/clients/ChartClient.test.ts b/superset-frontend/packages/superset-ui-core/test/chart/clients/ChartClient.test.ts
index 8d11b98d175..6ec2ef0f487 100644
--- a/superset-frontend/packages/superset-ui-core/test/chart/clients/ChartClient.test.ts
+++ b/superset-frontend/packages/superset-ui-core/test/chart/clients/ChartClient.test.ts
@@ -160,42 +160,6 @@ describe('ChartClient', () => {
datasource: '1__table',
}),
).rejects.toEqual(new Error('Unknown chart type: rainbow_3d_pie')));
-
- test('fetches data from the legacy API if ChartMetadata has useLegacyApi=true,', () => {
- // note legacy charts do not register a buildQuery function in the registry
- getChartMetadataRegistry().registerValue(
- 'word_cloud_legacy',
- new ChartMetadata({
- name: 'Legacy Word Cloud',
- thumbnail: '.png',
- useLegacyApi: true,
- }),
- );
-
- fetchMock.post('glob:*/api/v1/chart/data', () =>
- Promise.reject(new Error('Unexpected all to v1 API')),
- );
-
- // post `Superset.route_base = ""`, the legacy endpoint
- // collapsed from `/superset/explore_json/` to `/explore_json/`.
- fetchMock.post('glob:*/explore_json/', {
- field1: 'abc',
- field2: 'def',
- });
-
- return expect(
- chartClient.loadQueryData({
- granularity: 'minute',
- viz_type: 'word_cloud_legacy',
- datasource: '1__table',
- }),
- ).resolves.toEqual([
- {
- field1: 'abc',
- field2: 'def',
- },
- ]);
- });
});
describe('.loadDatasource(datasourceKey, options)', () => {
diff --git a/superset-frontend/plugins/legacy-preset-chart-nvd3/src/vendor/superset/exploreUtils.ts b/superset-frontend/plugins/legacy-preset-chart-nvd3/src/vendor/superset/exploreUtils.ts
deleted file mode 100644
index 098b3a73f2e..00000000000
--- a/superset-frontend/plugins/legacy-preset-chart-nvd3/src/vendor/superset/exploreUtils.ts
+++ /dev/null
@@ -1,69 +0,0 @@
-/**
- * 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.
- */
-// @ts-nocheck -- vendor file; not fully typed
-/* eslint camelcase: 0 */
-import URI from 'urijs';
-import safeStringify from 'fast-safe-stringify';
-
-const MAX_URL_LENGTH = 8000;
-
-export function getURIDirectory(formData, endpointType = 'base') {
- // Building the directory part of the URI
- let directory = '/explore/';
- if (['json', 'csv', 'query', 'results', 'samples'].includes(endpointType)) {
- directory = '/superset/explore_json/';
- }
-
- return directory;
-}
-
-export function getExploreLongUrl(
- formData,
- endpointType,
- allowOverflow = true,
- extraSearch = {},
-) {
- if (!formData.datasource) {
- return null;
- }
-
- const uri = new URI('/');
- const directory = getURIDirectory(formData, endpointType);
- const search = uri.search(true);
- Object.keys(extraSearch).forEach(key => {
- search[key] = extraSearch[key];
- });
- search.form_data = safeStringify(formData);
- if (endpointType === 'standalone') {
- search.standalone = 'true';
- }
- const url = uri.directory(directory).search(search).toString();
- if (!allowOverflow && url.length > MAX_URL_LENGTH) {
- const minimalFormData = {
- datasource: formData.datasource,
- viz_type: formData.viz_type,
- };
-
- return getExploreLongUrl(minimalFormData, endpointType, false, {
- URL_IS_TOO_LONG_TO_SHARE: null,
- });
- }
-
- return url;
-}
diff --git a/superset-frontend/plugins/preset-chart-deckgl/src/utils/explore.ts b/superset-frontend/plugins/preset-chart-deckgl/src/utils/explore.ts
deleted file mode 100644
index 8b8ad24aabe..00000000000
--- a/superset-frontend/plugins/preset-chart-deckgl/src/utils/explore.ts
+++ /dev/null
@@ -1,68 +0,0 @@
-/**
- * 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 URI from 'urijs';
-import { JsonObject } from '@superset-ui/core';
-import { safeStringify } from './safeStringify';
-
-const MAX_URL_LENGTH = 8000;
-
-export function getURIDirectory(endpointType = 'base') {
- // Building the directory part of the URI
- let directory = '/explore/';
- if (['json', 'csv', 'query', 'results', 'samples'].includes(endpointType)) {
- directory = '/superset/explore_json/';
- }
-
- return directory;
-}
-
-export function getExploreLongUrl(
- formData: JsonObject,
- endpointType: string,
- allowOverflow = true,
- extraSearch: Record<string, any> = {},
-): string | undefined {
- if (!formData.datasource) {
- return undefined;
- }
-
- const uri = new URI('/');
- const directory = getURIDirectory(endpointType);
- const search = uri.search(true);
- Object.keys(extraSearch).forEach(key => {
- search[key] = extraSearch[key];
- });
- search.form_data = safeStringify(formData);
- if (endpointType === 'standalone') {
- search.standalone = 'true';
- }
- const url = uri.directory(directory).search(search).toString();
- if (!allowOverflow && url.length > MAX_URL_LENGTH) {
- const minimalFormData = {
- datasource: formData.datasource,
- viz_type: formData.viz_type,
- };
-
- return getExploreLongUrl(minimalFormData, endpointType, false, {
- URL_IS_TOO_LONG_TO_SHARE: null,
- });
- }
-
- return url;
-}
diff --git a/superset-frontend/src/components/Chart/ChartRenderer.test.tsx b/superset-frontend/src/components/Chart/ChartRenderer.test.tsx
index 92a2b8c52db..672a3995c7b 100644
--- a/superset-frontend/src/components/Chart/ChartRenderer.test.tsx
+++ b/superset-frontend/src/components/Chart/ChartRenderer.test.tsx
@@ -138,7 +138,6 @@ test('should not render chart context menu if the context menu is suppressed for
new ChartMetadata({
name: 'chart with suppressed context menu',
thumbnail: '.png',
- useLegacyApi: false,
suppressContextMenu: true,
}),
);
diff --git a/superset-frontend/src/components/Chart/DrillBy/DrillByModal.tsx b/superset-frontend/src/components/Chart/DrillBy/DrillByModal.tsx
index 57149ee55e0..89773d23f4f 100644
--- a/superset-frontend/src/components/Chart/DrillBy/DrillByModal.tsx
+++ b/superset-frontend/src/components/Chart/DrillBy/DrillByModal.tsx
@@ -54,7 +54,7 @@ import {
LOG_ACTIONS_FURTHER_DRILL_BY,
} from 'src/logger/LogUtils';
import { findPermission } from 'src/utils/findPermission';
-import { getQuerySettings, exportChart } from 'src/explore/exploreUtils';
+import { exportChart } from 'src/explore/exploreUtils';
import { isEmbedded } from 'src/dashboard/util/isEmbedded';
import { Dataset, DrillByType } from '../types';
import DrillByChart from './DrillByChart';
@@ -401,13 +401,11 @@ export default function DrillByModal({
const handleReload = useCallback(() => {
setChartDataResult(undefined);
setIsChartDataLoading(true);
- const [useLegacyApi] = getQuerySettings(drilledFormData);
+
getChartDataRequest({
formData: drilledFormData,
})
- .then(({ response, json }) =>
- handleChartDataResponse(response, json, useLegacyApi),
- )
+ .then(({ response, json }) => handleChartDataResponse(response, json))
.then(queriesResponse => {
setChartDataResult(queriesResponse);
})
@@ -491,15 +489,12 @@ export default function DrillByModal({
useEffect(() => {
if (drilledFormData) {
- const [useLegacyApi] = getQuerySettings(drilledFormData);
setIsChartDataLoading(true);
setChartDataResult(undefined);
getChartDataRequest({
formData: drilledFormData,
})
- .then(({ response, json }) =>
- handleChartDataResponse(response, json, useLegacyApi),
- )
+ .then(({ response, json }) => handleChartDataResponse(response, json))
.then(queriesResponse => {
setChartDataResult(queriesResponse);
})
diff --git a/superset-frontend/src/components/Chart/DrillBy/DrillBySubmenu.test.tsx b/superset-frontend/src/components/Chart/DrillBy/DrillBySubmenu.test.tsx
index 4da5b103ad0..d36ab01e29a 100644
--- a/superset-frontend/src/components/Chart/DrillBy/DrillBySubmenu.test.tsx
+++ b/superset-frontend/src/components/Chart/DrillBy/DrillBySubmenu.test.tsx
@@ -129,7 +129,6 @@ getChartMetadataRegistry().registerValue(
new ChartMetadata({
name: 'fake pie',
thumbnail: '.png',
- useLegacyApi: false,
behaviors: [Behavior.DrillBy],
}),
);
diff --git a/superset-frontend/src/components/Chart/chartAction.ts b/superset-frontend/src/components/Chart/chartAction.ts
index 65b94f231b0..b7b260f1e5c 100644
--- a/superset-frontend/src/components/Chart/chartAction.ts
+++ b/superset-frontend/src/components/Chart/chartAction.ts
@@ -36,8 +36,6 @@ import type { ControlStateMapping } from '@superset-ui/chart-controls';
import { getControlsState } from 'src/explore/store';
import {
getAnnotationJsonUrl,
- getExploreUrl,
- getLegacyEndpointType,
buildV1ChartDataPayload,
getQuerySettings,
getChartDataUri,
@@ -405,51 +403,6 @@ export const dynamicPluginControlsReady =
});
};
-const legacyChartDataRequest = async (
- formData: QueryFormData | LatestQueryFormData,
- resultFormat: string,
- resultType: string,
- force: boolean,
- method: 'GET' | 'POST' = 'POST',
- requestParams: RequestParams = {},
- parseMethod?: string,
-): Promise<ChartDataRequestResponse> => {
- const endpointType = getLegacyEndpointType({ resultFormat, resultType });
- const allowDomainSharding = Boolean(
- // eslint-disable-next-line camelcase
- domainShardingEnabled && requestParams?.dashboard_id,
- );
- const url = getExploreUrl({
- formData: formData as QueryFormData & {
- label_colors?: Record<string, string>;
- },
- endpointType,
- force,
- allowDomainSharding,
- method,
- requestParams: requestParams.dashboard_id
- ? { dashboard_id: String(requestParams.dashboard_id) }
- : {},
- });
- const querySettings: QuerySettings = {
- ...requestParams,
- url: url ?? undefined,
- postPayload: { form_data: formData },
- parseMethod,
- };
-
- return SupersetClient.post(
- querySettings as Parameters<typeof SupersetClient.post>[0],
- ).then(({ json, response }: { json: JsonObject; response: Response }) =>
- // Make the legacy endpoint return a payload that corresponds to the
- // V1 chart data endpoint response signature.
- ({
- response,
- json: { result: [json] },
- }),
- );
-};
-
const v1ChartDataRequest = async (
formData: QueryFormData | LatestQueryFormData,
resultFormat: string,
@@ -522,18 +475,7 @@ export async function getChartDataRequest({
credentials: 'include',
};
}
- const [useLegacyApi, parseMethod] = getQuerySettings(formData);
- if (useLegacyApi) {
- return legacyChartDataRequest(
- formData,
- resultFormat,
- resultType,
- force,
- method,
- querySettings,
- parseMethod,
- );
- }
+ const [parseMethod] = getQuerySettings(formData);
return v1ChartDataRequest(
formData,
resultFormat,
@@ -698,7 +640,6 @@ export function addChart(
export function handleChartDataResponse(
response: Response,
json: { result: QueryData[] },
- useLegacyApi?: boolean,
): Promise<QueryData[]> | QueryData[] {
if (isFeatureEnabled(FeatureFlag.GlobalAsyncQueries)) {
// deal with getChartDataRequest transforming the response data
@@ -711,11 +652,6 @@ export function handleChartDataResponse(
// Query is running asynchronously and we must await the results.
// When status is 202, result contains async event data (job_id, channel_id, etc.)
// which differs from QueryData. We cast through unknown to handle this safely.
- if (useLegacyApi) {
- return waitForAsyncData(
- result[0] as unknown as Parameters<typeof waitForAsyncData>[0],
- ) as Promise<QueryData[]>;
- }
return waitForAsyncData(
result as unknown as Parameters<typeof waitForAsyncData>[0],
) as Promise<QueryData[]>;
@@ -777,11 +713,8 @@ export function exploreJSON(
ownState,
});
- const [useLegacyApi] = getQuerySettings(formData);
const chartDataRequestCaught = chartDataRequest
- .then(({ response, json }) =>
- handleChartDataResponse(response, json, useLegacyApi),
- )
+ .then(({ response, json }) => handleChartDataResponse(response, json))
.then(queriesResponse => {
// Drop stale responses: if a newer query has started for this chart,
// its controller will have replaced ours in state, so ignore this
@@ -897,28 +830,10 @@ export function exploreJSON(
},
);
- // only retrieve annotations when calling the legacy API
- const annotationLayers: AnnotationLayer[] = useLegacyApi
- ? (formData.annotation_layers as AnnotationLayer[]) || []
- : [];
- const isDashboardRequest = (dashboardId ?? 0) > 0;
-
return Promise.all([
chartDataRequestCaught,
dispatch(triggerQuery(false, key as string | number)),
dispatch(updateQueryFormData(formData, key as string | number)),
- ...annotationLayers.map((annotation: AnnotationLayer) =>
- dispatch(
- runAnnotationQuery({
- annotation,
- timeout,
- formData,
- key,
- isDashboardRequest,
- force,
- }),
- ),
- ),
]);
};
}
diff --git a/superset-frontend/src/components/Chart/chartActions.test.ts b/superset-frontend/src/components/Chart/chartActions.test.ts
index 30ba44359aa..e211eea72c4 100644
--- a/superset-frontend/src/components/Chart/chartActions.test.ts
+++ b/superset-frontend/src/components/Chart/chartActions.test.ts
@@ -32,7 +32,6 @@ import {
AnnotationStyle,
} from '@superset-ui/core';
import * as toastActions from 'src/components/MessageToasts/actions';
-import { LOG_EVENT } from 'src/logger/actions';
import * as exploreUtils from 'src/explore/exploreUtils';
import * as actions from 'src/components/Chart/chartAction';
import * as asyncEvent from 'src/middleware/asyncEvent';
@@ -100,7 +99,7 @@ describe('chart actions', () => {
let getChartDataUriStub: jest.SpyInstance;
let buildV1ChartDataPayloadStub: jest.SpyInstance;
let waitForAsyncDataStub: jest.SpyInstance;
- let fakeMetadata: { useLegacyApi?: boolean; viz_type?: string };
+ let fakeMetadata: { viz_type?: string };
beforeAll(() => {
fetchMock.get('glob:*api/v1/security/csrf_token/*', { result: '1234' });
@@ -135,7 +134,7 @@ describe('chart actions', () => {
} as unknown as Awaited<
ReturnType<typeof exploreUtils.buildV1ChartDataPayload>
>);
- fakeMetadata = { useLegacyApi: true };
+ fakeMetadata = {};
mockedGetChartMetadataRegistry.mockImplementation(
() =>
({
@@ -322,7 +321,7 @@ describe('chart actions', () => {
// eslint-disable-next-line no-restricted-globals -- TODO: Migrate from describe blocks
describe('v1 API', () => {
beforeEach(() => {
- fakeMetadata = { viz_type: 'my_viz', useLegacyApi: false };
+ fakeMetadata = { viz_type: 'my_viz' };
});
test('should query with the built query', async () => {
@@ -465,221 +464,6 @@ describe('chart actions', () => {
});
});
- // eslint-disable-next-line no-restricted-globals -- TODO: Migrate from describe blocks
- describe('legacy API', () => {
- beforeEach(() => {
- fakeMetadata = { useLegacyApi: true };
- });
-
- test('should dispatch CHART_UPDATE_STARTED action before the query', () => {
- const actionThunk = actions.postChartFormData({
- viz_type: 'table',
- } as QueryFormData);
-
- return actionThunk(
- dispatch as unknown as actions.ChartThunkDispatch,
- mockGetState as unknown as () => actions.RootState,
- undefined,
- ).then(() => {
- // chart update, trigger query, update form data, success
- expect(dispatch.mock.calls.length).toBe(5);
- expect(fetchMock.callHistory.calls(MOCK_URL)).toHaveLength(1);
- expect(dispatch.mock.calls[0][0].type).toBe(
- actions.CHART_UPDATE_STARTED,
- );
- });
- });
-
- test('should dispatch TRIGGER_QUERY action with the query', () => {
- const actionThunk = actions.postChartFormData({
- viz_type: 'table',
- } as QueryFormData);
- return actionThunk(
- dispatch as unknown as actions.ChartThunkDispatch,
- mockGetState as unknown as () => actions.RootState,
- undefined,
- ).then(() => {
- // chart update, trigger query, update form data, success
- expect(dispatch.mock.calls.length).toBe(5);
- expect(fetchMock.callHistory.calls(MOCK_URL)).toHaveLength(1);
- expect(dispatch.mock.calls[1][0].type).toBe(actions.TRIGGER_QUERY);
- });
- });
-
- test('should dispatch UPDATE_QUERY_FORM_DATA action with the query', () => {
- const actionThunk = actions.postChartFormData({
- viz_type: 'table',
- } as QueryFormData);
- return actionThunk(
- dispatch as unknown as actions.ChartThunkDispatch,
- mockGetState as unknown as () => actions.RootState,
- undefined,
- ).then(() => {
- // chart update, trigger query, update form data, success
- expect(dispatch.mock.calls.length).toBe(5);
- expect(fetchMock.callHistory.calls(MOCK_URL)).toHaveLength(1);
- expect(dispatch.mock.calls[2][0].type).toBe(
- actions.UPDATE_QUERY_FORM_DATA,
- );
- });
- });
-
- test('should dispatch logEvent async action', () => {
- const actionThunk = actions.postChartFormData({
- viz_type: 'table',
- } as QueryFormData);
- return actionThunk(
- dispatch as unknown as actions.ChartThunkDispatch,
- mockGetState as unknown as () => actions.RootState,
- undefined,
- ).then(() => {
- // chart update, trigger query, update form data, success
- expect(dispatch.mock.calls.length).toBe(5);
- expect(fetchMock.callHistory.calls(MOCK_URL)).toHaveLength(1);
- expect(typeof dispatch.mock.calls[3][0]).toBe('function');
-
- dispatch.mock.calls[3][0](dispatch);
- expect(dispatch.mock.calls.length).toBe(6);
- expect(dispatch.mock.calls[5][0].type).toBe(LOG_EVENT);
- });
- });
-
- test('should dispatch CHART_UPDATE_SUCCEEDED action upon success', () => {
- // Pass a viz_type so getQuerySettings returns useLegacyApi from the mocked registry
- const actionThunk = actions.postChartFormData({
- viz_type: 'table',
- } as QueryFormData);
- return actionThunk(
- dispatch as unknown as actions.ChartThunkDispatch,
- mockGetState as unknown as () => actions.RootState,
- undefined,
- ).then(() => {
- // chart update, trigger query, update form data, success
- expect(dispatch.mock.calls.length).toBe(5);
- expect(fetchMock.callHistory.calls(MOCK_URL)).toHaveLength(1);
- expect(dispatch.mock.calls[4][0].type).toBe(
- actions.CHART_UPDATE_SUCCEEDED,
- );
- });
- });
-
- test('should dispatch CHART_UPDATE_FAILED action upon query timeout', () => {
- const unresolvingPromise = new Promise(() => {});
- fetchMock.removeRoute(MOCK_URL);
- fetchMock.post(MOCK_URL, () => unresolvingPromise, {
- name: MOCK_URL,
- });
-
- const timeoutInSec = 1 / 1000;
- const actionThunk = actions.postChartFormData(
- {} as QueryFormData,
- false,
- timeoutInSec,
- );
-
- return actionThunk(
- dispatch as unknown as actions.ChartThunkDispatch,
- mockGetState as unknown as () => actions.RootState,
- undefined,
- ).then(() => {
- // chart update, trigger query, update form data, fail
- expect(fetchMock.callHistory.calls(MOCK_URL)).toHaveLength(1);
- expect(dispatch.mock.calls.length).toBe(5);
- expect(dispatch.mock.calls[4][0].type).toBe(
- actions.CHART_UPDATE_FAILED,
- );
-
- fetchMock.removeRoute(MOCK_URL);
- setupDefaultFetchMock();
- });
- });
-
- test('should dispatch CHART_UPDATE_FAILED action upon non-timeout non-abort failure', () => {
- fetchMock.removeRoute(MOCK_URL);
- fetchMock.post(
- MOCK_URL,
- { throws: { statusText: 'misc error' } },
- { name: MOCK_URL },
- );
-
- const timeoutInSec = 100; // Set to a time that is longer than the time this will take to fail
- const actionThunk = actions.postChartFormData(
- {} as QueryFormData,
- false,
- timeoutInSec,
- );
-
- return actionThunk(
- dispatch as unknown as actions.ChartThunkDispatch,
- mockGetState as unknown as () => actions.RootState,
- undefined,
- ).then(() => {
- // chart update, trigger query, update form data, fail
- expect(dispatch.mock.calls.length).toBe(5);
- const updateFailedAction = dispatch.mock.calls[4][0];
- expect(updateFailedAction.type).toBe(actions.CHART_UPDATE_FAILED);
- expect(updateFailedAction.queriesResponse[0].error).toBe('misc error');
-
- fetchMock.removeRoute(MOCK_URL);
- setupDefaultFetchMock();
- });
- });
-
- test('should dispatch CHART_UPDATE_STOPPED action upon abort', () => {
- fetchMock.removeRoute(MOCK_URL);
- fetchMock.post(
- MOCK_URL,
- { throws: { name: 'AbortError' } },
- { name: MOCK_URL },
- );
-
- const timeoutInSec = 100;
- const actionThunk = actions.postChartFormData(
- {} as QueryFormData,
- false,
- timeoutInSec,
- );
-
- return actionThunk(
- dispatch as unknown as actions.ChartThunkDispatch,
- mockGetState as unknown as () => actions.RootState,
- undefined,
- ).then(() => {
- const types = dispatch.mock.calls
- .map((call: [{ type?: string }]) => call[0] && call[0].type)
- .filter(Boolean);
-
- expect(types).toContain(actions.CHART_UPDATE_STOPPED);
- expect(types).not.toContain(actions.CHART_UPDATE_FAILED);
-
- fetchMock.removeRoutes();
- setupDefaultFetchMock();
- });
- });
-
- test('should handle the bigint without regression', async () => {
- getExploreUrlStub.mockRestore();
- const mockBigIntUrl = '/mock/chart/data/bigint';
- const expectedBigNumber = '9223372036854775807';
- fetchMock.post(mockBigIntUrl, `{ "value": ${expectedBigNumber} }`, {
- name: mockBigIntUrl,
- });
- getExploreUrlStub = jest
- .spyOn(exploreUtils, 'getExploreUrl')
- .mockImplementation(() => mockBigIntUrl);
-
- // Need viz_type to trigger the mocked getChartMetadataRegistry for legacy API
- const { json } = await actions.getChartDataRequest({
- formData: { ...fakeMetadata, viz_type: 'table' } as QueryFormData,
- });
-
- expect(fetchMock.callHistory.calls(mockBigIntUrl)).toHaveLength(1);
- expect((json.result[0] as JsonObject).value.toString()).toEqual(
- expectedBigNumber,
- );
- });
- });
-
// eslint-disable-next-line no-restricted-globals -- TODO: Migrate from describe blocks
describe('runAnnotationQuery', () => {
const mockDispatch = jest.fn();
diff --git a/superset-frontend/src/explore/components/ExploreChartPanel/ExploreChartPanel.test.tsx b/superset-frontend/src/explore/components/ExploreChartPanel/ExploreChartPanel.test.tsx
index e0375f9d67f..ab9afb3beab 100644
--- a/superset-frontend/src/explore/components/ExploreChartPanel/ExploreChartPanel.test.tsx
+++ b/superset-frontend/src/explore/components/ExploreChartPanel/ExploreChartPanel.test.tsx
@@ -90,7 +90,6 @@ describe('ChartContainer', () => {
new ChartMetadata({
name: 'fake table',
thumbnail: '.png',
- useLegacyApi: false,
}),
);
render(<ChartContainer {...props} />, { useRedux: true });
diff --git a/superset-frontend/src/explore/components/ExploreChartPanel/index.tsx b/superset-frontend/src/explore/components/ExploreChartPanel/index.tsx
index 55a3b7647cf..11ae06ae86e 100644
--- a/superset-frontend/src/explore/components/ExploreChartPanel/index.tsx
+++ b/superset-frontend/src/explore/components/ExploreChartPanel/index.tsx
@@ -21,17 +21,14 @@ import { useDispatch, useSelector } from 'react-redux';
import Split from 'react-split';
import { t } from '@apache-superset/core/translation';
import {
- DatasourceType,
ensureIsArray,
isFeatureEnabled,
FeatureFlag,
- getChartMetadataRegistry,
SupersetClient,
QueryFormData,
JsonObject,
getExtensionsRegistry,
} from '@superset-ui/core';
-import { Alert } from '@apache-superset/core/components';
import { css, styled, useTheme } from '@apache-superset/core/theme';
import ChartContainer from 'src/components/Chart/ChartContainer';
import { updateExploreChartState } from 'src/explore/actions/exploreActions';
@@ -44,8 +41,6 @@ import {
setItem,
LocalStorageKeys,
} from 'src/utils/localStorageHelpers';
-import { SaveDatasetModal } from 'src/SqlLab/components/SaveDatasetModal';
-import { getDatasourceAsSaveableDataset } from 'src/utils/datasourceUtils';
import { buildV1ChartDataPayload } from 'src/explore/exploreUtils';
import { getChartRequiredFieldsMissingMessage } from 'src/utils/getChartRequiredFieldsMissingMessage';
import type { ChartState, Datasource } from 'src/explore/types';
@@ -223,17 +218,10 @@ const ExploreChartPanel = ({
: getItem(LocalStorageKeys.IsDatapanelOpen, false),
);
- const [showDatasetModal, setShowDatasetModal] = useState(false);
-
- const metaDataRegistry = getChartMetadataRegistry();
- const { useLegacyApi } = metaDataRegistry.get(vizType) ?? {};
- const vizTypeNeedsDataset =
- useLegacyApi && datasource.type !== DatasourceType.Table;
// added boolean column to below show boolean so that the errors aren't overlapping
const showAlertBanner =
!chartAlert &&
chartIsStale &&
- !vizTypeNeedsDataset &&
chart.chartStatus !== 'failed' &&
ensureIsArray(chart.queriesResponse).length > 0;
@@ -380,31 +368,6 @@ const ExploreChartPanel = ({
padding-top: ${theme.sizeUnit * 2}px;
`}
>
- {vizTypeNeedsDataset && (
- <Alert
- message={t('Chart type requires a dataset')}
- type="error"
- css={theme => css`
- margin: 0 0 ${theme.sizeUnit * 4}px 0;
- `}
- description={
- <>
- {t(
- 'This chart type is not supported when using an unsaved query as a chart source. ',
- )}
- <span
- role="button"
- tabIndex={0}
- onClick={() => setShowDatasetModal(true)}
- css={{ textDecoration: 'underline' }}
- >
- {t('Create a dataset')}
- </span>
- {t(' to visualize your data.')}
- </>
- }
- />
- )}
{showAlertBanner && (
<ExploreAlert
title={
@@ -562,17 +525,6 @@ const ExploreChartPanel = ({
canDownload={canDownload}
/>
</Split>
- {showDatasetModal && (
- <SaveDatasetModal
- visible={showDatasetModal}
- onHide={() => setShowDatasetModal(false)}
- buttonTextOnSave={t('Save')}
- buttonTextOnOverwrite={t('Overwrite')}
- datasource={getDatasourceAsSaveableDataset(datasource)}
- openWindow={false}
- formData={formData}
- />
- )}
</Styles>
);
};
diff --git a/superset-frontend/src/explore/components/ExploreViewContainer/ExploreViewContainer.test.tsx b/superset-frontend/src/explore/components/ExploreViewContainer/ExploreViewContainer.test.tsx
index 4ad5d3aed65..5a49ff50126 100644
--- a/superset-frontend/src/explore/components/ExploreViewContainer/ExploreViewContainer.test.tsx
+++ b/superset-frontend/src/explore/components/ExploreViewContainer/ExploreViewContainer.test.tsx
@@ -163,7 +163,6 @@ test('generates a new form_data param when none is available', async () => {
new ChartMetadata({
name: 'fake table',
thumbnail: '.png',
- useLegacyApi: false,
}),
);
const history = createMemoryHistory({ initialEntries: [defaultPath] });
@@ -226,7 +225,6 @@ test('doesnt call replace when pathname is not /explore', async () => {
new ChartMetadata({
name: 'fake table',
thumbnail: '.png',
- useLegacyApi: false,
}),
);
const history = createMemoryHistory({ initialEntries: ['/dashboard'] });
diff --git a/superset-frontend/src/explore/exploreUtils/exploreUtils.test.tsx b/superset-frontend/src/explore/exploreUtils/exploreUtils.test.tsx
index 4625fff6c89..478eba7ace4 100644
--- a/superset-frontend/src/explore/exploreUtils/exploreUtils.test.tsx
+++ b/superset-frontend/src/explore/exploreUtils/exploreUtils.test.tsx
@@ -66,7 +66,7 @@ describe('exploreUtils', () => {
force: false,
curUrl: 'http://superset.com',
});
- compareURI(URI(url!), URI('/explore_json/'));
+ compareURI(URI(url!), URI('/explore/'));
});
test('generates proper json forced url', () => {
const url = getExploreUrl({
@@ -75,16 +75,7 @@ describe('exploreUtils', () => {
force: true,
curUrl: 'superset.com',
});
- compareURI(URI(url!), URI('/explore_json/').search({ force: 'true' }));
- });
- test('generates proper csv URL', () => {
- const url = getExploreUrl({
- formData,
- endpointType: 'csv',
- force: false,
- curUrl: 'superset.com',
- });
- compareURI(URI(url!), URI('/explore_json/').search({ csv: 'true' }));
+ compareURI(URI(url!), URI('/explore/').search({ force: 'true' }));
});
test('generates proper standalone URL', () => {
const url = getExploreUrl({
@@ -107,7 +98,7 @@ describe('exploreUtils', () => {
force: false,
curUrl: 'superset.com?foo=bar',
});
- compareURI(URI(url!), URI('/explore_json/').search({ foo: 'bar' }));
+ compareURI(URI(url!), URI('/explore/').search({ foo: 'bar' }));
});
test('generate proper save slice url', () => {
const url = getExploreUrl({
@@ -116,7 +107,7 @@ describe('exploreUtils', () => {
force: false,
curUrl: 'superset.com?foo=bar',
});
- compareURI(URI(url!), URI('/explore_json/').search({ foo: 'bar' }));
+ compareURI(URI(url!), URI('/explore/').search({ foo: 'bar' }));
});
});
@@ -202,49 +193,33 @@ describe('exploreUtils', () => {
// eslint-disable-next-line no-restricted-globals -- TODO: Migrate from describe blocks
describe('getQuerySettings', () => {
beforeAll(() => {
- getChartMetadataRegistry()
- .registerValue('my_legacy_viz', {
- useLegacyApi: true,
- } as unknown as ChartMetadata)
- .registerValue('my_v1_viz', {
- useLegacyApi: false,
- } as unknown as ChartMetadata);
+ getChartMetadataRegistry().registerValue('my_custom_parse_viz', {
+ parseMethod: 'json',
+ } as unknown as ChartMetadata);
});
afterAll(() => {
- getChartMetadataRegistry().remove('my_legacy_viz').remove('my_v1_viz');
+ getChartMetadataRegistry().remove('my_custom_parse_viz');
});
- test('returns true for legacy viz', () => {
- const [useLegacyApi, parseMethod] = getQuerySettings({
+ test('returns the parse method for a registered viz', () => {
+ const [parseMethod] = getQuerySettings({
...formData,
- viz_type: 'my_legacy_viz',
+ viz_type: 'my_custom_parse_viz',
});
- expect(useLegacyApi).toBe(true);
- expect(parseMethod).toBe('json-bigint');
- });
-
- test('returns false for v1 viz', () => {
- const [useLegacyApi, parseMethod] = getQuerySettings({
- ...formData,
- viz_type: 'my_v1_viz',
- });
- expect(useLegacyApi).toBe(false);
- expect(parseMethod).toBe('json-bigint');
+ expect(parseMethod).toBe('json');
});
- test('returns false for formData with unregistered viz_type', () => {
- const [useLegacyApi, parseMethod] = getQuerySettings({
+ test('defaults the parse method for unregistered viz types', () => {
+ const [parseMethod] = getQuerySettings({
...formData,
viz_type: 'undefined_viz',
});
- expect(useLegacyApi).toBe(false);
expect(parseMethod).toBe('json-bigint');
});
- test('returns false for formData without viz_type', () => {
- const [useLegacyApi, parseMethod] = getQuerySettings(formData);
- expect(useLegacyApi).toBe(false);
+ test('defaults the parse method without a viz_type', () => {
+ const [parseMethod] = getQuerySettings(formData);
expect(parseMethod).toBe('json-bigint');
});
});
diff --git a/superset-frontend/src/explore/exploreUtils/exportChart.test.ts b/superset-frontend/src/explore/exploreUtils/exportChart.test.ts
index 3311e92c761..d939b043f60 100644
--- a/superset-frontend/src/explore/exploreUtils/exportChart.test.ts
+++ b/superset-frontend/src/explore/exploreUtils/exportChart.test.ts
@@ -56,7 +56,6 @@ const createMockExportResponse = (headers: Headers = new Headers()) => ({
blob: jest.fn().mockResolvedValue(mockBlob),
});
-// Minimal formData that won't trigger legacy API (useLegacyApi = false)
const baseFormData = {
datasource: '1__table',
viz_type: 'table',
@@ -179,138 +178,6 @@ test('exportChart passes xlsx exportType for Excel exports', async () => {
);
});
-test('exportChart legacy API (useLegacyApi=true) passes prefixed URL to onStartStreamingExport when app root is configured', async () => {
- const appRoot = '/superset';
- ensureAppRoot.mockImplementation((path: string) => `${appRoot}${path}`);
-
- getChartMetadataRegistry.mockReturnValue({
- get: jest.fn().mockReturnValue({ useLegacyApi: true, parseMethod: 'json' }),
- });
-
- const onStartStreamingExport = jest.fn();
- const legacyFormData = {
- datasource: '1__table',
- viz_type: 'legacy_viz',
- };
-
- await exportChart({
- formData: legacyFormData,
- resultFormat: 'csv',
- onStartStreamingExport: onStartStreamingExport as unknown as null,
- });
-
- expect(onStartStreamingExport).toHaveBeenCalledTimes(1);
- const callArgs = onStartStreamingExport.mock.calls[0][0];
- // post `Superset.route_base = ""`, the blueprint path is
- // `/explore_json/`. With appRoot=/superset, the prefixed URL is
- // `/superset/explore_json/?csv=true` β single-prefix, not the legacy
- // doubled `/superset/superset/explore_json/...` that this test used to
- // pin (which was the bug, now fixed at source).
