Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-20 04:22 UTC

aria-ml / dataeval

Python library for analyzing data quality and its impact on model performance across classification and object-detection tasks.

PythonMIT★ 20 stars⑂ 6 forkssince Nov 2023View on GitHub ↗

KindPluginLibraryhow this is determined

#ai #data #metrics #sufficiency #bias-detection #linter #out-of-distribution-detection #outlier-detection

aria-ml/dataeval holds a health index of 67 out of 100, placing it in the Good band. It scores highest on Vitality (94/100) and lowest on Sustainability & Governance (34/100). It was last updated today. A single contributor accounts for most of its recent work.

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.

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 61 is calibrated to 67 on the published index scale (record calibration 2026-08-02).

Ownership

ARiAPersonal account

0 followers9 public repossince Nov 2023ARiA

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	dataeval	1.1.4	3,060	86	18 days ago

Metrics by category

Vitality

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

94Exceptional · 21% of overall

Development activity

97Exceptional

How it's scored

36/36	Push recency — last push 0 days ago
33.2/36	Commit cadence — 48/52 weeks with commits
18/18	Commit volume — 768 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	768
human_commit_share	1
days_since_last_push	0
active_weeks_last_year	48

Release discipline

90Excellent

How it's scored

27/27	Ships releases — 5 releases published
36/36	Release recency — latest release 18 days ago
27/27	Release cadence — a release every ~10 days
0/10	OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.

Inputs used

releases_count	5
latest_release_tag	v1.1.4
releases_from_tags	no
days_since_latest_release	18
mean_days_between_releases	10

Community & Adoption

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

49Weak · 17% of overall

Popularity & adoption

26At Risk

How it's scored

20.7/60	Stars — 20 stars
5.8/25	Forks — 6 forks
0/15	Watchers — 2 watchers

Inputs used

forks	6
stars	20
watchers	2
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

70Good

How it's scored

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

Inputs used

has_readme	yes
has_license	yes
readme_badges	3
has_contributing	yes
has_issue_template	no
has_code_of_conduct	no
readme_badge_services	readthedocs.org, shields.io
has_pull_request_template	no

Ecosystem adoption (downloads)

58Moderate

How it's scored

46.5/80	Monthly downloads — 3,060 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	dataeval
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	3,060
unverified_packages_excluded	—

Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

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

34At Risk · 23% of overall

Maintainer resilience (bus factor)

20At Risk

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
2.4/22.5	Commit distribution — top contributor authored 89% of commits
5.4/13.5	Contributor breadth — 4 contributors
3/10	OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3

Inputs used

bus_factor	1
contributors_sampled	4
top_contributor_share	0.893

Issue & PR responsiveness

1Critical

How it's scored

0/42	Issue resolution — no issues or no data
0/30	PR acceptance — 0/1 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15	OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0

Inputs used

merged_prs	0
open_issues	0
closed_issues	0
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	0
prs_decided_30d	0
issue_closed_ratio	—
closed_unmerged_prs	1
first_time_authors_30d	0
first_time_prs_merged_30d	0
first_time_prs_decided_30d	0

Excluded from scoring (no data or not applicable): Issue resolution, Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

29At Risk

How it's scored

10/30	Ownership backing — personal (user) account
0/20	Verified domain — not applicable to user accounts
0/25	Owner reach — 0 followers of aria-ml
13.2/25	Track record — 9 public repos, account ~2 yr old

Inputs used

followers	0
owner_type	User
is_verified	—
owner_login	aria-ml
public_repos	9
account_age_days	1,076

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 18 days ago
20/20	Version history — 86 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	dataeval
ecosystems	pypi
any_deprecated	no
min_days_since_publish	18

Engineering Quality

Are baseline engineering and documentation practices in place?

84Excellent · 19% of overall

Engineering practices

80Excellent

How it's scored

24/24	CI workflows — 5 workflow(s)
24/24	Tests present
16/16	Linter config — pyproject.toml ([tool.ruff])
0/9.6	Pre-commit hooks
0/6.4	.editorconfig
0/20	OpenSSF Scorecard: CI-Tests — no data

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	yes
has_precommit_config	no

Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

90Excellent

How it's scored

30/30	README
25/25	Documentation directory
15/15	Documentation / homepage site — https://dataeval.readthedocs.io
10/10	Repository description
10/10	Topics — 8 topics
0/10	Wiki

Inputs used

topics	ai, data, metrics, sufficiency, bias-detection, linter, out-of-distribution-detection, outlier-detection
has_wiki	no
homepage	https://dataeval.readthedocs.io
docs_site	https://dataeval.readthedocs.io
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?

