Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-19 15:24 UTC

onnx / sklearn-onnx

Convert scikit-learn models and pipelines to ONNX

PythonApache-2.0★ 629 stars⑂ 128 forkssince Dec 2018View on GitHub ↗
KindCommand-line toolLibraryhow this is determined

onnx/sklearn-onnx holds a health index of 65 out of 100, placing it in the Good band. It scores highest on Sustainability & Governance (72/100) and lowest on Security (36/100). It was last updated 12 days ago. A single contributor accounts for most of its recent work.

65
overall / 100
Good

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.

65
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 60 is calibrated to 65 on the published index scale (record calibration 2026-08-02).

Ownership

2,739 followers30 public repossince Sep 2017

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIskl2onnx1.20.0-40201 days ago

Metrics by category

Vitality

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

58Moderate · 21% of overall
How it's scored
28.8/36Push recencylast push 12 days ago
8.3/36Commit cadence12/52 weeks with commits
13.3/18Commit volume29 commits in the last year
0/10OpenSSF Scorecard: Maintainedno data
Inputs used
commits_last_year29
human_commit_share1
days_since_last_push12
active_weeks_last_year12
How it's scored
27/27Ships releases31 releases published
16.2/36Release recencylatest release 201 days ago
12.6/27Release cadencea release every ~135.8 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count31
latest_release_tag1.20.0
releases_from_tagsno
days_since_latest_release201
mean_days_between_releases135.8

Community & Adoption

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

60Moderate · 17% of overall
How it's scored
45.4/60Stars629 stars
17.5/25Forks128 forks
5.6/15Watchers11 watchers
Inputs used
forks128
stars629
watchers11
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (Apache-2.0)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges4
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesgithub.com, shields.io
has_pull_request_templateno

Sustainability & Governance

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

72Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
3.5/22.5Commit distributiontop contributor authored 84% of commits
13.5/13.5Contributor breadth48 contributors
0/10OpenSSF Scorecard: Contributorsno data
Inputs used
bus_factor1
contributors_sampled48
top_contributor_share0.844
How it's scored
34.5/42Issue resolution82% of issues closed
25.8/30PR acceptance669/777 decided PRs merged
10.4/13Newcomer PR acceptance4/5 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs669
open_issues86
closed_issues395
prs_merged_7d0
prs_decided_7d0
prs_merged_30d5
prs_decided_30d6
issue_closed_ratio0.821
closed_unmerged_prs108
first_time_authors_30d4
first_time_prs_merged_30d4
first_time_prs_decided_30d5
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
24.7/25Owner reach2,739 followers of onnx
22.9/25Track record30 public repos, account ~8 yr old
Inputs used
followers2,739
owner_typeOrganization
is_verified
owner_loginonnx
public_repos30
account_age_days3,269
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
26/35Publish recencylatest publish 201 days ago
20/20Version history40 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesskl2onnx
ecosystemspypi
any_deprecatedno
min_days_since_publish201

Engineering Quality

Are baseline engineering and documentation practices in place?

70Good · 19% of overall
How it's scored
24/24CI workflows6 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Testsno data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

85Excellent
How it's scored
30/30README
25/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics2 topics
10/10Wiki
Inputs used
topicsscikit-learn, onnx
has_wikiyes
homepage
docs_site
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

36Weak · 16% of overall
How it's scored
0/30Security policy (SECURITY.md)
0/25Dependabot config
0/25Dependency lockfiles
20/20CodeQL workflow
Inputs used
sourcefile_signals
lockfiles
manifestsdocs/requirements.txt, pyproject.toml, requirements-dev.txt, requirements.txt
has_codeql_workflowyes
has_security_policyno
has_dependabot_configno

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_packages10
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:skl2onnx@1.20.0 runtime dependency closure — what installing the published package pulls in — 10 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.

50Moderate · 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 history100 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share1
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
0/10Reproducible environment
10/10Demonstrated agent practice13 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesno data
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0.13
toolchain_manifests
dependency_bot_commit_share0
How it's scored
0/45Type-checkable codePython without a type-check config
54.4/55Manageable file sizes4/395 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes68,996
source_files_sampled395
oversized_source_files4
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 examplesexamples
Inputs used
example_dirsexamples
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

629GitHub stars
48contributors
29commits, last 12 months
12days since last push
31releases
1bus factor
86open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • OpenSSF Scorecard did not return a usable result (2026/08/19 15:23:36 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks

More detail

Star and fork history 0 ★ / 128 ⇿
0Stars
128Forks
31Releases

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.

025507510012512442018-122022-102026-07
Major 0Minor 9Patch 15

Each point covers 7 days.

All dependencies 41

Full resolved dependency set from the GitHub dependency graph: 0 direct and 41 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIautopep8indirect
PyPIblackindirect
PyPIcatboostindirect
PyPIcategory-encodersindirect
PyPIcoverageindirect
PyPIflake8indirect
PyPIfuroindirect
PyPIjinja2indirect
PyPIjoblibindirect
PyPIlightgbmindirect
PyPIlokyindirect
PyPImatplotlibindirect
PyPImlinsightsindirect
PyPInbsphinxindirect
PyPIndonnxindirect
PyPIonnxindirect
PyPIonnx-array-apiindirect
PyPIonnxmltoolsindirect
PyPIonnxruntimeindirect
PyPIonnxruntime-extensionsindirect
PyPIonnxscriptindirect
PyPIpandasindirect
PyPIpillowindirect
PyPIpy-cpuinfoindirect
PyPIpy-spyindirect
PyPIpybind11indirect
PyPIpydotindirect
PyPIpyinstrumentindirect
PyPIpyodindirect
PyPIpytestindirect
PyPIpytest-covindirect
PyPIruffindirect
PyPIscikit-learnindirect
PyPIskl2onnxindirect
PyPIsphinxindirect
PyPIsphinx-galleryindirect
PyPIsphinx-runpythonindirect
PyPItabulateindirect
PyPItqdmindirect
PyPIwheelindirect
PyPIxgboostindirect
Dependency advisories 0

Installing pypi:skl2onnx@1.20.0 pulls in 10 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 v0.31.0 — full methodology · metrics wiki.

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