Öffentliches RegisterMittel
Software-GesundheitsberichtSchema 0.26.0 · Metriken 1.13.0 · 2026-07-22 00:46 UTC
jazzband / django-model-utils
Django model mixins and utilities.
jazzband/django-model-utils erreicht einen Gesundheitsindex von 69 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Engineering Quality (96/100) ab, am schwächsten bei Security (21/100). Zuletzt vor 8 Tagen aktualisiert. 4 Mitwirkende tragen den Großteil der jüngsten Arbeit.
69
gesamt / 100Software-Gesundheitsindex
Metriken werden auf einer Skala von 1–100 in gewichtete Kategorien gruppiert. Der Gesamtwert beginnt als ihr Mittel; sobald öffentliche Evidenz die Richtlinie für Hochrisikojurisdiktionen auslöst, wird die Bewertung angepasst und erhält die Obergrenze 49 (Gefährdet). AI Readiness liegt außerhalb.
69
Exzellent85-100Vorbildlich; erfüllt im Wesentlichen alle geprüften Kriterien
Gut70-84Gesund; geringfügige Lücken
Mittel50-69Akzeptabel mit deutlichen Lücken; Überprüfung empfohlen
Gefährdet30-49Erhebliche Schwächen; eine Übernahme erfordert Vorsicht
Kritisch1-29Schwerwiegende Probleme (aufgegeben, nur ein Maintainer, keine Hygiene)
Bewertungsprofil
Jede Achse ist eine Kategorie. Die Form zählt mehr als der Durchschnitt — ein gesundes Projekt füllt die gesamte Fläche, während ein Profil aus Spitzen und Kratern bedeutet, dass Stärke in einer Dimension Risiken in einer anderen verdeckt.
Eigentümerschaft
JazzbandOrganisation
2.270 Follower76 öffentliche Reposseit Okt. 2015
Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.
Paket-Ökosysteme
| Registry | Paket | Version | Downloads / Monat | Versionen | Zuletzt veröffentlicht |
|---|---|---|---|---|---|
| PyPI | django-model-utils | 5.0.0 | - | 43 | vor 685 Tagen |
Metriken nach Kategorie
Vitalität
Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?
49
Entwicklungsaktivität
47Gefährdet
Wie die Bewertung erfolgt
| 28.8/36 | Push-Aktualität — letzter Push vor 8 Tagen |
| 4.2/36 | Commit-Rhythmus — 6/52 Wochen mit Commits |
| 9.4/18 | Commit-Volumen — 10 Commits im letzten Jahr |
| 0/10 | OpenSSF Scorecard: Maintained — keine Daten |
Verwendete Eingangsdaten
| commits_last_year | 10 |
| human_commit_share | 0,96 |
| days_since_last_push | 8 |
| active_weeks_last_year | 6 |
Release-Disziplin
52Mittel
Wie die Bewertung erfolgt
| 27/27 | Liefert Releases aus — 11 Releases veröffentlicht |
| 7.2/36 | Release-Aktualität — letztes Release vor 685 Tagen |
| 12.6/27 | Release-Rhythmus — ein Release etwa alle 192,1 Tage |
| 0/10 | OpenSSF Scorecard: Signed-Releases — keine Daten |
Verwendete Eingangsdaten
| releases_count | 11 |
| latest_release_tag | 5.0.0 |
| releases_from_tags | nein |
| days_since_latest_release | 685 |
| mean_days_between_releases | 192,1 |
Community & Verbreitung
Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?
93
Popularität & Verbreitung
86Exzellent
Wie die Bewertung erfolgt
| 55.8/60 | Stars — 2.761 Stars |
| 21.4/25 | Forks — 370 Forks |
| 9/15 | Watcher — 43 Watcher |
Verwendete Eingangsdaten
| forks | 370 |
| stars | 2.761 |
| watchers | 43 |
| growth_state | organic |
| growth_factor_pct | 100 |
Community-Gesundheit
100Exzellent
Wie die Bewertung erfolgt
| 22.5/22.5 | README |
| 22.5/22.5 | Lizenz — anerkannte Lizenz (BSD-3-Clause) |
| 18/18 | CONTRIBUTING-Leitfaden |
| 13.5/13.5 | Verhaltenskodex |
| 7.2/7.2 | Issue-Vorlage |
| 6.3/6.3 | PR-Vorlage |
Verwendete Eingangsdaten
| has_readme | ja |
| has_license | ja |
| has_contributing | ja |
| has_issue_template | ja |
| has_code_of_conduct | ja |
| has_pull_request_template | ja |
Nachhaltigkeit & Governance
Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?
