Public record
Software health reportschema 0.26.0 · metrics 2.10.0 · 2026-07-22 01:43 UTC

nipy / nibabel

Python package to access a cacophony of neuro-imaging file formats

PythonCustom license★ 781 stars⑂ 290 forkssince Jul 2010View on GitHub ↗

nipy/nibabel holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (96/100) and lowest on Security (69/100). It was last updated today. 2 contributors account for most of its recent work.

94
overall / 100
Exceptional

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.

94
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 81 is calibrated to 94 on the published index scale (record calibration 2026-08-02).

Ownership

NIPY developersOrganization
220 followers38 public repossince Mar 2010

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPInibabel5.4.2-48132 days ago

Metrics by category

Vitality

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

79Good · 21% of overall
How it's scored
36/36Push recencylast push 0 days ago
18.7/36Commit cadence27/52 weeks with commits
18/18Commit volume283 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year283
human_commit_share0.82
days_since_last_push0
active_weeks_last_year27
How it's scored
27/27Ships releases46 releases published
27/36Release recencylatest release 133 days ago
12.6/27Release cadencea release every ~124.7 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count46
latest_release_tag5.4.1
releases_from_tagsno
days_since_latest_release133
mean_days_between_releases124.7
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?

77Good · 17% of overall
How it's scored
46.9/60Stars781 stars
20.5/25Forks290 forks
8.1/15Watchers30 watchers
Inputs used
forks290
stars781
watchers30
growth_stateorganic
growth_factor_pct100
How it's scored
22.5/22.5README
16.9/22.5Licenselicense file present, not a recognized license
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services
has_pull_request_templateno

Sustainability & Governance

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

81Excellent · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
15.3/22.5Commit distributiontop contributor authored 32% of commits
13.5/13.5Contributor breadth98 contributors
10/10OpenSSF Scorecard: Contributorsproject has 107 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled98
top_contributor_share0.32
How it's scored
33.1/42Issue resolution79% of issues closed
25.8/30PR acceptance798/929 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
10.5/15OpenSSF Scorecard: Code-ReviewFound 7/9 approved changesets -- score normalized to 7
Inputs used
merged_prs798
open_issues116
closed_issues433
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0.789
closed_unmerged_prs131
first_time_authors_30d
first_time_prs_merged_30d
first_time_prs_decided_30d
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
16.9/25Owner reach220 followers of nipy
23.6/25Track record38 public repos, account ~16 yr old
Inputs used
followers220
owner_typeOrganization
is_verified
owner_loginnipy
public_repos38
account_age_days5,957
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 132 days ago
20/20Version history48 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesnibabel
ecosystemspypi
any_deprecatedno
min_days_since_publish132

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall
How it's scored
24/24CI workflows4 workflow(s)
24/24Tests present
16/16Linter configtox.ini
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests17 out of 17 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 sitehttp://nipy.org/nibabel/
10/10Repository description
10/10Topics14 topics
10/10Wiki
Inputs used
topicspython, neuroimaging, brain-imaging, nifti, gifti, cifti-2, streamlines, data-formats, dicom, tck, trk, afni-brik-head, ecat, minc
has_wikiyes
homepagehttp://nipy.org/nibabel/
docs_sitehttp://nipy.org/nibabel/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

69Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
2.5/2.5CI-Tests17 out of 17 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
5.2/7.5Code-ReviewFound 7/9 approved changesets -- score normalized to 7
2.5/2.5Contributorsproject has 107 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
7.5/7.5Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
5/5Packagingpackaging workflow detected
5/5Pinned-Dependenciesall dependencies are pinned
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities15 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6.1
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 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_packages2
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:nibabel@5.4.2 runtime dependency closure — what installing the published package pulls in — 2 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.

75Good · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
39.7/40Legible commit history61 of 82 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.744
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapMakefile, doc/Makefile
22/22Automated tests
11/11Lint / format configtox.ini
11/11Static type checkingnibabel/py.typed
10/10Reproducible environmentlockfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance15 of the last 100 commits are automated dependency updates
10/10OpenSSF Scorecard: Pinned-Dependenciesall dependencies are pinned
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile, doc/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configsnibabel/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.15
How it's scored
27/45Type-checkable codePython with type-check config (nibabel/py.typed)
54.3/55Manageable file sizes3/245 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes95,350
source_files_sampled245
oversized_source_files3
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 examplesnotebooks
Inputs used
example_dirsnotebooks
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

781GitHub stars
98contributors
283commits, last 12 months
0days since last push
46releases
2bus factor
116open issues
PyPIpackage ecosystems

More detail

Star and fork history 781 ★ / 290 ⇿
781Stars
290Forks
46Releases

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.

0200400600800781282242010-072018-072026-07
Major 5Minor 14Patch 24

Each point covers 15 days.

