Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-09 18:36 UTC

koaning / scikit-lego

Extra blocks for scikit-learn pipelines.

PythonMIT★ 1,411 stars⑂ 130 forkssince Jan 2019View on GitHub ↗

#scikit-learn #machine-learning #common-sense

koaning/scikit-lego holds a health index of 91 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (96/100) and lowest on AI Readiness (59/100). It was last updated 7 days ago. A single contributor accounts for most of its recent work.

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.

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)

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 77 is calibrated to 91 on the published index scale (record calibration 2026-08-02).

Ownership

vincent d warmerdam Personal account

2,834 followers334 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

Registry	Package	Version	Downloads / mo	Versions	Last publish
PyPI	scikit-lego	0.9.10	-	59	10 days ago

Metrics by category

Vitality

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

80Excellent · 21% of overall

Development activity

72Good

How it's scored

36/36	Push recency — last push 7 days ago
11.1/36	Commit cadence — 16/52 weeks with commits
14.7/18	Commit volume — 42 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 22 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	42
human_commit_share	0.87
days_since_last_push	7
active_weeks_last_year	16

Release discipline

92Excellent

How it's scored

27/27	Ships releases — 48 releases published
36/36	Release recency — latest release 10 days ago
19.8/27	Release cadence — a release every ~96.2 days
0/10	OpenSSF Scorecard: Signed-Releases — no data

Inputs used

releases_count	48
latest_release_tag	v0.9.10
releases_from_tags	no
days_since_latest_release	10
mean_days_between_releases	96.2

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

75Good

How it's scored

51.1/60	Stars — 1,411 stars
17.6/25	Forks — 130 forks
6.7/15	Watchers — 17 watchers

Inputs used

forks	130
stars	1,411
watchers	17
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

72Good

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (MIT)
0/18	CONTRIBUTING guide
13.5/13.5	Code of conduct
0/7.2	Issue template
6.3/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	6
has_contributing	no
has_issue_template	no
has_code_of_conduct	yes
readme_badge_services	shields.io
has_pull_request_template	yes

Sustainability & Governance

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

73Good · 23% of overall

Maintainer resilience (bus factor)

43Weak

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
10.6/22.5	Commit distribution — top contributor authored 53% of commits
13.5/13.5	Contributor breadth — 64 contributors
10/10	OpenSSF Scorecard: Contributors — project has 5 contributing companies or organizations

Inputs used

bus_factor	1
contributors_sampled	64
top_contributor_share	0.527

Issue & PR responsiveness

87Excellent

How it's scored

38.9/42	Issue resolution — 92% of issues closed
24.7/30	PR acceptance — 398/484 decided PRs merged
13/13	Newcomer PR acceptance — 3/3 first-time contributors' PRs merged in 30d
10.5/15	OpenSSF Scorecard: Code-Review — Found 15/20 approved changesets -- score normalized to 7

Inputs used

merged_prs	398
open_issues	25
closed_issues	310
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	5
prs_decided_30d	5
issue_closed_ratio	0.925
closed_unmerged_prs	86
first_time_authors_30d	2
first_time_prs_merged_30d	3
first_time_prs_decided_30d	3

Ownership & stewardship

75Good

How it's scored

10/30	Ownership backing — personal (user) account
0/20	Verified domain — not applicable to user accounts
24.8/25	Owner reach — 2,834 followers of koaning
25/25	Track record — 334 public repos, account ~15 yr old

Inputs used

followers	2,834
owner_type	User
is_verified	—
owner_login	koaning
public_repos	334
account_age_days	5,487

Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 10 days ago
20/20	Version history — 59 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	scikit-lego
ecosystems	pypi
any_deprecated	no
min_days_since_publish	10

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

94Exceptional

How it's scored

24/24	CI workflows — 4 workflow(s)
24/24	Tests present
16/16	Linter config — pyproject.toml ([tool.ruff])
9.6/9.6	Pre-commit hooks
0/6.4	.editorconfig
20/20	OpenSSF Scorecard: CI-Tests — 29 out of 29 merged PRs checked by a CI test -- score normalized to 10

