Fix no-op equality checks in Vertex AI trigger tests by hideki-y · Pull Request #66894 · apache/airflow

hideki-y · 2026-05-14T02:17:28Z

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare actual_data == expected_data expression instead of assert actual_data == expected_data, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing assert so the checks actually validate the serialized trigger payloads.

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

boring-cyborg · 2026-05-14T02:17:37Z

Congratulations on your first Pull Request and welcome to the Apache Airflow community! If you have any issues or are unsure about any anything please check our Contributors' Guide
Here are some useful points:

Pay attention to the quality of your code (ruff, mypy and type annotations). Our prek-hooks will help you with that.
In case of a new feature add useful documentation (in docstrings or in docs/ directory). Adding a new operator? Check this short guide Consider adding an example Dag that shows how users should use it.
Consider using Breeze environment for testing locally, it's a heavy docker but it ships with a working Airflow and a lot of integrations.
Be patient and persistent. It might take some time to get a review or get the final approval from Committers.
Please follow ASF Code of Conduct for all communication including (but not limited to) comments on Pull Requests, Mailing list and Slack.
Be sure to read the Airflow Coding style.
Always keep your Pull Requests rebased, otherwise your build might fail due to changes not related to your commits.
Apache Airflow is a community-driven project and together we are making it better 🚀.
In case of doubts contact the developers at:
Mailing List: dev@airflow.apache.org
Slack: https://s.apache.org/airflow-slack

shahar1

Great catch, thanks!

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

boring-cyborg · 2026-05-15T05:00:35Z

Awesome work, congrats on your first merged pull request! You are invited to check our Issue Tracker for additional contributions.

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

hideki-y · 2026-05-14T02:17:28Z

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare actual_data == expected_data expression instead of assert actual_data == expected_data, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing assert so the checks actually validate the serialized trigger payloads.

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

boring-cyborg · 2026-05-14T02:17:37Z

Congratulations on your first Pull Request and welcome to the Apache Airflow community! If you have any issues or are unsure about any anything please check our Contributors' Guide
Here are some useful points:

Pay attention to the quality of your code (ruff, mypy and type annotations). Our prek-hooks will help you with that.
In case of a new feature add useful documentation (in docstrings or in docs/ directory). Adding a new operator? Check this short guide Consider adding an example Dag that shows how users should use it.
Consider using Breeze environment for testing locally, it's a heavy docker but it ships with a working Airflow and a lot of integrations.
Be patient and persistent. It might take some time to get a review or get the final approval from Committers.
Please follow ASF Code of Conduct for all communication including (but not limited to) comments on Pull Requests, Mailing list and Slack.
Be sure to read the Airflow Coding style.
Always keep your Pull Requests rebased, otherwise your build might fail due to changes not related to your commits.
Apache Airflow is a community-driven project and together we are making it better 🚀.
In case of doubts contact the developers at:
Mailing List: dev@airflow.apache.org
Slack: https://s.apache.org/airflow-slack

shahar1

Great catch, thanks!

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

boring-cyborg · 2026-05-15T05:00:35Z

Awesome work, congrats on your first merged pull request! You are invited to check our Issue Tracker for additional contributions.

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

hideki-y · 2026-05-14T02:17:28Z

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare actual_data == expected_data expression instead of assert actual_data == expected_data, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing assert so the checks actually validate the serialized trigger payloads.

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

boring-cyborg · 2026-05-14T02:17:37Z

Congratulations on your first Pull Request and welcome to the Apache Airflow community! If you have any issues or are unsure about any anything please check our Contributors' Guide
Here are some useful points:

Pay attention to the quality of your code (ruff, mypy and type annotations). Our prek-hooks will help you with that.
In case of a new feature add useful documentation (in docstrings or in docs/ directory). Adding a new operator? Check this short guide Consider adding an example Dag that shows how users should use it.
Consider using Breeze environment for testing locally, it's a heavy docker but it ships with a working Airflow and a lot of integrations.
Be patient and persistent. It might take some time to get a review or get the final approval from Committers.
Please follow ASF Code of Conduct for all communication including (but not limited to) comments on Pull Requests, Mailing list and Slack.
Be sure to read the Airflow Coding style.
Always keep your Pull Requests rebased, otherwise your build might fail due to changes not related to your commits.
Apache Airflow is a community-driven project and together we are making it better 🚀.
In case of doubts contact the developers at:
Mailing List: dev@airflow.apache.org
Slack: https://s.apache.org/airflow-slack

shahar1

Great catch, thanks!

