31a16fbb40
### What changes were proposed in this pull request? This PR proposes migration of [`pyspark-stubs`](https://github.com/zero323/pyspark-stubs) into Spark codebase. ### Why are the changes needed? ### Does this PR introduce _any_ user-facing change? Yes. This PR adds type annotations directly to Spark source. This can impact interaction with development tools for users, which haven't used `pyspark-stubs`. ### How was this patch tested? - [x] MyPy tests of the PySpark source ``` mypy --no-incremental --config python/mypy.ini python/pyspark ``` - [x] MyPy tests of Spark examples ``` MYPYPATH=python/ mypy --no-incremental --config python/mypy.ini examples/src/main/python/ml examples/src/main/python/sql examples/src/main/python/sql/streaming ``` - [x] Existing Flake8 linter - [x] Existing unit tests Tested against: - `mypy==0.790+dev.e959952d9001e9713d329a2f9b196705b028f894` - `mypy==0.782` Closes #29591 from zero323/SPARK-32681. Authored-by: zero323 <mszymkiewicz@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
77 lines
3.2 KiB
Python
77 lines
3.2 KiB
Python
#
|
|
# 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 unittest
|
|
|
|
from pyspark.ml.image import ImageSchema
|
|
from pyspark.testing.mlutils import SparkSessionTestCase
|
|
from pyspark.sql import Row
|
|
from pyspark.testing.utils import QuietTest
|
|
|
|
|
|
class ImageFileFormatTest(SparkSessionTestCase):
|
|
|
|
def test_read_images(self):
|
|
data_path = 'data/mllib/images/origin/kittens'
|
|
df = self.spark.read.format("image") \
|
|
.option("dropInvalid", True) \
|
|
.option("recursiveFileLookup", True) \
|
|
.load(data_path)
|
|
self.assertEqual(df.count(), 4)
|
|
first_row = df.take(1)[0][0]
|
|
# compare `schema.simpleString()` instead of directly compare schema,
|
|
# because the df loaded from datasouce may change schema column nullability.
|
|
self.assertEqual(df.schema.simpleString(), ImageSchema.imageSchema.simpleString())
|
|
self.assertEqual(df.schema["image"].dataType.simpleString(),
|
|
ImageSchema.columnSchema.simpleString())
|
|
array = ImageSchema.toNDArray(first_row)
|
|
self.assertEqual(len(array), first_row[1])
|
|
self.assertEqual(ImageSchema.toImage(array, origin=first_row[0]), first_row)
|
|
expected = {'CV_8UC3': 16, 'Undefined': -1, 'CV_8U': 0, 'CV_8UC1': 0, 'CV_8UC4': 24}
|
|
self.assertEqual(ImageSchema.ocvTypes, expected)
|
|
expected = ['origin', 'height', 'width', 'nChannels', 'mode', 'data']
|
|
self.assertEqual(ImageSchema.imageFields, expected)
|
|
self.assertEqual(ImageSchema.undefinedImageType, "Undefined")
|
|
|
|
with QuietTest(self.sc):
|
|
self.assertRaisesRegexp(
|
|
TypeError,
|
|
"image argument should be pyspark.sql.types.Row; however",
|
|
lambda: ImageSchema.toNDArray("a"))
|
|
|
|
with QuietTest(self.sc):
|
|
self.assertRaisesRegexp(
|
|
ValueError,
|
|
"image argument should have attributes specified in",
|
|
lambda: ImageSchema.toNDArray(Row(a=1)))
|
|
|
|
with QuietTest(self.sc):
|
|
self.assertRaisesRegexp(
|
|
TypeError,
|
|
"array argument should be numpy.ndarray; however, it got",
|
|
lambda: ImageSchema.toImage("a"))
|
|
|
|
|
|
if __name__ == "__main__":
|
|
from pyspark.ml.tests.test_image 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)
|