mirror of https://github.com/apache/superset.git
251 lines
9.7 KiB
Python
251 lines
9.7 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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# isort:skip_file
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from datetime import datetime
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import tests.integration_tests.test_app
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from superset.dataframe import df_to_records
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from superset.db_engine_specs import BaseEngineSpec
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from superset.result_set import dedup, SupersetResultSet
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from .base_tests import SupersetTestCase
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class TestSupersetResultSet(SupersetTestCase):
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def test_dedup(self):
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self.assertEqual(dedup(["foo", "bar"]), ["foo", "bar"])
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self.assertEqual(
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dedup(["foo", "bar", "foo", "bar", "Foo"]),
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["foo", "bar", "foo__1", "bar__1", "Foo"],
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)
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self.assertEqual(
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dedup(["foo", "bar", "bar", "bar", "Bar"]),
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["foo", "bar", "bar__1", "bar__2", "Bar"],
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)
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self.assertEqual(
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dedup(["foo", "bar", "bar", "bar", "Bar"], case_sensitive=False),
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["foo", "bar", "bar__1", "bar__2", "Bar__3"],
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)
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def test_get_columns_basic(self):
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data = [("a1", "b1", "c1"), ("a2", "b2", "c2")]
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cursor_descr = (("a", "string"), ("b", "string"), ("c", "string"))
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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self.assertEqual(
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results.columns,
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[
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{"is_date": False, "type": "STRING", "name": "a"},
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{"is_date": False, "type": "STRING", "name": "b"},
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{"is_date": False, "type": "STRING", "name": "c"},
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],
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)
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def test_get_columns_with_int(self):
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data = [("a1", 1), ("a2", 2)]
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cursor_descr = (("a", "string"), ("b", "int"))
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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self.assertEqual(
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results.columns,
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[
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{"is_date": False, "type": "STRING", "name": "a"},
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{"is_date": False, "type": "INT", "name": "b"},
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],
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)
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def test_get_columns_type_inference(self):
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data = [
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(1.2, 1, "foo", datetime(2018, 10, 19, 23, 39, 16, 660000), True),
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(3.14, 2, "bar", datetime(2019, 10, 19, 23, 39, 16, 660000), False),
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]
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cursor_descr = (("a", None), ("b", None), ("c", None), ("d", None), ("e", None))
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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self.assertEqual(
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results.columns,
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[
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{"is_date": False, "type": "FLOAT", "name": "a"},
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{"is_date": False, "type": "INT", "name": "b"},
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{"is_date": False, "type": "STRING", "name": "c"},
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{"is_date": True, "type": "DATETIME", "name": "d"},
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{"is_date": False, "type": "BOOL", "name": "e"},
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],
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)
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def test_is_date(self):
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data = [("a", 1), ("a", 2)]
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cursor_descr = (("a", "string"), ("a", "string"))
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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self.assertEqual(results.is_temporal("DATE"), True)
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self.assertEqual(results.is_temporal("DATETIME"), True)
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self.assertEqual(results.is_temporal("TIME"), True)
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self.assertEqual(results.is_temporal("TIMESTAMP"), True)
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self.assertEqual(results.is_temporal("STRING"), False)
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self.assertEqual(results.is_temporal(""), False)
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self.assertEqual(results.is_temporal(None), False)
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def test_dedup_with_data(self):
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data = [("a", 1), ("a", 2)]
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cursor_descr = (("a", "string"), ("a", "string"))
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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column_names = [col["name"] for col in results.columns]
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self.assertListEqual(column_names, ["a", "a__1"])
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def test_int64_with_missing_data(self):
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data = [(None,), (1239162456494753670,), (None,), (None,), (None,), (None,)]
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cursor_descr = [("user_id", "bigint", None, None, None, None, True)]
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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self.assertEqual(results.columns[0]["type"], "BIGINT")
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def test_data_as_list_of_lists(self):
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data = [[1, "a"], [2, "b"]]
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cursor_descr = [
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("user_id", "INT", None, None, None, None, True),
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("username", "STRING", None, None, None, None, True),
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]
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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df = results.to_pandas_df()
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self.assertEqual(
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df_to_records(df),
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[{"user_id": 1, "username": "a"}, {"user_id": 2, "username": "b"}],
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)
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def test_nullable_bool(self):
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data = [(None,), (True,), (None,), (None,), (None,), (None,)]
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cursor_descr = [("is_test", "bool", None, None, None, None, True)]
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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self.assertEqual(results.columns[0]["type"], "BOOL")
