[kz930]

What changes were proposed in this PR?

The Python that "Export to Python" writes carried notes meant for whoever maintains the generator: why a frame is copied, why a row is dropped before scoring, why an empty cell keeps its row. Someone running the exported script does not need them, and they made the script longer to read. This PR takes those comments out of the exported code in 24 operators, and keeps a one or two line note in Scala above the string where the reason is worth keeping.

• Machine learning: the sklearn estimators' shared training, testing and fit-and-score code, Linear Regression, and the Machine Learning Scorer.
• Hugging Face: Iris Logistic Regression, Sentiment Analysis, Spam SMS Detection, Text Summarization.
• Visualization: Bar, Box/Violin, Bubble, Bullet, Choropleth, Contour, Dendrogram, Gauge, Hierarchy, Histogram 2D, Icicle, Radar, Tree Plot, URL Visualizer.
• Unnest String.

Only comments go. The translator's own markers stay: the # [Operator] heading over each section, # --- Output ---, and the # TODO it writes for an operator it cannot export yet. The Python that operators run inside the engine is not touched.

Any related issues, documentation, discussions?

The comments came in with the export PRs #8365, #8367, #8368, #8504 and #8340.

#9035 also changes Unnest String's export. Whichever of the two merges second keeps the other's change.

How was this PR tested?

No generated statement changes, only comment lines. Running the verification suite before and after, the 1,098 scripts it generates for 142 operators are identical once comment lines and temporary paths are set aside, and none of them has an explanatory comment left. All of WorkflowOperator/test passes (2,912 tests), as do scalafmtCheck and scalafixAll --check.

Was this PR authored or co-authored using generative AI tooling?

Generated-by: Claude Code (Claude Opus 5.5)

🤖 Generated with Claude Code

[github-actions]

Automated Reviewer Suggestions

Based on the git blame history of the changed files, we recommend the following reviewers:

• Contributors with relevant context: @aglinxinyuan
  You can notify them by mentioning @aglinxinyuan in a comment.

[github-actions]

⚠️ Benchmark changes need a look

🟢 0 better · 🔴 5 worse · ⚪ 10 noise (<±5%) · 0 without baseline

Compared against main 8fbd4f2 benchmarked on this same runner, so the delta is largely free of cross-runner hardware noise. The "7d avg" column still reflects the gh-pages dashboard. Treat <±5% as noise unless repeated.

Dashboard · Run

	config	throughput	MB/s	latency	max Δ latest / 7d
🔴	bs=10 sw=10 sl=64	519	0.317	18,855/23,785/23,785 us	🔴 +16.3% / 🔴 +94.6%
🔴	bs=100 sw=10 sl=64	1,217	0.743	78,252/120,539/120,539 us	🔴 +13.9% / 🔴 +38.3%
⚪	bs=1000 sw=10 sl=64	1,439	0.878	692,198/775,517/775,517 us	⚪ within ±5% / 🟢 -11.3%

Baseline details

Latest main 8fbd4f2 from same runner

config	metric	PR	latest main	7d avg	Δ latest	Δ 7d
bs=10 sw=10 sl=64	throughput	519 tuples/sec	568 tuples/sec	1,019 tuples/sec	-8.6%	-49.1%
bs=10 sw=10 sl=64	MB/s	0.317 MB/s	0.347 MB/s	0.622 MB/s	-8.6%	-49.0%
bs=10 sw=10 sl=64	p50	18,855 us	16,213 us	10,144 us	+16.3%	+85.9%
bs=10 sw=10 sl=64	p95	23,785 us	24,119 us	12,225 us	-1.4%	+94.6%
bs=10 sw=10 sl=64	p99	23,785 us	24,119 us	15,527 us	-1.4%	+53.2%
bs=100 sw=10 sl=64	throughput	1,217 tuples/sec	1,232 tuples/sec	1,371 tuples/sec	-1.2%	-11.2%
bs=100 sw=10 sl=64	MB/s	0.743 MB/s	0.752 MB/s	0.837 MB/s	-1.2%	-11.2%
bs=100 sw=10 sl=64	p50	78,252 us	78,450 us	79,910 us	-0.3%	-2.1%
bs=100 sw=10 sl=64	p95	120,539 us	105,791 us	87,155 us	+13.9%	+38.3%
bs=100 sw=10 sl=64	p99	120,539 us	105,791 us	106,643 us	+13.9%	+13.0%
bs=1000 sw=10 sl=64	throughput	1,439 tuples/sec	1,442 tuples/sec	1,415 tuples/sec	-0.2%	+1.7%
bs=1000 sw=10 sl=64	MB/s	0.878 MB/s	0.88 MB/s	0.864 MB/s	-0.2%	+1.6%
bs=1000 sw=10 sl=64	p50	692,198 us	693,654 us	780,407 us	-0.2%	-11.3%
bs=1000 sw=10 sl=64	p95	775,517 us	749,780 us	817,814 us	+3.4%	-5.2%
bs=1000 sw=10 sl=64	p99	775,517 us	749,780 us	848,683 us	+3.4%	-8.6%

Raw CSV

config_idx,batch_size,schema_width,string_len,num_batches,total_ms,total_tuples,total_bytes,tuples_per_sec,mb_per_sec,lat_p50_us,lat_p95_us,lat_p99_us
0,10,10,64,20,385.09,200,128000,519,0.317,18854.51,23785.19,23785.19
1,100,10,64,20,1642.87,2000,1280000,1217,0.743,78251.84,120539.34,120539.34
2,1000,10,64,20,13900.10,20000,12800000,1439,0.878,692197.93,775516.62,775516.62

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 91.81%. Comparing base (8fbd4f2) to head (b816be7).
⚠️ Report is 2 commits behind head on main.

Additional details and impacted files

@@            Coverage Diff            @@
##               main    #9154   +/-   ##
=========================================
  Coverage     91.81%   91.81%           
- Complexity     5069     5070    +1     
=========================================
  Files          1271     1271           
  Lines         55208    55207    -1     
  Branches       6987     6987           
=========================================
+ Hits          50688    50689    +1     
+ Misses         2800     2799    -1     
+ Partials       1720     1719    -1     

Flag	Coverage Δ		*Carryforward flag
access-control-service	77.44% <ø> (ø)
agent-service	99.16% <ø> (ø)		Carriedforward from 8fbd4f2
amber	85.97% <100.00%> (+<0.01%)	⬆️
computing-unit-managing-service	61.84% <ø> (ø)
config-service	87.50% <ø> (ø)
file-service	81.92% <ø> (ø)
frontend	96.50% <ø> (ø)		Carriedforward from 8fbd4f2
notebook-migration-service	83.77% <ø> (ø)
pyamber	98.54% <ø> (ø)		Carriedforward from 8fbd4f2
workflow-compiling-service	72.61% <ø> (ø)

*This pull request uses carry forward flags. Click here to find out more.

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[aglinxinyuan]

LGTM!

[kz930]

@carloea2 This removes the explanatory comments that the merged export PRs left in exported Python, and keeps a short note in Scala where the reason matters. The generated statements are unchanged across all 1,098 verification scripts. Could you take a look?