The single home for Jupyter notebook testing: wires parameterized execution (papermill), output regression (nbval), function-level unit tests (testbook), output stripping (nbstripout), and artifact upload into one working GitHub Actions CI pipeline, with per-tool depth for papermill (parameters tag, CLI/API, sweeps) and nbval (strict/lax modes, per-cell markers, sanitize config) in references/. Includes a notebook PR review checklist covering untested notebooks, --nbval-lax misuse, hardcoded credentials, non-deterministic output cells, missing parameters tags, and committed outputs, with BLOCK / WARN / INFO severities and a BLOCK-or-PASS verdict. Use when notebooks must run as parameterized regression jobs in CI, when a repo ships .ipynb files whose outputs must stay stable, or when a PR that adds or modifies notebooks needs a structured quality review.
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{
"name": "testland/notebook-ci-pipeline-author",
"description": "The single home for Jupyter notebook testing: wires parameterized execution (papermill), output regression (nbval), function-level unit tests (testbook), output stripping (nbstripout), and artifact upload into one working GitHub Actions CI pipeline, with per-tool depth for papermill (parameters tag, CLI/API, sweeps) and nbval (strict/lax modes, per-cell markers, sanitize config) in references/. Includes a notebook PR review checklist covering untested notebooks, --nbval-lax misuse, hardcoded credentials, non-deterministic output cells, missing parameters tags, and committed outputs, with BLOCK / WARN / INFO severities and a BLOCK-or-PASS verdict. Use when notebooks must run as parameterized regression jobs in CI, when a repo ships .ipynb files whose outputs must stay stable, or when a PR that adds or modifies notebooks needs a structured quality review.",
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"version": "1.2.9"
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