Registro público
Informe de salud del softwareesquema 0.26.0 · métricas 1.13.0 · 2026-07-22 00:46 UTC

jazzband / django-model-utils

Django model mixins and utilities.

PythonBSD-3-Clause★ 2761 estrellas⑂ 370 forksdesde nov 2009Ver en GitHub ↗

jazzband/django-model-utils tiene un índice de salud de 69 sobre 100, lo que lo sitúa en la banda Moderado. Su puntuación más alta es Engineering Quality (96/100) y la más baja, Security (21/100). Se actualizó por última vez hace 8 días. 4 personas concentran la mayor parte del trabajo reciente.

69
global / 100
Moderado

Índice de salud del software

Las métricas se agrupan en categorías ponderadas sobre una escala de 1 a 100. El resultado global parte de su media; cuando la evidencia pública activa la Política de Jurisdicciones de Alto Riesgo, la calificación se ajusta y recibe el límite 49 (En riesgo). Preparación para IA queda fuera.

69
Excelente85-100Ejemplar; cumple prácticamente todos los criterios evaluados
Bueno70-84Saludable; carencias menores
Moderado50-69Aceptable con carencias notables; se recomienda revisión
En riesgo30-49Debilidades significativas; su adopción exige cautela
Crítico1-29Problemas graves (proyecto abandonado, un solo mantenedor, sin higiene)
VitalidadComunidad yAdopciónSostenibilidady GobernanzaCalidad deIngenieríaSeguridadPreparaciónpara IA

Perfil de puntuación

Cada eje es una categoría. La forma importa más que la media: un proyecto sano llena toda la figura, mientras que un perfil de picos y cráteres indica que la fortaleza en una dimensión enmascara el riesgo en otra.

Titularidad

JazzbandOrganización
2270 seguidores76 repositorios públicosdesde oct 2015

Este repositorio está respaldado por una organización: una custodia compartida y responsable que puede sobrevivir a cualquier mantenedor individual.

Ecosistemas de paquetes

RegistroPaqueteVersiónDescargas / mesVersionesÚltima publicación
PyPIdjango-model-utils5.0.0-43hace 685 días

Métricas por categoría

Vitalidad

¿Está vivo el proyecto: se escribe código y se publican versiones?

49En riesgo · 22% del índice global
Cómo se puntúa
28.8/36Recencia de push — último push hace 8 días
4.2/36Cadencia de commits — 6/52 semanas con commits
9.4/18Volumen de commits — 10 commits en el último año
0/10OpenSSF Scorecard: Maintained — sin datos
Datos de entrada utilizados
commits_last_year10
human_commit_share0,96
days_since_last_push8
active_weeks_last_year6
Cómo se puntúa
27/27Publica versiones — 11 versiones publicadas
7.2/36Recencia de las versiones — última versión hace 685 días
12.6/27Cadencia de publicación — una versión cada ~192,1 días
0/10OpenSSF Scorecard: Signed-Releases — sin datos
Datos de entrada utilizados
releases_count11
latest_release_tag5.0.0
releases_from_tagsno
days_since_latest_release685
mean_days_between_releases192,1

Comunidad y Adopción

¿Tiene el proyecto usuarios, descargas, atención y unas condiciones acogedoras para quienes contribuyen?

93Excelente · 18% del índice global
Cómo se puntúa
55.8/60Estrellas — 2761 estrellas
21.4/25Forks — 370 forks
9/15Observadores — 43 observadores
Datos de entrada utilizados
forks370
stars2761
watchers43
growth_stateorganic
growth_factor_pct100
Cómo se puntúa
22.5/22.5README
22.5/22.5Licencia — licencia reconocida (BSD-3-Clause)
18/18Guía CONTRIBUTING
13.5/13.5Código de conducta
7.2/7.2Plantilla de issues
6.3/6.3Plantilla de PR
Datos de entrada utilizados
has_readme
has_license
has_contributing
has_issue_template
has_code_of_conduct
has_pull_request_template

Sostenibilidad y Gobernanza

¿Sobrevivirá el proyecto a sus personas: factor bus, capacidad de respuesta, quién lo respalda y mantenimiento del paquete?

