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>
111 lines
4.2 KiB
Python
111 lines
4.2 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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import py4j
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from pyspark.ml.image import ImageSchema
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from pyspark.testing.mlutils import PySparkTestCase, SparkSessionTestCase
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from pyspark.sql import HiveContext, Row
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from pyspark.testing.utils import QuietTest
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class ImageReaderTest(SparkSessionTestCase):
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def test_read_images(self):
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data_path = 'data/mllib/images/origin/kittens'
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df = ImageSchema.readImages(data_path, recursive=True, dropImageFailures=True)
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self.assertEqual(df.count(), 4)
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first_row = df.take(1)[0][0]
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array = ImageSchema.toNDArray(first_row)
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self.assertEqual(len(array), first_row[1])
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self.assertEqual(ImageSchema.toImage(array, origin=first_row[0]), first_row)
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self.assertEqual(df.schema, ImageSchema.imageSchema)
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self.assertEqual(df.schema["image"].dataType, ImageSchema.columnSchema)
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expected = {'CV_8UC3': 16, 'Undefined': -1, 'CV_8U': 0, 'CV_8UC1': 0, 'CV_8UC4': 24}
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self.assertEqual(ImageSchema.ocvTypes, expected)
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expected = ['origin', 'height', 'width', 'nChannels', 'mode', 'data']
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self.assertEqual(ImageSchema.imageFields, expected)
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self.assertEqual(ImageSchema.undefinedImageType, "Undefined")
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with QuietTest(self.sc):
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self.assertRaisesRegexp(
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TypeError,
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"image argument should be pyspark.sql.types.Row; however",
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lambda: ImageSchema.toNDArray("a"))
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with QuietTest(self.sc):
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self.assertRaisesRegexp(
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ValueError,
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"image argument should have attributes specified in",
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lambda: ImageSchema.toNDArray(Row(a=1)))
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with QuietTest(self.sc):
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self.assertRaisesRegexp(
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TypeError,
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"array argument should be numpy.ndarray; however, it got",
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lambda: ImageSchema.toImage("a"))
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class ImageReaderTest2(PySparkTestCase):
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@classmethod
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def setUpClass(cls):
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super(ImageReaderTest2, cls).setUpClass()
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cls.hive_available = True
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# Note that here we enable Hive's support.
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cls.spark = None
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try:
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cls.sc._jvm.org.apache.hadoop.hive.conf.HiveConf()
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except py4j.protocol.Py4JError:
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cls.tearDownClass()
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cls.hive_available = False
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except TypeError:
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cls.tearDownClass()
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cls.hive_available = False
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if cls.hive_available:
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cls.spark = HiveContext._createForTesting(cls.sc)
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def setUp(self):
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if not self.hive_available:
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self.skipTest("Hive is not available.")
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@classmethod
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def tearDownClass(cls):
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super(ImageReaderTest2, cls).tearDownClass()
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if cls.spark is not None:
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cls.spark.sparkSession.stop()
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cls.spark = None
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def test_read_images_multiple_times(self):
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# This test case is to check if `ImageSchema.readImages` tries to
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# initiate Hive client multiple times. See SPARK-22651.
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data_path = 'data/mllib/images/origin/kittens'
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ImageSchema.readImages(data_path, recursive=True, dropImageFailures=True)
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ImageSchema.readImages(data_path, recursive=True, dropImageFailures=True)
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if __name__ == "__main__":
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from pyspark.ml.tests.test_image 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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