Public record
Software health reportschema 0.11.0 · metrics 2.10.0 · 2026-07-17 08:00 UTC

koaning / scikit-lego

Extra blocks for scikit-learn pipelines.

PythonMIT★ 1,408 stars⑂ 126 forkssince Jan 2019View on GitHub ↗
KindLibraryhow this is determined
#scikit-learn#machine-learning#common-sense

koaning/scikit-lego holds a health index of 87 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (96/100) and lowest on AI Readiness (44/100). It was last updated 6 days ago. A single contributor accounts for most of its recent work.

87
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.

87
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 73 is calibrated to 87 on the published index scale (record calibration 2026-08-02).

Ownership

vincent d warmerdam Personal account
2,786 followers331 public repossince Sep 2011@marimo-team

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIscikit-lego0.9.9-5811 days ago

Metrics by category

Vitality

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

75Good · 21% of overall

Development activity

64Moderate
How it's scored
36/36Push recency — last push 6 days ago
9/36Commit cadence — 13/52 weeks with commits
13.1/18Commit volume — 28 commits in the last year
6/10OpenSSF Scorecard: Maintained — 8 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 6
Inputs used
commits_last_year28
human_commit_share—
days_since_last_push6
active_weeks_last_year13

Release discipline

92Excellent
How it's scored
27/27Ships releases — 47 releases published
36/36Release recency — latest release 11 days ago
19.8/27Release cadence — a release every ~93.2 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count47
latest_release_tagv0.9.9
releases_from_tagsno
days_since_latest_release11
mean_days_between_releases93.2
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?

74Good · 17% of overall

Popularity & adoption

76Good
How it's scored
51.1/60Stars — 1,408 stars
17.5/25Forks — 126 forks
7/15Watchers — 19 watchers
Inputs used
forks126
stars1,408
watchers19
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

72Good
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
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_badges—
has_contributingno
has_issue_templateno
has_code_of_conductyes
readme_badge_services—
has_pull_request_templateyes

Sustainability & Governance

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

72Good · 23% of overall

Maintainer resilience (bus factor)

43Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
10.7/22.5Commit distribution — top contributor authored 52% of commits
13.5/13.5Contributor breadth — 62 contributors
10/10OpenSSF Scorecard: Contributors — project has 5 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled62
top_contributor_share0.525

Issue & PR responsiveness

81Excellent
How it's scored
38.5/42Issue resolution — 92% of issues closed
24.5/30PR acceptance — 384/470 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
7.5/15OpenSSF Scorecard: Code-Review — Found 14/24 approved changesets -- score normalized to 5
Inputs used
merged_prs384
open_issues28
closed_issues306
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio0.916
closed_unmerged_prs86
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.

Ownership & stewardship

75Good
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
24.8/25Owner reach — 2,786 followers of koaning
25/25Track record — 331 public repos, account ~14 yr old
Inputs used
followers2,786
owner_typeUser
is_verified—
owner_loginkoaning
public_repos331
account_age_days5,432
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 11 days ago
20/20Version history — 58 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesscikit-lego
ecosystemspypi
any_deprecatedno
min_days_since_publish11

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 4 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 26 out of 26 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://koaning.github.io/scikit-lego/
10/10Repository description
10/10Topics — 3 topics
10/10Wiki
Inputs used
topicsscikit-learn, machine-learning, common-sense
has_wikiyes
homepagehttps://koaning.github.io/scikit-lego/
docs_sitehttps://koaning.github.io/scikit-lego/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

48Weak · 16% of overall

Security posture

48Weak
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 — 26 out of 26 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
3.8/7.5Code-Review — Found 14/24 approved changesets -- score normalized to 5
2.5/2.5Contributors — project has 5 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
4.5/7.5Maintained — 8 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 6
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
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 — 34 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate4.8
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

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.

44Weak · 4% of overall

Agent context & guidance

1Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no data
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share—
agent_instruction_files—
agent_instruction_max_bytes—
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

73Good
How it's scored
18/18One-command bootstrap — Makefile, docs/Makefile
22/22Automated tests
11/11Lint / format config
0/11Static type checking
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no data
5/8Automated maintenance — dependency automation configured, none observed in the sampled commits
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesMakefile, docs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs—
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.

Code legibility for models

55Moderate
How it's scored
0/45Type-checkable code — Python without a type-check config
55/55Manageable file sizes — 0/136 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes56,157
source_files_sampled136
oversized_source_files0

Key facts

1,408GitHub stars
62contributors
28commits, last 12 months
6days since last push
47releases
1bus factor
28open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 4.8 / 10
4.8aggregate

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 · 2026-07-17 08:00 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-Tests26 out of 26 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
5Code-ReviewFound 14/24 approved changesets -- score normalized to 5
10Contributorsproject has 5 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
6Maintained8 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 6
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
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
0Vulnerabilities34 existing vulnerabilities detected
Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPInarwhals>=1.5.0pyproject.toml
PyPIpandas>=1.1.5pyproject.toml
PyPIscikit-learn>=1.0pyproject.toml
PyPIsklearn-compat>=0.1.3pyproject.toml
All dependencies 177