78Bueno · 24% del índice global
Cómo se puntúa
43.2/54Factor bus — la mitad de los commits recae en 4 contribuyente(s)
16.2/22.5Distribución de commits — el principal contribuyente firma el 28% de los commits
13.5/13.5Amplitud de contribuyentes — 99 contribuyentes
0/10OpenSSF Scorecard: Contributors — sin datos
Datos de entrada utilizados
bus_factor4
contributors_sampled99
top_contributor_share0,28
Cómo se puntúa
30.3/46.8Resolución de issues — 65% de issues cerradas
29.8/38.3Aceptación de PR — 268/344 PR decididos fusionados
0/15OpenSSF Scorecard: Code-Review — sin datos
Datos de entrada utilizados
merged_prs268
open_issues105
closed_issues194
issue_closed_ratio0,649
closed_unmerged_prs76
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
24.1/25Alcance del propietario — 2270 seguidores de jazzband
25/25Trayectoria — 76 repos públicos, cuenta de ~10 años
Datos de entrada utilizados
followers2270
owner_typeOrganization
is_verified
owner_loginjazzband
public_repos76
account_age_days3933
Cómo se puntúa
25/25Publicado y resoluble — 1 paquete(s) en pypi
14/35Recencia de publicación — última publicación hace 685 días
20/20Historial de versiones — 43 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packagesdjango-model-utils
ecosystemspypi
any_deprecatedno
min_days_since_publish685

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

96Excelente · 20% del índice global
Cómo se puntúa
24/24Flujos de trabajo de CI — 3 flujo(s) de trabajo
24/24Pruebas presentes
16/16Configuración de linter — tox.ini
9.6/9.6Hooks de pre-commit
6.4/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — sin datos
Datos de entrada utilizados
has_ci
has_tests
has_editorconfig
has_linter_config
has_precommit_config

Documentación

90Excelente
Cómo se puntúa
30/30README
25/25Directorio de documentación
15/15Sitio de documentación / página del proyecto — https://django-model-utils.readthedocs.io
10/10Descripción del repositorio
0/10Topics
10/10Wiki
Datos de entrada utilizados
topics
has_wiki
homepagehttps://django-model-utils.readthedocs.io
has_readme
has_docs_dir
has_description

Seguridad

¿Son sólidas las prácticas visibles de seguridad y de cadena de suministro, sin exposición jurisdiccional de alto riesgo sin resolver?

21Crítico · 16% del índice global
Cómo se puntúa
0/30Política de seguridad (SECURITY.md)
0/25Configuración de Dependabot
0/25Lockfiles de dependencias — biblioteca publicada — los lockfiles son cosa de las aplicaciones, no se esperan aquí
0/20Flujo de trabajo de CodeQL
Datos de entrada utilizados
sourcefile_signals
lockfiles
manifestsrequirements-mypy.txt, requirements-test.txt, requirements.txt, setup.cfg, setup.py
has_codeql_workflowno
has_security_policyno
has_dependabot_configno
Excluidos de la puntuación (sin datos o no aplicable): Lockfiles de dependencias. Los pesos restantes se han renormalizado.
Cómo se puntúa
35/35Dependencias directas libres de avisos conocidos — ninguna dependencia directa tiene un aviso conocido
25/25Dependencias indirectas libres de avisos conocidos — ninguna dependencia indirecta tiene un aviso conocido
0/40Sin avisos pendientes — ningún aviso tiene fecha de publicación
Datos de entrada utilizados
sourceosv
advisories0
affected_packages0
assessed_packages3
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Excluidos de la puntuación (sin datos o no aplicable): Sin avisos pendientes. Los pesos restantes se han renormalizado. Se cotejó el cierre de dependencias en tiempo de ejecución de pypi:django-model-utils@5.0.0 —lo que arrastra la instalación del paquete publicado—: 3 paquetes. No se analiza la alcanzabilidad.

Preparación para IA

¿Hasta qué punto está el repositorio preparado para desarrollarse y mantenerse con agentes de codificación de IA? Es una insignia independiente y experimental — peso 0,0, de modo que se presenta por separado y no afecta a la puntuación de salud global.

