[1/3] sdks/python: refactor Milvus-related utilities as preparation step for Milvus Sink I/O integration

[moawnallah]

Change Description

Towards #35046.
Depends on #35920.
Next #36729.

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[moawnallah]

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[moawnallah]

Regards dynamic batching perhaps it is in nice to have category. For now we can safely use the default JDBC I/O connector default batch size (1000)

[moawnallah]

Will make this PR in reviewable state after this PR #35467 merged. It refactors and unify some code related to testing from both Milvus Enrichment Handler and Sink I/O

[moawnallah]

The test test_gpu_auto_convert_to_cpu in the CI workflow run beam_PreCommit_Python_ML (Run Python_ML PreCommit 3.9) failed with an error unrelated to this PR's changeset. This appears to be an unconcerning transient timeout error.
CI Run: https://github.com/apache/beam/actions/runs/19015233042/job/54302103752?pr=35708

📋 Failure Logs

[gw5] [ 30%] FAILED apache_beam/ml/inference/pytorch_inference_test.py::PytorchRunInferencePipelineTest::test_gpu_auto_convert_to_cpu _________ PytorchRunInferencePipelineTest.test_gpu_auto_convert_to_cpu _________
[gw5] linux -- Python 3.9.22 /runner/_work/beam/beam/sdks/python/test-suites/tox/py39/build/srcs/sdks/python/target/.tox-py39-ml/py39-ml/bin/python
self = <apache_beam.ml.inference.pytorch_inference_test.PytorchRunInferencePipelineTest testMethod=test_gpu_auto_convert_to_cpu>
def test_gpu_auto_convert_to_cpu(self):
""" This tests the scenario in which the user defines `device='GPU'` for the PytorchModelHandlerX, but runs the pipeline on a machine without GPU, we automatically detect this discrepancy and do automatic conversion to CPU. A warning is also logged to inform the user."""
with self.assertLogs() as log:
with TestPipeline() as pipeline:
examples = torch.from_numpy(
np.array([1, 5, 3, 10], dtype="float32").reshape(-1, 1))
state_dict = OrderedDict([('linear.weight', torch.Tensor([[2.0]])),
('linear.bias', torch.Tensor([0.5]))])
path = os.path.join(self.tmpdir, 'my_state_dict_path')
torch.save(state_dict, path)
model_handler = PytorchModelHandlerTensor(
state_dict_path=path,
model_class=PytorchLinearRegression,
model_params={
'input_dim': 1, 'output_dim': 1
},
device='GPU')
# Upon initialization, device is cuda
self.assertEqual(model_handler._device, torch.device('cuda'))
pcoll = pipeline |'start'>> beam.Create(examples)
# pylint: disable=expression-not-assigned
pcoll | RunInference(model_handler)
# During model loading, device converted to cuda> self.assertEqual(model_handler._device, torch.device('cuda'))
apache_beam/ml/inference/pytorch_inference_test.py:770: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/pipeline.py:670: in __exit__
self.result = self.run()
target/.tox-py39-ml/py39-ml/lib/python3.9/site-packages/apache_beam/testing/test_pipeline.py:122: in run
state = result.wait_until_finish(duration=self.timeout)
...

---

The test test_external_test_specs in the CI workflow run beam_PreCommit_Python (Run Python PreCommit 3.9) failed with an error unrelated to this PR's changeset. This appears to be an unconcerning transient gRPC timeout error.
CI Run: https://github.com/apache/beam/actions/runs/19015233009/job/54302103686?pr=35708

