Disable PDF export for s390x architecture in Jupyter Minimal images #1521
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WalkthroughThis change updates s390x platform support by adding new compatible targets in the CI matrix generator, conditionally skipping PDF dependency installation on s390x in a shell script, and skipping the PDF export test on unsupported architectures in the JupyterLab test suite. It also introduces centralized architecture support configuration and utility functions for architecture detection and feature support checks in container tests. Changes
Estimated code review effort🎯 2 (Simple) | ⏱️ ~10 minutes Possibly related issues
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Hi @Nash-123. Thanks for your PR. I'm waiting for a opendatahub-io member to verify that this patch is reasonable to test. If it is, they should reply with Once the patch is verified, the new status will be reflected by the I understand the commands that are listed here. Instructions for interacting with me using PR comments are available here. If you have questions or suggestions related to my behavior, please file an issue against the kubernetes-sigs/prow repository. |
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🧹 Nitpick comments (2)
jupyter/utils/install_pdf_deps.sh (1)
20-24: LGTM! Clean approach to disable PDF dependencies on s390x.The early exit prevents unnecessary TexLive and Pandoc installation on s390x architecture. The exit status 0 correctly indicates successful completion of the script's intended behavior.
Consider using the already-computed ARCH variable for consistency:
-if [[ "$(uname -m)" == "s390x" ]]; then +if [[ "${ARCH}" == "s390x" ]]; thentests/containers/workbenches/jupyterlab/jupyterlab_test.py (1)
61-68: Architecture detection works but could be optimized.The logic correctly skips PDF export tests on s390x architecture. However, starting and stopping the container twice (once for architecture detection, once for the actual test) adds unnecessary overhead.
Consider checking architecture after the main container start to avoid double start/stop:
- # Skip if we're running on s390x architecture - container.start(wait_for_readiness=False) - try: - exit_code, arch_output = container.exec(["uname", "-m"]) - if exit_code == 0 and arch_output.decode().strip() == "s390x": - pytest.skip("PDF export functionality is not supported on s390x architecture") - finally: - docker_utils.NotebookContainer(container).stop(timeout=0) test_file_name = "test.ipybn" # ... test_file_content ... try: container.start(wait_for_readiness=True) + # Skip if we're running on s390x architecture + exit_code, arch_output = container.exec(["uname", "-m"]) + if exit_code == 0 and arch_output.decode().strip() == "s390x": + pytest.skip("PDF export functionality is not supported on s390x architecture") # ... rest of test logic ...
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ci/cached-builds/gen_gha_matrix_jobs.py(1 hunks)jupyter/utils/install_pdf_deps.sh(1 hunks)tests/containers/workbenches/jupyterlab/jupyterlab_test.py(1 hunks)
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🧠 Learnings (4)
📓 Common learnings
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-09T10:24:37.290Z
Learning: jiridanek requested GitHub issue creation for TeX Live installation robustness improvements in jupyter/utils/install_pdf_deps.sh during PR #1357 review, specifically for network resilience and error handling improvements to address flaky CI failures. Issue was created with comprehensive problem description covering network download failures, mirror fallback mechanisms, retry logic, caching strategies, multiple solution options with code examples, detailed acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Dockerfile.rocm:50-50
Timestamp: 2025-07-08T19:30:01.738Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in ROCm TensorFlow image during PR #1333 review. Issue #1346 was created with comprehensive problem description covering hardcoded x86_64 architecture breaking multi-arch support, detailed impact analysis, three solution options (runtime detection, BuildKit TARGETARCH integration, hybrid approach) with pros/cons analysis, comprehensive acceptance criteria covering core requirements and testing, phased implementation guidance, related files identification, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: jupyter/pytorch/ubi9-python-3.12/Dockerfile.cuda:65-66
Timestamp: 2025-07-09T12:31:02.033Z
Learning: jiridanek requested GitHub issue creation for MSSQL repo file hardcoding problem during PR #1320 review. Issue #1363 was created and updated with comprehensive problem description covering hardcoded x86_64 MSSQL repo files breaking multi-architecture builds across 10 affected Dockerfiles (including datascience, CUDA, ROCm, and TrustyAI variants), detailed root cause analysis, three solution options with code examples, clear acceptance criteria for all image types, implementation guidance following established multi-architecture patterns, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-09T10:24:37.290Z
Learning: jiridanek requested GitHub issue creation for TeX Live installation robustness improvements in jupyter/utils/install_pdf_deps.sh during PR #1357 review, specifically for network resilience and error handling improvements to address flaky CI failures. Issue #1361 was successfully created with comprehensive problem description covering network download failures, mirror fallback mechanisms, retry logic, caching strategies, multiple solution options with code examples, detailed acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/datascience/ubi9-python-3.12/Pipfile:33-34
