Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-22 11:34 UTC

aria-ml / dataeval

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

PythonMIT★ 18 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 69 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.

69
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.

69
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 62 is calibrated to 69 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

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIdataeval1.0.63,67981133 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
36/36Push recency — last push 0 days ago
33.2/36Commit cadence — 48/52 weeks with commits
18/18Commit volume — 633 commits in the last year
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year633
human_commit_share1
days_since_last_push0
active_weeks_last_year48

Release discipline

90Excellent
How it's scored
27/27Ships releases — 21 releases published
36/36Release recency — latest release 2 days ago
27/27Release cadence — a release every ~16.6 days
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Inputs used
releases_count21
latest_release_tagv1.1.0-rc6
releases_from_tagsno
days_since_latest_release2
mean_days_between_releases16.6

Community & Adoption

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

50Moderate · 17% of overall

Popularity & adoption

26At Risk
How it's scored
20/60Stars — 18 stars
5.8/25Forks — 6 forks
0/15Watchers — 2 watchers
Inputs used
forks6
stars18
watchers2
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

70Good
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_servicesreadthedocs.org, shields.io
has_pull_request_templateno

Ecosystem adoption (downloads)

59Moderate
How it's scored
47.5/80Monthly downloads — 3,679 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesdataeval
dependents—
ecosystemspypi
total_downloads—
monthly_downloads3,679
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
9/54Bus factor — 1 contributor(s) cover half of all commits
2.6/22.5Commit distribution — top contributor authored 88% of commits
5.4/13.5Contributor breadth — 4 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled4
top_contributor_share0.884

Issue & PR responsiveness

1Critical
How it's scored
0/42Issue resolution — no issues or no data
0/30PR acceptance — 0/1 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs0
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio—
closed_unmerged_prs1
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Issue resolution, Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

29At Risk
How it's scored
10/30Ownership backing — personal (user) account
0/20Verified domain — not applicable to user accounts
0/25Owner reach — 0 followers of aria-ml
12.9/25Track record — 9 public repos, account ~2 yr old
Inputs used
followers0
owner_typeUser
is_verified—
owner_loginaria-ml
public_repos9
account_age_days1,017
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 133 days ago
20/20Version history — 81 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdataeval
ecosystemspypi
any_deprecatedno
min_days_since_publish133

Engineering Quality

Are baseline engineering and documentation practices in place?

84Excellent · 19% of overall

Engineering practices

80Excellent
How it's scored
24/24CI workflows — 5 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://dataeval.readthedocs.io
10/10Repository description
10/10Topics — 8 topics
0/10Wiki
Inputs used
topicsai, data, metrics, sufficiency, bias-detection, linter, out-of-distribution-detection, outlier-detection
has_wikino
homepagehttps://dataeval.readthedocs.io
docs_sitehttps://dataeval.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionyes

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
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
0/2.5CI-Tests — no data
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/30 approved changesets -- score normalized to 0
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
7.5/7.5Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
5/5SAST — SAST tool detected: CodeQL
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 84 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate3.4
Excluded from scoring (no data or not applicable): CI-Tests, Packaging. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages19
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:dataeval@1.0.6 runtime dependency closure — what installing the published package pulls in — 19 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.

51Moderate · 4% of overall

Agent context & guidance

8Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
8.5/40Legible commit history — 16 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.16
agent_instruction_files—
agent_instruction_max_bytes—

Verify loop (build / test / typecheck)

72Good
How it's scored
18/18One-command bootstrap — noxfile.py
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — src/dataeval/py.typed
10/10Reproducible environment — devcontainer, Dockerfile, lockfile
0/10Demonstrated agent practice — no agent-authored commits among the last 100
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilespoetry.lock, uv.lock
has_dockerfileyes
typed_languageno
bootstrap_filesnoxfile.py
has_devcontaineryes
has_linter_configyes
typecheck_configssrc/dataeval/py.typed
agent_commit_share0
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

81Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (src/dataeval/py.typed)
54.2/55Manageable file sizes — 6/424 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes189,504
source_files_sampled424
oversized_source_files6

Key facts

18GitHub stars
4contributors
633commits, last 12 months
0days since last push
21releases
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
14Releases

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.

