Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-10-19 18:09 UTC

Datahenge / cairn

CI/CD application for creating custom images with frappe-docker

PythonMIT★ 1 star⑂ 0 forkssince Jul 2026View on GitHub ↗
KindCommand-line toolLibraryhow this is determined
#deployment#deployment-automation#devops#docker-registry#erpnext#frappe#frappe-erpnext#frappe-framework

Datahenge/cairn holds a health index of 47 out of 100, placing it in the Weak band. It scores highest on Engineering Quality (84/100) and lowest on Vitality (31/100). It was last updated 19 days ago. A single contributor accounts for most of its recent work.

47
overall / 100
Weak

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.

47
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 48 is calibrated to 47 on the published index scale (record calibration 2026-08-02).

Ownership

Datahenge LLCOrganization
20 followers22 public repossince Apr 2021

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIdatahenge-cairn0.4.152,4792919 days agodeploymentdevopsdockererpnextfrappe

Metrics by category

Vitality

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

31At Risk · 21% of overall

Development activity

51Moderate
How it's scored
28.8/36Push recency — last push 19 days ago
4.2/36Commit cadence — 6/52 weeks with commits
18/18Commit volume — 183 commits in the last year
0/10OpenSSF Scorecard: Maintained — project was created within the last 90 days. Please review its contents carefully
Inputs used
commits_last_year183
human_commit_share1
days_since_last_push19
active_weeks_last_year6

Release discipline

1Critical
How it's scored
0/27Ships releases — no releases published
0/36Release recency — no releases
0/27Release cadence — no releases
0/10OpenSSF Scorecard: Signed-Releases — no data
Inputs used
releases_count0
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?

32At Risk · 17% of overall

Popularity & adoption

1Critical
How it's scored
0/60Stars — 1 stars
0/25Forks — 0 forks
0/15Watchers — 0 watchers
Inputs used
forks0
stars1
watchers0
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_badges0
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_services—
has_pull_request_templateno

Ecosystem adoption (downloads)

57Moderate
How it's scored
45.3/80Monthly downloads — 2,479 downloads/month across pypi
0/20Registry dependents — not reported by this ecosystem
Inputs used
packagesdatahenge-cairn
dependents—
ecosystemspypi
total_downloads—
monthly_downloads2,479
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?

39Weak · 23% of overall

Maintainer resilience (bus factor)

13Critical
How it's scored
9/54Bus factor — 1 contributor(s) cover half of all commits
0/22.5Commit distribution — top contributor authored 100% of commits
1.4/13.5Contributor breadth — 1 contributors
3/10OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3
Inputs used
bus_factor1
contributors_sampled1
top_contributor_share1

Issue & PR responsiveness

1Critical
How it's scored
0/42Issue resolution — no issues or no data
0/30PR acceptance — no decided pull requests or no data
0/13Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0
Inputs used
merged_prs0
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio—
closed_unmerged_prs0
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Issue resolution, PR acceptance, Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

60Moderate
How it's scored
30/30Ownership backing — organization-owned
0/20Verified domain
9.5/25Owner reach — 20 followers of Datahenge
20.9/25Track record — 22 public repos, account ~5 yr old
Inputs used
followers20
owner_typeOrganization
is_verifiedno
owner_loginDatahenge
public_repos22
account_age_days2,008

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable — 1 package(s) on pypi
35/35Publish recency — latest publish 19 days ago
20/20Version history — 29 published versions
20/20Not deprecated — active, not deprecated or yanked
Inputs used
packagesdatahenge-cairn
ecosystemspypi
any_deprecatedno
min_days_since_publish19

Engineering Quality

Are baseline engineering and documentation practices in place?

84Excellent · 19% of overall

Engineering practices

80Excellent
How it's scored
24/24CI workflows — 1 workflow(s)
24/24Tests present
16/16Linter config — pyproject.toml ([tool.ruff])
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — no data
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configno
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: CI-Tests. Remaining weights renormalized.

Documentation

90Excellent
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage site — https://datahenge.github.io/cairn/
10/10Repository description
10/10Topics — 8 topics
0/10Wiki
Inputs used
topicsdeployment, deployment-automation, devops, docker-registry, erpnext, frappe, frappe-erpnext, frappe-framework
has_wikino
homepagehttps://datahenge.github.io/cairn/
docs_sitehttps://datahenge.github.io/cairn/
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

50Moderate · 16% of overall

Security posture

37Weak
How it's scored
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
0/2.5CI-Tests — no data
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5Code-Review — Found 0/30 approved changesets -- score normalized to 0
0.8/2.5Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5Dependency-Update-Tool — no update tool detected
0/5Fuzzing — project is not fuzzed
2.5/2.5License — license file detected
0/7.5Maintained — project was created within the last 90 days. Please review its contents carefully
0/5Packaging — no data
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — no SAST tool detected
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — no data
7.5/7.5Token-Permissions — GitHub workflow tokens follow principle of least privilege
5.2/7.5Vulnerabilities — 3 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate3.7
Excluded from scoring (no data or not applicable): CI-Tests, Packaging, Signed-Releases. Remaining weights renormalized.

