Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-08 19:18 UTC

jupyterhub / jupyter-server-proxy

Jupyter notebook server extension to proxy web services.

PythonBSD-3-Clause★ 399 stars⑂ 152 forkssince Oct 2016View on GitHub ↗
KindLibraryCommand-line toolNetwork servicehow this is determined
#jupyter-notebook#jupyter#jupyterhub#proxy#binder

jupyterhub/jupyter-server-proxy holds a health index of 89 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (96/100) and lowest on Security (62/100). It was last updated 3 days ago. 3 contributors account for most of its recent work.

89
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.

89
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 75 is calibrated to 89 on the published index scale (record calibration 2026-08-02).

Ownership

JupyterHubOrganization
488 followers76 public repossince Mar 2016

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIjupyter_server_proxy4.5.0-38129 days agojupyterjupyterlabjupyterlab-extension
npm@jupyterhub/jupyter-server-proxy4.5.0649128 days agojupyterjupyterlabjupyterlab-extension

Metrics by category

Vitality

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

67Good · 21% of overall

Development activity

72Good
How it's scored
36/36Push recency — last push 3 days ago
14.5/36Commit cadence — 21/52 weeks with commits
16.9/18Commit volume — 75 commits in the last year
5/10OpenSSF Scorecard: Maintained — 7 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
Inputs used
commits_last_year75
human_commit_share0.74
days_since_last_push3
active_weeks_last_year21

Release discipline

60Moderate
How it's scored
27/27Ships releases — 2 releases published
0/36Release recency — latest release 2,798 days ago
27/27Release cadence — a release every ~0 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count2
latest_release_tagv0.8.8
releases_from_tagsno
days_since_latest_release2,798
mean_days_between_releases0
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?

66Good · 17% of overall

Popularity & adoption

67Good
How it's scored
42.2/60Stars — 399 stars
18.2/25Forks — 152 forks
6.7/15Watchers — 17 watchers
Inputs used
forks152
stars399
watchers17
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (BSD-3-Clause)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges5
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io
has_pull_request_templateyes

Ecosystem adoption (downloads)

30At Risk
How it's scored
24.2/80Monthly downloads — 64 downloads/month across npm, pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesjupyter_server_proxy, @jupyterhub/jupyter-server-proxy
dependents—
ecosystemsnpm, pypi
total_downloads—
monthly_downloads64
unverified_packages_excluded—
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?

84Excellent · 23% of overall

Maintainer resilience (bus factor)

77Good
How it's scored
36/54Bus factor — 3 contributor(s) cover half of all commits
17.5/22.5Commit distribution — top contributor authored 22% of commits
13.5/13.5Contributor breadth — 72 contributors
10/10OpenSSF Scorecard: Contributors — project has 124 contributing companies or organizations
Inputs used
bus_factor3
contributors_sampled72
top_contributor_share0.223

Issue & PR responsiveness

71Good
How it's scored
27.5/42Issue resolution — 66% of issues closed
25.6/30PR acceptance — 292/342 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
9/15OpenSSF Scorecard: Code-Review — Found 6/10 approved changesets -- score normalized to 6
Inputs used
merged_prs292
open_issues78
closed_issues148
prs_merged_7d0
prs_decided_7d0
prs_merged_30d1
prs_decided_30d1
issue_closed_ratio0.655
closed_unmerged_prs50
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.

Ownership & stewardship

93Exceptional
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
19.3/25Owner reach — 488 followers of jupyterhub
25/25Track record — 76 public repos, account ~10 yr old
Inputs used
followers488
owner_typeOrganization
is_verified—
owner_loginjupyterhub
public_repos76
account_age_days3,795
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 2 package(s) on npm, pypi
35/35Publish recency — latest publish 128 days ago
20/20Version history — 38 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesjupyter_server_proxy, @jupyterhub/jupyter-server-proxy
ecosystemsnpm, pypi
any_deprecatedno
min_days_since_publish128

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 3 workflow(s)
24/24Tests present
16/16Linter config — .flake8
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 13 out of 13 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://jupyter-server-proxy.readthedocs.io
10/10Repository description
10/10Topics — 5 topics
10/10Wiki
Inputs used
topicsjupyter-notebook, jupyter, jupyterhub, proxy, binder
has_wikiyes
homepagehttps://jupyter-server-proxy.readthedocs.io
docs_sitehttps://jupyter-server-proxy.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

62Moderate · 16% of overall

Security posture

52Moderate
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 13 out of 13 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
4.5/7.5Code-Review — Found 6/10 approved changesets -- score normalized to 6
2.5/2.5Contributors — project has 124 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
3.8/7.5Maintained — 7 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
5/5Packaging — packaging workflow detected
1/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 2
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 32 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate5.2
Excluded from scoring (no data or not applicable): Branch-Protection, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages66
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:jupyter_server_proxy@4.5.0 runtime dependency closure — what installing the published package pulls in — 66 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.

