Sergei Lebedev created BEAM-13384:
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Summary: apache_beam does not explicitly re-export metrics
Key: BEAM-13384
URL: https://issues.apache.org/jira/browse/BEAM-13384
Project: Beam
Issue Type: Bug
Components: sdk-py-core
Reporter: Sergei Lebedev
apache_beam/__init__.py does not re-export the metrics subpackage and thus
forces users to rely on import time side-effects. Specifically, it seems fairly
common to create metrics as
{code:java}
import apache_beam as beam
# ...
c = beam.metrics.Metrics.counter("ns", "counter"){code}
This works at runtime, because apache_beam imports the metrics subpackage
indirectly through one of its dependencies and get the "metrics" attribute as a
side-effect of that import (see [last
paragraph|https://docs.python.org/3/reference/import.html#submodules] in "The
import system" for an explanation of how that works).
Examples from GitHub
*
[tensorflow/transform|https://github.com/tensorflow/transform/blob/e0331bda765b7cc34347b38da74270dd3c01939b/tensorflow_transform/beam/impl.py#L282]
*
[tensorflow/tfx|https://github.com/tensorflow/tfx/blob/578c40cc23d5dd661826f5ed0e16db58479db1b4/tfx/components/transform/executor.py#L600]
*
[google-research/tapas|https://github.com/google-research/tapas/blob/f3d9f068e6eedb252883049b582516a1294ff951/tapas/utils/pretrain_utils.py#L65]
*
[google/tensorflow-recorder|https://github.com/google/tensorflow-recorder/blob/231b2c5422593d4eb7fc8502d5023425d08bedd6/tfrecorder/beam_pipeline.py#L141]
*
[kubeflow/examples|https://github.com/kubeflow/examples/blob/fcd2ef38027c1c0a91af2370c2beedb4c24298a8/code_search/src/code_search/dataflow/do_fns/prediction_do_fn.py#L112]
I think we should re-export metrics in apache_beam/__init__.py, similarly to
coders and io.
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