78
Wie die Bewertung erfolgt
| 43.2/54 | Bus-Faktor — 4 Beitragende decken die Hälfte aller Commits ab |
| 16.2/22.5 | Commit-Verteilung — wichtigste beitragende Person verfasste 28 % der Commits |
| 13.5/13.5 | Breite der Beitragenden — 99 Beitragende |
| 0/10 | OpenSSF Scorecard: Contributors — keine Daten |
Verwendete Eingangsdaten
| bus_factor | 4 |
| contributors_sampled | 99 |
| top_contributor_share | 0,28 |
Wie die Bewertung erfolgt
| 30.3/46.8 | Issue-Lösungsquote — 65 % der Issues geschlossen |
| 29.8/38.3 | PR-Annahme — 268/344 entschiedene PRs gemergt |
| 0/15 | OpenSSF Scorecard: Code-Review — keine Daten |
Verwendete Eingangsdaten
| merged_prs | 268 |
| open_issues | 105 |
| closed_issues | 194 |
| issue_closed_ratio | 0,649 |
| closed_unmerged_prs | 76 |
Wie die Bewertung erfolgt
| 30/30 | Organisatorische Trägerschaft — im Besitz einer Organisation |
| 0/20 | Verifizierte Domain |
| 24.1/25 | Reichweite des Inhabers — 2.270 Follower von jazzband |
| 25/25 | Kontohistorie — 76 öffentliche Repos, Kontoalter ca. 10 Jahre |
Verwendete Eingangsdaten
| followers | 2.270 |
| owner_type | Organization |
| is_verified | — |
| owner_login | jazzband |
| public_repos | 76 |
| account_age_days | 3.933 |
Paketpflege
79Gut
Wie die Bewertung erfolgt
| 25/25 | Veröffentlicht & auflösbar — 1 Paket(e) auf pypi |
| 14/35 | Veröffentlichungsaktualität — letzte Veröffentlichung vor 685 Tagen |
| 20/20 | Versionshistorie — 43 veröffentlichte Versionen |
| 20/20 | Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen |
Verwendete Eingangsdaten
| packages | django-model-utils |
| ecosystems | pypi |
| any_deprecated | nein |
| min_days_since_publish | 685 |
Engineering-Qualität
Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?
96
Engineering-Praktiken
100Exzellent
Wie die Bewertung erfolgt
| 24/24 | CI-Workflows — 3 Workflow(s) |
| 24/24 | Tests vorhanden |
| 16/16 | Linter-Konfiguration — tox.ini |
| 9.6/9.6 | Pre-Commit-Hooks |
| 6.4/6.4 | .editorconfig |
| 0/20 | OpenSSF Scorecard: CI-Tests — keine Daten |
Verwendete Eingangsdaten
| has_ci | ja |
| has_tests | ja |
| has_editorconfig | ja |
| has_linter_config | ja |
| has_precommit_config | ja |
Dokumentation
90Exzellent
Wie die Bewertung erfolgt
| 30/30 | README |
| 25/25 | Dokumentationsverzeichnis |
| 15/15 | Dokumentations-/Homepage-Site — https://django-model-utils.readthedocs.io |
| 10/10 | Repository-Beschreibung |
| 0/10 | Topics |
| 10/10 | Wiki |
Verwendete Eingangsdaten
| topics | — |
| has_wiki | ja |
| homepage | https://django-model-utils.readthedocs.io |
| has_readme | ja |
| has_docs_dir | ja |
| has_description | ja |
Sicherheit
Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?
