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Fix cloudML TFT install avoiding pip ResolutionTooDeep #38781

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Fix cloudML TFT install avoiding pip ResolutionTooDeep #38781

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db5afa8
Fix cloudML TFT install avoiding pip ResolutionTooDeep
aIbrahiim Jun 3, 2026
5f29ee1
Trigger workflow
aIbrahiim Jun 3, 2026
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2 changes: 1 addition & 1 deletion .github/trigger_files/beam_CloudML_Benchmarks_Dataflow.json
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
{
"comment": "Modify this file in a trivial way to cause this test suite to run.",
"modification": 1
"modification": 3
}
5 changes: 4 additions & 1 deletion sdks/python/test-suites/dataflow/common.gradle
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Expand Up @@ -571,7 +571,10 @@ task installTFTRequirements {
exec {
workingDir "$rootProject.projectDir/sdks/python/apache_beam/testing/benchmarks/cloudml/"
executable 'sh'
args '-c', ". ${envdir}/bin/activate && pip install -r requirements.txt"
args '-c', ". ${envdir}/bin/activate && " +
"grep -v '^tensorflow-transform' requirements.txt > /tmp/cloudml_tft_base_requirements.txt && " +
"pip install -r /tmp/cloudml_tft_base_requirements.txt && " +
"pip install --no-deps tensorflow-transform==1.16.0"
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@gemini-code-assist gemini-code-assist Bot Jun 3, 2026

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medium

Using a hardcoded temporary file path like /tmp/cloudml_tft_base_requirements.txt can lead to conflicts, permission issues, or race conditions if multiple builds or tasks run concurrently on the same machine.

It is safer to use mktemp to create a unique temporary file and ensure it is cleaned up after the installation is complete.

      args '-c', ". ${envdir}/bin/activate && " +
          'tmp_file=$(mktemp) && ' +
          'grep -v "^tensorflow-transform" requirements.txt > "$tmp_file" && ' +
          'pip install -r "$tmp_file" && ' +
          'rm "$tmp_file" && ' +
          'pip install --no-deps tensorflow-transform==1.16.0'

}
}
}
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