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Fix/add experiment refactor#38252

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ash6898 wants to merge 2 commits intoapache:masterfrom
ash6898:fix/add-experiment-refactor
Open

Fix/add experiment refactor#38252
ash6898 wants to merge 2 commits intoapache:masterfrom
ash6898:fix/add-experiment-refactor

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@ash6898 ash6898 commented Apr 21, 2026

addresses #19347

Summary

Replace manual experiment list manipulation with the existing helper methods:

  • Python: Convert experiments.append(...) to debug_options.add_experiment(...) in 5 files
  • Java: Replace getExperiments()/modify/setExperiments() pattern with ExperimentalOptions.addExperiment(...) in 3 files

This is a pure refactor — no behavior change. The helper methods already handle null-init and deduplication internally.

Files changed

Python:

  • sdks/python/apache_beam/pipeline.py
  • sdks/python/apache_beam/runners/portability/fn_api_runner/fn_runner.py
  • sdks/python/apache_beam/io/iobase_test.py
  • sdks/python/apache_beam/io/external/xlang_parquetio_test.py
  • sdks/python/apache_beam/runners/dataflow/internal/apiclient.py

Java:

  • runners/google-cloud-dataflow-java/src/main/java/.../DataflowPipelineTranslator.java
  • runners/google-cloud-dataflow-java/src/main/java/.../DataflowRunner.java
  • runners/google-cloud-dataflow-java/worker/src/main/.../GrpcWindmillServer.java

ash6898 added 2 commits April 18, 2026 16:22
Replaces manual list manipulation pattern with DebugOptions.add_experiment()
which handles null-init and deduplication internally.

Resolves apache#19347
… Java

Replaces getExperiments()/modify/setExperiments() boilerplate with
ExperimentalOptions.addExperiment() which handles null-init and deduplication.

Resolves apache#19347
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Summary of Changes

Hello, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request performs a clean refactor of how pipeline experiments are managed in the codebase. By migrating from manual list operations to established helper methods, the implementation becomes more concise and robust, ensuring consistent handling of experiment flags without altering existing behavior.

Highlights

  • Refactoring Experiment Management: Replaced manual list manipulation of pipeline experiments with centralized helper methods across both Python and Java SDKs.
  • Improved Robustness: Utilized existing helper methods that inherently handle null-initialization and deduplication, reducing boilerplate and potential bugs.

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