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	yes
has_precommit_config	yes

Documentation

100Exceptional

How it's scored

30/30	README
25/25	Documentation directory
15/15	Documentation / homepage site — https://koaning.github.io/scikit-lego/
10/10	Repository description
10/10	Topics — 3 topics
10/10	Wiki

Inputs used

topics	scikit-learn, machine-learning, common-sense
has_wiki	yes
homepage	https://koaning.github.io/scikit-lego/
docs_site	https://koaning.github.io/scikit-lego/
has_readme	yes
has_docs_dir	yes
has_description	yes

Security

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

67Good · 16% of overall

Security posture

59Moderate

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0/7.5	Branch-Protection — no data
2.5/2.5	CI-Tests — 29 out of 29 merged PRs checked by a CI test -- score normalized to 10
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
5.2/7.5	Code-Review — Found 15/20 approved changesets -- score normalized to 7
2.5/2.5	Contributors — project has 5 contributing companies or organizations
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5	Dependency-Update-Tool — update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
7.5/7.5	Maintained — 22 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
0/5	Packaging — no data
0/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5	SAST — SAST tool is not run on all commits -- score normalized to 0
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — no data
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
5.2/7.5	Vulnerabilities — 3 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	15
scorecard_version	v5.5.0
checks_inconclusive	3
scorecard_aggregate	5.9

Excluded from scoring (no data or not applicable): Branch-Protection, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional

How it's scored

35/35	Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40	No advisories left outstanding — no advisory carries a publication date

Inputs used

source	osv
advisories	0
affected_packages	0
assessed_packages	11
unassessed_packages	0
affected_by_severity	none
direct_affected_packages	0

Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:scikit-lego@0.9.10 runtime dependency closure — what installing the published package pulls in — 11 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.

59Moderate · 4% of overall

Agent context & guidance

40Weak

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15	Machine-readable docs (llms.txt)
40/40	Legible commit history — 79 of 87 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.908
agent_instruction_files	—
agent_instruction_max_bytes	—

Verify loop (build / test / typecheck)

75Good

How it's scored

18/18	One-command bootstrap — Makefile, docs/Makefile
22/22	Automated tests
11/11	Lint / format config — pyproject.toml ([tool.ruff])
0/11	Static type checking
10/10	Reproducible environment — lockfile
6/10	Demonstrated agent practice — 3 of the last 100 commits agent-authored or agent-credited
8/8	Automated maintenance — 13 of the last 100 commits are automated dependency updates
0/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0

Inputs used

has_nix	no
has_tests	yes
lockfiles	uv.lock
has_dockerfile	no
typed_language	no
bootstrap_files	Makefile, docs/Makefile
has_devcontainer	no
has_linter_config	yes
typecheck_configs	—
agent_commit_share	0.03
toolchain_manifests	—
dependency_bot_commit_share	0.13

Code legibility for models

55Moderate

How it's scored

0/45	Type-checkable code — Python without a type-check config
55/55	Manageable file sizes — 0/136 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	56,157
source_files_sampled	136
oversized_source_files	0

Key facts

1,411GitHub stars

64contributors

42commits, last 12 months

7days since last push

48releases

1bus factor

25open issues

PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
pypi download statistics for 'scikit-lego' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced

More detail

Star and fork history 0 ★ / 130 ⇿

0Stars

130Forks

47Releases

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.

Major 0Minor 7Patch 40

Each point covers 7 days.

