superset flights 源码
superset flights 代码
文件路径：/superset/examples/flights.py
# 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()
engine = database.get_sqla_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!")
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