Public record
Software health reportschema 0.30.0 · metrics 2.10.0 · 2026-08-04 18:21 UTC

aio-libs / frozenlist

FrozenList is a list-like structure that implements collections.abc.MutableSequence and can be made immutable.

PythonApache-2.0★ 123 stars⑂ 39 forkssince Aug 2019View on GitHub ↗

aio-libs/frozenlist holds a health index of 94 out of 100, placing it in the Exceptional band. It scores highest on Engineering Quality (100/100) and lowest on Vitality (73/100). It was last updated 1 day ago. 2 contributors account for most of its recent work.

94
overall / 100
Exceptional

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.

94
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 81 is calibrated to 94 on the published index scale (record calibration 2026-08-02).

Ownership

aio-libsOrganization
1,200 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 publish
PyPIfrozenlist1.8.0-18302 days ago

Metrics by category

Vitality

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

73Good · 21% of overall
How it's scored
36/36Push recencylast push 1 days ago
15.9/36Commit cadence23/52 weeks with commits
18/18Commit volume117 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 6 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year117
human_commit_share0.3
days_since_last_push1
active_weeks_last_year23
How it's scored
27/27Ships releases19 releases published
16.2/36Release recencylatest release 302 days ago
12.6/27Release cadencea release every ~128.9 days
6/10OpenSSF Scorecard: Signed-Releases4 out of the last 5 releases have a total of 4 signed artifacts.
Inputs used
releases_count19
latest_release_tagv1.8.0
releases_from_tagsno
days_since_latest_release302
mean_days_between_releases128.9

Community & Adoption

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

74Good · 17% of overall
How it's scored
33.8/60Stars123 stars
13.2/25Forks39 forks
4.7/15Watchers8 watchers
Inputs used
forks39
stars123
watchers8
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

100Exceptional
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
7.2/7.2Issue template
6.3/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges6
has_contributingyes
has_issue_templateyes
has_code_of_conductyes
readme_badge_servicescodecov.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?

80Excellent · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
13.7/22.5Commit distributiontop contributor authored 39% of commits
13.5/13.5Contributor breadth18 contributors
10/10OpenSSF Scorecard: Contributorsproject has 59 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled18
top_contributor_share0.392
How it's scored
39.6/42Issue resolution94% of issues closed
25.6/30PR acceptance649/762 decided PRs merged
0/13Newcomer PR acceptance0/1 first-time contributors' PRs merged in 30d
0/15OpenSSF Scorecard: Code-Reviewno data
Inputs used
merged_prs649
open_issues3
closed_issues50
prs_merged_7d0
prs_decided_7d1
prs_merged_30d0
prs_decided_30d1
issue_closed_ratio0.943
closed_unmerged_prs113
first_time_authors_30d1
first_time_prs_merged_30d0
first_time_prs_decided_30d1
Excluded from scoring (no data or not applicable): 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 reach1,200 followers of aio-libs
25/25Track record68 public repos, account ~12 yr old
Inputs used
followers1,200
owner_typeOrganization
is_verified
owner_loginaio-libs
public_repos68
account_age_days4,516
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
26/35Publish recencylatest publish 302 days ago
20/20Version history18 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesfrozenlist
ecosystemspypi
any_deprecatedno
min_days_since_publish302

Engineering Quality

Are baseline engineering and documentation practices in place?

100Exceptional · 19% of overall

Engineering practices

100Exceptional
How it's scored
24/24CI workflows5 workflow(s)
24/24Tests present
16/16Linter configtox.ini
9.6/9.6Pre-commit hooks
6.4/6.4.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_editorconfigyes
has_linter_configyes
has_precommit_configyes

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://frozenlist.aio-libs.org
10/10Repository description
10/10Topics2 topics
10/10Wiki
Inputs used
topicsaiohttp, frozenlist
has_wikiyes
homepagehttps://frozenlist.aio-libs.org
docs_sitehttps://frozenlist.aio-libs.org
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

79Good · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
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 59 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
7.5/7.5Maintained30 commit(s) and 6 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
5/5SASTSAST tool is run on all commits
5/5Security-Policysecurity policy file detected
4.5/7.5Signed-Releases4 out of the last 5 releases have a total of 4 signed artifacts.
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate7.4
Excluded from scoring (no data or not applicable): Branch-Protection, 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
advisories0
affected_packages0
assessed_packages11
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 11 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.

77Good · 4% of overall
How it's scored
45/45Agent instructionsAGENTS.md, CLAUDE.md
0/15Machine-readable docs (llms.txt)
37.3/40Legible commit history21 of 30 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.7
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes16,543
How it's scored
18/18One-command bootstrapMakefile, docs/Makefile
22/22Automated tests
11/11Lint / format configtox.ini
11/11Static type checking.mypy.ini, frozenlist/py.typed
0/10Reproducible environment
2/10Demonstrated agent practice1 of the last 100 commits agent-authored or agent-credited
8/8Automated maintenance68 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, docs/Makefile
has_devcontainerno
has_linter_configyes
typecheck_configs.mypy.ini, frozenlist/py.typed
agent_commit_share0.01
toolchain_manifests
dependency_bot_commit_share0.68
How it's scored
27/45Type-checkable codePython with type-check config (.mypy.ini, frozenlist/py.typed)
55/55Manageable file sizes0/12 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes13,395
source_files_sampled12
oversized_source_files0

Key facts

123GitHub stars
18contributors
117commits, last 12 months
1days since last push
19releases
2bus factor
3open 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 ★ / 39 ⇿
0Stars
39Forks
18Releases

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.

0102030403922019-112023-022026-06
Major 1Minor 8Patch 6

Each point covers 7 days.

OpenSSF Scorecard 7.4 / 10
7.4aggregate

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 · 2026-08-04 18:20 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-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 59 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 6 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
10SASTSAST tool is run on all commits
10Security-Policysecurity policy file detected
6Signed-Releases4 out of the last 5 releases have a total of 4 signed artifacts.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 14

Full resolved dependency set from the GitHub dependency graph: 0 direct and 14 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIaiohttp-theme0.1.7indirect
PyPIbuildindirect
PyPIcoverage7.15.2indirect
PyPIcython3.2.9indirect
PyPIpre-commit4.6.1indirect
PyPIpytest9.1.1indirect
PyPIpytest-cov7.1.0indirect
PyPIsphinx7.4.7indirect
PyPIsphinxcontrib-spelling8.0.1indirect
PyPIsphinxcontrib-towncrierindirect
PyPItowncrier25.8.0indirect
PyPItox4.58.0indirect
PyPItwineindirect
PyPItypes-setuptools83.0.0.20260724indirect
Dependency advisories 0

This repository publishes no package the index resolves, so its own dependency graph was assessed — 11 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 v0.30.0 — full methodology · metrics wiki.

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