Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 04:19 UTC

jupyter-incubator / sparkmagic

Jupyter magics and kernels for working with remote Spark clusters

PythonCustom license★ 1,366 stars⑂ 443 forkssince Sep 2015View on GitHub ↗
KindNetwork serviceNotebookhow this is determined

jupyter-incubator/sparkmagic holds a health index of 46 out of 100, placing it in the Weak band. It scores highest on Community & Adoption (75/100) and lowest on Vitality (25/100). It was last updated 337 days ago. 2 contributors account for most of its recent work.

46
overall / 100
Weak

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.

46
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 53 is calibrated to 54 on the published index scale (record calibration 2026-08-02).

Ownership

jupyter-incubatorOrganization
31 followers4 public repossince Aug 2015

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

Metrics by category

Vitality

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

25At Risk · 21% of overall
How it's scored
3.6/36Push recencylast push 337 days ago
0.7/36Commit cadence1/52 weeks with commits
2.7/18Commit volume1 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year1
human_commit_share0.73
days_since_last_push337
active_weeks_last_year1
How it's scored
27/27Ships releases18 releases published
7.2/36Release recencylatest release 401 days ago
12.6/27Release cadencea release every ~129.8 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count18
latest_release_tag0.23.0
releases_from_tagsno
days_since_latest_release401
mean_days_between_releases129.8
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?

75Good · 17% of overall
How it's scored
50.9/60Stars1,366 stars
22/25Forks443 forks
9.1/15Watchers44 watchers
Inputs used
forks443
stars1,366
watchers44
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
0/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges2
has_contributingno
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesshields.io, travis-ci.org
has_pull_request_templateyes

Sustainability & Governance

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

67Good · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
15.1/22.5Commit distributiontop contributor authored 33% of commits
13.5/13.5Contributor breadth53 contributors
10/10OpenSSF Scorecard: Contributorsproject has 10 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled53
top_contributor_share0.33
How it's scored
29.2/42Issue resolution70% of issues closed
24.1/30PR acceptance385/480 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
3/15OpenSSF Scorecard: Code-ReviewFound 2/10 approved changesets -- score normalized to 2
Inputs used
merged_prs385
open_issues135
closed_issues307
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.695
closed_unmerged_prs95
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 domainverified-domain status not read for this organization
10.8/25Owner reach31 followers of jupyter-incubator
17.1/25Track record4 public repos, account ~10 yr old
Inputs used
followers31
owner_typeOrganization
is_verified
owner_loginjupyter-incubator
public_repos4
account_age_days4,003
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

53Moderate · 19% of overall
How it's scored
24/24CI workflows5 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 7 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

60Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics12 topics
10/10Wiki
Inputs used
topicsspark, kernel, cluster, livy, magic, sql-query, pandas-dataframe, jupyter, pyspark, kerberos, notebook, jupyter-notebook
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

49Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
0/2.5CI-Tests0 out of 7 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1.5/7.5Code-ReviewFound 2/10 approved changesets -- score normalized to 2
2.5/2.5Contributorsproject has 10 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
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
5/5Packagingpackaging workflow detected
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
4.5/5Security-Policysecurity policy file detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities65 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate4.5
Excluded from scoring (no data or not applicable): Branch-Protection, Signed-Releases. Remaining weights renormalized.
How it's scored
16/35Direct dependencies free of known advisories1 affected: pytest 8.3.3 (moderate 6.8)
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
34.2/40No advisories left outstanding1 advisory-carrying package(s) unaddressed past 90 days; oldest published 202 days ago
Inputs used
sourceosv
advisories122
affected_packages14
assessed_packages115
unassessed_packages14
affected_by_severityhigh 8, moderate 5, low 1
direct_affected_packages1
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories. Remaining weights renormalized. Matched 115 resolved dependencies against OSV. 14 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. This repository publishes no package the index resolves, so the repository dependency graph was assessed instead. That graph mixes development and test pins with shipped dependencies, so only the declared runtime dependencies are scored; transitive findings are reported as context and excluded from the score. 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.

42Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history57 of 73 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.781
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
10/10Reproducible environmentDockerfile, lockfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance27 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilespoetry.lock
has_dockerfileyes
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.27
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/128 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes35,450
source_files_sampled128
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)
0/20MCP server
40/40Runnable examplesexamples, notebooks
Inputs used
example_dirsexamples, notebooks
has_mcp_signalno
api_schema_files
interfaces_expected_ofnetwork-service

Key facts

1,366GitHub stars
53contributors
1commits, last 12 months
337days since last push
18releases
2bus factor
135open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • Could not fetch pypi package 'development' from its registry
  • Advisory severity resolved for 120 of 122 advisories (lookup cap); the remainder are reported as unknown severity

More detail

Star and fork history 0 ★ / 443 ⇿
0Stars
443Forks
18Releases

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.

010020030040050042172015-092020-112026-01
Major 0Minor 10Patch 8

Each point covers 10 days.

OpenSSF Scorecard 4.5 / 10
4.5aggregate

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 · 2026-08-13 04:18 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
0CI-Tests0 out of 7 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 2/10 approved changesets -- score normalized to 2
10Contributorsproject has 10 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
9Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities65 existing vulnerabilities detected
Direct dependencies 7
RegistryPackageVersion constraintManifest
PyPIhdijupyterutilspyproject.toml
PyPIautovizwidgetpyproject.toml
PyPIsparkmagicpyproject.toml
PyPInumpy^1.24.4pyproject.toml
PyPIpandas^2.0.3pyproject.toml
PyPIpytest^8.3.3pyproject.toml
PyPImock^5.1.0pyproject.toml
All dependencies 129

