[
https://issues.apache.org/jira/browse/BEAM-6522?focusedWorklogId=231877&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-231877
]
ASF GitHub Bot logged work on BEAM-6522:
----------------------------------------
Author: ASF GitHub Bot
Created on: 24/Apr/19 06:15
Start Date: 24/Apr/19 06:15
Worklog Time Spent: 10m
Work Description: tvalentyn commented on pull request #8130: [BEAM-6522]
Fix fastavro on Python 3
URL: https://github.com/apache/beam/pull/8130#discussion_r277967068
##########
File path: sdks/python/apache_beam/io/avroio_test.py
##########
@@ -472,10 +476,55 @@ def test_sink_transform_snappy(self):
assert_that(readback, equal_to([json.dumps(r) for r in self.RECORDS]))
-class TestFastAvro(TestAvro):
[email protected](sys.version_info[0] == 3 and
+ os.environ.get('RUN_SKIPPED_PY3_TESTS') != '1',
+ 'This test still needs to be fixed on Python 3. '
+ 'TODO: BEAM-6522.')
+class TestAvro(AvroBase, unittest.TestCase):
+ def __init__(self, methodName='runTest'):
+ super(TestAvro, self).__init__(methodName)
+ self.use_fastavro = False
+ self.SCHEMA = Parse(self.SCHEMA_STRING)
+
+ def _write_data(self,
+ directory=None,
+ prefix=tempfile.template,
+ codec='null',
+ count=len(RECORDS)):
+ with tempfile.NamedTemporaryFile(delete=False,
+ dir=directory,
+ prefix=prefix) as f:
+ writer = DataFileWriter(f, DatumWriter(), self.SCHEMA, codec=codec)
+ len_records = len(self.RECORDS)
+ for i in range(count):
+ writer.append(self.RECORDS[i % len_records])
+ writer.close()
+ self._temp_files.append(f.name)
+ return f.name
+
+
+class TestFastAvro(AvroBase, unittest.TestCase):
def __init__(self, methodName='runTest'):
super(TestFastAvro, self).__init__(methodName)
self.use_fastavro = True
+ self.SCHEMA = parse_schema(json.loads(self.SCHEMA_STRING))
+
+ def _write_data(self,
+ directory=None,
+ prefix=tempfile.template,
+ codec='null',
+ count=len(RECORDS),
+ sync_interval=16000):
Review comment:
Let's not redefine default values for `writer()` method in the test.
Currently the defaults for `codec` and `sync_interval` match the respective
defaults in `fastavro/avro`, but if the library implementation changes the
default in the future, the test may be still hardcoding old value. How about
something like:
```
def _write_data(self,
directory=None,
prefix=tempfile.template,
count=len(RECORDS),
**kwargs):
...
writer(f, self.SCHEMA, all_records, **kwargs)
```
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Issue Time Tracking
-------------------
Worklog Id: (was: 231877)
Time Spent: 4h 50m (was: 4h 40m)
> Avro RecordSchema class is not picklable
> ----------------------------------------
>
> Key: BEAM-6522
> URL: https://issues.apache.org/jira/browse/BEAM-6522
> Project: Beam
> Issue Type: Sub-task
> Components: sdk-py-core
> Reporter: Robbe
> Assignee: Robbe
> Priority: Major
> Labels: triaged
> Time Spent: 4h 50m
> Remaining Estimate: 0h
>
> The avroio module still has 4 failing tests. This is actually 2 times the
> same 2 tests, both for Avro and Fastavro.