Timestamp: 2025-07-08T19:26:17.140Z
Learning: jiridanek requested GitHub issue creation for jupyter-client dependency pinning inconsistency during PR #1333 review, specifically asking to note the implications of breaking changes in 9.x versions. Issue #1343 was created with comprehensive problem description covering inconsistent pinning style across all Python 3.12 runtime images, detailed breaking changes analysis (kernel protocol, session management, connection security, API changes, async/await modifications), reproducibility and security impact assessment, multiple solution options with code examples, phased acceptance criteria, implementation guidance, testing approach, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/pytorch/ubi9-python-3.12/utils/bootstrapper.py:619-626
Timestamp: 2025-07-08T19:33:14.340Z
Learning: jiridanek requested GitHub issue creation for Python 3.12 version check bug in bootstrapper.py during PR #1333 review. Issue #1348 was created with comprehensive problem description covering version check exclusion affecting all Python 3.12 runtime images, detailed impact analysis of bootstrapper execution failures, clear solution with code examples, affected files list including all 6 runtime bootstrapper copies, acceptance criteria for testing and verification, implementation notes about code duplication and upstream reporting, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/tensorflow/ubi9-python-3.12/Dockerfile.cuda:38-38
Timestamp: 2025-07-08T19:30:20.513Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in TensorFlow CUDA runtime image during PR #1333 review. Issue was created with comprehensive problem description covering hardcoded NVARCH limitation, multiple solution options using TARGETARCH build argument with architecture mapping, acceptance criteria for multi-architecture builds, implementation guidance with code examples, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. The automated issue creation failed despite appearing successful, so comprehensive issue content was provided for manual creation covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1379
File: .tekton/odh-workbench-jupyter-datascience-cpu-py312-ubi9-push.yaml:14-17
Timestamp: 2025-07-11T11:15:47.424Z
Learning: jiridanek requested GitHub issue creation for CEL filter problem in datascience workbench Tekton pipelines during PR #1379 review. Issue #1383 was successfully created with comprehensive problem description covering both Python 3.11 and 3.12 pipelines incorrectly watching jupyter/minimal directories instead of jupyter/datascience directories, detailed impact analysis of pipeline execution failures, complete solution with before/after code examples, thorough acceptance criteria for path updates and pipeline triggering verification, implementation notes about repository structure alignment, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
tests/containers/workbenches/jupyterlab/jupyterlab_test.py (5)
Learnt from: jiridanek
PR: #1426
File: tests/browser/tests/codeserver.spec.ts:5-7
Timestamp: 2025-07-22T06:05:14.887Z
Learning: jiridanek requested GitHub issue creation for testcontainers internal API import fix during PR #1426 review. The issue covers replacing fragile internal build file imports with public Wait.forHttp() builder API to ensure compatibility across testcontainers version updates, affecting both 2024b and main branches with comprehensive problem description, code examples, and acceptance criteria.
Learnt from: jiridanek
PR: #1426
File: tests/browser/tests/codeserver.spec.ts:5-7
Timestamp: 2025-07-22T06:05:14.887Z
Learning: jiridanek requested GitHub issue creation for testcontainers internal API import fix during PR #1426 review. Issue #1428 was successfully created covering replacement of fragile internal build file imports with public Wait.forHttp() builder API to ensure compatibility across testcontainers version updates, affecting both 2024b and main branches with comprehensive problem description, solution with code examples, and acceptance criteria for systematic tracking of technical improvements.
Learnt from: jiridanek
PR: #1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. The automated issue creation failed despite appearing successful, so comprehensive issue content was provided for manual creation covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/test/test_notebook.ipynb:44-50
Timestamp: 2025-07-03T16:18:59.234Z
Learning: In the opendatahub-io/notebooks repository, the expected_versions.json file referenced in test notebooks (like test_notebook.ipynb) is generated during test execution, not included as a static file in the PR. This is an established testing pattern that should not be flagged as a missing file issue. The pattern is actively managed through issues like #1243 "Improve error handling in get_expected_version() functions across test notebooks" and #1254 "Fix undefined variable error in ROCm PyTorch Python 3.12 test notebook".
Learnt from: jiridanek
PR: #1306
File: jupyter/trustyai/ubi9-python-3.12/Dockerfile.cpu:135-136
Timestamp: 2025-07-04T05:52:49.464Z
Learning: jiridanek requested GitHub issue creation for improving fragile sed-based Jupyter kernel display_name modification in jupyter/trustyai/ubi9-python-3.12/Dockerfile.cpu during PR #1306 review. Issue #1321 was created with comprehensive problem description covering JSON corruption risks, greedy regex patterns, maintenance burden, and proposed Python-based JSON parsing solution with detailed acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements.
