# # 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 pyspark.pandas.utils import ( lazy_property, validate_arguments_and_invoke_function, validate_bool_kwarg, ) from pyspark.testing.pandasutils import PandasOnSparkTestCase from pyspark.testing.sqlutils import SQLTestUtils some_global_variable = 0 class UtilsTest(PandasOnSparkTestCase, SQLTestUtils): # a dummy to_html version with an extra parameter that pandas does not support # used in test_validate_arguments_and_invoke_function def to_html(self, max_rows=None, unsupported_param=None): args = locals() pdf = pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}, index=[0, 1, 3]) validate_arguments_and_invoke_function(pdf, self.to_html, pd.DataFrame.to_html, args) def to_clipboard(self, sep=",", **kwargs): args = locals() pdf = pd.DataFrame({"a": [1, 2, 3], "b": [4, 5, 6]}, index=[0, 1, 3]) validate_arguments_and_invoke_function( pdf, self.to_clipboard, pd.DataFrame.to_clipboard, args ) # Support for **kwargs self.to_clipboard(sep=",", index=False) def test_validate_arguments_and_invoke_function(self): # This should pass and run fine self.to_html() self.to_html(unsupported_param=None) self.to_html(max_rows=5) # This should fail because we are explicitly setting an unsupported param # to a non-default value with self.assertRaises(TypeError): self.to_html(unsupported_param=1) def test_lazy_property(self): obj = TestClassForLazyProp() # If lazy prop is not working, the second test would fail (because it'd be 2) self.assert_eq(obj.lazy_prop, 1) self.assert_eq(obj.lazy_prop, 1) def test_validate_bool_kwarg(self): # This should pass and run fine pandas_on_spark = True self.assert_eq(validate_bool_kwarg(pandas_on_spark, "pandas_on_spark"), True) pandas_on_spark = False self.assert_eq(validate_bool_kwarg(pandas_on_spark, "pandas_on_spark"), False) pandas_on_spark = None self.assert_eq(validate_bool_kwarg(pandas_on_spark, "pandas_on_spark"), None) # This should fail because we are explicitly setting a non-boolean value pandas_on_spark = "true" with self.assertRaisesRegex( TypeError, 'For argument "pandas_on_spark" expected type bool, received type str.' ): validate_bool_kwarg(pandas_on_spark, "pandas_on_spark") class TestClassForLazyProp: def __init__(self): self.some_variable = 0 @lazy_property def lazy_prop(self): self.some_variable += 1 return self.some_variable if __name__ == "__main__": import unittest from pyspark.pandas.tests.test_utils 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)