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128 lines
4.5 KiB
Python
128 lines
4.5 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 logging
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import random
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import geohash
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from sqlalchemy import DateTime, Float, inspect, String
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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.models.slice import Slice
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from superset.sql.parse import Table
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from superset.utils.core import DatasourceType
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from .helpers import (
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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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read_example_data,
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)
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logger = logging.getLogger(__name__)
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def load_long_lat_data(only_metadata: bool = False, force: bool = False) -> None:
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"""Loading lat/long data from a csv file in the repo"""
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tbl_name = "long_lat"
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database = database_utils.get_example_database()
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with database.get_sqla_engine() as engine:
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schema = inspect(engine).default_schema_name
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table_exists = database.has_table(Table(tbl_name, schema))
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if not only_metadata and (not table_exists or force):
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pdf = read_example_data(
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"examples://san_francisco.csv.gz", encoding="utf-8", compression="gzip"
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)
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start = datetime.datetime.now().replace(
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hour=0, minute=0, second=0, microsecond=0
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)
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pdf["datetime"] = [
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start + datetime.timedelta(hours=i * 24 / (len(pdf) - 1))
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for i in range(len(pdf))
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]
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pdf["occupancy"] = [random.randint(1, 6) for _ in range(len(pdf))] # noqa: S311
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pdf["radius_miles"] = [random.uniform(1, 3) for _ in range(len(pdf))] # noqa: S311
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pdf["geohash"] = pdf[["LAT", "LON"]].apply(
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lambda x: geohash.encode(*x), axis=1
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)
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pdf["delimited"] = pdf["LAT"].map(str).str.cat(pdf["LON"].map(str), sep=",")
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pdf.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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"longitude": Float(),
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"latitude": Float(),
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"number": Float(),
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"street": String(100),
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"unit": String(10),
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"city": String(50),
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"district": String(50),
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"region": String(50),
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"postcode": Float(),
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"id": String(100),
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"datetime": DateTime(),
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"occupancy": Float(),
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"radius_miles": Float(),
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"geohash": String(12),
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"delimited": String(60),
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},
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index=False,
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)
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logger.debug("Done loading table!")
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logger.debug("-" * 80)
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logger.debug("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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db.session.add(obj)
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obj.main_dttm_col = "datetime"
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obj.database = database
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obj.filter_select_enabled = True
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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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"since": "2014-01-01",
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"until": "now",
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"viz_type": "mapbox",
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"all_columns_x": "LON",
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"all_columns_y": "LAT",
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"mapbox_style": "https://tile.openstreetmap.org/{z}/{x}/{y}.png",
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"all_columns": ["occupancy"],
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"row_limit": 500000,
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}
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logger.debug("Creating a slice")
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slc = Slice(
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slice_name="OSM Long/Lat",
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viz_type="osm",
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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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