Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-13 23:51 UTC

datalayer / jupyter-ui

⚛️ React.js components 💯% compatible with 🪐 Jupyter.

TypeScript · Jupyter NotebookCustom license★ 464 stars⑂ 61 forkssince Oct 2021View on GitHub ↗
KindLibraryCommand-line toolWeb interfacehow this is determined

datalayer/jupyter-ui holds a health index of 80 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (90/100) and lowest on Vitality (51/100). It was last updated 1 day ago. A single contributor accounts for most of its recent work.

80
overall / 100
Excellent

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

80
Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met
Excellent80-92Strong across the board; minor gaps
Good65-79Healthy; gaps are limited and manageable
Moderate50-64Acceptable with notable gaps; review recommended
Weak35-49Material weaknesses across several areas
At Risk20-34Significant weaknesses; adoption warrants caution
Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 68 is calibrated to 80 on the published index scale (record calibration 2026-08-02).

Ownership

DatalayerOrganization
126 followers45 public repossince Jul 2013

This repository is backed by an organization — shared, accountable stewardship that can outlive any single maintainer.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIipyscriptpoints to another repo — not scored0.1.0.dev0-11577 days agojupyterwidgetsipython
npm@datalayer/jupyter-react2.0.1410,56414324 days agojupyterjupyterlabreact
PyPIipyreactivepoints to another repo — not scored0.1.0.dev0-11577 days agojupyterwidgetsipython
npm@datalayer/jupyter-lexical1.0.212,9383024 days agojupyterreactlexical
PyPIjupyter_react0.8.06215531 days ago
PyPIjupyter_lexical0.0.2-2531 days ago
npm@datalayer/jupyter-docusaurus-plugin1.0.03411317 days ago

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

51Moderate · 21% of overall
How it's scored
36/36Push recencylast push 1 days ago
22.2/36Commit cadence32/52 weeks with commits
17.7/18Commit volume93 commits in the last year
9/10OpenSSF Scorecard: Maintained10 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 9
Inputs used
commits_last_year93
human_commit_share1
days_since_last_push1
active_weeks_last_year32
How it's scored
0/27Ships releasesno releases published
0/36Release recencyno releases
0/27Release cadenceno releases
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count0
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

65Good · 17% of overall
How it's scored
43.2/60Stars464 stars
14.8/25Forks61 forks
5.6/15Watchers11 watchers
Inputs used
forks61
stars464
watchers11
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
16.9/22.5Licenselicense file present, not a recognized license
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges10
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateno
How it's scored
55.2/80Monthly downloads13,843 downloads/month across npm
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packages@datalayer/jupyter-react, @datalayer/jupyter-lexical, @datalayer/jupyter-docusaurus-plugin
dependents
ecosystemsnpm
total_downloads
monthly_downloads13,843
unverified_packages_excludedjupyter_react, jupyter_lexical
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

66Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
3.1/22.5Commit distributiontop contributor authored 86% of commits
13.5/13.5Contributor breadth15 contributors
10/10OpenSSF Scorecard: Contributorsproject has 20 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled15
top_contributor_share0.862
How it's scored
34.5/42Issue resolution82% of issues closed
26.4/30PR acceptance206/234 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs206
open_issues46
closed_issues211
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.821
closed_unmerged_prs28
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domain
15.1/25Owner reach126 followers of datalayer
24.1/25Track record45 public repos, account ~13 yr old
Inputs used
followers126
owner_typeOrganization
is_verifiedno
owner_logindatalayer
public_repos45
account_age_days4,809

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable5 package(s) on npm, pypi
35/35Publish recencylatest publish 17 days ago
20/20Version history143 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packages@datalayer/jupyter-react, @datalayer/jupyter-lexical, jupyter_react, jupyter_lexical, @datalayer/jupyter-docusaurus-plugin
ecosystemsnpm, pypi
any_deprecatedno
min_days_since_publish17

Engineering Quality

Are baseline engineering and documentation practices in place?

90Excellent · 19% of overall
How it's scored
24/24CI workflows6 workflow(s)
24/24Tests present
16/16Linter config.eslintrc.js, .eslintrc.json, eslint.config.js, packages/react/package.json ("eslintConfig", "prettier")
0/9.6Pre-commit hooks
6.4/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests7 out of 7 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configno

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://jupyter-ui.datalayer.tech
10/10Repository description
10/10Topics12 topics
0/10Wiki
Inputs used
topicsjupyter, reactjs, datalayer, ipywidgets, ui, data, data-product, data-visualisation, jupyterlab, lumino, notebook, data-science
has_wikino
homepagehttps://jupyter-ui.datalayer.tech
docs_sitehttps://jupyter-ui.datalayer.tech
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

66Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
2.2/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
2.5/2.5CI-Tests7 out of 7 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 0/30 approved changesets -- score normalized to 0
2.5/2.5Contributorsproject has 20 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.2/2.5Licenselicense file detected
6.8/7.5Maintained10 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 9
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
4/5SASTSAST tool is not run on all commits -- score normalized to 8
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.7
Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages20
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:ipyscript@0.1.0.dev0 runtime dependency closure — what installing the published package pulls in — 20 packages. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

