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Posted to github@beam.apache.org by GitBox <gi...@apache.org> on 2022/08/15 17:38:48 UTC
[GitHub] [beam] pabloem opened a new pull request, #22233: Trying out property-based tests for Beam python coders
pabloem opened a new pull request, #22233:
URL: https://github.com/apache/beam/pull/22233
I discovered this little library and decided to try it out to write a couple tests.
We may be able to use it to write some simple x-lang coder tests? : )
For info (and examples) of the library: https://hypothesis.readthedocs.io/en/latest/quickstart.html
fyi: @TheNeuralBit @robertwb
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[GitHub] [beam] pabloem commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1245940612
Run Python PreCommit
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[GitHub] [beam] Abacn commented on a diff in pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
Abacn commented on code in PR #22233:
URL: https://github.com/apache/beam/pull/22233#discussion_r961646234
##########
sdks/python/apache_beam/coders/row_coder.py:
##########
@@ -150,7 +150,9 @@ def _coder_from_type(field_type):
def _nonnull_coder_from_type(field_type):
type_info = field_type.WhichOneof("type_info")
if type_info == "atomic_type":
- if field_type.atomic_type in (schema_pb2.INT32, schema_pb2.INT64):
+ if field_type.atomic_type in (schema_pb2.INT16,
Review Comment:
From #19815 INT16 was encoded in BigEndianShortCoder in Java side but just not implemented in other SDKs. This may cause data corruption. The "Encountered a type that is not currently supported by RowCoder" Exception is currently correctly raised.
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[GitHub] [beam] pabloem commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1245754917
Run Python 3.8 PostCommit
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[GitHub] [beam] TheNeuralBit commented on a diff in pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
TheNeuralBit commented on code in PR #22233:
URL: https://github.com/apache/beam/pull/22233#discussion_r964804914
##########
sdks/python/apache_beam/coders/row_coder.py:
##########
@@ -162,6 +164,8 @@ def _nonnull_coder_from_type(field_type):
return BooleanCoder()
elif field_type.atomic_type == schema_pb2.BYTES:
return BytesCoder()
+ elif field_type.atomic_type == schema_pb2.BYTE:
Review Comment:
Thanks for raising this @Abacn :)
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[GitHub] [beam] pabloem commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1245754699
Run Python PreCommit
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[GitHub] [beam] Abacn commented on a diff in pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
Abacn commented on code in PR #22233:
URL: https://github.com/apache/beam/pull/22233#discussion_r961647096
##########
sdks/python/apache_beam/coders/row_coder.py:
##########
@@ -162,6 +164,8 @@ def _nonnull_coder_from_type(field_type):
return BooleanCoder()
elif field_type.atomic_type == schema_pb2.BYTES:
return BytesCoder()
+ elif field_type.atomic_type == schema_pb2.BYTE:
Review Comment:
Same here (according to #19815)
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[GitHub] [beam] pabloem commented on a diff in pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on code in PR #22233:
URL: https://github.com/apache/beam/pull/22233#discussion_r961859503
##########
sdks/python/apache_beam/coders/row_coder.py:
##########
@@ -162,6 +164,8 @@ def _nonnull_coder_from_type(field_type):
return BooleanCoder()
elif field_type.atomic_type == schema_pb2.BYTES:
return BytesCoder()
+ elif field_type.atomic_type == schema_pb2.BYTE:
Review Comment:
removed. Thanks!
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[GitHub] [beam] pabloem commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1238342025
Run Python 3.8 PostCommit
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[GitHub] [beam] TheNeuralBit commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
TheNeuralBit commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1188215850
Neat! This could be helpful for DataFrame tests too. frames_test.py is loaded with tests that just make sure Beam gets the same result as pandas for a certain operation. These all just have some arbitrary test data, it could catch some issues if we generate the data with hypothesis instead.
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[GitHub] [beam] pabloem commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1235801022
@Abacn ptal? : )
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[GitHub] [beam] pabloem commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1245772181
Run Python PreCommit
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[GitHub] [beam] pabloem commented on a diff in pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on code in PR #22233:
URL: https://github.com/apache/beam/pull/22233#discussion_r961312211
##########
sdks/python/apache_beam/coders/coders_property_based_test.py:
##########
@@ -0,0 +1,138 @@
+#
+# 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.
+#
+
+"""Property tests for coders in the Python SDK.
+
+The tests in this file utilize the hypothesis library to generate random test
+cases and run them against Beam's coder implementations.
+
+These tests are similar to fuzzing, except they test invariant properties
+of code.
+"""
+
+import math
+import typing
+import unittest
+# TODO(pabloem): Include other categories of characters
+from datetime import datetime
+from string import ascii_letters
+from string import digits
+
+import numpy as np
+from hypothesis import strategies as st
+from hypothesis import assume
+from hypothesis import given
+from hypothesis import settings
+from pytz import utc
+
+from apache_beam.coders import FloatCoder
+from apache_beam.coders import RowCoder
+from apache_beam.coders import StrUtf8Coder
+from apache_beam.coders.typecoders import registry as coders_registry
+from apache_beam.typehints.schemas import typing_to_runner_api
+from apache_beam.utils.timestamp import Timestamp
+
+SCHEMA_TYPES = [str, bytes, Timestamp, int, np.int32, np.int64, bool]
+
+SCHEMA_TYPES_TO_STRATEGY = {
+ str: st.text(),
+ bytes: st.binary(),
+ # Maximum datetime on year 3000 to conform to Windows OS limits.