47Weak · 16% of overall

Security posture

34At Risk

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0/7.5	Branch-Protection — branch protection not enabled on development/release branches
0/2.5	CI-Tests — no data
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5	Code-Review — Found 0/30 approved changesets -- score normalized to 0
0.8/2.5	Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5	Dependency-Update-Tool — no update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
7.5/7.5	Maintained — 30 commit(s) and 0 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
5/5	SAST — SAST tool detected: CodeQL
0/5	Security-Policy — security policy file not detected
0/7.5	Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5	Vulnerabilities — 18 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	16
scorecard_version	v5.5.0
checks_inconclusive	2
scorecard_aggregate	3.4

Excluded from scoring (no data or not applicable): CI-Tests, Packaging. 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
0/25	Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40	No advisories left outstanding — no advisory carries a publication date

Inputs used

source	osv
advisories	33
affected_packages	6
assessed_packages	272
unassessed_packages	0
affected_by_severity	high 6
direct_affected_packages	0

Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 272 resolved dependencies against OSV. 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.

53Moderate · 4% of overall

Agent context & guidance

14Critical

How it's scored

0/45	Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15	Machine-readable docs (llms.txt)
14.4/40	Legible commit history — 27 of 100 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.27
agent_instruction_files	—
agent_instruction_max_bytes	—

Verify loop (build / test / typecheck)

72Good

How it's scored

18/18	One-command bootstrap — noxfile.py
22/22	Automated tests
11/11	Lint / format config — pyproject.toml ([tool.ruff])
11/11	Static type checking — src/dataeval/py.typed
10/10	Reproducible environment — devcontainer, Dockerfile, lockfile
0/10	Demonstrated agent practice — no agent-authored commits among the last 100
0/8	Automated maintenance — no automated dependency updates observed
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	yes
typed_language	no
bootstrap_files	noxfile.py
has_devcontainer	yes
has_linter_config	yes
typecheck_configs	src/dataeval/py.typed
agent_commit_share	0
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

81Excellent

How it's scored

27/45	Type-checkable code — Python with type-check config (src/dataeval/py.typed)
54.1/55	Manageable file sizes — 9/530 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	298,829
source_files_sampled	530
oversized_source_files	9

Key facts

20GitHub stars

4contributors

768commits, last 12 months

0days since last push

5releases

1bus factor

0open issues

PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

Star and fork history 0 ★ / 6 ⇿

0Stars

6Forks

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.

OpenSSF Scorecard 3.4 / 10

3.4aggregate

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 · 2026-10-20 04:22 UTC

10	Binary-Artifacts	no binaries found in the repo
0	Branch-Protection	branch protection not enabled on development/release branches
n/a	CI-Tests	no pull request found
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
0	Code-Review	Found 0/30 approved changesets -- score normalized to 0
3	Contributors	project has 1 contributing companies or organizations -- score normalized to 3
10	Dangerous-Workflow	no dangerous workflow patterns detected
0	Dependency-Update-Tool	no update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
10	Maintained	30 commit(s) and 0 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
10	SAST	SAST tool detected: CodeQL
0	Security-Policy	security policy file not detected
0	Signed-Releases	Project has not signed or included provenance with any releases.
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
0	Vulnerabilities	18 existing vulnerabilities detected

Direct dependencies 12

Registry	Package	Version constraint	Manifest
PyPI	maite	`>=0.9.4`	pyproject.toml
PyPI	numba	`>=0.61.0`	pyproject.toml
PyPI	lightgbm	`>=4`	pyproject.toml
PyPI	numpy	`>=1.24.2`	pyproject.toml
PyPI	polars	`>=1.0.0`	pyproject.toml
PyPI	pydantic	`>=2.8`	pyproject.toml
PyPI	scikit-learn	`>=1.5.0`	pyproject.toml
PyPI	scipy	`>=1.10.0`	pyproject.toml
PyPI	torch	`>=2.2.0`	pyproject.toml
PyPI	typing-extensions	`>=4.12`	pyproject.toml
PyPI	xxhash	`>=3.4`	pyproject.toml
PyPI	psutil	`>=7.0.0`	pyproject.toml