ci/cached-builds/gen_gha_matrix_jobs.py (13)
Learnt from: jiridanek
PR: #1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. The automated issue creation failed despite appearing successful, so comprehensive issue content was provided for manual creation covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:39:23.433Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue #1373 was successfully created on the second attempt with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue #1364 was created with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue was created with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue was created with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue was created with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue was created with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-11T11:16:05.131Z
Learning: jiridanek requested GitHub issue creation for RStudio py311 Tekton push pipelines during PR #1379 review. Issue #1384 was successfully created covering two RStudio variants (CPU and CUDA) found in manifests/base/params-latest.env, with comprehensive problem description, implementation requirements following the same pattern as other workbench pipelines, clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1379
File: .tekton/odh-workbench-jupyter-pytorch-cuda-py312-ubi9-push.yaml:40-44
Timestamp: 2025-07-11T11:15:25.572Z
Learning: jiridanek requested GitHub issue creation for critical Tekton array parameter syntax error during PR #1379 review, affecting all 32 pipeline files with additional-tags parameter. Issue #1382 was created with comprehensive problem description covering both Python 3.11 and 3.12 pipeline files (16 each), detailed root cause analysis of value: vs values: syntax error, critical impact assessment of complete pipeline execution failure, complete list of all affected files across workbench and runtime types, implementation commands with sed scripts, detailed acceptance criteria, implementation notes about systematic copy-paste error propagation, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1379
File: .tekton/odh-workbench-jupyter-datascience-cpu-py312-ubi9-push.yaml:14-17
Timestamp: 2025-07-11T11:15:47.424Z
Learning: jiridanek requested GitHub issue creation for CEL filter problem in datascience workbench Tekton pipelines during PR #1379 review. Issue #1383 was successfully created with comprehensive problem description covering both Python 3.11 and 3.12 pipelines incorrectly watching jupyter/minimal directories instead of jupyter/datascience directories, detailed impact analysis of pipeline execution failures, complete solution with before/after code examples, thorough acceptance criteria for path updates and pipeline triggering verification, implementation notes about repository structure alignment, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1197
File: runtimes/minimal/ubi9-python-3.11/requirements.txt:395-405
Timestamp: 2025-06-26T15:28:35.416Z
Learning: psutil version 7.x is compatible with UBI9, CentOS Stream 9, and RHEL 9 platforms in the opendatahub-io/notebooks repository. The upgrade from psutil 5.x to 7.x has been validated for these environments.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-11T11:54:28.202Z
Learning: In opendatahub-io/notebooks, Python 3.12-based images (e.g., runtime-cuda-pytorch-ubi9-python-3.12) may fail container runtime tests with "libcrypt.so.1 => not found" for MySQL SASL2 plugin libraries if libxcrypt-compat is missing. The solution is to install libxcrypt-compat in the Dockerfile.
Learnt from: jiridanek
PR: #1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Pipfile:13-15
Timestamp: 2025-07-03T07:03:45.020Z
Learning: The Python 3.11 infrastructure for ROCm TensorFlow images in opendatahub-io/notebooks is already properly configured in the Makefile with both BASE_DIRS entries for Pipfile lock renewals and all-images targets for CI builds, requiring only commenting out the corresponding Python 3.12 entries when downgrading due to wheel availability issues.
jupyter/utils/install_pdf_deps.sh (5)
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-09T10:24:37.290Z
Learning: jiridanek requested GitHub issue creation for TeX Live installation robustness improvements in jupyter/utils/install_pdf_deps.sh during PR #1357 review, specifically for network resilience and error handling improvements to address flaky CI failures. Issue was created with comprehensive problem description covering network download failures, mirror fallback mechanisms, retry logic, caching strategies, multiple solution options with code examples, detailed acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-09T10:24:37.290Z
Learning: jiridanek requested GitHub issue creation for TeX Live installation robustness improvements in jupyter/utils/install_pdf_deps.sh during PR #1357 review, specifically for network resilience and error handling improvements to address flaky CI failures. Issue #1361 was successfully created with comprehensive problem description covering network download failures, mirror fallback mechanisms, retry logic, caching strategies, multiple solution options with code examples, detailed acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: #1260
File: jupyter/utils/install_pdf_deps.sh:13-27
Timestamp: 2025-07-03T13:04:11.835Z
Learning: jiridanek requested GitHub issue creation for investigating alternatives to directory move operation in install_pdf_deps.sh during PR #1260 review, specifically to explore cleaner architectural approaches like installing TeX Live directly to /usr/local/texlive/bin instead of using filesystem manipulation post-installation.
Learnt from: jiridanek
PR: #1260
File: jupyter/utils/install_pdf_deps.sh:13-27
Timestamp: 2025-07-03T13:04:11.835Z
Learning: jiridanek requested GitHub issue creation for investigating alternatives to directory move operation in install_pdf_deps.sh during PR #1260 review, specifically to explore cleaner architectural approaches like installing TeX Live directly to /usr/local/texlive/bin instead of using filesystem manipulation post-installation. Issue #1291 was created with comprehensive problem description, multiple solution options, acceptance criteria, and proper context linking.
Learnt from: jiridanek
PR: #1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. The automated issue creation failed despite appearing successful, so comprehensive issue content was provided for manual creation covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
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- GitHub Check: build (jupyter-minimal-ubi9-python-3.12, 3.12, linux/amd64, false) / build
- GitHub Check: build (rocm-jupyter-minimal-ubi9-python-3.11, 3.11, linux/amd64, false) / build
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🔇 Additional comments (1)
ci/cached-builds/gen_gha_matrix_jobs.py (1)
36-37: LGTM! Correctly enables s390x builds for Jupyter Minimal images.The addition of these two targets to the S390X_COMPATIBLE set properly enables CI builds for Jupyter Minimal images on s390x architecture, aligning with the broader PR objective of supporting s390x while disabling PDF export functionality on this platform.
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Actionable comments posted: 1
♻️ Duplicate comments (1)
tests/containers/workbenches/jupyterlab/jupyterlab_test.py (1)
59-63: Acknowledge interim architecture detection approach.This implementation correctly integrates architecture-aware testing but still uses the container start/stop approach for architecture detection that was identified as inefficient in our previous discussion.
While this works for the current PR objectives, Issue #1576 tracks the systematic improvements for more efficient session-level caching and centralized configuration that we discussed.
🧹 Nitpick comments (4)
tests/containers/workbenches/jupyterlab/jupyterlab_test.py (1)
59-63: Fix formatting and acknowledge architecture improvement.Great implementation of the centralized architecture detection! This aligns perfectly with the systematic improvements discussed in Issue #1576.
