Public record
Software health reportschema 0.12.0 · metrics 2.10.0 · 2026-07-18 13:51 UTC

beartype / plum

Multiple dispatch in Python

PythonMIT★ 647 stars⑂ 27 forkssince Nov 2017View on GitHub ↗
KindLibraryhow this is determined
#multiple-dispatch#python

beartype/plum holds a health index of 88 out of 100, placing it in the Excellent band. It scores highest on Engineering Quality (96/100) and lowest on Community & Adoption (56/100). It was last updated 4 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

beartypeOrganization
60 followers8 public repossince Apr 2020

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIplum-dispatch2.9.0-7681 days agomultipledispatch

Metrics by category

Vitality

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

84Excellent · 21% of overall

Development activity

79Good
How it's scored
36/36Push recency — last push 4 days ago
15.9/36Commit cadence — 23/52 weeks with commits
17.4/18Commit volume — 86 commits in the last year
10/10OpenSSF Scorecard: Maintained — 13 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year86
human_commit_share—
days_since_last_push4
active_weeks_last_year23

Release discipline

92Excellent
How it's scored
27/27Ships releases — 75 releases published
36/36Release recency — latest release 81 days ago
19.8/27Release cadence — a release every ~52.8 days
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count75
latest_release_tagv2.9.0
releases_from_tagsno
days_since_latest_release81
mean_days_between_releases52.8
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?

56Moderate · 17% of overall

Popularity & adoption

61Moderate
How it's scored
45.6/60Stars — 647 stars
11.8/25Forks — 27 forks
3.3/15Watchers — 5 watchers
Inputs used
forks27
stars647
watchers5
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

50Moderate
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_badges—
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Sustainability & Governance

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

68Good · 23% of overall

Maintainer resilience (bus factor)

38Weak
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
5.6/22.5Commit distribution — top contributor authored 75% of commits
13.5/13.5Contributor breadth — 15 contributors
10/10OpenSSF Scorecard: Contributors — project has 13 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled15
top_contributor_share0.752

Issue & PR responsiveness

71Good
How it's scored
28.3/42Issue resolution — 67% of issues closed
27.9/30PR acceptance — 132/142 decided PRs merged
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
6/15OpenSSF Scorecard: Code-Review — Found 7/17 approved changesets -- score normalized to 4
Inputs used
merged_prs132
open_issues43
closed_issues89
prs_merged_7d—
prs_decided_7d—
prs_merged_30d—
prs_decided_30d—
issue_closed_ratio0.674
closed_unmerged_prs10
first_time_authors_30d—
first_time_prs_merged_30d—
first_time_prs_decided_30d—
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

77Good
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain — verified-domain status not read for this organization
12.8/25Owner reach — 60 followers of beartype
18.9/25Track record — 8 public repos, account ~6 yr old
Inputs used
followers60
owner_typeOrganization
is_verified—
owner_loginbeartype
public_repos8
account_age_days2,297
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 81 days ago
20/20Version history — 76 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesplum-dispatch
ecosystemspypi
any_deprecatedno
min_days_since_publish81

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

94Exceptional
How it's scored
24/24CI workflows — 6 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 20 out of 20 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

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://beartype.github.io/plum
10/10Repository description
10/10Topics — 2 topics
10/10Wiki
Inputs used
topicsmultiple-dispatch, python
has_wikiyes
homepagehttps://beartype.github.io/plum
docs_sitehttps://beartype.github.io/plum
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

Security posture

66Good
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — no data
2.5/2.5CI-Tests — 20 out of 20 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
3/7.5Code-Review — Found 7/17 approved changesets -- score normalized to 4
2.5/2.5Contributors — project has 13 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
7.5/7.5Maintained — 13 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
5/5SAST — SAST tool is run on all commits
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
6/7.5Vulnerabilities — 2 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6.6
Excluded from scoring (no data or not applicable): Branch-Protection, Signed-Releases. Remaining weights renormalized.

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.