- expect(callArgs.url).toBe('/superset/explore_json/?csv=true');
- expect(callArgs.exportType).toBe('csv');
-});
-
-test('exportChart legacy API builds relative URL for CSV export without app root', async () => {
- ensureAppRoot.mockImplementation((path: string) => path);
-
- getChartMetadataRegistry.mockReturnValue({
- get: jest.fn().mockReturnValue({ useLegacyApi: true, parseMethod: 'json' }),
- });
-
- const onStartStreamingExport = jest.fn();
- const legacyFormData = {
- datasource: '1__table',
- viz_type: 'world_map',
- };
-
- await exportChart({
- formData: legacyFormData,
- resultFormat: 'csv',
- onStartStreamingExport: onStartStreamingExport as unknown as null,
- });
-
- expect(onStartStreamingExport).toHaveBeenCalledTimes(1);
- const callArgs = onStartStreamingExport.mock.calls[0][0];
- expect(callArgs.url).toBe('/explore_json/?csv=true');
-});
-
-test('exportChart legacy API builds relative URL for xlsx export', async () => {
- ensureAppRoot.mockImplementation((path: string) => path);
-
- getChartMetadataRegistry.mockReturnValue({
- get: jest.fn().mockReturnValue({ useLegacyApi: true, parseMethod: 'json' }),
- });
-
- const onStartStreamingExport = jest.fn();
- const legacyFormData = {
- datasource: '1__table',
- viz_type: 'bubble',
- };
-
- await exportChart({
- formData: legacyFormData,
- resultFormat: 'xlsx',
- resultType: 'results',
- onStartStreamingExport: onStartStreamingExport as unknown as null,
- });
-
- expect(onStartStreamingExport).toHaveBeenCalledTimes(1);
- const callArgs = onStartStreamingExport.mock.calls[0][0];
- expect(callArgs.url).toBe('/explore_json/?xlsx=true');
-});
-
-test('exportChart legacy API calls postBlob with relative URL', async () => {
- const { SupersetClient } = jest.requireMock('@superset-ui/core');
- ensureAppRoot.mockImplementation((path: string) => path);
- SupersetClient.postBlob.mockResolvedValue(createMockExportResponse());
-
- getChartMetadataRegistry.mockReturnValue({
- get: jest.fn().mockReturnValue({ useLegacyApi: true, parseMethod: 'json' }),
- });
-
- const legacyFormData = {
- datasource: '1__table',
- viz_type: 'world_map',
- };
-
- await exportChart({
- formData: legacyFormData,
- resultFormat: 'csv',
- resultType: 'full',
- });
-
- expect(SupersetClient.postBlob).toHaveBeenCalledTimes(1);
- const [url] = SupersetClient.postBlob.mock.calls[0];
- expect(url).toBe('/explore_json/?csv=true');
- expect(url).not.toMatch(/^https?:\/\//);
- expect(downloadBlob).toHaveBeenCalled();
-});
-
-test('exportChart legacy API includes force param when force=true', async () => {
- ensureAppRoot.mockImplementation((path: string) => path);
-
- getChartMetadataRegistry.mockReturnValue({
- get: jest.fn().mockReturnValue({ useLegacyApi: true, parseMethod: 'json' }),
- });
-
- const onStartStreamingExport = jest.fn();
- const legacyFormData = {
- datasource: '1__table',
- viz_type: 'world_map',
- };
-
- await exportChart({
- formData: legacyFormData,
- resultFormat: 'csv',
- force: true,
- onStartStreamingExport: onStartStreamingExport as unknown as null,
- });
-
- expect(onStartStreamingExport).toHaveBeenCalledTimes(1);
- const callArgs = onStartStreamingExport.mock.calls[0][0];
- expect(callArgs.url).toBe('/explore_json/?force=true&csv=true');
-});
-
test('exportChart successfully exports chart as CSV', async () => {
const { SupersetClient } = jest.requireMock('@superset-ui/core');
const mockResponse = createMockExportResponse();
diff --git a/superset-frontend/src/explore/exploreUtils/getExploreUrl.test.ts b/superset-frontend/src/explore/exploreUtils/getExploreUrl.test.ts
index 782d4412863..de1f7a38c70 100644
--- a/superset-frontend/src/explore/exploreUtils/getExploreUrl.test.ts
+++ b/superset-frontend/src/explore/exploreUtils/getExploreUrl.test.ts
@@ -36,44 +36,22 @@ test('Get ExploreUrl with default params', () => {
expect(getExploreUrl(params)).toBe('http://localhost/explore/');
});
-test('Get ExploreUrl with endpointType:full', () => {
+test('Get ExploreUrl for any endpoint type resolves to the explore page', () => {
const params = createParams();
expect(getExploreUrl({ ...params, endpointType: 'full' })).toBe(
- 'http://localhost/explore_json/',
+ 'http://localhost/explore/',
);
});
-test('Get ExploreUrl with endpointType:full and method:GET', () => {
- const params = createParams();
- expect(
- getExploreUrl({ ...params, endpointType: 'full', method: 'GET' }),
- ).toBe('http://localhost/explore_json/');
-});
-
-test('Get relative ExploreUrl with endpointType:csv', () => {
- const params = createParams();
- expect(
- getExploreUrl({ ...params, endpointType: 'csv', relative: true }),
- ).toBe('/explore_json/?csv=true');
-});
-
-test('Get relative ExploreUrl with endpointType:xlsx', () => {
- const params = createParams();
- expect(
- getExploreUrl({ ...params, endpointType: 'xlsx', relative: true }),
- ).toBe('/explore_json/?xlsx=true');
-});
-
test('Get relative ExploreUrl with force:true', () => {
const params = createParams();
expect(
getExploreUrl({
...params,
- endpointType: 'csv',
force: true,
relative: true,
}),
- ).toBe('/explore_json/?force=true&csv=true');
+ ).toBe('/explore/?force=true');
});
test('Get relative ExploreUrl with endpointType:base', () => {
diff --git a/superset-frontend/src/explore/exploreUtils/getLegacyEndpointType.test.ts b/superset-frontend/src/explore/exploreUtils/getLegacyEndpointType.test.ts
deleted file mode 100644
index eca145a680d..00000000000
--- a/superset-frontend/src/explore/exploreUtils/getLegacyEndpointType.test.ts
+++ /dev/null
@@ -1,40 +0,0 @@
-/**
- * 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 { getLegacyEndpointType } from '.';
-
-const createParams = () => ({
- resultType: 'resultType',
- resultFormat: 'resultFormat',
-});
-
-test('Should return resultType when resultFormat!=csv', () => {
- expect(getLegacyEndpointType(createParams())).toBe('resultType');
-});
-
-test('Should return resultFormat when resultFormat:csv', () => {
- expect(
- getLegacyEndpointType({ ...createParams(), resultFormat: 'csv' }),
- ).toBe('csv');
-});
-
-test('Should return resultFormat when resultFormat:xlsx', () => {
- expect(
- getLegacyEndpointType({ ...createParams(), resultFormat: 'xlsx' }),
- ).toBe('xlsx');
-});
diff --git a/superset-frontend/src/explore/exploreUtils/getURIDirectory.test.ts b/superset-frontend/src/explore/exploreUtils/getURIDirectory.test.ts
index 7d3b004cd4d..c9789c8d9da 100644
--- a/superset-frontend/src/explore/exploreUtils/getURIDirectory.test.ts
+++ b/superset-frontend/src/explore/exploreUtils/getURIDirectory.test.ts
@@ -18,17 +18,9 @@
*/
import { getURIDirectory } from '.';
-test('Cases in which the "explore_json" will be returned', () => {
- // post `Superset.route_base = ""` collapse the legacy
- // `/superset/explore_json/` endpoint is gone; `getURIDirectory` now
- // returns the bare `/explore_json/` path (appRoot is applied at the
- // outer `ensureAppRoot` layer when `includeAppRoot=true`).
- ['full', 'json', 'csv', 'query', 'results', 'samples'].forEach(name => {
- expect(getURIDirectory(name)).toBe('/explore_json/');
+test('always returns the explore directory', () => {
+ ['full', 'json', 'any-string'].forEach(name => {
+ expect(getURIDirectory(name)).toBe('/explore/');
});
-});
-
-test('Cases in which the "explore" will be returned', () => {
- expect(getURIDirectory('any-string')).toBe('/explore/');
expect(getURIDirectory()).toBe('/explore/');
});
diff --git a/superset-frontend/src/explore/exploreUtils/index.ts b/superset-frontend/src/explore/exploreUtils/index.ts
index 3e1cd406fbe..f4fc374c143 100644
--- a/superset-frontend/src/explore/exploreUtils/index.ts
+++ b/superset-frontend/src/explore/exploreUtils/index.ts
@@ -156,19 +156,7 @@ export function getURIDirectory(
endpointType: EndpointType | string = 'base',
includeAppRoot = true,
): string {
- // Building the directory part of the URI
- const uri = [
- 'full',
- 'json',
- 'csv',
- 'xlsx',
- 'query',
- 'results',
- 'samples',
- ].includes(endpointType)
- ? '/explore_json/'
- : '/explore/';
- return includeAppRoot ? ensureAppRoot(uri) : uri;
+ return includeAppRoot ? ensureAppRoot('/explore/') : '/explore/';
}
export function mountExploreUrl(
@@ -267,24 +255,9 @@ export function getExploreUrl({
if (force) {
search.force = 'true';
}
- if (endpointType === 'csv') {
- search.csv = 'true';
- }
- if (endpointType === 'xlsx') {
- search.xlsx = 'true';
- }
if (endpointType === URL_PARAMS.standalone.name) {
search.standalone = '1';
}
- if (endpointType === 'query') {
- search.query = 'true';
- }
- if (endpointType === 'results') {
- search.results = 'true';
- }
- if (endpointType === 'samples') {
- search.samples = 'true';
- }
const paramNames = Object.keys(requestParams);
if (paramNames.length) {
paramNames.forEach(name => {
@@ -298,14 +271,11 @@ export function getExploreUrl({
export const getQuerySettings = (
formData: Partial<QueryFormData>,
-): [boolean, string] => {
+): [string] => {
const vizMetadata = formData.viz_type
? getChartMetadataRegistry().get(formData.viz_type)
: undefined;
- return [
- vizMetadata?.useLegacyApi ?? false,
- vizMetadata?.parseMethod ?? 'json-bigint',
- ];
+ return [vizMetadata?.parseMethod ?? 'json-bigint'];
};
export const buildV1ChartDataPayload = async ({
@@ -346,15 +316,6 @@ export const buildV1ChartDataPayload = async ({
);
};
-export const getLegacyEndpointType = ({
- resultType,
- resultFormat,
-}: {
- resultType: string;
- resultFormat: string;
-}): string =>
- resultFormat === 'csv' || resultFormat === 'xlsx' ? resultFormat : resultType;
-
export const exportChart = async ({
formData,
resultFormat = 'json',
@@ -363,30 +324,14 @@ export const exportChart = async ({
ownState = {},
onStartStreamingExport = null,
}: ExportChartParams): Promise<void> => {
- let url: string | null;
- let payload: QueryFormData | ReturnType<typeof buildQueryContext>;
- const [useLegacyApi] = getQuerySettings(formData);
- if (useLegacyApi) {
- const endpointType = getLegacyEndpointType({ resultFormat, resultType });
- url = getExploreUrl({
- formData,
- endpointType,
- force,
- allowDomainSharding: false,
- relative: true,
- includeAppRoot: false,
- });
- payload = formData;
- } else {
- url = '/api/v1/chart/data';
- payload = await buildV1ChartDataPayload({
- formData,
- force,
- resultFormat,
- resultType,
- ownState,
- });
- }
+ const url = '/api/v1/chart/data';
+ const payload = await buildV1ChartDataPayload({
+ formData,
+ force,
+ resultFormat,
+ resultType,
+ ownState,
+ });
// Check if streaming export handler is provided (from dashboard Chart.jsx)
if (onStartStreamingExport) {
diff --git a/superset-frontend/src/explore/exploreUtils/shouldUseLegacyApi.test.ts b/superset-frontend/src/explore/exploreUtils/shouldUseLegacyApi.test.ts
deleted file mode 100644
index caeeae68787..00000000000
--- a/superset-frontend/src/explore/exploreUtils/shouldUseLegacyApi.test.ts
+++ /dev/null
@@ -1,59 +0,0 @@
-/**
- * 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 { getChartMetadataRegistry } from '@superset-ui/core';
-import { getQuerySettings } from '.';
-
-jest.mock('@superset-ui/core', () => ({
- ...jest.requireActual('@superset-ui/core'),
- getChartMetadataRegistry: jest.fn(),
-}));
-
-const mockedGetChartMetadataRegistry = getChartMetadataRegistry as jest.Mock;
-
-test('Should return false', () => {
- const get = jest.fn();
- mockedGetChartMetadataRegistry.mockReturnValue({ get } as any);
- expect(get).toHaveBeenCalledTimes(0);
- const [useLegacyApi] = getQuerySettings({ viz_type: 'name_test' });
- expect(useLegacyApi).toBe(false);
- expect(get).toHaveBeenCalledTimes(1);
- expect(get).toHaveBeenCalledWith('name_test');
-});
-
-test('Should return true', () => {
- const get = jest.fn();
- get.mockReturnValue({ useLegacyApi: true });
- mockedGetChartMetadataRegistry.mockReturnValue({ get } as any);
- expect(get).toHaveBeenCalledTimes(0);
- const [useLegacyApi] = getQuerySettings({ viz_type: 'name_test' });
- expect(useLegacyApi).toBe(true);
- expect(get).toHaveBeenCalledTimes(1);
- expect(get).toHaveBeenCalledWith('name_test');
-});
-
-test('Should return false when useLegacyApi:false', () => {
- const get = jest.fn();
- get.mockReturnValue({ useLegacyApi: false });
- mockedGetChartMetadataRegistry.mockReturnValue({ get } as any);
- expect(get).toHaveBeenCalledTimes(0);
- const [useLegacyApi] = getQuerySettings({ viz_type: 'name_test' });
- expect(useLegacyApi).toBe(false);
- expect(get).toHaveBeenCalledTimes(1);
- expect(get).toHaveBeenCalledWith('name_test');
-});
diff --git a/superset/async_events/async_query_manager.py b/superset/async_events/async_query_manager.py
index 4a8c840e413..0ed0292b2aa 100644
--- a/superset/async_events/async_query_manager.py
+++ b/superset/async_events/async_query_manager.py
@@ -121,7 +121,6 @@ class AsyncQueryManager:
self._jwt_expiration_seconds: int = 0
self._load_chart_data_into_cache_job: Any = None
# pylint: disable=invalid-name
- self._load_explore_json_into_cache_job: Any = None
def init_app(self, app: Flask) -> None:
cache_type = app.config.get("CACHE_CONFIG", {}).get("CACHE_TYPE")
@@ -162,13 +161,9 @@ class AsyncQueryManager:
self.register_request_handlers(app)
# pylint: disable=import-outside-toplevel
- from superset.tasks.async_queries import (
- load_chart_data_into_cache,
- load_explore_json_into_cache,
- )
+ from superset.tasks.async_queries import load_chart_data_into_cache
self._load_chart_data_into_cache_job = load_chart_data_into_cache
- self._load_explore_json_into_cache_job = load_explore_json_into_cache
def register_request_handlers(self, app: Flask) -> None:
@app.after_request
@@ -280,29 +275,6 @@ class AsyncQueryManager:
channel_id, job_id, user_id, status=self.STATUS_PENDING
)
- # pylint: disable=too-many-arguments
- def submit_explore_json_job(
- self,
- channel_id: str,
- form_data: dict[str, Any],
- response_type: str,
- force: Optional[bool] = False,
- user_id: Optional[int] = None,
- ) -> dict[str, Any]:
- # pylint: disable=import-outside-toplevel
- from superset import security_manager
-
- job_metadata = self.init_job(channel_id, user_id)
- self._load_explore_json_into_cache_job.delay(
- {**job_metadata, "guest_token": guest_user.guest_token}
- if (guest_user := security_manager.get_current_guest_user_if_guest())
- else job_metadata,
- form_data,
- response_type,
- force,
- )
- return job_metadata
-
def submit_chart_data_job(
self,
channel_id: str,
diff --git a/superset/charts/api.py b/superset/charts/api.py
index 0098996a502..5fdf0adb745 100644
--- a/superset/charts/api.py
+++ b/superset/charts/api.py
@@ -1055,7 +1055,7 @@ class ChartRestApi(BaseSupersetModelRestApi):
Warms up the cache for the chart.
Note for slices a force refresh occurs.
In terms of the `extra_filters` these can be obtained from records in the JSON
- encoded `logs.json` column associated with the `explore_json` action.
+ encoded `logs.json` column associated with the `explore` action.
requestBody:
description: >-
Identifies the chart to warm up cache for, and any additional dashboard or
diff --git a/superset/commands/chart/warm_up_cache.py b/superset/commands/chart/warm_up_cache.py
index f36e1c16c71..11ff21683ad 100644
--- a/superset/commands/chart/warm_up_cache.py
+++ b/superset/commands/chart/warm_up_cache.py
@@ -18,8 +18,6 @@
from typing import Any, cast, Optional, Union
-from flask import g
-
from superset.commands.base import BaseCommand
from superset.commands.chart.data.get_data_command import ChartDataCommand
from superset.commands.chart.exceptions import (
@@ -33,8 +31,7 @@ from superset.extensions import db, security_manager
from superset.models.slice import Slice
from superset.utils import json
from superset.utils.core import error_msg_from_exception, QueryObjectFilterClause
-from superset.views.utils import get_dashboard_extra_filters, get_form_data, get_viz
-from superset.viz import viz_types
+from superset.views.utils import get_dashboard_extra_filters
class ChartWarmUpCacheCommand(BaseCommand):
@@ -58,27 +55,6 @@ class ChartWarmUpCacheCommand(BaseCommand):
return get_dashboard_extra_filters(chart_id, self._dashboard_id)
- def _warm_up_legacy_cache(
- self, chart: Slice, form_data: dict[str, Any]
- ) -> tuple[Any, Any]:
- """Warm up cache for legacy visualizations."""
- if not chart.datasource:
- raise ChartInvalidError("Chart's datasource does not exist")
-
- if self._dashboard_id:
- form_data["extra_filters"] = self._get_dashboard_filters(chart.id)
-
- g.form_data = form_data
- payload = get_viz(
- datasource_type=chart.datasource.type,
- datasource_id=chart.datasource.id,
- form_data=form_data,
- force=True,
- ).get_payload()
- delattr(g, "form_data")
-
- return payload["errors"] or None, payload["status"]
-
def _warm_up_non_legacy_cache(self, chart: Slice) -> tuple[Any, Any]:
"""Warm up cache for non-legacy visualizations."""
query_context = chart.get_query_context()
@@ -112,12 +88,7 @@ class ChartWarmUpCacheCommand(BaseCommand):
chart = cast(Slice, self._chart_or_id)
try:
- form_data = get_form_data(chart.id, use_slice_data=True)[0]
-
- if form_data.get("viz_type") in viz_types:
- error, status = self._warm_up_legacy_cache(chart, form_data)
- else:
- error, status = self._warm_up_non_legacy_cache(chart)
+ error, status = self._warm_up_non_legacy_cache(chart)
except Exception as ex: # pylint: disable=broad-except
error = error_msg_from_exception(ex)
status = None
diff --git a/superset/common/query_context_processor.py b/superset/common/query_context_processor.py
index bd7e8c9ccbe..6f344bd775f 100644
--- a/superset/common/query_context_processor.py
+++ b/superset/common/query_context_processor.py
@@ -53,8 +53,6 @@ from superset.utils.core import (
is_adhoc_metric,
)
from superset.utils.pandas_postprocessing.utils import unescape_separator
-from superset.views.utils import get_viz
-from superset.viz import viz_types
if TYPE_CHECKING:
from superset.common.query_context import QueryContext
@@ -487,29 +485,6 @@ class QueryContextProcessor:
)
try:
- if chart.viz_type in viz_types:
- if not chart.datasource:
- raise QueryObjectValidationError(
- _(
- f"""The dataset for chart ID {chart.id} (referenced by
- annotation layer '{annotation_layer["name"]}') was
- not found. Please check that the dataset exists and
- is accessible."""
- )
- )
-
- form_data = chart.form_data.copy()
- form_data.update(annotation_layer.get("overrides", {}))
-
- payload = get_viz(
- datasource_type=chart.datasource.type,
- datasource_id=chart.datasource.id,
- form_data=form_data,
- force=force,
- ).get_payload()
-
- return payload["data"]
-
if not (query_context := chart.get_query_context()):
raise QueryObjectValidationError(
_(
diff --git a/superset/config.py b/superset/config.py
index f84493a44f2..03a62301039 100644
--- a/superset/config.py
+++ b/superset/config.py
@@ -349,7 +349,6 @@ WTF_CSRF_ENABLED = True
WTF_CSRF_EXEMPT_LIST = [
"superset.charts.data.api.data",
"superset.dashboards.api.cache_dashboard_screenshot",
- "superset.views.core.explore_json",
"superset.views.core.log",
"superset.views.datasource.views.samples",
"flask_appbuilder.security.views.acs",
diff --git a/superset/datasets/api.py b/superset/datasets/api.py
index 4801e3afcc5..1cc41907069 100644
--- a/superset/datasets/api.py
+++ b/superset/datasets/api.py
@@ -1167,7 +1167,7 @@ class DatasetRestApi(BaseSupersetModelRestApi):
Warms up the cache for the table.
Note for slices a force refresh occurs.
In terms of the `extra_filters` these can be obtained from records in the JSON
- encoded `logs.json` column associated with the `explore_json` action.
+ encoded `logs.json` column associated with the `explore` action.
requestBody:
description: >-
Identifies the database and table to warm up cache for, and any
diff --git a/superset/mcp_service/utils/permissions_utils.py b/superset/mcp_service/utils/permissions_utils.py
index 36977e8866e..38956fb2bec 100644
--- a/superset/mcp_service/utils/permissions_utils.py
+++ b/superset/mcp_service/utils/permissions_utils.py
@@ -55,7 +55,7 @@ SENSITIVE_FIELD_PERMISSIONS = {
"sql": "can_sql_json", # SQL Lab permissions
"extra": "can_this_form_get", # Advanced form permissions
"database_id": "can_this_form_get", # Database access permissions
- "query_context": "can_explore_json", # Explore permissions
+ "query_context": "can_explore", # Explore permissions
"cache_key": "can_warm_up_cache", # Cache management permissions
"css": "can_this_form_get", # Dashboard styling permissions
}
diff --git a/superset/middleware/legacy_prefix_redirect.py b/superset/middleware/legacy_prefix_redirect.py
index 61747ba57fa..91f38d9e0a3 100644
--- a/superset/middleware/legacy_prefix_redirect.py
+++ b/superset/middleware/legacy_prefix_redirect.py
@@ -21,7 +21,7 @@ After ``Superset.route_base = ""`` collapsed the historical ``/superset``
prefix off every view, bookmarks/email links/external integrations to the
legacy paths would 404. This middleware closes that gap for one release
cycle (removed at EOL ``5.0.0``, matching the ``@deprecated`` gate on
-``Superset.explore`` and ``Superset.explore_json``).
+``Superset.explore``).
Layering invariant
------------------
@@ -98,8 +98,6 @@ LEGACY_REDIRECT_MAP: dict[str, tuple[frozenset[str], str]] = {
"/file-handler": (frozenset({"GET"}), "/file-handler"),
"/log/": (frozenset({"POST"}), "/log/"),
"/sqllab/history/": (frozenset({"GET"}), "/sqllab/history/"),
- "/explore_json/": (frozenset({"GET", "POST"}), "/explore_json/"),
- "/explore_json/data/": (frozenset({"GET"}), "/explore_json/data/"),
# views/explore.py β ExploreView (route_base = "/explore") owns the
# bare /explore/ rule; Superset.explore (deprecated) provides the
# POST handler. ExplorePermalinkView.permalink (route_base = "")
diff --git a/superset/models/slice.py b/superset/models/slice.py
index e9d977b027b..9942bffb51e 100644
--- a/superset/models/slice.py
+++ b/superset/models/slice.py
@@ -48,7 +48,6 @@ from superset.tasks.thumbnails import cache_chart_thumbnail
from superset.tasks.utils import get_current_user
from superset.thumbnails.digest import get_chart_digest
from superset.utils import core as utils, json
-from superset.viz import BaseViz, viz_types
if TYPE_CHECKING:
from superset.common.query_context import QueryContext
@@ -198,15 +197,6 @@ class Slice( # pylint: disable=too-many-public-methods
datasource = self.datasource
return datasource.url if datasource else None
- @property
- def viz(self) -> BaseViz | None:
- form_data = json.loads(self.params)
- viz_class = viz_types.get(self.viz_type)
- datasource = self.datasource
- if viz_class and datasource:
- return viz_class(datasource=datasource, form_data=form_data)
- return None
-
@property
def description_markeddown(self) -> str:
return utils.markdown(self.description or "")
@@ -217,8 +207,7 @@ class Slice( # pylint: disable=too-many-public-methods
data: dict[str, Any] = {}
self.token = ""
try:
- viz = self.viz
- data = viz.data if viz else self.form_data
+ data = self.form_data
self.token = utils.get_form_data_token(data)
except Exception as ex: # pylint: disable=broad-except
logger.exception(ex)
@@ -328,11 +317,6 @@ class Slice( # pylint: disable=too-many-public-methods
"""Defines the url to access the slice"""
return self.get_explore_url()
- @property
- def explore_json_url(self) -> str:
- """Defines the url to access the slice"""
- return self.get_explore_url("/explore_json")
-
@property
def edit_url(self) -> str:
return f"/chart/edit/{self.id}"
diff --git a/superset/security/manager.py b/superset/security/manager.py
index 352edf7e9c3..248ee92dbd6 100644
--- a/superset/security/manager.py
+++ b/superset/security/manager.py
@@ -114,7 +114,6 @@ if TYPE_CHECKING:
from superset.models.slice import Slice
from superset.models.sql_lab import Query
from superset.semantic_layers.models import SemanticLayer, SemanticView
- from superset.viz import BaseViz
logger = logging.getLogger(__name__)
@@ -1079,7 +1078,6 @@ class SupersetSecurityManager( # pylint: disable=too-many-public-methods
("can_read", "Chart"),
("can_dashboard", "Superset"),
("can_slice", "Superset"),
- ("can_explore_json", "Superset"),
("can_dashboard_permalink", "Superset"),
("can_read", "DashboardPermalinkRestApi"),
# Dashboard filter interactions
@@ -3451,7 +3449,6 @@ class SupersetSecurityManager( # pylint: disable=too-many-public-methods
query: Optional["Query | Explorable"] = None,
query_context: Optional["QueryContext"] = None,
table: Optional["Table"] = None,
- viz: Optional["BaseViz"] = None,
sql: Optional[str] = None,
catalog: Optional[str] = None,
schema: Optional[str] = None,
@@ -3466,7 +3463,6 @@ class SupersetSecurityManager( # pylint: disable=too-many-public-methods
:param query: The SQL Lab query
:param query_context: The query context
:param table: The Superset table (requires database)
- :param viz: The visualization
:param sql: The SQL string (requires database)
:param catalog: Optional catalog name
:param schema: Optional schema name
@@ -3692,15 +3688,12 @@ class SupersetSecurityManager( # pylint: disable=too-many-public-methods
)
)
- if datasource or query_context or viz:
+ if datasource or query_context:
form_data = None
if query_context:
datasource = query_context.datasource
form_data = query_context.form_data
- elif viz:
- datasource = viz.datasource
- form_data = viz.form_data
assert datasource
diff --git a/superset/tasks/async_queries.py b/superset/tasks/async_queries.py
index f9aa9efc2fe..ca20e676603 100644
--- a/superset/tasks/async_queries.py
+++ b/superset/tasks/async_queries.py
@@ -16,10 +16,9 @@
# under the License.
from __future__ import annotations
-import copy
import dataclasses
import logging
-from typing import Any, cast, TYPE_CHECKING
+from typing import Any, TYPE_CHECKING
from celery.exceptions import SoftTimeLimitExceeded
from flask import current_app, g
@@ -30,17 +29,13 @@ from superset.charts.schemas import ChartDataQueryContextSchema
from superset.exceptions import (
SupersetErrorException,
SupersetErrorsException,
- SupersetVizException,
)
from superset.extensions import (
async_query_manager,
- cache_manager,
celery_app,
security_manager,
)
-from superset.utils.cache import generate_cache_key, set_and_log_cache
from superset.utils.core import override_user
-from superset.views.utils import get_datasource_info, get_viz
if TYPE_CHECKING:
from superset.common.query_context import QueryContext
@@ -122,77 +117,3 @@ def load_chart_data_into_cache(
job_metadata, async_query_manager.STATUS_ERROR, errors=errors
)
raise
-
-
-@celery_app.task(name="load_explore_json_into_cache", soft_time_limit=query_timeout)
-def load_explore_json_into_cache( # pylint: disable=too-many-locals
- job_metadata: dict[str, Any],
- form_data: dict[str, Any],
- response_type: str | None = None,
- force: bool = False,
-) -> None:
- cache_key_prefix = "ejr-" # ejr: explore_json request
-
- with override_user(_load_user_from_job_metadata(job_metadata), force=False):
- try:
- set_form_data(form_data)
- datasource_id, datasource_type = get_datasource_info(None, None, form_data)
-
- # Perform a deep copy here so that below we can cache the original
- # value of the form_data object. This is necessary since the viz
- # objects modify the form_data object. If the modified version were
- # to be cached here, it will lead to a cache miss when clients
- # attempt to retrieve the value of the completed async query.
- original_form_data = copy.deepcopy(form_data)
-
- viz_obj = get_viz(
- datasource_type=cast(str, datasource_type),
- datasource_id=datasource_id,
- form_data=form_data,
- force=force,
- )
- # run query & cache results
- payload = viz_obj.get_payload()
- if viz_obj.has_error(payload):
- raise SupersetVizException(errors=payload["errors"])
-
- # Cache the original form_data value for async retrieval
- cache_value = {
- "form_data": original_form_data,
- "response_type": response_type,
- }
- cache_key = generate_cache_key(cache_value, cache_key_prefix)
- cache_instance = cache_manager.cache
- cache_timeout = (
- cache_instance.cache.default_timeout if cache_instance.cache else None
- )
- set_and_log_cache(
- cache_instance, cache_key, cache_value, cache_timeout=cache_timeout
- )
- result_url = f"/explore_json/data/{cache_key}"
- async_query_manager.update_job(
- job_metadata,
- async_query_manager.STATUS_DONE,
- result_url=result_url,
- )
- except SoftTimeLimitExceeded as ex:
- logger.warning(
- "A timeout occurred while loading explore json, error: %s", ex
- )
- raise
- except Exception as ex:
- if isinstance(ex, SupersetVizException):
- errors = ex.errors
- # Extract SIP-40 style errors when available
- elif isinstance(ex, SupersetErrorException):
- errors = [dataclasses.asdict(ex.error)] # type: ignore
- elif isinstance(ex, SupersetErrorsException):
- errors = [dataclasses.asdict(error) for error in ex.errors] # type: ignore
- else:
- error = ex.message if hasattr(ex, "message") else str(ex)
- errors = [error] # type: ignore
-
- async_query_manager.update_job(
- job_metadata, async_query_manager.STATUS_ERROR, errors=errors
- )
- raise
diff --git a/superset/views/core.py b/superset/views/core.py
index 84932ae55ac..30b7fc593d1 100755
--- a/superset/views/core.py
+++ b/superset/views/core.py
@@ -39,7 +39,6 @@ from flask_appbuilder import expose
from flask_appbuilder.security.decorators import (
has_access,
has_access_api,
- permission_name,
)
from flask_babel import gettext as __, lazy_gettext as _
from sqlalchemy.exc import SQLAlchemyError
@@ -51,7 +50,6 @@ from superset import (
is_feature_enabled,
security_manager,
)
-from superset.async_events.async_query_manager import AsyncQueryTokenException
from superset.commands.chart.exceptions import ChartNotFoundError
from superset.commands.chart.warm_up_cache import ChartWarmUpCacheCommand
from superset.commands.dashboard.exceptions import DashboardAccessDeniedError
@@ -60,19 +58,15 @@ from superset.commands.dataset.exceptions import DatasetNotFoundError
from superset.commands.explore.form_data.get import GetFormDataCommand
from superset.commands.explore.form_data.parameters import CommandParameters
from superset.commands.explore.permalink.get import GetExplorePermalinkCommand
-from superset.common.chart_data import ChartDataResultFormat, ChartDataResultType
from superset.connectors.sqla.models import BaseDatasource, SqlaTable
from superset.daos.chart import ChartDAO
from superset.daos.datasource import DatasourceDAO
from superset.dashboards.permalink.exceptions import DashboardPermalinkGetFailedError
from superset.exceptions import (
- CacheLoadError,
- SupersetErrorException,
SupersetException,
SupersetSecurityException,
)
from superset.explore.permalink.exceptions import ExplorePermalinkGetFailedError
-from superset.extensions import async_query_manager, cache_manager
from superset.models.core import Database
from superset.models.dashboard import Dashboard
from superset.models.slice import Slice
@@ -83,10 +77,8 @@ from superset.superset_typing import (
)
from superset.tasks.utils import get_current_user
from superset.utils import core as utils, json
-from superset.utils.cache import etag_cache
from superset.utils.core import (
DatasourceType,
- GenericDataType,
get_user_id,
ReservedUrlParameters,
)
@@ -94,28 +86,19 @@ from superset.views.base import (
api,
BaseSupersetView,
common_bootstrap_payload,
- CsvResponse,
- data_payload_response,
deprecated,
- generate_download_headers,
json_error_response,
json_success,
- XlsxResponse,
)
from superset.views.error_handling import handle_api_exception
from superset.views.utils import (
bootstrap_user_data,
- check_datasource_perms,
- check_explore_cache_perms,
- check_resource_permissions,
get_datasource_info,
get_explore_redirect_url,
get_form_data,
- get_viz,
redirect_to_login,
sanitize_datasource_data,
)
-from superset.viz import BaseViz
logger = logging.getLogger(__name__)
@@ -159,245 +142,6 @@ class Superset(BaseSupersetView):
endpoint_params[ReservedUrlParameters.STANDALONE.value] = "true"
return redirect(url_for("ExploreView.root", **endpoint_params))
- def get_query_string_response(self, viz_obj: BaseViz) -> FlaskResponse:
- query = None
- try:
- if query_obj := viz_obj.query_obj():
- query = viz_obj.datasource.get_query_str(query_obj)
- except Exception as ex: # pylint: disable=broad-except
- err_msg = utils.error_msg_from_exception(ex)
- logger.exception(err_msg)
- return json_error_response(err_msg)
-
- if not query:
- query = __("Query cannot be loaded.")
-
- return self.json_response(
- {"query": query, "language": viz_obj.datasource.query_language}
- )
-
- def get_raw_results(self, viz_obj: BaseViz) -> FlaskResponse:
- payload = viz_obj.get_df_payload()
- if viz_obj.has_error(payload):
- return json_error_response(payload=payload, status=400)
- response = {
- "data": payload["df"].to_dict("records")
- if payload["df"] is not None
- else [],
- "colnames": payload.get("colnames"),
- "coltypes": payload.get("coltypes"),
- "rowcount": payload.get("rowcount"),
- "sql_rowcount": payload.get("sql_rowcount"),
- }
- return self.json_response(response)
-
- def get_samples(self, viz_obj: BaseViz) -> FlaskResponse:
- return self.json_response(viz_obj.get_samples())
-
- @staticmethod
- def send_data_payload_response(viz_obj: BaseViz, payload: Any) -> FlaskResponse:
- return data_payload_response(*viz_obj.payload_json_and_has_error(payload))
-
- def generate_json(
- self, viz_obj: BaseViz, response_type: str | None = None
- ) -> FlaskResponse:
- if response_type == ChartDataResultFormat.CSV:
- return CsvResponse(
- viz_obj.get_csv(), headers=generate_download_headers("csv")
- )
-
- if response_type == ChartDataResultFormat.XLSX:
- return self._generate_xlsx(viz_obj)
-
- if response_type == ChartDataResultType.QUERY:
- return self.get_query_string_response(viz_obj)
-
- if response_type == ChartDataResultType.RESULTS:
- return self.get_raw_results(viz_obj)
-
- if response_type == ChartDataResultType.SAMPLES:
- return self.get_samples(viz_obj)
-
- payload = viz_obj.get_payload()
- return self.send_data_payload_response(viz_obj, payload)
-
- @staticmethod
- def _generate_xlsx(viz_obj: BaseViz) -> FlaskResponse:
- import pandas as pd
-
- from superset.utils.excel import apply_column_types, df_to_excel
-
- payload = viz_obj.get_df_payload()
- df = payload.get("df")
- if df is None:
- df = pd.DataFrame()
- coltypes: list[GenericDataType] = []
- else:
- coltypes = payload.get("coltypes") or []
- if coltypes:
- df = apply_column_types(df, coltypes)
- xlsx_data = df_to_excel(df, index=False)
- return XlsxResponse(xlsx_data, headers=generate_download_headers("xlsx"))
-
- @event_logger.log_this
- @api
- @has_access_api
- @handle_api_exception
- @permission_name("explore_json")
- @expose("/explore_json/data/<cache_key>", methods=("GET",))
- @check_resource_permissions(check_explore_cache_perms)
- @deprecated(eol_version="5.0.0")
- def explore_json_data(self, cache_key: str) -> FlaskResponse:
- """Serves cached result data for async explore_json calls
-
- `self.generate_json` receives this input and returns different
- payloads based on the request args in the first block
-
- TODO: form_data should not be loaded twice from cache
- (also loaded in `check_explore_cache_perms`)
- """
- try:
- cached = cache_manager.cache.get(cache_key)
- if not cached:
- raise CacheLoadError("Cached data not found")
-
- form_data = cached.get("form_data")
- response_type = cached.get("response_type")
- # Set form_data in Flask Global as it is used as a fallback
- # for async queries with jinja context
- g.form_data = form_data
- datasource_id, datasource_type = get_datasource_info(None, None, form_data)
-
- viz_obj = get_viz(
- datasource_type=cast(str, datasource_type),
- datasource_id=datasource_id,
- form_data=form_data,
- force_cached=True,
- )
-
- return self.generate_json(viz_obj, response_type)
- except SupersetErrorException:
- # Let structured Superset errors (e.g. OAuth2RedirectError) propagate
- # so the global Flask error handler serializes them.
- raise
- except SupersetException as ex:
- return json_error_response(utils.error_msg_from_exception(ex), 400)
-
- @api
- @has_access_api
- @handle_api_exception
- @event_logger.log_this
- @expose(
- "/explore_json/<datasource_type>/<int:datasource_id>/",
- methods=(
- "GET",
- "POST",
- ),
- )
- @expose(
- "/explore_json/",
- methods=(
- "GET",
- "POST",
- ),
- )
- @etag_cache()
- @check_resource_permissions(check_datasource_perms)
- @deprecated(eol_version="5.0.0", new_target="/api/v1/chart/data")
- def explore_json( # noqa: C901
- self, datasource_type: str | None = None, datasource_id: int | None = None
- ) -> FlaskResponse:
- """Serves all request that GET or POST form_data
-
- This endpoint evolved to be the entry point of many different
- requests that GETs or POSTs a form_data.
-
- `self.generate_json` receives this input and returns different
- payloads based on the request args in the first block
-
- TODO: break into one endpoint for each return shape"""
-
- response_type = ChartDataResultFormat.JSON.value
- responses: list[ChartDataResultFormat | ChartDataResultType] = list(
- ChartDataResultFormat
- )
- responses.extend(list(ChartDataResultType))
- for response_option in responses:
- if request.args.get(response_option) == "true":
- response_type = response_option
- break
-
- # Verify user has permission to export data files
- if response_type in (
- ChartDataResultFormat.CSV,
- ChartDataResultFormat.XLSX,
- ):
- if is_feature_enabled("GRANULAR_EXPORT_CONTROLS"):
- can_export = security_manager.can_access("can_export_data", "Superset")
- else:
- can_export = security_manager.can_access("can_csv", "Superset")
- if not can_export:
- return json_error_response(
- _("You don't have the rights to export data"),
- status=403,
- )
-
- form_data = get_form_data()[0]
- try:
- datasource_id, datasource_type = get_datasource_info(
- datasource_id, datasource_type, form_data
- )
- force = request.args.get("force") == "true"
-
- # TODO: support CSV, SQL query and other non-JSON types
- if (
- is_feature_enabled("GLOBAL_ASYNC_QUERIES")
- and response_type == ChartDataResultFormat.JSON
- ):
- # First, look for the chart query results in the cache.
- with contextlib.suppress(CacheLoadError):
- viz_obj = get_viz(
- datasource_type=cast(str, datasource_type),
- datasource_id=datasource_id,
- form_data=form_data,
- force_cached=True,
- force=force,
- )
- payload = viz_obj.get_payload()
- # If the chart query has already been cached, return it immediately.
- if payload is not None:
- return self.send_data_payload_response(viz_obj, payload)
- # Otherwise, kick off a background job to run the chart query.
- # Clients will either poll or be notified of query completion,
- # at which point they will call the /explore_json/data/<cache_key>
- # endpoint to retrieve the results.
