Registro público
Informe de salud del softwareesquema 0.11.0 · métricas 1.13.0 · 2026-07-17 00:16 UTC

NVIDIA / cuda-python

CUDA Python: Performance meets Productivity

Cython · PythonApache-2.0★ 3316 estrellas⑂ 307 forksdesde jun 2021Ver en GitHub ↗

NVIDIA/cuda-python tiene un índice de salud de 83 sobre 100, lo que lo sitúa en la banda Bueno. Su puntuación más alta es Vitality (95/100) y la más baja, Security (70/100). Se actualizó por última vez hoy. 3 personas concentran la mayor parte del trabajo reciente.

83
global / 100
Bueno

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.

83
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

NVIDIA CorporationOrganización
28.050 seguidores766 repositorios públicosdesde may 2012

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
PyPIcuda-bindings13.3.1-20hace 48 días
PyPIcuda-core1.1.0-15hace 7 días
PyPIcuda-pathfinder1.5.6-25hace 16 días
PyPIcuda-python13.3.1-43hace 48 días

Métricas por categoría

Vitalidad

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

95Excelente · 22% del índice global
Cómo se puntúa
36/36Recencia de push — último push hace 0 días
35.3/36Cadencia de commits — 51/52 semanas con commits
18/18Volumen de commits — 829 commits en el último año
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 23 issue activity found in the last 90 days -- score normalized to 10
Datos de entrada utilizados
commits_last_year829
human_commit_share
days_since_last_push0
active_weeks_last_year51
Cómo se puntúa
27/27Publica versiones — 83 versiones publicadas
36/36Recencia de las versiones — última versión hace 7 días
27/27Cadencia de publicación — una versión cada ~9,6 días
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Datos de entrada utilizados
releases_count83
latest_release_tagcuda-core-v1.1.0
releases_from_tagsno
days_since_latest_release7
mean_days_between_releases9,6

Comunidad y Adopción

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

82Bueno · 18% del índice global
Cómo se puntúa
57.1/60Estrellas — 3316 estrellas
20.7/25Forks — 307 forks
9.4/15Observadores — 50 observadores
Datos de entrada utilizados
forks307
stars3316
watchers50
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Cómo se puntúa
22.5/22.5README
22.5/22.5Licencia — licencia reconocida (Apache-2.0)
18/18Guía CONTRIBUTING
0/13.5Código de conducta
0/7.2Plantilla de issues
6.3/6.3Plantilla de PR
Datos de entrada utilizados
has_readme
has_license
has_contributing
has_issue_templateno
has_code_of_conductno
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?

84Bueno · 24% del índice global
Cómo se puntúa
36/54Factor bus — la mitad de los commits recae en 3 contribuyente(s)
16.3/22.5Distribución de commits — el principal contribuyente firma el 28% de los commits
13.5/13.5Amplitud de contribuyentes — 64 contribuyentes
10/10OpenSSF Scorecard: Contributors — project has 39 contributing companies or organizations
Datos de entrada utilizados
bus_factor3
contributors_sampled64
top_contributor_share0,276
Cómo se puntúa
36.5/46.8Resolución de issues — 78% de issues cerradas
32.3/38.3Aceptación de PR — 1167/1380 PR decididos fusionados
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Datos de entrada utilizados
merged_prs1167
open_issues202
closed_issues721
issue_closed_ratio0,781
closed_unmerged_prs213
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
25/25Alcance del propietario — 28.050 seguidores de NVIDIA
25/25Trayectoria — 766 repos públicos, cuenta de ~14 años
Datos de entrada utilizados
followers28.050
owner_typeOrganization
is_verified
owner_loginNVIDIA
public_repos766
account_age_days5180
Cómo se puntúa
25/25Publicado y resoluble — 4 paquete(s) en pypi
35/35Recencia de publicación — última publicación hace 7 días
20/20Historial de versiones — 43 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packagescuda-bindings, cuda-core, cuda-pathfinder, cuda-python
ecosystemspypi
any_deprecatedno
min_days_since_publish7

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

82Bueno · 20% del índice global
Cómo se puntúa
24/24Flujos de trabajo de CI — 20 flujo(s) de trabajo
24/24Pruebas presentes
16/16Configuración de linter — ruff.toml
9.6/9.6Hooks de pre-commit
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
Datos de entrada utilizados
has_ci
has_tests
has_editorconfigno
has_linter_config
has_precommit_config

Documentación

65Moderado
Cómo se puntúa
30/30README
0/25Directorio de documentación
15/15Sitio de documentación / página del proyecto — https://nvidia.github.io/cuda-python/
10/10Descripción del repositorio
0/10Topics
10/10Wiki
Datos de entrada utilizados
topics
has_wiki
homepagehttps://nvidia.github.io/cuda-python/
has_readme
has_docs_dirno
has_description

Seguridad

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

70Bueno · 16% del índice global
Cómo se puntúa
7.5/7.5Binary-Artifacts — no binaries found in the repo
3/7.5Branch-Protection — branch protection is not maximal on development and all release branches
2.5/2.5CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 39 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
2.5/2.5Licencia — license file detected
7.5/7.5Maintained — 30 commit(s) and 23 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
2.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5
3.5/5SAST — SAST tool detected but not run on all commits
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
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_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate7

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.

