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- # Licensed to the Apache Software Foundation (ASF) under one
- # or more contributor license agreements. See the NOTICE file
- # distributed with this work for additional information
- # regarding copyright ownership. The ASF licenses this file
- # to you under the Apache License, Version 2.0 (the
- # "License"); you may not use this file except in compliance
- # with the License. You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing,
- # software distributed under the License is distributed on an
- # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
- # KIND, either express or implied. See the License for the
- # specific language governing permissions and limitations
- # under the License.
- import datetime
- import random
- import geohash
- import pandas as pd
- from sqlalchemy import DateTime, Float, String
- from superset import db
- from superset.models.slice import Slice
- from superset.utils import core as utils
- from .helpers import (
- get_example_data,
- get_slice_json,
- merge_slice,
- misc_dash_slices,
- TBL,
- )
- def load_long_lat_data(only_metadata: bool = False, force: bool = False) -> None:
- """Loading lat/long data from a csv file in the repo"""
- tbl_name = "long_lat"
- database = utils.get_example_database()
- table_exists = database.has_table_by_name(tbl_name)
- if not only_metadata and (not table_exists or force):
- data = get_example_data("san_francisco.csv.gz", make_bytes=True)
- pdf = pd.read_csv(data, encoding="utf-8")
- start = datetime.datetime.now().replace(
- hour=0, minute=0, second=0, microsecond=0
- )
- pdf["datetime"] = [
- start + datetime.timedelta(hours=i * 24 / (len(pdf) - 1))
- for i in range(len(pdf))
- ]
- pdf["occupancy"] = [random.randint(1, 6) for _ in range(len(pdf))]
- pdf["radius_miles"] = [random.uniform(1, 3) for _ in range(len(pdf))]
- pdf["geohash"] = pdf[["LAT", "LON"]].apply(lambda x: geohash.encode(*x), axis=1)
- pdf["delimited"] = pdf["LAT"].map(str).str.cat(pdf["LON"].map(str), sep=",")
- pdf.to_sql( # pylint: disable=no-member
- tbl_name,
- database.get_sqla_engine(),
- if_exists="replace",
- chunksize=500,
- dtype={
- "longitude": Float(),
- "latitude": Float(),
- "number": Float(),
- "street": String(100),
- "unit": String(10),
- "city": String(50),
- "district": String(50),
- "region": String(50),
- "postcode": Float(),
- "id": String(100),
- "datetime": DateTime(),
- "occupancy": Float(),
- "radius_miles": Float(),
- "geohash": String(12),
- "delimited": String(60),
- },
- index=False,
- )
- print("Done loading table!")
- print("-" * 80)
- print("Creating table reference")
- obj = db.session.query(TBL).filter_by(table_name=tbl_name).first()
- if not obj:
- obj = TBL(table_name=tbl_name)
- obj.main_dttm_col = "datetime"
- obj.database = database
- db.session.merge(obj)
- db.session.commit()
- obj.fetch_metadata()
- tbl = obj
- slice_data = {
- "granularity_sqla": "day",
- "since": "2014-01-01",
- "until": "now",
- "viz_type": "mapbox",
- "all_columns_x": "LON",
- "all_columns_y": "LAT",
- "mapbox_style": "mapbox://styles/mapbox/light-v9",
- "all_columns": ["occupancy"],
- "row_limit": 500000,
- }
- print("Creating a slice")
- slc = Slice(
- slice_name="Mapbox Long/Lat",
- viz_type="mapbox",
- datasource_type="table",
- datasource_id=tbl.id,
- params=get_slice_json(slice_data),
- )
- misc_dash_slices.add(slc.slice_name)
- merge_slice(slc)
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