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

boring-cyborg · 2026-05-15T05:00:35Z

Awesome work, congrats on your first merged pull request! You are invited to check our Issue Tracker for additional contributions.

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

hideki-y · 2026-05-14T02:17:28Z

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare actual_data == expected_data expression instead of assert actual_data == expected_data, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing assert so the checks actually validate the serialized trigger payloads.

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

boring-cyborg · 2026-05-14T02:17:37Z

Congratulations on your first Pull Request and welcome to the Apache Airflow community! If you have any issues or are unsure about any anything please check our Contributors' Guide
Here are some useful points:

Pay attention to the quality of your code (ruff, mypy and type annotations). Our prek-hooks will help you with that.
In case of a new feature add useful documentation (in docstrings or in docs/ directory). Adding a new operator? Check this short guide Consider adding an example Dag that shows how users should use it.
Consider using Breeze environment for testing locally, it's a heavy docker but it ships with a working Airflow and a lot of integrations.
Be patient and persistent. It might take some time to get a review or get the final approval from Committers.
Please follow ASF Code of Conduct for all communication including (but not limited to) comments on Pull Requests, Mailing list and Slack.
Be sure to read the Airflow Coding style.
Always keep your Pull Requests rebased, otherwise your build might fail due to changes not related to your commits.
Apache Airflow is a community-driven project and together we are making it better 🚀.
In case of doubts contact the developers at:
Mailing List: dev@airflow.apache.org
Slack: https://s.apache.org/airflow-slack

shahar1

Great catch, thanks!

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

boring-cyborg · 2026-05-15T05:00:35Z

Awesome work, congrats on your first merged pull request! You are invited to check our Issue Tracker for additional contributions.

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

hideki-y · 2026-05-14T02:17:28Z

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare actual_data == expected_data expression instead of assert actual_data == expected_data, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing assert so the checks actually validate the serialized trigger payloads.

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

boring-cyborg · 2026-05-14T02:17:37Z

Congratulations on your first Pull Request and welcome to the Apache Airflow community! If you have any issues or are unsure about any anything please check our Contributors' Guide
Here are some useful points:

Pay attention to the quality of your code (ruff, mypy and type annotations). Our prek-hooks will help you with that.
In case of a new feature add useful documentation (in docstrings or in docs/ directory). Adding a new operator? Check this short guide Consider adding an example Dag that shows how users should use it.
Consider using Breeze environment for testing locally, it's a heavy docker but it ships with a working Airflow and a lot of integrations.
Be patient and persistent. It might take some time to get a review or get the final approval from Committers.
Please follow ASF Code of Conduct for all communication including (but not limited to) comments on Pull Requests, Mailing list and Slack.
Be sure to read the Airflow Coding style.
Always keep your Pull Requests rebased, otherwise your build might fail due to changes not related to your commits.
Apache Airflow is a community-driven project and together we are making it better 🚀.
In case of doubts contact the developers at:
Mailing List: dev@airflow.apache.org
Slack: https://s.apache.org/airflow-slack

shahar1

Great catch, thanks!

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

boring-cyborg · 2026-05-15T05:00:35Z

Awesome work, congrats on your first merged pull request! You are invited to check our Issue Tracker for additional contributions.

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

hideki-y · 2026-05-14T02:17:28Z

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare actual_data == expected_data expression instead of assert actual_data == expected_data, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing assert so the checks actually validate the serialized trigger payloads.

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

boring-cyborg · 2026-05-14T02:17:37Z

Congratulations on your first Pull Request and welcome to the Apache Airflow community! If you have any issues or are unsure about any anything please check our Contributors' Guide
Here are some useful points:

Pay attention to the quality of your code (ruff, mypy and type annotations). Our prek-hooks will help you with that.
In case of a new feature add useful documentation (in docstrings or in docs/ directory). Adding a new operator? Check this short guide Consider adding an example Dag that shows how users should use it.
Consider using Breeze environment for testing locally, it's a heavy docker but it ships with a working Airflow and a lot of integrations.
Be patient and persistent. It might take some time to get a review or get the final approval from Committers.
Please follow ASF Code of Conduct for all communication including (but not limited to) comments on Pull Requests, Mailing list and Slack.
Be sure to read the Airflow Coding style.
Always keep your Pull Requests rebased, otherwise your build might fail due to changes not related to your commits.
Apache Airflow is a community-driven project and together we are making it better 🚀.
In case of doubts contact the developers at:
Mailing List: dev@airflow.apache.org
Slack: https://s.apache.org/airflow-slack

shahar1

Great catch, thanks!