123456612025-032025-102026-04
Major 1Minor 2Patch 6
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 · 2026-08-22 11:34 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool detected: CodeQL
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities84 existing vulnerabilities detected
Direct dependencies 12
RegistryPackageVersion constraintManifest
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PyPInumba>=0.61.0pyproject.toml
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All dependencies 440

Full resolved dependency set from the GitHub dependency graph: 26 direct and 414 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

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PyPInvidia-nccl-cu122.29.3indirect
PyPInvidia-nccl-cu132.29.7indirect
PyPInvidia-nvjitlink13.3.33indirect
PyPInvidia-nvjitlink-cu1212.6.85indirect
PyPInvidia-nvshmem-cu123.4.5indirect
PyPInvidia-nvshmem-cu133.4.5indirect
PyPInvidia-nvtx13.0.85indirect
PyPInvidia-nvtx-cu1212.6.77indirect
PyPIonnx1.21.0indirect
PyPIonnx1.22.0indirect
PyPIonnx-ir1.0.0indirect
PyPIonnxruntime1.23.2indirect
PyPIonnxruntime1.24.4indirect
PyPIonnxruntime1.28.0indirect
PyPIonnxruntime-gpu1.23.2indirect
PyPIonnxruntime-gpu1.24.4indirect
PyPIonnxruntime-gpu1.26.0indirect
PyPIonnxruntime-gpu1.29.0indirect
PyPIonnxscript0.7.1indirect
PyPIopencv-contrib-python4.11.0.86indirect
PyPIopencv-contrib-python4.12.0.88indirect
PyPIopencv-python4.11.0.86indirect
PyPIopencv-python4.12.0.88indirect
PyPIopencv-python-headless4.11.0.86indirect
PyPIopencv-python-headless4.12.0.88indirect
PyPIoverrides7.7.0indirect
PyPIpackaging26.0indirect
PyPIpackaging26.2indirect
PyPIpandas2.3.3indirect
PyPIpandas3.0.3indirect
PyPIpandas3.0.5indirect
PyPIpandocfilters1.5.1indirect
PyPIparso0.8.6indirect
PyPIparso0.8.7indirect
PyPIpbs-installer2025.12.17indirect
PyPIpexpect4.9.0indirect
PyPIpillow12.2.0indirect
PyPIpillow12.3.0indirect
PyPIpip26.0.1indirect
PyPIpip26.2indirect
PyPIpkginfo1.12.1.2indirect
PyPIplatformdirs4.11.0indirect
PyPIplatformdirs4.9.4indirect
PyPIplotly6.6.0indirect
PyPIplotly6.9.0indirect
PyPIpluggy1.6.0indirect
PyPIpoetry2.2.0indirect
PyPIpoetry-core2.2.0indirect
PyPIpolars-runtime-321.39.3indirect
PyPIpolars-runtime-321.43.1indirect
PyPIprometheus-client0.24.1indirect
PyPIprometheus-client0.26.0indirect
PyPIprompt-toolkit3.0.52indirect
PyPIprompt-toolkit3.0.53indirect
PyPIprotobuf7.34.1indirect
PyPIprotobuf7.35.1indirect
PyPIptyprocess0.7.0indirect
PyPIpure-eval0.2.3indirect
PyPIpycparser3.0indirect
PyPIpydantic-core2.41.5indirect
PyPIpydantic-core2.46.4indirect
PyPIpydantic-extra-types2.11.1indirect
PyPIpygments2.20.0indirect
PyPIpyparsing3.3.2indirect
PyPIpyproject-hooks1.2.0indirect
PyPIpyproject2conda0.22.1indirect
PyPIpyproject2conda0.23.1indirect
PyPIpyreadline33.5.4indirect
PyPIpyreadline33.5.6indirect
PyPIpyright1.1.408indirect
PyPIpyright1.1.411indirect
PyPIpytest9.0.2indirect
PyPIpytest9.1.1indirect
PyPIpytest-cov7.1.0indirect
PyPIpytest-xdist3.8.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpython-discovery1.2.1indirect
PyPIpython-discovery1.5.1indirect
PyPIpython-json-logger4.1.0indirect
PyPIpytz2026.2indirect
PyPIpytz2026.3.post1indirect
PyPIpywin32-ctypes0.2.3indirect
PyPIpywinpty3.0.3indirect
PyPIpywinpty3.0.5indirect