64Moderate · 4% of overall

Agent context & guidance

32At Risk
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
32.4/40Legible commit history — 45 of 74 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.608
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

82Excellent
How it's scored
18/18One-command bootstrap — docs/Makefile
22/22Automated tests
11/11Lint / format config — .flake8
11/11Static type checking — labextension/tsconfig.json
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
8/8Automated maintenance — 15 of the last 100 commits are automated dependency updates
2/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 2
Inputs used
has_nixno
has_testsyes
lockfilesyarn.lock
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configslabextension/tsconfig.json
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0.15

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (labextension/tsconfig.json)
55/55Manageable file sizes — 0/37 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes41,127
source_files_sampled37
oversized_source_files0

Key facts

399GitHub stars
72contributors
75commits, last 12 months
3days since last push
2releases
3bus factor
78open issues
npm, PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 152 ⇿
0Stars
152Forks
2Releases

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.

025507510012515014942017-072021-122026-06
Major 0Minor 0Patch 2

Each point covers 9 days.

OpenSSF Scorecard 5.2 / 10
5.2aggregate

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 · 2026-08-08 19:18 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal error: error during branchesHandler.setup: internal error: some github tokens can't read classic branch protection rules: https://github.com/ossf/scorecard-action/blob/main/docs/authentication/fine-grained-auth-token.md
10CI-Tests13 out of 13 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
6Code-ReviewFound 6/10 approved changesets -- score normalized to 6
10Contributorsproject has 124 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
5Maintained7 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 5
10Packagingpackaging workflow detected
2Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 2
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities32 existing vulnerabilities detected
Direct dependencies 9
RegistryPackageVersion constraintManifest
npm@jupyterlab/application^3.0 || ^4.0labextension/package.json
npm@jupyterlab/filebrowser^3.0 || ^4.0labextension/package.json
npm@jupyterlab/launcher^3.0 || ^4.0labextension/package.json
PyPIaiohttp—pyproject.toml
PyPIimportlib_metadata>=4.8.3pyproject.toml
PyPIjupyter-server>=1.24.0pyproject.toml
PyPIsimpervisor>=1.0.0pyproject.toml
PyPItornado>=6.1.0pyproject.toml
PyPItraitlets>= 5.1.0pyproject.toml
All dependencies 589

Full resolved dependency set from the GitHub dependency graph: 9 direct and 580 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
npm@jupyterlab/application4.5.6direct
npm@jupyterlab/filebrowser4.5.6direct
npm@jupyterlab/launcher4.5.6direct
PyPIaiohttp—direct
PyPIimportlib-metadata—direct
PyPIjupyter-server—direct
PyPIsimpervisor—direct
PyPItornado—direct
PyPItraitlets—direct
npm@arcanis/slice-ansi1.1.1indirect
npm@babel/code-frame7.29.0indirect
npm@babel/helper-validator-identifier7.28.5indirect
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npm@fortawesome/fontawesome-free5.15.4indirect
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npm@jridgewell/sourcemap-codec1.5.5indirect
npm@jridgewell/trace-mapping0.3.31indirect
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npm@jupyter/web-components0.16.7indirect
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npm@jupyterlab/rendermime4.5.6indirect
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npm@jupyterlab/services7.5.6indirect
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npm@jupyterlab/statedb4.5.6indirect
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PyPIjupyter-server-proxy—indirect
PyPImyst-parser—indirect
PyPIsphinx-autobuild—indirect
PyPIsphinx-book-theme—indirect
PyPIsphinx-copybutton—indirect
PyPIsphinxext-opengraph—indirect
PyPIsphinxext-rediraffe—indirect
Dependency advisories 0

Installing pypi:jupyter_server_proxy@4.5.0 pulls in 66 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.

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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 v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI, npm.