- try:
- async_channel_id = (
- async_query_manager.parse_channel_id_from_request(request)
- )
- job_metadata = async_query_manager.submit_explore_json_job(
- async_channel_id, form_data, response_type, force, get_user_id()
- )
- except AsyncQueryTokenException:
- return json_error_response("Not authorized", 401)
-
- return json_success(json.dumps(job_metadata), status=202)
-
- viz_obj = get_viz(
- datasource_type=cast(str, datasource_type),
- datasource_id=datasource_id,
- form_data=form_data,
- force=force,
- )
-
- return self.generate_json(viz_obj, response_type)
- except SupersetErrorException:
- # Let structured Superset errors (e.g. OAuth2RedirectError) propagate
- # so the global Flask error handler serializes them.
- raise
- except SupersetException as ex:
- return json_error_response(utils.error_msg_from_exception(ex), 400)
-
@has_access
@event_logger.log_this
@expose(
@@ -711,7 +455,7 @@ class Superset(BaseSupersetView):
Note for slices a force refresh occurs.
In terms of the `extra_filters` these can be obtained from records in the JSON
- encoded `logs.json` column associated with the `explore_json` action.
+ encoded `logs.json` column associated with the `explore` action.
"""
slice_id = request.args.get("slice_id")
dashboard_id = request.args.get("dashboard_id")
diff --git a/superset/views/utils.py b/superset/views/utils.py
index 3bc6ddd5c37..deb05a6bd92 100644
--- a/superset/views/utils.py
+++ b/superset/views/utils.py
@@ -34,19 +34,14 @@ from flask import (
from flask_appbuilder.security.sqla import models as ab_models
from flask_appbuilder.security.sqla.models import User
from flask_babel import _
-from sqlalchemy.exc import NoResultFound
-from superset import appbuilder, dataframe, db, result_set, viz
+from superset import appbuilder, dataframe, db, result_set
from superset.common.db_query_status import QueryStatus
-from superset.daos.datasource import DatasourceDAO
-from superset.errors import ErrorLevel, SupersetError, SupersetErrorType
from superset.exceptions import (
- CacheLoadError,
SerializationError,
SupersetException,
- SupersetSecurityException,
)
-from superset.extensions import cache_manager, feature_flag_manager, security_manager
+from superset.extensions import feature_flag_manager, security_manager
from superset.legacy import update_time_range
from superset.models.core import Database
from superset.models.dashboard import Dashboard
@@ -60,7 +55,6 @@ from superset.superset_typing import (
from superset.utils import json
from superset.utils.core import DatasourceType
from superset.utils.decorators import stats_timing
-from superset.viz import BaseViz
logger = logging.getLogger(__name__)
stats_logger = app.config["STATS_LOGGER"]
@@ -181,24 +175,6 @@ def get_permissions(
return roles_permissions, transformed_permissions
-def get_viz(
- form_data: FormData,
- datasource_type: str,
- datasource_id: int,
- force: bool = False,
- force_cached: bool = False,
-) -> BaseViz:
- viz_type = form_data.get("viz_type", "table")
- datasource = DatasourceDAO.get_datasource(
- DatasourceType(datasource_type),
- datasource_id,
- )
- viz_obj = viz.viz_types[viz_type](
- datasource, form_data=form_data, force=force, force_cached=force_cached
- )
- return viz_obj
-
-
def loads_request_json(request_json_data: str) -> dict[Any, Any]:
"""Parse a JSON request payload, coercing non-objects to ``{}``.
@@ -636,81 +612,6 @@ def check_resource_permissions(
return decorator
-def check_explore_cache_perms(_self: Any, cache_key: str) -> None:
- """
- Loads async explore_json request data from cache and performs access check
-
- :param _self: the Superset view instance
- :param cache_key: the cache key passed into /explore_json/data/
- :raises SupersetSecurityException: If the user cannot access the resource
- """
- cached = cache_manager.cache.get(cache_key)
- if not cached:
- raise CacheLoadError("Cached data not found")
-
- check_datasource_perms(_self, form_data=cached["form_data"])
-
-
-def check_datasource_perms(
- _self: Any,
- datasource_type: Optional[str] = None,
- datasource_id: Optional[int] = None,
- **kwargs: Any,
-) -> None:
- """
- Check if user can access a cached response from explore_json.
-
- This function takes `self` since it must have the same signature as the
- the decorated method.
-
- :param datasource_type: The datasource type
- :param datasource_id: The datasource ID
- :raises SupersetSecurityException: If the user cannot access the resource
- """
-
- form_data = kwargs["form_data"] if "form_data" in kwargs else get_form_data()[0]
-
- try:
- datasource_id, datasource_type = get_datasource_info(
- datasource_id, datasource_type, form_data
- )
- except SupersetException as ex:
- raise SupersetSecurityException(
- SupersetError(
- error_type=SupersetErrorType.FAILED_FETCHING_DATASOURCE_INFO_ERROR,
- level=ErrorLevel.ERROR,
- message=str(ex),
- )
- ) from ex
-
- if datasource_type is None:
- raise SupersetSecurityException(
- SupersetError(
- error_type=SupersetErrorType.UNKNOWN_DATASOURCE_TYPE_ERROR,
- level=ErrorLevel.ERROR,
- message=_("Could not determine datasource type"),
- )
- )
-
- try:
- viz_obj = get_viz(
- datasource_type=datasource_type,
- datasource_id=datasource_id,
- form_data=form_data,
- force=False,
- )
- except NoResultFound as ex:
- raise SupersetSecurityException(
- SupersetError(
- error_type=SupersetErrorType.UNKNOWN_DATASOURCE_TYPE_ERROR,
- level=ErrorLevel.ERROR,
- message=_("Could not find viz object"),
- )
- ) from ex
-
- viz_obj.raise_for_access()
-
-
def _deserialize_results_payload(
payload: Union[bytes, str], query: Query, use_msgpack: Optional[bool] = False
) -> dict[str, Any]:
diff --git a/superset/viz.py b/superset/viz.py
deleted file mode 100644
index 1536af58da4..00000000000
--- a/superset/viz.py
+++ /dev/null
@@ -1,2742 +0,0 @@
-# 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.
-# pylint: disable=too-many-lines
-"""This module contains the 'Viz' objects
-
-These objects represent the backend of all the visualizations that
-Superset can render.
-"""
-
-from __future__ import annotations
-
-import copy
-import dataclasses
-import logging
-import math
-from collections import OrderedDict
-from datetime import datetime, timedelta
-from itertools import product
-from typing import Any, cast, Optional, TYPE_CHECKING
-
-import numpy as np
-import pandas as pd
-import polyline
-import pygeohash
-from dateutil import relativedelta as rdelta
-from deprecation import deprecated
-from flask import current_app, request
-from flask_babel import lazy_gettext as _
-from geopy.point import Point
-from pandas.tseries.frequencies import to_offset
-
-from superset.common.db_query_status import QueryStatus
-from superset.constants import CACHE_DISABLED_TIMEOUT
-from superset.errors import ErrorLevel, SupersetError, SupersetErrorType
-from superset.exceptions import (
- CacheLoadError,
- NullValueException,
- QueryObjectValidationError,
- SpatialException,
- SupersetErrorException,
- SupersetSecurityException,
-)
-from superset.extensions import cache_manager, security_manager
-from superset.models.helpers import QueryResult
-from superset.sql.parse import sanitize_clause
-from superset.superset_typing import (
- Column,
- Metric,
- QueryObjectDict,
- VizData,
- VizPayload,
-)
-from superset.utils import core as utils, csv, json
-from superset.utils.cache import set_and_log_cache
-from superset.utils.cache_keys import add_impersonation_cache_key_if_needed
-from superset.utils.core import (
- apply_max_row_limit,
- DateColumn,
- DTTM_ALIAS,
- ExtraFiltersReasonType,
- get_column_name,
- get_column_names,
- get_column_names_from_columns,
- JS_MAX_INTEGER,
- merge_extra_filters,
- simple_filter_to_adhoc,
-)
-from superset.utils.date_parser import get_since_until, parse_past_timedelta
-from superset.utils.hashing import hash_from_str
-from superset.utils.pandas_postprocessing.utils import (
- escape_separator,
- FLAT_COLUMN_SEPARATOR,
-)
-
-if TYPE_CHECKING:
- from superset.connectors.sqla.models import BaseDatasource
-
-logger = logging.getLogger(__name__)
-
-METRIC_KEYS = [
- "metric",
- "metrics",
- "percent_metrics",
- "metric_2",
- "secondary_metric",
- "x",
- "y",
- "size",
-]
-
-# Allowlist of resampler aggregation methods that may be invoked dynamically via
-# ``getattr`` on a pandas ``Resampler``. Restricting the set of callable names
-# keeps the dynamic dispatch limited to known-safe aggregations.
-ALLOWED_RESAMPLE_METHODS = frozenset(
- {
- "asfreq",
- "bfill",
- "count",
- "ffill",
- "first",
- "last",
- "max",
- "mean",
- "median",
- "min",
- "std",
- "sum",
- "var",
- }
-)
-
-
-class BaseViz: # pylint: disable=too-many-public-methods
- """All visualizations derive this base class"""
-
- viz_type: str | None = None
- verbose_name = "Base Viz"
- credits = ""
- is_timeseries = False
- cache_type = "df"
- enforce_numerical_metrics = True
-
- @deprecated(deprecated_in="3.0")
- def __init__(
- self,
- datasource: BaseDatasource,
- form_data: dict[str, Any],
- force: bool = False,
- force_cached: bool = False,
- ) -> None:
- if not datasource:
- raise QueryObjectValidationError(_("Viz is missing a datasource"))
-
- self.datasource = datasource
- self.request = request
- self.viz_type = form_data.get("viz_type")
- self.form_data = form_data
-
- self.query = ""
- self.token = utils.get_form_data_token(form_data)
-
- self.groupby: list[Column] = self.form_data.get("groupby") or []
- self.time_shift = timedelta()
-
- self.status: str | None = None
- self.error_msg = ""
- self.results: QueryResult | None = None
- self.applied_filter_columns: list[Column] = []
- self.rejected_filter_columns: list[Column] = []
- self.errors: list[dict[str, Any]] = []
- self.force = force
- self._force_cached = force_cached
- self.from_dttm: datetime | None = None
- self.to_dttm: datetime | None = None
- self._extra_chart_data: list[tuple[str, pd.DataFrame]] = []
-
- self.process_metrics()
-
- self.applied_filters: list[dict[str, str]] = []
- self.rejected_filters: list[dict[str, str]] = []
-
- @property
- @deprecated(deprecated_in="3.0")
- def force_cached(self) -> bool:
- return self._force_cached
-
- @deprecated(deprecated_in="3.0")
- def process_metrics(self) -> None:
- # metrics in Viz is order sensitive, so metric_dict should be
- # OrderedDict
- self.metric_dict = OrderedDict()
- for mkey in METRIC_KEYS:
- val = self.form_data.get(mkey)
- if val:
- if not isinstance(val, list):
- val = [val]
- for o in val:
- label = utils.get_metric_name(o)
- self.metric_dict[label] = o
-
- # Cast to list needed to return serializable object in py3
- self.all_metrics = list(self.metric_dict.values())
- self.metric_labels = list(self.metric_dict.keys())
-
- @staticmethod
- @deprecated(deprecated_in="3.0")
- def handle_js_int_overflow(
- data: dict[str, list[dict[str, Any]]],
- ) -> dict[str, list[dict[str, Any]]]:
- for record in data.get("records", {}):
- for k, v in list(record.items()):
- if isinstance(v, int):
- # if an int is too big for Java Script to handle
- # convert it to a string
- if abs(v) > JS_MAX_INTEGER:
- record[k] = str(v)
- return data
-
- @deprecated(deprecated_in="3.0")
- def run_extra_queries(self) -> None:
- """Lifecycle method to use when more than one query is needed
-
- In rare-ish cases, a visualization may need to execute multiple
- queries. That is the case for FilterBox or for time comparison
- in Line chart for instance.
-
- In those cases, we need to make sure these queries run before the
- main `get_payload` method gets called, so that the overall caching
- metadata can be right. The way it works here is that if any of
- the previous `get_df_payload` calls hit the cache, the main
- payload's metadata will reflect that.
-
- The multi-query support may need more work to become a first class
- use case in the framework, and for the UI to reflect the subtleties
- (show that only some of the queries were served from cache for
- instance). In the meantime, since multi-query is rare, we treat
- it with a bit of a hack. Note that the hack became necessary
- when moving from caching the visualization's data itself, to caching
- the underlying query(ies).
- """
-
- @deprecated(deprecated_in="3.0")
- def apply_rolling(self, df: pd.DataFrame) -> pd.DataFrame:
- rolling_type = self.form_data.get("rolling_type")
- rolling_periods = int(self.form_data.get("rolling_periods") or 0)
- min_periods = int(self.form_data.get("min_periods") or 0)
-
- if rolling_type in ("mean", "std", "sum") and rolling_periods:
- kwargs = {"window": rolling_periods, "min_periods": min_periods}
- if rolling_type == "mean":
- df = df.rolling(**kwargs).mean()
- elif rolling_type == "std":
- df = df.rolling(**kwargs).std()
- elif rolling_type == "sum":
- df = df.rolling(**kwargs).sum()
- elif rolling_type == "cumsum":
- df = df.cumsum()
- if min_periods:
- df = df[min_periods:]
- if df.empty:
- raise QueryObjectValidationError(
- _(
- "Applied rolling window did not return any data. Please make sure "
- "the source query satisfies the minimum periods defined in the "
- "rolling window."
- )
- )
- return df
-
- @deprecated(deprecated_in="3.0")
- def get_samples(self) -> dict[str, Any]:
- query_obj = self.query_obj()
- query_obj.update(
- {
- "is_timeseries": False,
- "groupby": [],
- "metrics": [],
- "orderby": [],
- "row_limit": current_app.config["SAMPLES_ROW_LIMIT"],
- "columns": [o.column_name for o in self.datasource.columns],
- "from_dttm": None,
- "to_dttm": None,
- }
- )
- payload = self.get_df_payload(query_obj) # leverage caching logic
- return {
- "data": payload["df"].to_dict(orient="records"),
- "colnames": payload.get("colnames"),
- "coltypes": payload.get("coltypes"),
- "rowcount": payload.get("rowcount"),
- "sql_rowcount": payload.get("sql_rowcount"),
- }
-
- @deprecated(deprecated_in="3.0")
- def get_df(self, query_obj: QueryObjectDict | None = None) -> pd.DataFrame:
- """Returns a pandas dataframe based on the query object"""
- if not query_obj:
- query_obj = self.query_obj()
- if not query_obj:
- return pd.DataFrame()
-
- self.error_msg = ""
-
- timestamp_format = None
- if self.datasource.type == "table":
- granularity_col = self.datasource.get_column(query_obj["granularity"])
- if granularity_col:
- timestamp_format = granularity_col.python_date_format
-
- # The datasource here can be different backend but the interface is common
- self.results = self.datasource.query(query_obj)
- self.applied_filter_columns = self.results.applied_filter_columns or []
- self.rejected_filter_columns = self.results.rejected_filter_columns or []
- self.query = self.results.query
- self.status = self.results.status
- self.errors = self.results.errors
-
- df = self.results.df
- # Transform the timestamp we received from database to pandas supported
- # datetime format. If no python_date_format is specified, the pattern will
- # be considered as the default ISO date format
- # If the datetime format is unix, the parse will use the corresponding
- # parsing logic.
- if not df.empty:
- utils.normalize_dttm_col(
- df=df,
- dttm_cols=tuple( # noqa: C409
- [
- DateColumn.get_legacy_time_column(
- timestamp_format=timestamp_format,
- offset=self.datasource.offset,
- time_shift=self.form_data.get("time_shift"),
- )
- ]
- ),
- )
-
- if self.enforce_numerical_metrics:
- self.df_metrics_to_num(df)
-
- df.replace([np.inf, -np.inf], np.nan, inplace=True)
- return df
-
- @deprecated(deprecated_in="3.0")
- def df_metrics_to_num(self, df: pd.DataFrame) -> None:
- """Converting metrics to numeric when pandas.read_sql cannot"""
- metrics = self.metric_labels
- for col, dtype in df.dtypes.items():
- if dtype.type == np.object_ and col in metrics:
- df[col] = pd.to_numeric(df[col], errors="coerce")
-
- @deprecated(deprecated_in="3.0")
- def process_query_filters(self) -> None:
- utils.convert_legacy_filters_into_adhoc(self.form_data)
- merge_extra_filters(self.form_data)
- engine = self.datasource.database.db_engine_spec.engine
- utils.split_adhoc_filters_into_base_filters(self.form_data, engine)
-
- @staticmethod
- @deprecated(deprecated_in="3.0")
- def dedup_columns(*columns_args: list[Column] | None) -> list[Column]:
- # dedup groupby and columns while preserving order
- labels: list[str] = []
- deduped_columns: list[Column] = []
- for columns in columns_args:
- for column in columns or []:
- label = get_column_name(column)
- if label not in labels:
- deduped_columns.append(column)
- return deduped_columns
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict: # pylint: disable=too-many-locals
- """Building a query object"""
- self.process_query_filters()
-
- metrics = self.all_metrics or []
-
- groupby = self.dedup_columns(self.groupby, self.form_data.get("columns"))
-
- is_timeseries = self.is_timeseries
-
- if DTTM_ALIAS in (groupby_labels := get_column_names(groupby)):
- del groupby[groupby_labels.index(DTTM_ALIAS)]
- is_timeseries = True
-
- granularity = self.form_data.get("granularity_sqla")
- limit = int(self.form_data.get("limit") or 0)
- timeseries_limit_metric = self.form_data.get("timeseries_limit_metric")
-
- # apply row limit to query
- row_limit = int(
- self.form_data.get("row_limit") or current_app.config["ROW_LIMIT"]
- )
- row_limit = apply_max_row_limit(row_limit)
-
- # default order direction
- order_desc = self.form_data.get("order_desc", True)
-
- try:
- since, until = get_since_until(
- relative_start=current_app.config["DEFAULT_RELATIVE_START_TIME"],
- relative_end=current_app.config["DEFAULT_RELATIVE_END_TIME"],
- time_range=self.form_data.get("time_range"),
- since=self.form_data.get("since"),
- until=self.form_data.get("until"),
- )
- except ValueError as ex:
- raise QueryObjectValidationError(str(ex)) from ex
-
- time_shift = self.form_data.get("time_shift", "")
- self.time_shift = parse_past_timedelta(time_shift)
- from_dttm = None if since is None else (since - self.time_shift)
- to_dttm = None if until is None else (until - self.time_shift)
- if from_dttm and to_dttm and from_dttm > to_dttm:
- raise QueryObjectValidationError(
- _("From date cannot be larger than to date")
- )
-
- self.from_dttm = from_dttm
- self.to_dttm = to_dttm
-
- # validate sql filters
- for param in ("where", "having"):
- clause = self.form_data.get(param)
- if clause:
- engine = self.datasource.database.db_engine_spec.engine
- sanitized_clause = sanitize_clause(clause, engine)
- if sanitized_clause != clause:
- self.form_data[param] = sanitized_clause
-
- # extras are used to query elements specific to a datasource type
- # for instance the extra where clause that applies only to Tables
- extras = {
- "having": self.form_data.get("having", ""),
- "time_grain_sqla": self.form_data.get("time_grain_sqla"),
- "where": self.form_data.get("where", ""),
- }
-
- return {
- "granularity": granularity,
- "from_dttm": from_dttm,
- "to_dttm": to_dttm,
- "is_timeseries": is_timeseries,
- "groupby": groupby,
- "metrics": metrics,
- "row_limit": row_limit,
- "filter": self.form_data.get("filters", []),
- "series_limit": limit,
- "extras": extras,
- "series_limit_metric": timeseries_limit_metric,
- "order_desc": order_desc,
- }
-
- @property
- @deprecated(deprecated_in="3.0")
- def cache_timeout(self) -> int:
- if self.form_data.get("cache_timeout") is not None:
- return int(self.form_data["cache_timeout"])
- if self.datasource.cache_timeout is not None:
- return self.datasource.cache_timeout
- if (
- hasattr(self.datasource, "database")
- and self.datasource.database.cache_timeout
- ) is not None:
- return self.datasource.database.cache_timeout
- if (
- current_app.config["DATA_CACHE_CONFIG"].get("CACHE_DEFAULT_TIMEOUT")
- is not None
- ):
- return current_app.config["DATA_CACHE_CONFIG"]["CACHE_DEFAULT_TIMEOUT"]
- return current_app.config["CACHE_DEFAULT_TIMEOUT"]
-
- @deprecated(deprecated_in="3.0")
- def get_json(self) -> str:
- return json.dumps(
- self.get_payload(), default=json.json_int_dttm_ser, ignore_nan=True
- )
-
- @deprecated(deprecated_in="3.0")
- def cache_key(self, query_obj: QueryObjectDict, **extra: Any) -> str:
- """
- The cache key is made out of the key/values in `query_obj`, plus any
- other key/values in `extra`.
-
- We remove datetime bounds that are hard values, and replace them with
- the use-provided inputs to bounds, which may be time-relative (as in
- "5 days ago" or "now").
-
- The `extra` arguments are currently used by time shift queries, since
- different time shifts will differ only in the `from_dttm`, `to_dttm`,
- `inner_from_dttm`, and `inner_to_dttm` values which are stripped.
- """
- # Cast to dict[str, Any] to allow mutable operations (update, del)
- # since TypedDict doesn't support these operations in the same way
- cache_dict: dict[str, Any] = copy.copy(cast(dict[str, Any], query_obj))
- cache_dict.update(extra)
-
- for k in ["from_dttm", "to_dttm", "inner_from_dttm", "inner_to_dttm"]:
- if k in cache_dict:
- del cache_dict[k]
-
- cache_dict["time_range"] = self.form_data.get("time_range")
- cache_dict["datasource"] = self.datasource.uid
- cache_dict["extra_cache_keys"] = self.datasource.get_extra_cache_keys(query_obj)
- cache_dict["rls"] = security_manager.get_rls_cache_key(self.datasource)
- cache_dict["changed_on"] = self.datasource.changed_on
-
- # Add an impersonation key to cache if impersonation is enabled on the db
- # or if the CACHE_QUERY_BY_USER flag is on or per_user_caching is enabled on
- # the database
- try:
- add_impersonation_cache_key_if_needed(self.datasource.database, cache_dict)
- except AttributeError:
- # datasource or database do not exist
- pass
-
- json_data = self.json_dumps(cache_dict, sort_keys=True)
- return hash_from_str(json_data)
-
- @deprecated(deprecated_in="3.0")
- def get_payload(self, query_obj: QueryObjectDict | None = None) -> VizPayload:
- """Returns a payload of metadata and data"""
-
- try:
- self.run_extra_queries()
- except SupersetSecurityException as ex:
- error = dataclasses.asdict(ex.error)
- self.errors.append(error)
- self.status = QueryStatus.FAILED
-
- payload = self.get_df_payload(query_obj)
-
- # if payload does not have a df, we are raising an error here.
- df = cast(Optional[pd.DataFrame], payload["df"])
-
- if self.status != QueryStatus.FAILED:
- payload["data"] = self.get_data(df)
- if "df" in payload:
- del payload["df"]
-
- applied_filter_columns = self.applied_filter_columns or []
- rejected_filter_columns = self.rejected_filter_columns or []
- applied_time_extras = self.form_data.get("applied_time_extras", {})
- applied_time_columns, rejected_time_columns = utils.get_time_filter_status(
- self.datasource, applied_time_extras
- )
- payload["applied_filters"] = [
- {"column": get_column_name(col)} for col in applied_filter_columns
- ] + applied_time_columns
- payload["rejected_filters"] = [
- {
- "reason": ExtraFiltersReasonType.COL_NOT_IN_DATASOURCE,
- "column": get_column_name(col),
- }
- for col in rejected_filter_columns
- ] + rejected_time_columns
- if df is not None:
- payload["colnames"] = list(df.columns)
-
- return payload
-
- @deprecated(deprecated_in="3.0")
- def get_df_payload( # pylint: disable=too-many-statements # noqa: C901
- self, query_obj: QueryObjectDict | None = None, **kwargs: Any
- ) -> dict[str, Any]:
- """Handles caching around the df payload retrieval"""
- if not query_obj:
- query_obj = self.query_obj()
- cache_key = self.cache_key(query_obj, **kwargs) if query_obj else None
- cache_value = None
- logger.info("Cache key: %s", cache_key)
- is_loaded = False
- stacktrace = None
- df = None
- cache_timeout = self.cache_timeout
- force = self.force or cache_timeout == CACHE_DISABLED_TIMEOUT
- if cache_key and cache_manager.data_cache and not force:
- cache_value = cache_manager.data_cache.get(cache_key)
- if cache_value:
- current_app.config["STATS_LOGGER"].incr("loading_from_cache")
- try:
- df = cache_value["df"]
- self.query = cache_value["query"]
- self.applied_filter_columns = cache_value.get(
- "applied_filter_columns", []
- )
- self.rejected_filter_columns = cache_value.get(
- "rejected_filter_columns", []
- )
- self.status = QueryStatus.SUCCESS
- is_loaded = True
- current_app.config["STATS_LOGGER"].incr("loaded_from_cache")
- except Exception as ex: # pylint: disable=broad-except
- logger.exception(ex)
- logger.error(
- "Error reading cache: %s",
- utils.error_msg_from_exception(ex),
- exc_info=True,
- )
- logger.info("Serving from cache")
-
- if query_obj and not is_loaded:
- if self.force_cached:
- logger.warning(
- "force_cached (viz.py): value not found for cache key %s",
- cache_key,
- )
- raise CacheLoadError(_("Cached value not found"))
- try:
- invalid_columns = [
- col
- for col in get_column_names_from_columns(
- query_obj.get("columns") or []
- )
- + get_column_names_from_columns(query_obj.get("groupby") or [])
- + utils.get_column_names_from_metrics(
- cast(list[Metric], query_obj.get("metrics") or [])
- )
- if col not in self.datasource.column_names
- ]
- if invalid_columns:
- raise QueryObjectValidationError(
- _(
- "Columns missing in datasource: %(invalid_columns)s",
- invalid_columns=invalid_columns,
- )
- )
- df = self.get_df(query_obj)
- if self.status != QueryStatus.FAILED:
- current_app.config["STATS_LOGGER"].incr("loaded_from_source")
- if not self.force:
- current_app.config["STATS_LOGGER"].incr(
- "loaded_from_source_without_force"
- )
- is_loaded = True
- except QueryObjectValidationError as ex:
- error = dataclasses.asdict(
- SupersetError(
- message=str(ex),
- level=ErrorLevel.ERROR,
- error_type=SupersetErrorType.VIZ_GET_DF_ERROR,
- )
- )
- self.errors.append(error)
- self.status = QueryStatus.FAILED
- except SupersetErrorException:
- # Let structured Superset errors (e.g. OAuth2RedirectError) propagate
- # so the global Flask error handler serializes them.
- raise
- except Exception as ex: # pylint: disable=broad-except
- logger.exception(ex)
-
- error = dataclasses.asdict(
- SupersetError(
- message=str(ex),
- level=ErrorLevel.ERROR,
- error_type=SupersetErrorType.VIZ_GET_DF_ERROR,
- )
- )
- self.errors.append(error)
- self.status = QueryStatus.FAILED
- # Only expose the raw stacktrace when explicitly enabled, mirroring
- # the gating used elsewhere (e.g. superset.views.base.get_error_msg).
- # ``get_stacktrace()`` itself returns ``None`` unless SHOW_STACKTRACE
- # is set, so gating purely on that config keeps the two consistent.
- if current_app.config.get("SHOW_STACKTRACE"):
- stacktrace = utils.get_stacktrace()
-
- if is_loaded and cache_key and self.status != QueryStatus.FAILED:
- set_and_log_cache(
- cache_instance=cache_manager.data_cache,
- cache_key=cache_key,
- cache_value={"df": df, "query": self.query},
- cache_timeout=cache_timeout,
- datasource_uid=self.datasource.uid,
- )
- return {
- "cache_key": cache_key,
- "cached_dttm": cache_value["dttm"] if cache_value is not None else None,
- "cache_timeout": cache_timeout,
- "df": df,
- "errors": self.errors,
- "form_data": self.form_data,
- "is_cached": cache_value is not None,
- "query": self.query,
- "from_dttm": self.from_dttm,
- "to_dttm": self.to_dttm,
- "status": self.status,
- "stacktrace": stacktrace,
- "rowcount": len(df.index) if df is not None else 0,
- "colnames": list(df.columns) if df is not None else None,
- "coltypes": (
- utils.extract_dataframe_dtypes(df, self.datasource)
- if df is not None
- else None
- ),
- }
-
- @staticmethod
- @deprecated(deprecated_in="3.0")
- def json_dumps(query_obj: Any, sort_keys: bool = False) -> str:
- return json.dumps(
- query_obj,
- default=json.json_int_dttm_ser,
- ignore_nan=True,
- sort_keys=sort_keys,
- )
-
- @staticmethod
- @deprecated(deprecated_in="3.0")
- def has_error(payload: VizPayload) -> bool:
- return (
- payload.get("status") == QueryStatus.FAILED
- or payload.get("error") is not None
- or bool(payload.get("errors"))
- )
-
- @deprecated(deprecated_in="3.0")
- def payload_json_and_has_error(self, payload: VizPayload) -> tuple[str, bool]:
- return self.json_dumps(payload), self.has_error(payload)
-
- @property
- @deprecated(deprecated_in="3.0")
- def data(self) -> dict[str, Any]:
- """This is the data object serialized to the js layer"""
- content = {
- "form_data": self.form_data,
- "token": self.token,
- "viz_name": self.viz_type,
- "filter_select_enabled": self.datasource.filter_select_enabled,
- }
- return content
-
- @deprecated(deprecated_in="3.0")
- def get_csv(self) -> str | None:
- df = self.get_df_payload()["df"] # leverage caching logic
- include_index = not isinstance(df.index, pd.RangeIndex)
- return csv.df_to_escaped_csv(
- df, index=include_index, **current_app.config["CSV_EXPORT"]
- )
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- return df.to_dict(orient="records")
-
- @property
- @deprecated(deprecated_in="3.0")
- def json_data(self) -> str:
- return json.dumps(self.data)
-
- @deprecated(deprecated_in="3.0")
- def raise_for_access(self) -> None:
- """
- Raise an exception if the user cannot access the resource.
-
- :raises SupersetSecurityException: If the user cannot access the resource
- """
-
- security_manager.raise_for_access(viz=self)
-
-
-class TimeTableViz(BaseViz):
- """A data table with rich time-series related columns"""
-
- viz_type = "time_table"
- verbose_name = _("Time Table View")
- credits = 'a <a href="https://github.com/airbnb/superset">Superset</a> original'
- is_timeseries = True
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- query_obj = super().query_obj()
-
- if not self.form_data.get("metrics"):
- raise QueryObjectValidationError(_("Pick at least one metric"))
-
- if self.form_data.get("groupby") and len(self.form_data["metrics"]) > 1:
- raise QueryObjectValidationError(
- _("When using 'Group By' you are limited to use a single metric")
- )
-
- sort_by = utils.get_first_metric_name(query_obj["metrics"])
- is_asc = not query_obj.get("order_desc")
- query_obj["orderby"] = [(sort_by, is_asc)]
-
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- if df.empty:
- return None
-
- columns = None
- values: list[str] | str = self.metric_labels
- if self.form_data.get("groupby"):
- values = self.metric_labels[0]
- columns = get_column_names(self.form_data.get("groupby"))
- pt = df.pivot_table(index=DTTM_ALIAS, columns=columns, values=values)
- pt.index = pt.index.map(str)
- pt = pt.sort_index()
- if isinstance(pt.columns, pd.MultiIndex):
- pt.columns = [
- FLAT_COLUMN_SEPARATOR.join(escape_separator(str(s)) for s in col)
- for col in pt.columns
- ]
- return {
- "records": pt.to_dict(orient="index"),
- "columns": list(pt.columns),
- "is_group_by": bool(self.form_data.get("groupby")),
- }
-
-
-class CalHeatmapViz(BaseViz):
- """Calendar heatmap."""
-
- viz_type = "cal_heatmap"
- verbose_name = _("Calendar Heatmap")
- credits = "<a href=https://github.com/wa0x6e/cal-heatmap>cal-heatmap</a>"
- is_timeseries = True
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData: # pylint: disable=too-many-locals # noqa: C901
- if df.empty:
- return None
-
- form_data = self.form_data
- data = {}
- records = df.to_dict("records")
- for metric in self.metric_labels:
- values = {}
- for query_obj in records:
- v = query_obj[DTTM_ALIAS]
- if hasattr(v, "value"):
- v = v.value
- values[str(v / 10**9)] = query_obj.get(metric)
- data[metric] = values
-
- try:
- start, end = get_since_until(
- relative_start=current_app.config["DEFAULT_RELATIVE_START_TIME"],
- relative_end=current_app.config["DEFAULT_RELATIVE_END_TIME"],
- time_range=form_data.get("time_range"),
- since=form_data.get("since"),
- until=form_data.get("until"),
- )
- except ValueError as ex:
- raise QueryObjectValidationError(str(ex)) from ex
- if not start or not end:
- raise QueryObjectValidationError(
- "Please provide both time bounds (Since and Until)"
- )
- domain = form_data.get("domain_granularity")
- diff_delta = rdelta.relativedelta(end, start)
- diff_secs = (end - start).total_seconds()
-
- if domain == "year":
- range_ = end.year - start.year + 1
- elif domain == "month":
- range_ = diff_delta.years * 12 + diff_delta.months + 1
- elif domain == "week":
- range_ = diff_delta.years * 53 + diff_delta.weeks + 1
- elif domain == "day":
- range_ = diff_secs // (24 * 60 * 60) + 1 # type: ignore
- else:
- range_ = diff_secs // (60 * 60) + 1 # type: ignore
-
- return {
- "data": data,
- "start": start,
- "domain": domain,
- "subdomain": form_data.get("subdomain_granularity"),
- "range": range_,
- }
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- query_obj = super().query_obj()
- query_obj["metrics"] = self.form_data.get("metrics")
- mapping = {
- "min": "PT1M",
- "hour": "PT1H",
- "day": "P1D",
- "week": "P1W",
- "month": "P1M",
- "year": "P1Y",
- }
- query_obj["extras"]["time_grain_sqla"] = mapping[
- self.form_data.get("subdomain_granularity", "min")
- ]
- return query_obj
-
-
-class NVD3Viz(BaseViz):
- """Base class for all nvd3 vizs"""
-
- credits = '<a href="http://nvd3.org/">NVD3.org</a>'
- viz_type: str | None = None
- verbose_name = "Base NVD3 Viz"
- is_timeseries = False
-
-
-class BulletViz(NVD3Viz):
- """Based on the NVD3 bullet chart"""
-
- viz_type = "bullet"
- verbose_name = _("Bullet Chart")
- is_timeseries = False
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- form_data = self.form_data
- query_obj = super().query_obj()
- self.metric = form_data[ # pylint: disable=attribute-defined-outside-init
- "metric"
- ]
-
- query_obj["metrics"] = [self.metric]
- if not self.metric:
- raise QueryObjectValidationError(_("Pick a metric to display"))
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- if df.empty:
- return None
- df["metric"] = df[[utils.get_metric_name(self.metric)]]
- values = df["metric"].values
- return {
- "measures": values.tolist(),
- }
-
-
-class NVD3TimeSeriesViz(NVD3Viz):
- """A rich line chart component with tons of options"""
-
- viz_type = "line"
- verbose_name = _("Time Series - Line Chart")
- sort_series = False
- is_timeseries = True
- pivot_fill_value: int | None = None
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- query_obj = super().query_obj()
- sort_by = self.form_data.get(
- "timeseries_limit_metric"
- ) or utils.get_first_metric_name(query_obj.get("metrics") or [])
- is_asc = not self.form_data.get("order_desc")
- if sort_by:
- sort_by_label = utils.get_metric_name(sort_by)
- if sort_by_label not in utils.get_metric_names(query_obj["metrics"]):
- query_obj["metrics"].append(sort_by)
- query_obj["orderby"] = [(sort_by, is_asc)]
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def to_series( # pylint: disable=too-many-branches # noqa: C901
- self, df: pd.DataFrame, classed: str = "", title_suffix: str = ""
- ) -> list[dict[str, Any]]:
- cols = []
- for col in df.columns:
- if col == "":
- cols.append("N/A")
- elif col is None:
- cols.append("NULL")
- else:
- cols.append(col)
- df.columns = cols
- series = df.to_dict("series")
-
- chart_data = []
- for name in df.T.index.tolist():
- ys = series[name]
- if df[name].dtype.kind not in "biufc":
- continue
- series_title: list[str] | str | tuple[str, ...]
- if isinstance(name, list):
- series_title = [str(title) for title in name]
- elif isinstance(name, tuple):
- series_title = tuple(str(title) for title in name)
- else:
- series_title = str(name)
- if (
- isinstance(series_title, (list, tuple))
- and len(series_title) > 1
- and len(self.metric_labels) == 1
- ):
- # Removing metric from series name if only one metric
- series_title = series_title[1:]
- if title_suffix:
- if isinstance(series_title, str):
- series_title = (series_title, title_suffix)
- elif isinstance(series_title, list):
- series_title = series_title + [title_suffix]
- elif isinstance(series_title, tuple):
- series_title = series_title + (title_suffix,)
-
- values = []
- non_nan_cnt = 0
- for ds in df.index:
- if ds in ys:
- data = {"x": ds, "y": ys[ds]}
- if not np.isnan(ys[ds]):
- non_nan_cnt += 1
- else:
- data = {}
- values.append(data)
-
- if non_nan_cnt == 0:
- continue
-
- data = {"key": series_title, "values": values}
- if classed:
- data["classed"] = classed
- chart_data.append(data)
- return chart_data
-
- @deprecated(deprecated_in="3.0")
- def process_data(self, df: pd.DataFrame, aggregate: bool = False) -> VizData:
- if df.empty:
- return df
-
- if aggregate:
- df = df.pivot_table(
- index=DTTM_ALIAS,
- columns=get_column_names(self.form_data.get("groupby")),
- values=self.metric_labels,
- fill_value=0,
- aggfunc=sum,
- )
- else:
- df = df.pivot_table(
- index=DTTM_ALIAS,
- columns=get_column_names(self.form_data.get("groupby")),
- values=self.metric_labels,
- fill_value=self.pivot_fill_value,
- )
-
- rule = self.form_data.get("resample_rule")
- method = self.form_data.get("resample_method")
-
- if rule and method:
- # ``method`` comes straight from ``form_data`` and may be a
- # non-string (e.g. a list) for malformed requests; guard the
- # membership test so unsupported input returns a controlled
- # validation error instead of an unhashable-type ``TypeError``.