PyPIpyyaml6.0.3indirect
PyPIpyzmq27.1.0indirect
PyPIrapidfuzz3.14.3indirect
PyPIrapidfuzz3.14.5indirect
PyPIrdflib7.6.0indirect
PyPIreferencing0.37.0indirect
PyPIrequests2.33.1indirect
PyPIrequests2.34.2indirect
PyPIrequests-toolbelt1.0.0indirect
PyPIrfc3339-validator0.1.4indirect
PyPIrfc3986-validator0.1.1indirect
PyPIrfc3987-syntax1.1.0indirect
PyPIrich14.3.3indirect
PyPIrich15.0.0indirect
PyPIroman-numerals4.1.0indirect
PyPIroman-numerals-py4.1.0indirect
PyPIrpds-py0.30.0indirect
PyPIrpds-py2026.6.3indirect
PyPIruff0.15.9indirect
PyPIruff0.16.1indirect
PyPIscikit-image0.25.2indirect
PyPIscikit-image0.26.0indirect
PyPIsecretstorage3.5.0indirect
PyPIsend2trash2.1.0indirect
PyPIsetuptools82.0.1indirect
PyPIsetuptools83.0.0indirect
PyPIshellingham1.5.4indirect
PyPIsix1.17.0indirect
PyPIsnowballstemmer3.0.1indirect
PyPIsnowballstemmer3.1.1indirect
PyPIsoupsieve2.8.3indirect
PyPIsoupsieve2.9.1indirect
PyPIsphinx8.1.3indirect
PyPIsphinx8.2.3indirect
PyPIsphinx-autoapi3.8.0indirect
PyPIsphinx-design0.6.1indirect
PyPIsphinx-design0.7.0indirect
PyPIsphinx-immaterial0.13.9indirect
PyPIsphinx-new-tab-link0.8.1indirect
PyPIsphinx-tabs3.5.0indirect
PyPIsphinxcontrib-applehelp2.0.0indirect
PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-extdevhelper-kasane0.2.1indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
PyPIsphinxcontrib-qthelp2.0.0indirect
PyPIsphinxcontrib-serializinghtml2.0.0indirect
PyPIsqlalchemy2.0.49indirect
PyPIsqlalchemy2.0.51indirect
PyPIstack-data0.6.3indirect
PyPIsympy1.14.0indirect
PyPItabulate0.10.0indirect
PyPIterminado0.18.1indirect
PyPIthreadpoolctl3.6.0indirect
PyPItifffile2025.5.10indirect
PyPItifffile2026.3.3indirect
PyPItifffile2026.7.31indirect
PyPItinycss21.4.0indirect
PyPItinycss21.5.1indirect
PyPItomli2.4.1indirect
PyPItomlkit0.14.0indirect
PyPItomlkit0.15.1indirect
PyPItorchmetrics1.9.0indirect
PyPItorchvision0.28.0indirect
PyPItorchvision0.28.0+cpuindirect
PyPItorchvision0.28.0+cu126indirect
PyPItorchvision0.28.0+cu130indirect
PyPItornado6.5.5indirect
PyPItornado6.5.7indirect
PyPItqdm4.68.3indirect
PyPItqdm4.70.0indirect
PyPItraitlets5.14.3indirect
PyPItraitlets5.16.0indirect
PyPItriton3.7.1indirect
PyPItrove-classifiers2026.1.14.14indirect
PyPItrove-classifiers2026.6.1.19indirect
PyPItyper0.24.1indirect
PyPItyper0.27.0indirect
PyPItypes-pyyaml6.0.12.20260724indirect
PyPItypes-requests2.33.0.20260712indirect
PyPItyping-inspection0.4.2indirect
PyPItypos1.49.0indirect
PyPItzdata2026.1indirect
PyPItzdata2026.3indirect
PyPIultralytics8.4.114indirect
PyPIultralytics8.4.60indirect
PyPIultralytics-thop2.0.19indirect
PyPIultralytics-thop2.1.6indirect
PyPIuri-template1.3.0indirect
PyPIurllib32.6.3indirect
PyPIurllib32.7.0indirect
PyPIuv0.11.3indirect
PyPIuv0.12.1indirect
PyPIvirtualenv21.2.0indirect
PyPIvirtualenv21.7.1indirect
PyPIwcwidth0.6.0indirect
PyPIwcwidth0.8.2indirect
PyPIwebcolors25.10.0indirect
PyPIwebencodings0.5.1indirect
PyPIwebsocket-client1.9.0indirect
PyPIwidgetsnbextension4.0.15indirect
PyPIxattr1.3.0indirect
PyPIzipp3.23.0indirect
PyPIzipp4.1.0indirect
PyPIzstandard0.25.0indirect
Dependency advisories 0

Installing pypi:dataeval@1.0.6 pulls in 19 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.

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