| # |
| # 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.errors import AnalysisException |
| from pyspark.sql import functions as F |
| from pyspark import pandas as ps |
| from pyspark.testing.pandasutils import PandasOnSparkTestCase |
| from pyspark.testing.sqlutils import SQLTestUtils |
| |
| |
| class SparkIndexOpsMethodsTestsMixin: |
| @property |
| def pser(self): |
| return pd.Series([1, 2, 3, 4, 5, 6, 7], name="x") |
| |
| @property |
| def psser(self): |
| return ps.from_pandas(self.pser) |
| |
| def test_series_transform_negative(self): |
| with self.assertRaisesRegex( |
| ValueError, "The output of the function.* pyspark.sql.Column.*int" |
| ): |
| self.psser.spark.transform(lambda scol: 1) |
| |
| with self.assertRaisesRegex(AnalysisException, ".*UNRESOLVED_COLUMN.*`non-existent`.*"): |
| self.psser.spark.transform(lambda scol: F.col("non-existent")) |
| |
| def test_multiindex_transform_negative(self): |
| with self.assertRaisesRegex( |
| NotImplementedError, "MultiIndex does not support spark.transform yet" |
| ): |
| midx = pd.MultiIndex( |
| [["lama", "cow", "falcon"], ["speed", "weight", "length"]], |
| [[0, 0, 0, 1, 1, 1, 2, 2, 2], [1, 1, 1, 1, 1, 2, 1, 2, 2]], |
| ) |
| s = ps.Series([45, 200, 1.2, 30, 250, 1.5, 320, 1, 0.3], index=midx) |
| s.index.spark.transform(lambda scol: scol) |
| |
| def test_series_apply_negative(self): |
| with self.assertRaisesRegex( |
| ValueError, "The output of the function.* pyspark.sql.Column.*int" |
| ): |
| self.psser.spark.apply(lambda scol: 1) |
| |
| with self.assertRaisesRegex(AnalysisException, ".*UNRESOLVED_COLUMN.*`non-existent`.*"): |
| self.psser.spark.transform(lambda scol: F.col("non-existent")) |
| |
| |
| class SparkIndexOpsMethodsTests( |
| SparkIndexOpsMethodsTestsMixin, PandasOnSparkTestCase, SQLTestUtils |
| ): |
| pass |
| |
| |
| if __name__ == "__main__": |
| import unittest |
| from pyspark.pandas.tests.test_indexops_spark import * # noqa: F401 |
| |
| try: |
| import xmlrunner |
| |
| testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2) |
| except ImportError: |
| testRunner = None |
| unittest.main(testRunner=testRunner, verbosity=2) |