📋 Failure Logs

[gw3] [ 99%] FAILED apache_beam/yaml/main_test.py::MainTest::test_external_test_specs
______________________ MainTest.test_external_test_specs _______________________
[gw3] linux -- Python 3.9.22 /runner/_work/beam/beam/sdks/python/test-suites/tox/py39/build/srcs/sdks/python/target/.tox-py39/py39/bin/python
self = <apache_beam.yaml.main_test.MainTest testMethod=test_external_test_specs>
def test_external_test_specs(self):
with tempfile.TemporaryDirectory() as tmpdir:
good_suite = os.path.join(tmpdir, 'good.yaml')
with open(good_suite, 'w') as fout:
fout.write(PASSING_TEST_SUITE)
bad_suite = os.path.join(tmpdir, 'bad.yaml')
with open(bad_suite, 'w') as fout:
fout.write(FAILING_TEST_SUITE)
# Must pass.> main.run_tests([
'--yaml_pipeline',
TEST_PIPELINE,
'--test_suite',
good_suite,
],
exit=False)
apache_beam/yaml/main_test.py:167: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ argv = ['--yaml_pipeline', '\npipeline:\n type: chain\n transforms:\n - type: Create\n config:\n elements: [...ork/beam/beam/sdks/python/test-suites/tox/py39/build/srcs/sdks/python/target/.tox-py39/py39/tmp/tmpuubw5yj6/good.yaml']
exit = False
def run_tests(argv=None, exit=True):
known_args, pipeline_args, _, pipeline_yaml = _build_pipeline_yaml_from_argv(
argv)
pipeline_spec = yaml.load(pipeline_yaml, Loader=yaml_transform.SafeLineLoader)
options = _build_pipeline_options(pipeline_spec, pipeline_args)
if known_args.create_test and known_args.fix_tests:
raise ValueError(
'At most one of --create_test and --fix_tests may be specified.')
elif known_args.create_test:
result = unittest.TestResult()
tests = []
else:
if known_args.test_suite:
with open(known_args.test_suite) as fin:
test_suite_holder = yaml.load(
fin, Loader=yaml_transform.SafeLineLoader) or {}
else:
test_suite_holder = pipeline_spec
test_specs = test_suite_holder.get('tests', [])
if not isinstance(test_specs, list):
raise TypeError('tests attribute must be a list of test specifications.')
elif not test_specs:
raise RuntimeError(
'No tests found. '"If you haven't added a set of tests yet, you can get started by "'running your pipeline with the --create_test flag enabled.')
tests = [
yaml_testing.YamlTestCase(
pipeline_spec, test_spec, options, known_args.fix_tests)
fortest_specin test_specs
]
suite = unittest.TestSuite(tests)
result = unittest.TextTestRunner().run(suite)
if known_args.fix_tests or known_args.create_test:
update_tests(known_args, pipeline_yaml, pipeline_spec, options, tests)
if exit:
# emulates unittest.main()
sys.exit(0 ifresult.wasSuccessful() else 1)
else:
if not result.wasSuccessful():
> raise RuntimeError(result)
E RuntimeError: <unittest.runner.TextTestResult run=1 errors=1 failures=0>
apache_beam/yaml/main.py:196: RuntimeError
----------------------------- Captured stderr call -----------------------------
E
======================================================================
ERROR: ExternalTest (line 3)
----------------------------------------------------------------------
Traceback (most recent call last):
File "/runner/_work/beam/beam/sdks/python/test-suites/tox/py39/build/srcs/sdks/python/apache_beam/yaml/yaml_testing.py", line 51, in runTest
self._fixes = run_test(
File "/runner/_work/beam/beam/sdks/python/test-suites/tox/py39/build/srcs/sdks/python/apache_beam/yaml/yaml_testing.py", line 102, in run_test
_ = p | yaml_transform.YamlTransform(
File "/runner/_work/beam/beam/sdks/python/test-suites/tox/py39/build/srcs/sdks/python/target/.tox-py39/py39/lib/python3.9/site-packages/apache_beam/pipeline.py", line 672, in __exit__
self.result.wait_until_finish()
File "/runner/_work/beam/beam/sdks/python/test-suites/tox/py39/build/srcs/sdks/python/target/.tox-py39/py39/lib/python3.9/site-packages/apache_beam/runners/portability/portable_runner.py", line 571, in wait_until_finish
raise self._runtime_exception
File "/runner/_work/beam/beam/sdks/python/test-suites/tox/py39/build/srcs/sdks/python/target/.tox-py39/py39/lib/python3.9/site-packages/apache_beam/runners/portability/portable_runner.py", line 580, in _observe_state
forstate_responsein self._state_stream:
File "/runner/_work/beam/beam/sdks/python/test-suites/tox/py39/build/srcs/sdks/python/target/.tox-py39/py39/lib/python3.9/site-packages/grpc/_channel.py", line 543, in __next__
returnself._next()
File "/runner/_work/beam/beam/sdks/python/test-suites/tox/py39/build/srcs/sdks/python/target/.tox-py39/py39/lib/python3.9/site-packages/grpc/_channel.py", line 969, in _next
raise self
grpc._channel._MultiThreadedRendezvous: <_MultiThreadedRendezvous of RPC that terminated with:
status = StatusCode.DEADLINE_EXCEEDED
details = "Deadline Exceeded"
debug_error_string = "UNKNOWN:Error received from peer {created_time:"2025-11-02T17:37:42.69913264+00:00", grpc_status:4, grpc_message:"Deadline Exceeded"}"

---

The Publish Test Results CI step in the CI workflow run PreCommit Python PVR Flink failed to successsfully publish those test results and it is unrelated to this PR's changeset. It seems a transient error
CI Run: https://github.com/apache/beam/pull/35708/checks?check_run_id=54302996157

[moawnallah]

Hey @damccorm, I think this PR is now ready for review. I've added the Milvus Sink I/O integration along with unit and integration tests, and did some refactoring by unifying core/testing utilities between the Milvus enrichment handler and sink I/O. All relevant CI tests are passing, and I'd love to receive any feedback when you have time for it

[damccorm]

Thanks! Pausing my review for now since my last comment would cause a major set of changes

[damccorm]

Thanks! It looks like there are now merge conflicts, but other than that and my one comment this looks good

[moawnallah]

@damccorm – addressed the recent comments and moved the jupyter notebook update to be after the Beam version is released (as in #35708 (comment)). The relevant CI tests are passing in the CI and the CI failed tests are unrelated to the changeset this PR introduce. I think the PR is now ready for another look

[damccorm]

Thanks!