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32bb1ce3ff
* pass datasource_type and datasource_id to form_data * add datasource_type to delete command * add datasource_type to delete command * fix old keys implementation * add more tests
122 lines
4.0 KiB
Python
122 lines
4.0 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, inspect, String
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from sqlalchemy.sql import column
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import superset.utils.database as database_utils
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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.models.slice import Slice
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from superset.utils.core import DatasourceType
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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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get_table_connector_registry,
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merge_slice,
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misc_dash_slices,
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)
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def load_country_map_data(only_metadata: bool = False, force: bool = False) -> None:
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"""Loading data for map with country map"""
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tbl_name = "birth_france_by_region"
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database = database_utils.get_example_database()
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engine = database.get_sqla_engine()
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schema = inspect(engine).default_schema_name
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table_exists = database.has_table_by_name(tbl_name)
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if not only_metadata and (not table_exists or force):
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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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)
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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(
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tbl_name,
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engine,
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schema=schema,
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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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)
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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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table = get_table_connector_registry()
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obj = db.session.query(table).filter_by(table_name=tbl_name).first()
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if not obj:
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obj = table(table_name=tbl_name, schema=schema)
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obj.main_dttm_col = "dttm"
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obj.database = database
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obj.filter_select_enabled = True
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if not any(col.metric_name == "avg__2004" for col in obj.metrics):
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col = str(column("2004").compile(db.engine))
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obj.metrics.append(SqlMetric(metric_name="avg__2004", expression=f"AVG({col})"))
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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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"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": {"type": "INT", "column_name": "2004"},
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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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"select_country": "france",
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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=DatasourceType.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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