OpenSSF Scorecard 6.1 / 10
6.1aggregate

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 · 2026-07-22 01:42 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-Tests17 out of 17 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
7Code-ReviewFound 7/9 approved changesets -- score normalized to 7
10Contributorsproject has 107 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense file detected
10Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
10Pinned-Dependenciesall dependencies are pinned
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
0Vulnerabilities15 existing vulnerabilities detected
Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPInumpy>=1.25pyproject.toml
PyPIpackaging>=20pyproject.toml
PyPIimportlib_resources>=5.12pyproject.toml
PyPItyping_extensions>=4.6pyproject.toml
All dependencies 92

Full resolved dependency set from the GitHub dependency graph: 5 direct and 87 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIimportlib-resources7.1.0direct
PyPInumpy2.2.6direct
PyPInumpy2.4.4direct
PyPIpackaging26.2direct
PyPItyping-extensions4.15.0direct
PyPIaccessible-pygments0.0.5indirect
PyPIalabaster1.0.0indirect
PyPIast-serialize0.4.0indirect
PyPIbabel2.18.0indirect
PyPIbackports-zstd1.5.0indirect
PyPIbeautifulsoup44.14.3indirect
PyPIcachetools7.1.1indirect
PyPIcertifi2026.4.22indirect
PyPIcfgv3.5.0indirect
PyPIcharset-normalizer3.4.7indirect
PyPIcolorama0.4.6indirect
PyPIcontourpy1.3.2indirect
PyPIcontourpy1.3.3indirect
PyPIcoverage7.14.0indirect
PyPIcycler0.12.1indirect
PyPIdistlib0.4.0indirect
PyPIdocutils0.21.2indirect
PyPIdocutils0.22.4indirect
PyPIexceptiongroup1.3.1indirect
PyPIexecnet2.1.2indirect
PyPIfilelock3.29.0indirect
PyPIfonttools4.63.0indirect
PyPIh5py3.16.0indirect
PyPIidentify2.6.19indirect
PyPIidna3.15indirect
PyPIimagesize2.0.0indirect
PyPIindexed-gzip1.10.3indirect
PyPIiniconfig2.3.0indirect
PyPIjinja23.1.6indirect
PyPIkiwisolver1.5.0indirect
PyPIlibrt0.11.0indirect
PyPImarkupsafe3.0.3indirect
PyPImatplotlib3.10.9indirect
PyPImypy2.1.0indirect
PyPImypy-extensions1.1.0indirect
PyPInodeenv1.10.0indirect
PyPInumpydoc1.10.0indirect
PyPIpathspec1.1.1indirect
PyPIpillow12.2.0indirect
PyPIplatformdirs4.9.6indirect
PyPIpluggy1.6.0indirect
PyPIpre-commit4.6.0indirect
PyPIpre-commit-uv4.2.1indirect
PyPIpydata-sphinx-theme0.19.0indirect
PyPIpydicom3.0.2indirect
PyPIpygments2.20.0indirect
PyPIpyparsing3.3.2indirect
PyPIpyproject-api1.10.0indirect
PyPIpytest9.1.0indirect
PyPIpytest-cov7.1.0indirect
PyPIpytest-doctestplus1.7.1indirect
PyPIpytest-httpserver1.1.5indirect
PyPIpytest-run-parallel0.9.1indirect
PyPIpytest-xdist3.8.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-discovery1.3.1indirect
PyPIpyyaml6.0.3indirect
PyPIrequests2.34.2indirect
PyPIroman-numerals4.1.0indirect
PyPIscipy1.15.3indirect
PyPIscipy1.17.1indirect
PyPIsix1.17.0indirect
PyPIsnowballstemmer3.0.1indirect
PyPIsoupsieve2.8.3indirect
PyPIsphinx8.1.3indirect
PyPIsphinx9.0.4indirect
PyPIsphinx9.1.0indirect
PyPIsphinx-copybutton0.5.2indirect
PyPIsphinx-design0.6.1indirect
PyPIsphinx-design0.7.0indirect
PyPIsphinxcontrib-applehelp2.0.0indirect
PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-qthelp2.0.0indirect
PyPIsphinxcontrib-serializinghtml2.0.0indirect
PyPItexext0.6.8indirect
PyPItomli2.4.1indirect
PyPItomli-w1.2.0indirect
PyPItox4.55.1indirect
PyPItox-uv1.35.2indirect
PyPItox-uv-bare1.35.2indirect
PyPItypes-pillow10.2.0.20240822indirect
PyPIurllib32.7.0indirect
PyPIuv0.11.15indirect
PyPIvirtualenv21.3.3indirect
PyPIwerkzeug3.1.8indirect
Dependency advisories 0

Installing pypi:nibabel@5.4.2 pulls in 2 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 v0.26.0 — full methodology · metrics wiki.

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