+ Timestamp: st.datetimes(
+ min_value=datetime(1970, 1, 1, 1, 1),
+ max_value=datetime(
+ 3000, 1, 1, 0,
+ 0)).map(lambda dt: Timestamp.from_utc_datetime(dt.astimezone(utc))),
+ int: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.int32: st.integers(min_value=-(1 << 31 - 1), max_value=1 << 31 - 1),
+ np.int64: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.uint32: st.integers(min_value=0, max_value=1 << 32 - 1),
+ np.uint64: st.integers(min_value=0, max_value=1 << 64 - 1),
+ bool: st.booleans()
+}
+
+# A hypothesis strategy that generates schemas.
+# A schema is a list containing tuples of strings (field names), types (field
+# types) and boolean (nullable or not).
+# This strategy currently generates rows with simple types (i.e. non-list, and
+# non-map fields).
+SCHEMA_GENERATOR_STRATEGY = st.lists(
+ st.tuples(
+ st.text(ascii_letters + digits + '_', min_size=1),
+ st.sampled_from(SCHEMA_TYPES),
+ st.booleans()))
+
+
+class ProperyTestingCoders(unittest.TestCase):
+ @given(st.text())
+ def test_string_coder(self, txt: str):
+ coder = StrUtf8Coder()
+ self.assertEqual(coder.decode(coder.encode(txt)), txt)
+
+ @given(st.floats())
+ def test_float_coder(self, num: float):
+ coder = FloatCoder()
+ test_num = coder.decode(coder.encode(num))
+ if math.isnan(num):
+ # This special branch is needed because by definition
+ # nan != nan.
+ self.assertTrue(math.isnan(test_num))
+ else:
+ self.assertEqual(coder.decode(coder.encode(num)), num)
+
+ @settings(deadline=None, print_blob=True)
+ @given(st.data())
+ def test_row_coder(self, data: st.DataObject):
+ """Generate rows and schemas, and test their encoding/decoding.
+
+ The schemas are generated based on the SCHEMA_GENERATOR_STRATEGY.
+ """
+ schema = data.draw(SCHEMA_GENERATOR_STRATEGY)
+ # Assume that the cardinality of the set of names is the same
+ # as the length of the schema. This means there's no duplicate
+ # names for fields.
+ # If this condition does not hold, then we must not continue the
+ # test.
+ assume(len({name for name, _, _ in schema}) == len(schema))
+ assume(
+ len({n[0]
+ for n, _, _ in schema}.intersection(set(digits + '_'))) == 0)
+ RowType = typing.NamedTuple( # type: ignore
+ 'RandomRowType',
+ [(name, type_ if not nullable else typing.Optional[type_]) for name,
+ type_,
+ nullable in schema])
Review Comment:
added to the above issue.
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[GitHub] [beam] pabloem commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1235099212
Run Python 3.8 PostCommit
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[GitHub] [beam] pabloem commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1246019173
thanks y'all
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[GitHub] [beam] pabloem commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1238341819
I've removed changes to RowCoder. I'll merge after tests pass now. Thanks y'all.
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[GitHub] [beam] github-actions[bot] commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
github-actions[bot] commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1181517205
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[GitHub] [beam] pabloem closed pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem closed pull request #22233: Trying out property-based tests for Beam python coders
URL: https://github.com/apache/beam/pull/22233
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[GitHub] [beam] codecov[bot] commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
codecov[bot] commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1215618540
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```diff
@@ Coverage Diff @@
## master #22233 +/- ##
==========================================
- Coverage 74.25% 74.24% -0.01%
==========================================
Files 702 705 +3
Lines 92961 93267 +306
==========================================
+ Hits 69028 69250 +222
- Misses 22666 22750 +84
Partials 1267 1267
```
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|---|---|---|
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[GitHub] [beam] Abacn commented on a diff in pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
Abacn commented on code in PR #22233:
URL: https://github.com/apache/beam/pull/22233#discussion_r961935382
##########
sdks/python/apache_beam/coders/row_coder.py:
##########
@@ -162,6 +164,8 @@ def _nonnull_coder_from_type(field_type):
return BooleanCoder()
elif field_type.atomic_type == schema_pb2.BYTES:
return BytesCoder()
+ elif field_type.atomic_type == schema_pb2.BYTE:
Review Comment:
@pabloem commented here
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[GitHub] [beam] pabloem commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1235098917
note @TheNeuralBit that I added a few things to RowCoder
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[GitHub] [beam] pabloem commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1182555838
Example of the sort of failures that these tests will find:
```
dt = datetime.datetime(3002, 1, 1, 0, 0)
> lambda dt: Timestamp.from_utc_datetime(dt.astimezone(utc))),
int: st.integers(min_value=-(1 << 64 - 1), max_value=1 << 64 - 1),
np.int32: st.integers(min_value=-(1 << 31 - 1), max_value=1 << 31 - 1),
np.int64: st.integers(min_value=-(1 << 64 - 1), max_value=1 << 64 - 1),
np.uint32: st.integers(min_value=0, max_value=1 << 32 - 1),
np.uint64: st.integers(min_value=0, max_value=1 << 65 - 1),
bool: st.booleans()
}
E OSError: [Errno 22] Invalid argument
```
In this case, datetime in year 3002 is not supported? Taking a look...
