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fix-sample
| Author | SHA1 | Date | |
|---|---|---|---|
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339d6cac70 |
14
.github/workflows/superset-frontend.yml
vendored
14
.github/workflows/superset-frontend.yml
vendored
@@ -122,13 +122,25 @@ jobs:
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pattern: coverage-artifacts-*
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path: coverage/
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- name: Reorganize test result reports
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run: |
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find coverage/
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for i in {1..8}; do
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mv coverage/coverage-artifacts-${i}/coverage-final.json coverage/coverage-shard-${i}.json
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done
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shell: bash
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- name: Merge Code Coverage
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run: npx nyc merge coverage/ merged-output/coverage-summary.json
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- name: Upload Code Coverage
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uses: codecov/codecov-action@fb8b3582c8e4def4969c97caa2f19720cb33a72f # v7.0.0
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with:
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flags: javascript
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use_oidc: true
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verbose: true
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directory: coverage
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disable_search: true
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files: merged-output/coverage-summary.json
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slug: apache/superset
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lint-frontend:
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@@ -54,7 +54,7 @@ dependencies = [
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"deprecation>=2.1.0, <2.2.0",
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"flask>=2.2.5, <4.0.0",
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"flask-appbuilder>=5.2.2, <6.0.0",
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"flask-caching>=2.4.1, <3",
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"flask-caching>=2.1.0, <3",
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"flask-compress>=1.13, <2.0",
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"flask-talisman>=1.0.0, <2.0",
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"flask-login>=0.6.0, < 1.0",
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@@ -92,7 +92,7 @@ dependencies = [
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"Pillow>=11.0.0, <13",
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"polyline>=2.0.0, <3.0",
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"pydantic>=2.8.0",
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"pyparsing>=3.3.2, <4",
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"pyparsing>=3.0.6, <4",
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"python-dateutil",
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"python-dotenv", # optional dependencies for Flask but required for Superset, see https://flask.palletsprojects.com/en/stable/installation/#optional-dependencies
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"pygeohash",
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@@ -127,7 +127,7 @@ aurora-data-api = ["preset-sqlalchemy-aurora-data-api>=0.2.8,<0.3"]
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bigquery = [
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"pandas-gbq>=0.35.0",
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"sqlalchemy-bigquery>=1.17.0",
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"google-cloud-bigquery>=3.42.2",
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"google-cloud-bigquery>=3.42.1",
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]
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clickhouse = ["clickhouse-connect>=1.4.2, <2.0"]
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cockroachdb = ["cockroachdb>=0.3.5, <0.4"]
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@@ -142,8 +142,8 @@ databricks = [
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"databricks-sql-connector>=4.2.6, <4.4.0",
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"databricks-sqlalchemy==1.0.5",
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]
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datafusion = ["flightsql-dbapi>=0.2.2, <0.3"]
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db2 = ["ibm-db-sa<=0.4.4, >=0.4.4"]
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datafusion = ["flightsql-dbapi>=0.2.0, <0.3"]
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db2 = ["ibm-db-sa>0.3.8, <=0.4.4"]
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denodo = ["denodo-sqlalchemy>=2.0.5,<2.1.0"]
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dremio = ["sqlalchemy-dremio>=1.2.1, <4"]
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drill = ["sqlalchemy-drill>=1.1.10, <2"]
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@@ -189,7 +189,7 @@ ocient = [
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"shapely",
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"geojson",
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]
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oracle = ["oracledb>=4.0.2, <5"]
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oracle = ["oracledb>=2.0.0, <5"]
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parseable = ["sqlalchemy-parseable>=0.1.6,<0.2.0"]
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pinot = ["pinotdb>=5.0.0, <10.0.0"]
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playwright = ["playwright>=1.61.0, <2"]
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@@ -201,7 +201,7 @@ redshift = ["sqlalchemy-redshift>=0.8.1, <0.9"]
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risingwave = ["sqlalchemy-risingwave"]
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shillelagh = ["shillelagh[all]>=1.4.4, <2"]
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singlestore = ["sqlalchemy-singlestoredb>=1.2.1, <2"]
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snowflake = ["snowflake-sqlalchemy>=1.11.0, <2"]
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snowflake = ["snowflake-sqlalchemy>=1.10.2, <2"]
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sqlite = ["syntaqlite>=0.7.0,<0.8.0"]
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spark = [
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"pyhive[hive_pure_sasl]>=0.7",
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@@ -227,7 +227,7 @@ development = [
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"docker",
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"flask-testing",
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"freezegun",
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"grpcio>=1.82.1",
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"grpcio>=1.81.1",
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"openapi-spec-validator",
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"parameterized",
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"pip",
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@@ -130,7 +130,7 @@ flask-appbuilder==5.2.2
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# apache-superset-core
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flask-babel==3.1.0
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# via flask-appbuilder
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flask-caching==2.4.1
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flask-caching==2.3.1
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# via apache-superset (pyproject.toml)
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flask-compress==1.24
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# via apache-superset (pyproject.toml)
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@@ -329,7 +329,7 @@ pyopenssl==26.3.0
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# via
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# -r requirements/base.in
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# shillelagh
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pyparsing==3.3.2
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pyparsing==3.2.3
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# via apache-superset (pyproject.toml)
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pysocks==1.7.1
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# via urllib3
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@@ -276,7 +276,7 @@ flask-babel==3.1.0
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# via
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# -c requirements/base-constraint.txt
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# flask-appbuilder
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flask-caching==2.4.1
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flask-caching==2.3.1
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# via
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# -c requirements/base-constraint.txt
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# apache-superset
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@@ -341,7 +341,7 @@ geopy==2.4.1
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# apache-superset
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gevent==26.4.0
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# via apache-superset
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google-api-core==2.33.0
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google-api-core==2.23.0
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# via
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# google-cloud-bigquery
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# google-cloud-core
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@@ -362,7 +362,7 @@ google-auth-oauthlib==1.2.1
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# via
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# pandas-gbq
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# pydata-google-auth
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google-cloud-bigquery==3.42.2
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google-cloud-bigquery==3.42.1
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# via
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# apache-superset
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# pandas-gbq
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@@ -386,7 +386,7 @@ greenlet==3.5.3
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# sqlalchemy
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griffelib==2.0.2
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# via fastmcp-slim
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grpcio==1.83.0
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grpcio==1.81.1
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# via
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# apache-superset