Full resolved dependency set from the GitHub dependency graph: 4 direct and 173 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInarwhals2.8.0direct
PyPIpandas2.3.3direct
PyPIscikit-learn1.7.2direct
PyPIsklearn-compat0.1.4direct
PyPIanyio4.11.0indirect
PyPIappnope0.1.4indirect
PyPIargon2-cffi25.1.0indirect
PyPIargon2-cffi-bindings25.1.0indirect
PyPIarrow1.3.0indirect
PyPIasttokens3.0.0indirect
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PyPIattrs25.4.0indirect
PyPIbabel2.17.0indirect
PyPIbackrefs5.9indirect
PyPIbeautifulsoup44.14.2indirect
PyPIbleach6.2.0indirect
PyPIcertifi2025.10.5indirect
PyPIcffi2.0.0indirect
PyPIcfgv3.4.0indirect
PyPIcharset-normalizer3.4.3indirect
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PyPIdecorator5.2.1indirect
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PyPIexecnet2.1.1indirect
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PyPIipython-pygments-lexers1.1.1indirect
PyPIipywidgets8.1.7indirect
PyPIisoduration20.11.0indirect
PyPIjedi0.19.2indirect
PyPIjinja23.1.6indirect
PyPIjoblib1.5.2indirect
PyPIjson50.12.1indirect
PyPIjsonpointer3.0.0indirect
PyPIjsonschema4.25.1indirect
PyPIjsonschema-specifications2025.9.1indirect
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PyPIjupyter-lsp2.3.0indirect
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PyPIjupyterlab-pygments0.3.0indirect
PyPIjupyterlab-server2.28.0indirect
PyPIjupyterlab-widgets3.0.15indirect
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PyPIllvmlite0.45.1indirect
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PyPImatplotlib3.10.7indirect
PyPImatplotlib-inline0.1.7indirect
PyPImergedeep1.3.4indirect
PyPImistune3.2.1indirect
PyPImkdocs1.6.1indirect
PyPImkdocs-autorefs1.4.3indirect
PyPImkdocs-get-deps0.2.0indirect
PyPImkdocs-material9.6.21indirect
PyPImkdocs-material-extensions1.3.1indirect
PyPImkdocstrings0.30.1indirect
PyPImkdocstrings-python1.18.2indirect
PyPInbclient0.10.2indirect
PyPInbconvert7.17.1indirect
PyPInbformat5.10.4indirect
PyPInest-asyncio1.6.0indirect
PyPInodeenv1.9.1indirect
PyPInotebook7.5.7indirect
PyPInotebook-shim0.2.4indirect
PyPInumba0.62.1indirect
PyPInumpy1.26.4indirect
PyPIosqp1.0.4indirect
PyPIoverrides7.7.0indirect
PyPIpackaging25.0indirect
PyPIpaginate0.5.7indirect
PyPIpandocfilters1.5.1indirect
PyPIparso0.8.5indirect
PyPIpathspec0.12.1indirect
PyPIpexpect4.9.0indirect
PyPIpillow12.2.0indirect
PyPIplatformdirs4.5.0indirect
PyPIpluggy1.6.0indirect
PyPIpolars1.34.0indirect
PyPIpolars-runtime-321.34.0indirect
PyPIpre-commit4.3.0indirect
PyPIprometheus-client0.23.1indirect
PyPIprompt-toolkit3.0.52indirect
PyPIpsutil7.1.0indirect
PyPIptyprocess0.7.0indirect
PyPIpure-eval0.2.3indirect
PyPIpyarrow21.0.0indirect
PyPIpycparser2.23indirect
PyPIpygments2.20.0indirect
PyPIpymdown-extensions10.16.1indirect
PyPIpynndescent0.5.13indirect
PyPIpyparsing3.2.5indirect
PyPIpytest9.0.3indirect
PyPIpytest-cov7.0.0indirect
PyPIpytest-mock3.15.1indirect
PyPIpytest-xdist3.8.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-discovery1.2.1indirect
PyPIpython-json-logger4.0.0indirect
PyPIpytz2025.2indirect
PyPIpywin32311indirect
PyPIpywinpty3.0.2indirect
PyPIpyyaml6.0.3indirect
PyPIpyyaml-env-tag1.1indirect
PyPIpyzmq27.1.0indirect
PyPIreferencing0.36.2indirect
PyPIrequests2.33.1indirect
PyPIrfc3339-validator0.1.4indirect
PyPIrfc3986-validator0.1.1indirect
PyPIrfc3987-syntax1.1.0indirect
PyPIrpds-py0.27.1indirect
PyPIruff0.15.10indirect
PyPIscikit-lego0.9.9indirect
PyPIscipy1.15.3indirect
PyPIscipy1.16.2indirect
PyPIscs3.2.9indirect
PyPIsend2trash1.8.3indirect
PyPIsetuptools80.9.0indirect
PyPIsix1.17.0indirect
PyPIsniffio1.3.1indirect
PyPIsoupsieve2.8indirect
PyPIstack-data0.6.3indirect
PyPIterminado0.18.1indirect
PyPIthreadpoolctl3.6.0indirect
PyPItinycss21.4.0indirect
PyPItomli2.3.0indirect
PyPItornado6.5.5indirect
PyPItqdm4.67.1indirect
PyPItraitlets5.14.3indirect
PyPItypes-python-dateutil2.9.0.20251008indirect
PyPItyping-extensions4.15.0indirect
PyPItzdata2025.2indirect
PyPIumap-learn0.5.9.post2indirect
PyPIuri-template1.3.0indirect
PyPIurllib32.6.3indirect
PyPIvirtualenv21.2.0indirect
PyPIwatchdog6.0.0indirect
PyPIwcwidth0.2.14indirect
PyPIwebcolors24.11.1indirect
PyPIwebencodings0.5.1indirect
PyPIwebsocket-client1.9.0indirect
PyPIwidgetsnbextension4.0.14indirect
PyPIwrapt1.17.3indirect
Raw JSON report machine-readable

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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 v0.11.0 — full methodology · metrics wiki.

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