86Excellent · 4% of overall
How it's scored
45/45Agent instructionsCLAUDE.md
0/15Machine-readable docs (llms.txt)
40/40Legible commit history87 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.87
agent_instruction_filesCLAUDE.md
agent_instruction_max_bytes7,207
How it's scored
18/18One-command bootstrapMakefile, docs/Makefile, examples/vite/Makefile, packages/docusaurus-plugin/Makefile, packages/embed/Makefile, packages/ipyreactive/docs/Makefile, packages/ipyscript/docs/Makefile, packages/lexical/Makefile, packages/react/Makefile, storybook/Makefile
22/22Automated tests
11/11Lint / format config.eslintrc.js, .eslintrc.json, eslint.config.js, packages/react/package.json ("eslintConfig", "prettier")
11/11Static type checkingdocs/tsconfig.json, examples/lexical/tsconfig.json, examples/next-js/tsconfig.json, examples/vite/tsconfig.json, packages/docusaurus-plugin/tsconfig.json, packages/embed/tsconfig.json, packages/ipyreactive/tsconfig.json, packages/ipyscript/tsconfig.json, packages/lexical/tsconfig.json, packages/react/tsconfig.json, storybook/tsconfig.json, tsconfig.json
10/10Reproducible environmentdevcontainer, Dockerfile
4/10Demonstrated agent practice2 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileyes
typed_languageyes
bootstrap_filesMakefile, docs/Makefile, examples/vite/Makefile, packages/docusaurus-plugin/Makefile, packages/embed/Makefile, packages/ipyreactive/docs/Makefile, packages/ipyscript/docs/Makefile, packages/lexical/Makefile, packages/react/Makefile, storybook/Makefile
has_devcontaineryes
has_linter_configyes
typecheck_configsdocs/tsconfig.json, examples/lexical/tsconfig.json, examples/next-js/tsconfig.json, examples/vite/tsconfig.json, packages/docusaurus-plugin/tsconfig.json, packages/embed/tsconfig.json, packages/ipyreactive/tsconfig.json, packages/ipyscript/tsconfig.json, packages/lexical/tsconfig.json, packages/react/tsconfig.json, storybook/tsconfig.json, tsconfig.json
agent_commit_share0.02
toolchain_manifests
dependency_bot_commit_share0
How it's scored
45/45Type-checkable codeTypeScript (statically typed)
54.9/55Manageable file sizes1/788 source files over 60KB
Inputs used
primary_languageTypeScript
largest_source_bytes60,922
source_files_sampled788
oversized_source_files1
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesdemos, examples, notebooks
Inputs used
example_dirsdemos, examples, notebooks
has_mcp_signalno
api_schema_files
interfaces_expected_of
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

464GitHub stars
15contributors
93commits, last 12 months
1days since last push
0releases
1bus factor
46open issues
npmpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Could not fetch npm package '@datalayer/jupyter-ui-storybook' from its registry
  • Could not fetch npm package '@datalayer/jupyter-embed' from its registry
  • pypi package 'ipyscript' points at a different repository (https://github.com/datalayer/ipyscript); excluded from ecosystem scoring
  • pypi package 'ipyreactive' points at a different repository (https://github.com/datalayer/ipyreactive); excluded from ecosystem scoring
  • pypi download statistics for 'jupyter_lexical' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced

More detail

Star and fork history 0 ★ / 61 ⇿
0Stars
61Forks

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

01020304050606032022-022024-022026-02

Each point covers 4 days.

OpenSSF Scorecard 5.7 / 10
5.7aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-09-13 23:51 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests7 out of 7 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
10Contributorsproject has 20 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
9Maintained10 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 9
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
8SASTSAST tool is not run on all commits -- score normalized to 8
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 160
RegistryPackageVersion constraintManifest
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npm@primer/react^37.31.0packages/embed/package.json
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npmy-protocols^1.0.5packages/react/package.json
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npmzustand^4.4.1packages/react/package.json
PyPIdatalayer_corepackages/react/pyproject.toml
PyPIjupyter_server>=2.10,<3packages/react/pyproject.toml
All dependencies 329

Full resolved dependency set from the GitHub dependency graph: 147 direct and 182 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPIjupyter-serverdirect
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PyPIhatchling1.21.1indirect
PyPIipywidgetsindirect
PyPIjupyter-packaging0.7.9indirect
PyPIjupyter-sphinxindirect
PyPIjupyterlabindirect
PyPIjupyterlab4.1.0indirect
PyPInbsphinxindirect
PyPInbsphinx-linkindirect
PyPInbvalindirect
PyPIpypandocindirect
PyPIpytestindirect
PyPIpytest-check-linksindirect
PyPIpytest-covindirect
PyPIrecommonmarkindirect
PyPIsetuptoolsindirect
PyPIsphinxindirect
PyPIsphinx-rtd-themeindirect
Dependency advisories 0

Installing pypi:ipyscript@0.1.0.dev0 pulls in 20 packages, direct and transitive: 0 carry known advisories, of which 0 are direct dependencies.

No known advisories affect the assessed dependencies.

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI, npm.