- if not isinstance(method, str) or method not in ALLOWED_RESAMPLE_METHODS:
- raise QueryObjectValidationError(
- _(
- "Resample method '%(method)s' is not supported.",
- method=method,
- )
- )
- df = getattr(df.resample(rule), method)()
-
- if self.sort_series:
- dfs = df.sum()
- dfs.sort_values(ascending=False, inplace=True)
- df = df[dfs.index]
-
- df = self.apply_rolling(df)
- if self.form_data.get("contribution"):
- dft = df.T
- df = (dft / dft.sum()).T
-
- return df
-
- @deprecated(deprecated_in="3.0")
- def run_extra_queries(self) -> None:
- time_compare = self.form_data.get("time_compare") or []
- # backwards compatibility
- if not isinstance(time_compare, list):
- time_compare = [time_compare]
-
- max_time_compare = current_app.config["VIZ_TIME_COMPARE_MAX"]
- if len(time_compare) > max_time_compare:
- raise QueryObjectValidationError(
- _(
- "Too many time comparisons requested. The maximum allowed is "
- "%(max)s, but %(count)s were requested.",
- max=max_time_compare,
- count=len(time_compare),
- )
- )
-
- for option in time_compare:
- query_object = self.query_obj()
- try:
- delta = parse_past_timedelta(option)
- except ValueError as ex:
- raise QueryObjectValidationError(str(ex)) from ex
- query_object["inner_from_dttm"] = query_object["from_dttm"]
- query_object["inner_to_dttm"] = query_object["to_dttm"]
-
- if not query_object["from_dttm"] or not query_object["to_dttm"]:
- raise QueryObjectValidationError(
- _(
- "An enclosed time range (both start and end) must be specified "
- "when using a Time Comparison."
- )
- )
- query_object["from_dttm"] -= delta
- query_object["to_dttm"] -= delta
-
- df2 = self.get_df_payload(query_object, time_compare=option).get("df")
- if df2 is not None and DTTM_ALIAS in df2:
- dttm_series = df2[DTTM_ALIAS] + delta
- df2 = df2.drop(DTTM_ALIAS, axis=1)
- df2 = pd.concat([dttm_series, df2], axis=1)
- label = f"{option} offset"
- df2 = self.process_data(df2)
- self._extra_chart_data.append((label, df2))
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- comparison_type = self.form_data.get("comparison_type") or "values"
- df = self.process_data(df)
- if comparison_type == "values":
- # Filter out series with all NaN
- chart_data = self.to_series(df.dropna(axis=1, how="all"))
-
- for i, (label, df2) in enumerate(self._extra_chart_data):
- chart_data.extend(
- self.to_series(df2, classed=f"time-shift-{i}", title_suffix=label)
- )
- else:
- chart_data = []
- for i, (label, df2) in enumerate(self._extra_chart_data):
- # reindex df2 into the df2 index
- combined_index = df.index.union(df2.index)
- df2 = (
- df2.reindex(combined_index)
- .interpolate(method="time")
- .reindex(df.index)
- )
-
- if comparison_type == "absolute":
- diff = df - df2
- elif comparison_type == "percentage":
- diff = (df - df2) / df2
- elif comparison_type == "ratio":
- diff = df / df2
- else:
- raise QueryObjectValidationError(
- f"Invalid `comparison_type`: {comparison_type}"
- )
-
- # remove leading/trailing NaNs from the time shift difference
- diff = diff[diff.first_valid_index() : diff.last_valid_index()]
-
- chart_data.extend(
- self.to_series(diff, classed=f"time-shift-{i}", title_suffix=label)
- )
-
- if not self.sort_series:
- chart_data = sorted(chart_data, key=lambda x: tuple(x["key"]))
- return chart_data
-
-
-class NVD3TimePivotViz(NVD3TimeSeriesViz):
- """Time Series - Periodicity Pivot"""
-
- viz_type = "time_pivot"
- sort_series = True
- verbose_name = _("Time Series - Period Pivot")
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- query_obj = super().query_obj()
- query_obj["metrics"] = [self.form_data.get("metric")]
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- if df.empty:
- return None
-
- df = self.process_data(df)
- freq = to_offset(self.form_data.get("freq"))
- try:
- freq = type(freq)(freq.n, normalize=True, **freq.kwds)
- except ValueError:
- freq = type(freq)(freq.n, **freq.kwds)
- df.index.name = None
- df[DTTM_ALIAS] = df.index.map(freq.rollback)
- df["ranked"] = df[DTTM_ALIAS].rank(method="dense", ascending=False) - 1
- df.ranked = df.ranked.map(int)
- df["series"] = "-" + df.ranked.map(str)
- df["series"] = df["series"].str.replace("-0", "current")
- rank_lookup = {
- row["series"]: row["ranked"] for row in df.to_dict(orient="records")
- }
- max_ts = df[DTTM_ALIAS].max()
- max_rank = df["ranked"].max()
- df[DTTM_ALIAS] = df.index + (max_ts - df[DTTM_ALIAS])
- df = df.pivot_table(
- index=DTTM_ALIAS,
- columns="series",
- values=utils.get_metric_name(self.form_data["metric"]),
- )
- chart_data = self.to_series(df)
- for series in chart_data:
- series["rank"] = rank_lookup[series["key"]]
- series["perc"] = 1 - (series["rank"] / (max_rank + 1))
- return chart_data
-
-
-class ChordViz(BaseViz):
- """A Chord diagram"""
-
- viz_type = "chord"
- verbose_name = _("Directed Force Layout")
- credits = '<a href="https://github.com/d3/d3-chord">Bostock</a>'
- is_timeseries = False
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- query_obj = super().query_obj()
- query_obj["groupby"] = [
- self.form_data.get("groupby"),
- self.form_data.get("columns"),
- ]
- query_obj["metrics"] = [self.form_data.get("metric")]
- if self.form_data.get("sort_by_metric", False):
- query_obj["orderby"] = [(query_obj["metrics"][0], False)]
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- if df.empty:
- return None
-
- df.columns = ["source", "target", "value"]
-
- # Preparing a symmetrical matrix like d3.chords calls for
- nodes = list(set(df["source"]) | set(df["target"]))
- matrix = {}
- for source, target in product(nodes, nodes):
- matrix[(source, target)] = 0
- for source, target, value in df.to_records(index=False):
- matrix[(source, target)] = value
- return {
- "nodes": list(nodes),
- "matrix": [[matrix[(n1, n2)] for n1 in nodes] for n2 in nodes],
- }
-
-
-class CountryMapViz(BaseViz):
- """A country centric"""
-
- viz_type = "country_map"
- verbose_name = _("Country Map")
- is_timeseries = False
- credits = "From bl.ocks.org By john-guerra"
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- query_obj = super().query_obj()
- metric = self.form_data.get("metric")
- entity = self.form_data.get("entity")
- if not self.form_data.get("select_country"):
- raise QueryObjectValidationError("Must specify a country")
- if not metric:
- raise QueryObjectValidationError("Must specify a metric")
- if not entity:
- raise QueryObjectValidationError("Must provide ISO codes")
- query_obj["metrics"] = [metric]
- query_obj["groupby"] = [entity]
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- if df.empty:
- return None
- cols = get_column_names([self.form_data.get("entity")]) # type: ignore
- metric = self.metric_labels[0]
- cols += [metric]
- ndf = df[cols]
- df = ndf
- df.columns = ["country_id", "metric"]
- return df.to_dict(orient="records")
-
-
-class WorldMapViz(BaseViz):
- """A country centric world map"""
-
- viz_type = "world_map"
- verbose_name = _("World Map")
- is_timeseries = False
- credits = 'datamaps on <a href="https://www.npmjs.com/package/datamaps">npm</a>'
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- query_obj = super().query_obj()
- query_obj["groupby"] = [self.form_data["entity"]]
- if self.form_data.get("sort_by_metric", False):
- query_obj["orderby"] = [(query_obj["metrics"][0], False)]
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- if df.empty:
- return None
-
- # pylint: disable=import-outside-toplevel
- from superset.examples import countries
-
- cols = get_column_names([self.form_data.get("entity")]) # type: ignore
- metric = utils.get_metric_name(self.form_data["metric"])
- secondary_metric = (
- utils.get_metric_name(self.form_data["secondary_metric"])
- if self.form_data.get("secondary_metric")
- else None
- )
- columns = ["country", "m1", "m2"]
- if metric == secondary_metric:
- ndf = df[cols]
- ndf["m1"] = df[metric]
- ndf["m2"] = ndf["m1"]
- else:
- if secondary_metric:
- cols += [metric, secondary_metric]
- else:
- cols += [metric]
- columns = ["country", "m1"]
- ndf = df[cols]
- df = ndf
- df.columns = columns
- data = df.to_dict(orient="records")
- for row in data:
- country = None
- if isinstance(row["country"], str):
- if "country_fieldtype" in self.form_data:
- country = countries.get(
- self.form_data["country_fieldtype"], row["country"]
- )
- if country:
- row["code"] = country[self.form_data["country_fieldtype"]]
- row["country"] = country["cca3"]
- row["latitude"] = country["lat"]
- row["longitude"] = country["lng"]
- row["name"] = country["name"]
- else:
- row["country"] = "XXX"
- return data
-
-
-class ParallelCoordinatesViz(BaseViz):
- """Interactive parallel coordinate implementation
-
- Uses this amazing javascript library
- https://github.com/syntagmatic/parallel-coordinates
- """
-
- viz_type = "para"
- verbose_name = _("Parallel Coordinates")
- credits = (
- '<a href="https://syntagmatic.github.io/parallel-coordinates/">'
- "Syntagmatic's library</a>"
- )
- is_timeseries = False
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- query_obj = super().query_obj()
- query_obj["groupby"] = [self.form_data.get("series")]
- if sort_by := self.form_data.get("timeseries_limit_metric"):
- sort_by_label = utils.get_metric_name(sort_by)
- if sort_by_label not in utils.get_metric_names(query_obj["metrics"]):
- query_obj["metrics"].append(sort_by)
- if self.form_data.get("order_desc"):
- query_obj["orderby"] = [
- (sort_by, not self.form_data.get("order_desc", True))
- ]
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- return df.to_dict(orient="records")
-
-
-class HorizonViz(NVD3TimeSeriesViz):
- """Horizon chart
-
- https://www.npmjs.com/package/d3-horizon-chart
- """
-
- viz_type = "horizon"
- verbose_name = _("Horizon Charts")
- credits = (
- '<a href="https://www.npmjs.com/package/d3-horizon-chart">d3-horizon-chart</a>'
- )
-
-
-class DeckGLMultiLayer(BaseViz):
- """Pile on multiple DeckGL layers"""
-
- viz_type = "deck_multi"
- verbose_name = _("Deck.gl - Multiple Layers")
-
- is_timeseries = False
- credits = '<a href="https://uber.github.io/deck.gl/">deck.gl</a>'
-
- @staticmethod
- def _merge_filter_metadata(
- *filter_groups: list[dict[str, Any]] | None,
- ) -> list[dict[str, Any]]:
- """Merge multiple filter metadata lists, de-duplicating identical entries.
-
- Used to combine the applied/rejected filter metadata reported by each
- child layer into a single list for the multi-layer chart payload.
- """
- merged_filters: list[dict[str, Any]] = []
- seen_filters: set[str] = set()
-
- for filters in filter_groups:
- for filter_metadata in filters or []:
- if not isinstance(filter_metadata, dict):
- continue
-
- cache_key = json.dumps(filter_metadata, sort_keys=True)
- if cache_key in seen_filters:
- continue
-
- merged_filters.append(filter_metadata)
- seen_filters.add(cache_key)
-
- return merged_filters
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- return {}
-
- def _filter_items_by_scope(
- self,
- items: list[Any],
- layer_index: int,
- layer_filter_scope: dict[str, list[int]],
- ) -> list[Any]:
- """Filter items based on layer filter scope."""
- filtered_items = []
- for filter_item in items:
- filter_id = getattr(filter_item, "filterId", None)
- if filter_id:
- filter_scope = layer_filter_scope.get(filter_id, [])
- if filter_scope is None:
- filter_scope = []
- if not filter_scope or layer_index in filter_scope:
- filtered_items.append(filter_item)
- else:
- filtered_items.append(filter_item)
- return filtered_items
-
- def _process_extra_form_data_filters(
- self,
- layer_index: int,
- layer_filter_scope: dict[str, list[int]],
- filter_data_mapping: dict[str, list[Any]],
- extra_form_data: dict[str, Any],
- ) -> dict[str, Any]:
- """Process extra_form_data filters with layer-specific filtering."""
- if not extra_form_data or not filter_data_mapping:
- return extra_form_data
-
- filtered_extra_form_data_filters = []
- for filter_id, filter_scope in layer_filter_scope.items():
- if filter_scope is None:
- filter_scope = []
-
- if not filter_scope or layer_index in filter_scope:
- filters_from_this_filter = filter_data_mapping.get(filter_id, [])
- filtered_extra_form_data_filters.extend(filters_from_this_filter)
-
- return {
- **extra_form_data,
- "filters": filtered_extra_form_data_filters,
- }
-
- def _apply_layer_filtering(
- self, form_data: dict[str, Any], layer_index: int
- ) -> dict[str, Any]:
- """Apply layer-specific filtering to form data."""
- layer_filter_scope = self.form_data.get("layer_filter_scope", {})
- filter_data_mapping = self.form_data.get("filter_data_mapping", {})
-
- if not layer_filter_scope:
- form_data["extra_filters"] = self.form_data.get("extra_filters", [])
- form_data["adhoc_filters"] = self.form_data.get("adhoc_filters")
- form_data["extra_form_data"] = self.form_data.get("extra_form_data")
- return form_data
-
- filtered_extra_filters = self._filter_items_by_scope(
- self.form_data.get("extra_filters", []), layer_index, layer_filter_scope
- )
- filtered_adhoc_filters = self._filter_items_by_scope(
- self.form_data.get("adhoc_filters", []), layer_index, layer_filter_scope
- )
-
- extra_form_data = self.form_data.get("extra_form_data", {})
- filtered_extra_form_data = self._process_extra_form_data_filters(
- layer_index, layer_filter_scope, filter_data_mapping, extra_form_data
- )
-
- form_data["extra_filters"] = filtered_extra_filters
- form_data["adhoc_filters"] = filtered_adhoc_filters
- form_data["extra_form_data"] = filtered_extra_form_data
- return form_data
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- # Late imports to avoid circular import issues
- # pylint: disable=import-outside-toplevel
- from superset import db
- from superset.models.slice import Slice
-
- slice_ids = self.form_data.get("deck_slices") or []
- max_slices = current_app.config["DECK_MULTI_MAX_SLICES"]
- if len(slice_ids) > max_slices:
- raise QueryObjectValidationError(
- _(
- "Too many sub-slices requested. The maximum allowed is "
- "%(max)s, but %(count)s were requested.",
- max=max_slices,
- count=len(slice_ids),
- )
- )
- slices = db.session.query(Slice).filter(Slice.id.in_(slice_ids)).all()
-
- features: dict[str, list[Any]] = {}
- self.applied_filters = []
- self.rejected_filters = []
-
- for layer_index, slc in enumerate(slices):
- form_data = slc.form_data
- form_data = self._apply_layer_filtering(form_data, layer_index)
-
- viz_type_name = form_data.get("viz_type")
- viz_class = viz_types.get(viz_type_name)
- if not viz_class:
- continue # skip unknown viz types
-
- viz_instance = viz_class(datasource=slc.datasource, form_data=form_data)
- payload = viz_instance.get_payload()
- if payload:
- self.applied_filters = self._merge_filter_metadata(
- self.applied_filters,
- payload.get("applied_filters"),
- )
- self.rejected_filters = self._merge_filter_metadata(
- self.rejected_filters,
- payload.get("rejected_filters"),
- )
-
- if (
- payload
- and "data" in payload
- and payload["data"] is not None
- and "features" in payload["data"]
- ):
- if viz_type_name not in features:
- features[viz_type_name] = []
- features[viz_type_name].extend(payload["data"]["features"])
-
- return {
- "features": features,
- "mapboxApiKey": current_app.config["MAPBOX_API_KEY"],
- "slices": [slc.data for slc in slices if slc.data is not None],
- }
-
- @deprecated(deprecated_in="3.0")
- def get_payload(self, query_obj: QueryObjectDict | None = None) -> VizPayload:
- """Extend the base payload with merged child-layer filter metadata.
-
- The applied/rejected filter metadata collected from each sub-slice in
- ``get_data`` is merged into the base payload so dashboard filter badges
- reflect the filters applied across all layers.
- """
- payload = super().get_payload(query_obj)
- payload["applied_filters"] = self._merge_filter_metadata(
- payload.get("applied_filters"),
- self.applied_filters,
- )
- payload["rejected_filters"] = self._merge_filter_metadata(
- payload.get("rejected_filters"),
- self.rejected_filters,
- )
- return payload
-
-
-class BaseDeckGLViz(BaseViz):
- """Base class for deck.gl visualizations"""
-
- is_timeseries = False
- credits = '<a href="https://uber.github.io/deck.gl/">deck.gl</a>'
- spatial_control_keys: list[str] = []
-
- def _extract_tooltip_columns(self) -> list[str]:
- """Extract column names from tooltip_contents configuration."""
- tooltip_columns = []
- if tooltip_contents := self.form_data.get("tooltip_contents", []):
- for item in tooltip_contents:
- if isinstance(item, str):
- tooltip_columns.append(item)
- elif isinstance(item, dict) and item.get("item_type") == "column":
- column_name = item.get("column_name")
- if column_name:
- tooltip_columns.append(column_name)
- return tooltip_columns
-
- def _add_tooltip_columns_to_query(
- self, query_obj: QueryObjectDict, tooltip_columns: list[str]
- ) -> None:
- """Add tooltip columns to the appropriate query field."""
- if not tooltip_columns:
- return
-
- if query_obj.get("metrics"):
- existing_groupby = set(query_obj.get("groupby", []))
- for col in tooltip_columns:
- if col not in existing_groupby:
- query_obj.setdefault("groupby", []).append(col)
- else:
- existing_columns = set(query_obj.get("columns", []))
- for col in tooltip_columns:
- if col not in existing_columns:
- query_obj.setdefault("columns", []).append(col)
-
- def _integrate_tooltip_columns(self, query_obj: QueryObjectDict) -> QueryObjectDict:
- """Helper method to integrate tooltip columns into query object."""
- tooltip_columns = self._extract_tooltip_columns()
- self._add_tooltip_columns_to_query(query_obj, tooltip_columns)
- return query_obj
-
- def _add_tooltip_properties(
- self, properties: dict[str, Any], data: dict[str, Any]
- ) -> dict[str, Any]:
- """Helper method to add tooltip fields to properties dictionary."""
- tooltip_columns = self._extract_tooltip_columns()
- for col in tooltip_columns:
- if col in data:
- properties[col] = data[col]
- return properties
-
- def _get_base_properties(self, data: dict[str, Any]) -> dict[str, Any]:
- """Get base properties common to most deck.gl layers."""
- return {
- "position": data.get("spatial"),
- "weight": (data.get(self.metric_label) if self.metric_label else None) or 1,
- }
-
- def _setup_metric_label(self) -> None:
- """Setup metric label for the visualization."""
- self.metric_label: str | None = ( # pylint: disable=attribute-defined-outside-init
- utils.get_metric_name(self.metric) if self.metric else None
- )
-
- def __init__(
- self, datasource: BaseDatasource, form_data: dict[str, Any], **kwargs: Any
- ) -> None:
- # Apply layer-specific filtering for deck multi layer charts in edit mode
- if self._should_apply_layer_filtering(form_data):
- form_data = self._apply_multilayer_filtering(form_data)
- super().__init__(datasource, form_data, **kwargs)
-
- def _should_apply_layer_filtering(self, form_data: dict[str, Any]) -> bool:
- """Check if this is a deck layer that's part of a multilayer setup."""
- return (
- "slice_id" in form_data
- and "adhoc_filters" in form_data
- and self._has_layer_scoped_filters(form_data)
- )
-
- def _has_layer_scoped_filters(self, form_data: dict[str, Any]) -> bool:
- """Check if any filter has layerFilterScope (indicates multilayer context)."""
- for filter_item in form_data.get("adhoc_filters", []):
- if (
- isinstance(filter_item, dict)
- and filter_item.get("layerFilterScope") is not None
- ):
- return True
- return False
-
- def _apply_multilayer_filtering(self, form_data: dict[str, Any]) -> dict[str, Any]:
- """
- Filter adhoc_filters based on layer scope for this specific layer.
-
- In deck multi-layer charts, each individual layer should only receive:
- 1. Global filters (filters without layerFilterScope)
- 2. Filters specifically scoped to this layer
-
- This prevents over-filtering when multiple layer-scoped filters are present.
- """
- slice_id = form_data.get("slice_id")
- deck_slices = self._get_deck_slices_from_filters(form_data)
-
- if not deck_slices or slice_id not in deck_slices:
- return form_data
-
- layer_index = deck_slices.index(slice_id)
- filtered_adhoc_filters = []
-
- for filter_item in form_data.get("adhoc_filters", []):
- layer_scope = self._get_filter_layer_scope(filter_item)
-
- # Include global filters (no layer scope) or filters scoped to this layer
- if layer_scope is None or layer_index in layer_scope:
- filtered_adhoc_filters.append(filter_item)
-
- modified_form_data = form_data.copy()
- modified_form_data["adhoc_filters"] = filtered_adhoc_filters
- return modified_form_data
-
- def _get_deck_slices_from_filters(
- self, form_data: dict[str, Any]
- ) -> list[int] | None:
- """Extract deck_slices from any filter that contains it."""
- for filter_item in form_data.get("adhoc_filters", []):
- if isinstance(filter_item, dict) and "deck_slices" in filter_item:
- return filter_item["deck_slices"]
- return None
-
- def _get_filter_layer_scope(self, filter_item: Any) -> list[int] | None:
- """Extract layerFilterScope from a filter item."""
- if isinstance(filter_item, dict):
- return filter_item.get("layerFilterScope")
- return getattr(filter_item, "layerFilterScope", None)
-
- @deprecated(deprecated_in="3.0")
- def get_metrics(self) -> list[str]:
- # pylint: disable=attribute-defined-outside-init
- self.metric = self.form_data.get("size")
- return [self.metric] if self.metric else []
-
- @deprecated(deprecated_in="3.0")
- def process_spatial_query_obj(self, key: str, group_by: list[str]) -> None:
- group_by.extend(self.get_spatial_columns(key))
-
- @deprecated(deprecated_in="3.0")
- def get_spatial_columns(self, key: str) -> list[str]:
- spatial = self.form_data.get(key)
- if spatial is None:
- raise ValueError(_("Bad spatial key"))
-
- if spatial.get("type") == "latlong":
- return [spatial.get("lonCol"), spatial.get("latCol")]
-
- if spatial.get("type") == "delimited":
- return [spatial.get("lonlatCol")]
-
- if spatial.get("type") == "geohash":
- return [spatial.get("geohashCol")]
- return []
-
- @staticmethod
- @deprecated(deprecated_in="3.0")
- def parse_coordinates(latlong: Any) -> tuple[float, float] | None:
- if not latlong:
- return None
- try:
- point = Point(latlong)
- return (point.latitude, point.longitude)
- except Exception as ex:
- raise SpatialException(
- _("Invalid spatial point encountered: %(latlong)s", latlong=latlong)
- ) from ex
-
- @staticmethod
- @deprecated(deprecated_in="3.0")
- def reverse_geohash_decode(geohash_code: str) -> tuple[str, str]:
- lat, lng = pygeohash.decode(geohash_code)
- return (lng, lat)
-
- @staticmethod
- @deprecated(deprecated_in="3.0")
- def reverse_latlong(df: pd.DataFrame, key: str) -> None:
- df[key] = [tuple(reversed(o)) for o in df[key] if isinstance(o, (list, tuple))]
-
- @deprecated(deprecated_in="3.0")
- def process_spatial_data_obj(self, key: str, df: pd.DataFrame) -> pd.DataFrame:
- spatial = self.form_data.get(key)
- if spatial is None:
- raise ValueError(_("Bad spatial key"))
-
- if spatial.get("type") == "latlong":
- df[key] = list(
- zip(
- pd.to_numeric(df[spatial.get("lonCol")], errors="coerce"),
- pd.to_numeric(df[spatial.get("latCol")], errors="coerce"),
- strict=False,
- )
- )
- elif spatial.get("type") == "delimited":
- lon_lat_col = spatial.get("lonlatCol")
- df[key] = df[lon_lat_col].apply(self.parse_coordinates)
- del df[lon_lat_col]
- elif spatial.get("type") == "geohash":
- df[key] = df[spatial.get("geohashCol")].map(self.reverse_geohash_decode)
- del df[spatial.get("geohashCol")]
-
- if spatial.get("reverseCheckbox"):
- self.reverse_latlong(df, key)
-
- if df.get(key) is None:
- raise NullValueException(
- _(
- "Encountered invalid NULL spatial entry, \
- please consider filtering those out"
- )
- )
- return df
-
- @deprecated(deprecated_in="3.0")
- def add_null_filters(self) -> None:
- spatial_columns = set()
- for key in self.spatial_control_keys:
- for column in self.get_spatial_columns(key):
- spatial_columns.add(column)
-
- if self.form_data.get("adhoc_filters") is None:
- self.form_data["adhoc_filters"] = []
-
- if line_column := self.form_data.get("line_column"):
- spatial_columns.add(line_column)
-
- for column in sorted(spatial_columns):
- filter_ = simple_filter_to_adhoc(
- {"col": column, "op": "IS NOT NULL", "val": ""}
- )
- self.form_data["adhoc_filters"].append(filter_)
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- # add NULL filters
- if self.form_data.get("filter_nulls", True):
- self.add_null_filters()
-
- query_obj = super().query_obj()
- group_by: list[str] = []
-
- for key in self.spatial_control_keys:
- self.process_spatial_query_obj(key, group_by)
-
- if self.form_data.get("dimension"):
- group_by += [self.form_data["dimension"]]
-
- if self.form_data.get("js_columns"):
- group_by += self.form_data.get("js_columns") or []
- # Ensure this value is sorted so that it does not
- # cause the cache key generation (which hashes the
- # query object) to generate different keys for values
- # that should be considered the same.
- group_by = sorted(set(group_by))
- if metrics := self.get_metrics():
- query_obj["groupby"] = group_by
- query_obj["metrics"] = metrics
- query_obj["columns"] = []
- first_metric = query_obj["metrics"][0]
- query_obj["orderby"] = [
- (first_metric, not self.form_data.get("order_desc", True))
- ]
- else:
- query_obj["columns"] = group_by
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_js_columns(self, data: dict[str, Any]) -> dict[str, Any]:
- cols = self.form_data.get("js_columns") or []
- return {col: data.get(col) for col in cols}
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- if df.empty:
- return None
-
- # Processing spatial info
- for key in self.spatial_control_keys:
- df = self.process_spatial_data_obj(key, df)
-
- features = []
- for data in df.to_dict(orient="records"):
- feature = self.get_properties(data)
- extra_props = self.get_js_columns(data)
- if extra_props:
- feature["extraProps"] = extra_props
- features.append(feature)
-
- return {
- "features": features,
- "mapboxApiKey": current_app.config["MAPBOX_API_KEY"],
- "metricLabels": self.metric_labels,
- }
-
- @deprecated(deprecated_in="3.0")
- def get_properties(self, data: dict[str, Any]) -> dict[str, Any]:
- raise NotImplementedError()
-
-
-class DeckScatterViz(BaseDeckGLViz):
- """deck.gl's ScatterLayer"""
-
- viz_type = "deck_scatter"
- verbose_name = _("Deck.gl - Scatter plot")
- spatial_control_keys = ["spatial"]
- is_timeseries = True
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- # pylint: disable=attribute-defined-outside-init
- self.is_timeseries = bool(self.form_data.get("time_grain_sqla"))
- self.point_radius_fixed = self.form_data.get("point_radius_fixed") or {
- "type": "fix",
- "value": 500,
- }
-
- query_obj = super().query_obj()
- return self._integrate_tooltip_columns(query_obj)
-
- @deprecated(deprecated_in="3.0")
- def get_metrics(self) -> list[str]:
- # pylint: disable=attribute-defined-outside-init
- self.metric = None
- if self.point_radius_fixed.get("type") == "metric":
- self.metric = self.point_radius_fixed["value"]
- return [self.metric]
- return []
-
- @deprecated(deprecated_in="3.0")
- def get_properties(self, data: dict[str, Any]) -> dict[str, Any]:
- properties = {
- "metric": data.get(self.metric_label) if self.metric_label else None,
- "radius": (
- self.fixed_value
- if self.fixed_value
- else data.get(self.metric_label)
- if self.metric_label
- else None
- ),
- "cat_color": data.get(self.dim) if self.dim else None,
- "position": data.get("spatial"),
- DTTM_ALIAS: data.get(DTTM_ALIAS),
- }
-
- return self._add_tooltip_properties(properties, data)
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- self._setup_metric_label()
- # pylint: disable=attribute-defined-outside-init
- self.point_radius_fixed = self.form_data.get("point_radius_fixed")
- self.fixed_value = None
- self.dim = self.form_data.get("dimension")
- if self.point_radius_fixed and self.point_radius_fixed.get("type") != "metric":
- self.fixed_value = self.point_radius_fixed.get("value")
- return super().get_data(df)
-
-
-class DeckScreengrid(BaseDeckGLViz):
- """deck.gl's ScreenGridLayer"""
-
- viz_type = "deck_screengrid"
- verbose_name = _("Deck.gl - Screen Grid")
- spatial_control_keys = ["spatial"]
- is_timeseries = True
-
- def _extract_tooltip_columns(self) -> list[str]:
- """Extract column names from tooltip_contents configuration."""
- tooltip_columns = []
- if tooltip_contents := self.form_data.get("tooltip_contents", []):
- for item in tooltip_contents:
- if isinstance(item, str):
- tooltip_columns.append(item)
- elif isinstance(item, dict) and item.get("item_type") == "column":
- column_name = item.get("column_name")
- if column_name:
- tooltip_columns.append(column_name)
- return tooltip_columns
-
- def _add_tooltip_columns_to_query(
- self, query_obj: QueryObjectDict, tooltip_columns: list[str]
- ) -> None:
- """Add tooltip columns to the appropriate query field."""
- if not tooltip_columns:
- return
-
- if query_obj.get("metrics"):
- # Add to groupby when metrics exist
- existing_groupby = set(query_obj.get("groupby", []))
- for col in tooltip_columns:
- if col not in existing_groupby:
- query_obj.setdefault("groupby", []).append(col)
- else:
- # Add to columns when no metrics
- existing_columns = set(query_obj.get("columns", []))
- for col in tooltip_columns:
- if col not in existing_columns:
- query_obj.setdefault("columns", []).append(col)
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- self.is_timeseries = bool(self.form_data.get("time_grain_sqla"))
- tooltip_columns = self._extract_tooltip_columns()
- query_obj = super().query_obj()
- self._add_tooltip_columns_to_query(query_obj, tooltip_columns)
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_properties(self, data: dict[str, Any]) -> dict[str, Any]:
- properties = {
- "position": data.get("spatial"),
- "weight": (data.get(self.metric_label) if self.metric_label else None) or 1,
- "__timestamp": data.get(DTTM_ALIAS) or data.get("__time"),
- }
-
- # For Screengrid, the frontend handles the cell-to-points mapping
- # The backend just provides the aggregated data and tooltip fields
-
- # For Screengrid, automatically collect all values for tooltip fields
- # When user selects LON as tooltip field, {{ LON }} will show all LON values
- tooltip_columns = self._extract_tooltip_columns()
- for col in tooltip_columns:
- if col in data:
- # For Screengrid, each cell contains multiple points, provide as-is
- # The frontend will handle displaying multiple values appropriately
- properties[col] = data[col]
-
- return properties
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- self.metric_label = ( # pylint: disable=attribute-defined-outside-init
- utils.get_metric_name(self.metric) if self.metric else None
- )
- return super().get_data(df)
-
-
-class DeckGrid(BaseDeckGLViz):
- """deck.gl's GridLayer"""
-
- viz_type = "deck_grid"
- verbose_name = _("Deck.gl - 3D Grid")
- spatial_control_keys = ["spatial"]
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- tooltip_columns = self._extract_tooltip_columns()
- query_obj = super().query_obj()
- self._add_tooltip_columns_to_query(query_obj, tooltip_columns)
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_properties(self, data: dict[str, Any]) -> dict[str, Any]:
- properties = {
- "position": data.get("spatial"),
- "weight": (data.get(self.metric_label) if self.metric_label else None) or 1,
- }
- # Add tooltip fields to properties
- tooltip_columns = self._extract_tooltip_columns()
- for col in tooltip_columns:
- if col in data:
- properties[col] = data[col]
- return properties
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- self.metric_label = ( # pylint: disable=attribute-defined-outside-init
- utils.get_metric_name(self.metric) if self.metric else None
- )
- return super().get_data(df)
-
-
-@deprecated(deprecated_in="3.0")
-def geohash_to_json(geohash_code: str) -> list[list[float]]:
- # Get the center and the error margins
- lat, lon, lat_err, lon_err = pygeohash.decode_exactly(geohash_code)
- # Calculate the Bounding Box
- bbox = {
- "n": lat + lat_err,
- "s": lat - lat_err,
- "e": lon + lon_err,
- "w": lon - lon_err,
- }
- return [
- [bbox["w"], bbox["n"]],
- [bbox["e"], bbox["n"]],
- [bbox["e"], bbox["s"]],
- [bbox["w"], bbox["s"]],
- [bbox["w"], bbox["n"]],
- ]
-
-
-class DeckPathViz(BaseDeckGLViz):
- """deck.gl's PathLayer"""
-
- viz_type = "deck_path"
- verbose_name = _("Deck.gl - Paths")
- deck_viz_key = "path"
- is_timeseries = True
- deser_map = {
- "json": json.loads,
- "polyline": polyline.decode,
- "geohash": geohash_to_json,
- }
-
- def _extract_tooltip_columns(self) -> list[str]:
- tooltip_columns = []
- if tooltip_contents := self.form_data.get("tooltip_contents", []):
- for item in tooltip_contents:
- if isinstance(item, str):
- tooltip_columns.append(item)
- elif isinstance(item, dict) and item.get("item_type") == "column":
- column_name = item.get("column_name")
- if column_name:
- tooltip_columns.append(column_name)
- return tooltip_columns
-
- def _add_tooltip_columns_to_query(
- self, query_obj: QueryObjectDict, tooltip_columns: list[str]
- ) -> None:
- if not tooltip_columns:
- return
- if query_obj.get("metrics"):
- existing_groupby = set(query_obj.get("groupby", []))
- for col in tooltip_columns:
- if col not in existing_groupby:
- query_obj.setdefault("groupby", []).append(col)
- else:
- existing_columns = set(query_obj.get("columns", []))
- for col in tooltip_columns:
- if col not in existing_columns:
- query_obj.setdefault("columns", []).append(col)
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- # pylint: disable=attribute-defined-outside-init
- self.is_timeseries = bool(self.form_data.get("time_grain_sqla"))
- tooltip_columns = self._extract_tooltip_columns()
- query_obj = super().query_obj()
- self.metric = self.form_data.get("metric")
- line_col = self.form_data.get("line_column")
- if query_obj["metrics"]:
- self.has_metrics = True
- query_obj["groupby"].append(line_col)
- else:
- self.has_metrics = False
- query_obj["columns"].append(line_col)
- self._add_tooltip_columns_to_query(query_obj, tooltip_columns)
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_properties(self, data: dict[str, Any]) -> dict[str, Any]:
- line_type = self.form_data["line_type"]
- deser = self.deser_map[line_type]
- line_column = self.form_data["line_column"]
- path = deser(data[line_column])
- if self.form_data.get("reverse_long_lat"):
- path = [(o[1], o[0]) for o in path]
- data[self.deck_viz_key] = path
- data["__timestamp"] = data.get(DTTM_ALIAS) or data.get("__time")
- return data
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- self.metric_label = ( # pylint: disable=attribute-defined-outside-init
- utils.get_metric_name(self.metric) if self.metric else None
- )
- return super().get_data(df)
-
-
-class DeckPolygon(DeckPathViz):
- """deck.gl's Polygon Layer"""
-
- viz_type = "deck_polygon"
- deck_viz_key = "polygon"
- verbose_name = _("Deck.gl - Polygon")
-
- def _extract_tooltip_columns(self) -> list[str]:
- tooltip_columns = []
- if tooltip_contents := self.form_data.get("tooltip_contents", []):
- for item in tooltip_contents:
- if isinstance(item, str):
- tooltip_columns.append(item)
- elif isinstance(item, dict) and item.get("item_type") == "column":
- column_name = item.get("column_name")
- if column_name:
- tooltip_columns.append(column_name)
- return tooltip_columns
-
- def _add_tooltip_columns_to_query(
- self, query_obj: QueryObjectDict, tooltip_columns: list[str]
- ) -> None:
- if not tooltip_columns:
- return
- if query_obj.get("metrics"):
- existing_groupby = set(query_obj.get("groupby", []))
- for col in tooltip_columns:
- if col not in existing_groupby:
- query_obj.setdefault("groupby", []).append(col)
- else:
- existing_columns = set(query_obj.get("columns", []))
- for col in tooltip_columns:
- if col not in existing_columns:
- query_obj.setdefault("columns", []).append(col)
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- self.elevation = self.form_data.get("point_radius_fixed") or {
- "type": "fix",
- "value": 500,
- }
- tooltip_columns = self._extract_tooltip_columns()
- query_obj = super().query_obj()
- self._add_tooltip_columns_to_query(query_obj, tooltip_columns)
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_metrics(self) -> list[str]:
- metrics = [self.form_data.get("metric")]
- if self.elevation.get("type") == "metric":
- metrics.append(self.elevation.get("value"))
- return [metric for metric in metrics if metric]
-
- @deprecated(deprecated_in="3.0")
- def get_properties(self, data: dict[str, Any]) -> dict[str, Any]:
- super().get_properties(data)
- elevation = self.form_data["point_radius_fixed"]["value"]
- type_ = self.form_data["point_radius_fixed"]["type"]
- data["elevation"] = (
- data.get(utils.get_metric_name(elevation))
- if type_ == "metric"
- else elevation
- )
- return data
-
-
-class DeckHex(BaseDeckGLViz):
- """deck.gl's DeckLayer"""
-
- viz_type = "deck_hex"
- verbose_name = _("Deck.gl - 3D HEX")
- spatial_control_keys = ["spatial"]
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- tooltip_columns = self._extract_tooltip_columns()
- query_obj = super().query_obj()
- self._add_tooltip_columns_to_query(query_obj, tooltip_columns)
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_properties(self, data: dict[str, Any]) -> dict[str, Any]:
- properties = {
- "position": data.get("spatial"),
- "weight": (data.get(self.metric_label) if self.metric_label else None) or 1,
- }
- # Add tooltip fields to properties
- tooltip_columns = self._extract_tooltip_columns()
- for col in tooltip_columns:
- if col in data:
- properties[col] = data[col]
- return properties
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- self.metric_label = ( # pylint: disable=attribute-defined-outside-init
- utils.get_metric_name(self.metric) if self.metric else None
- )
- return super().get_data(df)
-
-
-class DeckHeatmap(BaseDeckGLViz):
- """deck.gl's HeatmapLayer"""
-
- viz_type = "deck_heatmap"
- verbose_name = _("Deck.gl - Heatmap")
- spatial_control_keys = ["spatial"]
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- tooltip_columns = self._extract_tooltip_columns()
- query_obj = super().query_obj()
- self._add_tooltip_columns_to_query(query_obj, tooltip_columns)
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_properties(self, data: dict[str, Any]) -> dict[str, Any]:
- properties = {
- "position": data.get("spatial"),
- "weight": (data.get(self.metric_label) if self.metric_label else None) or 1,
- }
- tooltip_columns = self._extract_tooltip_columns()
- for col in tooltip_columns:
- if col in data:
- properties[col] = data[col]
-
- return properties
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- self.metric_label = ( # pylint: disable=attribute-defined-outside-init
- utils.get_metric_name(self.metric) if self.metric else None
- )
- return super().get_data(df)
-
-
-class DeckContour(BaseDeckGLViz):
- """deck.gl's ContourLayer"""
-
- viz_type = "deck_contour"
- verbose_name = _("Deck.gl - Contour")
- spatial_control_keys = ["spatial"]
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- query_obj = super().query_obj()
-
- # Extract and add tooltip columns
- tooltip_columns = self._extract_tooltip_columns()
- self._add_tooltip_columns_to_query(query_obj, tooltip_columns)
-
- return query_obj
-
- def get_properties(self, data: dict[str, Any]) -> dict[str, Any]:
- properties = {
- "position": data.get("spatial"),
- "weight": (data.get(self.metric_label) if self.metric_label else None) or 1,
- # Include all original data for tooltip access
- "_originalData": data,
- }
-
- # Add tooltip data at top level too for backward compatibility
- tooltip_columns = self._extract_tooltip_columns()
- for col in tooltip_columns:
- if col in data:
- properties[col] = data[col]
-
- return properties
-
- def get_data(self, df: pd.DataFrame) -> VizData:
- self.metric_label = ( # pylint: disable=attribute-defined-outside-init
- utils.get_metric_name(self.metric) if self.metric else None
- )
- return super().get_data(df)
-
-
-class DeckGeoJson(BaseDeckGLViz):
- """deck.gl's GeoJSONLayer"""
-
- viz_type = "deck_geojson"
- verbose_name = _("Deck.gl - GeoJSON")
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- query_obj = super().query_obj()
- query_obj["columns"] += [self.form_data.get("geojson")]
- query_obj["metrics"] = []
- query_obj["groupby"] = []
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_properties(self, data: dict[str, Any]) -> dict[str, Any]:
- geojson = data[get_column_name(self.form_data["geojson"])]
- return json.loads(geojson)
-
-
-class DeckArc(BaseDeckGLViz):
- """deck.gl's Arc Layer"""
-
- viz_type = "deck_arc"
- verbose_name = _("Deck.gl - Arc")
- spatial_control_keys = ["start_spatial", "end_spatial"]
- is_timeseries = True
-
- def _extract_tooltip_columns(self) -> list[str]:
- tooltip_columns = []
- if tooltip_contents := self.form_data.get("tooltip_contents", []):
- for item in tooltip_contents:
- if isinstance(item, str):
- tooltip_columns.append(item)
- elif isinstance(item, dict) and item.get("item_type") == "column":
- column_name = item.get("column_name")
- if column_name:
- tooltip_columns.append(column_name)
- return tooltip_columns
-
- def _add_tooltip_columns_to_query(
- self, query_obj: QueryObjectDict, tooltip_columns: list[str]
- ) -> None:
- if not tooltip_columns:
- return
- if query_obj.get("metrics"):
- existing_groupby = set(query_obj.get("groupby", []))
- for col in tooltip_columns:
- if col not in existing_groupby:
- query_obj.setdefault("groupby", []).append(col)
- else:
- existing_columns = set(query_obj.get("columns", []))
- for col in tooltip_columns:
- if col not in existing_columns:
- query_obj.setdefault("columns", []).append(col)
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- self.is_timeseries = bool(self.form_data.get("time_grain_sqla"))
- tooltip_columns = self._extract_tooltip_columns()
- query_obj = super().query_obj()
- self._add_tooltip_columns_to_query(query_obj, tooltip_columns)
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_properties(self, data: dict[str, Any]) -> dict[str, Any]:
- dim = self.form_data.get("dimension")
- properties = {
- "sourcePosition": data.get("start_spatial"),
- "targetPosition": data.get("end_spatial"),
- "cat_color": data.get(dim) if dim else None,
- DTTM_ALIAS: data.get(DTTM_ALIAS),
- }
- # Add tooltip fields to properties
- tooltip_columns = self._extract_tooltip_columns()
- for col in tooltip_columns:
- if col in data:
- properties[col] = data[col]
- return properties
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- if df.empty:
- return None
- return {
- "features": super().get_data(df)["features"],
- "mapboxApiKey": current_app.config["MAPBOX_API_KEY"],
- }
-
-
-class PairedTTestViz(BaseViz):
- """A table displaying paired t-test values"""
-
- viz_type = "paired_ttest"
- verbose_name = _("Time Series - Paired t-test")
- sort_series = False
- is_timeseries = True
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- query_obj = super().query_obj()
- if sort_by := self.form_data.get("timeseries_limit_metric"):
- sort_by_label = utils.get_metric_name(sort_by)
- if sort_by_label not in utils.get_metric_names(query_obj["metrics"]):
- query_obj["metrics"].append(sort_by)
- if self.form_data.get("order_desc"):
- query_obj["orderby"] = [
- (sort_by, not self.form_data.get("order_desc", True))
- ]
- return query_obj
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- """
- Transform received data frame into an object of the form:
- {
- 'metric1': [
- {
- groups: ('groupA', ... ),
- values: [ {x, y}, ... ],
- }, ...