However, there's a minor formatting issue to fix:
- if not is_feature_supported(container_architecture,"pdf_export"): + if not is_feature_supported(container_architecture, "pdf_export"):tests/containers/architecture_utils.py (3)
8-8: Fix formatting - add blank line before fixture.+ @pytest.fixture(scope="function")
21-21: Fix formatting - add blank line before function.+ def is_feature_supported(architecture: str, feature: str) -> bool:
25-25: Fix formatting - add blank line before function.+ def get_architecture_limitation_reason(architecture: str, feature: str) -> str:
📜 Review details
Configuration used: .coderabbit.yaml
Review profile: CHILL
Plan: Pro
📒 Files selected for processing (5)
ci/cached-builds/gen_gha_matrix_jobs.py(1 hunks)jupyter/utils/install_pdf_deps.sh(1 hunks)tests/containers/architecture_support.py(1 hunks)tests/containers/architecture_utils.py(1 hunks)tests/containers/workbenches/jupyterlab/jupyterlab_test.py(2 hunks)
✅ Files skipped from review due to trivial changes (1)
- tests/containers/architecture_support.py
🚧 Files skipped from review as they are similar to previous changes (2)
- ci/cached-builds/gen_gha_matrix_jobs.py
- jupyter/utils/install_pdf_deps.sh
🧰 Additional context used
🧠 Learnings (34)
📓 Common learnings
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1521
File: tests/containers/workbenches/jupyterlab/jupyterlab_test.py:61-68
Timestamp: 2025-08-01T09:33:23.033Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection efficiency and centralization in JupyterLab tests during PR #1521 review. Issue #1576 was successfully created covering performance inefficiency of current container start/stop approach for architecture detection, need for centralized configuration of architecture-specific limitations, comprehensive solution options including session caching and helper functions, detailed acceptance criteria covering performance and maintainability requirements, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-09T10:24:37.290Z
Learning: jiridanek requested GitHub issue creation for TeX Live installation robustness improvements in jupyter/utils/install_pdf_deps.sh during PR #1357 review, specifically for network resilience and error handling improvements to address flaky CI failures. Issue #1361 was successfully created with comprehensive problem description covering network download failures, mirror fallback mechanisms, retry logic, caching strategies, multiple solution options with code examples, detailed acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-09T10:24:37.290Z
Learning: jiridanek requested GitHub issue creation for TeX Live installation robustness improvements in jupyter/utils/install_pdf_deps.sh during PR #1357 review, specifically for network resilience and error handling improvements to address flaky CI failures. Issue was created with comprehensive problem description covering network download failures, mirror fallback mechanisms, retry logic, caching strategies, multiple solution options with code examples, detailed acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-11T11:16:05.131Z
Learning: jiridanek requested GitHub issue creation for RStudio py311 Tekton push pipelines during PR #1379 review. Issue #1384 was successfully created covering two RStudio variants (CPU and CUDA) found in manifests/base/params-latest.env, with comprehensive problem description, implementation requirements following the same pattern as other workbench pipelines, clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/kustomize/base/service.yaml:5-15
Timestamp: 2025-07-02T18:59:15.788Z
Learning: jiridanek creates targeted GitHub issues for specific test quality improvements identified during PR reviews in opendatahub-io/notebooks. Issue #1268 demonstrates this by converting a review comment about insufficient tf2onnx conversion test validation into a comprehensive improvement plan with clear acceptance criteria, code examples, and ROCm-specific context.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1379
File: .tekton/odh-workbench-jupyter-datascience-cpu-py312-ubi9-push.yaml:14-17
Timestamp: 2025-07-11T11:15:47.424Z
Learning: jiridanek requested GitHub issue creation for CEL filter problem in datascience workbench Tekton pipelines during PR #1379 review. Issue #1383 was successfully created with comprehensive problem description covering both Python 3.11 and 3.12 pipelines incorrectly watching jupyter/minimal directories instead of jupyter/datascience directories, detailed impact analysis of pipeline execution failures, complete solution with before/after code examples, thorough acceptance criteria for path updates and pipeline triggering verification, implementation notes about repository structure alignment, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Dockerfile.rocm:50-50
Timestamp: 2025-07-08T19:30:01.738Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in ROCm TensorFlow image during PR #1333 review. Issue #1346 was created with comprehensive problem description covering hardcoded x86_64 architecture breaking multi-arch support, detailed impact analysis, three solution options (runtime detection, BuildKit TARGETARCH integration, hybrid approach) with pros/cons analysis, comprehensive acceptance criteria covering core requirements and testing, phased implementation guidance, related files identification, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: jupyter/pytorch/ubi9-python-3.12/Dockerfile.cuda:65-66
Timestamp: 2025-07-09T12:31:02.033Z
Learning: jiridanek requested GitHub issue creation for MSSQL repo file hardcoding problem during PR #1320 review. Issue #1363 was created and updated with comprehensive problem description covering hardcoded x86_64 MSSQL repo files breaking multi-architecture builds across 10 affected Dockerfiles (including datascience, CUDA, ROCm, and TrustyAI variants), detailed root cause analysis, three solution options with code examples, clear acceptance criteria for all image types, implementation guidance following established multi-architecture patterns, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. The automated issue creation failed despite appearing successful, so comprehensive issue content was provided for manual creation covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue #1364 was created with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue was created with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue was created with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue was created with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue was created with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:39:23.433Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue #1373 was successfully created on the second attempt with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Learnt from: atheo89
PR: opendatahub-io/notebooks#1258
File: codeserver/ubi9-python-3.11/Dockerfile.cpu:32-32
Timestamp: 2025-07-07T11:08:48.524Z
Learning: atheo89 requested GitHub issue creation for multi-architecture Dockerfile improvements during PR #1258 review, specifically for enhancing structural consistency across Docker stages, replacing $(uname -m) with ${TARGETARCH} for cross-architecture builds, and adding OCI-compliant metadata labels. Issue #1332 was created with comprehensive problem description, phased implementation approach, detailed acceptance criteria, implementation guidance with code examples, and proper context linking, continuing the established pattern of systematic code quality improvements.
