Registro público
Informe de salud del softwareesquema 0.27.0 · métricas 1.13.0 · 2026-07-28 14:40 UTC

computationalmodelling / nbval

A py.test plugin to validate Jupyter notebooks

Python · Jupyter NotebookLicencia propia★ 453 estrellas⑂ 54 forksdesde abr 2015Ver en GitHub ↗

computationalmodelling/nbval tiene un índice de salud de 56 sobre 100, lo que lo sitúa en la banda Moderado. Su puntuación más alta es Engineering Quality (68/100) y la más baja, Vitality (22/100). Se actualizó por última vez hace 314 días. 2 personas concentran la mayor parte del trabajo reciente.

56
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.

56
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

22 seguidores7 repositorios públicosdesde abr 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
PyPInbval0.11.0585.75419hace 876 días

Métricas por categoría

Vitalidad

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

22Crítico · 22% del índice global
Cómo se puntúa
3.6/36Recencia de push — último push hace 314 días
2.1/36Cadencia de commits — 3/52 semanas con commits
9.4/18Volumen de commits — 10 commits en el último año
0/10OpenSSF Scorecard: Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Datos de entrada utilizados
commits_last_year10
human_commit_share0,99
days_since_last_push314
active_weeks_last_year3
Cómo se puntúa
16.2/27Publica versiones — 12 etiquetas de versión (sin releases de GitHub)
0/36Recencia de las versiones — última versión hace 876 días
12.6/27Cadencia de publicación — una versión cada ~299,3 días
0/10OpenSSF Scorecard: Signed-Releases — sin datos
Datos de entrada utilizados
releases_count12
latest_release_tag0.11.0
releases_from_tags
days_since_latest_release876
mean_days_between_releases299,3
Excluidos de la puntuación (sin datos o no aplicable): OpenSSF Scorecard: Signed-Releases. Los pesos restantes se han renormalizado.

Comunidad y Adopción

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

65Moderado · 18% del índice global
Cómo se puntúa
43.1/60Estrellas — 453 estrellas
14.4/25Forks — 54 forks
5.3/15Observadores — 10 observadores
Datos de entrada utilizados
forks54
stars453
watchers10
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Cómo se puntúa
22.5/22.5README
16.9/22.5Licencia — archivo de licencia presente, no es una licencia reconocida
0/18Guía CONTRIBUTING
0/13.5Código de conducta
0/7.2Plantilla de issues
0/6.3Plantilla de PR
Datos de entrada utilizados
has_readme
has_license
has_contributingno
has_issue_templateno
has_code_of_conductno
has_pull_request_templateno
Cómo se puntúa
76.9/80Descargas mensuales — 585.754 descargas/mes en pypi
0/20Dependientes en el registro — no lo informa este ecosistema
Datos de entrada utilizados
packagesnbval
dependents
ecosystemspypi
total_downloads
monthly_downloads585.754
Excluidos de la puntuación (sin datos o no aplicable): Dependientes en el registro. Los pesos restantes se han renormalizado.

Sostenibilidad y Gobernanza

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

66Moderado · 24% del índice global
Cómo se puntúa
25.2/54Factor bus — la mitad de los commits recae en 2 contribuyente(s)
14.6/22.5Distribución de commits — el principal contribuyente firma el 35% de los commits
13.5/13.5Amplitud de contribuyentes — 32 contribuyentes
10/10OpenSSF Scorecard: Contributors — project has 69 contributing companies or organizations
Datos de entrada utilizados
bus_factor2
contributors_sampled32
top_contributor_share0,349
Cómo se puntúa
28.2/46.8Resolución de issues — 60% de issues cerradas
33.6/38.3Aceptación de PR — 93/106 PR decididos fusionados
12/15OpenSSF Scorecard: Code-Review — Found 13/15 approved changesets -- score normalized to 8
Datos de entrada utilizados
merged_prs93
open_issues46
closed_issues70
issue_closed_ratio0,603
closed_unmerged_prs13
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
9.8/25Alcance del propietario — 22 seguidores de computationalmodelling
18.6/25Trayectoria — 7 repos públicos, cuenta de ~11 años
Datos de entrada utilizados
followers22
owner_typeOrganization
is_verified
owner_logincomputationalmodelling
public_repos7
account_age_days4128
Cómo se puntúa
25/25Publicado y resoluble — 1 paquete(s) en pypi
4/35Recencia de publicación — última publicación hace 876 días
20/20Historial de versiones — 19 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packagesnbval
ecosystemspypi
any_deprecatedno
min_days_since_publish876

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

68Moderado · 20% del índice global
Cómo se puntúa
24/24Flujos de trabajo de CI — 2 flujo(s) de trabajo
24/24Pruebas presentes
0/16Configuración de linter
0/9.6Hooks de pre-commit
0/6.4.editorconfig
8/20OpenSSF Scorecard: CI-Tests — 6 out of 15 merged PRs checked by a CI test -- score normalized to 4
Datos de entrada utilizados
has_ci
has_tests
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentación

85Excelente
Cómo se puntúa
30/30README
25/25Directorio de documentación
0/15Sitio de documentación / página del proyecto
10/10Descripción del repositorio
10/10Topics — 6 topics
10/10Wiki
Datos de entrada utilizados
topicsipython-notebook, jupyter-notebook, python, testing, pytest-plugin, pytest
has_wiki
homepage
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?

