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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
111 lines
3.4 KiB
Python
111 lines
3.4 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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import datetime
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import pandas as pd
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from sqlalchemy import BigInteger, Date, 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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get_example_data,
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get_slice_json,
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merge_slice,
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misc_dash_slices,
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Slice,
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TBL,
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)
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def load_country_map_data():
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"""Loading data for map with country map"""
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csv_bytes = get_example_data(
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'birth_france_data_for_country_map.csv', is_gzip=False, make_bytes=True)
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data = pd.read_csv(csv_bytes, encoding='utf-8')
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data['dttm'] = datetime.datetime.now().date()
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data.to_sql( # pylint: disable=no-member
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'birth_france_by_region',
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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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'DEPT_ID': String(10),
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'2003': BigInteger,
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'2004': BigInteger,
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'2005': BigInteger,
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'2006': BigInteger,
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'2007': BigInteger,
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'2008': BigInteger,
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'2009': BigInteger,
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'2010': BigInteger,
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'2011': BigInteger,
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'2012': BigInteger,
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'2013': BigInteger,
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'2014': BigInteger,
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'dttm': Date(),
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},
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index=False)
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print('Done loading table!')
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print('-' * 80)
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print('Creating table reference')
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obj = db.session.query(TBL).filter_by(table_name='birth_france_by_region').first()
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if not obj:
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obj = TBL(table_name='birth_france_by_region')
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obj.main_dttm_col = 'dttm'
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obj.database = utils.get_or_create_main_db()
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if not any(col.metric_name == 'avg__2004' for col in obj.metrics):
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obj.metrics.append(SqlMetric(
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metric_name='avg__2004',
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expression='AVG(2004)',
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))
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db.session.merge(obj)
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db.session.commit()
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obj.fetch_metadata()
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tbl = obj
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slice_data = {
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'granularity_sqla': '',
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'since': '',
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'until': '',
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'where': '',
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'viz_type': 'country_map',
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'entity': 'DEPT_ID',
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'metric': {
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'expressionType': 'SIMPLE',
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'column': {
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'type': 'INT',
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'column_name': '2004',
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},
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'aggregate': 'AVG',
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'label': 'Boys',
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'optionName': 'metric_112342',
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},
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'row_limit': 500000,
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}
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print('Creating a slice')
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slc = Slice(
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slice_name='Birth in France by department in 2016',
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viz_type='country_map',
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datasource_type='table',
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datasource_id=tbl.id,
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params=get_slice_json(slice_data),
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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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