📚 Learning: jiridanek requested github issue creation for improving architecture detection efficiency and centra...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1521
File: tests/containers/workbenches/jupyterlab/jupyterlab_test.py:61-68
Timestamp: 2025-08-01T09:33:23.033Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection efficiency and centralization in JupyterLab tests during PR #1521 review. Issue #1576 was successfully created covering performance inefficiency of current container start/stop approach for architecture detection, need for centralized configuration of architecture-specific limitations, comprehensive solution options including session caching and helper functions, detailed acceptance criteria covering performance and maintainability requirements, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/architecture_utils.pytests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: atheo89 requested github issue creation for multi-architecture dockerfile improvements during pr #12...
Learnt from: atheo89
PR: opendatahub-io/notebooks#1258
File: codeserver/ubi9-python-3.11/Dockerfile.cpu:32-32
Timestamp: 2025-07-07T11:08:48.524Z
Learning: atheo89 requested GitHub issue creation for multi-architecture Dockerfile improvements during PR #1258 review, specifically for enhancing structural consistency across Docker stages, replacing $(uname -m) with ${TARGETARCH} for cross-architecture builds, and adding OCI-compliant metadata labels. Issue #1332 was created with comprehensive problem description, phased implementation approach, detailed acceptance criteria, implementation guidance with code examples, and proper context linking, continuing the established pattern of systematic code quality improvements.
Applied to files:
tests/containers/architecture_utils.pytests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for multi-architecture support in tensorflow cuda runtime ...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/tensorflow/ubi9-python-3.12/Dockerfile.cuda:38-38
Timestamp: 2025-07-08T19:30:20.513Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in TensorFlow CUDA runtime image during PR #1333 review. Issue was created with comprehensive problem description covering hardcoded NVARCH limitation, multiple solution options using TARGETARCH build argument with architecture mapping, acceptance criteria for multi-architecture builds, implementation guidance with code examples, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/architecture_utils.pytests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for multi-architecture support in rocm tensorflow image du...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-tensorflow/ubi9-python-3.12/Dockerfile.rocm:50-50
Timestamp: 2025-07-08T19:30:01.738Z
Learning: jiridanek requested GitHub issue creation for multi-architecture support in ROCm TensorFlow image during PR #1333 review. Issue #1346 was created with comprehensive problem description covering hardcoded x86_64 architecture breaking multi-arch support, detailed impact analysis, three solution options (runtime detection, BuildKit TARGETARCH integration, hybrid approach) with pros/cons analysis, comprehensive acceptance criteria covering core requirements and testing, phased implementation guidance, related files identification, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/architecture_utils.pytests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for improving architecture detection in buildinputs tool d...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. The automated issue creation failed despite appearing successful, so comprehensive issue content was provided for manual creation covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/architecture_utils.pytests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for improving architecture detection in buildinputs tool d...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue #1364 was created with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/architecture_utils.pytests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for openshift client architecture mapping problem affectin...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: jupyter/pytorch/ubi9-python-3.12/Dockerfile.cuda:42-52
Timestamp: 2025-07-09T12:29:56.162Z
Learning: jiridanek requested GitHub issue creation for OpenShift client architecture mapping problem affecting 29 Dockerfiles during PR #1320 review. Issue was created with comprehensive analysis covering all affected files using $(uname -m) returning 'aarch64' but OpenShift mirror expecting 'arm64', systematic solution using BuildKit TARGETARCH mapping with proper amd64→x86_64 and arm64→arm64 conversion, detailed acceptance criteria, and implementation guidance, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/architecture_utils.pytests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for improving architecture detection in buildinputs tool d...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:02:13.228Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue was created with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/architecture_utils.pytests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for cel filter problem in datascience workbench tekton pip...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1379
File: .tekton/odh-workbench-jupyter-datascience-cpu-py312-ubi9-push.yaml:14-17
Timestamp: 2025-07-11T11:15:47.424Z
Learning: jiridanek requested GitHub issue creation for CEL filter problem in datascience workbench Tekton pipelines during PR #1379 review. Issue #1383 was successfully created with comprehensive problem description covering both Python 3.11 and 3.12 pipelines incorrectly watching jupyter/minimal directories instead of jupyter/datascience directories, detailed impact analysis of pipeline execution failures, complete solution with before/after code examples, thorough acceptance criteria for path updates and pipeline triggering verification, implementation notes about repository structure alignment, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for mssql repo file hardcoding problem during pr #1320 rev...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: jupyter/pytorch/ubi9-python-3.12/Dockerfile.cuda:65-66
Timestamp: 2025-07-09T12:31:02.033Z
Learning: jiridanek requested GitHub issue creation for MSSQL repo file hardcoding problem during PR #1320 review. Issue #1363 was created and updated with comprehensive problem description covering hardcoded x86_64 MSSQL repo files breaking multi-architecture builds across 10 affected Dockerfiles (including datascience, CUDA, ROCm, and TrustyAI variants), detailed root cause analysis, three solution options with code examples, clear acceptance criteria for all image types, implementation guidance following established multi-architecture patterns, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for rstudio py311 tekton push pipelines during pr #1379 re...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-11T11:16:05.131Z
