bbbdaa82a4
## What changes were proposed in this pull request?
Currently, some of PySpark tests sill assume the tests could be ran in Python 2.6 by importing `unittest2`. For instance:
```python
if sys.version_info[:2] <= (2, 6):
try:
import unittest2 as unittest
except ImportError:
sys.stderr.write('Please install unittest2 to test with Python 2.6 or earlier')
sys.exit(1)
else:
import unittest
```
While I am here, I removed some of unused imports and reordered imports per PEP 8.
We officially dropped Python 2.6 support a while ago and started to discuss about Python 2 drop. It's better to remove them out.
## How was this patch tested?
Manually tests, and existing tests via Jenkins.
Closes #23077 from HyukjinKwon/SPARK-26105.
Lead-authored-by: hyukjinkwon <gurwls223@apache.org>
Co-authored-by: Bryan Cutler <cutlerb@gmail.com>
Signed-off-by: hyukjinkwon <gurwls223@apache.org>
70 lines
3 KiB
Python
70 lines
3 KiB
Python
#
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# Licensed to the Apache Software Foundation (ASF) under one or more
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# contributor license agreements. See the NOTICE file distributed with
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# this work for additional information regarding copyright ownership.
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# The ASF licenses this file to You under the Apache License, Version 2.0
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# (the "License"); you may not use this file except in compliance with
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# 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, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import unittest
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from pyspark.ml.pipeline import Pipeline
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from pyspark.testing.mlutils import MockDataset, MockEstimator, MockTransformer, PySparkTestCase
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class PipelineTests(PySparkTestCase):
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def test_pipeline(self):
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dataset = MockDataset()
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estimator0 = MockEstimator()
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transformer1 = MockTransformer()
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estimator2 = MockEstimator()
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transformer3 = MockTransformer()
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pipeline = Pipeline(stages=[estimator0, transformer1, estimator2, transformer3])
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pipeline_model = pipeline.fit(dataset, {estimator0.fake: 0, transformer1.fake: 1})
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model0, transformer1, model2, transformer3 = pipeline_model.stages
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self.assertEqual(0, model0.dataset_index)
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self.assertEqual(0, model0.getFake())
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self.assertEqual(1, transformer1.dataset_index)
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self.assertEqual(1, transformer1.getFake())
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self.assertEqual(2, dataset.index)
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self.assertIsNone(model2.dataset_index, "The last model shouldn't be called in fit.")
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self.assertIsNone(transformer3.dataset_index,
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"The last transformer shouldn't be called in fit.")
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dataset = pipeline_model.transform(dataset)
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self.assertEqual(2, model0.dataset_index)
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self.assertEqual(3, transformer1.dataset_index)
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self.assertEqual(4, model2.dataset_index)
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self.assertEqual(5, transformer3.dataset_index)
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self.assertEqual(6, dataset.index)
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def test_identity_pipeline(self):
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dataset = MockDataset()
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def doTransform(pipeline):
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pipeline_model = pipeline.fit(dataset)
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return pipeline_model.transform(dataset)
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# check that empty pipeline did not perform any transformation
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self.assertEqual(dataset.index, doTransform(Pipeline(stages=[])).index)
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# check that failure to set stages param will raise KeyError for missing param
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self.assertRaises(KeyError, lambda: doTransform(Pipeline()))
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if __name__ == "__main__":
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from pyspark.ml.tests.test_pipeline import *
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try:
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import xmlrunner
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testRunner = xmlrunner.XMLTestRunner(output='target/test-reports')
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except ImportError:
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testRunner = None
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unittest.main(testRunner=testRunner, verbosity=2)
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