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[GitHub] [beam] Abacn commented on a diff in pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
Abacn commented on code in PR #22233:
URL: https://github.com/apache/beam/pull/22233#discussion_r961916145
##########
sdks/python/apache_beam/coders/row_coder.py:
##########
@@ -162,6 +164,8 @@ def _nonnull_coder_from_type(field_type):
return BooleanCoder()
elif field_type.atomic_type == schema_pb2.BYTES:
return BytesCoder()
+ elif field_type.atomic_type == schema_pb2.BYTE:
Review Comment:
It seems OK because when BytesCoder encoding/decoding single byte with nested=False is the same as Java's ByteCoder (write one bytes); but if the stream has other data after this byte it is not the case.
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[GitHub] [beam] pabloem commented on a diff in pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on code in PR #22233:
URL: https://github.com/apache/beam/pull/22233#discussion_r961914182
##########
sdks/python/apache_beam/coders/row_coder.py:
##########
@@ -162,6 +164,8 @@ def _nonnull_coder_from_type(field_type):
return BooleanCoder()
elif field_type.atomic_type == schema_pb2.BYTES:
return BytesCoder()
+ elif field_type.atomic_type == schema_pb2.BYTE:
Review Comment:
- nvm - Byte seems to be okay. Should I leave it as is?
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[GitHub] [beam] pabloem commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1235787007
Run Python 3.8 PostCommit
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[GitHub] [beam] pabloem commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1216889715
r: @TheNeuralBit
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[GitHub] [beam] pabloem merged pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem merged PR #22233:
URL: https://github.com/apache/beam/pull/22233
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[GitHub] [beam] github-actions[bot] commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
github-actions[bot] commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1216977203
Stopping reviewer notifications for this pull request: review requested by someone other than the bot, ceding control
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[GitHub] [beam] pabloem commented on pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on PR #22233:
URL: https://github.com/apache/beam/pull/22233#issuecomment-1217238580
Run Python_PVR_Flink PreCommit
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[GitHub] [beam] TheNeuralBit commented on a diff in pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
TheNeuralBit commented on code in PR #22233:
URL: https://github.com/apache/beam/pull/22233#discussion_r959943053
##########
sdks/python/apache_beam/coders/coders_property_based_test.py:
##########
@@ -0,0 +1,138 @@
+#
+# 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.
+#
+
+"""Property tests for coders in the Python SDK.
+
+The tests in this file utilize the hypothesis library to generate random test
+cases and run them against Beam's coder implementations.
+
+These tests are similar to fuzzing, except they test invariant properties
+of code.
+"""
+
+import math
+import typing
+import unittest
+# TODO(pabloem): Include other categories of characters
+from datetime import datetime
+from string import ascii_letters
+from string import digits
+
+import numpy as np
+from hypothesis import strategies as st
+from hypothesis import assume
+from hypothesis import given
+from hypothesis import settings
+from pytz import utc
+
+from apache_beam.coders import FloatCoder
+from apache_beam.coders import RowCoder
+from apache_beam.coders import StrUtf8Coder
+from apache_beam.coders.typecoders import registry as coders_registry
+from apache_beam.typehints.schemas import typing_to_runner_api
+from apache_beam.utils.timestamp import Timestamp
+
+SCHEMA_TYPES = [str, bytes, Timestamp, int, np.int32, np.int64, bool]
+
+SCHEMA_TYPES_TO_STRATEGY = {
+ str: st.text(),
+ bytes: st.binary(),
+ # Maximum datetime on year 3000 to conform to Windows OS limits.
+ Timestamp: st.datetimes(
+ min_value=datetime(1970, 1, 1, 1, 1),
+ max_value=datetime(
+ 3000, 1, 1, 0,
+ 0)).map(lambda dt: Timestamp.from_utc_datetime(dt.astimezone(utc))),
+ int: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.int32: st.integers(min_value=-(1 << 31 - 1), max_value=1 << 31 - 1),
+ np.int64: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.uint32: st.integers(min_value=0, max_value=1 << 32 - 1),
+ np.uint64: st.integers(min_value=0, max_value=1 << 64 - 1),
Review Comment:
Is it intentional to have unsigned ints here? They're not supported in Beam schemas.
##########
sdks/python/apache_beam/coders/coders_property_based_test.py:
##########
@@ -0,0 +1,138 @@
+#
+# 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.
+#
+
+"""Property tests for coders in the Python SDK.
+
+The tests in this file utilize the hypothesis library to generate random test
+cases and run them against Beam's coder implementations.
+
+These tests are similar to fuzzing, except they test invariant properties
+of code.
+"""
+
+import math
+import typing
+import unittest
+# TODO(pabloem): Include other categories of characters
+from datetime import datetime
+from string import ascii_letters
+from string import digits
+
+import numpy as np
+from hypothesis import strategies as st
+from hypothesis import assume
+from hypothesis import given
+from hypothesis import settings
+from pytz import utc
+
+from apache_beam.coders import FloatCoder
+from apache_beam.coders import RowCoder
+from apache_beam.coders import StrUtf8Coder
+from apache_beam.coders.typecoders import registry as coders_registry
+from apache_beam.typehints.schemas import typing_to_runner_api
+from apache_beam.utils.timestamp import Timestamp
+
+SCHEMA_TYPES = [str, bytes, Timestamp, int, np.int32, np.int64, bool]
Review Comment:
It would be nice to have a way to keep this up to date as new types are added in schemas.py. Perhaps a test that checks this set is equivalent to the keys in PRIMITIVE_TO_ATOMIC_TYPE: https://github.com/apache/beam/blob/149ed074428ff9b5344169da7d54e8ee271aaba1/sdks/python/apache_beam/typehints/schemas.py#L104
Plus the registered logical types: https://github.com/apache/beam/blob/149ed074428ff9b5344169da7d54e8ee271aaba1/sdks/python/apache_beam/typehints/schemas.py#L505
##########
sdks/python/apache_beam/coders/coders_property_based_test.py:
##########
@@ -0,0 +1,138 @@
+#
+# 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.