Learning: jiridanek requested GitHub issue creation for RStudio py311 Tekton push pipelines during PR #1379 review. Issue #1384 was successfully created covering two RStudio variants (CPU and CUDA) found in manifests/base/params-latest.env, with comprehensive problem description, implementation requirements following the same pattern as other workbench pipelines, clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for misleading cuda prefix in trustyai image tags during p...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review. Issue was created with comprehensive problem description covering both Python 3.11 and 3.12 versions, repository pattern analysis showing correct vs incorrect naming, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for misleading cuda prefix in trustyai image tags during p...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1306
File: jupyter/trustyai/ubi9-python-3.12/kustomize/base/kustomization.yaml:8-12
Timestamp: 2025-07-08T19:09:48.746Z
Learning: jiridanek requested GitHub issue creation for misleading CUDA prefix in TrustyAI image tags during PR #1306 review, affecting both Python 3.11 and 3.12 versions. Issue #1338 was created with comprehensive problem description covering both affected images, repository pattern analysis comparing correct vs incorrect naming conventions, clear solution with code examples, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for improving architecture detection in buildinputs tool d...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: scripts/buildinputs/dockerfile.go:35-35
Timestamp: 2025-07-10T15:39:23.433Z
Learning: jiridanek requested GitHub issue creation for improving architecture detection in buildinputs tool during PR #1320 review. Issue #1373 was successfully created on the second attempt with comprehensive problem description covering qemu-user s390x build failures where runtime.GOARCH returns host architecture instead of target architecture, detailed impact analysis, four solution options (environment variable detection, configuration parameter, platform detection logic, hybrid approach), clear acceptance criteria for multi-architecture support, phased implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for smart-open library s3/gcs backend compatibility concer...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T12:44:00.167Z
Learning: jiridanek requested GitHub issue creation for smart-open library S3/GCS backend compatibility concern in PR #1269. Issue #1289 was successfully created with comprehensive problem description, acceptance criteria, implementation guidance, testing approach, and proper context linking, following the established pattern of systematic issue tracking for technical improvements.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for smart-open library s3/gcs backend compatibility concer...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:33:55.209Z
Learning: jiridanek requested GitHub issue creation for smart-open library S3/GCS backend compatibility concern in PR #1269. Issue #1296 was successfully created with comprehensive problem description, acceptance criteria, implementation guidance, testing approach, and proper context linking, following the established pattern of systematic issue tracking for technical improvements.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek consistently requests github issue creation for technical improvements identified during c...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/nginx/root/usr/share/container-scripts/nginx/common.sh:1-3
Timestamp: 2025-07-03T12:07:19.365Z
Learning: jiridanek consistently requests GitHub issue creation for technical improvements identified during code reviews in opendatahub-io/notebooks, ensuring systematic tracking of code quality enhancements like shell script portability issues with comprehensive descriptions, solution options, and acceptance criteria.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for smart-open library compatibility concern in pr #1269, ...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T12:44:00.167Z
Learning: jiridanek requested GitHub issue creation for smart-open library compatibility concern in PR #1269, specifically about potential S3/GCS backend functionality loss due to smart-open dropping implicit extras since version 6.x. Issue creation follows established pattern of comprehensive problem descriptions, acceptance criteria, implementation guidance, and proper context linking.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for markdown linting improvements in pr #1269, specificall...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:01:18.625Z
Learning: jiridanek requested GitHub issue creation for markdown linting improvements in PR #1269, specifically addressing MD014 violations in README files and suggesting repository-wide markdown linter integration. Issue #1290 was created with comprehensive tooling recommendations, implementation phases, acceptance criteria, and systematic approach to documentation quality improvements.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for cgi script error handling improvements in codeserver/u...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/nginx/api/kernels/access.cgi:6-6
Timestamp: 2025-07-03T12:31:19.195Z
Learning: jiridanek requested GitHub issue creation for CGI script error handling improvements in codeserver/ubi9-python-3.12/nginx/api/kernels/access.cgi during PR #1269 review. Issue #1286 was created with comprehensive problem description, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for markdown linting improvements in pr #1269, specificall...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-07-03T13:01:18.625Z
Learning: jiridanek requested GitHub issue creation for markdown linting improvements in PR #1269, specifically addressing MD014 violations in README files while also suggesting repository-wide markdown linter integration. Issue #1290 was successfully created with comprehensive tooling recommendations, phased implementation plan, clear acceptance criteria, and systematic approach to documentation quality improvements, continuing the established pattern of systematic code quality enhancements.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for cgi script timestamp validation improvement identified...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/nginx/api/kernels/access.cgi:10-10
Timestamp: 2025-07-03T12:31:26.098Z
Learning: jiridanek requested GitHub issue creation for CGI script timestamp validation improvement identified during PR #1269 review, specifically for handling invalid timestamp data in codeserver/ubi9-python-3.12/nginx/api/kernels/access.cgi to prevent malformed output and improve reliability.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for shell script error handling improvements in codeserver...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/run-code-server.sh:20-40