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# google-api-core
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@@ -795,7 +795,7 @@ pyopenssl==26.3.0
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# -c requirements/base-constraint.txt
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# google-auth
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# shillelagh
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pyparsing==3.3.2
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pyparsing==3.2.3
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# via
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# -c requirements/base-constraint.txt
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# apache-superset
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@@ -66,6 +66,12 @@ const StyledTable = styled(Table)<{
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showRowCount?: boolean;
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}>`
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${({ theme, isPaginationSticky, showRowCount }) => `
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th.ant-column-cell {
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overflow: hidden;
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text-overflow: ellipsis;
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white-space: nowrap;
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}
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.actions {
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opacity: 0;
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font-size: ${theme.fontSizeXL}px;
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@@ -1,67 +0,0 @@
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/**
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* Licensed to the Apache Software Foundation (ASF) under one
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* or more contributor license agreements. See the NOTICE file
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* distributed with this work for additional information
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* regarding copyright ownership. The ASF licenses this file
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* to you under the Apache License, Version 2.0 (the
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* "License"); you may not use this file except in compliance
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* with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing,
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* software distributed under the License is distributed on an
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* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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* KIND, either express or implied. See the License for the
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* specific language governing permissions and limitations
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* under the License.
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*/
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import { executeQuery } from './actions';
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import fetchMock from 'fetch-mock';
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fetchMock.post('glob:*/sqllab/execute', { result: [] });
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afterAll(() => {
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fetchMock.clearHistory().removeRoutes();
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});
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test('executeQuery', async () => {
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const mockDispatch = jest.fn();
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const mockedQueryExecutePayload = {
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client_id: 'client_id_1',
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database_id: 1,
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runAsync: false,
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catalog: null,
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schema: 'schema_1',
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sql: '1',
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tmp_table_name: 'tmp_table_1',
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select_as_cta: false,
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ctas_method: 'SELECT',
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queryLimit: 10,
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expand_data: false,
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};
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const returnedDispatchFunc = executeQuery(mockedQueryExecutePayload);
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await returnedDispatchFunc(mockDispatch);
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const [
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[setQueryIsLoadingActionObject],
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[setQueryResultActionObject],
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[setQueryIsNotLoadingActionObject],
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] = mockDispatch.mock.calls;
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expect(setQueryIsLoadingActionObject).toStrictEqual({
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type: 'SET_QUERY_IS_LOADING',
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payload: true,
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});
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expect(setQueryResultActionObject).toStrictEqual({
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type: 'SET_QUERY_RESULT',
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payload: {
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result: [],
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},
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});
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expect(setQueryIsNotLoadingActionObject).toStrictEqual({
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type: 'SET_QUERY_IS_LOADING',
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payload: false,
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});
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});
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@@ -67,7 +67,7 @@ export function executeQuery(payload: QueryExecutePayload) {
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const result = await executeQueryApi(payload);
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dispatch(setQueryResult(result as QueryExecuteResponse));
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} catch (error) {
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dispatch(setQueryError((error as Error).message));
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dispatch(setQueryError(error.message));
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} finally {
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dispatch(setQueryIsLoading(false));
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}
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@@ -2017,13 +2017,26 @@ def _process_datetime_column(
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# Parse with or without format (suppress warning if no format)
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if format_to_use:
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df[col.col_label] = pd.to_datetime(
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converted = pd.to_datetime(
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df[col.col_label],
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utc=False,
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format=format_to_use,
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errors="coerce",
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exact=False,
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)
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# A format that coerces every non-null value to NaT is a mismatch
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# (e.g. an epoch-millis column that inherited a '%Y' string format
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# when used as a chart's granularity). Assigning it would silently
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# blank the whole column, so keep the original values instead.
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if df[col.col_label].notna().any() and not converted.notna().any():
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logger.warning(
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"Datetime format %s coerced every value of column %s to NaT; "
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"keeping the original values",
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format_to_use,
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col.col_label,
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)
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else:
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df[col.col_label] = converted
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else:
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with warnings.catch_warnings():
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warnings.filterwarnings("ignore", message=".*Could not infer format.*")
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@@ -273,6 +273,22 @@ def test_normalize_dttm_col() -> None:
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assert df["__time"].astype(str).tolist() == ["2017-07-01"]
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def test_normalize_dttm_col_mismatched_format_keeps_values() -> None:
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"""A datetime format that coerces every value to NaT is a mismatch (e.g. an
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epoch-millis column that inherited a ``%Y`` string format when used as a
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chart's granularity); applying it would silently blank the whole column, so
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the original values are kept instead of being nulled. Regression for the
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Samples pane showing N/A for such columns."""
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df = pd.DataFrame({"year": [1136073600000, 473385600000]}) # epoch ms
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before = df["year"].tolist()
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normalize_dttm_col(df, (DateColumn(col_label="year", timestamp_format="%Y"),))
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# not blanked to NaT/None
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assert df["year"].notna().all()
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assert df["year"].tolist() == before
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def test_normalize_dttm_col_epoch_seconds() -> None:
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"""Test conversion of epoch seconds."""
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df = pd.DataFrame(
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