Dependency advisories

100Exceptional
How it's scored
35/35Direct dependencies free of known advisories — no direct dependency carries a known advisory
25/25Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
0/40No advisories left outstanding — no advisory carries a publication date
Inputs used
sourceosv
advisories0
affected_packages0
assessed_packages7
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:datahenge-cairn@0.4.15 runtime dependency closure — what installing the published package pulls in — 7 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.

70Good · 4% of overall

Agent context & guidance

73Good
How it's scored
45/45Agent instructions — AGENTS.md, CLAUDE.md
0/15Machine-readable docs (llms.txt)
27.7/40Legible commit history — 52 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url—
legible_history_share0.52
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes10,224

Verify loop (build / test / typecheck)

64Moderate
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format config — pyproject.toml ([tool.ruff])
11/11Static type checking — src/cairn/py.typed
10/10Reproducible environment — Dockerfile, lockfile
10/10Demonstrated agent practice — 50 of the last 100 commits agent-authored or agent-credited
0/8Automated maintenance — no automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfilesuv.lock
has_dockerfileyes
typed_languageno
bootstrap_files—
has_devcontainerno
has_linter_configyes
typecheck_configssrc/cairn/py.typed
agent_commit_share0.5
toolchain_manifests—
dependency_bot_commit_share0

Code legibility for models

82Excellent
How it's scored
27/45Type-checkable code — Python with type-check config (src/cairn/py.typed)
55/55Manageable file sizes — 0/71 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes41,873
source_files_sampled71
oversized_source_files0

Key facts

1GitHub stars
1contributors
183commits, last 12 months
19days since last push
0releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token

More detail

OpenSSF Scorecard 3.7 / 10
3.7aggregate

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 · 2026-10-19 18:09 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
n/aCI-Testsno pull request found
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 0/30 approved changesets -- score normalized to 0
3Contributorsproject has 1 contributing companies or organizations -- score normalized to 3
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintainedproject was created within the last 90 days. Please review its contents carefully
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTno SAST tool detected
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
7Vulnerabilities3 existing vulnerabilities detected
Direct dependencies 1
RegistryPackageVersion constraintManifest
PyPItyper>=0.12pyproject.toml
All dependencies 66

Full resolved dependency set from the GitHub dependency graph: 1 direct and 65 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPItyper0.27.1direct
PyPIannotated-doc0.0.5indirect
PyPIbabel2.18.0indirect
PyPIbackports-tarfile1.2.0indirect
PyPIbackrefs8.0indirect
PyPIbuild1.5.0indirect
PyPIcertifi2026.7.22indirect
PyPIcffi2.1.1indirect
PyPIcharset-normalizer3.4.9indirect
PyPIclick8.4.2indirect
PyPIcolorama0.4.6indirect
PyPIcoverage7.15.3indirect
PyPIcryptography50.0.0indirect
PyPIdatahenge-cairn0.4.15indirect
PyPIdocutils0.23indirect
PyPIghp-import2.1.0indirect
PyPIid1.6.1indirect
PyPIidna3.18indirect
PyPIimportlib-metadata9.0.0indirect
PyPIiniconfig2.3.0indirect
PyPIjaraco-classes3.4.0indirect
PyPIjaraco-context6.1.2indirect
PyPIjaraco-functools4.6.0indirect
PyPIjeepney0.9.0indirect
PyPIjinja23.1.6indirect
PyPIkeyring25.7.0indirect
PyPImarkdown3.10.3indirect
PyPImarkdown-it-py4.2.0indirect
PyPImarkupsafe3.0.3indirect
PyPImdurl0.1.2indirect
PyPImergedeep1.3.4indirect
PyPImkdocs1.6.1indirect
PyPImkdocs-get-deps0.2.2indirect
PyPImkdocs-material9.7.7indirect
PyPImkdocs-material-extensions1.3.1indirect
PyPImore-itertools11.1.0indirect
PyPInh30.3.6indirect
PyPIpackaging26.3indirect
PyPIpaginate0.5.7indirect
PyPIpathspec1.1.1indirect
PyPIplatformdirs4.11.0indirect
PyPIpluggy1.6.0indirect
PyPIpycparser3.0indirect
PyPIpygments2.20.0indirect
PyPIpymdown-extensions11.0.1indirect
PyPIpyproject-hooks1.2.0indirect
PyPIpytest9.1.1indirect
PyPIpytest-cov7.1.0indirect
PyPIpython-dateutil2.9.0.post0indirect
PyPIpywin32-ctypes0.2.3indirect
PyPIpyyaml6.0.3indirect
PyPIpyyaml-env-tag1.1indirect
PyPIreadme-renderer45.0indirect
PyPIrequests2.34.2indirect
PyPIrequests-toolbelt1.0.0indirect
PyPIrfc39862.0.0indirect
PyPIrich15.0.0indirect
PyPIruff0.16.1indirect
PyPIsecretstorage3.5.0indirect
PyPIshellingham1.5.4indirect
PyPIsix1.17.0indirect
PyPItomli2.4.1indirect
PyPItwine7.0.0indirect
PyPIurllib32.7.0indirect
PyPIwatchdog6.0.0indirect
PyPIzipp4.1.0indirect
Dependency advisories 0

Installing pypi:datahenge-cairn@0.4.15 pulls in 7 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

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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 v0.34.0 — full methodology · metrics wiki.

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