+#
+
+"""Property tests for coders in the Python SDK.
+
+The tests in this file utilize the hypothesis library to generate random test
+cases and run them against Beam's coder implementations.
+
+These tests are similar to fuzzing, except they test invariant properties
+of code.
+"""
+
+import math
+import typing
+import unittest
+# TODO(pabloem): Include other categories of characters
+from datetime import datetime
+from string import ascii_letters
+from string import digits
+
+import numpy as np
+from hypothesis import strategies as st
+from hypothesis import assume
+from hypothesis import given
+from hypothesis import settings
+from pytz import utc
+
+from apache_beam.coders import FloatCoder
+from apache_beam.coders import RowCoder
+from apache_beam.coders import StrUtf8Coder
+from apache_beam.coders.typecoders import registry as coders_registry
+from apache_beam.typehints.schemas import typing_to_runner_api
+from apache_beam.utils.timestamp import Timestamp
+
+SCHEMA_TYPES = [str, bytes, Timestamp, int, np.int32, np.int64, bool]
+
+SCHEMA_TYPES_TO_STRATEGY = {
+ str: st.text(),
+ bytes: st.binary(),
+ # Maximum datetime on year 3000 to conform to Windows OS limits.
+ Timestamp: st.datetimes(
+ min_value=datetime(1970, 1, 1, 1, 1),
+ max_value=datetime(
+ 3000, 1, 1, 0,
+ 0)).map(lambda dt: Timestamp.from_utc_datetime(dt.astimezone(utc))),
+ int: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.int32: st.integers(min_value=-(1 << 31 - 1), max_value=1 << 31 - 1),
+ np.int64: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.uint32: st.integers(min_value=0, max_value=1 << 32 - 1),
+ np.uint64: st.integers(min_value=0, max_value=1 << 64 - 1),
+ bool: st.booleans()
+}
+
+# A hypothesis strategy that generates schemas.
+# A schema is a list containing tuples of strings (field names), types (field
+# types) and boolean (nullable or not).
+# This strategy currently generates rows with simple types (i.e. non-list, and
+# non-map fields).
+SCHEMA_GENERATOR_STRATEGY = st.lists(
+ st.tuples(
+ st.text(ascii_letters + digits + '_', min_size=1),
+ st.sampled_from(SCHEMA_TYPES),
+ st.booleans()))
+
+
+class ProperyTestingCoders(unittest.TestCase):
+ @given(st.text())
+ def test_string_coder(self, txt: str):
+ coder = StrUtf8Coder()
+ self.assertEqual(coder.decode(coder.encode(txt)), txt)
+
+ @given(st.floats())
+ def test_float_coder(self, num: float):
+ coder = FloatCoder()
+ test_num = coder.decode(coder.encode(num))
+ if math.isnan(num):
+ # This special branch is needed because by definition
+ # nan != nan.
+ self.assertTrue(math.isnan(test_num))
+ else:
+ self.assertEqual(coder.decode(coder.encode(num)), num)
+
+ @settings(deadline=None, print_blob=True)
+ @given(st.data())
+ def test_row_coder(self, data: st.DataObject):
+ """Generate rows and schemas, and test their encoding/decoding.
+
+ The schemas are generated based on the SCHEMA_GENERATOR_STRATEGY.
+ """
+ schema = data.draw(SCHEMA_GENERATOR_STRATEGY)
+ # Assume that the cardinality of the set of names is the same
+ # as the length of the schema. This means there's no duplicate
+ # names for fields.
+ # If this condition does not hold, then we must not continue the
+ # test.
+ assume(len({name for name, _, _ in schema}) == len(schema))
+ assume(
+ len({n[0]
+ for n, _, _ in schema}.intersection(set(digits + '_'))) == 0)
+ RowType = typing.NamedTuple( # type: ignore
+ 'RandomRowType',
+ [(name, type_ if not nullable else typing.Optional[type_]) for name,
+ type_,
+ nullable in schema])
Review Comment:
Another potential follow-up: Add a test that's parameterized by the schema proto instead of a generated row type. There are some schemas that we can't generate natively in Python, but we can get from other SDKs in the form of schema protos, and we need to be able to handle them. (For example, the millis_instant type that @Abacn just added).
##########
sdks/python/apache_beam/coders/coders_property_based_test.py:
##########
@@ -0,0 +1,138 @@
+#
+# 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.
+#
+
+"""Property tests for coders in the Python SDK.
+
+The tests in this file utilize the hypothesis library to generate random test
+cases and run them against Beam's coder implementations.
+
+These tests are similar to fuzzing, except they test invariant properties
+of code.
