[jira] [Created] (BEAM-13384) apache_beam does not explicitly re-export metrics

["Sergei Lebedev (Jira)" <ji...@apache.org>]

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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