All dependencies 272

Full resolved dependency set from the GitHub dependency graph: 16 direct and 256 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	lightgbm	`4.7.0`	direct
PyPI	maite	`0.9.5`	direct
PyPI	numba	`0.66.0`	direct
PyPI	numpy	`2.4.6`	direct
PyPI	polars	`2.0.0`	direct
PyPI	psutil	`7.2.2`	direct
PyPI	pydantic	`2.13.4`	direct
PyPI	scikit-learn	`1.9.0`	direct
PyPI	scipy	`1.17.1`	direct
PyPI	scipy	`1.18.0`	direct
PyPI	torch	`2.13.0`	direct
PyPI	torch	`2.13.0+cpu`	direct
PyPI	torch	`2.13.0+cu126`	direct
PyPI	torch	`2.13.0+cu130`	direct
PyPI	typing-extensions	`4.16.0`	direct
PyPI	xxhash	`3.8.1`	direct
PyPI	ai-edge-litert	`2.1.6`	indirect
PyPI	alabaster	`1.0.0`	indirect
PyPI	annotated-doc	`0.0.5`	indirect
PyPI	annotated-types	`0.8.0`	indirect
PyPI	anyio	`4.14.2`	indirect
PyPI	appdirs	`1.4.4`	indirect
PyPI	appnope	`0.1.4`	indirect
PyPI	argcomplete	`3.7.0`	indirect
PyPI	argon2-cffi	`25.1.0`	indirect
PyPI	argon2-cffi-bindings	`25.1.0`	indirect
PyPI	arrow	`1.4.0`	indirect
PyPI	astroid	`4.1.2`	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	backports-strenum	`1.3.1`	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	charset-normalizer	`3.4.9`	indirect
PyPI	click	`8.4.2`	indirect
PyPI	codespell	`2.4.3`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	colorlog	`6.12.0`	indirect
PyPI	comm	`0.2.3`	indirect
PyPI	contourpy	`1.3.3`	indirect
PyPI	coverage	`7.15.2`	indirect
PyPI	cuda-bindings	`12.9.4`	indirect
PyPI	cuda-bindings	`13.3.1`	indirect
PyPI	cuda-pathfinder	`1.6.0`	indirect
PyPI	cuda-toolkit	`12.6.3`	indirect
PyPI	cuda-toolkit	`13.0.3.0`	indirect
PyPI	cycler	`0.12.1`	indirect
PyPI	dataeval-plots	`0.0.8`	indirect
PyPI	debugpy	`1.8.21`	indirect
PyPI	defusedxml	`0.7.1`	indirect
PyPI	dependency-groups	`1.3.1`	indirect
PyPI	distlib	`0.4.3`	indirect
PyPI	docutils	`0.21.2`	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	flatbuffers	`25.12.19`	indirect
PyPI	fonttools	`4.63.0`	indirect
PyPI	fqdn	`1.5.1`	indirect
PyPI	fsspec	`2026.7.0`	indirect
PyPI	greenlet	`3.5.4`	indirect
PyPI	h11	`0.16.0`	indirect
PyPI	httpcore	`1.0.9`	indirect
PyPI	httpx	`0.28.1`	indirect
PyPI	humanize	`4.16.0`	indirect
PyPI	idna	`3.18`	indirect
PyPI	imageio	`2.37.4`	indirect
PyPI	imagesize	`2.0.0`	indirect
PyPI	importlib-metadata	`9.0.0`	indirect
PyPI	iniconfig	`2.3.0`	indirect
PyPI	ipykernel	`7.3.0`	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-cache	`1.0.1`	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	jupytext	`1.19.5`	indirect
PyPI	kiwisolver	`1.5.0`	indirect
PyPI	lark	`1.3.1`	indirect
PyPI	lazy-loader	`0.5`	indirect
PyPI	lightning-utilities	`0.15.3`	indirect
PyPI	llvmlite	`0.48.0`	indirect
PyPI	maite-datasets	`0.0.21`	indirect
PyPI	markdown-it-py	`4.2.0`	indirect
PyPI	markupsafe	`3.0.1`	indirect
PyPI	matplotlib	`3.11.1`	indirect
PyPI	matplotlib-inline	`0.2.2`	indirect
PyPI	mdit-py-plugins	`0.6.1`	indirect
PyPI	mdurl	`0.1.2`	indirect
PyPI	mistune	`3.3.4`	indirect
PyPI	ml-dtypes	`0.5.4`	indirect
