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3d08266714
* [load_examples] download data at runtime When running `superset load_examples` to load example data sets, Superset used to load from the local package. This created a few issues notably around licensing (what are these datasets licensed as?) and around package size. For now, I moved the data sets here: https://github.com/apache-superset/examples-data Altered the logic to download the data from where it is stored. * flakes
141 lines
4.1 KiB
Python
141 lines
4.1 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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"""Loads datasets, dashboards and slices in a new superset instance"""
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# pylint: disable=C,R,W
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import textwrap
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import pandas as pd
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from sqlalchemy import Float, String
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from superset import db
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from superset.connectors.sqla.models import SqlMetric
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from superset.utils import core as utils
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from .helpers import (
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DATA_FOLDER, get_example_data, merge_slice, misc_dash_slices, Slice, TBL,
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)
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def load_energy():
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"""Loads an energy related dataset to use with sankey and graphs"""
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tbl_name = 'energy_usage'
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data = get_example_data('energy.json.gz')
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pdf = pd.read_json(data)
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pdf.to_sql(
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tbl_name,
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db.engine,
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if_exists='replace',
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chunksize=500,
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dtype={
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'source': String(255),
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'target': String(255),
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'value': Float(),
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},
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index=False)
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print('Creating table [wb_health_population] reference')
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tbl = db.session.query(TBL).filter_by(table_name=tbl_name).first()
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if not tbl:
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tbl = TBL(table_name=tbl_name)
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tbl.description = 'Energy consumption'
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tbl.database = utils.get_or_create_main_db()
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if not any(col.metric_name == 'sum__value' for col in tbl.metrics):
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tbl.metrics.append(SqlMetric(
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metric_name='sum__value',
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expression='SUM(value)',
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))
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db.session.merge(tbl)
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db.session.commit()
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tbl.fetch_metadata()
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slc = Slice(
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slice_name='Energy Sankey',
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viz_type='sankey',
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datasource_type='table',
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datasource_id=tbl.id,
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params=textwrap.dedent("""\
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{
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"collapsed_fieldsets": "",
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"groupby": [
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"source",
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"target"
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],
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"having": "",
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"metric": "sum__value",
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"row_limit": "5000",
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"slice_name": "Energy Sankey",
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"viz_type": "sankey",
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"where": ""
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}
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"""),
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)
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misc_dash_slices.add(slc.slice_name)
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merge_slice(slc)
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slc = Slice(
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slice_name='Energy Force Layout',
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viz_type='directed_force',
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datasource_type='table',
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datasource_id=tbl.id,
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params=textwrap.dedent("""\
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{
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"charge": "-500",
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"collapsed_fieldsets": "",
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"groupby": [
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"source",
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"target"
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],
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"having": "",
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"link_length": "200",
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"metric": "sum__value",
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"row_limit": "5000",
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"slice_name": "Force",
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"viz_type": "directed_force",
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"where": ""
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}
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"""),
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)
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misc_dash_slices.add(slc.slice_name)
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merge_slice(slc)
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slc = Slice(
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slice_name='Heatmap',
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viz_type='heatmap',
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datasource_type='table',
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datasource_id=tbl.id,
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params=textwrap.dedent("""\
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{
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"all_columns_x": "source",
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"all_columns_y": "target",
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"canvas_image_rendering": "pixelated",
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"collapsed_fieldsets": "",
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"having": "",
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"linear_color_scheme": "blue_white_yellow",
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"metric": "sum__value",
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"normalize_across": "heatmap",
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"slice_name": "Heatmap",
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"viz_type": "heatmap",
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"where": "",
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"xscale_interval": "1",
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"yscale_interval": "1"
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}
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"""),
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)
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misc_dash_slices.add(slc.slice_name)
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merge_slice(slc)
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