Full resolved dependency set from the GitHub dependency graph: 8 direct and 121 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIautovizwidgetdirect
PyPIhdijupyterutilsdirect
PyPImock5.1.0direct
PyPInumpydirect
PyPInumpy1.24.4direct
PyPIpandasdirect
PyPIpandas2.0.3direct
PyPIpytest8.3.3direct
PyPIanyio3.6.2indirect
PyPIappnope0.1.3indirect
PyPIargon2-cffi21.3.0indirect
PyPIargon2-cffi-bindings21.2.0indirect
PyPIarrow1.2.3indirect
PyPIasttokens2.2.1indirect
PyPIattrs22.2.0indirect
PyPIbackcall0.2.0indirect
PyPIbeautifulsoup44.11.1indirect
PyPIbleach5.0.1indirect
PyPIcertifi2024.7.4indirect
PyPIcffi1.15.1indirect
PyPIcharset-normalizer2.1.1indirect
PyPIcolorama0.4.6indirect
PyPIcomm0.1.2indirect
PyPIcryptography43.0.1indirect
PyPIdebugpy1.6.4indirect
PyPIdecorator5.1.1indirect
PyPIdefusedxml0.7.1indirect
PyPIentrypoints0.4indirect
PyPIexceptiongroup1.1.0indirect
PyPIexecuting1.2.0indirect
PyPIfastjsonschema2.16.2indirect
PyPIfqdn1.5.1indirect
PyPIgssapi1.8.2indirect
PyPIidna3.7indirect
PyPIimportlib-metadata6.0.0indirect
PyPIimportlib-resources5.10.2indirect
PyPIiniconfig1.1.1indirect
PyPIipykernelindirect
PyPIipykernel6.19.4indirect
PyPIipythonindirect
PyPIipython8.10.0indirect
PyPIipython-genutils0.2.0indirect
PyPIipywidgetsindirect
PyPIipywidgets8.0.4indirect
PyPIisoduration20.11.0indirect
PyPIjedi0.18.2indirect
PyPIjinja23.1.3indirect
PyPIjsonpointer2.3indirect
PyPIjsonschema4.17.3indirect
PyPIjupyterindirect
PyPIjupyter1.0.0indirect
PyPIjupyter-client7.4.8indirect
PyPIjupyter-console6.4.4indirect
PyPIjupyter-core5.1.1indirect
PyPIjupyter-events0.5.0indirect
PyPIjupyter-server2.0.6indirect
PyPIjupyter-server-terminals0.4.3indirect
PyPIjupyterlab-pygments0.2.2indirect
PyPIjupyterlab-widgets3.0.5indirect
PyPIkrb50.4.1indirect
PyPImarkupsafe2.1.1indirect
PyPImatplotlib-inline0.1.6indirect
PyPImistune2.0.4indirect
PyPInbclassic0.4.8indirect
PyPInbclient0.7.2indirect
PyPInbconvert7.2.7indirect
PyPInbformat5.7.1indirect
PyPInest-asyncioindirect
PyPInest-asyncio1.5.5indirect
PyPInose1.3.7indirect
PyPInotebookindirect
PyPInotebook6.5.2indirect
PyPInotebook-shim0.2.2indirect
PyPIpackaging22.0indirect
PyPIpandocfilters1.5.0indirect
PyPIparso0.8.3indirect
PyPIpexpect4.8.0indirect
PyPIpickleshare0.7.5indirect
PyPIpkgutil-resolve-name1.3.10indirect
PyPIplatformdirs2.6.2indirect
PyPIplotlyindirect
PyPIplotly5.24.1indirect
PyPIpluggy1.5.0indirect
PyPIprometheus-client0.15.0indirect
PyPIprompt-toolkit3.0.36indirect
PyPIpsutil5.9.4indirect
PyPIptyprocess0.7.0indirect
PyPIpure-eval0.2.2indirect
PyPIpy1.11.0indirect
PyPIpycparser2.21indirect
PyPIpygments2.15.0indirect
PyPIpyrsistent0.19.3indirect
PyPIpyspnego0.7.0indirect
PyPIpython-dateutil2.8.2indirect
PyPIpython-json-logger2.0.4indirect
PyPIpytz2022.7indirect
PyPIpywin32305indirect
PyPIpywinpty2.0.9indirect
PyPIpyyaml6.0indirect
PyPIpyzmq24.0.1indirect
PyPIqtconsole5.4.0indirect
PyPIqtpy2.3.0indirect
PyPIrequestsindirect
PyPIrequests2.32.3indirect
PyPIrequests-kerberosindirect
PyPIrequests-kerberos0.14.0indirect
PyPIrfc3339-validator0.1.4indirect
PyPIrfc3986-validator0.1.1indirect
PyPIsend2trash1.8.0indirect
PyPIsix1.16.0indirect
PyPIsniffio1.3.0indirect
PyPIsoupsieve2.3.2.post1indirect
PyPIstack-data0.6.2indirect
PyPItenacity8.1.0indirect
PyPIterminado0.17.1indirect
PyPItinycss21.2.1indirect
PyPItomli2.0.1indirect
PyPItornadoindirect
PyPItornado6.4.2indirect
PyPItraitlets5.8.0indirect
PyPItzdata2024.2indirect
PyPIuri-template1.2.0indirect
PyPIurllib31.26.19indirect
PyPIwcwidth0.2.5indirect
PyPIwebcolors1.12indirect
PyPIwebencodings0.5.1indirect
PyPIwebsocket-client1.4.2indirect
PyPIwidgetsnbextension4.0.5indirect
PyPIzipp3.19.1indirect
Dependency advisories 14

This repository publishes no package the index resolves, so its own dependency graph was assessed — 115 packages, which also include development and test pins that never ship: 14 carry known advisories, of which 1 are direct. 14 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
cryptography43.0.1indirecthigh1149.0.0
jinja23.1.3indirecthigh83.1.6
jupyter-core5.1.1indirecthigh25.8.1
jupyter-server2.0.6indirecthigh202.20.0
mistune2.0.4indirecthigh283.3.0
soupsieve2.3.2.post1indirecthigh42.8.4
tornado6.4.2indirecthigh206.5.7
urllib31.26.19indirecthigh102.7.0
pytest8.3.3directmoderate29.0.3
bleach5.0.1indirectmoderate26.4.0
idna3.7indirectmoderate23.15
nbconvert7.2.7indirectmoderate67.17.1
requests2.32.3indirectmoderate42.33.0
pygments2.15.0indirectlow32.20.0

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 v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics.