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test_datetime_ops.py
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test_datetime_ops.py
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#
# 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 datetime
import numpy as np
import pandas as pd
from pandas.api.types import CategoricalDtype
from pyspark import pandas as ps
from pyspark.pandas.config import option_context
from pyspark.pandas.tests.data_type_ops.testing_utils import TestCasesUtils
from pyspark.testing.pandasutils import PandasOnSparkTestCase
class DatetimeOpsTest(PandasOnSparkTestCase, TestCasesUtils):
@property
def pser(self):
return pd.Series(pd.date_range("1994-1-31 10:30:15", periods=3, freq="M"))
@property
def psser(self):
return ps.from_pandas(self.pser)
@property
def some_datetime(self):
return datetime.datetime(1994, 1, 31, 10, 30, 00)
def test_add(self):
self.assertRaises(TypeError, lambda: self.psser + "x")
self.assertRaises(TypeError, lambda: self.psser + 1)
self.assertRaises(TypeError, lambda: self.psser + self.some_datetime)
with option_context("compute.ops_on_diff_frames", True):
for psser in self.pssers:
self.assertRaises(TypeError, lambda: self.psser + psser)
def test_sub(self):
self.assertRaises(TypeError, lambda: self.psser - "x")
self.assertRaises(TypeError, lambda: self.psser - 1)
self.assert_eq(
(self.pser - self.some_datetime).dt.total_seconds().astype("int"),
self.psser - self.some_datetime,
)
with option_context("compute.ops_on_diff_frames", True):
for pser, psser in self.pser_psser_pairs:
if pser.dtype == np.dtype("<M8[ns]"):
self.assert_eq(
(self.pser - pser).dt.total_seconds().astype("int"),
(self.psser - psser).sort_index(),
)
else:
self.assertRaises(TypeError, lambda: self.psser - psser)
def test_mul(self):
self.assertRaises(TypeError, lambda: self.psser * "x")
self.assertRaises(TypeError, lambda: self.psser * 1)
self.assertRaises(TypeError, lambda: self.psser * self.some_datetime)
with option_context("compute.ops_on_diff_frames", True):
for psser in self.pssers:
self.assertRaises(TypeError, lambda: self.psser * psser)
def test_truediv(self):
self.assertRaises(TypeError, lambda: self.psser / "x")
self.assertRaises(TypeError, lambda: self.psser / 1)
self.assertRaises(TypeError, lambda: self.psser / self.some_datetime)
with option_context("compute.ops_on_diff_frames", True):
for psser in self.pssers:
self.assertRaises(TypeError, lambda: self.psser / psser)
def test_floordiv(self):
self.assertRaises(TypeError, lambda: self.psser // "x")
self.assertRaises(TypeError, lambda: self.psser // 1)
self.assertRaises(TypeError, lambda: self.psser // self.some_datetime)
with option_context("compute.ops_on_diff_frames", True):
for psser in self.pssers:
self.assertRaises(TypeError, lambda: self.psser // psser)
def test_mod(self):
self.assertRaises(TypeError, lambda: self.psser % "x")
self.assertRaises(TypeError, lambda: self.psser % 1)
self.assertRaises(TypeError, lambda: self.psser % self.some_datetime)
with option_context("compute.ops_on_diff_frames", True):
for psser in self.pssers:
self.assertRaises(TypeError, lambda: self.psser % psser)
def test_pow(self):
self.assertRaises(TypeError, lambda: self.psser ** "x")
self.assertRaises(TypeError, lambda: self.psser ** 1)
self.assertRaises(TypeError, lambda: self.psser ** self.some_datetime)
with option_context("compute.ops_on_diff_frames", True):
for psser in self.pssers:
self.assertRaises(TypeError, lambda: self.psser ** psser)
def test_radd(self):
self.assertRaises(TypeError, lambda: "x" + self.psser)
self.assertRaises(TypeError, lambda: 1 + self.psser)
self.assertRaises(TypeError, lambda: self.some_datetime + self.psser)
def test_rsub(self):
self.assertRaises(TypeError, lambda: "x" - self.psser)
self.assertRaises(TypeError, lambda: 1 - self.psser)
self.assert_eq(
(self.some_datetime - self.pser).dt.total_seconds().astype("int"),
self.some_datetime - self.psser,
)
def test_rmul(self):
self.assertRaises(TypeError, lambda: "x" * self.psser)
self.assertRaises(TypeError, lambda: 1 * self.psser)
self.assertRaises(TypeError, lambda: self.some_datetime * self.psser)
def test_rtruediv(self):
self.assertRaises(TypeError, lambda: "x" / self.psser)
self.assertRaises(TypeError, lambda: 1 / self.psser)
self.assertRaises(TypeError, lambda: self.some_datetime / self.psser)
def test_rfloordiv(self):
self.assertRaises(TypeError, lambda: "x" // self.psser)
self.assertRaises(TypeError, lambda: 1 // self.psser)
self.assertRaises(TypeError, lambda: self.some_datetime // self.psser)
def test_rmod(self):
self.assertRaises(TypeError, lambda: 1 % self.psser)
self.assertRaises(TypeError, lambda: self.some_datetime % self.psser)
def test_rpow(self):
self.assertRaises(TypeError, lambda: "x" ** self.psser)
self.assertRaises(TypeError, lambda: 1 ** self.psser)
self.assertRaises(TypeError, lambda: self.some_datetime ** self.psser)
def test_and(self):
self.assertRaises(TypeError, lambda: self.psser & True)
self.assertRaises(TypeError, lambda: self.psser & False)
self.assertRaises(TypeError, lambda: self.psser & self.psser)
def test_rand(self):
self.assertRaises(TypeError, lambda: True & self.psser)
self.assertRaises(TypeError, lambda: False & self.psser)
def test_or(self):
self.assertRaises(TypeError, lambda: self.psser | True)
self.assertRaises(TypeError, lambda: self.psser | False)
self.assertRaises(TypeError, lambda: self.psser | self.psser)
def test_ror(self):
self.assertRaises(TypeError, lambda: True | self.psser)
self.assertRaises(TypeError, lambda: False | self.psser)
def test_from_to_pandas(self):
data = pd.date_range("1994-1-31 10:30:15", periods=3, freq="M")
pser = pd.Series(data)
psser = ps.Series(data)
self.assert_eq(pser, psser.to_pandas())
self.assert_eq(ps.from_pandas(pser), psser)
def test_isnull(self):
self.assert_eq(self.pser.isnull(), self.psser.isnull())
def test_astype(self):
pser = self.pser
psser = self.psser
self.assert_eq(pser.astype(str), psser.astype(str))
self.assert_eq(pser.astype("category"), psser.astype("category"))
cat_type = CategoricalDtype(categories=["a", "b", "c"])
self.assert_eq(pser.astype(cat_type), psser.astype(cat_type))
if __name__ == "__main__":
import unittest
from pyspark.pandas.tests.data_type_ops.test_datetime_ops import * # noqa: F401
try:
import xmlrunner # type: ignore[import]
testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2)
except ImportError:
testRunner = None
unittest.main(testRunner=testRunner, verbosity=2)