> *apache_beam.io.avroio_test.TestAvro.test_sink_transform*
> *apache_beam.io.avroio_test.TestFastAvro.test_sink_transform*
> fail with:
> {code:java}
> Traceback (most recent call last):
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/io/avroio_test.py",
> line 432, in test_sink_transform
> | avroio.WriteToAvro(path, self.SCHEMA, use_fastavro=self.use_fastavro)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/pvalue.py", line
> 112, in __or__
> return self.pipeline.apply(ptransform, self)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/pipeline.py", line
> 515, in apply
> pvalueish_result = self.runner.apply(transform, pvalueish, self._options)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/runners/runner.py",
> line 193, in apply
> return m(transform, input, options)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/runners/runner.py",
> line 199, in apply_PTransform
> return transform.expand(input)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/io/avroio.py", line
> 528, in expand
> return pcoll | beam.io.iobase.Write(self._sink)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/pvalue.py", line
> 112, in __or__
> return self.pipeline.apply(ptransform, self)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/pipeline.py", line
> 515, in apply
> pvalueish_result = self.runner.apply(transform, pvalueish, self._options)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/runners/runner.py",
> line 193, in apply
> return m(transform, input, options)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/runners/runner.py",
> line 199, in apply_PTransform
> return transform.expand(input)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/io/iobase.py", line
> 960, in expand
> return pcoll | WriteImpl(self.sink)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/pvalue.py", line
> 112, in __or__
> return self.pipeline.apply(ptransform, self)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/pipeline.py", line
> 515, in apply
> pvalueish_result = self.runner.apply(transform, pvalueish, self._options)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/runners/runner.py",
> line 193, in apply
> return m(transform, input, options)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/runners/runner.py",
> line 199, in apply_PTransform
> return transform.expand(input)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/io/iobase.py", line
> 979, in expand
> lambda _, sink: sink.initialize_write(), self.sink)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/transforms/core.py",
> line 1103, in Map
> pardo = FlatMap(wrapper, *args, **kwargs)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/transforms/core.py",
> line 1054, in FlatMap
> pardo = ParDo(CallableWrapperDoFn(fn), *args, **kwargs)
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/transforms/core.py",
> line 864, in __init__
> super(ParDo, self).__init__(fn, *args, **kwargs)
> File
> "/home/robbe/workspace/beam/sdks/python/apache_beam/transforms/ptransform.py",
> line 646, in __init__
> self.args = pickler.loads(pickler.dumps(self.args))
> File
> "/home/robbe/workspace/beam/sdks/python/apache_beam/internal/pickler.py",
> line 247, in loads
> return dill.loads(s)
> File
> "/home/robbe/workspace/beam/sdks/python/.eggs/dill-0.2.9-py3.5.egg/dill/_dill.py",
> line 317, in loads
> return load(file, ignore)
> File
> "/home/robbe/workspace/beam/sdks/python/.eggs/dill-0.2.9-py3.5.egg/dill/_dill.py",
> line 305, in load
> obj = pik.load()
> File
> "/home/robbe/workspace/beam/sdks/python/target/.tox/py3/lib/python3.5/site-packages/avro/schema.py",
> line 173, in __setitem__
> % (key, value, self))
> Exception: Attempting to map key 'favorite_color' to value <avro.schema.Field
> object at 0x7f8f72d0d0b8> in ImmutableDict {}
> {code}
>
> *apache_beam.io.avroio_test.TestAvro.test_split_points*
> *apache_beam.io.avroio_test.TestFastAvro.test_split_points*
> fail with:
>
> {code:java}
> Traceback (most recent call last):
> File "/home/robbe/workspace/beam/sdks/python/apache_beam/io/avroio_test.py",
> line 308, in test_split_points
> self.assertEquals(split_points_report[-10:], [(2, 1)] * 10)
> AssertionError: Lists differ: [(10, 1), (10, 1), (10, 1), (10, 1), (10, 1[42
> chars], 1)] != [(2, 1), (2, 1), (2, 1), (2, 1), (2, 1), (2[32 chars], 1)]
> First differing element 0:
> (10, 1)
> (2, 1)
> + [(2, 1), (2, 1), (2, 1), (2, 1), (2, 1), (2, 1), (2, 1), (2, 1), (2, 1),
> (2, 1)]
> - [(10, 1),
> - (10, 1),
> - (10, 1),
> - (10, 1),
> - (10, 1),
> - (10, 1),
> - (10, 1),
> - (10, 1),
> - (10, 1),
> - (10, 1)]
> {code}
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