code: 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 = database_utils.get_example_database()
  
      with database.get_sqla_engine_with_context() as engine:
          schema = inspect(engine).default_schema_name
          table_exists = database.has_table_by_name(tbl_name)
  
          if not only_metadata and (not table_exists or force):
              url = get_example_url("energy.json.gz")
              pdf = pd.read_json(url, compression="gzip")
              pdf = pdf.head(100) if sample else pdf
              pdf.to_sql(
                  tbl_name,
                  engine,
                  schema=schema,
                  if_exists="replace",
                  chunksize=500,
                  dtype={
                      "source": String(255),
                      "target": String(255),
                      "value": Float(),
                  },
                  index=False,
                  method="multi",
              )
  
      print("Creating table [wb_health_population] 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, schema=schema)
          db.session.add(tbl)
      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.commit()
      tbl.fetch_metadata()
  
      slc = Slice(
          slice_name="Energy Sankey",
          viz_type="sankey",
          datasource_type=DatasourceType.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=DatasourceType.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=DatasourceType.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)
  
file_path: superset/superset/examples/energy.py
imports: import textwrap
  import pandas
  from sqlalchemy import Float, inspect, String
  from sqlalchemy.sql import column
  import superset.utils.database
  from superset import db
  from superset.connectors.sqla.models import SqlMetric
  from superset.models.slice import Slice
  from superset.utils.core import DatasourceType
  from .helpers import get_example_url, get_table_connector_registry, merge_slice, misc_dash_slices
label_desc: Use image node_id 1 for calling a global function with example usage: load_energy(only_metadata, force, sample) without return types