Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-26 01:49 UTC

pyvista / pyvista-validation

Python · CMIT★ 1 star⑂ 0 forkssince Aug 2026View on GitHub ↗

pyvista/pyvista-validation holds a health index of 83 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (84/100) and lowest on Community & Adoption (41/100). It was last updated today. A single contributor accounts for most of its recent work.

83
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.

83
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 70 is calibrated to 83 on the published index scale (record calibration 2026-08-02).

Ownership

PyVistaOrganization · verified domain
510 followers66 public repossince May 2019

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIpyvista-validation0.3.0323,75070 days agoarraynumpyvalidation

Metrics by category

Vitality

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

77Good · 21% of overall
How it's scored
36/36Push recency — last push 0 days ago
10.4/36Commit cadence — 15/52 weeks with commits
14.8/18Commit volume — 43 commits in the last year
0/10OpenSSF Scorecard: Maintained — project was created within the last 90 days. Please review its contents carefully
Inputs used
commits_last_year43
human_commit_share0.93
days_since_last_push0
active_weeks_last_year15

Release discipline

100Exceptional
How it's scored
27/27Ships releases — 7 releases published
36/36Release recency — latest release 0 days ago
27/27Release cadence — a release every ~4.5 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count7
latest_release_tagv0.3.0
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases4.5
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?

41Weak · 17% of overall
How it's scored
0/60Stars — 1 stars
0/25Forks — 0 forks
0/15Watchers — 1 watchers
Inputs used
forks0
stars1
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5License — recognized license (MIT)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno
How it's scored
73.5/80Monthly downloads — 323,750 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagespyvista-validation
dependents—
ecosystemspypi
total_downloads—
monthly_downloads323,750
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?

72Good · 23% of overall
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
7.2/22.5Commit distribution — top contributor authored 68% of commits
12.2/13.5Contributor breadth — 9 contributors
10/10OpenSSF Scorecard: Contributors — project has 12 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled9
top_contributor_share0.682
How it's scored
0/42Issue resolution — no issues or no data
27.4/30PR acceptance — 32/35 decided PRs merged
13/13Newcomer PR acceptance — 26/26 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/24 approved changesets -- score normalized to 0
Inputs used
merged_prs32
open_issues0
closed_issues0
prs_merged_7d3
prs_decided_7d3
prs_merged_30d26
prs_decided_30d26
issue_closed_ratio—
closed_unmerged_prs3
first_time_authors_30d1
first_time_prs_merged_30d26
first_time_prs_decided_30d26
Excluded from scoring (no data or not applicable): Issue resolution. Remaining weights renormalized.
How it's scored
30/30Ownership backing — organization-owned
20/20Verified domain
19.5/25Owner reach — 510 followers of pyvista
25/25Track record — 66 public repos, account ~7 yr old
Inputs used
followers510
owner_typeOrganization
is_verifiedyes
owner_loginpyvista
public_repos66
account_age_days2,698

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 0 days ago
20/20Version history — 7 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagespyvista-validation
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

84Excellent · 19% of overall
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
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
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — http://validation.pyvista.org/
0/10Repository description
0/10Topics
0/10Wiki
Inputs used
topics—
has_wikino
homepagehttp://validation.pyvista.org/
docs_sitehttp://validation.pyvista.org/
has_readmeyes
has_docs_diryes
has_descriptionno

Security

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

71Good · 16% of overall
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
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
0/7.5Code-Review — Found 0/24 approved changesets -- score normalized to 0
2.5/2.5Contributors — project has 12 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
0/7.5Maintained — project was created within the last 90 days. Please review its contents carefully
5/5Packaging — packaging workflow detected
5/5Pinned-Dependencies — all dependencies are pinned
5/5SAST — SAST tool is run on all commits
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate6.4
Excluded from scoring (no data or not applicable): Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
0/25Indirect dependencies free of known advisories — transitive set not separable from development and test dependencies in this scope
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages6
unassessed_packages3
affected_by_severitynone
direct_affected_packages0
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories, No advisories left outstanding. Remaining weights renormalized. Matched 6 resolved dependencies against OSV. 3 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list. 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.

70Good · 4% of overall
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history — 83 of 93 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.892
agent_instruction_files—
agent_instruction_max_bytes—
How it's scored
18/18One-command bootstrap — doc/Makefile
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — pyvista_validation/py.typed
0/10Reproducible environment
10/10Demonstrated agent practice — 31 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance — 7 of the last 100 commits are automated dependency updates
10/10OpenSSF Scorecard: Pinned-Dependencies — all dependencies are pinned
Inputs used
has_nixno
has_testsyes
lockfiles—
has_dockerfileno
typed_languageno
bootstrap_filesdoc/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configspyvista_validation/py.typed
agent_commit_share0.31
toolchain_manifests—
dependency_bot_commit_share0.07
How it's scored
27/45Type-checkable code — Python with type-check config (pyvista_validation/py.typed)
51.8/55Manageable file sizes — 2/34 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes123,212
source_files_sampled34
oversized_source_files2

Key facts

1GitHub stars
9contributors
43commits, last 12 months
0days since last push
7releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • deps.dev does not index pypi:pyvista-validation@0.3.0; advisories assessed against the repository dependency graph instead

More detail

OpenSSF Scorecard 6.4 / 10
6.4aggregate

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 · 2026-09-26 01:49 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
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
0Code-ReviewFound 0/24 approved changesets -- score normalized to 0
10Contributorsproject has 12 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintainedproject was created within the last 90 days. Please review its contents carefully
10Packagingpackaging workflow detected
10Pinned-Dependenciesall dependencies are pinned
10SASTSAST tool is run on all commits
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 2
RegistryPackageVersion constraintManifest
PyPInumpy>=1.21.0pyproject.toml
PyPItyping-extensions>=4.4pyproject.toml
All dependencies 9

Full resolved dependency set from the GitHub dependency graph: 1 direct and 8 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPInumpy—direct
PyPInumpydoc1.11.0indirect
PyPIsetuptools—indirect
PyPIsetuptools-scm—indirect
PyPIsphinx8.2.3indirect
PyPIsphinx-book-theme1.1.4indirect
PyPIsphinx-copybutton0.5.2indirect
PyPIsphinx-notfound-page1.1.0indirect
PyPItype-assert0.3.0indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 6 packages, which also include development and test pins that never ship: 0 carry known advisories, of which 0 are direct. 3 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

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 v0.34.0 — full methodology · metrics wiki.

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