blob: 98b444f9db2f6d6e1970369c7f0b77afbbdb7e9c [file] [log] [blame]
# 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, inspect, String
from sqlalchemy.sql import column
import superset.utils.database as database_utils
from superset import db
from superset.connectors.sqla.models import SqlMetric
from superset.models.slice import Slice
from superset.sql_parse import Table
from superset.utils.core import DatasourceType
from .helpers import (
get_example_url,
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 = database_utils.get_example_database()
with database.get_sqla_engine() as engine:
schema = inspect(engine).default_schema_name
table_exists = database.has_table(Table(tbl_name, schema))
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)