PyPI	mpmath	`1.3.0`	indirect
PyPI	myst-nb	`1.4.0`	indirect
PyPI	myst-parser	`5.1.0`	indirect
PyPI	narwhals	`2.24.0`	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	networkx	`3.6.1`	indirect
PyPI	nodeenv	`1.10.0`	indirect
PyPI	nodejs-wheel-binaries	`24.16.0`	indirect
PyPI	notebook	`7.6.1`	indirect
PyPI	notebook-shim	`0.2.4`	indirect
PyPI	nox	`2026.7.11`	indirect
PyPI	nox-uv	`0.8.0`	indirect
PyPI	nvidia-cublas	`13.1.1.3`	indirect
PyPI	nvidia-cublas-cu12	`12.6.4.1`	indirect
PyPI	nvidia-cuda-cupti	`13.0.85`	indirect
PyPI	nvidia-cuda-cupti-cu12	`12.6.80`	indirect
PyPI	nvidia-cuda-nvrtc	`13.0.88`	indirect
PyPI	nvidia-cuda-nvrtc-cu12	`12.6.85`	indirect
PyPI	nvidia-cuda-runtime	`13.0.96`	indirect
PyPI	nvidia-cuda-runtime-cu12	`12.6.77`	indirect
PyPI	nvidia-cudnn-cu12	`9.10.2.21`	indirect
PyPI	nvidia-cudnn-cu13	`9.20.0.48`	indirect
PyPI	nvidia-cufft	`12.0.0.61`	indirect
PyPI	nvidia-cufft-cu12	`11.3.0.4`	indirect
PyPI	nvidia-cufile	`1.15.1.6`	indirect
PyPI	nvidia-cufile-cu12	`1.11.1.6`	indirect
PyPI	nvidia-curand	`10.4.0.35`	indirect
PyPI	nvidia-curand-cu12	`10.3.7.77`	indirect
PyPI	nvidia-cusolver	`12.0.4.66`	indirect
PyPI	nvidia-cusolver-cu12	`11.7.1.2`	indirect
PyPI	nvidia-cusparse	`12.6.3.3`	indirect
PyPI	nvidia-cusparse-cu12	`12.5.4.2`	indirect
PyPI	nvidia-cusparselt-cu12	`0.7.1`	indirect
PyPI	nvidia-cusparselt-cu13	`0.8.1`	indirect
PyPI	nvidia-ml-py	`13.610.43`	indirect
PyPI	nvidia-nccl-cu12	`2.29.3`	indirect
PyPI	nvidia-nccl-cu13	`2.29.7`	indirect
PyPI	nvidia-nvjitlink	`13.3.33`	indirect
PyPI	nvidia-nvjitlink-cu12	`12.6.85`	indirect
PyPI	nvidia-nvshmem-cu12	`3.4.5`	indirect
PyPI	nvidia-nvshmem-cu13	`3.4.5`	indirect
PyPI	nvidia-nvtx	`13.0.85`	indirect
PyPI	nvidia-nvtx-cu12	`12.6.77`	indirect
PyPI	onnx	`1.22.0`	indirect
PyPI	onnx-ir	`1.0.0`	indirect
PyPI	onnxmltools	`1.16.0`	indirect
PyPI	onnxruntime	`1.28.0`	indirect
PyPI	onnxruntime-gpu	`1.26.0`	indirect
PyPI	onnxruntime-gpu	`1.29.0`	indirect
PyPI	onnxscript	`0.7.1`	indirect
PyPI	opencv-python	`4.11.0.86`	indirect
PyPI	opencv-python-headless	`4.11.0.86`	indirect
PyPI	overrides	`7.7.0`	indirect
PyPI	packaging	`26.2`	indirect
PyPI	pandas	`3.0.5`	indirect
PyPI	pandocfilters	`1.5.1`	indirect
PyPI	parso	`0.8.7`	indirect
PyPI	pexpect	`4.9.0`	indirect
PyPI	pillow	`12.3.0`	indirect
PyPI	pip	`26.2`	indirect
PyPI	platformdirs	`4.11.0`	indirect
PyPI	plotly	`6.9.0`	indirect
PyPI	pluggy	`1.6.0`	indirect
PyPI	polars-runtime-32	`2.0.0`	indirect
PyPI	prometheus-client	`0.26.0`	indirect
PyPI	prompt-toolkit	`3.0.53`	indirect
PyPI	protobuf	`7.35.1`	indirect
PyPI	ptyprocess	`0.7.0`	indirect
PyPI	pure-eval	`0.2.3`	indirect
PyPI	pycparser	`3.0`	indirect
PyPI	pydantic-core	`2.46.4`	indirect
PyPI	pydantic-extra-types	`2.11.1`	indirect
PyPI	pygments	`2.20.0`	indirect
PyPI	pyparsing	`3.3.2`	indirect
PyPI	pyproject2conda	`0.23.1`	indirect
PyPI	pyright	`1.1.411`	indirect
PyPI	pytest	`9.1.1`	indirect
PyPI	pytest-cov	`7.1.0`	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	pywinpty	`3.0.5`	indirect