+"""
+
+import math
+import typing
+import unittest
+# TODO(pabloem): Include other categories of characters
+from datetime import datetime
+from string import ascii_letters
+from string import digits
+
+import numpy as np
+from hypothesis import strategies as st
+from hypothesis import assume
+from hypothesis import given
+from hypothesis import settings
+from pytz import utc
+
+from apache_beam.coders import FloatCoder
+from apache_beam.coders import RowCoder
+from apache_beam.coders import StrUtf8Coder
+from apache_beam.coders.typecoders import registry as coders_registry
+from apache_beam.typehints.schemas import typing_to_runner_api
+from apache_beam.utils.timestamp import Timestamp
+
+SCHEMA_TYPES = [str, bytes, Timestamp, int, np.int32, np.int64, bool]
+
+SCHEMA_TYPES_TO_STRATEGY = {
+ str: st.text(),
+ bytes: st.binary(),
+ # Maximum datetime on year 3000 to conform to Windows OS limits.
+ Timestamp: st.datetimes(
+ min_value=datetime(1970, 1, 1, 1, 1),
+ max_value=datetime(
+ 3000, 1, 1, 0,
+ 0)).map(lambda dt: Timestamp.from_utc_datetime(dt.astimezone(utc))),
+ int: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.int32: st.integers(min_value=-(1 << 31 - 1), max_value=1 << 31 - 1),
+ np.int64: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.uint32: st.integers(min_value=0, max_value=1 << 32 - 1),
+ np.uint64: st.integers(min_value=0, max_value=1 << 64 - 1),
+ bool: st.booleans()
+}
+
+# A hypothesis strategy that generates schemas.
+# A schema is a list containing tuples of strings (field names), types (field
+# types) and boolean (nullable or not).
+# This strategy currently generates rows with simple types (i.e. non-list, and
+# non-map fields).
+SCHEMA_GENERATOR_STRATEGY = st.lists(
+ st.tuples(
+ st.text(ascii_letters + digits + '_', min_size=1),
+ st.sampled_from(SCHEMA_TYPES),
+ st.booleans()))
+
+
+class ProperyTestingCoders(unittest.TestCase):
+ @given(st.text())
+ def test_string_coder(self, txt: str):
+ coder = StrUtf8Coder()
+ self.assertEqual(coder.decode(coder.encode(txt)), txt)
+
+ @given(st.floats())
+ def test_float_coder(self, num: float):
+ coder = FloatCoder()
+ test_num = coder.decode(coder.encode(num))
+ if math.isnan(num):
+ # This special branch is needed because by definition
+ # nan != nan.
+ self.assertTrue(math.isnan(test_num))
+ else:
+ self.assertEqual(coder.decode(coder.encode(num)), num)
+
+ @settings(deadline=None, print_blob=True)
+ @given(st.data())
+ def test_row_coder(self, data: st.DataObject):
+ """Generate rows and schemas, and test their encoding/decoding.
+
+ The schemas are generated based on the SCHEMA_GENERATOR_STRATEGY.
+ """
+ schema = data.draw(SCHEMA_GENERATOR_STRATEGY)
+ # Assume that the cardinality of the set of names is the same
+ # as the length of the schema. This means there's no duplicate
+ # names for fields.
+ # If this condition does not hold, then we must not continue the
+ # test.
+ assume(len({name for name, _, _ in schema}) == len(schema))
+ assume(
+ len({n[0]
+ for n, _, _ in schema}.intersection(set(digits + '_'))) == 0)
+ RowType = typing.NamedTuple( # type: ignore
+ 'RandomRowType',
+ [(name, type_ if not nullable else typing.Optional[type_]) for name,
+ type_,
+ nullable in schema])
+ coders_registry.register_coder(RowType, RowCoder)
+
+ # TODO(pabloem): Also apply nullability for these schemas.
Review Comment:
Please file an issue and link here. We should also consider testing the structured types (list, map, nested row, ...) https://github.com/apache/beam/blob/149ed074428ff9b5344169da7d54e8ee271aaba1/model/pipeline/src/main/proto/org/apache/beam/model/pipeline/v1/schema.proto#L68-L72
That could be part of the same issue or another issue
##########
sdks/python/apache_beam/coders/coders_property_based_test.py:
##########
@@ -0,0 +1,138 @@
+#
+# 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.
+#
+
+"""Property tests for coders in the Python SDK.
+
+The tests in this file utilize the hypothesis library to generate random test
+cases and run them against Beam's coder implementations.
+
+These tests are similar to fuzzing, except they test invariant properties
+of code.
+"""
+
+import math
+import typing
+import unittest
+# TODO(pabloem): Include other categories of characters
+from datetime import datetime
+from string import ascii_letters
+from string import digits
+
+import numpy as np
+from hypothesis import strategies as st
+from hypothesis import assume
+from hypothesis import given
+from hypothesis import settings
+from pytz import utc
+
+from apache_beam.coders import FloatCoder
+from apache_beam.coders import RowCoder
+from apache_beam.coders import StrUtf8Coder
+from apache_beam.coders.typecoders import registry as coders_registry
+from apache_beam.typehints.schemas import typing_to_runner_api
+from apache_beam.utils.timestamp import Timestamp
+
+SCHEMA_TYPES = [str, bytes, Timestamp, int, np.int32, np.int64, bool]
+
+SCHEMA_TYPES_TO_STRATEGY = {
+ str: st.text(),
+ bytes: st.binary(),
+ # Maximum datetime on year 3000 to conform to Windows OS limits.
