Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-04 20:09 UTC

pallets-eco / blinker

A fast Python in-process signal/event dispatching system.

PythonMIT★ 2,084 stars⑂ 189 forkssince Jul 2013View on GitHub ↗

pallets-eco/blinker holds a health index of 34 out of 100, placing it in the At Risk band. It scores highest on Community & Adoption (87/100) and lowest on Vitality (28/100). It was last updated 258 days ago. 2 contributors account for most of its recent work.

34
overall / 100
At Risk

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.

34
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 64 is calibrated to 73 on the published index scale (record calibration 2026-08-02).

Ownership

Pallets EcosystemOrganization
342 followers38 public repossince May 2021

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIblinker1.9.0-17634 days ago

Metrics by category

Vitality

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

28At Risk · 21% of overall
How it's scored
3.6/36Push recencylast push 258 days ago
0/36Commit cadence0/52 weeks with commits
0/18Commit volume0 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year0
human_commit_share0.84
days_since_last_push258
active_weeks_last_year0
How it's scored
27/27Ships releases10 releases published
7.2/36Release recencylatest release 634 days ago
19.8/27Release cadencea release every ~93.9 days
10/10OpenSSF Scorecard: Signed-Releases5 out of the last 5 releases have a total of 5 signed artifacts.
Inputs used
releases_count10
latest_release_tag1.9.0
releases_from_tagsno
days_since_latest_release634
mean_days_between_releases93.9

Community & Adoption

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

87Excellent · 17% of overall
How it's scored
53.8/60Stars2,084 stars
19/25Forks189 forks
8.7/15Watchers37 watchers
Inputs used
forks189
stars2,084
watchers37
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 (MIT)
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_badges0
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_services
has_pull_request_templateyes

Sustainability & Governance

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

75Good · 23% of overall
How it's scored
25.2/54Bus factor2 contributor(s) cover half of all commits
12.8/22.5Commit distributiontop contributor authored 43% of commits
13.5/13.5Contributor breadth18 contributors
10/10OpenSSF Scorecard: Contributorsproject has 43 contributing companies or organizations
Inputs used
bus_factor2
contributors_sampled18
top_contributor_share0.432
How it's scored
42/42Issue resolution100% of issues closed
20.4/30PR acceptance92/135 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
3/15OpenSSF Scorecard: Code-ReviewFound 5/23 approved changesets -- score normalized to 2
Inputs used
merged_prs92
open_issues0
closed_issues53
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio1
closed_unmerged_prs43
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. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domainverified-domain status not read for this organization
18.2/25Owner reach342 followers of pallets-eco
22/25Track record38 public repos, account ~5 yr old
Inputs used
followers342
owner_typeOrganization
is_verified
owner_loginpallets-eco
public_repos38
account_age_days1,896
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 634 days ago
20/20Version history17 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesblinker
ecosystemspypi
any_deprecatedno
min_days_since_publish634

Engineering Quality

Are baseline engineering and documentation practices in place?

84Excellent · 19% of overall
How it's scored
24/24CI workflows4 workflow(s)
24/24Tests present
16/16Linter config
9.6/9.6Pre-commit hooks
6.4/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 8 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigyes
has_linter_configyes
has_precommit_configyes

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://blinker.readthedocs.io
10/10Repository description
10/10Topics3 topics
0/10Wiki
Inputs used
topicsblinker, python, signals
has_wikino
homepagehttps://blinker.readthedocs.io
docs_sitehttps://blinker.readthedocs.io
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

51Moderate · 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
0/2.5CI-Tests0 out of 8 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1.5/7.5Code-ReviewFound 5/23 approved changesets -- score normalized to 2
2.5/2.5Contributorsproject has 43 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
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packagingno data
5/5Pinned-Dependenciesall dependencies are pinned
0/5SASTSAST tool is not run on all commits -- score normalized to 0
4.5/5Security-Policysecurity policy file detected
7.5/7.5Signed-Releases5 out of the last 5 releases have a total of 5 signed artifacts.
0/7.5Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities27 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5.1
Excluded from scoring (no data or not applicable): Packaging. 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.

58Moderate · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
26.7/40Legible commit history42 of 84 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.5
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config
11/11Static type checkingsrc/blinker/py.typed
10/10Reproducible environmentlockfile
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance12 of the last 100 commits are automated dependency updates
10/10OpenSSF Scorecard: Pinned-Dependenciesall dependencies are pinned
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configyes
typecheck_configssrc/blinker/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.12
How it's scored
27/45Type-checkable codePython with type-check config (src/blinker/py.typed)
55/55Manageable file sizes0/7 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes19,132
source_files_sampled7
oversized_source_files0

Key facts

2,084GitHub stars
18contributors
0commits, last 12 months
258days since last push
10releases
2bus 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 ★ / 189 ⇿
0Stars
189Forks
10Releases

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.

0408012016020018532013-082019-122026-04
Major 0Minor 3Patch 5

Each point covers 12 days.

OpenSSF Scorecard 5.1 / 10
5.1aggregate

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 · 2026-08-04 20:09 UTC

10Binary-Artifactsno binaries found in the repo
3Branch-Protectionbranch protection is not maximal on development and all release branches
0CI-Tests0 out of 8 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
2Code-ReviewFound 5/23 approved changesets -- score normalized to 2
10Contributorsproject has 43 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not detected
10Pinned-Dependenciesall dependencies are pinned
0SASTSAST tool is not run on all commits -- score normalized to 0
9Security-Policysecurity policy file detected
10Signed-Releases5 out of the last 5 releases have a total of 5 signed artifacts.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities27 existing vulnerabilities detected
All dependencies 0

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

RegistryPackageVersionRelation
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies to assess

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.