- ], ...
- }
- """
-
- if df.empty:
- return None
-
- groups = get_column_names(self.form_data.get("groupby"))
- metrics = self.metric_labels
- df = df.pivot_table(index=DTTM_ALIAS, columns=groups, values=metrics)
- cols = []
- # Be rid of falsy keys
- for col in df.columns:
- if col == "":
- cols.append("N/A")
- elif col is None:
- cols.append("NULL")
- else:
- cols.append(col)
- df.columns = cols
- data: dict[str, list[dict[str, Any]]] = {}
- series = df.to_dict("series")
- for name_set in df.columns:
- # If no groups are defined, nameSet will be the metric name
- has_group = not isinstance(name_set, str)
- data_ = {
- "group": name_set[1:] if has_group else "All",
- "values": [
- {
- "x": t,
- "y": series[name_set][t] if t in series[name_set] else None,
- }
- for t in df.index
- ],
- }
- key = name_set[0] if has_group else name_set
- if key in data:
- data[key].append(data_)
- else:
- data[key] = [data_]
- return data
-
-
-class RoseViz(NVD3TimeSeriesViz):
- viz_type = "rose"
- verbose_name = _("Time Series - Nightingale Rose Chart")
- sort_series = False
- is_timeseries = True
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- if df.empty:
- return None
-
- data = super().get_data(df)
- result: dict[str, list[dict[str, str]]] = {}
- for datum in data:
- key = datum["key"]
- for val in datum["values"]:
- timestamp = val["x"].value
- if not result.get(timestamp):
- result[timestamp] = []
- value = 0 if math.isnan(val["y"]) else val["y"]
- result[timestamp].append(
- {
- "key": key,
- "value": value, # type: ignore
- "name": ", ".join(key) if isinstance(key, list) else key,
- "time": val["x"],
- }
- )
- return result
-
-
-class PartitionViz(NVD3TimeSeriesViz):
- """
- A hierarchical data visualization with support for time series.
- """
-
- viz_type = "partition"
- verbose_name = _("Partition Diagram")
-
- @deprecated(deprecated_in="3.0")
- def query_obj(self) -> QueryObjectDict:
- query_obj = super().query_obj()
- time_op = self.form_data.get("time_series_option", "not_time")
- # Return time series data if the user specifies so
- query_obj["is_timeseries"] = time_op != "not_time"
- return query_obj
-
- @staticmethod
- @deprecated(deprecated_in="3.0")
- def levels_for(
- time_op: str, groups: list[str], df: pd.DataFrame
- ) -> dict[int, pd.Series]:
- """
- Compute the partition at each `level` from the dataframe.
- """
- levels = {}
- for i in range(0, len(groups) + 1):
- agg_df = df.groupby(groups[:i]) if i else df
- levels[i] = (
- agg_df.mean(numeric_only=True)
- if time_op == "agg_mean"
- else agg_df.sum(numeric_only=True)
- )
- return levels
-
- @staticmethod
- @deprecated(deprecated_in="3.0")
- def levels_for_diff(
- time_op: str, groups: list[str], df: pd.DataFrame
- ) -> dict[int, pd.DataFrame]:
- # Obtain a unique list of the time grains
- times = list(set(df[DTTM_ALIAS]))
- times.sort()
- until = times[len(times) - 1]
- since = times[0]
- # Function describing how to calculate the difference
- func = {
- "point_diff": [pd.Series.sub, lambda a, b, fill_value: a - b],
- "point_factor": [pd.Series.div, lambda a, b, fill_value: a / float(b)],
- "point_percent": [
- lambda a, b, fill_value=0: a.div(b, fill_value=fill_value) - 1,
- lambda a, b, fill_value: a / float(b) - 1,
- ],
- }[time_op]
- agg_df = df.groupby(DTTM_ALIAS).sum(numeric_only=True)
- levels = {
- 0: pd.Series(
- {
- m: func[1](agg_df[m][until], agg_df[m][since], 0)
- for m in agg_df.columns
- }
- )
- }
- for i in range(1, len(groups) + 1):
- agg_df = df.groupby([DTTM_ALIAS] + groups[:i]).sum(numeric_only=True)
- levels[i] = pd.DataFrame(
- {
- m: func[0](agg_df[m][until], agg_df[m][since], fill_value=0)
- for m in agg_df.columns
- }
- )
- return levels
-
- @deprecated(deprecated_in="3.0")
- def levels_for_time(
- self, groups: list[str], df: pd.DataFrame
- ) -> dict[int, VizData]:
- procs = {}
- for i in range(0, len(groups) + 1):
- self.form_data["groupby"] = groups[:i]
- df_drop = df.drop(groups[i:], axis=1)
- procs[i] = self.process_data(df_drop, aggregate=True)
- self.form_data["groupby"] = groups
- return procs
-
- @deprecated(deprecated_in="3.0")
- def nest_values(
- self,
- levels: dict[int, pd.DataFrame],
- level: int = 0,
- metric: str | None = None,
- dims: list[str] | None = None,
- ) -> list[dict[str, Any]]:
- """
- Nest values at each level on the back-end with
- access and setting, instead of summing from the bottom.
- """
- if dims is None:
- dims = []
- if not level:
- return [
- {
- "name": m,
- "val": levels[0][m],
- "children": self.nest_values(levels, 1, m),
- }
- for m in levels[0].index
- ]
- if level == 1:
- metric_level = levels[1][metric]
- return [
- {
- "name": i,
- "val": metric_level[i],
- "children": self.nest_values(levels, 2, metric, [i]),
- }
- for i in metric_level.index
- ]
- if level >= len(levels):
- return []
-
- dim_level = levels[level][metric]
- for d in dims:
- if d not in dim_level:
- return []
- dim_level = dim_level[d]
-
- return [
- {
- "name": [*dims, i],
- "val": dim_level[i],
- "children": self.nest_values(levels, level + 1, metric, dims + [i]),
- }
- for i in dim_level.index
- ]
-
- @deprecated(deprecated_in="3.0")
- def nest_procs(
- self,
- procs: dict[int, pd.DataFrame],
- level: int = -1,
- dims: tuple[str, ...] | None = None,
- time: Any = None,
- ) -> list[dict[str, Any]]:
- if dims is None:
- dims = ()
- if level == -1:
- return [
- {"name": m, "children": self.nest_procs(procs, 0, (m,))}
- for m in procs[0].columns
- ]
- if not level:
- return [
- {
- "name": t,
- "val": procs[0][dims[0]][t],
- "children": self.nest_procs(procs, 1, dims, t),
- }
- for t in procs[0].index
- ]
- if level >= len(procs):
- return []
- return [
- {
- "name": i,
- "val": procs[level][dims][i][time],
- "children": self.nest_procs(procs, level + 1, dims + (i,), time),
- }
- for i in procs[level][dims].columns
- ]
-
- @deprecated(deprecated_in="3.0")
- def get_data(self, df: pd.DataFrame) -> VizData:
- if df.empty:
- return None
- groups = get_column_names(self.form_data.get("groupby"))
- time_op = self.form_data.get("time_series_option", "not_time")
- if not groups:
- raise ValueError(_("Please choose at least one groupby"))
- if time_op == "not_time":
- levels = self.levels_for("agg_sum", groups, df)
- elif time_op in ["agg_sum", "agg_mean"]:
- levels = self.levels_for(time_op, groups, df)
- elif time_op in ["point_diff", "point_factor", "point_percent"]:
- levels = self.levels_for_diff(time_op, groups, df)
- elif time_op == "adv_anal":
- procs = self.levels_for_time(groups, df)
- return self.nest_procs(procs)
- else:
- levels = self.levels_for("agg_sum", [DTTM_ALIAS] + groups, df)
- return self.nest_values(levels)
-
-
-def _get_subclasses(cls: type[BaseViz]) -> set[type[BaseViz]]:
- return set(cls.__subclasses__()).union(
- [sc for c in cls.__subclasses__() for sc in _get_subclasses(c)]
- )
-
-
-@deprecated(deprecated_in="3.0")
-def get_subclasses(cls: type[BaseViz]) -> set[type[BaseViz]]:
- return _get_subclasses(cls)
-
-
-viz_types = {
- o.viz_type: o
- for o in _get_subclasses(BaseViz)
- if o.viz_type not in current_app.config["VIZ_TYPE_DENYLIST"]
-}
diff --git a/tests/integration_tests/core_tests.py b/tests/integration_tests/core_tests.py
index 3390da5b266..6464f3c1db1 100644
--- a/tests/integration_tests/core_tests.py
+++ b/tests/integration_tests/core_tests.py
@@ -43,7 +43,7 @@ from superset.common.db_query_status import QueryStatus
from superset.connectors.sqla.models import SqlaTable
from superset.db_engine_specs.base import BaseEngineSpec
from superset.db_engine_specs.mssql import MssqlEngineSpec
-from superset.exceptions import OAuth2RedirectError, SupersetException
+from superset.exceptions import SupersetException
from superset.extensions import cache_manager
from superset.models import core as models
from superset.models.dashboard import Dashboard
@@ -120,29 +120,6 @@ class TestCore(SupersetTestCase):
resp = self.client.get("/slice/-1/")
assert resp.status_code == 404
- @pytest.mark.usefixtures("load_world_bank_dashboard_with_slices")
- def test_viz_cache_key(self):
- self.login(ADMIN_USERNAME)
- slc = self.get_slice("% Rural")
-
- viz = slc.viz
- qobj = viz.query_obj()
- cache_key = viz.cache_key(qobj)
-
- qobj["groupby"] = []
- cache_key_with_groupby = viz.cache_key(qobj)
- assert cache_key != cache_key_with_groupby
-
- assert viz.cache_key(qobj) != viz.cache_key(qobj, time_compare="12 weeks")
-
- assert viz.cache_key(qobj, time_compare="28 days") != viz.cache_key(
- qobj, time_compare="12 weeks"
- )
-
- qobj["inner_from_dttm"] = datetime.datetime(1901, 1, 1)
-
- assert cache_key_with_groupby == viz.cache_key(qobj)
-
def test_admin_only_menu_views(self):
def assert_admin_view_menus_in(role_name, assert_func):
role = security_manager.find_role(role_name)
@@ -447,84 +424,6 @@ class TestCore(SupersetTestCase):
assert "comment 2" in rendered_query
assert "FROM tbl" in rendered_query
- def test_slice_payload_no_datasource(self):
- form_data = {
- "viz_type": "dist_bar",
- }
- self.login(ADMIN_USERNAME)
- rv = self.client.post(
- "/explore_json/",
- data={"form_data": json.dumps(form_data)},
- )
- data = json.loads(rv.data.decode("utf-8"))
-
- assert (
- data["errors"][0]["message"]
- == "The dataset associated with this chart no longer exists"
- )
-
- def test_explore_json_data_invalid_cache_key(self):
- self.login(ADMIN_USERNAME)
- cache_key = "invalid-cache-key"
- rv = self.client.get(f"/explore_json/data/{cache_key}")
- data = json.loads(rv.data.decode("utf-8"))
-
- assert rv.status_code == 404
- assert data["error"] == "Cached data not found"
-
- @pytest.mark.usefixtures("load_world_bank_dashboard_with_slices")
- @mock.patch("superset.viz.BaseViz.get_df")
- def test_explore_json_propagates_oauth2_redirect_error(
- self, mock_get_df: mock.Mock
- ) -> None:
- """
- SupersetErrorException exceptions bubble up properly.
- """
- mock_get_df.side_effect = OAuth2RedirectError(
- url="https://accounts.example.com/o/oauth2/v2/auth?...",
- tab_id="tab-123",
- redirect_uri="https://superset.example.com/oauth2/redirect",
- )
-
- self.login(ADMIN_USERNAME)
- slc = self.get_slice("% Rural")
- rv = self.client.post(
- f"/explore_json/{slc.datasource_type}/{slc.datasource_id}/",
- data={"form_data": json.dumps(slc.form_data)},
- )
- data = json.loads(rv.data.decode("utf-8"))
-
- assert "errors" in data, data
- assert data["errors"][0]["error_type"] == "OAUTH2_REDIRECT"
- assert data["errors"][0]["extra"] == {
- "url": "https://accounts.example.com/o/oauth2/v2/auth?...",
- "tab_id": "tab-123",
- "redirect_uri": "https://superset.example.com/oauth2/redirect",
- }
-
- @pytest.mark.usefixtures("load_world_bank_dashboard_with_slices")
- @mock.patch("superset.viz.BaseViz.get_df")
- def test_explore_json_generic_exception_still_returns_viz_get_df_error(
- self, mock_get_df: mock.Mock
- ) -> None:
- """
- Non-Superset exceptions raised by ``get_df`` are reported as the
- generic ``VIZ_GET_DF_ERROR``.
- """
- mock_get_df.side_effect = RuntimeError("boom")
-
- self.login(ADMIN_USERNAME)
- slc = self.get_slice("% Rural")
- rv = self.client.post(
- f"/explore_json/{slc.datasource_type}/{slc.datasource_id}/",
- data={"form_data": json.dumps(slc.form_data)},
- )
- data = json.loads(rv.data.decode("utf-8"))
-
- assert "errors" in data, data
- assert data["errors"][0]["error_type"] == "VIZ_GET_DF_ERROR"
- assert data["errors"][0]["message"] == "boom"
-
def test_results_default_deserialization(self):
use_new_deserialization = False
data = [("a", 4, 4.0, "2019-08-18T16:39:16.660000")]
diff --git a/tests/integration_tests/security_tests.py b/tests/integration_tests/security_tests.py
index c089bf4cf25..1b8f8698ee5 100644
--- a/tests/integration_tests/security_tests.py
+++ b/tests/integration_tests/security_tests.py
@@ -31,7 +31,7 @@ from flask import current_app, g
from flask_appbuilder.security.sqla.models import Role
from superset.daos.datasource import DatasourceDAO # noqa: F401
from superset.models.dashboard import Dashboard
-from superset import appbuilder, db, security_manager, viz
+from superset import appbuilder, db, security_manager
from superset.connectors.sqla.models import SqlaTable
from superset.errors import ErrorLevel, SupersetError, SupersetErrorType
from superset.exceptions import SupersetSecurityException
@@ -1356,8 +1356,6 @@ class TestRolePermission(SupersetTestCase):
assert ("can_explore", "Superset") in perm_set
assert ("can_share_chart", "Superset") in perm_set
assert ("can_share_dashboard", "Superset") in perm_set
- assert ("can_explore_json", "Superset") in perm_set
- assert ("can_explore_json", "Superset") in perm_set
assert ("can_userinfo", "UserDBModelView") in perm_set
assert ("can_view_chart_as_table", "Dashboard") in perm_set
assert ("can_view_query", "Dashboard") in perm_set
@@ -2062,24 +2060,6 @@ class TestSecurityManager(SupersetTestCase):
with self.assertRaises(SupersetSecurityException): # noqa: PT027
security_manager.raise_for_access(database=database, table=table)
- @patch("superset.security.SupersetSecurityManager.is_owner")
- @patch("superset.security.SupersetSecurityManager.can_access")
- @patch("superset.security.SupersetSecurityManager.can_access_schema")
- def test_raise_for_access_viz(
- self, mock_can_access_schema, mock_can_access, mock_is_owner
- ):
- test_viz = viz.TimeTableViz(self.get_datasource_mock(), form_data={})
-
- mock_can_access_schema.return_value = True
- security_manager.raise_for_access(viz=test_viz)
-
- mock_can_access.return_value = False
- mock_can_access_schema.return_value = False
- mock_is_owner.return_value = False
- with override_user(security_manager.find_user("gamma")):
- with self.assertRaises(SupersetSecurityException): # noqa: PT027
- security_manager.raise_for_access(viz=test_viz)
-
@pytest.mark.usefixtures("load_birth_names_dashboard_with_slices")
@pytest.mark.usefixtures("load_world_bank_dashboard_with_slices")
@with_feature_flags(DASHBOARD_RBAC=True)
diff --git a/tests/integration_tests/tasks/async_queries_tests.py b/tests/integration_tests/tasks/async_queries_tests.py
index 728076011bd..16d618f0ece 100644
--- a/tests/integration_tests/tasks/async_queries_tests.py
+++ b/tests/integration_tests/tasks/async_queries_tests.py
@@ -29,7 +29,6 @@ from superset.async_events.cache_backend import (
)
from superset.commands.chart.data.get_data_command import ChartDataCommand
from superset.commands.chart.exceptions import ChartDataQueryFailedError
-from superset.exceptions import SupersetException
from superset.extensions import async_query_manager, security_manager
from tests.integration_tests.base_tests import SupersetTestCase
from tests.integration_tests.fixtures.birth_names_dashboard import (
@@ -154,120 +153,3 @@ class TestAsyncQueries(SupersetTestCase):
set_form_data.side_effect = SoftTimeLimitExceeded()
load_chart_data_into_cache(job_metadata, form_data)
set_form_data.assert_called_once_with(form_data, "error", errors=errors)
-
- @parameterized.expand(
- [
- ("RedisCacheBackend", mock.Mock(spec=RedisCacheBackend)),
- ("RedisSentinelCacheBackend", mock.Mock(spec=RedisSentinelCacheBackend)),
- ]
- )
- @pytest.mark.usefixtures("load_birth_names_dashboard_with_slices")
- @pytest.mark.skip(reason="This test will be changed to use the api/v1/data")
- @mock.patch.object(async_query_manager, "update_job")
- def test_load_explore_json_into_cache(
- self, cache_type, cache_backend, mock_update_job
- ):
- from superset.tasks.async_queries import load_explore_json_into_cache
-
- app._got_first_request = False
-
- async_query_manager.get_cache_backend = mock.Mock(return_value=cache_backend)
- async_query_manager.init_app(app)
-
- table = self.get_table(name="birth_names")
- user = security_manager.find_user("gamma")
- form_data = {
- "datasource": f"{table.id}__table",
- "viz_type": "dist_bar",
- "granularity_sqla": "ds",
- "time_range": "No filter",
- "metrics": ["count"],
- "adhoc_filters": [],
- "groupby": ["gender"],
- "row_limit": 100,
- }
- job_metadata = {
- "channel_id": str(uuid4()),
- "job_id": str(uuid4()),
- "user_id": user.id,
- "status": "pending",
- "errors": [],
- }
-
- load_explore_json_into_cache(job_metadata, form_data)
-
- mock_update_job.assert_called_once_with(
- job_metadata, "done", result_url=mock.ANY
- )
-
- @parameterized.expand(
- [
- ("RedisCacheBackend", mock.Mock(spec=RedisCacheBackend)),
- ("RedisSentinelCacheBackend", mock.Mock(spec=RedisSentinelCacheBackend)),
- ]
- )
- @mock.patch.object(async_query_manager, "update_job")
- @mock.patch("superset.tasks.async_queries.set_form_data")
- def test_load_explore_json_into_cache_error(
- self, cache_type, cache_backend, mock_set_form_data, mock_update_job
- ):
- from superset.tasks.async_queries import load_explore_json_into_cache
-
- app._got_first_request = False
-
- async_query_manager.get_cache_backend = mock.Mock(return_value=cache_backend)
- async_query_manager.init_app(app)
-
- user = security_manager.find_user("gamma")
- form_data = {}
- job_metadata = {
- "channel_id": str(uuid4()),
- "job_id": str(uuid4()),
- "user_id": user.id,
- "status": "pending",
- "errors": [],
- }
-
- with pytest.raises(SupersetException):
- load_explore_json_into_cache(job_metadata, form_data)
-
- mock_set_form_data.assert_called_once_with(form_data)
- errors = ["The dataset associated with this chart no longer exists"]
- mock_update_job.assert_called_once_with(job_metadata, "error", errors=errors)
-
- @parameterized.expand(
- [
- ("RedisCacheBackend", mock.Mock(spec=RedisCacheBackend)),
- ("RedisSentinelCacheBackend", mock.Mock(spec=RedisSentinelCacheBackend)),
- ]
- )
- @mock.patch.object(ChartDataCommand, "run")
- @mock.patch.object(async_query_manager, "update_job")
- def test_soft_timeout_load_explore_json_into_cache(
- self, cache_type, cache_backend, mock_update_job, mock_run_command
- ):
- from superset.tasks.async_queries import load_explore_json_into_cache
-
- app._got_first_request = False
-
- async_query_manager.get_cache_backend = mock.Mock(return_value=cache_backend)
- async_query_manager.init_app(app)
-
- user = security_manager.find_user("gamma")
- form_data = {}
- job_metadata = {
- "channel_id": str(uuid4()),
- "job_id": str(uuid4()),
- "user_id": user.id,
- "status": "pending",
- "errors": [],
- }
- errors = ["A timeout occurred while loading explore JSON data"]
-
- with pytest.raises(SoftTimeLimitExceeded): # noqa: PT012
- with mock.patch(
- "superset.tasks.async_queries.set_form_data"
- ) as set_form_data:
- set_form_data.side_effect = SoftTimeLimitExceeded()
- load_explore_json_into_cache(job_metadata, form_data)
- set_form_data.assert_called_once_with(form_data, "error", errors=errors)
diff --git a/tests/integration_tests/utils_tests.py b/tests/integration_tests/utils_tests.py
index fc083cd7e3c..a27062f7585 100644
--- a/tests/integration_tests/utils_tests.py
+++ b/tests/integration_tests/utils_tests.py
@@ -37,7 +37,7 @@ import tests.integration_tests.test_app # noqa: F401
from superset import db, security_manager
from superset.constants import NO_TIME_RANGE
from superset.exceptions import CertificateException, SupersetException # noqa: F401
-from superset.models.core import Database, Log
+from superset.models.core import Database
from superset.models.dashboard import Dashboard # noqa: F401
from superset.models.slice import Slice # noqa: F401
from superset.utils.core import (
@@ -63,7 +63,6 @@ from superset.utils import schema
from superset.utils.hashing import hash_from_str
from superset.views.utils import build_extra_filters, get_form_data # noqa: F401
from tests.integration_tests.base_tests import SupersetTestCase
-from tests.integration_tests.constants import ADMIN_USERNAME
from tests.integration_tests.fixtures.world_bank_dashboard import (
load_world_bank_dashboard_with_slices, # noqa: F401
load_world_bank_data, # noqa: F401
@@ -354,36 +353,6 @@ class TestUtils(SupersetTestCase):
assert form_data == {}
assert slc is None
- @pytest.mark.usefixtures("load_world_bank_dashboard_with_slices")
- def test_log_this(self) -> None:
- # TODO: Add additional scenarios.
- self.login(ADMIN_USERNAME)
- slc = self.get_slice("% Rural")
- dashboard_id = 1
-
- assert slc.viz is not None
- resp = self.get_json_resp( # noqa: F841
- f"/explore_json/{slc.datasource_type}/{slc.datasource_id}/"
- + f'?form_data={{"slice_id": {slc.id}}}&dashboard_id={dashboard_id}',
- {"form_data": json.dumps(slc.viz.form_data)},
- )
-
- record = (
- db.session.query(Log)
- .filter_by(action="explore_json", slice_id=slc.id)
- .order_by(Log.dttm.desc())
- .first()
- )
-
- assert record.dashboard_id == dashboard_id
- assert json.loads(record.json)["dashboard_id"] == str(dashboard_id)
- assert json.loads(record.json)["form_data"]["slice_id"] == slc.id
-
- assert (
- json.loads(record.json)["form_data"]["viz_type"]
- == slc.viz.form_data["viz_type"]
- )
-
def test_schema_validate_json(self):
valid = '{"a": 5, "b": [1, 5, ["g", "h"]]}'
assert schema.validate_json(valid) is None
diff --git a/tests/integration_tests/viz_tests.py b/tests/integration_tests/viz_tests.py
deleted file mode 100644
index ad6d9b16a5a..00000000000
--- a/tests/integration_tests/viz_tests.py
+++ /dev/null
@@ -1,2453 +0,0 @@
-# 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.
