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dced2f8564
Co-authored-by: bito-code-review[bot] <188872107+bito-code-review[bot]@users.noreply.github.com> Co-authored-by: Claude <noreply@anthropic.com>
105 lines
3.4 KiB
Python
105 lines
3.4 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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from __future__ import annotations
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import logging
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from datetime import datetime
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from typing import Dict, List, TYPE_CHECKING
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from flask_appbuilder.models.sqla.interface import SQLAInterface
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from superset.charts.filters import ChartFilter
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from superset.commands.chart.exceptions import ChartNotFoundError
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from superset.daos.base import BaseDAO
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from superset.extensions import db
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from superset.models.core import FavStar, FavStarClassName
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from superset.models.slice import id_or_uuid_filter, Slice
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from superset.utils.core import get_user_id
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if TYPE_CHECKING:
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pass
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logger = logging.getLogger(__name__)
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# Custom filterable fields for charts
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CHART_CUSTOM_FIELDS = {
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"viz_type": ["eq", "in_", "like"],
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"datasource_name": ["eq", "in_", "like"],
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}
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class ChartDAO(BaseDAO[Slice]):
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base_filter = ChartFilter
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@classmethod
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def get_filterable_columns_and_operators(cls) -> Dict[str, List[str]]:
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filterable = super().get_filterable_columns_and_operators()
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# Add custom fields for charts
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filterable.update(CHART_CUSTOM_FIELDS)
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return filterable
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@staticmethod
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def get_by_id_or_uuid(id_or_uuid: str) -> Slice:
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query = db.session.query(Slice).filter(id_or_uuid_filter(id_or_uuid))
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# Apply chart base filters
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query = ChartFilter("id", SQLAInterface(Slice, db.session)).apply(query, None)
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chart = query.one_or_none()
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if not chart:
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raise ChartNotFoundError()
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return chart
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@staticmethod
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def favorited_ids(charts: list[Slice]) -> list[FavStar]:
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ids = [chart.id for chart in charts]
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return [
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star.obj_id
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for star in db.session.query(FavStar.obj_id)
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.filter(
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FavStar.class_name == FavStarClassName.CHART,
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FavStar.obj_id.in_(ids),
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FavStar.user_id == get_user_id(),
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)
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.all()
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]
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@staticmethod
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def add_favorite(chart: Slice) -> None:
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ids = ChartDAO.favorited_ids([chart])
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if chart.id not in ids:
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db.session.add(
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FavStar(
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class_name=FavStarClassName.CHART,
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obj_id=chart.id,
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user_id=get_user_id(),
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dttm=datetime.now(),
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)
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)
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@staticmethod
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def remove_favorite(chart: Slice) -> None:
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fav = (
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db.session.query(FavStar)
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.filter(
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FavStar.class_name == FavStarClassName.CHART,
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FavStar.obj_id == chart.id,
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FavStar.user_id == get_user_id(),
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)
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.one_or_none()
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)
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if fav:
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db.session.delete(fav)
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