feat(pyamber): add workflow transport runtime

[carloea2]

What changes were proposed in this PR?

Add a small pytexera.workflow runtime for generated Python UDFs. It provides:

• Cloudpickle encoding for selected Python values, including aliases and cycles;
• explicit field-presence tracking;
• boundary import and export helpers;
• tuple-operator adapters used by generated UDF modules.

Cloudpickle payloads are internal workflow data. Deserialization remains inside Python UDF workers that already execute user-provided Python code; this API must not be used as a safe decoder for untrusted bytes.

Any related issues, documentation, discussions?

Related to #8319 and discussion #8160.

How was this PR tested?

python -m pytest amber/src/test/python/pytexera/workflow/test_codec.py amber/src/test/python/pytexera/workflow/test_operators.py amber/src/test/python/pytexera/workflow/test_runtime.py -q

Result: 22 passed.

The tests cover round trips, aliases, cycles, missing fields, malformed envelopes, boundary routing, and operator behavior.

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

Generated-by: OpenAI Codex (GPT-5)

[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.

[codecov-commenter]

Codecov Report

❌ Patch coverage is 75.96899% with 62 lines in your changes missing coverage. Please review.
✅ Project coverage is 93.97%. Comparing base (fc7cfcd) to head (1090ffd).

Files with missing lines	Patch %	Lines
amber/src/main/python/pytexera/workflow/runtime.py	77.23%	16 Missing and 12 partials ⚠️
amber/src/main/python/pytexera/workflow/codec.py	65.51%	10 Missing and 10 partials ⚠️
...ber/src/main/python/pytexera/workflow/operators.py	81.08%	9 Missing and 5 partials ⚠️

Additional details and impacted files

@@             Coverage Diff              @@
##               main    #8321      +/-   ##
============================================
- Coverage     94.07%   93.97%   -0.10%     
  Complexity     4814     4814              
============================================
  Files          1196     1200       +4     
  Lines         48713    48971     +258     
  Branches       5866     5910      +44     
============================================
+ Hits          45825    46021     +196     
- Misses         1436     1471      +35     
- Partials       1452     1479      +27     

Flag	Coverage Δ		*Carryforward flag
access-control-service	81.00% <ø> (ø)		Carriedforward from fc7cfcd
agent-service	99.32% <ø> (ø)		Carriedforward from fc7cfcd
amber	90.12% <ø> (ø)		Carriedforward from fc7cfcd
computing-unit-managing-service	73.67% <ø> (ø)		Carriedforward from fc7cfcd
config-service	87.00% <ø> (ø)		Carriedforward from fc7cfcd
file-service	87.91% <ø> (ø)		Carriedforward from fc7cfcd
frontend	96.80% <ø> (ø)		Carriedforward from fc7cfcd
notebook-migration-service	79.31% <ø> (ø)		Carriedforward from fc7cfcd
pyamber	97.00% <75.96%> (-1.18%)	⬇️
workflow-compiling-service	77.19% <ø> (ø)		Carriedforward from fc7cfcd

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

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[github-actions]

⚠️ Benchmark changes need a look

🟢 4 better · 🔴 4 worse · ⚪ 7 noise (<±5%) · 0 without baseline

Compared against main fc7cfcd 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	459	0.28	20,275/29,804/29,804 us	🔴 +29.6% / 🔴 +87.4%
🟢	bs=100 sw=10 sl=64	995	0.607	98,788/109,842/109,842 us	🟢 -33.2% / 🟢 -9.1%
⚪	bs=1000 sw=10 sl=64	1,160	0.708	862,759/896,414/896,414 us	⚪ within ±5% / 🟢 -17.1%

Baseline details

Latest main fc7cfcd from same runner

config	metric	PR	latest main	7d avg	Δ latest	Δ 7d
bs=10 sw=10 sl=64	throughput	459 tuples/sec	506 tuples/sec	750.65 tuples/sec	-9.3%	-38.9%
bs=10 sw=10 sl=64	MB/s	0.28 MB/s	0.309 MB/s	0.458 MB/s	-9.4%	-38.9%
bs=10 sw=10 sl=64	p50	20,275 us	20,498 us	13,049 us	-1.1%	+55.4%
bs=10 sw=10 sl=64	p95	29,804 us	23,000 us	15,902 us	+29.6%	+87.4%
bs=10 sw=10 sl=64	p99	29,804 us	23,000 us	19,184 us	+29.6%	+55.4%
bs=100 sw=10 sl=64	throughput	995 tuples/sec	944 tuples/sec	960.3 tuples/sec	+5.4%	+3.6%
bs=100 sw=10 sl=64	MB/s	0.607 MB/s	0.576 MB/s	0.586 MB/s	+5.4%	+3.6%
bs=100 sw=10 sl=64	p50	98,788 us	98,747 us	104,199 us	+0.0%	-5.2%
bs=100 sw=10 sl=64	p95	109,842 us	164,332 us	110,645 us	-33.2%	-0.7%
bs=100 sw=10 sl=64	p99	109,842 us	164,332 us	120,888 us	-33.2%	-9.1%
bs=1000 sw=10 sl=64	throughput	1,160 tuples/sec	1,149 tuples/sec	993.27 tuples/sec	+1.0%	+16.8%
bs=1000 sw=10 sl=64	MB/s	0.708 MB/s	0.702 MB/s	0.606 MB/s	+0.9%	+16.8%
bs=1000 sw=10 sl=64	p50	862,759 us	866,721 us	1,012,191 us	-0.5%	-14.8%
bs=1000 sw=10 sl=64	p95	896,414 us	911,599 us	1,054,057 us	-1.7%	-15.0%
bs=1000 sw=10 sl=64	p99	896,414 us	911,599 us	1,081,313 us	-1.7%	-17.1%

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
0,10,10,64,20,435.67,200,128000,459,0.280,20274.81,29804.24,29804.24
1,100,10,64,20,2010.71,2000,1280000,995,0.607,98787.63,109842.16,109842.16
2,1000,10,64,20,17241.00,20000,12800000,1160,0.708,862759.18,896414.09,896414.09