Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-17 23:49 UTC

chaobrain / saiunit

Unit-aware computations for AI-driven scientific computing, compatible with NumPy, JAX, PyTorch, CuPy, Dask, ndonnx.

PythonApache-2.0★ 20 stars⑂ 2 forkssince Feb 2025View on GitHub ↗

chaobrain/saiunit holds a health index of 88 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (95/100) and lowest on Community & Adoption (55/100). It was last updated 6 days ago. A single contributor accounts for most of its recent work.

88
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.

88
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 74 is calibrated to 88 on the published index scale (record calibration 2026-08-02).

Ownership

39 followers21 public repossince Oct 2024

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIsaiunit0.5.2-2926 days agophysical-unitphysical-quantityscientific-computingai-for-science

Metrics by category

Vitality

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

86Excellent · 21% of overall
How it's scored
36/36Push recencylast push 6 days ago
12.5/36Commit cadence18/52 weeks with commits
18/18Commit volume118 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year118
human_commit_share0.87
days_since_last_push6
active_weeks_last_year18

Release discipline

100Exceptional
How it's scored
27/27Ships releases17 releases published
36/36Release recencylatest release 26 days ago
27/27Release cadencea release every ~15.5 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count17
latest_release_tagv0.5.2
releases_from_tagsno
days_since_latest_release26
mean_days_between_releases15.5
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?

55Moderate · 17% of overall
How it's scored
20.7/60Stars20 stars
0/25Forks2 forks
2.7/15Watchers4 watchers
Inputs used
forks2
stars20
watchers4
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

92Excellent
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (Apache-2.0)
18/18CONTRIBUTING guide
13.5/13.5Code of conduct
0/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges5
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicesbadge.fury.io, github.com, readthedocs.org, shields.io
has_pull_request_templateyes

Sustainability & Governance

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

66Good · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
4/22.5Commit distributiontop contributor authored 82% of commits
6.8/13.5Contributor breadth5 contributors
6/10OpenSSF Scorecard: Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled5
top_contributor_share0.823
How it's scored
42/42Issue resolution100% of issues closed
28.2/30PR acceptance124/132 decided PRs merged
13/13Newcomer PR acceptance2/2 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 2/28 approved changesets -- score normalized to 0
Inputs used
merged_prs124
open_issues0
closed_issues10
prs_merged_7d1
prs_decided_7d1
prs_merged_30d5
prs_decided_30d5
issue_closed_ratio1
closed_unmerged_prs8
first_time_authors_30d1
first_time_prs_merged_30d2
first_time_prs_decided_30d2
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
11.5/25Owner reach39 followers of chaobrain
13.4/25Track record21 public repos, account ~1 yr old
Inputs used
followers39
owner_typeOrganization
is_verified
owner_loginchaobrain
public_repos21
account_age_days660
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 26 days ago
20/20Version history29 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagessaiunit
ecosystemspypi
any_deprecatedno
min_days_since_publish26

Engineering Quality

Are baseline engineering and documentation practices in place?

95Exceptional · 19% of overall
How it's scored
24/24CI workflows4 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
18/20OpenSSF Scorecard: CI-Tests25 out of 27 merged PRs checked by a CI test -- score normalized to 9
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 sitehttps://saiunit.readthedocs.io/
10/10Repository description
10/10Topics4 topics
10/10Wiki
Inputs used
topicsai4science, physical-quantities, physical-units, scientific-computing
has_wikiyes
homepagehttps://saiunit.readthedocs.io/
docs_sitehttps://saiunit.readthedocs.io/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

66Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
2.2/2.5CI-Tests25 out of 27 merged PRs checked by a CI test -- score normalized to 9
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 2/28 approved changesets -- score normalized to 0
1.5/2.5Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10/10Dangerous-Workflowno dangerous workflow patterns detected
7.5/7.5Dependency-Update-Toolupdate tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
7.5/7.5Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
5/5Packagingpackaging workflow detected
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
5/5Security-Policysecurity policy file detected
0/7.5Signed-Releasesno data
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.8
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 advisoriesno direct dependency carries a known advisory
25/25Indirect dependencies free of known advisoriesno indirect dependency carries a known advisory
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages4
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:saiunit@0.5.2 runtime dependency closure — what installing the published package pulls in — 4 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.

67Good · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
40/40Legible commit history80 of 87 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.92
agent_instruction_files
agent_instruction_max_bytes
How it's scored
18/18One-command bootstrapdocs/Makefile
22/22Automated tests
11/11Lint / format config
11/11Static type checkingbrainunit/brainunit/py.typed, saiunit/py.typed
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance13 of the last 100 commits are automated dependency updates
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configsbrainunit/brainunit/py.typed, saiunit/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.13
How it's scored
27/45Type-checkable codePython with type-check config (brainunit/brainunit/py.typed, saiunit/py.typed)
52.7/55Manageable file sizes8/193 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes259,085
source_files_sampled193
oversized_source_files8
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesexamples, notebooks
Inputs used
example_dirsexamples, notebooks
has_mcp_signalno
api_schema_files
interfaces_expected_of
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

20GitHub stars
5contributors
118commits, last 12 months
6days since last push
17releases
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 ★ / 2 ⇿
0Stars
2Forks
16Releases

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.

111222212025-052026-012026-08
Major 0Minor 5Patch 11

Each point covers 2 days.

OpenSSF Scorecard 5.8 / 10
5.8aggregate

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 · 2026-08-17 23:49 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
9CI-Tests25 out of 27 merged PRs checked by a CI test -- score normalized to 9
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 2/28 approved changesets -- score normalized to 0
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
10Security-Policysecurity policy file detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPInumpypyproject.toml
PyPItyping_extensionspyproject.toml
PyPIarray_api_compat>=1.9pyproject.toml
PyPIopt_einsumpyproject.toml
All dependencies 26

Full resolved dependency set from the GitHub dependency graph: 4 direct and 22 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIarray-api-compatdirect
PyPInumpydirect
PyPIopt-einsumdirect
PyPItyping-extensionsdirect
PyPIabsl-pyindirect
PyPIbrainstateindirect
PyPIbrainx-sphinx-headerindirect
PyPIcupy-cuda12xindirect
PyPIdaskindirect
PyPIjaxindirect
PyPIjaxlibindirect
PyPIjinja2indirect
PyPIjupyter-sphinxindirect
PyPImatplotlibindirect
PyPImyst-nbindirect
PyPIndonnxindirect
PyPIpandocindirect
PyPIpytestindirect
PyPIsphinxindirect
PyPIsphinx-autodoc-typehintsindirect
PyPIsphinx-book-themeindirect
PyPIsphinx-copybuttonindirect
PyPIsphinx-designindirect
PyPIsphinx-remove-toctreesindirect
PyPIsphinx-thebeindirect
PyPItorchindirect
Dependency advisories 0

Installing pypi:saiunit@0.5.2 pulls in 4 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

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 v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.