OpenSSF Scorecard 5.9 / 10

5.9aggregate

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 · 2026-09-09 18:36 UTC

10	Binary-Artifacts	no binaries found in the repo
n/a	Branch-Protection	internal 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
10	CI-Tests	29 out of 29 merged PRs checked by a CI test -- score normalized to 10
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
7	Code-Review	Found 15/20 approved changesets -- score normalized to 7
10	Contributors	project has 5 contributing companies or organizations
10	Dangerous-Workflow	no dangerous workflow patterns detected
10	Dependency-Update-Tool	update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
10	Maintained	22 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
n/a	Packaging	packaging workflow not detected
0	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 0
0	SAST	SAST tool is not run on all commits -- score normalized to 0
0	Security-Policy	security policy file not detected
n/a	Signed-Releases	no releases found
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
7	Vulnerabilities	3 existing vulnerabilities detected

Direct dependencies 5

Registry	Package	Version constraint	Manifest
PyPI	narwhals	`>=1.5.0`	pyproject.toml
PyPI	numpy	`>=1.26.4`	pyproject.toml
PyPI	pandas	`>=2.0.3`	pyproject.toml
PyPI	scikit-learn	`>=1.4.2`	pyproject.toml
PyPI	sklearn-compat	`>=0.1.3`	pyproject.toml

