# 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 pandas as pd from sqlalchemy import DateTime, inspect import superset.utils.database as database_utils from superset import db from .helpers import get_example_url, get_table_connector_registry def load_flights(only_metadata: bool = False, force: bool = False) -> None: """Loading random time series data from a zip file in the repo""" tbl_name = "flights" database = database_utils.get_example_database() with database.get_sqla_engine_with_context() as engine: schema = inspect(engine).default_schema_name table_exists = database.has_table_by_name(tbl_name) if not only_metadata and (not table_exists or force): flight_data_url = get_example_url("flight_data.csv.gz") pdf = pd.read_csv(flight_data_url, encoding="latin-1", compression="gzip") # Loading airports info to join and get lat/long airports_url = get_example_url("airports.csv.gz") airports = pd.read_csv(airports_url, encoding="latin-1", compression="gzip") airports = airports.set_index("IATA_CODE") pdf[ # pylint: disable=unsupported-assignment-operation,useless-suppression "ds" ] = ( pdf.YEAR.map(str) + "-0" + pdf.MONTH.map(str) + "-0" + pdf.DAY.map(str) ) pdf.ds = pd.to_datetime(pdf.ds) pdf.drop(columns=["DAY", "MONTH", "YEAR"]) pdf = pdf.join(airports, on="ORIGIN_AIRPORT", rsuffix="_ORIG") pdf = pdf.join(airports, on="DESTINATION_AIRPORT", rsuffix="_DEST") pdf.to_sql( tbl_name, engine, schema=schema, if_exists="replace", chunksize=500, dtype={"ds": DateTime}, index=False, ) table = get_table_connector_registry() tbl = db.session.query(table).filter_by(table_name=tbl_name).first() if not tbl: tbl = table(table_name=tbl_name, schema=schema) tbl.description = "Random set of flights in the US" tbl.database = database tbl.filter_select_enabled = True db.session.merge(tbl) db.session.commit() tbl.fetch_metadata() print("Done loading table!")