Public record
Software health reportschema 0.16.0 · metrics 2.10.0 · 2026-07-21 02:45 UTC

domdfcoding / apeye-core

Core (offline) functionality for the apeye library.

PythonBSD-3-Clause★ 0 stars⑂ 2 forkssince Jun 2022View on GitHub ↗

domdfcoding/apeye-core holds a health index of 56 out of 100, placing it in the Moderate band. It scores highest on Engineering Quality (71/100) and lowest on Sustainability & Governance (44/100). It was last updated 14 days ago. A single contributor accounts for most of its recent work.

56
overall / 100
Moderate

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.

56
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 54 is calibrated to 56 on the published index scale (record calibration 2026-08-02).

Ownership

Dominic Davis-FosterPersonal account
50 followers222 public repossince Jul 2014

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIapeye-core1.1.51,555,84610902 days agourl

Metrics by category

Vitality

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

48Weak · 21% of overall
How it's scored
28.8/36Push recencylast push 14 days ago
4.8/36Commit cadence7/52 weeks with commits
9.7/18Commit volume11 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_year11
human_commit_share
days_since_last_push14
active_weeks_last_year7
How it's scored
27/27Ships releases10 releases published
16.2/36Release recencylatest release 222 days ago
12.6/27Release cadencea release every ~143 days
0/10OpenSSF Scorecard: Signed-ReleasesProject has not signed or included provenance with any releases.
Inputs used
releases_count10
latest_release_tagv1.1.5
releases_from_tagsno
days_since_latest_release222
mean_days_between_releases143

Community & Adoption

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

50Moderate · 17% of overall
How it's scored
0/60Stars0 stars
0/25Forks2 forks
0/15Watchers1 watchers
Inputs used
forks2
stars0
watchers1
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (BSD-3-Clause)
18/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges
has_contributingyes
has_issue_templateno
has_code_of_conductno
readme_badge_services
has_pull_request_templateno
How it's scored
80/80Monthly downloads1,555,846 downloads/month across pypi
0/20Registry dependentsnot reported by this ecosystem
Inputs used
packagesapeye-core
dependents
ecosystemspypi
total_downloads
monthly_downloads1,555,846
unverified_packages_excluded
Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

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

44Weak · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
10.1/22.5Commit distributiontop contributor authored 55% of commits
2.7/13.5Contributor breadth2 contributors
10/10OpenSSF Scorecard: Contributorsproject has 8 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.553
How it's scored
0/42Issue resolution0% of issues closed
20.8/30PR acceptance34/49 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 0/7 approved changesets -- score normalized to 0
Inputs used
merged_prs34
open_issues3
closed_issues0
prs_merged_7d
prs_decided_7d
prs_merged_30d
prs_decided_30d
issue_closed_ratio0
closed_unmerged_prs15
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.
How it's scored
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
12.3/25Owner reach50 followers of domdfcoding
25/25Track record222 public repos, account ~12 yr old
Inputs used
followers50
owner_typeUser
is_verified
owner_logindomdfcoding
public_repos222
account_age_days4,401
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.
How it's scored
25/25Published & resolvable1 package(s) on pypi
4/35Publish recencylatest publish 902 days ago
20/20Version history10 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesapeye-core
ecosystemspypi
any_deprecatedno
min_days_since_publish902

Engineering Quality

Are baseline engineering and documentation practices in place?

71Good · 19% of overall
How it's scored
24/24CI workflows6 workflow(s)
24/24Tests present
16/16Linter config.pylintrc, tox.ini
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
4/20OpenSSF Scorecard: CI-Tests6 out of 23 merged PRs checked by a CI test -- score normalized to 2
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes

Documentation

60Moderate
How it's scored
30/30README
0/25Documentation directory
0/15Documentation / homepage site
10/10Repository description
10/10Topics2 topics
10/10Wiki
Inputs used
topicspython, url
has_wikiyes
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?

59Moderate · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionno data
0.5/2.5CI-Tests6 out of 23 merged PRs checked by a CI test -- score normalized to 2
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0/7.5Code-ReviewFound 0/7 approved changesets -- score normalized to 0
2.5/2.5Contributorsproject has 8 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
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
0/5Security-Policysecurity policy file not detected
0/7.5Signed-ReleasesProject has not signed or included provenance with any releases.
5.2/7.5Token-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_aggregate4.9
Excluded from scoring (no data or not applicable): Branch-Protection. 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:apeye-core@1.1.5 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.

50Moderate · 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 bootstrapjustfile
22/22Automated tests
11/11Lint / format config.pylintrc, tox.ini
11/11Static type checkingapeye_core/py.typed
0/10Reproducible environment
0/10Demonstrated agent practiceno data
5/8Automated maintenancedependency automation configured, none observed in the sampled commits
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_filesjustfile
has_devcontainerno
has_linter_configyes
typecheck_configsapeye_core/py.typed
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.
How it's scored
27/45Type-checkable codePython with type-check config (apeye_core/py.typed)
55/55Manageable file sizes0/8 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes32,415
source_files_sampled8
oversized_source_files0

Key facts

0GitHub stars
2contributors
11commits, last 12 months
14days since last push
10releases
1bus factor
3open issues
PyPIpackage ecosystems

More detail

OpenSSF Scorecard 4.9 / 10
4.9aggregate

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 · 2026-07-21 02:45 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
2CI-Tests6 out of 23 merged PRs checked by a CI test -- score normalized to 2
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/7 approved changesets -- score normalized to 0
10Contributorsproject has 8 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
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
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
7Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
All dependencies 13

Full resolved dependency set from the GitHub dependency graph: 0 direct and 13 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIbackports-datetime-fromisoformatindirect
PyPIbackports-datetime-fromisoformat1.0.0indirect
PyPIcoincidenceindirect
PyPIcoverageindirect
PyPIcoverage-pyver-pragmaindirect
PyPIdomdf-python-toolsindirect
PyPIidnaindirect
PyPIimportlib-metadataindirect
PyPIpytestindirect
PyPIpytest-covindirect
PyPIpytest-httpserverindirect
PyPIpytest-randomlyindirect
PyPIpytest-timeoutindirect
Dependency advisories 0

Installing pypi:apeye-core@1.1.5 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 v0.16.0 — full methodology · metrics wiki.

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