+ Timestamp: st.datetimes(
+ min_value=datetime(1970, 1, 1, 1, 1),
+ max_value=datetime(
+ 3000, 1, 1, 0,
+ 0)).map(lambda dt: Timestamp.from_utc_datetime(dt.astimezone(utc))),
+ int: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.int32: st.integers(min_value=-(1 << 31 - 1), max_value=1 << 31 - 1),
+ np.int64: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.uint32: st.integers(min_value=0, max_value=1 << 32 - 1),
+ np.uint64: st.integers(min_value=0, max_value=1 << 64 - 1),
+ bool: st.booleans()
+}
+
+# A hypothesis strategy that generates schemas.
+# A schema is a list containing tuples of strings (field names), types (field
+# types) and boolean (nullable or not).
+# This strategy currently generates rows with simple types (i.e. non-list, and
+# non-map fields).
+SCHEMA_GENERATOR_STRATEGY = st.lists(
+ st.tuples(
+ st.text(ascii_letters + digits + '_', min_size=1),
+ st.sampled_from(SCHEMA_TYPES),
+ st.booleans()))
+
+
+class ProperyTestingCoders(unittest.TestCase):
+ @given(st.text())
+ def test_string_coder(self, txt: str):
+ coder = StrUtf8Coder()
+ self.assertEqual(coder.decode(coder.encode(txt)), txt)
+
+ @given(st.floats())
+ def test_float_coder(self, num: float):
+ coder = FloatCoder()
+ test_num = coder.decode(coder.encode(num))
+ if math.isnan(num):
+ # This special branch is needed because by definition
+ # nan != nan.
+ self.assertTrue(math.isnan(test_num))
+ else:
+ self.assertEqual(coder.decode(coder.encode(num)), num)
+
+ @settings(deadline=None, print_blob=True)
+ @given(st.data())
+ def test_row_coder(self, data: st.DataObject):
+ """Generate rows and schemas, and test their encoding/decoding.
+
+ The schemas are generated based on the SCHEMA_GENERATOR_STRATEGY.
+ """
+ schema = data.draw(SCHEMA_GENERATOR_STRATEGY)
+ # Assume that the cardinality of the set of names is the same
+ # as the length of the schema. This means there's no duplicate
+ # names for fields.
+ # If this condition does not hold, then we must not continue the
+ # test.
+ assume(len({name for name, _, _ in schema}) == len(schema))
+ assume(
+ len({n[0]
+ for n, _, _ in schema}.intersection(set(digits + '_'))) == 0)
+ RowType = typing.NamedTuple( # type: ignore
+ 'RandomRowType',
+ [(name, type_ if not nullable else typing.Optional[type_]) for name,
+ type_,
+ nullable in schema])
+ coders_registry.register_coder(RowType, RowCoder)
+
+ # TODO(pabloem): Also apply nullability for these schemas.
+ row = RowType( # type: ignore
+ **{
+ name: data.draw(SCHEMA_TYPES_TO_STRATEGY[type_])
+ for name,
+ type_,
+ nullable in schema
+ })
+
+ expected_coder = RowCoder(typing_to_runner_api(RowType).row_type.schema)
+ real_coder = coders_registry.get_coder(RowType)
+ self.assertEqual(expected_coder.decode(expected_coder.encode(row)), row)
+ self.assertEqual(real_coder.decode(real_coder.encode(row)), row)
+ self.assertEqual(real_coder.encode(row), expected_coder.encode(row))
Review Comment:
If you drop this you won't need to add RowType to the registry either.
##########
sdks/python/apache_beam/coders/coders_property_based_test.py:
##########
@@ -0,0 +1,138 @@
+#
+# 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.
+#
+
+"""Property tests for coders in the Python SDK.
+
+The tests in this file utilize the hypothesis library to generate random test
+cases and run them against Beam's coder implementations.
+
+These tests are similar to fuzzing, except they test invariant properties
+of code.
+"""
+
+import math
+import typing
+import unittest
+# TODO(pabloem): Include other categories of characters
+from datetime import datetime
+from string import ascii_letters
+from string import digits
+
+import numpy as np
+from hypothesis import strategies as st
+from hypothesis import assume
+from hypothesis import given
+from hypothesis import settings
+from pytz import utc
+
+from apache_beam.coders import FloatCoder
+from apache_beam.coders import RowCoder
+from apache_beam.coders import StrUtf8Coder
+from apache_beam.coders.typecoders import registry as coders_registry
+from apache_beam.typehints.schemas import typing_to_runner_api
+from apache_beam.utils.timestamp import Timestamp
+
+SCHEMA_TYPES = [str, bytes, Timestamp, int, np.int32, np.int64, bool]
+
+SCHEMA_TYPES_TO_STRATEGY = {
+ str: st.text(),
+ bytes: st.binary(),
+ # Maximum datetime on year 3000 to conform to Windows OS limits.
+ Timestamp: st.datetimes(
+ min_value=datetime(1970, 1, 1, 1, 1),
+ max_value=datetime(
+ 3000, 1, 1, 0,
+ 0)).map(lambda dt: Timestamp.from_utc_datetime(dt.astimezone(utc))),
+ int: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.int32: st.integers(min_value=-(1 << 31 - 1), max_value=1 << 31 - 1),
+ np.int64: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.uint32: st.integers(min_value=0, max_value=1 << 32 - 1),
+ np.uint64: st.integers(min_value=0, max_value=1 << 64 - 1),
+ bool: st.booleans()
+}
+
+# A hypothesis strategy that generates schemas.
+# A schema is a list containing tuples of strings (field names), types (field
+# types) and boolean (nullable or not).
+# This strategy currently generates rows with simple types (i.e. non-list, and
+# non-map fields).
