Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-08 18:32 UTC

aio-libs / janus

Thread-safe asyncio-aware queue for Python

PythonApache-2.0★ 964 stars⑂ 54 forkssince Jun 2015View on GitHub ↗

aio-libs/janus holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Sustainability & Governance (82/100) and lowest on AI Readiness (43/100). It was last updated 5 days ago. 2 contributors account for most of its recent work.

78
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.

78
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 67 is calibrated to 78 on the published index scale (record calibration 2026-08-02).

Ownership

aio-libsOrganization
1,203 followers68 public repossince Mar 2014

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIjanus2.0.0-21603 days agojanusqueueasyncio

Metrics by category

Vitality

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

48Weak · 21% of overall
How it's scored
36/36Push recencylast push 5 days ago
0/36Commit cadence31/52 weeks with commits, discounted for automation: 0 of the last 100 commits human-authored, spanning 517 days
0/18Commit volume52 commits in the last year, discounted for automation: 0 of the last 100 commits human-authored, spanning 517 days
7/10OpenSSF Scorecard: Maintained9 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 7
Inputs used
commits_last_year52
human_commit_share0
days_since_last_push5
active_weeks_last_year31
How it's scored
27/27Ships releases16 releases published
7.2/36Release recencylatest release 603 days ago
12.6/27Release cadencea release every ~278.7 days
8/10OpenSSF Scorecard: Signed-Releases2 out of the last 2 releases have a total of 2 signed artifacts.
Inputs used
releases_count16
latest_release_tagv2.0.0
releases_from_tagsno
days_since_latest_release603
mean_days_between_releases278.7

Community & Adoption

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

80Excellent · 17% of overall
How it's scored
48.4/60Stars964 stars
14.4/25Forks54 forks
6.5/15Watchers16 watchers
Inputs used
forks54
stars964
watchers16
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_badges3
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateyes

Sustainability & Governance

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

82Excellent · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
12/22.5Commit distributiontop contributor authored 47% of commits
13.5/13.5Contributor breadth20 contributors
10/10OpenSSF Scorecard: Contributorsproject has 5 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled20
top_contributor_share0.467
How it's scored
40/42Issue resolution95% of issues closed
27.9/30PR acceptance756/813 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs756
open_issues2
closed_issues41
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.953
closed_unmerged_prs57
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance, OpenSSF Scorecard: Code-Review. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
22.1/25Owner reach1,203 followers of aio-libs
25/25Track record68 public repos, account ~12 yr old
Inputs used
followers1,203
owner_typeOrganization
is_verified
owner_loginaio-libs
public_repos68
account_age_days4,520
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
14/35Publish recencylatest publish 603 days ago
20/20Version history21 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesjanus
ecosystemspypi
any_deprecatedno
min_days_since_publish603

Engineering Quality

Are baseline engineering and documentation practices in place?

61Moderate · 19% of overall
How it's scored
24/24CI workflows2 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

50Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics4 topics
0/10Wiki
Inputs used
topicsasyncio, queue, threadsafe, mypy
has_wikino
homepage
docs_site
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

69Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
2.2/7.5Branch-Protectionbranch protection is not maximal on development and all release branches
2.5/2.5CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-Reviewno data
2.5/2.5Contributorsproject has 5 contributing companies or organizations
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
5.2/7.5Maintained9 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 7
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
6/7.5Signed-Releases2 out of the last 2 releases have a total of 2 signed artifacts.
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
3.8/7.5Vulnerabilities5 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate6.1
Excluded from scoring (no data or not applicable): Code-Review. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisoriesno direct dependency carries a known advisory
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
0/40No advisories left outstandingno advisory carries a publication date
Inputs used
sourceosv
advisories5
affected_packages2
assessed_packages15
unassessed_packages1
affected_by_severitycritical 1, moderate 1
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 15 resolved dependencies against OSV. 1 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.

43Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
0/40Legible commit historyno 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.
How it's scored
18/18One-command bootstrapMakefile
22/22Automated tests
0/11Lint / format config
11/11Static type checkingjanus/py.typed
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance100 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_filesMakefile
has_devcontainerno
has_linter_configno
typecheck_configsjanus/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share1
How it's scored
27/45Type-checkable codePython with type-check config (janus/py.typed)
55/55Manageable file sizes0/6 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes26,346
source_files_sampled6
oversized_source_files0

Key facts

964GitHub stars
20contributors
52commits, last 12 months
5days since last push
16releases
2bus factor
2open 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 ★ / 54 ⇿
0Stars
54Forks
11Releases

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.

01020304050605422016-032021-052026-07
Major 2Minor 5Patch 4

Each point covers 10 days.

OpenSSF Scorecard 6.1 / 10
6.1aggregate

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 · 2026-08-08 18:31 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
n/aCode-ReviewFound no human activity in the last 30 changesets
10Contributorsproject has 5 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
7Maintained9 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 7
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
8Signed-Releases2 out of the last 2 releases have a total of 2 signed artifacts.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
5Vulnerabilities5 existing vulnerabilities detected
All dependencies 16

Full resolved dependency set from the GitHub dependency graph: 0 direct and 16 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIbackports-asyncio-runner1.2.0indirect
PyPIbandit1.8.6indirect
PyPIblack25.11.0indirect
PyPIcoverage7.10.6indirect
PyPIdocutils0.23indirect
PyPIflake87.3.0indirect
PyPIisort6.1.0indirect
PyPImypy1.17.1indirect
PyPIpyroma5.0.1indirect
PyPIpytest8.4.2indirect
PyPIpytest-asyncio1.2.0indirect
PyPIpytest-codspeed5.0.3indirect
PyPIpytest-cov7.1.0indirect
PyPIsetuptoolsindirect
PyPItox4.30.3indirect
PyPIwheel0.47.0indirect
Dependency advisories 2

This repository publishes no package the index resolves, so its own dependency graph was assessed — 15 packages, which also include development and test pins that never ship: 2 carry known advisories, of which 0 are direct. 1 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
black25.11.0indirectcritical326.3.1
pytest8.4.2indirectmoderate29.0.3

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.