-# isort:skip_file
-from datetime import datetime
-import logging
-from unittest.mock import Mock, patch
-
-import numpy as np
-import pandas as pd
-import pytest
-
-import tests.integration_tests.test_app # noqa: F401
-import superset.viz as viz
-from flask import current_app
-from superset.exceptions import QueryObjectValidationError, SpatialException
-from superset.utils.core import DTTM_ALIAS, ExtraFiltersReasonType
-from superset.utils.pandas_postprocessing.utils import FLAT_COLUMN_SEPARATOR
-from tests.conftest import with_config
-
-from .base_tests import SupersetTestCase
-from .utils import load_fixture
-
-logger = logging.getLogger(__name__)
-
-
-class TestBaseViz(SupersetTestCase):
- def test_constructor_exception_no_datasource(self):
- form_data = {}
- datasource = None
- with self.assertRaises(Exception): # noqa: B017, PT027
- viz.BaseViz(datasource, form_data)
-
- def test_process_metrics(self):
- # test TimeTableViz metrics in correct order
- form_data = {
- "url_params": {},
- "row_limit": 500,
- "metric": "sum__SP_POP_TOTL",
- "entity": "country_code",
- "secondary_metric": "sum__SP_POP_TOTL",
- "granularity_sqla": "year",
- "page_length": 0,
- "all_columns": [],
- "viz_type": "time_table",
- "since": "2014-01-01",
- "until": "2014-01-02",
- "metrics": ["sum__SP_POP_TOTL", "SUM(SE_PRM_NENR_MA)", "SUM(SP_URB_TOTL)"],
- "country_fieldtype": "cca3",
- "percent_metrics": ["count"],
- "slice_id": 74,
- "time_grain_sqla": None,
- "order_by_cols": [],
- "groupby": ["country_name"],
- "compare_lag": "10",
- "limit": "25",
- "datasource": "2__table",
- "table_timestamp_format": "%Y-%m-%d %H:%M:%S",
- "markup_type": "markdown",
- "where": "",
- "compare_suffix": "o10Y",
- }
- datasource = Mock()
- datasource.type = "table"
- test_viz = viz.BaseViz(datasource, form_data)
- expect_metric_labels = [
- "sum__SP_POP_TOTL",
- "SUM(SE_PRM_NENR_MA)",
- "SUM(SP_URB_TOTL)",
- "count",
- ]
- assert test_viz.metric_labels == expect_metric_labels
- assert test_viz.all_metrics == expect_metric_labels
-
- def test_get_df_returns_empty_df(self):
- form_data = {"dummy": 123}
- query_obj = {"granularity": "day"}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseViz(datasource, form_data)
- result = test_viz.get_df(query_obj)
- assert isinstance(result, pd.DataFrame)
- assert result.empty
-
- def test_get_df_handles_dttm_col(self):
- form_data = {"dummy": 123}
- query_obj = {"granularity": "day"}
- results = Mock()
- results.query = Mock()
- results.status = Mock()
- results.error_message = Mock()
- datasource = Mock()
- datasource.type = "table"
- datasource.query = Mock(return_value=results)
- mock_dttm_col = Mock()
- datasource.get_column = Mock(return_value=mock_dttm_col)
-
- test_viz = viz.BaseViz(datasource, form_data)
- test_viz.df_metrics_to_num = Mock()
- test_viz.get_fillna_for_columns = Mock(return_value=0)
-
- results.df = pd.DataFrame(data={DTTM_ALIAS: ["1960-01-01 05:00:00"]})
- datasource.offset = 0
- mock_dttm_col = Mock()
- datasource.get_column = Mock(return_value=mock_dttm_col)
- mock_dttm_col.python_date_format = "epoch_ms"
- result = test_viz.get_df(query_obj)
- import logging # noqa: F401
-
- logger.info(result)
- pd.testing.assert_series_equal(
- result[DTTM_ALIAS], pd.Series([datetime(1960, 1, 1, 5, 0)], name=DTTM_ALIAS)
- )
-
- mock_dttm_col.python_date_format = None
- result = test_viz.get_df(query_obj)
- pd.testing.assert_series_equal(
- result[DTTM_ALIAS], pd.Series([datetime(1960, 1, 1, 5, 0)], name=DTTM_ALIAS)
- )
-
- datasource.offset = 1
- result = test_viz.get_df(query_obj)
- pd.testing.assert_series_equal(
- result[DTTM_ALIAS], pd.Series([datetime(1960, 1, 1, 6, 0)], name=DTTM_ALIAS)
- )
-
- datasource.offset = 0
- results.df = pd.DataFrame(data={DTTM_ALIAS: ["1960-01-01"]})
- mock_dttm_col.python_date_format = "%Y-%m-%d"
- result = test_viz.get_df(query_obj)
- pd.testing.assert_series_equal(
- result[DTTM_ALIAS], pd.Series([datetime(1960, 1, 1, 0, 0)], name=DTTM_ALIAS)
- )
-
- def test_cache_timeout(self):
- datasource = self.get_datasource_mock()
- datasource.cache_timeout = 0
- test_viz = viz.BaseViz(datasource, form_data={})
- assert 0 == test_viz.cache_timeout
-
- datasource.cache_timeout = 156
- test_viz = viz.BaseViz(datasource, form_data={})
- assert 156 == test_viz.cache_timeout
-
- datasource.cache_timeout = None
- datasource.database.cache_timeout = 0
- assert 0 == test_viz.cache_timeout
-
- datasource.database.cache_timeout = 1666
- assert 1666 == test_viz.cache_timeout
-
- datasource.database.cache_timeout = None
- test_viz = viz.BaseViz(datasource, form_data={})
- assert (
- current_app.config["DATA_CACHE_CONFIG"]["CACHE_DEFAULT_TIMEOUT"]
- == test_viz.cache_timeout
- )
-
- data_cache_timeout = current_app.config["DATA_CACHE_CONFIG"][
- "CACHE_DEFAULT_TIMEOUT"
- ]
- current_app.config["DATA_CACHE_CONFIG"]["CACHE_DEFAULT_TIMEOUT"] = None
- datasource.database.cache_timeout = None
- test_viz = viz.BaseViz(datasource, form_data={})
- assert current_app.config["CACHE_DEFAULT_TIMEOUT"] == test_viz.cache_timeout
- # restore DATA_CACHE_CONFIG timeout
- current_app.config["DATA_CACHE_CONFIG"]["CACHE_DEFAULT_TIMEOUT"] = (
- data_cache_timeout
- )
-
-
-class TestPairedTTest(SupersetTestCase):
- def test_get_data_transforms_dataframe(self):
- form_data = {
- "groupby": ["groupA", "groupB", "groupC"],
- "metrics": ["metric1", "metric2", "metric3"],
- }
- datasource = self.get_datasource_mock()
- # Test data
- raw = {}
- raw[DTTM_ALIAS] = [100, 200, 300, 100, 200, 300, 100, 200, 300]
- raw["groupA"] = ["a1", "a1", "a1", "b1", "b1", "b1", "c1", "c1", "c1"]
- raw["groupB"] = ["a2", "a2", "a2", "b2", "b2", "b2", "c2", "c2", "c2"]
- raw["groupC"] = ["a3", "a3", "a3", "b3", "b3", "b3", "c3", "c3", "c3"]
- raw["metric1"] = [1, 2, 3, 4, 5, 6, 7, 8, 9]
- raw["metric2"] = [10, 20, 30, 40, 50, 60, 70, 80, 90]
- raw["metric3"] = [100, 200, 300, 400, 500, 600, 700, 800, 900]
- df = pd.DataFrame(raw)
- pairedTTestViz = viz.viz_types["paired_ttest"](datasource, form_data) # noqa: N806
- data = pairedTTestViz.get_data(df)
- # Check method correctly transforms data
- expected = {
- "metric1": [
- {
- "values": [
- {"x": 100, "y": 1},
- {"x": 200, "y": 2},
- {"x": 300, "y": 3},
- ],
- "group": ("a1", "a2", "a3"),
- },
- {
- "values": [
- {"x": 100, "y": 4},
- {"x": 200, "y": 5},
- {"x": 300, "y": 6},
- ],
- "group": ("b1", "b2", "b3"),
- },
- {
- "values": [
- {"x": 100, "y": 7},
- {"x": 200, "y": 8},
- {"x": 300, "y": 9},
- ],
- "group": ("c1", "c2", "c3"),
- },
- ],
- "metric2": [
- {
- "values": [
- {"x": 100, "y": 10},
- {"x": 200, "y": 20},
- {"x": 300, "y": 30},
- ],
- "group": ("a1", "a2", "a3"),
- },
- {
- "values": [
- {"x": 100, "y": 40},
- {"x": 200, "y": 50},
- {"x": 300, "y": 60},
- ],
- "group": ("b1", "b2", "b3"),
- },
- {
- "values": [
- {"x": 100, "y": 70},
- {"x": 200, "y": 80},
- {"x": 300, "y": 90},
- ],
- "group": ("c1", "c2", "c3"),
- },
- ],
- "metric3": [
- {
- "values": [
- {"x": 100, "y": 100},
- {"x": 200, "y": 200},
- {"x": 300, "y": 300},
- ],
- "group": ("a1", "a2", "a3"),
- },
- {
- "values": [
- {"x": 100, "y": 400},
- {"x": 200, "y": 500},
- {"x": 300, "y": 600},
- ],
- "group": ("b1", "b2", "b3"),
- },
- {
- "values": [
- {"x": 100, "y": 700},
- {"x": 200, "y": 800},
- {"x": 300, "y": 900},
- ],
- "group": ("c1", "c2", "c3"),
- },
- ],
- }
- assert data == expected
-
- def test_get_data_empty_null_keys(self):
- form_data = {"groupby": [], "metrics": [""]}
- datasource = self.get_datasource_mock()
- # Test data
- raw = {}
- raw[DTTM_ALIAS] = [100, 200, 300]
- raw[""] = [1, 2, 3]
- raw[None] = [10, 20, 30]
-
- df = pd.DataFrame(raw)
- pairedTTestViz = viz.viz_types["paired_ttest"](datasource, form_data) # noqa: N806
- data = pairedTTestViz.get_data(df)
- # Check method correctly transforms data
- expected = {
- "N/A": [
- {
- "values": [
- {"x": 100, "y": 1},
- {"x": 200, "y": 2},
- {"x": 300, "y": 3},
- ],
- "group": "All",
- }
- ],
- }
- assert data == expected
-
- form_data = {"groupby": [], "metrics": [None]}
- with self.assertRaises(ValueError): # noqa: PT027
- viz.viz_types["paired_ttest"](datasource, form_data)
-
-
-class TestPartitionViz(SupersetTestCase):
- @patch("superset.viz.BaseViz.query_obj")
- def test_query_obj_time_series_option(self, super_query_obj):
- datasource = self.get_datasource_mock()
- form_data = {}
- test_viz = viz.PartitionViz(datasource, form_data)
- super_query_obj.return_value = {}
- query_obj = test_viz.query_obj()
- assert not query_obj["is_timeseries"]
- test_viz.form_data["time_series_option"] = "agg_sum"
- query_obj = test_viz.query_obj()
- assert query_obj["is_timeseries"]
-
- def test_levels_for_computes_levels(self):
- raw = {}
- raw[DTTM_ALIAS] = [100, 200, 300, 100, 200, 300, 100, 200, 300]
- raw["groupA"] = ["a1", "a1", "a1", "b1", "b1", "b1", "c1", "c1", "c1"]
- raw["groupB"] = ["a2", "a2", "a2", "b2", "b2", "b2", "c2", "c2", "c2"]
- raw["groupC"] = ["a3", "a3", "a3", "b3", "b3", "b3", "c3", "c3", "c3"]
- raw["metric1"] = [1, 2, 3, 4, 5, 6, 7, 8, 9]
- raw["metric2"] = [10, 20, 30, 40, 50, 60, 70, 80, 90]
- raw["metric3"] = [100, 200, 300, 400, 500, 600, 700, 800, 900]
- df = pd.DataFrame(raw)
- groups = ["groupA", "groupB", "groupC"]
- time_op = "agg_sum"
- test_viz = viz.PartitionViz(Mock(), {})
- levels = test_viz.levels_for(time_op, groups, df)
- assert 4 == len(levels)
- expected = {DTTM_ALIAS: 1800, "metric1": 45, "metric2": 450, "metric3": 4500}
- assert expected == levels[0].to_dict()
- expected = {
- DTTM_ALIAS: {"a1": 600, "b1": 600, "c1": 600},
- "metric1": {"a1": 6, "b1": 15, "c1": 24},
- "metric2": {"a1": 60, "b1": 150, "c1": 240},
- "metric3": {"a1": 600, "b1": 1500, "c1": 2400},
- }
- assert expected == levels[1].to_dict()
- assert ["groupA", "groupB"] == levels[2].index.names
- assert ["groupA", "groupB", "groupC"] == levels[3].index.names
- time_op = "agg_mean"
- levels = test_viz.levels_for(time_op, groups, df)
- assert 4 == len(levels)
- expected = {
- DTTM_ALIAS: 200.0,
- "metric1": 5.0,
- "metric2": 50.0,
- "metric3": 500.0,
- }
- assert expected == levels[0].to_dict()
- expected = {
- DTTM_ALIAS: {"a1": 200, "c1": 200, "b1": 200},
- "metric1": {"a1": 2, "b1": 5, "c1": 8},
- "metric2": {"a1": 20, "b1": 50, "c1": 80},
- "metric3": {"a1": 200, "b1": 500, "c1": 800},
- }
- assert expected == levels[1].to_dict()
- assert ["groupA", "groupB"] == levels[2].index.names
- assert ["groupA", "groupB", "groupC"] == levels[3].index.names
-
- def test_levels_for_diff_computes_difference(self):
- raw = {}
- raw[DTTM_ALIAS] = [100, 200, 300, 100, 200, 300, 100, 200, 300]
- raw["groupA"] = ["a1", "a1", "a1", "b1", "b1", "b1", "c1", "c1", "c1"]
- raw["groupB"] = ["a2", "a2", "a2", "b2", "b2", "b2", "c2", "c2", "c2"]
- raw["groupC"] = ["a3", "a3", "a3", "b3", "b3", "b3", "c3", "c3", "c3"]
- raw["metric1"] = [1, 2, 3, 4, 5, 6, 7, 8, 9]
- raw["metric2"] = [10, 20, 30, 40, 50, 60, 70, 80, 90]
- raw["metric3"] = [100, 200, 300, 400, 500, 600, 700, 800, 900]
- df = pd.DataFrame(raw)
- groups = ["groupA", "groupB", "groupC"]
- test_viz = viz.PartitionViz(Mock(), {})
- time_op = "point_diff"
- levels = test_viz.levels_for_diff(time_op, groups, df)
- expected = {"metric1": 6, "metric2": 60, "metric3": 600}
- assert expected == levels[0].to_dict()
- expected = {
- "metric1": {"a1": 2, "b1": 2, "c1": 2},
- "metric2": {"a1": 20, "b1": 20, "c1": 20},
- "metric3": {"a1": 200, "b1": 200, "c1": 200},
- }
- assert expected == levels[1].to_dict()
- assert 4 == len(levels)
- assert ["groupA", "groupB", "groupC"] == levels[3].index.names
-
- def test_levels_for_time_calls_process_data_and_drops_cols(self):
- raw = {}
- raw[DTTM_ALIAS] = [100, 200, 300, 100, 200, 300, 100, 200, 300]
- raw["groupA"] = ["a1", "a1", "a1", "b1", "b1", "b1", "c1", "c1", "c1"]
- raw["groupB"] = ["a2", "a2", "a2", "b2", "b2", "b2", "c2", "c2", "c2"]
- raw["groupC"] = ["a3", "a3", "a3", "b3", "b3", "b3", "c3", "c3", "c3"]
- raw["metric1"] = [1, 2, 3, 4, 5, 6, 7, 8, 9]
- raw["metric2"] = [10, 20, 30, 40, 50, 60, 70, 80, 90]
- raw["metric3"] = [100, 200, 300, 400, 500, 600, 700, 800, 900]
- df = pd.DataFrame(raw)
- groups = ["groupA", "groupB", "groupC"]
- test_viz = viz.PartitionViz(Mock(), {"groupby": groups})
-
- def return_args(df_drop, aggregate):
- return df_drop
-
- test_viz.process_data = Mock(side_effect=return_args)
- levels = test_viz.levels_for_time(groups, df)
- assert 4 == len(levels)
- cols = [DTTM_ALIAS, "metric1", "metric2", "metric3"]
- assert sorted(cols) == sorted(levels[0].columns.tolist())
- cols += ["groupA"]
- assert sorted(cols) == sorted(levels[1].columns.tolist())
- cols += ["groupB"]
- assert sorted(cols) == sorted(levels[2].columns.tolist())
- cols += ["groupC"]
- assert sorted(cols) == sorted(levels[3].columns.tolist())
- assert 4 == len(test_viz.process_data.mock_calls)
-
- def test_nest_values_returns_hierarchy(self):
- raw = {}
- raw["groupA"] = ["a1", "a1", "a1", "b1", "b1", "b1", "c1", "c1", "c1"]
- raw["groupB"] = ["a2", "a2", "a2", "b2", "b2", "b2", "c2", "c2", "c2"]
- raw["groupC"] = ["a3", "a3", "a3", "b3", "b3", "b3", "c3", "c3", "c3"]
- raw["metric1"] = [1, 2, 3, 4, 5, 6, 7, 8, 9]
- raw["metric2"] = [10, 20, 30, 40, 50, 60, 70, 80, 90]
- raw["metric3"] = [100, 200, 300, 400, 500, 600, 700, 800, 900]
- df = pd.DataFrame(raw)
- test_viz = viz.PartitionViz(Mock(), {})
- groups = ["groupA", "groupB", "groupC"]
- levels = test_viz.levels_for("agg_sum", groups, df)
- nest = test_viz.nest_values(levels)
- assert 3 == len(nest)
- for i in range(0, 3):
- assert "metric" + str(i + 1) == nest[i]["name"]
- assert 3 == len(nest[0]["children"])
- assert 1 == len(nest[0]["children"][0]["children"])
- assert 1 == len(nest[0]["children"][0]["children"][0]["children"])
-
- def test_nest_values_returns_hierarchy_when_more_dimensions(self):
- raw = {}
- raw["category"] = ["a", "a", "a"]
- raw["subcategory"] = ["a.2", "a.1", "a.2"]
- raw["sub_subcategory"] = ["a.2.1", "a.1.1", "a.2.2"]
- raw["metric1"] = [5, 10, 15]
- raw["metric2"] = [50, 100, 150]
- raw["metric3"] = [500, 1000, 1500]
- df = pd.DataFrame(raw)
- test_viz = viz.PartitionViz(Mock(), {})
- groups = ["category", "subcategory", "sub_subcategory"]
- levels = test_viz.levels_for("agg_sum", groups, df)
- nest = test_viz.nest_values(levels)
- assert 3 == len(nest)
- for i in range(0, 3):
- assert "metric" + str(i + 1) == nest[i]["name"]
- assert 1 == len(nest[0]["children"])
- assert 2 == len(nest[0]["children"][0]["children"])
- assert 1 == len(nest[0]["children"][0]["children"][0]["children"])
- assert 2 == len(nest[0]["children"][0]["children"][1]["children"])
-
- def test_nest_procs_returns_hierarchy(self):
- raw = {}
- raw[DTTM_ALIAS] = [100, 200, 300, 100, 200, 300, 100, 200, 300]
- raw["groupA"] = ["a1", "a1", "a1", "b1", "b1", "b1", "c1", "c1", "c1"]
- raw["groupB"] = ["a2", "a2", "a2", "b2", "b2", "b2", "c2", "c2", "c2"]
- raw["groupC"] = ["a3", "a3", "a3", "b3", "b3", "b3", "c3", "c3", "c3"]
- raw["metric1"] = [1, 2, 3, 4, 5, 6, 7, 8, 9]
- raw["metric2"] = [10, 20, 30, 40, 50, 60, 70, 80, 90]
- raw["metric3"] = [100, 200, 300, 400, 500, 600, 700, 800, 900]
- df = pd.DataFrame(raw)
- test_viz = viz.PartitionViz(Mock(), {})
- groups = ["groupA", "groupB", "groupC"]
- metrics = ["metric1", "metric2", "metric3"]
- procs = {}
- for i in range(0, 4):
- df_drop = df.drop(groups[i:], axis=1)
- pivot = df_drop.pivot_table(
- index=DTTM_ALIAS, columns=groups[:i], values=metrics
- )
- procs[i] = pivot
- nest = test_viz.nest_procs(procs)
- assert 3 == len(nest)
- for i in range(0, 3):
- assert "metric" + str(i + 1) == nest[i]["name"]
- assert None is nest[i].get("val")
- assert 3 == len(nest[0]["children"])
- assert 3 == len(nest[0]["children"][0]["children"])
- assert 1 == len(nest[0]["children"][0]["children"][0]["children"])
- assert 1 == len(
- nest[0]["children"][0]["children"][0]["children"][0]["children"]
- )
-
- def test_get_data_calls_correct_method(self):
- raw = {}
- raw[DTTM_ALIAS] = [100, 200, 300, 100, 200, 300, 100, 200, 300]
- raw["groupA"] = ["a1", "a1", "a1", "b1", "b1", "b1", "c1", "c1", "c1"]
- raw["groupB"] = ["a2", "a2", "a2", "b2", "b2", "b2", "c2", "c2", "c2"]
- raw["groupC"] = ["a3", "a3", "a3", "b3", "b3", "b3", "c3", "c3", "c3"]
- raw["metric1"] = [1, 2, 3, 4, 5, 6, 7, 8, 9]
- raw["metric2"] = [10, 20, 30, 40, 50, 60, 70, 80, 90]
- raw["metric3"] = [100, 200, 300, 400, 500, 600, 700, 800, 900]
- df = pd.DataFrame(raw)
- test_viz = viz.PartitionViz(Mock(), {})
- with self.assertRaises(ValueError): # noqa: PT027
- test_viz.get_data(df)
- test_viz.levels_for = Mock(return_value=1)
- test_viz.nest_values = Mock(return_value=1)
- test_viz.form_data["groupby"] = ["groups"]
- test_viz.form_data["time_series_option"] = "not_time"
- test_viz.get_data(df)
- assert "agg_sum" == test_viz.levels_for.mock_calls[0][1][0]
- test_viz.form_data["time_series_option"] = "agg_sum"
- test_viz.get_data(df)
- assert "agg_sum" == test_viz.levels_for.mock_calls[1][1][0]
- test_viz.form_data["time_series_option"] = "agg_mean"
- test_viz.get_data(df)
- assert "agg_mean" == test_viz.levels_for.mock_calls[2][1][0]
- test_viz.form_data["time_series_option"] = "point_diff"
- test_viz.levels_for_diff = Mock(return_value=1)
- test_viz.get_data(df)
- assert "point_diff" == test_viz.levels_for_diff.mock_calls[0][1][0]
- test_viz.form_data["time_series_option"] = "point_percent"
- test_viz.get_data(df)
- assert "point_percent" == test_viz.levels_for_diff.mock_calls[1][1][0]
- test_viz.form_data["time_series_option"] = "point_factor"
- test_viz.get_data(df)
- assert "point_factor" == test_viz.levels_for_diff.mock_calls[2][1][0]
- test_viz.levels_for_time = Mock(return_value=1)
- test_viz.nest_procs = Mock(return_value=1)
- test_viz.form_data["time_series_option"] = "adv_anal"
- test_viz.get_data(df)
- assert 1 == len(test_viz.levels_for_time.mock_calls)
- assert 1 == len(test_viz.nest_procs.mock_calls)
- test_viz.form_data["time_series_option"] = "time_series"
- test_viz.get_data(df)
- assert "agg_sum" == test_viz.levels_for.mock_calls[3][1][0]
- assert 7 == len(test_viz.nest_values.mock_calls)
-
-
-class TestRoseVis(SupersetTestCase):
- def test_rose_vis_get_data(self):
- raw = {}
- t1 = pd.Timestamp("2000")
- t2 = pd.Timestamp("2002")
- t3 = pd.Timestamp("2004")
- raw[DTTM_ALIAS] = [t1, t2, t3, t1, t2, t3, t1, t2, t3]
- raw["groupA"] = ["a1", "a1", "a1", "b1", "b1", "b1", "c1", "c1", "c1"]
- raw["groupB"] = ["a2", "a2", "a2", "b2", "b2", "b2", "c2", "c2", "c2"]
- raw["groupC"] = ["a3", "a3", "a3", "b3", "b3", "b3", "c3", "c3", "c3"]
- raw["metric1"] = [1, 2, 3, 4, 5, 6, 7, 8, 9]
- df = pd.DataFrame(raw)
- fd = {"metrics": ["metric1"], "groupby": ["groupA"]}
- test_viz = viz.RoseViz(Mock(), fd)
- test_viz.metrics = fd["metrics"]
- res = test_viz.get_data(df)
- expected = {
- 946684800000000000: [
- {"time": t1, "value": 1, "key": ("a1",), "name": ("a1",)},
- {"time": t1, "value": 4, "key": ("b1",), "name": ("b1",)},
- {"time": t1, "value": 7, "key": ("c1",), "name": ("c1",)},
- ],
- 1009843200000000000: [
- {"time": t2, "value": 2, "key": ("a1",), "name": ("a1",)},
- {"time": t2, "value": 5, "key": ("b1",), "name": ("b1",)},
- {"time": t2, "value": 8, "key": ("c1",), "name": ("c1",)},
- ],
- 1072915200000000000: [
- {"time": t3, "value": 3, "key": ("a1",), "name": ("a1",)},
- {"time": t3, "value": 6, "key": ("b1",), "name": ("b1",)},
- {"time": t3, "value": 9, "key": ("c1",), "name": ("c1",)},
- ],
- }
- assert expected == res
-
-
-class TestTimeSeriesTableViz(SupersetTestCase):
- def test_get_data_metrics(self):
- form_data = {"metrics": ["sum__A", "count"], "groupby": []}
- datasource = self.get_datasource_mock()
- raw = {}
- t1 = pd.Timestamp("2000")
- t2 = pd.Timestamp("2002")
- raw[DTTM_ALIAS] = [t1, t2]
- raw["sum__A"] = [15, 20]
- raw["count"] = [6, 7]
- df = pd.DataFrame(raw)
- test_viz = viz.TimeTableViz(datasource, form_data)
- data = test_viz.get_data(df)
- # Check method correctly transforms data
- assert {"count", "sum__A"} == set(data["columns"])
- time_format = "%Y-%m-%d %H:%M:%S"
- expected = {
- t1.strftime(time_format): {"sum__A": 15, "count": 6},
- t2.strftime(time_format): {"sum__A": 20, "count": 7},
- }
- assert expected == data["records"]
-
- def test_get_data_group_by(self):
- form_data = {"metrics": ["sum__A"], "groupby": ["groupby1"]}
- datasource = self.get_datasource_mock()
- raw = {}
- t1 = pd.Timestamp("2000")
- t2 = pd.Timestamp("2002")
- raw[DTTM_ALIAS] = [t1, t1, t1, t2, t2, t2]
- raw["sum__A"] = [15, 20, 25, 30, 35, 40]
- raw["groupby1"] = ["a1", "a2", "a3", "a1", "a2", "a3"]
- df = pd.DataFrame(raw)
- test_viz = viz.TimeTableViz(datasource, form_data)
- data = test_viz.get_data(df)
- # Check method correctly transforms data
- assert {"a1", "a2", "a3"} == set(data["columns"])
- time_format = "%Y-%m-%d %H:%M:%S"
- expected = {
- t1.strftime(time_format): {"a1": 15, "a2": 20, "a3": 25},
- t2.strftime(time_format): {"a1": 30, "a2": 35, "a3": 40},
- }
- assert expected == data["records"]
-
- def test_get_data_multiple_group_by(self):
- sep = FLAT_COLUMN_SEPARATOR
- form_data = {"metrics": ["sum__A"], "groupby": ["groupby1", "groupby2"]}
- datasource = self.get_datasource_mock()
- raw = {}
- t1 = pd.Timestamp("2000")
- t2 = pd.Timestamp("2002")
- raw[DTTM_ALIAS] = [t1, t1, t1, t1, t2, t2, t2, t2]
- raw["sum__A"] = [15, 20, 25, 30, 35, 40, 45, 50]
- raw["groupby1"] = ["a1", "a2", "a1", "a2", "a1", "a2", "a1", "a2"]
- raw["groupby2"] = ["b1", "b1", "b2", "b2", "b1", "b1", "b2", "b2"]
- df = pd.DataFrame(raw)
- test_viz = viz.TimeTableViz(datasource, form_data)
- data = test_viz.get_data(df)
- # Columns should be flattened strings, not tuples
- a1_b1 = f"a1{sep}b1"
- a1_b2 = f"a1{sep}b2"
- a2_b1 = f"a2{sep}b1"
- a2_b2 = f"a2{sep}b2"
- assert {a1_b1, a1_b2, a2_b1, a2_b2} == set(data["columns"])
- time_format = "%Y-%m-%d %H:%M:%S"
- expected = {
- t1.strftime(time_format): {
- a1_b1: 15,
- a1_b2: 25,
- a2_b1: 20,
- a2_b2: 30,
- },
- t2.strftime(time_format): {
- a1_b1: 35,
- a1_b2: 45,
- a2_b1: 40,
- a2_b2: 50,
- },
- }
- assert expected == data["records"]
- assert data["is_group_by"] is True
-
- @patch("superset.viz.BaseViz.query_obj")
- def test_query_obj_throws_metrics_and_groupby(self, super_query_obj):
- datasource = self.get_datasource_mock()
- form_data = {"groupby": ["a"]}
- super_query_obj.return_value = {}
- test_viz = viz.TimeTableViz(datasource, form_data)
- with self.assertRaises(Exception): # noqa: B017, PT027
- test_viz.query_obj()
- form_data["metrics"] = ["x", "y"]
- test_viz = viz.TimeTableViz(datasource, form_data)
- with self.assertRaises(Exception): # noqa: B017, PT027
- test_viz.query_obj()
-
- def test_query_obj_order_by(self):
- test_viz = viz.TimeTableViz(
- self.get_datasource_mock(), {"metrics": ["sum__A", "count"], "groupby": []}
- )
- query_obj = test_viz.query_obj()
- assert query_obj["orderby"] == [("sum__A", False)]
-
-
-class TestBaseDeckGLViz(SupersetTestCase):
- def test_get_metrics(self):
- form_data = load_fixture("deck_path_form_data.json")
- datasource = self.get_datasource_mock()
- test_viz_deckgl = viz.BaseDeckGLViz(datasource, form_data)
- result = test_viz_deckgl.get_metrics()
- assert result == [form_data.get("size")]
-
- form_data = {}
- test_viz_deckgl = viz.BaseDeckGLViz(datasource, form_data)
- result = test_viz_deckgl.get_metrics()
- assert result == []
-
- def test_extract_tooltip_columns_string_items(self):
- """Test _extract_tooltip_columns with string items in tooltip_contents"""
- form_data = {"tooltip_contents": ["column1", "column2", "column3"]}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._extract_tooltip_columns()
- assert result == ["column1", "column2", "column3"]
-
- def test_extract_tooltip_columns_dict_items(self):
- """Test _extract_tooltip_columns with dict items in tooltip_contents"""
- form_data = {
- "tooltip_contents": [
- {"item_type": "column", "column_name": "LAT"},
- {"item_type": "column", "column_name": "LON"},
- {"item_type": "metric", "metric_name": "count"},
- {"item_type": "column", "column_name": "CITY"},
- ]
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._extract_tooltip_columns()
- assert result == ["LAT", "LON", "CITY"]
-
- def test_extract_tooltip_columns_mixed_items(self):
- """Test _extract_tooltip_columns with mixed string and dict items"""
- form_data = {
- "tooltip_contents": [
- "string_column",
- {"item_type": "column", "column_name": "dict_column"},
- {
- "item_type": "invalid",
- "column_name": "invalid_column",
- },
- {"item_type": "column"},
- ]
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._extract_tooltip_columns()
- assert result == ["string_column", "dict_column"]
-
- def test_extract_tooltip_columns_empty(self):
- """Test _extract_tooltip_columns with empty or missing tooltip_contents"""
- form_data = {"tooltip_contents": []}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._extract_tooltip_columns()
- assert result == []
-
- form_data = {}
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._extract_tooltip_columns()
- assert result == []
-
- def test_add_tooltip_columns_to_query_with_metrics(self):
- """Test _add_tooltip_columns_to_query when query has metrics"""
- form_data = {}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- query_obj = {
- "metrics": ["count", "avg_value"],
- "groupby": ["existing_column"],
- "columns": [],
- }
- tooltip_columns = ["tooltip_col1", "tooltip_col2", "existing_column"]
-
- test_viz._add_tooltip_columns_to_query(query_obj, tooltip_columns)
-
- # Should add to groupby, avoiding duplicates
- assert "tooltip_col1" in query_obj["groupby"]
- assert "tooltip_col2" in query_obj["groupby"]
- assert query_obj["groupby"].count("existing_column") == 1 # No duplicate
-
- def test_add_tooltip_columns_to_query_without_metrics(self):
- """Test _add_tooltip_columns_to_query when query has no metrics"""
- form_data = {}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- query_obj = {"metrics": [], "groupby": [], "columns": ["existing_column"]}
- tooltip_columns = ["tooltip_col1", "tooltip_col2", "existing_column"]
-
- test_viz._add_tooltip_columns_to_query(query_obj, tooltip_columns)
-
- # Should add to columns, avoiding duplicates
- assert "tooltip_col1" in query_obj["columns"]
- assert "tooltip_col2" in query_obj["columns"]
- assert query_obj["columns"].count("existing_column") == 1 # No duplicate
-
- def test_add_tooltip_columns_to_query_empty_columns(self):
- """Test _add_tooltip_columns_to_query with empty tooltip columns"""
- form_data = {}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- query_obj = {"metrics": [], "groupby": [], "columns": []}
- original_query_obj = query_obj.copy()
-
- test_viz._add_tooltip_columns_to_query(query_obj, [])
-
- # Should not modify query_obj
- assert query_obj == original_query_obj
-
- def test_integrate_tooltip_columns(self):
- """Test _integrate_tooltip_columns helper method"""
- form_data = {"tooltip_contents": ["LON", "LAT"]}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- query_obj = {"metrics": ["count"], "groupby": ["region"]}
-
- result = test_viz._integrate_tooltip_columns(query_obj)
-
- assert "LON" in result["groupby"]
- assert "LAT" in result["groupby"]
- assert "region" in result["groupby"]
- assert result is query_obj # Should return the same object
-
- def test_add_tooltip_properties(self):
- """Test _add_tooltip_properties helper method"""
- form_data = {"tooltip_contents": ["CITY", "POPULATION", "missing_column"]}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- properties = {"position": [1, 2], "weight": 100}
- data = {"CITY": "New York", "POPULATION": 8000000, "other_column": "value"}
-
- result = test_viz._add_tooltip_properties(properties, data)
-
- assert result["CITY"] == "New York"
- assert result["POPULATION"] == 8000000
- assert "missing_column" not in result # Missing column should not be added
- assert "other_column" not in result # Non-tooltip column should not be added
- assert result["position"] == [1, 2] # Original properties should remain
- assert result["weight"] == 100
- assert result is properties # Should return the same object
-
- def test_get_base_properties(self):
- """Test _get_base_properties helper method"""
- form_data = {}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
- test_viz.metric_label = "test_metric"
-
- data = {"spatial": [10.5, 20.3], "test_metric": 42, "other_field": "value"}
-
- result = test_viz._get_base_properties(data)
-
- assert result["position"] == [10.5, 20.3]
- assert result["weight"] == 42
- assert len(result) == 2 # Should only have position and weight
-
- def test_get_base_properties_no_metric(self):
- """Test _get_base_properties when no metric is available"""
- form_data = {}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
- test_viz.metric_label = None
-
- data = {"spatial": [10.5, 20.3]}
-
- result = test_viz._get_base_properties(data)
-
- assert result["position"] == [10.5, 20.3]
- assert result["weight"] == 1 # Should default to 1
-
- def test_setup_metric_label(self):
- """Test _setup_metric_label helper method"""
- form_data = {}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
- test_viz.metric = "SUM(sales)"
-
- with patch("superset.utils.core.get_metric_name") as mock_get_metric_name:
- mock_get_metric_name.return_value = "sum__sales"
-
- test_viz._setup_metric_label()
-
- assert test_viz.metric_label == "sum__sales"
- mock_get_metric_name.assert_called_once_with("SUM(sales)")
-
- def test_setup_metric_label_no_metric(self):
- """Test _setup_metric_label when metric is None"""
- form_data = {}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
- test_viz.metric = None
-
- test_viz._setup_metric_label()
-
- assert test_viz.metric_label is None
-
- def test_scatterviz_get_metrics(self):
- form_data = load_fixture("deck_path_form_data.json")
- datasource = self.get_datasource_mock()
-
- form_data = {}
- test_viz_deckgl = viz.DeckScatterViz(datasource, form_data)
- test_viz_deckgl.point_radius_fixed = {"type": "metric", "value": "int"}
- result = test_viz_deckgl.get_metrics()
- assert result == ["int"]
-
- form_data = {}
- test_viz_deckgl = viz.DeckScatterViz(datasource, form_data)
- test_viz_deckgl.point_radius_fixed = {}
- result = test_viz_deckgl.get_metrics()
- assert result == []
-
- def test_get_js_columns(self):
- form_data = load_fixture("deck_path_form_data.json")
- datasource = self.get_datasource_mock()
- mock_d = {"a": "dummy1", "b": "dummy2", "c": "dummy3"}
- test_viz_deckgl = viz.BaseDeckGLViz(datasource, form_data)
- result = test_viz_deckgl.get_js_columns(mock_d)
-
- assert result == {"color": None}
-
- def test_get_properties(self):
- mock_d = {}
- form_data = load_fixture("deck_path_form_data.json")
- datasource = self.get_datasource_mock()
- test_viz_deckgl = viz.BaseDeckGLViz(datasource, form_data)
-
- with self.assertRaises(NotImplementedError) as context: # noqa: PT027
- test_viz_deckgl.get_properties(mock_d)
-
- assert "" in str(context.exception)
-
- def test_process_spatial_query_obj(self):
- form_data = load_fixture("deck_path_form_data.json")
- datasource = self.get_datasource_mock()
- mock_key = "spatial_key"
- mock_gb = []
- test_viz_deckgl = viz.BaseDeckGLViz(datasource, form_data)
-
- with self.assertRaises(ValueError) as context: # noqa: PT027
- test_viz_deckgl.process_spatial_query_obj(mock_key, mock_gb)
-
- assert "Bad spatial key" in str(context.exception)
-
- test_form_data = {
- "latlong_key": {"type": "latlong", "lonCol": "lon", "latCol": "lat"},
- "delimited_key": {"type": "delimited", "lonlatCol": "lonlat"},
- "geohash_key": {"type": "geohash", "geohashCol": "geo"},
- }
-
- datasource = self.get_datasource_mock()
- expected_results = {
- "latlong_key": ["lon", "lat"],
- "delimited_key": ["lonlat"],
- "geohash_key": ["geo"],
- }
- for mock_key in ["latlong_key", "delimited_key", "geohash_key"]:
- mock_gb = []
- test_viz_deckgl = viz.BaseDeckGLViz(datasource, test_form_data)
- test_viz_deckgl.process_spatial_query_obj(mock_key, mock_gb)
- assert expected_results.get(mock_key) == mock_gb
-
- def test_geojson_query_obj(self):
- form_data = load_fixture("deck_geojson_form_data.json")
- datasource = self.get_datasource_mock()
- test_viz_deckgl = viz.DeckGeoJson(datasource, form_data)
- results = test_viz_deckgl.query_obj()
-
- assert results["metrics"] == []
- assert results["groupby"] == []
- assert results["columns"] == ["test_col"]
-
- def test_parse_coordinates(self):
- form_data = load_fixture("deck_path_form_data.json")
- datasource = self.get_datasource_mock()
- viz_instance = viz.BaseDeckGLViz(datasource, form_data)
-
- coord = viz_instance.parse_coordinates("1.23, 3.21")
- assert coord == (1.23, 3.21)
-
- coord = viz_instance.parse_coordinates("1.23 3.21")
- assert coord == (1.23, 3.21)
-
- assert viz_instance.parse_coordinates(None) is None
-
- assert viz_instance.parse_coordinates("") is None
-
- def test_parse_coordinates_raises(self):
- form_data = load_fixture("deck_path_form_data.json")
- datasource = self.get_datasource_mock()
- test_viz_deckgl = viz.BaseDeckGLViz(datasource, form_data)
-
- with self.assertRaises(SpatialException): # noqa: PT027
- test_viz_deckgl.parse_coordinates("NULL")
-
- with self.assertRaises(SpatialException): # noqa: PT027
- test_viz_deckgl.parse_coordinates("fldkjsalkj,fdlaskjfjadlksj")
-
- def test_deckscatter_query_obj_integration(self):
- """Test DeckScatterViz query_obj uses new tooltip integration"""
- form_data = {
- "tooltip_contents": ["CITY", "POPULATION"],
- "time_grain_sqla": "P1D",
- "point_radius_fixed": {"type": "fix", "value": 500},
- "spatial": {
- "type": "latlong",
- "lonCol": "longitude",
- "latCol": "latitude",
- },
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.DeckScatterViz(datasource, form_data)
-
- with patch.object(test_viz, "_integrate_tooltip_columns") as mock_integrate:
- mock_integrate.return_value = {"mocked": "result"}
-
- result = test_viz.query_obj()
-
- # Should call the new helper method
- mock_integrate.assert_called_once()
- assert result == {"mocked": "result"}
-
- # Should set up instance variables
- assert test_viz.is_timeseries is True
- assert test_viz.point_radius_fixed == {"type": "fix", "value": 500}
-
- def test_deckscatter_query_obj_no_time_grain(self):
- """Test DeckScatterViz query_obj when time_grain_sqla is not set"""
- form_data = {
- "tooltip_contents": ["CITY"],
- "point_radius_fixed": {"type": "metric", "value": "count"},
- "spatial": {
- "type": "latlong",
- "lonCol": "longitude",
- "latCol": "latitude",
- },
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.DeckScatterViz(datasource, form_data)
-
- with patch.object(test_viz, "_integrate_tooltip_columns") as mock_integrate:
- mock_integrate.return_value = {"result": "data"}
-
- test_viz.query_obj()
-
- # Should set timeseries to False when no time_grain_sqla
- assert test_viz.is_timeseries is False
-
- def test_deckscatter_get_properties_uses_helper(self):
- """Test DeckScatterViz get_properties uses new helper method"""
- form_data = {"tooltip_contents": ["CITY", "STATE"], "dimension": "region"}
- datasource = self.get_datasource_mock()
- test_viz = viz.DeckScatterViz(datasource, form_data)
- test_viz.metric_label = "count"
- test_viz.fixed_value = 10
- test_viz.dim = "region"
-
- data = {
- "spatial": [40.7, -74.0],
- "count": 100,
- "region": "northeast",
- "CITY": "New York",
- "STATE": "NY",
- "__timestamp": "2023-01-01",
- }
-
- with patch.object(test_viz, "_add_tooltip_properties") as mock_add_tooltip:
- mock_add_tooltip.return_value = {"final": "result"}
-
- result = test_viz.get_properties(data)
-
- expected_base_properties = {
- "metric": 100,
- "radius": 10,
- "cat_color": "northeast",
- "position": [40.7, -74.0],
- "__timestamp": "2023-01-01",
- }
- mock_add_tooltip.assert_called_once_with(expected_base_properties, data)
- assert result == {"final": "result"}
-
- def test_deckscatter_get_data_uses_setup_metric_label(self):
- """Test DeckScatterViz get_data uses new _setup_metric_label helper"""
- form_data = {
- "point_radius_fixed": {"type": "metric", "value": "avg_sales"},
- "dimension": "category",
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.DeckScatterViz(datasource, form_data)
- test_df = pd.DataFrame({"col1": [1, 2], "col2": [3, 4]})
-
- with patch.object(test_viz, "_setup_metric_label") as mock_setup:
- with patch("superset.viz.BaseDeckGLViz.get_data") as mock_super_get_data:
- mock_super_get_data.return_value = {"test": "data"}
-
- result = test_viz.get_data(test_df)
-
- mock_setup.assert_called_once()
-
- assert test_viz.point_radius_fixed == {
- "type": "metric",
- "value": "avg_sales",
- }
- assert test_viz.fixed_value is None
- assert test_viz.dim == "category"
-
- mock_super_get_data.assert_called_once_with(test_df)
- assert result == {"test": "data"}
-
- def test_deckscatter_get_data_with_fixed_radius(self):
- """Test DeckScatterViz get_data with fixed radius type"""
- form_data = {
- "point_radius_fixed": {"type": "fix", "value": 25},
- "dimension": "location",
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.DeckScatterViz(datasource, form_data)
- test_df = pd.DataFrame({"col1": [1, 2]})
-
- with patch.object(test_viz, "_setup_metric_label"):
- with patch("superset.viz.BaseDeckGLViz.get_data") as mock_super_get_data:
- mock_super_get_data.return_value = {"result": "ok"}
-
- test_viz.get_data(test_df)
-
- # Should set fixed_value when type is not 'metric'
- assert test_viz.fixed_value == 25
-
- def test_tooltip_integration_end_to_end(self):
- """Test complete tooltip integration from query_obj to get_properties"""
- form_data = {
- "tooltip_contents": ["CITY", "POPULATION"],
- "size": "count",
- "time_grain_sqla": None,
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.DeckScatterViz(datasource, form_data)
-
- with patch("superset.viz.BaseDeckGLViz.query_obj") as mock_super_query:
- mock_super_query.return_value = {
- "metrics": ["count"],
- "groupby": ["region"],
- "columns": [],
- }
-
- query_result = test_viz.query_obj()
-
- # Should have added tooltip columns to groupby
- assert "CITY" in query_result["groupby"]
- assert "POPULATION" in query_result["groupby"]
- assert "region" in query_result["groupby"]
-
- test_viz.metric_label = "count"
- test_viz.fixed_value = None
- test_viz.dim = "region"
-
- data = {
- "spatial": [40.7, -74.0],
- "count": 5000,
- "region": "northeast",
- "CITY": "New York",
- "POPULATION": 8000000,
- "__timestamp": "2023-01-01",
- }
-
- properties_result = test_viz.get_properties(data)
-
- # Should include both base properties and tooltip properties
- assert properties_result["position"] == [40.7, -74.0]
- assert properties_result["metric"] == 5000
- assert properties_result["cat_color"] == "northeast"
- assert properties_result["__timestamp"] == "2023-01-01"
- assert properties_result["CITY"] == "New York"
- assert properties_result["POPULATION"] == 8000000
-
- def test_filter_nulls(self):
- test_form_data = {
- "latlong_key": {"type": "latlong", "lonCol": "lon", "latCol": "lat"},
- "delimited_key": {"type": "delimited", "lonlatCol": "lonlat"},
- "geohash_key": {"type": "geohash", "geohashCol": "geo"},
- }
-
- datasource = self.get_datasource_mock()
- # SHA-256 filterOptionName hashes with default HASH_ALGORITHM
- expected_results = {
- "latlong_key": [
- {
- "clause": "WHERE",
- "expressionType": "SIMPLE",
- "filterOptionName": (
- "980dd3068274177120307d9182ea8e8ee1b7824d34fbc21c529441f5d3279f7f"
- ),
- "comparator": "",
- "operator": "IS NOT NULL",
- "subject": "lat",
- },
- {
- "clause": "WHERE",
- "expressionType": "SIMPLE",
- "filterOptionName": (
- "e368c259da27e5ec6a854772d9bff2c2af8dd5762352cef4ff6afc5bd8b6b9ea"
- ),
- "comparator": "",
- "operator": "IS NOT NULL",
- "subject": "lon",
- },
- ],
- "delimited_key": [
- {
- "clause": "WHERE",
- "expressionType": "SIMPLE",
- "filterOptionName": (
- "6ea33b70ab781033af421240019d3e3ad782928a3ad2999538f1f4b2a52305e2"
- ),
- "comparator": "",
- "operator": "IS NOT NULL",
- "subject": "lonlat",
- }
- ],
- "geohash_key": [
- {
- "clause": "WHERE",
- "expressionType": "SIMPLE",
- "filterOptionName": (
- "48bbd94cd6afb1885d8550e2928bc01a2d3bc7d1f4f1d0929b10d6f4021b7f14"
- ),
- "comparator": "",
- "operator": "IS NOT NULL",
- "subject": "geo",
- }
- ],
- }
- for mock_key in ["latlong_key", "delimited_key", "geohash_key"]:
- test_viz_deckgl = viz.BaseDeckGLViz(datasource, test_form_data.copy())
- test_viz_deckgl.spatial_control_keys = [mock_key]
- test_viz_deckgl.add_null_filters()
- adhoc_filters = test_viz_deckgl.form_data["adhoc_filters"]
- assert expected_results.get(mock_key) == adhoc_filters
-
- def test_init_with_layer_filtering_applied(self):
- """Test BaseDeckGLViz.__init__ applies layer filtering when conditions are
- met."""