PyPI	pyyaml	`6.0.3`	indirect
PyPI	pyzmq	`27.1.0`	indirect
PyPI	rapidfuzz	`3.14.5`	indirect
PyPI	rdflib	`7.6.0`	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	rich	`15.0.0`	indirect
PyPI	roman-numerals	`4.1.0`	indirect
PyPI	roman-numerals-py	`4.1.0`	indirect
PyPI	rpds-py	`2026.6.3`	indirect
PyPI	ruff	`0.16.1`	indirect
PyPI	scikit-image	`0.26.0`	indirect
PyPI	send2trash	`2.1.0`	indirect
PyPI	setuptools	`83.0.0`	indirect
PyPI	shellingham	`1.5.4`	indirect
PyPI	six	`1.17.0`	indirect
PyPI	skl2onnx	`1.20.0`	indirect
PyPI	snowballstemmer	`3.1.1`	indirect
PyPI	soupsieve	`2.9.1`	indirect
PyPI	sphinx	`8.2.3`	indirect
PyPI	sphinx-autoapi	`3.8.0`	indirect
PyPI	sphinx-design	`0.7.0`	indirect
PyPI	sphinx-immaterial	`0.13.9`	indirect
PyPI	sphinx-new-tab-link	`0.8.1`	indirect
PyPI	sphinx-tabs	`3.5.0`	indirect
PyPI	sphinxcontrib-applehelp	`2.0.0`	indirect
PyPI	sphinxcontrib-devhelp	`2.0.0`	indirect
PyPI	sphinxcontrib-extdevhelper-kasane	`0.2.1`	indirect
PyPI	sphinxcontrib-htmlhelp	`2.1.0`	indirect
PyPI	sphinxcontrib-jsmath	`1.0.1`	indirect
PyPI	sphinxcontrib-qthelp	`2.0.0`	indirect
PyPI	sphinxcontrib-serializinghtml	`2.0.0`	indirect
PyPI	sqlalchemy	`2.0.51`	indirect
PyPI	stack-data	`0.6.3`	indirect
PyPI	sympy	`1.14.0`	indirect
PyPI	tabulate	`0.10.0`	indirect
PyPI	terminado	`0.18.1`	indirect
PyPI	threadpoolctl	`3.6.0`	indirect
PyPI	tifffile	`2026.3.3`	indirect
PyPI	tifffile	`2026.7.31`	indirect
PyPI	tinycss2	`1.5.1`	indirect
PyPI	tomli	`2.4.1`	indirect
PyPI	torchmetrics	`1.9.0`	indirect
PyPI	torchvision	`0.28.0`	indirect
PyPI	torchvision	`0.28.0+cpu`	indirect
PyPI	torchvision	`0.28.0+cu126`	indirect
PyPI	torchvision	`0.28.0+cu130`	indirect
PyPI	tornado	`6.5.7`	indirect
PyPI	tqdm	`4.70.0`	indirect
PyPI	traitlets	`5.16.0`	indirect
PyPI	triton	`3.7.1`	indirect
PyPI	typer	`0.27.0`	indirect
PyPI	typing-inspection	`0.4.2`	indirect
PyPI	typos	`1.49.0`	indirect
PyPI	tzdata	`2026.3`	indirect
PyPI	ultralytics	`8.4.114`	indirect
PyPI	ultralytics-thop	`2.1.6`	indirect
PyPI	uri-template	`1.3.0`	indirect
PyPI	urllib3	`2.7.0`	indirect
PyPI	uv	`0.12.1`	indirect
PyPI	virtualenv	`21.7.1`	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	zipp	`4.1.0`	indirect

Dependency advisories 6

This repository publishes no package the index resolves, so its own dependency graph was assessed — 272 packages, which also include development and test pins that never ship: 6 carry known advisories, of which 0 are direct.

Package	Version	Relation	Severity	Advisories	Fixed in
jupyter-server	`2.20.0`	indirect	high	2	`2.21.0`
jupyterlab	`4.6.2`	indirect	high	7	`7.6.3`
notebook	`7.6.1`	indirect	high	3	`7.6.3`
tornado	`6.5.7`	indirect	high	7	`6.5.9`
urllib3	`2.7.0`	indirect	high	6	`2.8.0`
virtualenv	`21.7.1`	indirect	high	8	`21.7.13`

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.

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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.

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