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Fix Dataflow cost benchmark after Dataflow client migration#38788

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aIbrahiim:fix/data-flow-benchmark-after-client-migration
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Fix Dataflow cost benchmark after Dataflow client migration#38788
aIbrahiim wants to merge 1 commit into
apache:masterfrom
aIbrahiim:fix/data-flow-benchmark-after-client-migration

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@aIbrahiim
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Fixes: #38782


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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 addresses compatibility issues in the Dataflow cost benchmark suite following a migration of the underlying Dataflow client. The changes primarily involve updating type annotations to use native datetime objects, correcting attribute references to match the new client interface, and simplifying internal logic for calculating job runtimes.

Highlights

  • Type Safety: Updated method signatures to use datetime objects instead of strings for time-related parameters, improving type safety and reducing manual parsing.
  • API Compatibility: Updated attribute access from messageText to message_text to align with the updated Dataflow client API.
  • Refactoring: Simplified job runtime calculation by removing redundant ISO format parsing and streamlined project ID retrieval in metrics collection.
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@github-actions github-actions Bot added the python label Jun 3, 2026
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Code Review

This pull request refactors dataflow_cost_benchmark.py to use datetime objects instead of ISO format strings for worker start and end times across several methods, simplifying the runtime calculation in _get_job_runtime. Additionally, it updates message.messageText to message.message_text and retrieves the project ID directly from self.project_id instead of querying the Dataflow client. There are no review comments, and the changes look correct and clean; therefore, I have no feedback to provide.

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github-actions Bot commented Jun 3, 2026

Checks are failing. Will not request review until checks are succeeding. If you'd like to override that behavior, comment assign set of reviewers

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The Inference Python Benchmarks Dataflow job is flaky

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