mirror of
https://github.com/apache/superset.git
synced 2026-07-21 06:05:46 +00:00
116 lines
3.8 KiB
Python
116 lines
3.8 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.
|
|
from datetime import datetime
|
|
|
|
from superset.common.query_object import QueryObject
|
|
|
|
|
|
def test_get_series_limit_prequery_obj():
|
|
"""
|
|
Test get_series_limit_prequery_obj method
|
|
"""
|
|
# Create a QueryObject with series limit settings
|
|
query_object = QueryObject(
|
|
columns=["country", "year"],
|
|
metrics=["sum__sales"],
|
|
series_limit=10,
|
|
from_dttm=datetime(2020, 1, 1),
|
|
to_dttm=datetime(2021, 1, 1),
|
|
filters=[{"col": "region", "op": "IN", "val": ["US", "EU"]}],
|
|
extras={"time_grain_sqla": "P1D"},
|
|
order_desc=False,
|
|
)
|
|
|
|
# Test basic prequery object creation
|
|
prequery_obj = query_object.get_series_limit_prequery_obj(
|
|
granularity="ds",
|
|
inner_from_dttm=None,
|
|
inner_to_dttm=None,
|
|
)
|
|
|
|
assert prequery_obj["is_timeseries"] is False
|
|
assert prequery_obj["row_limit"] == 10
|
|
assert prequery_obj["metrics"] == ["sum__sales"]
|
|
assert prequery_obj["granularity"] == "ds"
|
|
assert prequery_obj["groupby"] == ["country", "year"]
|
|
assert prequery_obj["from_dttm"] == datetime(2020, 1, 1)
|
|
assert prequery_obj["to_dttm"] == datetime(2021, 1, 1)
|
|
assert prequery_obj["filter"] == [
|
|
{"col": "region", "op": "IN", "val": ["US", "EU"]}
|
|
]
|
|
assert prequery_obj["orderby"] == []
|
|
assert prequery_obj["extras"] == {"time_grain_sqla": "P1D"}
|
|
assert prequery_obj["order_desc"] is True # Always True for prequery
|
|
|
|
|
|
def test_get_series_limit_prequery_obj_with_overrides():
|
|
"""
|
|
Test get_series_limit_prequery_obj with inner dates and orderby override
|
|
"""
|
|
query_object = QueryObject(
|
|
columns=["country"],
|
|
metrics=["count"],
|
|
series_limit=5,
|
|
from_dttm=datetime(2020, 1, 1),
|
|
to_dttm=datetime(2021, 1, 1),
|
|
)
|
|
|
|
# Test with inner dates and custom orderby
|
|
inner_from = datetime(2020, 6, 1)
|
|
inner_to = datetime(2020, 12, 31)
|
|
custom_orderby = [("sum__revenue", False)]
|
|
|
|
prequery_obj = query_object.get_series_limit_prequery_obj(
|
|
granularity="date_col",
|
|
inner_from_dttm=inner_from,
|
|
inner_to_dttm=inner_to,
|
|
orderby=custom_orderby,
|
|
)
|
|
|
|
assert prequery_obj["from_dttm"] == inner_from
|
|
assert prequery_obj["to_dttm"] == inner_to
|
|
assert prequery_obj["orderby"] == custom_orderby
|
|
|
|
|
|
def test_get_series_limit_prequery_obj_base_axis_filtering():
|
|
"""
|
|
Test that base axis columns are filtered out in prequery
|
|
"""
|
|
# Mock the x-axis column with proper structure for base axis
|
|
query_object = QueryObject(
|
|
columns=[
|
|
{
|
|
"label": "__timestamp",
|
|
"sqlExpression": "__timestamp",
|
|
"columnType": "BASE_AXIS",
|
|
},
|
|
"country",
|
|
"city",
|
|
],
|
|
metrics=["revenue"],
|
|
series_limit=20,
|
|
)
|
|
|
|
prequery_obj = query_object.get_series_limit_prequery_obj(
|
|
granularity=None,
|
|
inner_from_dttm=None,
|
|
inner_to_dttm=None,
|
|
)
|
|
|
|
# The columns in prequery should exclude the base axis column
|
|
assert prequery_obj["columns"] == ["country", "city"]
|