- datasource = self.get_datasource_mock()
- form_data = {
- "slice_id": 123,
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- "layerFilterScope": [0, 1],
- "deck_slices": [123, 456],
- },
- {
- "clause": "WHERE",
- "subject": "col2",
- "operator": "!=",
- "comparator": "value2",
- "layerFilterScope": [1],
- "deck_slices": [123, 456],
- },
- ],
- }
-
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- # Should only have the first filter (scoped to layer 0)
- assert len(test_viz.form_data["adhoc_filters"]) == 1
- assert test_viz.form_data["adhoc_filters"][0]["subject"] == "col1"
-
- def test_init_without_layer_filtering(self):
- """Test BaseDeckGLViz.__init__ doesn't apply filtering when conditions
- aren't met."""
- datasource = self.get_datasource_mock()
- form_data = {
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- }
- ]
- }
- original_filters = form_data["adhoc_filters"].copy()
-
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- # Filters should remain unchanged
- assert test_viz.form_data["adhoc_filters"] == original_filters
-
- def test_should_apply_layer_filtering_true(self):
- """Test _should_apply_layer_filtering returns True when all conditions are
- met."""
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- form_data = {"slice_id": 123, "adhoc_filters": [{"layerFilterScope": [0, 1]}]}
-
- result = test_viz._should_apply_layer_filtering(form_data)
- assert result is True
-
- def test_should_apply_layer_filtering_false_missing_slice_id(self):
- """Test _should_apply_layer_filtering returns False when slice_id is missing."""
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- form_data = {"adhoc_filters": [{"layerFilterScope": [0, 1]}]}
-
- result = test_viz._should_apply_layer_filtering(form_data)
- assert result is False
-
- def test_should_apply_layer_filtering_false_missing_adhoc_filters(self):
- """Test _should_apply_layer_filtering returns False when
- adhoc_filters missing"""
- form_data = {"slice_id": 123}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._should_apply_layer_filtering(form_data)
-
- assert result is False
-
- def test_should_apply_layer_filtering_false_no_layer_scoped_filters(self):
- """Test _should_apply_layer_filtering returns False when no
- layer scoped filters"""
- form_data = {
- "slice_id": 123,
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._should_apply_layer_filtering(form_data)
-
- assert result is False
-
- def test_has_layer_scoped_filters_true_with_dict(self):
- """Test _has_layer_scoped_filters returns True when filter
- has layerFilterScope"""
- form_data = {
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- "layerFilterScope": [0, 1],
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._has_layer_scoped_filters(form_data)
-
- assert result is True
-
- def test_has_layer_scoped_filters_true_with_non_none_value(self):
- """Test _has_layer_scoped_filters returns True when layerFilterScope not None"""
- form_data = {
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- "layerFilterScope": [],
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._has_layer_scoped_filters(form_data)
-
- assert result is True
-
- def test_has_layer_scoped_filters_false_none_value(self):
- """Test _has_layer_scoped_filters returns False when layerFilterScope is None"""
- form_data = {"adhoc_filters": [{"layerFilterScope": None}, {"clause": "WHERE"}]}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._has_layer_scoped_filters(form_data)
-
- assert result is False
-
- def test_has_layer_scoped_filters_false_no_scoped_filters(self):
- """Test _has_layer_scoped_filters returns False when no filters
- have layerFilterScope"""
- form_data = {
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._has_layer_scoped_filters(form_data)
-
- assert result is False
-
- def test_apply_multilayer_filtering_filters_by_layer_scope(self):
- """Test _apply_multilayer_filtering correctly filters by layer scope."""
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- form_data = {
- "slice_id": 456, # This is layer index 1
- "adhoc_filters": [
- {
- "subject": "global_filter",
- "deck_slices": [123, 456],
- # No layerFilterScope = global filter
- },
- {
- "subject": "layer_0_filter",
- "layerFilterScope": [0],
- "deck_slices": [123, 456],
- },
- {
- "subject": "layer_1_filter",
- "layerFilterScope": [1],
- "deck_slices": [123, 456],
- },
- {
- "subject": "layer_0_1_filter",
- "layerFilterScope": [0, 1],
- "deck_slices": [123, 456],
- },
- ],
- }
-
- result = test_viz._apply_multilayer_filtering(form_data)
-
- # Should include: global_filter, layer_1_filter, layer_0_1_filter
- assert len(result["adhoc_filters"]) == 3
- subjects = [f["subject"] for f in result["adhoc_filters"]]
- assert "global_filter" in subjects
- assert "layer_1_filter" in subjects
- assert "layer_0_1_filter" in subjects
- assert "layer_0_filter" not in subjects
-
- def test_apply_multilayer_filtering_no_deck_slices(self):
- """Test _apply_multilayer_filtering returns original form_data when no
- deck_slices."""
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- form_data = {"slice_id": 123, "adhoc_filters": [{"subject": "filter1"}]}
-
- result = test_viz._apply_multilayer_filtering(form_data)
-
- # Should return original form_data unchanged
- assert result == form_data
-
- def test_apply_multilayer_filtering_slice_not_in_deck_slices(self):
- """Test _apply_multilayer_filtering returns original when slice_id not in
- deck_slices."""
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- form_data = {
- "slice_id": 999, # Not in deck_slices
- "adhoc_filters": [{"subject": "filter1", "deck_slices": [123, 456]}],
- }
-
- result = test_viz._apply_multilayer_filtering(form_data)
-
- # Should return original form_data unchanged
- assert result == form_data
-
- def test_get_deck_slices_from_filters_found(self):
- """Test _get_deck_slices_from_filters returns deck_slices when found."""
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- form_data = {
- "adhoc_filters": [
- {"subject": "filter1"},
- {"subject": "filter2", "deck_slices": [123, 456, 789]},
- {"subject": "filter3"},
- ]
- }
-
- result = test_viz._get_deck_slices_from_filters(form_data)
-
- assert result == [123, 456, 789]
-
- def test_get_deck_slices_from_filters_not_found(self):
- """Test _get_deck_slices_from_filters returns None when not found."""
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- form_data = {"adhoc_filters": [{"subject": "filter1"}, {"subject": "filter2"}]}
-
- result = test_viz._get_deck_slices_from_filters(form_data)
-
- assert result is None
-
- def test_get_deck_slices_from_filters_empty_filters(self):
- """Test _get_deck_slices_from_filters returns None when adhoc_filters is
- empty."""
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- form_data = {"adhoc_filters": []}
-
- result = test_viz._get_deck_slices_from_filters(form_data)
-
- assert result is None
-
- def test_get_filter_layer_scope_dict(self):
- """Test _get_filter_layer_scope with dict filter item."""
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- filter_item = {"layerFilterScope": [0, 1, 2]}
- result = test_viz._get_filter_layer_scope(filter_item)
-
- assert result == [0, 1, 2]
-
- def test_get_filter_layer_scope_dict_none(self):
- """Test _get_filter_layer_scope with dict that has None layerFilterScope."""
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- filter_item = {"layerFilterScope": None}
- result = test_viz._get_filter_layer_scope(filter_item)
-
- assert result is None
-
- def test_get_filter_layer_scope_dict_missing_key(self):
- """Test _get_filter_layer_scope with dict missing layerFilterScope."""
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- filter_item = {"subject": "col1"}
- result = test_viz._get_filter_layer_scope(filter_item)
-
- assert result is None
-
- def test_get_filter_layer_scope_object_with_attribute(self):
- """Test _get_filter_layer_scope with object having layerFilterScope
- attribute."""
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- from unittest.mock import Mock
-
- filter_item = Mock()
- filter_item.layerFilterScope = [1, 2]
-
- result = test_viz._get_filter_layer_scope(filter_item)
-
- assert result == [1, 2]
-
- def test_get_filter_layer_scope_object_without_attribute(self):
- """Test _get_filter_layer_scope with object missing layerFilterScope
- attribute."""
- filter_item = Mock()
- del filter_item.layerFilterScope
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- result = test_viz._get_filter_layer_scope(filter_item)
-
- assert result is None
-
- def test_get_filter_layer_scope_non_dict_non_object(self):
- """Test _get_filter_layer_scope with non-dict, non-object types."""
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- # Test with string
- result = test_viz._get_filter_layer_scope("string_filter")
- assert result is None
-
- # Test with number
- result = test_viz._get_filter_layer_scope(123)
- assert result is None
-
- # Test with None
- result = test_viz._get_filter_layer_scope(None)
- assert result is None
-
-
-class TestDeckGLMultiLayer(SupersetTestCase):
- def test_filter_items_by_scope_with_filter_id(self):
- """Test _filter_items_by_scope method with items having filterId."""
- datasource = self.get_datasource_mock()
- form_data = {}
- test_viz = viz.DeckGLMultiLayer(datasource, form_data)
-
- filter_item_1 = Mock()
- filter_item_1.filterId = "filter_1"
- filter_item_2 = Mock()
- filter_item_2.filterId = "filter_2"
- filter_item_3 = Mock()
- filter_item_3.filterId = "filter_3"
-
- items = [filter_item_1, filter_item_2, filter_item_3]
- layer_index = 0
- layer_filter_scope = {"filter_1": [0, 1], "filter_2": [1], "filter_3": []}
-
- result = test_viz._filter_items_by_scope(items, layer_index, layer_filter_scope)
-
- assert len(result) == 2
- assert filter_item_1 in result
- assert filter_item_3 in result
- assert filter_item_2 not in result
-
- def test_filter_items_by_scope_without_filter_id(self):
- """Test _filter_items_by_scope method with items without filterId."""
- datasource = self.get_datasource_mock()
- form_data = {}
- test_viz = viz.DeckGLMultiLayer(datasource, form_data)
-
- filter_item_1 = Mock()
- del filter_item_1.filterId
- filter_item_2 = Mock()
- filter_item_2.filterId = None
-
- items = [filter_item_1, filter_item_2]
- layer_index = 0
- layer_filter_scope = {"filter_1": [1]}
-
- result = test_viz._filter_items_by_scope(items, layer_index, layer_filter_scope)
-
- assert len(result) == 2
- assert filter_item_1 in result
- assert filter_item_2 in result
-
- def test_process_extra_form_data_filters(self):
- """Test _process_extra_form_data_filters method."""
- datasource = self.get_datasource_mock()
- form_data = {}
- test_viz = viz.DeckGLMultiLayer(datasource, form_data)
-
- layer_index = 0
- layer_filter_scope = {"filter_1": [0, 1], "filter_2": [1], "filter_3": []}
- filter_data_mapping = {
- "filter_1": [{"column": "col1", "op": "==", "val": "value1"}],
- "filter_2": [{"column": "col2", "op": "!=", "val": "value2"}],
- "filter_3": [{"column": "col3", "op": ">", "val": 100}],
- }
- extra_form_data = {"existing_key": "existing_value"}
-
- result = test_viz._process_extra_form_data_filters(
- layer_index, layer_filter_scope, filter_data_mapping, extra_form_data
- )
-
- expected_filters = [
- {"column": "col1", "op": "==", "val": "value1"},
- {"column": "col3", "op": ">", "val": 100},
- ]
- assert result["filters"] == expected_filters
- assert result["existing_key"] == "existing_value"
-
- def test_process_extra_form_data_filters_empty_inputs(self):
- """Test _process_extra_form_data_filters with empty inputs."""
- datasource = self.get_datasource_mock()
- form_data = {}
- test_viz = viz.DeckGLMultiLayer(datasource, form_data)
-
- result = test_viz._process_extra_form_data_filters(0, {}, {}, {})
- assert result == {}
-
- extra_form_data = {"key": "value"}
- result = test_viz._process_extra_form_data_filters(0, {}, {}, extra_form_data)
- assert result == extra_form_data
-
- def test_apply_layer_filtering_without_layer_filter_scope(self):
- """Test _apply_layer_filtering when layer_filter_scope is empty."""
- datasource = self.get_datasource_mock()
- form_data = {
- "extra_filters": [Mock(), Mock()],
- "adhoc_filters": [Mock()],
- "extra_form_data": {"key": "value"},
- }
- test_viz = viz.DeckGLMultiLayer(datasource, form_data)
-
- layer_form_data = {"viz_type": "deck_scatter"}
- layer_index = 0
-
- result = test_viz._apply_layer_filtering(layer_form_data, layer_index)
-
- assert result["extra_filters"] == form_data["extra_filters"]
- assert result["adhoc_filters"] == form_data["adhoc_filters"]
- assert result["extra_form_data"] == form_data["extra_form_data"]
-
- def test_apply_layer_filtering_with_layer_filter_scope(self):
- """Test _apply_layer_filtering with layer_filter_scope."""
- datasource = self.get_datasource_mock()
-
- extra_filter_1 = Mock()
- extra_filter_1.filterId = "filter_1"
- extra_filter_2 = Mock()
- extra_filter_2.filterId = "filter_2"
-
- adhoc_filter_1 = Mock()
- adhoc_filter_1.filterId = "filter_1"
-
- form_data = {
- "layer_filter_scope": {"filter_1": [0], "filter_2": [1]},
- "filter_data_mapping": {
- "filter_1": [{"column": "col1", "op": "==", "val": "value1"}]
- },
- "extra_filters": [extra_filter_1, extra_filter_2],
- "adhoc_filters": [adhoc_filter_1],
- "extra_form_data": {"existing": "data"},
- }
- test_viz = viz.DeckGLMultiLayer(datasource, form_data)
-
- layer_form_data = {"viz_type": "deck_scatter"}
- layer_index = 0
-
- result = test_viz._apply_layer_filtering(layer_form_data, layer_index)
-
- assert len(result["extra_filters"]) == 1
- assert result["extra_filters"][0].filterId == "filter_1"
- assert len(result["adhoc_filters"]) == 1
- assert result["adhoc_filters"][0].filterId == "filter_1"
- assert result["extra_form_data"]["filters"] == [
- {"column": "col1", "op": "==", "val": "value1"}
- ]
-
- @with_config({"MAPBOX_API_KEY": "test_key"})
- @patch("superset.viz.viz_types")
- @patch("superset.db.session")
- def test_get_data_with_layer_filtering(self, mock_db_session, mock_viz_types):
- """Test get_data method with layer filtering enabled."""
- datasource = self.get_datasource_mock()
-
- slice_1 = Mock()
- slice_1.form_data = {"viz_type": "deck_scatter", "layer_name": "Layer 1"}
- slice_1.data = {"features": [{"type": "Feature"}]}
- slice_1.datasource = datasource
-
- slice_2 = Mock()
- slice_2.form_data = {"viz_type": "deck_path", "layer_name": "Layer 2"}
- slice_2.data = {"features": [{"type": "Feature"}]}
- slice_2.datasource = datasource
-
- # Mock the database query to return our slice objects
- mock_db_session.query.return_value.filter.return_value.all.return_value = [
- slice_1,
- slice_2,
- ]
-
- mock_scatter_viz_class = Mock()
- mock_scatter_viz_instance = Mock()
- mock_scatter_viz_instance.get_payload.return_value = {
- "data": {"features": [{"id": 1}]}
- }
- mock_scatter_viz_class.return_value = mock_scatter_viz_instance
-
- mock_path_viz_class = Mock()
- mock_path_viz_instance = Mock()
- mock_path_viz_instance.get_payload.return_value = {
- "data": {"features": [{"id": 2}]}
- }
- mock_path_viz_class.return_value = mock_path_viz_instance
-
- mock_viz_types.get.side_effect = lambda viz_type: {
- "deck_scatter": mock_scatter_viz_class,
- "deck_path": mock_path_viz_class,
- }.get(viz_type)
-
- form_data = {
- "layer_filter_scope": {"filter_1": [0], "filter_2": [1]},
- "filter_data_mapping": {
- "filter_1": [{"column": "col1", "op": "==", "val": "value1"}],
- "filter_2": [{"column": "col2", "op": "!=", "val": "value2"}],
- },
- "deck_slices": [1, 2], # Use integer IDs instead of Mock objects
- }
-
- test_viz = viz.DeckGLMultiLayer(datasource, form_data)
-
- test_viz._apply_layer_filtering = Mock(
- side_effect=lambda form_data, idx: form_data
- )
-
- result = test_viz.get_data(pd.DataFrame())
-
- assert test_viz._apply_layer_filtering.call_count == 2
- test_viz._apply_layer_filtering.assert_any_call(slice_1.form_data, 0)
- test_viz._apply_layer_filtering.assert_any_call(slice_2.form_data, 1)
-
- assert isinstance(result, dict)
- assert "features" in result
- assert "mapboxApiKey" in result
- assert "slices" in result
- assert result["mapboxApiKey"] == "test_key"
-
- @with_config({"MAPBOX_API_KEY": "test_key"})
- @patch("superset.viz.viz_types")
- @patch("superset.db.session")
- def test_get_data_filters_none_data_slices(self, mock_db_session, mock_viz_types):
- """Test get_data method filters out slices with None data."""
- datasource = self.get_datasource_mock()
-
- slice_1 = Mock()
- slice_1.form_data = {"viz_type": "deck_scatter"}
- slice_1.data = {"features": [{"type": "Feature"}]}
- slice_1.datasource = datasource
-
- slice_2 = Mock()
- slice_2.form_data = {"viz_type": "deck_path"}
- slice_2.data = None
- slice_2.datasource = datasource
-
- # Mock the database query to return our slice objects
- mock_db_session.query.return_value.filter.return_value.all.return_value = [
- slice_1,
- slice_2,
- ]
-
- mock_viz_class = Mock()
- mock_viz_instance = Mock()
- mock_viz_instance.get_payload.return_value = {"data": {"features": []}}
- mock_viz_class.return_value = mock_viz_instance
- mock_viz_types.get.return_value = mock_viz_class
-
- form_data = {"deck_slices": [1, 2]} # Use integer IDs instead of Mock objects
-
- test_viz = viz.DeckGLMultiLayer(datasource, form_data)
- result = test_viz.get_data(pd.DataFrame())
-
- assert isinstance(result, dict)
- assert len(result["slices"]) == 1
- assert result["slices"][0] == slice_1.data
-
- @with_config({"MAPBOX_API_KEY": "test_key"})
- @patch("superset.viz.viz_types")
- @patch("superset.db.session")
- def test_get_payload_includes_subslice_filter_metadata(
- self,
- mock_db_session,
- mock_viz_types,
- ):
- """Test deck.gl multi-layer payload includes child filter metadata."""
- datasource = self.get_datasource_mock()
-
- slice_1 = Mock()
- slice_1.form_data = {"viz_type": "deck_scatter"}
- slice_1.data = {"features": [{"type": "Feature"}]}
- slice_1.datasource = datasource
-
- slice_2 = Mock()
- slice_2.form_data = {"viz_type": "deck_path"}
- slice_2.data = {"features": [{"type": "Feature"}]}
- slice_2.datasource = datasource
-
- mock_db_session.query.return_value.filter.return_value.all.return_value = [
- slice_1,
- slice_2,
- ]
-
- mock_scatter_viz_class = Mock()
- mock_scatter_viz_instance = Mock()
- mock_scatter_viz_instance.get_payload.return_value = {
- "data": {"features": [{"id": 1}]},
- "applied_filters": [{"column": "Latitude"}],
- "rejected_filters": [],
- }
- mock_scatter_viz_class.return_value = mock_scatter_viz_instance
-
- mock_path_viz_class = Mock()
- mock_path_viz_instance = Mock()
- mock_path_viz_instance.get_payload.return_value = {
- "data": {"features": [{"id": 2}]},
- "applied_filters": [
- {"column": "Latitude"},
- {"column": "Longitude"},
- ],
- "rejected_filters": [
- {
- "column": "Country",
- "reason": ExtraFiltersReasonType.COL_NOT_IN_DATASOURCE,
- },
- ],
- }
- mock_path_viz_class.return_value = mock_path_viz_instance
-
- mock_viz_types.get.side_effect = lambda viz_type: {
- "deck_scatter": mock_scatter_viz_class,
- "deck_path": mock_path_viz_class,
- }.get(viz_type)
-
- test_viz = viz.DeckGLMultiLayer(datasource, {"deck_slices": [1, 2]})
- test_viz.get_df_payload = Mock(return_value={"df": pd.DataFrame()})
-
- result = test_viz.get_payload()
-
- assert result["applied_filters"] == [
- {"column": "Latitude"},
- {"column": "Longitude"},
- ]
- assert result["rejected_filters"] == [
- {
- "column": "Country",
- "reason": ExtraFiltersReasonType.COL_NOT_IN_DATASOURCE,
- },
- ]
-
- @with_config({"MAPBOX_API_KEY": "test_key"})
- def test_get_data_empty_deck_slices(self):
- """Test get_data method with empty deck_slices."""
- datasource = self.get_datasource_mock()
- form_data = {"deck_slices": []}
-
- test_viz = viz.DeckGLMultiLayer(datasource, form_data)
- result = test_viz.get_data(pd.DataFrame())
-
- assert isinstance(result, dict)
- assert result["features"] == {}
- assert result["slices"] == []
- assert result["mapboxApiKey"] == "test_key"
-
- def test_get_base_properties_no_metric(self):
- """Test _get_base_properties when metric_label is None"""
- form_data = {}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
- test_viz.metric_label = None
-
- data = {"spatial": [10.5, 20.3], "other_field": "value"}
-
- result = test_viz._get_base_properties(data)
-
- assert result["position"] == [10.5, 20.3]
- assert result["weight"] == 1
- assert len(result) == 2
-
- def test_setup_metric_label(self):
- """Test _setup_metric_label with metric"""
- form_data = {"size": "test_metric"}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
- test_viz.metric = Mock()
- test_viz.metric.value = "test_metric"
-
- with patch("superset.viz.utils.get_metric_name") as mock_get_name:
- mock_get_name.return_value = "test_metric"
- test_viz._setup_metric_label()
-
- assert test_viz.metric_label == "test_metric"
- mock_get_name.assert_called_once_with(test_viz.metric)
-
- def test_setup_metric_label_no_metric(self):
- """Test _setup_metric_label without metric"""
- form_data = {}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
- test_viz.metric = None
-
- test_viz._setup_metric_label()
-
- assert test_viz.metric_label is None
-
- def test_should_apply_layer_filtering_true(self):
- """Test _should_apply_layer_filtering returns True when conditions are met"""
- form_data = {
- "slice_id": 123,
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- "layerFilterScope": [0, 1],
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._should_apply_layer_filtering(form_data)
-
- assert result is True
-
- def test_should_apply_layer_filtering_false_missing_slice_id(self):
- """Test _should_apply_layer_filtering returns False when slice_id is missing"""
- form_data = {
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- "layerFilterScope": [0, 1],
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._should_apply_layer_filtering(form_data)
-
- assert result is False
-
- def test_should_apply_layer_filtering_false_missing_adhoc_filters(self):
- """Test _should_apply_layer_filtering returns False when
- adhoc_filters missing"""
- form_data = {"slice_id": 123}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._should_apply_layer_filtering(form_data)
-
- assert result is False
-
- def test_should_apply_layer_filtering_false_no_layer_scoped_filters(self):
- """Test _should_apply_layer_filtering returns False when no layer
- scoped filters"""
- form_data = {
- "slice_id": 123,
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._should_apply_layer_filtering(form_data)
-
- assert result is False
-
- def test_has_layer_scoped_filters_true_with_dict(self):
- """Test _has_layer_scoped_filters returns True when filter
- has layerFilterScope"""
- form_data = {
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- "layerFilterScope": [0, 1],
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._has_layer_scoped_filters(form_data)
-
- assert result is True
-
- def test_has_layer_scoped_filters_true_with_non_none_value(self):
- """Test _has_layer_scoped_filters returns True when layerFilterScope not None"""
- form_data = {
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- "layerFilterScope": [],
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._has_layer_scoped_filters(form_data)
-
- assert result is True
-
- def test_has_layer_scoped_filters_false_none_value(self):
- """Test _has_layer_scoped_filters returns False when layerFilterScope is None"""
- form_data = {
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- "layerFilterScope": None,
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._has_layer_scoped_filters(form_data)
-
- assert result is False
-
- def test_has_layer_scoped_filters_false_no_scoped_filters(self):
- """Test _has_layer_scoped_filters returns False when no filters have
- layerFilterScope"""
- form_data = {
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._has_layer_scoped_filters(form_data)
-
- assert result is False
-
- def test_apply_multilayer_filtering_filters_by_layer_scope(self):
- """Test _apply_multilayer_filtering filters adhoc_filters by layer scope"""
- form_data = {
- "slice_id": 123,
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- "layerFilterScope": [0, 1],
- "deck_slices": [123, 456],
- },
- {
- "clause": "WHERE",
- "subject": "col2",
- "operator": "!=",
- "comparator": "value2",
- "layerFilterScope": [1],
- "deck_slices": [123, 456],
- },
- {
- "clause": "WHERE",
- "subject": "col3",
- "operator": ">",
- "comparator": "value3",
- "layerFilterScope": [2],
- "deck_slices": [123, 456],
- },
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._apply_multilayer_filtering(form_data)
-
- assert len(result["adhoc_filters"]) == 1
- assert result["adhoc_filters"][0]["subject"] == "col1"
-
- def test_apply_multilayer_filtering_no_deck_slices(self):
- """Test _apply_multilayer_filtering when no deck_slices in filters"""
- form_data = {
- "slice_id": 123,
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- "layerFilterScope": [0],
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._apply_multilayer_filtering(form_data)
-
- assert len(result["adhoc_filters"]) == 1
- assert result["adhoc_filters"][0]["subject"] == "col1"
-
- def test_apply_multilayer_filtering_slice_not_in_deck_slices(self):
- """Test _apply_multilayer_filtering when slice_id not in deck_slices"""
- form_data = {
- "slice_id": 999,
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- "layerFilterScope": [0],
- "deck_slices": [123, 456],
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._apply_multilayer_filtering(form_data)
-
- # Should return original form_data unchanged when slice_id not in deck_slices
- assert result == form_data
-
- def test_get_deck_slices_from_filters_found(self):
- """Test _get_deck_slices_from_filters when deck_slices found"""
- form_data = {
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- "deck_slices": [123, 456],
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._get_deck_slices_from_filters(form_data)
-
- assert result == [123, 456]
-
- def test_get_deck_slices_from_filters_not_found(self):
- """Test _get_deck_slices_from_filters when no deck_slices found"""
- form_data = {
- "adhoc_filters": [
- {
- "clause": "WHERE",
- "subject": "col1",
- "operator": "==",
- "comparator": "value1",
- }
- ],
- }
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._get_deck_slices_from_filters(form_data)
-
- assert result is None
-
- def test_get_deck_slices_from_filters_empty_filters(self):
- """Test _get_deck_slices_from_filters with empty adhoc_filters"""
- form_data = {"adhoc_filters": []}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, form_data)
-
- result = test_viz._get_deck_slices_from_filters(form_data)
-
- assert result is None
-
- def test_get_filter_layer_scope_dict(self):
- """Test _get_filter_layer_scope with dict filter"""
- filter_item = {"layerFilterScope": [0, 1]}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- result = test_viz._get_filter_layer_scope(filter_item)
-
- assert result == [0, 1]
-
- def test_get_filter_layer_scope_dict_none(self):
- """Test _get_filter_layer_scope with dict filter having None layerFilterScope"""
- filter_item = {"layerFilterScope": None}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- result = test_viz._get_filter_layer_scope(filter_item)
-
- assert result is None
-
- def test_get_filter_layer_scope_dict_missing_key(self):
- """Test _get_filter_layer_scope with dict filter missing layerFilterScope key"""
- filter_item = {"other_key": "value"}
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- result = test_viz._get_filter_layer_scope(filter_item)
-
- assert result is None
-
- def test_get_filter_layer_scope_object_with_attribute(self):
- """Test _get_filter_layer_scope with object having layerFilterScope attribute"""
- filter_item = Mock()
- filter_item.layerFilterScope = [0, 1]
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- result = test_viz._get_filter_layer_scope(filter_item)
-
- assert result == [0, 1]
-
- def test_get_filter_layer_scope_object_without_attribute(self):
- """Test _get_filter_layer_scope with object missing
- layerFilterScope attribute"""
- filter_item = Mock()
- del filter_item.layerFilterScope
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- result = test_viz._get_filter_layer_scope(filter_item)
-
- assert result is None
-
- def test_get_filter_layer_scope_non_dict_non_object(self):
- """Test _get_filter_layer_scope with non-dict, non-object filter"""
- filter_item = "string_filter"
- datasource = self.get_datasource_mock()
- test_viz = viz.BaseDeckGLViz(datasource, {})
-
- result = test_viz._get_filter_layer_scope(filter_item)
-
- assert result is None
-
-
-class TestTimeSeriesViz(SupersetTestCase):
- def test_timeseries_unicode_data(self):
- datasource = self.get_datasource_mock()
- form_data = {"groupby": ["name"], "metrics": ["sum__payout"]}
- raw = {}
- raw["name"] = [
- "Real Madrid C.F.πΊπΈπ¬π§",
- "Real Madrid C.F.πΊπΈπ¬π§",
- "Real Madrid Basket",
- "Real Madrid Basket",
- ]
- raw["__timestamp"] = [
- "2018-02-20T00:00:00",
- "2018-03-09T00:00:00",
- "2018-02-20T00:00:00",
- "2018-03-09T00:00:00",
- ]
- raw["sum__payout"] = [2, 2, 4, 4]
- df = pd.DataFrame(raw)
-
- test_viz = viz.NVD3TimeSeriesViz(datasource, form_data)
- viz_data = {}
- viz_data = test_viz.get_data(df)
- expected = [
- {
- "values": [
- {"y": 4, "x": "2018-02-20T00:00:00"},
- {"y": 4, "x": "2018-03-09T00:00:00"},
- ],
- "key": ("Real Madrid Basket",),
- },
- {
- "values": [
- {"y": 2, "x": "2018-02-20T00:00:00"},
- {"y": 2, "x": "2018-03-09T00:00:00"},
- ],
- "key": ("Real Madrid C.F.\U0001f1fa\U0001f1f8\U0001f1ec\U0001f1e7",),
- },
- ]
- assert expected == viz_data
-
- def test_process_data_resample(self):
- datasource = self.get_datasource_mock()
-
- df = pd.DataFrame(
- {
- "__timestamp": pd.to_datetime(
- ["2019-01-01", "2019-01-02", "2019-01-05", "2019-01-07"]
- ),
- "y": [1.0, 2.0, 5.0, 7.0],
- }
- )
-
- assert viz.NVD3TimeSeriesViz(
- datasource,
- {"metrics": ["y"], "resample_method": "sum", "resample_rule": "1D"},
- ).process_data(df)["y"].tolist() == [1.0, 2.0, 0.0, 0.0, 5.0, 0.0, 7.0]
-
- np.testing.assert_equal(
- viz.NVD3TimeSeriesViz(
- datasource,
- {"metrics": ["y"], "resample_method": "asfreq", "resample_rule": "1D"},
- )
- .process_data(df)["y"]
- .tolist(),
- [1.0, 2.0, np.nan, np.nan, 5.0, np.nan, 7.0],
- )
-
- def test_apply_rolling(self):
- datasource = self.get_datasource_mock()
- df = pd.DataFrame(
- index=pd.to_datetime(
- ["2019-01-01", "2019-01-02", "2019-01-05", "2019-01-07"]
- ),
- data={"y": [1.0, 2.0, 3.0, 4.0]},
- )
- assert viz.NVD3TimeSeriesViz(
- datasource,
- {
- "metrics": ["y"],
- "rolling_type": "cumsum",
- "rolling_periods": 0,
- "min_periods": 0,
- },
- ).apply_rolling(df)["y"].tolist() == [1.0, 3.0, 6.0, 10.0]
- assert viz.NVD3TimeSeriesViz(
- datasource,
- {
- "metrics": ["y"],
- "rolling_type": "sum",
- "rolling_periods": 2,
- "min_periods": 0,
- },
- ).apply_rolling(df)["y"].tolist() == [1.0, 3.0, 5.0, 7.0]
- assert viz.NVD3TimeSeriesViz(
- datasource,
- {
- "metrics": ["y"],
- "rolling_type": "mean",
- "rolling_periods": 10,
- "min_periods": 0,
- },
- ).apply_rolling(df)["y"].tolist() == [1.0, 1.5, 2.0, 2.5]
-
- def test_apply_rolling_without_data(self):
- datasource = self.get_datasource_mock()
- df = pd.DataFrame(
- index=pd.to_datetime(
- ["2019-01-01", "2019-01-02", "2019-01-05", "2019-01-07"]
- ),
- data={"y": [1.0, 2.0, 3.0, 4.0]},
- )
- test_viz = viz.NVD3TimeSeriesViz(
- datasource,
- {
- "metrics": ["y"],
- "rolling_type": "cumsum",
- "rolling_periods": 4,
- "min_periods": 4,
- },
- )
- with pytest.raises(QueryObjectValidationError):
- test_viz.apply_rolling(df)
diff --git a/tests/unit_tests/async_events/async_query_manager_tests.py b/tests/unit_tests/async_events/async_query_manager_tests.py
index 534d402e48a..bd1998e5f4b 100644
--- a/tests/unit_tests/async_events/async_query_manager_tests.py
+++ b/tests/unit_tests/async_events/async_query_manager_tests.py
@@ -322,54 +322,3 @@ def test_validate_session_guest_user_creates_valid_token(async_query_manager):
mock_request.cookies = {JWT_TOKEN_COOKIE_NAME: token}
channel = async_query_manager.parse_channel_id_from_request(mock_request)
assert channel # valid UUID string
-
-
-@mark.parametrize(
- "cache_type, cache_backend",
- [
- ("RedisCacheBackend", mock.Mock(spec=RedisCacheBackend)),
- ("RedisSentinelCacheBackend", mock.Mock(spec=RedisSentinelCacheBackend)),
- ],
-)
-@mock.patch("superset.is_feature_enabled")
-def test_submit_explore_json_job_as_guest_user(
- is_feature_enabled_mock, async_query_manager, cache_type, cache_backend
-):
- is_feature_enabled_mock.return_value = True
- set_current_as_guest_user()
-
- # Mock the get_cache_backend method to return the current cache backend
- async_query_manager.get_cache_backend = mock.Mock(return_value=cache_backend)
-
- job_mock = Mock()
- async_query_manager._load_explore_json_into_cache_job = job_mock
- job_meta = async_query_manager.submit_explore_json_job(
- channel_id="test_channel_id",
- form_data={},
- response_type="json",
- )
-
- job_mock.delay.assert_called_once_with(
- {
- "channel_id": "test_channel_id",
- "errors": [],
- "guest_token": {
- "user": {},
- "resources": [{"type": "dashboard", "id": "some-uuid"}],
- "rls_rules": [{"clause": '"STATEID" = 3'}],
- "iat": 1700000000.0,
- "exp": 1700000300.0,
- "aud": "http://0.0.0.0:8080/",
- "type": "guest",
- },
- "job_id": ANY,
- "result_url": None,
- "status": "pending",
- "user_id": None,
- },
- {},
- "json",
- False,
- )
-
- assert "guest_token" not in job_meta
diff --git a/tests/unit_tests/commands/chart/warm_up_cache_test.py b/tests/unit_tests/commands/chart/warm_up_cache_test.py
index f178ab85e75..5f97e9b3fa2 100644
--- a/tests/unit_tests/commands/chart/warm_up_cache_test.py
+++ b/tests/unit_tests/commands/chart/warm_up_cache_test.py
@@ -57,33 +57,29 @@ def test_applies_dashboard_filters_to_non_legacy_chart(