All dependencies 184

Full resolved dependency set from the GitHub dependency graph: 8 direct and 176 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	narwhals	`2.24.0`	direct
PyPI	numpy	`2.2.6`	direct
PyPI	numpy	`2.4.6`	direct
PyPI	pandas	`2.3.3`	direct
PyPI	pandas	`3.0.5`	direct
PyPI	scikit-learn	`1.7.2`	direct
PyPI	scikit-learn	`1.9.0`	direct
PyPI	sklearn-compat	`0.1.6`	direct
PyPI	anyio	`4.14.2`	indirect
PyPI	appnope	`0.1.4`	indirect
PyPI	argon2-cffi	`25.1.0`	indirect
PyPI	argon2-cffi-bindings	`25.1.0`	indirect
PyPI	arrow	`1.4.0`	indirect
PyPI	asttokens	`3.0.2`	indirect
PyPI	async-lru	`2.3.0`	indirect
PyPI	attrs	`26.1.0`	indirect
PyPI	babel	`2.18.0`	indirect
PyPI	backrefs	`8.0`	indirect
PyPI	beautifulsoup4	`4.15.0`	indirect
PyPI	bleach	`6.4.0`	indirect
PyPI	certifi	`2026.7.22`	indirect
PyPI	cffi	`2.1.0`	indirect
PyPI	cfgv	`3.5.0`	indirect
PyPI	charset-normalizer	`3.4.9`	indirect
PyPI	clarabel	`0.11.1`	indirect
PyPI	click	`8.4.2`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	comm	`0.2.3`	indirect
PyPI	contourpy	`1.3.2`	indirect
PyPI	contourpy	`1.3.3`	indirect
PyPI	coverage	`7.15.2`	indirect
PyPI	cvxpy	`1.7.5`	indirect
PyPI	cvxpy	`1.9.2`	indirect
PyPI	cycler	`0.12.1`	indirect
PyPI	debugpy	`1.8.21`	indirect
PyPI	decorator	`5.3.1`	indirect
PyPI	defusedxml	`0.7.1`	indirect
PyPI	distlib	`0.4.3`	indirect
PyPI	exceptiongroup	`1.3.1`	indirect
PyPI	execnet	`2.1.2`	indirect
PyPI	executing	`2.2.1`	indirect
PyPI	fastjsonschema	`2.22.1`	indirect
PyPI	filelock	`3.32.2`	indirect
PyPI	fonttools	`4.63.0`	indirect
PyPI	formulaic	`1.2.2`	indirect
PyPI	fqdn	`1.5.1`	indirect
PyPI	ghp-import	`2.1.0`	indirect
PyPI	griffelib	`2.1.0`	indirect
PyPI	h11	`0.16.0`	indirect
PyPI	highspy	`1.15.1`	indirect
PyPI	httpcore	`1.0.9`	indirect
PyPI	httpx	`0.28.1`	indirect
PyPI	identify	`2.6.19`	indirect
PyPI	idna	`3.18`	indirect
PyPI	iniconfig	`2.3.0`	indirect
PyPI	interface-meta	`2.0.1`	indirect
PyPI	ipykernel	`7.3.0`	indirect
PyPI	ipython	`8.39.0`	indirect
PyPI	ipython	`9.16.0`	indirect
PyPI	ipython-pygments-lexers	`1.1.1`	indirect
PyPI	ipywidgets	`8.1.8`	indirect
PyPI	isoduration	`20.11.0`	indirect
PyPI	jedi	`0.20.0`	indirect
PyPI	jinja2	`3.1.6`	indirect
PyPI	joblib	`1.5.3`	indirect
PyPI	json5	`0.15.0`	indirect
PyPI	jsonpointer	`3.1.1`	indirect
PyPI	jsonschema	`4.26.0`	indirect
PyPI	jsonschema-specifications	`2025.9.1`	indirect
PyPI	jupyter	`1.1.1`	indirect
PyPI	jupyter-builder	`1.2.1`	indirect
PyPI	jupyter-client	`8.9.1`	indirect
PyPI	jupyter-console	`6.6.3`	indirect
PyPI	jupyter-core	`5.9.1`	indirect
PyPI	jupyter-events	`0.12.1`	indirect
PyPI	jupyter-lsp	`2.3.1`	indirect
PyPI	jupyter-server	`2.20.0`	indirect
PyPI	jupyter-server-terminals	`0.5.4`	indirect
PyPI	jupyterlab	`4.6.2`	indirect
PyPI	jupyterlab-pygments	`0.3.0`	indirect
PyPI	jupyterlab-server	`2.28.0`	indirect
PyPI	jupyterlab-widgets	`3.0.16`	indirect
PyPI	kiwisolver	`1.5.0`	indirect
PyPI	lark	`1.3.1`	indirect
PyPI	llvmlite	`0.48.0`	indirect
PyPI	markdown	`3.10.3`	indirect
PyPI	markupsafe	`3.0.3`	indirect
PyPI	matplotlib	`3.10.9`	indirect
PyPI	matplotlib	`3.11.1`	indirect
PyPI	matplotlib-inline	`0.2.2`	indirect
PyPI	mergedeep	`1.3.4`	indirect
PyPI	mistune	`3.3.4`	indirect
PyPI	mkdocs	`1.6.1`	indirect
PyPI	mkdocs-autorefs	`1.4.4`	indirect
PyPI	mkdocs-get-deps	`0.2.2`	indirect
PyPI	mkdocs-material	`9.7.7`	indirect
PyPI	mkdocs-material-extensions	`1.3.1`	indirect
PyPI	mkdocstrings	`1.0.6`	indirect