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

boring-cyborg · 2026-05-15T05:00:35Z

Awesome work, congrats on your first merged pull request! You are invited to check our Issue Tracker for additional contributions.

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

hideki-y · 2026-05-14T02:17:28Z

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare actual_data == expected_data expression instead of assert actual_data == expected_data, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing assert so the checks actually validate the serialized trigger payloads.

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

boring-cyborg · 2026-05-14T02:17:37Z

Congratulations on your first Pull Request and welcome to the Apache Airflow community! If you have any issues or are unsure about any anything please check our Contributors' Guide
Here are some useful points:

Pay attention to the quality of your code (ruff, mypy and type annotations). Our prek-hooks will help you with that.
In case of a new feature add useful documentation (in docstrings or in docs/ directory). Adding a new operator? Check this short guide Consider adding an example Dag that shows how users should use it.
Consider using Breeze environment for testing locally, it's a heavy docker but it ships with a working Airflow and a lot of integrations.
Be patient and persistent. It might take some time to get a review or get the final approval from Committers.
Please follow ASF Code of Conduct for all communication including (but not limited to) comments on Pull Requests, Mailing list and Slack.
Be sure to read the Airflow Coding style.
Always keep your Pull Requests rebased, otherwise your build might fail due to changes not related to your commits.
Apache Airflow is a community-driven project and together we are making it better 🚀.
In case of doubts contact the developers at:
Mailing List: dev@airflow.apache.org
Slack: https://s.apache.org/airflow-slack

shahar1

Great catch, thanks!

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

boring-cyborg · 2026-05-15T05:00:35Z

Awesome work, congrats on your first merged pull request! You are invited to check our Issue Tracker for additional contributions.

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

hideki-y · 2026-05-14T02:17:28Z

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare actual_data == expected_data expression instead of assert actual_data == expected_data, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing assert so the checks actually validate the serialized trigger payloads.

Was generative AI tooling used to co-author this PR?

Yes (please specify the tool below)

Read the Pull Request Guidelines for more information. Note: commit author/co-author name and email in commits become permanently public when merged.
For fundamental code changes, an Airflow Improvement Proposal (AIP) is needed.
When adding dependency, check compliance with the ASF 3rd Party License Policy.
For significant user-facing changes create newsfragment: {pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.

boring-cyborg · 2026-05-14T02:17:37Z

Congratulations on your first Pull Request and welcome to the Apache Airflow community! If you have any issues or are unsure about any anything please check our Contributors' Guide
Here are some useful points:

Pay attention to the quality of your code (ruff, mypy and type annotations). Our prek-hooks will help you with that.
In case of a new feature add useful documentation (in docstrings or in docs/ directory). Adding a new operator? Check this short guide Consider adding an example Dag that shows how users should use it.
Consider using Breeze environment for testing locally, it's a heavy docker but it ships with a working Airflow and a lot of integrations.
Be patient and persistent. It might take some time to get a review or get the final approval from Committers.
Please follow ASF Code of Conduct for all communication including (but not limited to) comments on Pull Requests, Mailing list and Slack.
Be sure to read the Airflow Coding style.
Always keep your Pull Requests rebased, otherwise your build might fail due to changes not related to your commits.
Apache Airflow is a community-driven project and together we are making it better 🚀.
In case of doubts contact the developers at:
Mailing List: dev@airflow.apache.org
Slack: https://s.apache.org/airflow-slack

shahar1

Great catch, thanks!

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

boring-cyborg · 2026-05-15T05:00:35Z

Awesome work, congrats on your first merged pull request! You are invited to check our Issue Tracker for additional contributions.

Four serialization tests in test_vertex_ai.py compared actual to expected data with a bare `actual_data == expected_data` expression instead of `assert actual_data == expected_data`, so the comparisons silently evaluated and discarded their result and the tests passed regardless of correctness. Add the missing `assert` so the checks actually validate the serialized trigger payloads.

boring-cyborgBot added area:providers provider:google Google (including GCP) related issues labels May 14, 2026

hideki-y marked this pull request as ready for review May 14, 2026 03:23

hideki-y requested a review from shahar1 as a code owner May 14, 2026 03:23

shahar1 approved these changes May 14, 2026
View reviewed changes

hideki-y force-pushed the fix_google_cloud_triggers_test branch from 22d941c to 668e6e2Compare May 14, 2026 23:13

shahar1 mentioned this pull request May 15, 2026
Enable ruff B015 to catch silent no-op comparisons in tests #66977
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shahar1 merged commit 767b72b into apache:mainMay 15, 2026
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