+SCHEMA_GENERATOR_STRATEGY = st.lists(
+ st.tuples(
+ st.text(ascii_letters + digits + '_', min_size=1),
+ st.sampled_from(SCHEMA_TYPES),
+ st.booleans()))
+
+
+class ProperyTestingCoders(unittest.TestCase):
+ @given(st.text())
+ def test_string_coder(self, txt: str):
+ coder = StrUtf8Coder()
+ self.assertEqual(coder.decode(coder.encode(txt)), txt)
+
+ @given(st.floats())
+ def test_float_coder(self, num: float):
+ coder = FloatCoder()
+ test_num = coder.decode(coder.encode(num))
+ if math.isnan(num):
+ # This special branch is needed because by definition
+ # nan != nan.
+ self.assertTrue(math.isnan(test_num))
+ else:
+ self.assertEqual(coder.decode(coder.encode(num)), num)
+
+ @settings(deadline=None, print_blob=True)
+ @given(st.data())
+ def test_row_coder(self, data: st.DataObject):
+ """Generate rows and schemas, and test their encoding/decoding.
+
+ The schemas are generated based on the SCHEMA_GENERATOR_STRATEGY.
+ """
+ schema = data.draw(SCHEMA_GENERATOR_STRATEGY)
+ # Assume that the cardinality of the set of names is the same
+ # as the length of the schema. This means there's no duplicate
+ # names for fields.
+ # If this condition does not hold, then we must not continue the
+ # test.
+ assume(len({name for name, _, _ in schema}) == len(schema))
+ assume(
+ len({n[0]
+ for n, _, _ in schema}.intersection(set(digits + '_'))) == 0)
+ RowType = typing.NamedTuple( # type: ignore
+ 'RandomRowType',
+ [(name, type_ if not nullable else typing.Optional[type_]) for name,
+ type_,
+ nullable in schema])
+ coders_registry.register_coder(RowType, RowCoder)
+
+ # TODO(pabloem): Also apply nullability for these schemas.
+ row = RowType( # type: ignore
+ **{
+ name: data.draw(SCHEMA_TYPES_TO_STRATEGY[type_])
+ for name,
+ type_,
+ nullable in schema
+ })
+
+ expected_coder = RowCoder(typing_to_runner_api(RowType).row_type.schema)
+ real_coder = coders_registry.get_coder(RowType)
+ self.assertEqual(expected_coder.decode(expected_coder.encode(row)), row)
+ self.assertEqual(real_coder.decode(real_coder.encode(row)), row)
+ self.assertEqual(real_coder.encode(row), expected_coder.encode(row))
Review Comment:
```suggestion
coder = RowCoder(typing_to_runner_api(RowType).row_type.schema)
self.assertEqual(coder.decode(coder.encode(row)), row)
```
I don't think we need to replicate the expected_coder/real_coder silliness here. That was just me being overly cautious to make sure the registration works.
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[GitHub] [beam] pabloem commented on a diff in pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on code in PR #22233:
URL: https://github.com/apache/beam/pull/22233#discussion_r961312058
##########
sdks/python/apache_beam/coders/coders_property_based_test.py:
##########
@@ -0,0 +1,138 @@
+#
+# 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.
+#
+
+"""Property tests for coders in the Python SDK.
+
+The tests in this file utilize the hypothesis library to generate random test
+cases and run them against Beam's coder implementations.
+
+These tests are similar to fuzzing, except they test invariant properties
+of code.
+"""
+
+import math
+import typing
+import unittest
+# TODO(pabloem): Include other categories of characters
+from datetime import datetime
+from string import ascii_letters
+from string import digits
+
+import numpy as np
+from hypothesis import strategies as st
+from hypothesis import assume
+from hypothesis import given
+from hypothesis import settings
+from pytz import utc
+
+from apache_beam.coders import FloatCoder
+from apache_beam.coders import RowCoder
+from apache_beam.coders import StrUtf8Coder
+from apache_beam.coders.typecoders import registry as coders_registry
+from apache_beam.typehints.schemas import typing_to_runner_api
+from apache_beam.utils.timestamp import Timestamp
+
+SCHEMA_TYPES = [str, bytes, Timestamp, int, np.int32, np.int64, bool]
+
+SCHEMA_TYPES_TO_STRATEGY = {
+ str: st.text(),
+ bytes: st.binary(),
+ # Maximum datetime on year 3000 to conform to Windows OS limits.
+ Timestamp: st.datetimes(
+ min_value=datetime(1970, 1, 1, 1, 1),
+ max_value=datetime(
+ 3000, 1, 1, 0,
+ 0)).map(lambda dt: Timestamp.from_utc_datetime(dt.astimezone(utc))),
+ int: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.int32: st.integers(min_value=-(1 << 31 - 1), max_value=1 << 31 - 1),
+ np.int64: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.uint32: st.integers(min_value=0, max_value=1 << 32 - 1),
+ np.uint64: st.integers(min_value=0, max_value=1 << 64 - 1),
+ bool: st.booleans()
+}
+
+# A hypothesis strategy that generates schemas.
+# A schema is a list containing tuples of strings (field names), types (field
+# types) and boolean (nullable or not).
+# This strategy currently generates rows with simple types (i.e. non-list, and
+# non-map fields).