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df = results.to_pandas_df()
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self.assertEqual(
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df_to_records(df),
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[
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{"is_test": None},
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{"is_test": True},
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{"is_test": None},
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{"is_test": None},
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{"is_test": None},
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{"is_test": None},
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],
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)
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def test_nested_types(self):
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data = [
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(
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4,
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[{"table_name": "unicode_test", "database_id": 1}],
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[1, 2, 3],
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{"chart_name": "scatter"},
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),
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(
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3,
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[{"table_name": "birth_names", "database_id": 1}],
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[4, 5, 6],
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{"chart_name": "plot"},
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),
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]
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cursor_descr = [("id",), ("dict_arr",), ("num_arr",), ("map_col",)]
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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self.assertEqual(results.columns[0]["type"], "INT")
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self.assertEqual(results.columns[1]["type"], "STRING")
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self.assertEqual(results.columns[2]["type"], "STRING")
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self.assertEqual(results.columns[3]["type"], "STRING")
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df = results.to_pandas_df()
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self.assertEqual(
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df_to_records(df),
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[
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{
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"id": 4,
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"dict_arr": '[{"table_name": "unicode_test", "database_id": 1}]',
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"num_arr": "[1, 2, 3]",
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"map_col": '{"chart_name": "scatter"}',
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},
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{
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"id": 3,
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"dict_arr": '[{"table_name": "birth_names", "database_id": 1}]',
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"num_arr": "[4, 5, 6]",
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"map_col": '{"chart_name": "plot"}',
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},
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],
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)
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def test_single_column_multidim_nested_types(self):
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data = [
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(
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[
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"test",
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[
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[
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"foo",
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123456,
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[
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[["test"], 3432546, 7657658766],
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[["fake"], 656756765, 324324324324],
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],
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]
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],
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["test2", 43, 765765765],
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None,
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None,
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],
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)
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]
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cursor_descr = [("metadata",)]
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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self.assertEqual(results.columns[0]["type"], "STRING")
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df = results.to_pandas_df()
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self.assertEqual(
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df_to_records(df),
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[
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{
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"metadata": '["test", [["foo", 123456, [[["test"], 3432546, 7657658766], [["fake"], 656756765, 324324324324]]]], ["test2", 43, 765765765], null, null]'
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}
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],
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)
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def test_nested_list_types(self):
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data = [([{"TestKey": [123456, "foo"]}],)]
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cursor_descr = [("metadata",)]
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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self.assertEqual(results.columns[0]["type"], "STRING")
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df = results.to_pandas_df()
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self.assertEqual(
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df_to_records(df), [{"metadata": '[{"TestKey": [123456, "foo"]}]'}]
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)
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def test_empty_datetime(self):
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data = [(None,)]
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cursor_descr = [("ds", "timestamp", None, None, None, None, True)]
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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self.assertEqual(results.columns[0]["type"], "TIMESTAMP")
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def test_no_type_coercion(self):
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data = [("a", 1), ("b", 2)]
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cursor_descr = [
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("one", "varchar", None, None, None, None, True),
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("two", "int", None, None, None, None, True),
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]
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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self.assertEqual(results.columns[0]["type"], "VARCHAR")
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self.assertEqual(results.columns[1]["type"], "INT")
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def test_empty_data(self):
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data = []
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cursor_descr = [
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("emptyone", "varchar", None, None, None, None, True),
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("emptytwo", "int", None, None, None, None, True),
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]
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results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
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self.assertEqual(results.columns, [])
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