57Moderate · 4% of overall

Agent context & guidance

1Critical
How it's scored
0/45Agent instructions — no CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit history — no data
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share—
agent_instruction_files—
agent_instruction_max_bytes—
Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.

Verify loop (build / test / typecheck)

89Excellent
How it's scored
18/18One-command bootstrap — noxfile.py
22/22Automated tests
11/11Lint / format config
11/11Static type checking — src/plum/py.typed
10/10Reproducible environment — lockfile
0/10Demonstrated agent practice — no data
0/8Automated maintenance — no data
1/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_filesnoxfile.py
has_devcontainerno
has_linter_configyes
typecheck_configssrc/plum/py.typed
agent_commit_share—
toolchain_manifests—
dependency_bot_commit_share—
Excluded from scoring (no data or not applicable): Demonstrated agent practice, Automated maintenance. Remaining weights renormalized.

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (src/plum/py.typed)
55/55Manageable file sizes — 0/44 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes22,779
source_files_sampled44
oversized_source_files0

Key facts

647GitHub stars
15contributors
86commits, last 12 months
4days since last push
75releases
1bus factor
43open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 6.6 / 10
6.6aggregate

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 · 2026-07-18 13:50 UTC

10Binary-Artifactsno binaries found in the repo
n/aBranch-Protectioninternal 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
10CI-Tests20 out of 20 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
4Code-ReviewFound 7/17 approved changesets -- score normalized to 4
10Contributorsproject has 13 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained13 commit(s) and 3 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
1Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 1
10SASTSAST tool is run on all commits
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
8Vulnerabilities2 existing vulnerabilities detected
Direct dependencies 4
RegistryPackageVersion constraintManifest
PyPIbeartype>=0.22.2pyproject.toml
PyPIbeartype>=0.16.2pyproject.toml
PyPItyping-extensions>=4.9.0pyproject.toml
PyPIrich>=10.0pyproject.toml
All dependencies 169

Full resolved dependency set from the GitHub dependency graph: 3 direct and 166 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
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PyPIrich14.2.0direct
PyPItyping-extensions4.15.0direct
PyPIaccessible-pygments0.0.5indirect
PyPIalabaster0.7.16indirect
PyPIanyio4.12.1indirect
PyPIappnope0.1.4indirect
PyPIargcomplete3.6.3indirect
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PyPIattrs25.4.0indirect
PyPIbabel2.17.0indirect
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PyPIbuild1.4.0indirect
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PyPIcffi2.0.0indirect
PyPIcfgv3.5.0indirect
PyPIcharset-normalizer3.4.4indirect
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PyPIdecorator5.2.1indirect
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PyPIh110.16.0indirect
PyPIhatch1.16.3indirect
PyPIhatch-mypyc0.16.0indirect
PyPIhatch-vcs0.5.0indirect
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PyPIsix1.17.0indirect
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PyPIsphinx-multitoc-numbering0.1.3indirect
PyPIsphinx-thebe0.3.1indirect
PyPIsphinx-togglebutton0.3.2indirect
PyPIsphinxcontrib-applehelp2.0.0indirect
PyPIsphinxcontrib-bibtex2.6.5indirect
PyPIsphinxcontrib-devhelp2.0.0indirect
PyPIsphinxcontrib-htmlhelp2.1.0indirect
PyPIsphinxcontrib-jsmath1.0.1indirect
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PyPIsphinxcontrib-serializinghtml2.0.0indirect
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PyPItomli2.3.0indirect
PyPItomli-w1.2.0indirect
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PyPItornado6.5.7indirect
PyPItraitlets5.14.3indirect
PyPItrove-classifiers2026.1.14.14indirect
PyPIuc-micro-py1.0.3indirect
PyPIurllib32.7.0indirect
PyPIuserpath1.9.2indirect
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PyPIwcwidth0.2.14indirect
PyPIwheel0.46.2indirect
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Raw JSON report machine-readable

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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 v0.12.0 — full methodology · metrics wiki.

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