Upgrade to Beam 2.72.0 - #3557
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Summary of ChangesHello, 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 primarily focuses on a comprehensive dependency upgrade across both Java and Python components. It advances the core Apache Beam framework to a newer release candidate, updates several Google Cloud client libraries, and refines Python dependency specifications. The changes aim to ensure compatibility with the latest versions of these critical components and improve the robustness of related tests. Highlights
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Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #3557 +/- ##
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- Coverage 52.35% 52.32% -0.04%
+ Complexity 6143 6138 -5
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Files 1053 1053
Lines 63361 63361
Branches 6947 6947
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- Hits 33174 33151 -23
- Misses 27939 27962 +23
Partials 2248 2248
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Now the error becomes We may need to do similar changes like here: |
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clickhouse tests passed in the latest run |
Abacn
added
improvement
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Build failure due to cannot find aiohttp 3.13.5 in internal pypi mirror |
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R: @apanich @tvalentyn if anyone still around |
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LGTM |
| @@ -1,4 +1,4 @@ | |||
| apache-beam[gcp]==2.71.0 | |||
| apache-beam[gcp] | |||
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I think that this doesn't work well. When there are several requirements, pip doesn't always resolve to the latest beam. For example,
is on an old beam. This doesn't a matter much for this example template, but would be easy to miss in other instances.I think we should add back version numbers here, proposing this in #4203
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This happens when your __build__ dir isn't fresh. Adding version is indeed safer, though need to change it every time on a version bump or rc validation
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I don't think it is just that. We're getting this even when getting PRs generated by GitHub actions and I reproed on a fresh GitHub codespace - neither of these have preexisting __build__ directories
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Also note that it only failed to update streaming-llm in those passes, not the other generated requirements. This suggests that this can be caused by including certain dependencies (for now these are ml deps, but I don't think there's any guarantee that the same thing couldn't happen for other dependencies)
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My guess is that pip resolves some of the other dependencies first, then picks a beam version which satisfies that; if the dependency (or one of its dependencies) is outside Beam's constraints, then we'll see this issue
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Yeah it's possible. It's noticed some Beam's optional dependency started to depend on Beam: apache/beam#39884
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