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74 lines
2.4 KiB
Python
74 lines
2.4 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 pandas as pd
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from sqlalchemy import DateTime
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from superset import db
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from superset.utils import core as utils
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from .helpers import config, get_example_data, get_slice_json, merge_slice, Slice, TBL
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def load_random_time_series_data():
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"""Loading random time series data from a zip file in the repo"""
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data = get_example_data("random_time_series.json.gz")
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pdf = pd.read_json(data)
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pdf.ds = pd.to_datetime(pdf.ds, unit="s")
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pdf.to_sql(
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"random_time_series",
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db.engine,
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if_exists="replace",
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chunksize=500,
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dtype={"ds": DateTime},
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index=False,
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)
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print("Done loading table!")
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print("-" * 80)
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print("Creating table [random_time_series] reference")
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obj = db.session.query(TBL).filter_by(table_name="random_time_series").first()
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if not obj:
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obj = TBL(table_name="random_time_series")
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obj.main_dttm_col = "ds"
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obj.database = utils.get_or_create_main_db()
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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": "day",
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"row_limit": config.get("ROW_LIMIT"),
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"since": "1 year ago",
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"until": "now",
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"metric": "count",
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"where": "",
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"viz_type": "cal_heatmap",
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"domain_granularity": "month",
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"subdomain_granularity": "day",
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}
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print("Creating a slice")
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slc = Slice(
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slice_name="Calendar Heatmap",
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viz_type="cal_heatmap",
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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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merge_slice(slc)
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