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206# 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.
# pylint: disable=unused-argument, import-outside-toplevel
from datetime import datetime
import pytest
from pandas import Timestamp
from pandas._libs.tslibs import NaT
from superset.dataframe import df_to_records
from superset.superset_typing import DbapiDescription
def test_df_to_records() -> None:
from superset.db_engine_specs import BaseEngineSpec
from superset.result_set import SupersetResultSet
data = [("a1", "b1", "c1"), ("a2", "b2", "c2")]
cursor_descr: DbapiDescription = [
(column, "string", None, None, None, None, False) for column in ("a", "b", "c")
]
results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
df = results.to_pandas_df()
assert df_to_records(df) == [
{"a": "a1", "b": "b1", "c": "c1"},
{"a": "a2", "b": "b2", "c": "c2"},
]
def test_df_to_records_NaT_type() -> None: # noqa: N802
from superset.db_engine_specs import BaseEngineSpec
from superset.result_set import SupersetResultSet
data = [(NaT,), (Timestamp("2023-01-06 20:50:31.749000+0000", tz="UTC"),)]
cursor_descr: DbapiDescription = [
("date", "timestamp with time zone", None, None, None, None, False)
]
results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
df = results.to_pandas_df()
assert df_to_records(df) == [
{"date": None},
{"date": "2023-01-06 20:50:31.749000+00:00"},
]
def test_df_to_records_mixed_emoji_type() -> None:
from superset.db_engine_specs import BaseEngineSpec
from superset.result_set import SupersetResultSet
data = [
("What's up?", "This is a string text", 1),
("What's up?", "This is a string with an 😍 added", 2),
("What's up?", NaT, 3),
("What's up?", "Last emoji 😁", 4),
]
cursor_descr: DbapiDescription = [
("question", "varchar", None, None, None, None, False),
("response", "varchar", None, None, None, None, False),
("count", "integer", None, None, None, None, False),
]
results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
df = results.to_pandas_df()
assert df_to_records(df) == [
{"question": "What's up?", "response": "This is a string text", "count": 1},
{
"question": "What's up?",
"response": "This is a string with an 😍 added",
"count": 2,
},
{
"question": "What's up?",
"response": None,
"count": 3,
},
{
"question": "What's up?",
"response": "Last emoji 😁",
"count": 4,
},
]
def test_df_to_records_mixed_accent_type() -> None:
from superset.db_engine_specs import BaseEngineSpec
from superset.result_set import SupersetResultSet
data = [
("What's up?", "This is a string text", 1),
("What's up?", "This is a string with áccent", 2),
("What's up?", NaT, 3),
("What's up?", "móre áccent", 4),
]
cursor_descr: DbapiDescription = [
("question", "varchar", None, None, None, None, False),
("response", "varchar", None, None, None, None, False),
("count", "integer", None, None, None, None, False),
]
results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
df = results.to_pandas_df()
assert df_to_records(df) == [
{"question": "What's up?", "response": "This is a string text", "count": 1},
{
"question": "What's up?",
"response": "This is a string with áccent",
"count": 2,
},
{
"question": "What's up?",
"response": None,
"count": 3,
},
{
"question": "What's up?",
"response": "móre áccent",
"count": 4,
},
]
def test_js_max_int() -> None:
from superset.db_engine_specs import BaseEngineSpec
from superset.result_set import SupersetResultSet
data = [(1, 1239162456494753670, "c1"), (2, 100, "c2")]
cursor_descr: DbapiDescription = [
("a", "int", None, None, None, None, False),
("b", "int", None, None, None, None, False),
("c", "string", None, None, None, None, False),
]
results = SupersetResultSet(data, cursor_descr, BaseEngineSpec)
df = results.to_pandas_df()
assert df_to_records(df) == [
{"a": 1, "b": "1239162456494753670", "c": "c1"},
{"a": 2, "b": 100, "c": "c2"},
]
@pytest.mark.parametrize(
"input_, expected",
[
pytest.param(
[
(datetime.strptime("1677-09-22 00:12:43", "%Y-%m-%d %H:%M:%S"), 1),
(datetime.strptime("2262-04-11 23:47:17", "%Y-%m-%d %H:%M:%S"), 2),
],
[
{
"a": datetime.strptime("1677-09-22 00:12:43", "%Y-%m-%d %H:%M:%S"),
"b": 1,
},
{
"a": datetime.strptime("2262-04-11 23:47:17", "%Y-%m-%d %H:%M:%S"),
"b": 2,
},
],
id="timestamp conversion fail",
),
pytest.param(
[
(datetime.strptime("1677-09-22 00:12:44", "%Y-%m-%d %H:%M:%S"), 1),
(datetime.strptime("2262-04-11 23:47:16", "%Y-%m-%d %H:%M:%S"), 2),
],
[
{"a": Timestamp("1677-09-22 00:12:44"), "b": 1},
{"a": Timestamp("2262-04-11 23:47:16"), "b": 2},
],
id="timestamp conversion success",
),
],
)
def test_max_pandas_timestamp(input_, expected) -> None:
from superset.db_engine_specs import BaseEngineSpec
from superset.result_set import SupersetResultSet
cursor_descr: DbapiDescription = [
("a", "datetime", None, None, None, None, False),
("b", "int", None, None, None, None, False),
]
results = SupersetResultSet(input_, cursor_descr, BaseEngineSpec)
df = results.to_pandas_df()
assert df_to_records(df) == expected