+SCHEMA_GENERATOR_STRATEGY = st.lists(
+ st.tuples(
+ st.text(ascii_letters + digits + '_', min_size=1),
+ st.sampled_from(SCHEMA_TYPES),
+ st.booleans()))
+
+
+class ProperyTestingCoders(unittest.TestCase):
+ @given(st.text())
+ def test_string_coder(self, txt: str):
+ coder = StrUtf8Coder()
+ self.assertEqual(coder.decode(coder.encode(txt)), txt)
+
+ @given(st.floats())
+ def test_float_coder(self, num: float):
+ coder = FloatCoder()
+ test_num = coder.decode(coder.encode(num))
+ if math.isnan(num):
+ # This special branch is needed because by definition
+ # nan != nan.
+ self.assertTrue(math.isnan(test_num))
+ else:
+ self.assertEqual(coder.decode(coder.encode(num)), num)
+
+ @settings(deadline=None, print_blob=True)
+ @given(st.data())
+ def test_row_coder(self, data: st.DataObject):
+ """Generate rows and schemas, and test their encoding/decoding.
+
+ The schemas are generated based on the SCHEMA_GENERATOR_STRATEGY.
+ """
+ schema = data.draw(SCHEMA_GENERATOR_STRATEGY)
+ # Assume that the cardinality of the set of names is the same
+ # as the length of the schema. This means there's no duplicate
+ # names for fields.
+ # If this condition does not hold, then we must not continue the
+ # test.
+ assume(len({name for name, _, _ in schema}) == len(schema))
+ assume(
+ len({n[0]
+ for n, _, _ in schema}.intersection(set(digits + '_'))) == 0)
+ RowType = typing.NamedTuple( # type: ignore
+ 'RandomRowType',
+ [(name, type_ if not nullable else typing.Optional[type_]) for name,
+ type_,
+ nullable in schema])
+ coders_registry.register_coder(RowType, RowCoder)
+
+ # TODO(pabloem): Also apply nullability for these schemas.
Review Comment:
aadded to the same issue
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[GitHub] [beam] pabloem commented on a diff in pull request #22233: Trying out property-based tests for Beam python coders
Posted by GitBox <gi...@apache.org>.
pabloem commented on code in PR #22233:
URL: https://github.com/apache/beam/pull/22233#discussion_r961310967
##########
sdks/python/apache_beam/coders/coders_property_based_test.py:
##########
@@ -0,0 +1,138 @@
+#
+# 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.
+#
+
+"""Property tests for coders in the Python SDK.
+
+The tests in this file utilize the hypothesis library to generate random test
+cases and run them against Beam's coder implementations.
+
+These tests are similar to fuzzing, except they test invariant properties
+of code.
+"""
+
+import math
+import typing
+import unittest
+# TODO(pabloem): Include other categories of characters
+from datetime import datetime
+from string import ascii_letters
+from string import digits
+
+import numpy as np
+from hypothesis import strategies as st
+from hypothesis import assume
+from hypothesis import given
+from hypothesis import settings
+from pytz import utc
+
+from apache_beam.coders import FloatCoder
+from apache_beam.coders import RowCoder
+from apache_beam.coders import StrUtf8Coder
+from apache_beam.coders.typecoders import registry as coders_registry
+from apache_beam.typehints.schemas import typing_to_runner_api
+from apache_beam.utils.timestamp import Timestamp
+
+SCHEMA_TYPES = [str, bytes, Timestamp, int, np.int32, np.int64, bool]
Review Comment:
Thanks! I've added the check for the primitives, but not for logical types. I created https://github.com/apache/beam/issues/23003 to track that.
##########
sdks/python/apache_beam/coders/coders_property_based_test.py:
##########
@@ -0,0 +1,138 @@
+#
+# 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.
+#
+
+"""Property tests for coders in the Python SDK.
+
+The tests in this file utilize the hypothesis library to generate random test
+cases and run them against Beam's coder implementations.
+
+These tests are similar to fuzzing, except they test invariant properties
+of code.
+"""
+
+import math
+import typing
+import unittest
+# TODO(pabloem): Include other categories of characters
+from datetime import datetime
+from string import ascii_letters
+from string import digits
+
+import numpy as np
+from hypothesis import strategies as st
+from hypothesis import assume
+from hypothesis import given
+from hypothesis import settings
+from pytz import utc
+
+from apache_beam.coders import FloatCoder
+from apache_beam.coders import RowCoder
+from apache_beam.coders import StrUtf8Coder
+from apache_beam.coders.typecoders import registry as coders_registry
+from apache_beam.typehints.schemas import typing_to_runner_api
+from apache_beam.utils.timestamp import Timestamp
+
+SCHEMA_TYPES = [str, bytes, Timestamp, int, np.int32, np.int64, bool]
+
+SCHEMA_TYPES_TO_STRATEGY = {
+ str: st.text(),
+ bytes: st.binary(),
+ # Maximum datetime on year 3000 to conform to Windows OS limits.
+ Timestamp: st.datetimes(
+ min_value=datetime(1970, 1, 1, 1, 1),
+ max_value=datetime(
+ 3000, 1, 1, 0,
+ 0)).map(lambda dt: Timestamp.from_utc_datetime(dt.astimezone(utc))),
+ int: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.int32: st.integers(min_value=-(1 << 31 - 1), max_value=1 << 31 - 1),
+ np.int64: st.integers(min_value=-(1 << 63 - 1), max_value=1 << 63 - 1),
+ np.uint32: st.integers(min_value=0, max_value=1 << 32 - 1),
+ np.uint64: st.integers(min_value=0, max_value=1 << 64 - 1),
Review Comment:
hm well, since they work I'll leave them there : )
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