Timestamp: 2025-07-03T12:27:09.739Z
Learning: jiridanek requested GitHub issue creation for shell script error handling improvements in codeserver/ubi9-python-3.12/run-code-server.sh create_dir_and_file function during PR #1269 review. Issue #1284 was created with comprehensive problem description, acceptance criteria, implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for cgi script timestamp validation improvement identified...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/nginx/api/kernels/access.cgi:10-10
Timestamp: 2025-07-03T12:31:26.098Z
Learning: jiridanek requested GitHub issue creation for CGI script timestamp validation improvement identified during PR #1269 review, specifically for handling invalid timestamp data in codeserver/ubi9-python-3.12/nginx/api/kernels/access.cgi to prevent malformed output and improve reliability. Issue #1287 was created with comprehensive problem descriptions, solution options, acceptance criteria, and proper context linking.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for mssql repo file hardcoding problem during pr #1320 rev...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1320
File: jupyter/pytorch/ubi9-python-3.12/Dockerfile.cuda:65-66
Timestamp: 2025-07-09T12:31:02.033Z
Learning: jiridanek requested GitHub issue creation for MSSQL repo file hardcoding problem during PR #1320 review. Issue #1357 was created with comprehensive problem description covering hardcoded x86_64 MSSQL repo files breaking multi-architecture builds across 6 affected Dockerfiles, detailed root cause analysis, three solution options with code examples, clear acceptance criteria, implementation guidance following established multi-architecture patterns, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for two nitpicks during pr #1588 review: comment wording i...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#0
File: :0-0
Timestamp: 2025-08-01T14:46:03.215Z
Learning: jiridanek requested GitHub issue creation for two nitpicks during PR #1588 review: comment wording improvement in ROCm TensorFlow Dockerfile and typo fix in Jupyter DataScience Dockerfile stage header. Issues #1589 and #1590 were successfully created with comprehensive problem descriptions, specific file locations and line numbers, clear before/after solutions, detailed acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for oc client installation permission problem in pytorch c...
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PR: opendatahub-io/notebooks#1333
File: runtimes/pytorch/ubi9-python-3.12/Dockerfile.cuda:17-25
Timestamp: 2025-07-09T08:07:30.628Z
Learning: jiridanek requested GitHub issue creation for oc client installation permission problem in PyTorch CUDA runtime Dockerfile during PR #1333 review. Issue #1356 was created with comprehensive problem description covering USER 1001 permission conflicts with root-owned /opt/app-root/bin directory, detailed impact analysis of build failures and non-executable binaries, current problematic code snippet, complete solution with user switching approach, clear acceptance criteria, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek requested github issue creation for bootstrapper code duplication problem in runtimes/rocm...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1333
File: runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py:1-769
Timestamp: 2025-07-08T19:35:49.482Z
Learning: jiridanek requested GitHub issue creation for bootstrapper code duplication problem in runtimes/rocm-pytorch/ubi9-python-3.12/utils/bootstrapper.py during PR #1333 review. After an initial failed attempt, issue #1349 was successfully created with comprehensive problem description covering maintenance overhead and consistency risks from duplicate implementations across 5 Python 3.12 runtime environments, four solution options (symlinks, import-based, template-based, direct shared import) with pros/cons analysis, clear acceptance criteria for consolidation and maintainability, step-by-step implementation guidance, and proper context linking, continuing the established pattern of systematic code quality improvements through detailed issue tracking.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek consistently creates comprehensive follow-up github issues from pr review comments in open...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb:22-29
Timestamp: 2025-07-02T18:27:51.097Z
Learning: jiridanek consistently creates comprehensive follow-up GitHub issues from PR review comments in opendatahub-io/notebooks, turning specific code quality concerns into systematic improvements tracked with proper context, acceptance criteria, and cross-references. Issue #1266 demonstrates this pattern by expanding a specific error handling concern in load_expected_versions() into a repository-wide improvement initiative.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek demonstrates excellent pattern recognition for identifying duplicated code issues across t...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1151
File: jupyter/tensorflow/ubi9-python-3.12/test/test_notebook.ipynb:31-34
Timestamp: 2025-07-01T07:03:05.385Z
Learning: jiridanek demonstrates excellent pattern recognition for identifying duplicated code issues across the opendatahub-io/notebooks repository. When spotting a potential problem in test notebooks, he correctly assesses that such patterns are likely replicated across multiple similar files rather than being isolated incidents, leading to more effective systematic solutions.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek efficiently identifies when coderabbit review suggestions are already covered by existing ...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1269
File: codeserver/ubi9-python-3.12/utils/process.sh:17-19
Timestamp: 2025-07-03T14:00:00.909Z
Learning: jiridanek efficiently identifies when CodeRabbit review suggestions are already covered by existing comprehensive issues, demonstrating excellent issue management and avoiding duplicate tracking of the same improvements across multiple locations.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: jiridanek consistently creates comprehensive follow-up github issues for security concerns raised du...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1259
File: jupyter/rocm/tensorflow/ubi9-python-3.12/Dockerfile.rocm:56-66
Timestamp: 2025-07-02T18:19:49.397Z
Learning: jiridanek consistently creates comprehensive follow-up GitHub issues for security concerns raised during PR reviews in opendatahub-io/notebooks, ensuring systematic tracking and resolution of supply-chain security improvements like GPG signature verification for package repositories.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
📚 Learning: in the opendatahub-io/notebooks repository, the test runner's python version (configured in github a...