PyPI	mkdocstrings-python	`2.0.5`	indirect
PyPI	nbclient	`0.11.0`	indirect
PyPI	nbconvert	`7.17.1`	indirect
PyPI	nbformat	`5.10.4`	indirect
PyPI	nest-asyncio2	`1.7.2`	indirect
PyPI	nodeenv	`1.10.0`	indirect
PyPI	notebook	`7.6.1`	indirect
PyPI	notebook-shim	`0.2.4`	indirect
PyPI	numba	`0.66.0`	indirect
PyPI	osqp	`1.1.3`	indirect
PyPI	overrides	`7.7.0`	indirect
PyPI	packaging	`26.2`	indirect
PyPI	paginate	`0.5.7`	indirect
PyPI	pandocfilters	`1.5.1`	indirect
PyPI	parso	`0.8.7`	indirect
PyPI	pathspec	`1.1.1`	indirect
PyPI	pexpect	`4.9.0`	indirect
PyPI	pillow	`12.3.0`	indirect
PyPI	platformdirs	`4.11.0`	indirect
PyPI	pluggy	`1.6.0`	indirect
PyPI	polars	`1.43.2`	indirect
PyPI	polars-runtime-32	`1.43.2`	indirect
PyPI	pre-commit	`4.6.1`	indirect
PyPI	prometheus-client	`0.26.0`	indirect
PyPI	prompt-toolkit	`3.0.53`	indirect
PyPI	psutil	`7.2.2`	indirect
PyPI	ptyprocess	`0.7.0`	indirect
PyPI	pure-eval	`0.2.3`	indirect
PyPI	pyarrow	`25.0.0`	indirect
PyPI	pycparser	`3.0`	indirect
PyPI	pygments	`2.20.0`	indirect
PyPI	pymdown-extensions	`11.0.1`	indirect
PyPI	pynndescent	`0.6.0`	indirect
PyPI	pyparsing	`3.3.2`	indirect
PyPI	pytest	`9.1.1`	indirect
PyPI	pytest-cov	`7.1.0`	indirect
PyPI	pytest-mock	`3.15.1`	indirect
PyPI	pytest-xdist	`3.8.0`	indirect
PyPI	python-dateutil	`2.9.0.post0`	indirect
PyPI	python-discovery	`1.5.1`	indirect
PyPI	python-json-logger	`4.1.0`	indirect
PyPI	pytz	`2026.3.post1`	indirect
PyPI	pywinpty	`3.0.5`	indirect
PyPI	pyyaml	`6.0.3`	indirect
PyPI	pyyaml-env-tag	`1.1`	indirect
PyPI	pyzmq	`27.1.0`	indirect
PyPI	qdldl	`0.1.9.post1`	indirect
PyPI	referencing	`0.37.0`	indirect
PyPI	requests	`2.34.2`	indirect
PyPI	rfc3339-validator	`0.1.4`	indirect
PyPI	rfc3986-validator	`0.1.1`	indirect
PyPI	rfc3987-syntax	`1.1.0`	indirect
PyPI	rpds-py	`0.30.0`	indirect
PyPI	rpds-py	`2026.6.3`	indirect
PyPI	ruff	`0.16.1`	indirect
PyPI	scikit-lego	`0.9.10`	indirect
PyPI	scipy	`1.15.3`	indirect
PyPI	scipy	`1.17.1`	indirect
PyPI	scipy	`1.18.0`	indirect
PyPI	scs	`3.2.11`	indirect
PyPI	send2trash	`2.1.0`	indirect
PyPI	setuptools	`83.0.0`	indirect
PyPI	six	`1.17.0`	indirect
PyPI	soupsieve	`2.9.1`	indirect
PyPI	sparsediffpy	`0.3.0`	indirect
PyPI	stack-data	`0.6.3`	indirect
PyPI	terminado	`0.18.1`	indirect
PyPI	threadpoolctl	`3.6.0`	indirect
PyPI	tinycss2	`1.5.1`	indirect
PyPI	tomli	`2.4.1`	indirect
PyPI	tornado	`6.5.7`	indirect
PyPI	tqdm	`4.70.0`	indirect
PyPI	traitlets	`5.16.0`	indirect
PyPI	typing-extensions	`4.16.0`	indirect
PyPI	tzdata	`2026.3`	indirect
PyPI	umap-learn	`0.5.12`	indirect
PyPI	uri-template	`1.3.0`	indirect
PyPI	urllib3	`2.7.0`	indirect
PyPI	virtualenv	`21.7.1`	indirect
PyPI	watchdog	`6.0.0`	indirect
PyPI	wcwidth	`0.8.2`	indirect
PyPI	webcolors	`25.10.0`	indirect
PyPI	webencodings	`0.5.1`	indirect
PyPI	websocket-client	`1.9.0`	indirect
PyPI	widgetsnbextension	`4.0.15`	indirect
PyPI	wrapt	`2.3.0`	indirect

Dependency advisories 0

Installing pypi:scikit-lego@0.9.10 pulls in 11 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

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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.

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 v0.34.0 — full methodology · metrics wiki.

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

Software health index

Score profile

Ownership

Package ecosystems

Metrics by category

Key facts

Data collection warnings

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