mirror of
https://github.com/apache/superset.git
synced 2026-04-12 12:47:53 +00:00
1fbce88a46
* fix: set correct schema on config import * Fix lint * Fix test * Fix tests * Fix another test * Fix another test * Fix base test * Add helper function * Fix examples * Fix test * Fix test * Fixing more tests
97 lines
3.1 KiB
Python
97 lines
3.1 KiB
Python
# 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, String
|
|
|
|
from superset import app, db
|
|
from superset.models.slice import Slice
|
|
from superset.utils import core as utils
|
|
|
|
from .helpers import (
|
|
get_example_data,
|
|
get_slice_json,
|
|
get_table_connector_registry,
|
|
merge_slice,
|
|
)
|
|
|
|
|
|
def load_random_time_series_data(
|
|
only_metadata: bool = False, force: bool = False
|
|
) -> None:
|
|
"""Loading random time series data from a zip file in the repo"""
|
|
tbl_name = "random_time_series"
|
|
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):
|
|
data = get_example_data("random_time_series.json.gz")
|
|
pdf = pd.read_json(data)
|
|
if database.backend == "presto":
|
|
pdf.ds = pd.to_datetime(pdf.ds, unit="s")
|
|
pdf.ds = pdf.ds.dt.strftime("%Y-%m-%d %H:%M%:%S")
|
|
else:
|
|
pdf.ds = pd.to_datetime(pdf.ds, unit="s")
|
|
|
|
pdf.to_sql(
|
|
tbl_name,
|
|
engine,
|
|
schema=schema,
|
|
if_exists="replace",
|
|
chunksize=500,
|
|
dtype={"ds": DateTime if database.backend != "presto" else String(255)},
|
|
index=False,
|
|
)
|
|
print("Done loading table!")
|
|
print("-" * 80)
|
|
|
|
print(f"Creating table [{tbl_name}] reference")
|
|
table = get_table_connector_registry()
|
|
obj = db.session.query(table).filter_by(table_name=tbl_name).first()
|
|
if not obj:
|
|
obj = table(table_name=tbl_name, schema=schema)
|
|
obj.main_dttm_col = "ds"
|
|
obj.database = database
|
|
obj.filter_select_enabled = True
|
|
db.session.merge(obj)
|
|
db.session.commit()
|
|
obj.fetch_metadata()
|
|
tbl = obj
|
|
|
|
slice_data = {
|
|
"granularity_sqla": "ds",
|
|
"row_limit": app.config["ROW_LIMIT"],
|
|
"since": "2019-01-01",
|
|
"until": "2019-02-01",
|
|
"metrics": ["count"],
|
|
"viz_type": "cal_heatmap",
|
|
"domain_granularity": "month",
|
|
"subdomain_granularity": "day",
|
|
}
|
|
|
|
print("Creating a slice")
|
|
slc = Slice(
|
|
slice_name="Calendar Heatmap",
|
|
viz_type="cal_heatmap",
|
|
datasource_type="table",
|
|
datasource_id=tbl.id,
|
|
params=get_slice_json(slice_data),
|
|
)
|
|
merge_slice(slc)
|