Public record
Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-08-28 09:53 UTC

DLRSP / django-model-mixin

Django application provide simple model's mixins to add common reusable attributes.

PythonMIT★ 0 stars⑂ 0 forkssince Oct 2023View on GitHub ↗
KindLibraryNetwork servicehow this is determined

DLRSP/django-model-mixin holds a health index of 69 out of 100, placing it in the Good band. It scores highest on Engineering Quality (86/100) and lowest on AI Readiness (34/100). It was last updated today. A single contributor accounts for most of its recent work.

69
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.

69
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 62 is calibrated to 69 on the published index scale (record calibration 2026-08-02).

Ownership

DLRSPOrganization
1 follower20 public repossince Jun 2015

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publishTags
PyPIdjango-model-mixin0.3.10-110 days agodjangomixinsmodelsreusable

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 0 days ago
5.5/36Commit cadence8/52 weeks with commits
14.2/18Commit volume37 commits in the last year
10/10OpenSSF Scorecard: Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Inputs used
commits_last_year37
human_commit_share0.78
days_since_last_push0
active_weeks_last_year8
How it's scored
27/27Ships releases10 releases published
36/36Release recencylatest release 0 days ago
19.8/27Release cadencea release every ~117.1 days
0/10OpenSSF Scorecard: Signed-ReleasesProject has not signed or included provenance with any releases.
Inputs used
releases_count10
latest_release_tagv0.3.10
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases117.1

Community & Adoption

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

40Weak · 17% of overall
How it's scored
0/60Stars0 stars
0/25Forks0 forks
0/15Watchers0 watchers
Inputs used
forks0
stars0
watchers0
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history

Community health

85Excellent
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
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges11
has_contributingyes
has_issue_templateno
has_code_of_conductyes
readme_badge_servicescodecov.io, github.com, shields.io
has_pull_request_templateno

Sustainability & Governance

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

54Moderate · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
0.5/22.5Commit distributiontop contributor authored 98% of commits
2.7/13.5Contributor breadth2 contributors
6/10OpenSSF Scorecard: Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
Inputs used
bus_factor1
contributors_sampled2
top_contributor_share0.976
How it's scored
0/42Issue resolutionno issues or no data
27.1/30PR acceptance167/185 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
0/15OpenSSF Scorecard: Code-ReviewFound 1/28 approved changesets -- score normalized to 0
Inputs used
merged_prs167
open_issues0
closed_issues0
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio
closed_unmerged_prs18
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Issue resolution, Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
30/30Ownership backingorganization-owned
0/20Verified domain
2.2/25Owner reach1 followers of DLRSP
21.6/25Track record20 public repos, account ~11 yr old
Inputs used
followers1
owner_typeOrganization
is_verifiedno
owner_loginDLRSP
public_repos20
account_age_days4,076

Package maintenance

100Exceptional
How it's scored
25/25Published & resolvable1 package(s) on pypi
35/35Publish recencylatest publish 0 days ago
20/20Version history11 published versions
20/20Not deprecatedactive, not deprecated or yanked
Inputs used
packagesdjango-model-mixin
ecosystemspypi
any_deprecatedno
min_days_since_publish0

Engineering Quality

Are baseline engineering and documentation practices in place?

86Excellent · 19% of overall
How it's scored
24/24CI workflows6 workflow(s)
24/24Tests present
16/16Linter configpyproject.toml ([tool.flake8], [tool.black], [tool.isort]), tox.ini
9.6/9.6Pre-commit hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests19 out of 19 merged PRs checked by a CI test -- score normalized to 10
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configyes
has_precommit_configyes
How it's scored
30/30README
0/25Documentation directory
15/15Documentation / homepage sitehttps://dlrsp.github.io/django-model-mixin/
10/10Repository description
10/10Topics4 topics
10/10Wiki
Inputs used
topicsdjango, mixins, models, reusable
has_wikiyes
homepagehttps://dlrsp.github.io/django-model-mixin/
docs_sitehttps://dlrsp.github.io/django-model-mixin/
has_readmeyes
has_docs_dirno
has_descriptionyes

Security

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

64Moderate · 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-Tests19 out of 19 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-ReviewFound 1/28 approved changesets -- score normalized to 0
1.5/2.5Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
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 0 issue activity found in the last 90 days -- score normalized to 10
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
5/5SASTSAST tool is run on all commits
4.5/5Security-Policysecurity policy file detected
0/7.5Signed-ReleasesProject has not signed or included provenance with any releases.
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_aggregate6.1
Excluded from scoring (no data or not applicable): Branch-Protection, Packaging. Remaining weights renormalized.
How it's scored
16.8/35Direct dependencies free of known advisories1 affected: django 4.2.30 (moderate 6.5)
0/25Indirect dependencies free of known advisoriestransitive set not separable from development and test dependencies in this scope
40/40No advisories left outstandingno advisory has been public longer than 90 days
Inputs used
sourceosv
advisories7
affected_packages1
assessed_packages5
unassessed_packages2
affected_by_severitymoderate 1
direct_affected_packages1
Excluded from scoring (no data or not applicable): Indirect dependencies free of known advisories. Remaining weights renormalized. Matched 5 resolved dependencies against OSV. 2 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.

34At Risk · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
13.7/40Legible commit history20 of 78 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.256
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
11/11Lint / format configpyproject.toml ([tool.flake8], [tool.black], [tool.isort]), tox.ini
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
8/8Automated maintenance7 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_files
has_devcontainerno
has_linter_configyes
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0.07
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/8 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes3,228
source_files_sampled8
oversized_source_files0

Key facts

0GitHub stars
2contributors
37commits, last 12 months
0days since last push
10releases
1bus factor
0open issues
PyPIpackage ecosystems

Data collection warnings

  • pypi download statistics for 'django-model-mixin' unavailable this scan (stats endpoint failed after retries); adoption may be under-evidenced
  • deps.dev does not index pypi:django-model-mixin@0.3.10; advisories assessed against the repository dependency graph instead

More detail

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 · 2026-08-28 09:53 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-Tests19 out of 19 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
0Code-ReviewFound 1/28 approved changesets -- score normalized to 0
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
10SASTSAST tool is run on all commits
9Security-Policysecurity policy file detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 1
RegistryPackageVersion constraintManifest
PyPIDjango>=3.2pyproject.toml
All dependencies 7

Full resolved dependency set from the GitHub dependency graph: 3 direct and 4 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

RegistryPackageVersionRelation
PyPIdjangodirect
PyPIdjango4.2.30direct
PyPIdjango5.2.17direct
PyPIasgiref3.12.1indirect
PyPIsetuptoolsindirect
PyPIsqlparse0.6.0indirect
PyPItyping-extensions4.16.0indirect
Dependency advisories 1

This repository publishes no package the index resolves, so its own dependency graph was assessed — 5 packages, which also include development and test pins that never ship: 1 carry known advisories, of which 1 are direct. 2 could not be assessed — no resolved version, an unsupported ecosystem, or beyond the reported package list.

PackageVersionRelationSeverityAdvisoriesFixed in
django4.2.30directmoderate76.0.8

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 v0.34.0 — full methodology · metrics wiki.

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