[PYTHON] Add new --auto_unique_labels option to StandardOptions

[hjtran]

Motivating Issue

The python SDK requires users specify a unique label for every transform. Often times, the first time a transform is applied there is a default label that will be unique, but any future applications of the transform will require that the user specify a new and unique label. This can be quite tedious since there are many (?) scenarios where a user won't actually care about the labels. A couple scenarios that came up in my experience:

• Writing unit tests with multiple assert_that()s requires unique label for each assert
• Writing a pipeline that branches and applies the same transform to each branch
• Writing a linear pipeline where I want to reuse the same transform (e.g. LogElements or Deduplicate)

Change Summary

This change adds a new --auto_unique_labels standard option. The option defaults to off so there's no change in the default behavior. If the option is set, then whenever a transform is applied with a non-unique label, a new label is generated that includes an automatically incremented suffix. For example, if Deduplicate is applied twice, then the second deduplicate will have a label of Deduplicate_1. Additional Deduplicates would have a label of Deduplicate_n.

Testing

Wrote a new unit test that tests the new behavior. The rest of the pipeline_test.py tests still pass except for one: test_display_data. It also fails on my fork's master though so I'm assuming it's unrelated (EDIT: confirmed unrelated, it's just failing b/c it doesn't expect the URN to change when pipeline_test.py is invoked directly, in which case the URN references __main__)

GitHub Actions Tests Status (on master branch)

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[hjtran]

reviewer: @robertwb

[github-actions]

Stopping reviewer notifications for this pull request: review requested by someone other than the bot, ceding control

[codecov]

Codecov Report

Merging #28984 (c7d1305) into master (38720a3) will decrease coverage by 33.86%.
Report is 452 commits behind head on master.
The diff coverage is 27.27%.

@@             Coverage Diff             @@
##           master   #28984       +/-   ##
===========================================
- Coverage   72.22%   38.37%   -33.86%     
===========================================
  Files         684      686        +2     
  Lines      100856   101673      +817     
===========================================
- Hits        72846    39013    -33833     
- Misses      26434    61084    +34650     
  Partials     1576     1576               

Flag	Coverage Δ
python	29.98% <27.27%> (-52.84%)	⬇️

Flags with carried forward coverage won't be shown. Click here to find out more.

Files	Coverage Δ
...dks/python/apache_beam/options/pipeline_options.py	64.84% <100.00%> (-29.69%)	⬇️
sdks/python/apache_beam/pipeline.py	19.79% <20.00%> (-72.07%)	⬇️

... and 314 files with indirect coverage changes

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[robertwb]

Thanks.