Learnt from: jiridanek
PR: opendatahub-io/notebooks#1247
File: .github/workflows/build-notebooks-TEMPLATE.yaml:50-53
Timestamp: 2025-07-01T14:36:52.852Z
Learning: In the opendatahub-io/notebooks repository, the test runner's Python version (configured in GitHub Actions UV setup) intentionally doesn't need to match the Python version of the container images being tested. jiridanek's team uses Python 3.12 for running tests while images may use different Python versions (like 3.11), and this approach works fine since the test code is separate from the application code running inside the containers.
Applied to files:
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
🪛 Ruff (0.12.2)
tests/containers/architecture_utils.py
8-8: Expected 2 blank lines, found 1
Add missing blank line(s)
(E302)
21-21: Expected 2 blank lines, found 1
Add missing blank line(s)
(E302)
25-25: Expected 2 blank lines, found 1
Add missing blank line(s)
(E302)
tests/containers/workbenches/jupyterlab/jupyterlab_test.py
12-12: tests.containers.architecture_utils.container_architecture imported but unused
Remove unused import: tests.containers.architecture_utils.container_architecture
(F401)
59-59: Redefinition of unused container_architecture from line 12
(F811)
61-61: Missing whitespace after ','
Add missing whitespace
(E231)
⏰ Context from checks skipped due to timeout of 90000ms. You can increase the timeout in your CodeRabbit configuration to a maximum of 15 minutes (900000ms). (31)
- GitHub Check: build (jupyter-datascience-ubi9-python-3.12, 3.12, linux/amd64, false) / build
- GitHub Check: build (cuda-jupyter-pytorch-ubi9-python-3.12, 3.12, linux/amd64, false) / build
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- GitHub Check: build (jupyter-minimal-ubi9-python-3.11, 3.11, linux/s390x, false) / build
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🔇 Additional comments (3)
tests/containers/architecture_utils.py (3)
1-7: Well-structured module setup.Clear module documentation and appropriate imports for the architecture detection functionality.
9-19: Consider scope optimization in future iterations.The implementation correctly handles architecture detection with proper cleanup. However, the function scope means a container is started/stopped for each test using this fixture.
This aligns with Issue #1576 for future optimization to session-level caching to improve test performance.
21-27: Well-designed helper functions.Clean interface for architecture-specific feature checking with sensible defaults:
is_feature_supporteddefaults toTrue(assumes support unless explicitly limited)get_architecture_limitation_reasonprovides descriptive error messages with fallback
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/lgtm |
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Signed-off-by: Nishan Acharya <[email protected]>
… in tests Signed-off-by: Nishan Acharya <[email protected]>
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Hi @jiridanek , |
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/lgtm |
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/ok-to-test |
There was a problem hiding this comment.
/kfbuild odh-workbench-jupyter-tensorflow-rocm-py312-ubi9-on-pull-request
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@coderabbitai ptal |
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Tip For best results, initiate chat on the files or code changes. 🧩 Analysis chain@jiridanek I'll review the changes in this PR that disables PDF export for s390x architecture in Jupyter Minimal images. 🏁 Script executed: Length of output: 7176 The implementation looks excellent! This is a clean, well-structured solution that properly addresses the s390x compatibility issue. Here are my observations: ✅ Strong Implementation Points:
🔍 Minor Observation:The current architecture detection approach starts and stops a container for each test that needs architecture information. While functional, this could be optimized for performance if architecture detection becomes more widely used across tests. 🏁 Script executed: Length of output: 6933 Perfect! The analysis confirms this is a focused, well-implemented solution. Currently, the 🎯 Final Assessment:This PR excellently demonstrates:
The implementation follows best practices and solves the s390x compatibility issue effectively without adding unnecessary complexity. 🚀 Ready for MergeThis is a solid implementation that properly enables s390x builds for Jupyter Minimal images while maintaining functionality on other architectures. The code is clean, well-documented, and follows good engineering practices. Optional Follow-up: If architecture detection becomes more widely used across tests in the future, we could optimize the performance by implementing session-level caching or centralized architecture detection. Would you like me to create a follow-up issue for potential architecture detection efficiency improvements? ✏️ Learnings added
🧠 Learnings used |
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/approve |
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[APPROVALNOTIFIER] This PR is APPROVED This pull-request has been approved by: jiridanek The full list of commands accepted by this bot can be found here. The pull request process is described here
Needs approval from an approver in each of these files:
Approvers can indicate their approval by writing |
@jiridanek: The enhanced tests in the second commit don't pass. I've split out the core of the work (first commit) into a separate PR that I'm looking into merging
Summary
This PR disables PDF export functionality for s390x (IBM Z) architecture in Jupyter Minimal images for both Python 3.11 and 3.12 versions due to known compatibility issues with this feature on s390x.
Changes Made
1. Modified
jupyter/utils/install_pdf_deps.shuname -m2. Updated
ci/cached-builds/gen_gha_matrix_jobs.pyjupyter-minimal-ubi9-python-3.11andjupyter-minimal-ubi9-python-3.12toS390X_COMPATIBLEset3. Modified
tests/containers/workbenches/jupyterlab/jupyterlab_test.pytest_pdf_exporttestTesting
Impact
Validation
c.c:- @jiridanek
Summary by CodeRabbit
Bug Fixes
Chores