60Moderado · 16% del índice global
Cómo se puntúa
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
1/2.5CI-Tests — 6 out of 15 merged PRs checked by a CI test -- score normalized to 4
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
6/7.5Code-Review — Found 13/15 approved changesets -- score normalized to 8
2.5/2.5Contributors — project has 69 contributing companies or organizations
10/10Dangerous-Workflow — no dangerous workflow patterns detected
7.5/7.5Dependency-Update-Tool — update tool detected
0/5Fuzzing — project is not fuzzed
2.2/2.5Licencia — license file detected
0/7.5Maintained — 0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — sin datos
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Datos de entrada utilizados
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate5,1
Excluidos de la puntuación (sin datos o no aplicable): signed_releases. 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_packages41
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:nbval@0.11.0 —lo que arrastra la instalación del paquete publicado—: 41 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.

41En riesgo · 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)
24.8/40Historial de commits legible — 46 de 99 commits humanos declaran su intención (asunto estructurado o cuerpo explicativo)
Datos de entrada utilizados
has_llms_txtno
legible_history_share0,465
agent_instruction_files
agent_instruction_max_bytes
Cómo se puntúa
18/18Arranque con un solo comando — docs/Makefile, issues/67/Makefile, tests/Makefile
22/22Pruebas automatizadas
0/11Configuración de lint / formato
0/11Verificación estática de tipos
0/10Entorno reproducible
0/10Práctica demostrada con agentes — ningún commit con autoría de agente entre los últimos 100
8/8Mantenimiento automatizado — 1 de los últimos 100 commits son actualizaciones automáticas de dependencias
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Datos de entrada utilizados
has_nixno
has_tests
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filesdocs/Makefile, issues/67/Makefile, tests/Makefile
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0,01
Cómo se puntúa
0/45Código verificable por tipos — Python sin configuración de verificación de tipos
55/55Tamaños de archivo manejables — 0/23 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes36.043
source_files_sampled23
oversized_source_files0
Cómo se puntúa
0/40Esquema de API (OpenAPI/GraphQL/proto)
0/20Servidor MCP
40/40Ejemplos ejecutables — notebooks
Datos de entrada utilizados
example_dirsnotebooks
has_mcp_signalno
api_schema_files

Datos clave

453estrellas de GitHub
32contribuidores
10commits en los últimos 12 meses
314días desde el último push
12versiones publicadas
2factor bus
46issues abiertas
PyPIecosistemas de paquetes

Advertencias de recopilación de datos

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

Más detalle

Historial de estrellas y forks 0 ★ / 54 ⇿
0Estrellas
54Forks
12Versiones

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.

01020304050605122015-042020-102026-04
Mayor 0Menor 3Parche 9

Cada punto abarca 11 días.

OpenSSF Scorecard 5.1 / 10
5.1agregado

Evaluación de seguridad independiente y agnóstica en cuanto a herramientas, procedente del proyecto de código abierto OpenSSF Scorecard. Cada comprobación premia una práctica de seguridad, no la herramienta de un proveedor concreto. Las comprobaciones que Scorecard no pudo determinar se marcan como n/d y se excluyen de la puntuación de seguridad (nunca se cuentan como cero).Scorecard v5.5.0 · 2026-07-28 14:39 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
4CI-Tests6 out of 15 merged PRs checked by a CI test -- score normalized to 4
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
8Code-ReviewFound 13/15 approved changesets -- score normalized to 8
10Contributorsproject has 69 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
9Licenselicense 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
n/dSigned-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Todas las dependencias 5

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 0 paquetes directos y 5 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
PyPIcoverageindirecta
PyPIipykernelindirecta
PyPIjupyter-clientindirecta
PyPInbformatindirecta
PyPIpytestindirecta
Avisos de dependencias 0

Instalar pypi:nbval@0.11.0 arrastra 41 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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                "key": "openssf_scorecard_contributors",
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                "key": "pr_acceptance",
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                "key": "openssf_scorecard_code_review",
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            "key": "stewardship",
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              "followers": 22,
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                "key": "ownership_backing",
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                "key": "owner_reach",
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                "key": "track_record",
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        ],
        "description": "Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?"
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                "key": "contributors",
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                "key": "dependency_update_tool",
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                "key": "fuzzing",
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                "points": 0,
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              {
                "key": "packaging",
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                "max_points": 5
              },
              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
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                "status": "missed",
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              },
              {
                "key": "sast",
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                "status": "missed",
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              },
              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file not detected",
                "points": 0,
                "status": "missed",
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              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
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                "status": "excluded",
                "details": [
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                ],
                "max_points": 7.5
              },
              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 0,
                "status": "missed",
                "details": [],
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              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "0 existing vulnerabilities detected",
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                "status": "met",
                "details": [],
                "max_points": 7.5
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            ]
          },
          {
            "key": "dependency_advisories",
            "band": "excellent",
            "name": "Dependency advisories",
            "note": "Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:nbval@0.11.0 runtime dependency closure — what installing the published package pulls in — 41 packages. Reachability is not analyzed.",
            "notes": [
              {
                "code": "excluded_no_data",
                "params": {
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              {
                "code": "weights_renormalized",
                "params": {}
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                "code": "advisories_scope_published",
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                }
              },
              {
                "code": "advisories_reachability",
                "params": {}
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        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
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                "points": 0,
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            "inputs": {
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              "lockfiles": [],
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              "dependency_bot_commit_share": 0.01
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                "details": [
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              {
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    "metrics_version": "1.13.0"
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  "warnings": [
    "Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token"
  ],
  "report_type": "repository",
  "generated_at": "2026-07-28T14:40:23.533935Z",
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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 v0.27.0 — metodología completa · wiki de métricas.

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