(texera) branch release/v1.2 updated: fix(MachineLearningScorer, v1.2): splice metric_list verbatim instead of double-encoding (#7003)

[xuangu]

This is an automated email from the ASF dual-hosted git repository.

xuang7 pushed a commit to branch release/v1.2
in repository https://gitbox.apache.org/repos/asf/texera.git


The following commit(s) were added to refs/heads/release/v1.2 by this push:
     new 8c02dce18f fix(MachineLearningScorer, v1.2): splice metric_list 
verbatim instead of double-encoding  (#7003)
8c02dce18f is described below

commit 8c02dce18fb0df64a3c05c3593f655cd1964e474
Author: Yicong Huang <17627829+yicong-hu...@users.noreply.github.com>
AuthorDate: Wed Jul 29 14:10:01 2026 -0400

    fix(MachineLearningScorer, v1.2): splice metric_list verbatim instead of 
double-encoding  (#7003)
    
    ### What changes were proposed in this PR?
    
    Backport of #6805 to `release/v1.2`, cherry-picked from
    3a51bfb8761e96d10460f097b0e1803e27c2c5d0.
    
    **Source fix only.** The test changes from #6805 were omitted: the
    touched test spec(s) do not exist on `release/v1.2` (or depend on
    main-only test infrastructure), so backporting them cleanly is not
    possible. Only the source fix is carried over, per maintainer guidance.
    
    ### Any related issues, documentation, discussions?
    
    Backport of #6805. Originally linked #6790.
    
    ### How was this PR tested?
    
    Release-branch CI runs on this PR. The source change cherry-picked
    cleanly; test changes were intentionally dropped (see above).
    
    ### Was this PR authored or co-authored using generative AI tooling?
    
    Yes — backport prepared with Claude Code (mechanical cherry-pick +
    conflict resolution; the change itself is #6805 by its original author).
    
    🤖 Generated with [Claude Code](https://claude.com/claude-code)
    
    Co-authored-by: Kary Zheng <150742834+kz...@users.noreply.github.com>
    Co-authored-by: Claude Opus 4.8 (1M context) <nore...@anthropic.com>
---
 .../machineLearning/Scorer/MachineLearningScorerOpDesc.scala        | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git 
a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/machineLearning/Scorer/MachineLearningScorerOpDesc.scala
 
b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/machineLearning/Scorer/MachineLearningScorerOpDesc.scala
index a2f72a513e..e43c3f3947 100644
--- 
a/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/machineLearning/Scorer/MachineLearningScorerOpDesc.scala
+++ 
b/common/workflow-operator/src/main/scala/org/apache/texera/amber/operator/machineLearning/Scorer/MachineLearningScorerOpDesc.scala
@@ -122,8 +122,10 @@ class MachineLearningScorerOpDesc extends 
PythonOperatorDescriptor {
       case _                           => throw new 
IllegalArgumentException("Unknown metric type")
     }
 
-  private def getSelectedMetrics(): EncodableString = {
-    // Return a string of metrics using the getEachScorerName() method
+  // Must be a plain String, not EncodableString: this is a raw Python fragment
+  // spliced verbatim into `metric_list = [...]`. An EncodableString would be
+  // re-encoded as one quoted value, collapsing the list into a single element.
+  private def getSelectedMetrics(): String = {
     val metric = if (isRegression) regressionMetrics else classificationMetrics
     metric.map(metric => getMetricName(metric)).mkString("'", "','", "'")
   }