63Moderado · 0% del índice global
Cómo se puntúa
0/45Instrucciones para agentes — sin CLAUDE.md / AGENTS.md / reglas de editor
0/15Documentación legible por máquinas (llms.txt)
29.4/40Historial de commits legible — 53 de 96 commits humanos declaran su intención (asunto estructurado o cuerpo explicativo)
Datos de entrada utilizados
has_llms_txtno
legible_history_share0,552
agent_instruction_files
agent_instruction_max_bytes
Cómo se puntúa
18/18Arranque con un solo comando — Makefile, docs/Makefile
22/22Pruebas automatizadas
11/11Configuración de lint / formato — tox.ini
11/11Verificación estática de tipos — model_utils/py.typed, mypy.ini
10/10Entorno reproducible — Dockerfile
2/10Práctica demostrada con agentes — 1 de los últimos 100 commits con autoría o crédito de agente
0/8Mantenimiento automatizado — no se observan actualizaciones automáticas de dependencias
0/10OpenSSF Scorecard: Pinned-Dependencies — sin datos
Datos de entrada utilizados
has_nixno
has_tests
lockfiles
has_dockerfile
typed_languageno
bootstrap_filesMakefile, docs/Makefile
has_devcontainerno
has_linter_config
typecheck_configsmodel_utils/py.typed, mypy.ini
agent_commit_share0,01
toolchain_manifests
dependency_bot_commit_share0
Cómo se puntúa
27/45Código verificable por tipos — Python con configuración de verificación de tipos (model_utils/py.typed, mypy.ini)
55/55Tamaños de archivo manejables — 0/36 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes38.202
source_files_sampled36
oversized_source_files0

Datos clave

2761estrellas de GitHub
99contribuidores
10commits en los últimos 12 meses
8días desde el último push
11versiones publicadas
4factor bus
105issues abiertas
PyPIecosistemas de paquetes

Advertencias de recopilación de datos

  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

Más detalle

Historial de estrellas y forks 2761 ★ / 370 ⇿
2761Estrellas
370Forks
11Versiones

Cuándo se añadió cada estrella y fork, recopilado de GitHub y agrupado por día. El crecimiento acumulado se sitúa justo encima de las adiciones diarias que lo componen, de modo que ambos se leen en conjunto: la acumulación orgánica sostenida no se parece en nada a un pico abrupto y efímero. Cuando esa diferencia es medible, se informa como autenticidad del crecimiento.

Solo se muestra el historial más reciente: este repositorio supera la ventana de recopilación, por lo que no se captura el historial más antiguo.

0500100015002000250030002761361182010-092018-082026-07
Mayor 2Menor 4Parche 4

Cada punto abarca 15 días.

Todas las dependencias 12

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 0 paquetes directos y 12 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
PyPIdjangoindirecta
PyPIdjango-stubs5.1.3indirecta
PyPImypyindirecta
PyPIpsycopgindirecta
PyPIpsycopg2-binaryindirecta
PyPIpytestindirecta
PyPIpytest-cov4.1.0indirecta
PyPIpytest-djangoindirecta
PyPIsphinxindirecta
PyPItime-machineindirecta
PyPItoxindirecta
PyPItwineindirecta
Avisos de dependencias 0

Instalar pypi:django-model-utils@5.0.0 arrastra 3 paquetes, directos y transitivos: 0 tienen avisos conocidos, de los cuales 0 son dependencias directas.

Ningún aviso conocido afecta a las dependencias evaluadas.

Un aviso significa que la versión registrada en el grafo de dependencias cae dentro del rango afectado de un aviso. No se analiza la alcanzabilidad, y el grafo incluye fijaciones de desarrollo y prueba: un hallazgo puede referirse al utillaje y no al software distribuido.

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          "body": "This catch was introduced in #367, but subsequent discussion\nin #370, #381 and #382 suggests that it wasn't the proper solution.\n\nNow that `AbstractModelTrackerTests` is re-enabled and passing,\nit becomes clear that `AttributeError` is no longer raised during\nunit testing when using a recent Django version. Therefore I think\nit is safe to remove the `try`/`except`.",
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          "author_name": "Maarten ter Huurne",
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          "author_name": "Maarten ter Huurne",
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}

Las puntuaciones son señales, no garantías. Reflejan prácticas públicamente visibles en GitHub; no son una auditoría de código ni una garantía de seguridad.

Los datos ausentes se excluyen y los pesos se renormalizan; nunca se puntúan como cero. La metodología es versionada y abierta: métricas v1.13.0, esquema v0.26.0 — metodología completa · wiki de métricas.

Cómo se sitúa un resultado dentro del registro general: estadísticas agregadasPyPI.