text: # 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 random
  import textwrap
  from typing import Dict, Set
  
  import pandas as pd
  import pytest
  from pandas import DataFrame
  from sqlalchemy import column, Float, String
  
  from superset import db
  from superset.connectors.sqla.models import SqlaTable, SqlMetric
  from superset.models.dashboard import Dashboard
  from superset.models.slice import Slice
  from superset.utils.core import get_example_database
  from tests.integration_tests.dashboard_utils import (
      create_slice,
      create_table_for_dashboard,
  )
  from tests.integration_tests.test_app import app
  
  misc_dash_slices: Set[str] = set()
  
  
  @pytest.fixture()
  def load_energy_table_with_slice():
      table_name = "energy_usage"
      df = _get_dataframe()
      with app.app_context():
          _create_energy_table(df, table_name)
          yield
          _cleanup()
  
  
  def _get_dataframe():
      data = _get_energy_data()
      return pd.DataFrame.from_dict(data)
  
  
  def _create_energy_table(df: DataFrame, table_name: str):
      database = get_example_database()
  
      table_description = "Energy consumption"
      schema = {"source": String(255), "target": String(255), "value": Float()}
      table = create_table_for_dashboard(
          df, table_name, database, schema, table_description
      )
      table.fetch_metadata()
  
      if not any(col.metric_name == "sum__value" for col in table.metrics):
          col = str(column("value").compile(db.engine))
          table.metrics.append(
              SqlMetric(metric_name="sum__value", expression=f"SUM({col})")
          )
  
      db.session.merge(table)
      db.session.commit()
      table.fetch_metadata()
  
      for slice_data in _get_energy_slices():
          _create_and_commit_energy_slice(
              table,
              slice_data["slice_title"],
              slice_data["viz_type"],
              slice_data["params"],
          )
  
  
  def _create_and_commit_energy_slice(
      table: SqlaTable, title: str, viz_type: str, param: Dict[str, str]
  ):
      slice = create_slice(title, viz_type, table, param)
      existing_slice = (
          db.session.query(Slice).filter_by(slice_name=slice.slice_name).first()
      )
      if existing_slice:
          db.session.delete(existing_slice)
      db.session.add(slice)
      db.session.commit()
      return slice
  
  
  def _cleanup() -> None:
      engine = get_example_database().get_sqla_engine()
      engine.execute("DROP TABLE IF EXISTS energy_usage")
      for slice_data in _get_energy_slices():
          slice = (
              db.session.query(Slice)
              .filter_by(slice_name=slice_data["slice_title"])
              .first()
          )
          db.session.delete(slice)
  
      metric = (
          db.session.query(SqlMetric).filter_by(metric_name="sum__value").one_or_none()
      )
      if metric:
          db.session.delete(metric)
  
      db.session.commit()
  
  
  def _get_energy_data():
      data = []
      for i in range(85):
          data.append(
              {
                  "source": f"energy_source{i}",
                  "target": f"energy_target{i}",
                  "value": random.uniform(0.1, 11.0),
              }
          )
      return data
  
  
  def _get_energy_slices():
      return [
          {
              "slice_title": "Energy Sankey",
              "viz_type": "sankey",
              "params": {
                  "collapsed_fieldsets": "",
                  "groupby": ["source", "target"],
                  "metric": "sum__value",
                  "row_limit": "5000",
                  "slice_name": "Energy Sankey",
                  "viz_type": "sankey",
              },
          },
          {
              "slice_title": "Energy Force Layout",
              "viz_type": "graph_chart",
              "params": {
                  "source": "source",
                  "target": "target",
                  "edgeLength": 400,
                  "repulsion": 1000,
                  "layout": "force",
                  "metric": "sum__value",
                  "row_limit": "5000",
                  "slice_name": "Force",
                  "viz_type": "graph_chart",
              },
          },
          {
              "slice_title": "Heatmap",
              "viz_type": "heatmap",
              "params": {
                  "all_columns_x": "source",
                  "all_columns_y": "target",
                  "canvas_image_rendering": "pixelated",
                  "collapsed_fieldsets": "",
                  "linear_color_scheme": "blue_white_yellow",
                  "metric": "sum__value",
                  "normalize_across": "heatmap",
                  "slice_name": "Heatmap",
                  "viz_type": "heatmap",
                  "xscale_interval": "1",
                  "yscale_interval": "1",
              },
          },
      ]
  