21
Sicherheitslage
1Kritisch
Wie die Bewertung erfolgt
| 0/30 | Sicherheitsrichtlinie (SECURITY.md) |
| 0/25 | Dependabot-Konfiguration |
| 0/25 | Lockfiles für Abhängigkeiten — veröffentlichte Bibliothek — Lockfiles sind Sache der Anwendung, hier nicht erwartet |
| 0/20 | CodeQL-Workflow |
Verwendete Eingangsdaten
| source | file_signals |
| lockfiles | — |
| manifests | requirements-mypy.txt, requirements-test.txt, requirements.txt, setup.cfg, setup.py |
| has_codeql_workflow | nein |
| has_security_policy | nein |
| has_dependabot_config | nein |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lockfiles für Abhängigkeiten. Die verbleibenden Gewichte wurden renormalisiert.
Abhängigkeits-Advisories
100Exzellent
Wie die Bewertung erfolgt
| 35/35 | Direkte Abhängigkeiten ohne bekannte Advisories — keine direkte Abhängigkeit trägt ein bekanntes Advisory |
| 25/25 | Indirekte Abhängigkeiten ohne bekannte Advisories — keine indirekte Abhängigkeit trägt ein bekanntes Advisory |
| 0/40 | Keine offenen Advisories — kein Advisory trägt ein Veröffentlichungsdatum |
Verwendete Eingangsdaten
| source | osv |
| advisories | 0 |
| affected_packages | 0 |
| assessed_packages | 3 |
| unassessed_packages | 0 |
| affected_by_severity | none |
| direct_affected_packages | 0 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Keine offenen Advisories. Die verbleibenden Gewichte wurden renormalisiert. Abgeglichen wurde die Laufzeit-Abhängigkeitshülle von pypi:django-model-utils@5.0.0 — das, was die Installation des veröffentlichten Pakets nach sich zieht — mit 3 Paketen. Erreichbarkeit wird nicht analysiert.
AI Readiness
Wie gut ist das Repository dafür ausgestattet, mit KI-Coding-Agenten entwickelt und gepflegt zu werden? Ein unabhängiges, experimentelles Badge — Gewicht 0,0, es wird eigenständig ausgewiesen und verändert den Gesamt-Gesundheitswert nicht.
63
AI-Agentenkontext & Leitlinien
29Kritisch
Wie die Bewertung erfolgt
| 0/45 | Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln |
| 0/15 | Maschinenlesbare Doku (llms.txt) |
| 29.4/40 | Lesbare Commit-Historie — 53 von 96 menschlichen Commits benennen ihre Absicht (strukturierter Betreff oder erläuternder Text) |
Verwendete Eingangsdaten
| has_llms_txt | nein |
| legible_history_share | 0,552 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Wie die Bewertung erfolgt
| 18/18 | Bootstrap mit einem Befehl — Makefile, docs/Makefile |
| 22/22 | Automatisierte Tests |
| 11/11 | Lint-/Format-Konfiguration — tox.ini |
| 11/11 | Statische Typprüfung — model_utils/py.typed, mypy.ini |
| 10/10 | Reproduzierbare Umgebung — Dockerfile |
| 2/10 | Belegte Agentenpraxis — 1 der letzten 100 Commits von Agenten verfasst oder ihnen zugeschrieben |
| 0/8 | Automatisierte Wartung — keine automatisierten Abhängigkeits-Updates beobachtet |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — keine Daten |
Verwendete Eingangsdaten
| has_nix | nein |
| has_tests | ja |
| lockfiles | — |
| has_dockerfile | ja |
| typed_language | nein |
| bootstrap_files | Makefile, docs/Makefile |
| has_devcontainer | nein |
| has_linter_config | ja |
| typecheck_configs | model_utils/py.typed, mypy.ini |
| agent_commit_share | 0,01 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
Wie die Bewertung erfolgt
| 27/45 | Typprüfbarer Code — Python mit Typprüfungs-Konfiguration (model_utils/py.typed, mypy.ini) |
| 55/55 | Handhabbare Dateigrößen — 0/36 Quelldateien über 60 KB |
Verwendete Eingangsdaten
| primary_language | Python |
| largest_source_bytes | 38.202 |
| source_files_sampled | 36 |
| oversized_source_files | 0 |
Eckdaten
2.761GitHub-Sterne
99Mitwirkende
10Commits, letzte 12 Monate
8Tage seit letztem Push
11Releases
4Bus-Faktor
105offene Issues
PyPIPaket-Ökosysteme
Warnungen zur Datenerhebung
- OpenSSF Scorecard timed out after 240s; skipping Scorecard checks
Weitere Details
Stern- und Fork-Verlauf 2.761 ★ / 370 ⇿
2.761Sterne
370Forks
11Releases
Wann jeder Stern und Fork hinzugefügt wurde, von GitHub erfasst und nach Tagen gruppiert. Das kumulierte Wachstum steht direkt über den täglichen Zugängen, aus denen es besteht, sodass beide gegeneinander lesbar sind: stetiger organischer Zuwachs sieht ganz anders aus als ein abrupter, kurzlebiger Ausschlag. Wo dieser Unterschied messbar ist, wird er als Wachstumsauthentizität ausgewiesen.
