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.
  """Loads datasets, dashboards and slices in a new superset instance"""
  import textwrap
  
  import pandas as pd
  from sqlalchemy import Float, String
  from sqlalchemy.sql import column
  
  from superset import db
  from superset.connectors.sqla.models import SqlMetric
  from superset.models.slice import Slice
  from superset.utils import core as utils
  
  from .helpers import (
      get_example_data,
      get_table_connector_registry,
      merge_slice,
      misc_dash_slices,
  )
  
  
  def load_energy(
      only_metadata: bool = False, force: bool = False, sample: bool = False
  ) -> None:
      """Loads an energy related dataset to use with sankey and graphs"""
      tbl_name = "energy_usage"
      database = utils.get_example_database()
      table_exists = database.has_table_by_name(tbl_name)
  
      if not only_metadata and (not table_exists or force):
          data = get_example_data("energy.json.gz")
          pdf = pd.read_json(data)
          pdf = pdf.head(100) if sample else pdf
          pdf.to_sql(
              tbl_name,
              database.get_sqla_engine(),
              if_exists="replace",
              chunksize=500,
              dtype={"source": String(255), "target": String(255), "value": Float()},
              index=False,
              method="multi",
          )
  
      print("Creating table [World Bank Health Data] reference")
      table = get_table_connector_registry()
      tbl = db.session.query(table).filter_by(table_name=tbl_name).first()
      if not tbl:
          tbl = table(table_name=tbl_name)
      tbl.description = "Energy consumption"
      tbl.database = database
      tbl.filter_select_enabled = True
  
      if not any(col.metric_name == "sum__value" for col in tbl.metrics):
          col = str(column("value").compile(db.engine))
          tbl.metrics.append(
              SqlMetric(metric_name="sum__value", expression=f"SUM({col})")
          )
  
      db.session.merge(tbl)
      db.session.commit()
      tbl.fetch_metadata()
  
      slc = Slice(
          slice_name="Energy Sankey",
          viz_type="sankey",
          datasource_type="table",
          datasource_id=tbl.id,
          params=textwrap.dedent(
              """\
          {
              "collapsed_fieldsets": "",
              "groupby": [
                  "source",
                  "target"
              ],
              "metric": "sum__value",
              "row_limit": "5000",
              "slice_name": "Energy Sankey",
              "viz_type": "sankey"
          }
          """
          ),
      )
      misc_dash_slices.add(slc.slice_name)
      merge_slice(slc)
  
      slc = Slice(
          slice_name="Energy Force Layout",
          viz_type="graph_chart",
          datasource_type="table",
          datasource_id=tbl.id,
          params=textwrap.dedent(
              """\
          {
              "source": "source",
              "target": "target",
              "edgeLength": 400,
              "repulsion": 1000,
              "layout": "force",
              "metric": "sum__value",
              "row_limit": "5000",
              "slice_name": "Force",
              "viz_type": "graph_chart"
          }
          """
          ),
      )
      misc_dash_slices.add(slc.slice_name)
      merge_slice(slc)
  
      slc = Slice(
          slice_name="Heatmap",
          viz_type="heatmap",
          datasource_type="table",
          datasource_id=tbl.id,
          params=textwrap.dedent(
              """\
          {
              "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"
          }
          """
          ),
      )
      misc_dash_slices.add(slc.slice_name)
      merge_slice(slc)
  