# Mock dependencies
with patch.object(chart, "get_query_context", return_value=mock_qc):
- with patch(
- "superset.commands.chart.warm_up_cache.get_form_data",
- return_value=[{"viz_type": "echarts_timeseries_bar"}],
- ):
- mock_chart_data_command.return_value.run.return_value = {
- "queries": [{"error": None, "status": "success"}]
- }
+ mock_chart_data_command.return_value.run.return_value = {
+ "queries": [{"error": None, "status": "success"}]
+ }
- # Execute with dashboard_id
- result = ChartWarmUpCacheCommand(chart, 42, None).run()
+ # Execute with dashboard_id
+ result = ChartWarmUpCacheCommand(chart, 42, None).run()
- # VALIDATE: Filters were added to query.filter
- assert len(mock_query.filter) == 1, "Filter should be added to query"
- assert mock_query.filter[0] == {
- "col": "country",
- "op": "in",
- "val": ["USA", "France"],
- }, "Filter content should match dashboard filter"
+ # VALIDATE: Filters were added to query.filter
+ assert len(mock_query.filter) == 1, "Filter should be added to query"
+ assert mock_query.filter[0] == {
+ "col": "country",
+ "op": "in",
+ "val": ["USA", "France"],
+ }, "Filter content should match dashboard filter"
- # VALIDATE: get_dashboard_extra_filters was called correctly
- mock_get_dashboard_filters.assert_called_once_with(123, 42)
+ # VALIDATE: get_dashboard_extra_filters was called correctly
+ mock_get_dashboard_filters.assert_called_once_with(123, 42)
- # VALIDATE: force flag was set
- assert mock_qc.force is True, "force should be set to True"
+ # VALIDATE: force flag was set
+ assert mock_qc.force is True, "force should be set to True"
- # VALIDATE: Result is correct
- assert result["chart_id"] == 123
+ # VALIDATE: Result is correct
+ assert result["chart_id"] == 123
@patch("superset.commands.chart.warm_up_cache.ChartDataCommand")
@@ -104,22 +100,18 @@ def test_no_filters_applied_without_dashboard_id(mock_chart_data_command):
mock_qc.queries = [mock_query]
with patch.object(chart, "get_query_context", return_value=mock_qc):
- with patch(
- "superset.commands.chart.warm_up_cache.get_form_data",
- return_value=[{"viz_type": "big_number"}],
- ):
- mock_chart_data_command.return_value.run.return_value = {
- "queries": [{"error": None, "status": "success"}]
- }
+ mock_chart_data_command.return_value.run.return_value = {
+ "queries": [{"error": None, "status": "success"}]
+ }
- # Execute WITHOUT dashboard_id
- ChartWarmUpCacheCommand(chart, None, None).run()
+ # Execute WITHOUT dashboard_id
+ ChartWarmUpCacheCommand(chart, None, None).run()
- # VALIDATE: Filter list unchanged (no dashboard filters added)
- assert len(mock_query.filter) == 1, "Filter count should remain the same"
- assert mock_query.filter == [
- {"col": "existing", "op": "==", "val": "filter"}
- ], "Existing filters should be unchanged"
+ # VALIDATE: Filter list unchanged (no dashboard filters added)
+ assert len(mock_query.filter) == 1, "Filter count should remain the same"
+ assert mock_query.filter == [
+ {"col": "existing", "op": "==", "val": "filter"}
+ ], "Existing filters should be unchanged"
@patch("superset.commands.chart.warm_up_cache.get_dashboard_extra_filters")
@@ -142,24 +134,20 @@ def test_extra_filters_parameter_takes_precedence(
mock_qc.queries = [mock_query]
with patch.object(chart, "get_query_context", return_value=mock_qc):
- with patch(
- "superset.commands.chart.warm_up_cache.get_form_data",
- return_value=[{"viz_type": "pie"}],
- ):
- mock_chart_data_command.return_value.run.return_value = {
- "queries": [{"error": None, "status": "success"}]
- }
+ mock_chart_data_command.return_value.run.return_value = {
+ "queries": [{"error": None, "status": "success"}]
+ }
- # Execute with extra_filters parameter
- extra_filters_json = '[{"col": "state", "op": "==", "val": "CA"}]'
- ChartWarmUpCacheCommand(chart, 42, extra_filters_json).run()
+ # Execute with extra_filters parameter
+ extra_filters_json = '[{"col": "state", "op": "==", "val": "CA"}]'
+ ChartWarmUpCacheCommand(chart, 42, extra_filters_json).run()
- # VALIDATE: get_dashboard_extra_filters should NOT be called
- mock_get_dashboard_filters.assert_not_called()
+ # VALIDATE: get_dashboard_extra_filters should NOT be called
+ mock_get_dashboard_filters.assert_not_called()
- # VALIDATE: extra_filters were parsed and applied
- assert len(mock_query.filter) == 1
- assert mock_query.filter[0] == {"col": "state", "op": "==", "val": "CA"}
+ # VALIDATE: extra_filters were parsed and applied
+ assert len(mock_query.filter) == 1
+ assert mock_query.filter[0] == {"col": "state", "op": "==", "val": "CA"}
@patch("superset.commands.chart.warm_up_cache.get_dashboard_extra_filters")
@@ -189,24 +177,20 @@ def test_handles_multiple_queries_in_query_context(
mock_qc.queries = [mock_query1, mock_query2]
with patch.object(chart, "get_query_context", return_value=mock_qc):
- with patch(
- "superset.commands.chart.warm_up_cache.get_form_data",
- return_value=[{"viz_type": "heatmap_v2"}],
- ):
- mock_chart_data_command.return_value.run.return_value = {
- "queries": [
- {"error": None, "status": "success"},
- {"error": None, "status": "success"},
- ]
- }
-
- ChartWarmUpCacheCommand(chart, 42, None).run()
-
- # VALIDATE: Filters added to BOTH queries
- assert len(mock_query1.filter) == 1, "Filter should be added to query 1"
- assert len(mock_query2.filter) == 1, "Filter should be added to query 2"
- assert mock_query1.filter[0]["col"] == "country"
- assert mock_query2.filter[0]["col"] == "country"
+ mock_chart_data_command.return_value.run.return_value = {
+ "queries": [
+ {"error": None, "status": "success"},
+ {"error": None, "status": "success"},
+ ]
+ }
+
+ ChartWarmUpCacheCommand(chart, 42, None).run()
+
+ # VALIDATE: Filters added to BOTH queries
+ assert len(mock_query1.filter) == 1, "Filter should be added to query 1"
+ assert len(mock_query2.filter) == 1, "Filter should be added to query 2"
+ assert mock_query1.filter[0]["col"] == "country"
+ assert mock_query2.filter[0]["col"] == "country"
@patch("superset.commands.chart.warm_up_cache.get_dashboard_extra_filters")
@@ -232,23 +216,19 @@ def test_handles_empty_dashboard_filters(
mock_qc.queries = [mock_query]
with patch.object(chart, "get_query_context", return_value=mock_qc):
- with patch(
- "superset.commands.chart.warm_up_cache.get_form_data",
- return_value=[{"viz_type": "echarts_area"}],
- ):
- mock_chart_data_command.return_value.run.return_value = {
- "queries": [{"error": None, "status": "success"}]
- }
+ mock_chart_data_command.return_value.run.return_value = {
+ "queries": [{"error": None, "status": "success"}]
+ }
- ChartWarmUpCacheCommand(chart, 42, None).run()
+ ChartWarmUpCacheCommand(chart, 42, None).run()
- # VALIDATE: No filters added (empty list case)
- assert len(mock_query.filter) == 0, (
- "No filters should be added when dashboard has no filters"
- )
- assert mock_get_dashboard_filters.called, (
- "Should still call get_dashboard_extra_filters"
- )
+ # VALIDATE: No filters added (empty list case)
+ assert len(mock_query.filter) == 0, (
+ "No filters should be added when dashboard has no filters"
+ )
+ assert mock_get_dashboard_filters.called, (
+ "Should still call get_dashboard_extra_filters"
+ )
@patch("superset.commands.chart.warm_up_cache.ChartDataCommand")
@@ -271,22 +251,18 @@ def test_invalid_json_in_extra_filters_raises_error(mock_chart_data_command):
mock_qc.queries = [mock_query]
with patch.object(chart, "get_query_context", return_value=mock_qc):
- with patch(
- "superset.commands.chart.warm_up_cache.get_form_data",
- return_value=[{"viz_type": "pie"}],
- ):
- result = ChartWarmUpCacheCommand(chart, 42, invalid_json).run()
-
- assert result["viz_error"] is not None, "Should return an error"
- assert result["chart_id"] == 128
- # JSONDecodeError messages vary across Python versions
- error_str = str(result["viz_error"]).lower()
- assert (
- "json" in error_str
- or "decode" in error_str
- or "expecting" in error_str
- or "delimiter" in error_str
- ), f"Error should be a JSON decode issue: {result['viz_error']}"
+ result = ChartWarmUpCacheCommand(chart, 42, invalid_json).run()
+
+ assert result["viz_error"] is not None, "Should return an error"
+ assert result["chart_id"] == 128
+ # JSONDecodeError messages vary across Python versions
+ error_str = str(result["viz_error"]).lower()
+ assert (
+ "json" in error_str
+ or "decode" in error_str
+ or "expecting" in error_str
+ or "delimiter" in error_str
+ ), f"Error should be a JSON decode issue: {result['viz_error']}"
@patch("superset.commands.chart.warm_up_cache.ChartDataCommand")
@@ -302,135 +278,17 @@ def test_none_query_context_raises_chart_invalid_error(mock_chart_data_command):
# Mock get_query_context to return None (chart has no query_context)
with patch.object(chart, "get_query_context", return_value=None):
- with patch(
- "superset.commands.chart.warm_up_cache.get_form_data",
- return_value=[{"viz_type": "echarts_timeseries"}],
- ):
- result = ChartWarmUpCacheCommand(chart, None, None).run()
-
- assert result["viz_error"] is not None, "Should return an error"
- assert result["chart_id"] == 129
- error_str = str(result["viz_error"]).lower()
- assert "query context" in error_str, (
- f"Error should mention query context: {result['viz_error']}"
- )
- assert "not exist" in error_str, (
- f"Error should mention not exist: {result['viz_error']}"
- )
-
-
-@patch("superset.commands.chart.warm_up_cache.viz_types", ["table"])
-def test_legacy_chart_without_datasource_raises_error():
- """Verify that legacy chart without datasource raises ChartInvalidError"""
- chart = Slice(
- id=130,
- slice_name="Legacy Chart",
- viz_type="table",
- datasource_id=None,
- datasource_type=None,
- )
-
- with patch.object(
- type(chart), "datasource", new_callable=lambda: property(lambda self: None)
- ):
- with patch(
- "superset.commands.chart.warm_up_cache.get_form_data",
- return_value=[{"viz_type": "table"}],
- ):
- result = ChartWarmUpCacheCommand(chart, None, None).run()
-
- assert result["viz_error"] is not None, "Should return an error"
- assert result["chart_id"] == 130
- error_str = str(result["viz_error"]).lower()
- assert "datasource" in error_str, (
- f"Error should mention datasource: {result['viz_error']}"
- )
- assert "not exist" in error_str, (
- f"Error should mention not exist: {result['viz_error']}"
- )
-
-
-@patch("superset.commands.chart.warm_up_cache.get_dashboard_extra_filters")
-@patch("superset.commands.chart.warm_up_cache.get_viz")
-@patch("superset.commands.chart.warm_up_cache.viz_types", ["table"])
-@patch("superset.commands.chart.warm_up_cache.g")
-def test_legacy_chart_warm_up_with_dashboard(
- mock_g, mock_get_viz, mock_get_dashboard_filters
-):
- """Test successful legacy chart warm-up with dashboard filters"""
- mock_get_dashboard_filters.return_value = [
- {"col": "country", "op": "==", "val": "USA"}
- ]
-
- chart = Slice(
- id=131,
- slice_name="Legacy Table",
- viz_type="table",
- datasource_id=1,
- datasource_type="table",
- )
-
- mock_datasource = Mock()
- mock_datasource.type = "table"
- mock_datasource.id = 1
-
- mock_viz = Mock()
- mock_viz.get_payload.return_value = {"errors": None, "status": "success"}
- mock_get_viz.return_value = mock_viz
-
- with patch.object(
- type(chart),
- "datasource",
- new_callable=lambda: property(lambda self: mock_datasource),
- ):
- with patch(
- "superset.commands.chart.warm_up_cache.get_form_data",
- return_value=[{"viz_type": "table"}],
- ):
- result = ChartWarmUpCacheCommand(chart, 42, None).run()
-
- assert result["chart_id"] == 131
- assert result["viz_error"] is None
- assert result["viz_status"] == "success"
- assert hasattr(mock_g, "form_data") is False
- mock_get_dashboard_filters.assert_called_once_with(131, 42)
-
-
-@patch("superset.commands.chart.warm_up_cache.get_viz")
-@patch("superset.commands.chart.warm_up_cache.viz_types", ["table"])
-@patch("superset.commands.chart.warm_up_cache.g")
-def test_legacy_chart_warm_up_without_dashboard(mock_g, mock_get_viz):
- """Test successful legacy chart warm-up without dashboard"""
- chart = Slice(
- id=134,
- slice_name="Legacy Table",
- viz_type="table",
- datasource_id=1,
- datasource_type="table",
- )
-
- mock_datasource = Mock()
- mock_datasource.type = "table"
- mock_datasource.id = 1
-
- mock_viz = Mock()
- mock_viz.get_payload.return_value = {"errors": None, "status": "success"}
- mock_get_viz.return_value = mock_viz
-
- with patch.object(
- type(chart),
- "datasource",
- new_callable=lambda: property(lambda self: mock_datasource),
- ):
- with patch(
- "superset.commands.chart.warm_up_cache.get_form_data",
- return_value=[{"viz_type": "table"}],
- ):
- result = ChartWarmUpCacheCommand(chart, None, None).run()
+ result = ChartWarmUpCacheCommand(chart, None, None).run()
- assert result["chart_id"] == 134
- assert result["viz_error"] is None
- assert result["viz_status"] == "success"
+ assert result["viz_error"] is not None, "Should return an error"
+ assert result["chart_id"] == 129
+ error_str = str(result["viz_error"]).lower()
+ assert "query context" in error_str, (
+ f"Error should mention query context: {result['viz_error']}"
+ )
+ assert "not exist" in error_str, (
+ f"Error should mention not exist: {result['viz_error']}"
+ )
@patch("superset.commands.chart.warm_up_cache.ChartDataCommand")
@@ -450,22 +308,18 @@ def test_non_legacy_chart_returns_first_error(mock_chart_data_command):
mock_qc.queries = [mock_query]
with patch.object(chart, "get_query_context", return_value=mock_qc):
- with patch(
- "superset.commands.chart.warm_up_cache.get_form_data",
- return_value=[{"viz_type": "echarts_timeseries"}],
- ):
- mock_chart_data_command.return_value.run.return_value = {
- "queries": [
- {"error": "Database connection failed", "status": "failed"},
- {"error": None, "status": "success"},
- ]
- }
-
- result = ChartWarmUpCacheCommand(chart, None, None).run()
-
- assert result["chart_id"] == 132
- assert result["viz_error"] == "Database connection failed"
- assert result["viz_status"] == "failed"
+ mock_chart_data_command.return_value.run.return_value = {
+ "queries": [
+ {"error": "Database connection failed", "status": "failed"},
+ {"error": None, "status": "success"},
+ ]
+ }
+
+ result = ChartWarmUpCacheCommand(chart, None, None).run()
+
+ assert result["chart_id"] == 132
+ assert result["viz_error"] == "Database connection failed"
+ assert result["viz_status"] == "failed"
@patch("superset.commands.chart.warm_up_cache.db")
diff --git a/tests/unit_tests/middleware/test_legacy_prefix_redirect.py b/tests/unit_tests/middleware/test_legacy_prefix_redirect.py
index dfb12933fce..f00e9aedbcf 100644
--- a/tests/unit_tests/middleware/test_legacy_prefix_redirect.py
+++ b/tests/unit_tests/middleware/test_legacy_prefix_redirect.py
@@ -84,9 +84,6 @@ _GET_REDIRECT_ROWS: list[tuple[str, str]] = [
("/superset/explore/", "/explore/"),
("/superset/explore/table/5/", "/explore/table/5/"),
("/superset/explore/p/key123/", "/explore/p/key123/"),
- ("/superset/explore_json/", "/explore_json/"),
- ("/superset/explore_json/table/5/", "/explore_json/table/5/"),
- ("/superset/explore_json/data/cache_abc/", "/explore_json/data/cache_abc/"),
("/superset/tags/", "/tags/"),
("/superset/all_entities/", "/all_entities/"),
]
@@ -95,8 +92,6 @@ _GET_REDIRECT_ROWS: list[tuple[str, str]] = [
_POST_BODY_PRESERVED_ROWS: list[tuple[str, str]] = [
("/superset/explore/", "/explore/"),
("/superset/explore/table/5/", "/explore/table/5/"),
- ("/superset/explore_json/", "/explore_json/"),
- ("/superset/explore_json/table/5/", "/explore_json/table/5/"),
("/superset/log/", "/log/"),
]
@@ -112,7 +107,6 @@ _POST_410_ROWS: list[str] = [
"/superset/file-handler",
"/superset/sqllab/history/",
"/superset/explore/p/key123/",
- "/superset/explore_json/data/cache_abc/",
"/superset/tags/",
"/superset/all_entities/",
]
@@ -513,8 +507,6 @@ _EXPECTED_KEYSET: frozenset[str] = frozenset(
"/file-handler",
"/log/",
"/sqllab/history/",
- "/explore_json/",
- "/explore_json/data/",
"/explore/",
"/explore/p/",
"/tags/",
diff --git a/tests/unit_tests/tasks/test_async_queries.py b/tests/unit_tests/tasks/test_async_queries.py
index d2e73466e07..77ad6b6fa7f 100644
--- a/tests/unit_tests/tasks/test_async_queries.py
+++ b/tests/unit_tests/tasks/test_async_queries.py
@@ -22,10 +22,8 @@ from flask_babel import lazy_gettext as _
from superset.commands.chart.exceptions import ChartDataQueryFailedError
from superset.errors import ErrorLevel, SupersetError, SupersetErrorType
from superset.exceptions import (
- OAuth2RedirectError,
SupersetErrorException,
SupersetErrorsException,
- SupersetVizException,
)
@@ -154,170 +152,3 @@ def test_load_chart_data_into_cache_with_superset_errors_exception(
assert errors[1]["message"] == "Table not found"
assert errors[1]["error_type"] == SupersetErrorType.TABLE_DOES_NOT_EXIST_ERROR
assert errors[1]["level"] == ErrorLevel.WARNING
-
-
-@mock.patch("superset.tasks.async_queries.security_manager")
-@mock.patch("superset.tasks.async_queries.async_query_manager")
-@mock.patch("superset.tasks.async_queries.get_viz")
-@mock.patch("superset.tasks.async_queries.get_datasource_info")
-def test_load_explore_json_into_cache_preserves_oauth2_redirect_error(
- mock_get_datasource_info,
- mock_get_viz,
- mock_async_query_manager,
- mock_security_manager,
-):
- """
- OAuth2RedirectError raised by ``viz_obj.get_payload`` must reach the async
- job's errors list as a structured SIP-40 envelope so the frontend can
- render the OAuth2 banner identically to the sync legacy path.
- """
- from superset.tasks.async_queries import load_explore_json_into_cache
-
- job_metadata = {"user_id": 1}
- form_data: dict = {}
-
- mock_get_datasource_info.return_value = (1, "table")
- mock_security_manager.get_user_by_id.return_value = mock.MagicMock()
- mock_async_query_manager.STATUS_ERROR = "error"
-
- viz_obj = mock.MagicMock()
- viz_obj.get_payload.side_effect = OAuth2RedirectError(
- url="https://accounts.example.com/o/oauth2/v2/auth?...",
- tab_id="tab-123",
- redirect_uri="https://superset.example.com/oauth2/redirect",
- )
- mock_get_viz.return_value = viz_obj
-
- with pytest.raises(OAuth2RedirectError):
- load_explore_json_into_cache(job_metadata, form_data)
-
- call_args = mock_async_query_manager.update_job.call_args
- assert call_args[0] == (job_metadata, "error")
- errors = call_args[1]["errors"]
- assert len(errors) == 1
- assert errors[0]["error_type"] == SupersetErrorType.OAUTH2_REDIRECT
- assert errors[0]["extra"] == {
- "url": "https://accounts.example.com/o/oauth2/v2/auth?...",
- "tab_id": "tab-123",
- "redirect_uri": "https://superset.example.com/oauth2/redirect",
- }
-
-
-@mock.patch("superset.tasks.async_queries.security_manager")
-@mock.patch("superset.tasks.async_queries.async_query_manager")
-@mock.patch("superset.tasks.async_queries.get_viz")
-@mock.patch("superset.tasks.async_queries.get_datasource_info")
-def test_load_explore_json_into_cache_preserves_superset_errors_exception(
- mock_get_datasource_info,
- mock_get_viz,
- mock_async_query_manager,
- mock_security_manager,
-):
- """SupersetErrorsException must be preserved as a list of SIP-40 dicts."""
- from superset.tasks.async_queries import load_explore_json_into_cache
-
- job_metadata = {"user_id": 1}
- form_data: dict = {}
-
- mock_get_datasource_info.return_value = (1, "table")
- mock_security_manager.get_user_by_id.return_value = mock.MagicMock()
- mock_async_query_manager.STATUS_ERROR = "error"
-
- viz_obj = mock.MagicMock()
- viz_obj.get_payload.side_effect = SupersetErrorsException(
- [
- SupersetError(
- message="Column not found",
- error_type=SupersetErrorType.COLUMN_DOES_NOT_EXIST_ERROR,
- level=ErrorLevel.ERROR,
- ),
- SupersetError(
- message="Table not found",
- error_type=SupersetErrorType.TABLE_DOES_NOT_EXIST_ERROR,
- level=ErrorLevel.WARNING,
- ),
- ]
- )
- mock_get_viz.return_value = viz_obj
-
- with pytest.raises(SupersetErrorsException):
- load_explore_json_into_cache(job_metadata, form_data)
-
- errors = mock_async_query_manager.update_job.call_args[1]["errors"]
- assert len(errors) == 2
- assert errors[0]["error_type"] == SupersetErrorType.COLUMN_DOES_NOT_EXIST_ERROR
- assert errors[1]["error_type"] == SupersetErrorType.TABLE_DOES_NOT_EXIST_ERROR
-
-
-@mock.patch("superset.tasks.async_queries.security_manager")
-@mock.patch("superset.tasks.async_queries.async_query_manager")
-@mock.patch("superset.tasks.async_queries.get_viz")
-@mock.patch("superset.tasks.async_queries.get_datasource_info")
-def test_load_explore_json_into_cache_preserves_superset_viz_exception(
- mock_get_datasource_info,
- mock_get_viz,
- mock_async_query_manager,
- mock_security_manager,
-):
- """
- Test that SupersetVizException passes ``ex.errors`` straight through.
- """
- from superset.tasks.async_queries import load_explore_json_into_cache
-
- job_metadata = {"user_id": 1}
- form_data: dict = {}
-
- mock_get_datasource_info.return_value = (1, "table")
- mock_security_manager.get_user_by_id.return_value = mock.MagicMock()
- mock_async_query_manager.STATUS_ERROR = "error"
-
- payload_errors = [
- {
- "message": "Bad column",
- "error_type": SupersetErrorType.VIZ_GET_DF_ERROR,
- "level": ErrorLevel.ERROR,
- }
- ]
- viz_obj = mock.MagicMock()
- viz_obj.get_payload.return_value = {"errors": payload_errors}
- viz_obj.has_error.return_value = True
- mock_get_viz.return_value = viz_obj
-
- with pytest.raises(SupersetVizException):
- load_explore_json_into_cache(job_metadata, form_data)
-
- errors = mock_async_query_manager.update_job.call_args[1]["errors"]
- assert errors == payload_errors
-
-
-@mock.patch("superset.tasks.async_queries.security_manager")
-@mock.patch("superset.tasks.async_queries.async_query_manager")
-@mock.patch("superset.tasks.async_queries.get_viz")
-@mock.patch("superset.tasks.async_queries.get_datasource_info")
-def test_load_explore_json_into_cache_falls_back_to_string_for_generic_exception(
- mock_get_datasource_info,
- mock_get_viz,
- mock_async_query_manager,
- mock_security_manager,
-):
- """
- Test that Non-Superset exception are passed as plain-string error.
- """
- from superset.tasks.async_queries import load_explore_json_into_cache
-
- job_metadata = {"user_id": 1}
- form_data: dict = {}
-
- mock_get_datasource_info.return_value = (1, "table")
- mock_security_manager.get_user_by_id.return_value = mock.MagicMock()
- mock_async_query_manager.STATUS_ERROR = "error"
-
- viz_obj = mock.MagicMock()
- viz_obj.get_payload.side_effect = RuntimeError("boom")
- mock_get_viz.return_value = viz_obj
-
- with pytest.raises(RuntimeError):
- load_explore_json_into_cache(job_metadata, form_data)
-
- errors = mock_async_query_manager.update_job.call_args[1]["errors"]
- assert errors == ["boom"]
diff --git a/tests/unit_tests/test_subdirectory_url_for.py b/tests/unit_tests/test_subdirectory_url_for.py
index 45fecb0a5b8..e09042a6451 100644
--- a/tests/unit_tests/test_subdirectory_url_for.py
+++ b/tests/unit_tests/test_subdirectory_url_for.py
@@ -168,19 +168,6 @@ def test_dashboard_model_url_has_no_route_prefix() -> None:
assert Dashboard.get_url(11, "births") == "/dashboard/births/"
-def test_slice_explore_json_url_has_no_route_prefix(app_context: None) -> None:
- """`Slice.explore_json_url` previously baked `/superset/explore_json` into
- the path. After `Superset.route_base = ""` the rule is `/explore_json/`,
- so the literal pointed at a non-existent route. Pin the prefix-free shape
- so downstream `ensureAppRoot` callers prepend the application root once.
- """
- from superset.models.slice import Slice
-
- slc = Slice(id=42)
- assert slc.explore_json_url.startswith("/explore_json/")
- assert "/superset/explore_json" not in slc.explore_json_url
-
-
def test_database_sql_url_resolves_to_live_sqllab_route() -> None:
"""`Database.sql_url` previously returned `/superset/sql/<id>/` β a route
that was removed when SQL Lab moved to its own blueprint at `/sqllab/`.
diff --git a/tests/unit_tests/test_viz_cache_key.py b/tests/unit_tests/test_viz_cache_key.py
deleted file mode 100644
index d6eb614265c..00000000000
--- a/tests/unit_tests/test_viz_cache_key.py
+++ /dev/null
@@ -1,111 +0,0 @@
-# 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.
-"""
-Behavioral tests for ``viz.BaseViz.cache_key`` covering per-user cache-key
-inclusion.
-"""
-
-from typing import Any
-from unittest.mock import patch
-
-from flask_appbuilder.security.sqla.models import User
-
-from superset import viz
-from superset.connectors.sqla.models import SqlaTable
-from superset.models.core import Database
-from superset.utils.core import override_user
-
-QUERY_OBJ: dict[str, Any] = {"row_limit": 100, "from_dttm": None, "to_dttm": None}
-
-
-def _viz_for(database: Database) -> viz.BaseViz:
- datasource = SqlaTable(
- table_name="t",
- columns=[],
- metrics=[],
- main_dttm_col=None,
- database=database,
- )
- return viz.BaseViz(datasource=datasource, form_data={"viz_type": "table"})
-
-
-def test_no_per_user_opt_in_keys_match_across_users():
- """
- Without any per-user caching opt-in, two different users on the same
- database/query must produce the *same* cache key (regression guard β we
- must not accidentally make every cache key per-user).
- """
- database = Database(database_name="d", sqlalchemy_uri="sqlite://")
- obj = _viz_for(database)
-
- with override_user(User(username="alice")):
- key_a = obj.cache_key(QUERY_OBJ)
- with override_user(User(username="bob")):
- key_b = obj.cache_key(QUERY_OBJ)
-
- assert key_a == key_b
-
-
-def test_per_user_caching_in_extra_yields_distinct_keys_per_user():
- """
- With ``per_user_caching: true`` set on the database, two different users
- must produce *different* cache keys for the same query.
- """
- database = Database(
- database_name="d",
- sqlalchemy_uri="sqlite://",
- extra='{"per_user_caching": true}',
- )
- obj = _viz_for(database)
-
- with override_user(User(username="alice")):
- key_a = obj.cache_key(QUERY_OBJ)
- with override_user(User(username="bob")):
- key_b = obj.cache_key(QUERY_OBJ)
-
- assert key_a != key_b
-
-
-def test_same_user_same_query_idempotent():
- database = Database(
- database_name="d",
- sqlalchemy_uri="sqlite://",
- extra='{"per_user_caching": true}',
- )
- obj = _viz_for(database)
-
- with override_user(User(username="alice")):
- assert obj.cache_key(QUERY_OBJ) == obj.cache_key(QUERY_OBJ)
-
-
-@patch("superset.utils.cache_keys.feature_flag_manager")
-def test_cache_query_by_user_flag_yields_distinct_keys(feature_flag_mock):
- """
- Global ``CACHE_QUERY_BY_USER`` flag also reaches the legacy viz path.
- """
- feature_flag_mock.is_feature_enabled.side_effect = (
- lambda feature=None: feature == "CACHE_QUERY_BY_USER"
- )
- database = Database(database_name="d", sqlalchemy_uri="sqlite://")
- obj = _viz_for(database)
-
- with override_user(User(username="alice")):
- key_a = obj.cache_key(QUERY_OBJ)
- with override_user(User(username="bob")):
- key_b = obj.cache_key(QUERY_OBJ)
-
- assert key_a != key_b
diff --git a/tests/unit_tests/test_viz_get_df_payload.py b/tests/unit_tests/test_viz_get_df_payload.py
deleted file mode 100644
index 96ae6c5e0d8..00000000000
--- a/tests/unit_tests/test_viz_get_df_payload.py
+++ /dev/null
@@ -1,244 +0,0 @@
-# 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.
-from typing import Any
-from unittest.mock import patch
-
-import pytest
-from flask import current_app
-
-from superset import viz
-from superset.common.db_query_status import QueryStatus
-from superset.connectors.sqla.models import SqlaTable
-from superset.errors import SupersetErrorType
-from superset.exceptions import (
- OAuth2RedirectError,
- QueryObjectValidationError,
-)
-from superset.models.core import Database
-
-QUERY_OBJ: dict[str, Any] = {"row_limit": 100, "from_dttm": None, "to_dttm": None}
-
-
-def _viz() -> viz.BaseViz:
- database = Database(database_name="d", sqlalchemy_uri="sqlite://")
- datasource = SqlaTable(
- table_name="t",
- columns=[],
- metrics=[],
- main_dttm_col=None,
- database=database,
- )
- # ``force=True`` skips the data cache lookup branch so ``get_df`` is always
- # invoked, which is what we want to assert error-handling against.
- return viz.BaseViz(
- datasource=datasource,
- form_data={"viz_type": "table"},
- force=True,
- )
-
-
-def _timeseries_viz(form_data: dict[str, Any]) -> viz.NVD3TimeSeriesViz:
- database = Database(database_name="d", sqlalchemy_uri="sqlite://")
- datasource = SqlaTable(
- table_name="t",
- columns=[],
- metrics=[],
- main_dttm_col=None,
- database=database,
- )
- base_form_data: dict[str, Any] = {"viz_type": "line", "metrics": ["value"]}
- base_form_data.update(form_data)
- return viz.NVD3TimeSeriesViz(
- datasource=datasource,
- form_data=base_form_data,
- force=True,
- )
-
-
-def _resample_df() -> Any:
- import pandas as pd
-
- from superset.utils.core import DTTM_ALIAS
-
- return pd.DataFrame(
- {
- DTTM_ALIAS: pd.to_datetime(["2024-01-01", "2024-01-02", "2024-01-03"]),
- "value": [1, 2, 3],
- }
- )
-
-
-def test_process_data_rejects_unknown_resample_method() -> None:
- """
- A resample method outside the allowlist must raise
- ``QueryObjectValidationError`` before any dynamic dispatch happens.
- """
- obj = _timeseries_viz({"resample_rule": "1D", "resample_method": "__class__"})
-
- with pytest.raises(QueryObjectValidationError):
- obj.process_data(_resample_df())
-
-
-def test_process_data_accepts_allowlisted_resample_method() -> None:
- """
- A valid resample method (e.g. ``mean``) is applied successfully.
- """
- obj = _timeseries_viz({"resample_rule": "1D", "resample_method": "mean"})
-
- result = obj.process_data(_resample_df())
-
- assert result is not None
- assert not result.empty
-
-
-def test_run_extra_queries_rejects_excessive_time_compare() -> None:
- """
- Requesting more time-shift comparisons than ``VIZ_TIME_COMPARE_MAX`` must
- raise ``QueryObjectValidationError`` before any sub-queries are issued.
- """
- max_compare = current_app.config["VIZ_TIME_COMPARE_MAX"]
- obj = _timeseries_viz(
- {"time_compare": [f"{i} days ago" for i in range(1, max_compare + 2)]}
- )
-
- with pytest.raises(QueryObjectValidationError):
- obj.run_extra_queries()
-
-
-def test_deck_multi_rejects_excessive_sub_slices() -> None:
- """
- Requesting more deck.gl sub-slices than ``DECK_MULTI_MAX_SLICES`` must raise
- ``QueryObjectValidationError`` before any sub-query is issued.
- """
- database = Database(database_name="d", sqlalchemy_uri="sqlite://")
- datasource = SqlaTable(
- table_name="t",
- columns=[],
- metrics=[],
- main_dttm_col=None,
- database=database,
- )
- max_slices = current_app.config["DECK_MULTI_MAX_SLICES"]
- obj = viz.DeckGLMultiLayer(
- datasource=datasource,
- form_data={
- "viz_type": "deck_multi",
- "deck_slices": list(range(max_slices + 1)),
- },
- force=True,
- )
-
- with pytest.raises(QueryObjectValidationError):
- obj.get_data(_resample_df())
-
-
-def test_get_df_payload_propagates_oauth2_redirect_error() -> None:
- """
- OAuth2RedirectError (a SupersetErrorException) must propagate out of
- ``get_df_payload`` so the global Flask error handler can serialize it.
- """
- obj = _viz()
- oauth_exc = OAuth2RedirectError(
- url="https://accounts.example.com/o/oauth2/v2/auth?...",
- tab_id="tab-123",
- redirect_uri="https://superset.example.com/oauth2/redirect",
- )
-
- with patch.object(viz.BaseViz, "get_df", side_effect=oauth_exc):
- with pytest.raises(OAuth2RedirectError) as exc_info:
- obj.get_df_payload(QUERY_OBJ)
-
- assert exc_info.value.error.error_type == SupersetErrorType.OAUTH2_REDIRECT
- assert exc_info.value.error.extra == {
- "url": "https://accounts.example.com/o/oauth2/v2/auth?...",
- "tab_id": "tab-123",
- "redirect_uri": "https://superset.example.com/oauth2/redirect",
- }
-
-
-def test_get_df_payload_captures_generic_exception_as_viz_get_df_error() -> None:
- """
- Non-Superset exception raised by ``get_df`` are downgraded to a
- ``VIZ_GET_DF_ERROR`` entry on ``self.errors``.
- """
- obj = _viz()
-
- with patch.object(viz.BaseViz, "get_df", side_effect=RuntimeError("boom")):
- payload = obj.get_df_payload(QUERY_OBJ)
-
- assert obj.status == QueryStatus.FAILED
- assert payload["status"] == QueryStatus.FAILED
- assert len(obj.errors) == 1
- assert obj.errors[0]["error_type"] == SupersetErrorType.VIZ_GET_DF_ERROR
- assert obj.errors[0]["message"] == "boom"
-
-
-def test_get_df_payload_captures_query_object_validation_error() -> None:
- """
- ``QueryObjectValidationError`` is reported as ``VIZ_GET_DF_ERROR``.
- """
- obj = _viz()
-
- with patch.object(
- viz.BaseViz,
- "get_df",
- side_effect=QueryObjectValidationError("bad query"),
- ):
- payload = obj.get_df_payload(QUERY_OBJ)
-
- assert obj.status == QueryStatus.FAILED
- assert payload["status"] == QueryStatus.FAILED
- assert len(obj.errors) == 1
- assert obj.errors[0]["error_type"] == SupersetErrorType.VIZ_GET_DF_ERROR
- assert obj.errors[0]["message"] == "bad query"
-
-
-def test_get_df_payload_hides_stacktrace_when_show_stacktrace_disabled() -> None:
- """
- The error payload must not expose a stacktrace when neither ``debug`` nor
- ``SHOW_STACKTRACE`` is enabled.
- """
- obj = _viz()
-
- # The test app runs with ``debug`` disabled, so toggling ``SHOW_STACKTRACE``
- # off is enough to exercise the hidden-stacktrace branch.
- assert current_app.debug is False
- with (
- patch.object(viz.BaseViz, "get_df", side_effect=RuntimeError("boom")),
- patch.dict(current_app.config, {"SHOW_STACKTRACE": False}),
- ):
- payload = obj.get_df_payload(QUERY_OBJ)
-
- assert obj.status == QueryStatus.FAILED
- assert payload["stacktrace"] is None
-
-
-def test_get_df_payload_shows_stacktrace_when_show_stacktrace_enabled() -> None:
- """
- The error payload must expose a stacktrace when ``SHOW_STACKTRACE`` is enabled.
- """
- obj = _viz()
-
- with (
- patch.object(viz.BaseViz, "get_df", side_effect=RuntimeError("boom")),
- patch.dict(current_app.config, {"SHOW_STACKTRACE": True}),
- ):
- payload = obj.get_df_payload(QUERY_OBJ)
-
- assert obj.status == QueryStatus.FAILED
- assert payload["stacktrace"] is not None
- assert "RuntimeError" in payload["stacktrace"]