Es wird nur die jüngste Historie angezeigt — dieses Repository überschreitet das Erfassungsfenster, sodass die früheste Historie nicht erfasst wird.
Major 2Minor 4Patch 4
Jeder Punkt umfasst 15 Tage.
Alle Abhängigkeiten 12
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 0 direkte und 12 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
| Registry | Paket | Version | Beziehung |
|---|---|---|---|
| PyPI | django | — | indirekt |
| PyPI | django-stubs | 5.1.3 | indirekt |
| PyPI | mypy | — | indirekt |
| PyPI | psycopg | — | indirekt |
| PyPI | psycopg2-binary | — | indirekt |
| PyPI | pytest | — | indirekt |
| PyPI | pytest-cov | 4.1.0 | indirekt |
| PyPI | pytest-django | — | indirekt |
| PyPI | sphinx | — | indirekt |
| PyPI | time-machine | — | indirekt |
| PyPI | tox | — | indirekt |
| PyPI | twine | — | indirekt |
Abhängigkeits-Advisories 0
Die Installation von pypi:django-model-utils@5.0.0 zieht 3 Pakete nach sich, direkt und transitiv: 0 tragen bekannte Advisories, davon 0 direkte Abhängigkeiten.
Keine bekannten Advisories betreffen die bewerteten Abhängigkeiten.
Ein Advisory bedeutet, dass die im Abhängigkeitsgraphen erfasste Version in den betroffenen Bereich eines Advisories fällt. Erreichbarkeit wird nicht analysiert, und der Graph enthält Entwicklungs- und Test-Pins — ein Fund kann das Werkzeug betreffen und nicht die ausgelieferte Software.
JSON-Rohbericht maschinenlesbar
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"body": "…class\n\nThe `soft` argument was made keyword-only, to avoid conflicts with new\npositional arguments that might be added to Django. It was already\nconflicting with the `keep_parents` argument.\n\nThe `using` argument is now passed to the superclass positionally,\nas otherwise it can overlap with `*args`, resulting in a `TypeError`\non calls where `keep_parents` is passed positionally.",
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"status": "met",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"sampled": 36,
"oversized": 0
}
}
],
"max_points": 55
}
]
}
],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
}
],
"metrics_version": "1.13.0"
},
"warnings": [
"OpenSSF Scorecard timed out after 240s; skipping Scorecard checks"
],
"report_type": "repository",
"generated_at": "2026-07-22T00:46:16.636197Z",
"schema_version": "0.26.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/j/jazzband/django-model-utils.svg",
"full_name": "jazzband/django-model-utils",
"license_state": "standard",
"license_spdx": "BSD-3-Clause"
}Bewertungen sind Signale, keine Garantien. Sie spiegeln öffentlich sichtbare Praxis auf GitHub wider — kein Code-Audit und keine Sicherheitsgarantie.
Fehlende Daten werden ausgeschlossen und die Gewichte neu normiert, nie als null bewertet. Die Methodik ist versioniert und offen: Metriken v1.13.0, Schema v0.26.0 — vollständige Methodik · Metriken-Wiki.
Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken — PyPI.