73Bueno · 0% del índice global
Cómo se puntúa
45/45Instrucciones para agentes — AGENTS.md, CLAUDE.md, benchmarks/cuda_bindings/AGENTS.md, benchmarks/cuda_core/AGENTS.md, cuda_bindings/AGENTS.md, cuda_bindings/CLAUDE.md, cuda_core/AGENTS.md, cuda_core/CLAUDE.md, cuda_pathfinder/AGENTS.md, cuda_pathfinder/CLAUDE.md, cuda_python/AGENTS.md, cuda_python/CLAUDE.md
0/15Documentación legible por máquinas (llms.txt)
0/40Historial de commits legible — sin datos
Datos de entrada utilizados
has_llms_txtno
legible_history_share
agent_instruction_filesAGENTS.md, CLAUDE.md, benchmarks/cuda_bindings/AGENTS.md, benchmarks/cuda_core/AGENTS.md, cuda_bindings/AGENTS.md, cuda_bindings/CLAUDE.md, cuda_core/AGENTS.md, cuda_core/CLAUDE.md, cuda_pathfinder/AGENTS.md, cuda_pathfinder/CLAUDE.md, cuda_python/AGENTS.md, cuda_python/CLAUDE.md
agent_instruction_max_bytes17.215
Excluidos de la puntuación (sin datos o no aplicable): Historial de commits legible. Los pesos restantes se han renormalizado.
Cómo se puntúa
18/18Arranque con un solo comando — cuda_bindings/docs/Makefile, cuda_core/docs/Makefile, cuda_pathfinder/docs/Makefile, cuda_python/docs/Makefile
22/22Pruebas automatizadas
11/11Configuración de lint / formato — ruff.toml
11/11Verificación estática de tipos — cuda_core/cuda/core/py.typed
0/10Entorno reproducible
0/10Práctica demostrada con agentes — sin datos
5/8Mantenimiento automatizado — automatización de dependencias configurada, no observada en los commits muestreados
5/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 5
Datos de entrada utilizados
has_nixno
has_tests
lockfiles
has_dockerfileno
typed_languageno
bootstrap_filescuda_bindings/docs/Makefile, cuda_core/docs/Makefile, cuda_pathfinder/docs/Makefile, cuda_python/docs/Makefile
has_devcontainerno
has_linter_config
typecheck_configscuda_core/cuda/core/py.typed
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
Excluidos de la puntuación (sin datos o no aplicable): Práctica demostrada con agentes. Los pesos restantes se han renormalizado.
Cómo se puntúa
27/45Código verificable por tipos — Cython con configuración de verificación de tipos (cuda_core/cuda/core/py.typed)
54.1/55Tamaños de archivo manejables — 5/317 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languageCython
largest_source_bytes103.852
source_files_sampled317
oversized_source_files5
Cómo se puntúa
0/40Esquema de API (OpenAPI/GraphQL/proto)
0/20Servidor MCP
40/40Ejemplos ejecutables — examples
Datos de entrada utilizados
example_dirsexamples
has_mcp_signalno
api_schema_files

Datos clave

3316estrellas de GitHub
64contribuidores
829commits en los últimos 12 meses
0días desde el último push
83versiones publicadas
3factor bus
202issues abiertas
PyPIecosistemas de paquetes

Advertencias de recopilación de datos

  • Could not fetch pypi package 'cuda-python-test-helpers' from its registry

Más detalle

OpenSSF Scorecard 7.0 / 10
7.0agregado

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 · 2026-07-17 00:15 UTC

10Binary-Artifactsno binaries found in the repo
4Branch-Protectionbranch protection is not maximal on development and all release branches
10CI-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 39 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 23 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 5
7SASTSAST tool detected but not run on all commits
10Security-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
Dependencias directas 4
RegistroPaqueteRestricción de versiónManifiesto
PyPIcuda-pathfinder>=1.4.2cuda_bindings/pyproject.toml
PyPIcuda-pathfinder>=1.4.2cuda_core/pyproject.toml
PyPInumpycuda_core/pyproject.toml
PyPIbackports.strenumcuda_core/pyproject.toml
Todas las dependencias 21

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 2 paquetes directos y 19 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
PyPIcuda-pathfinderdirecta
PyPInumpydirecta
PyPIcloudpickle3.1.2indirecta
PyPIcuda-bindingsindirecta
PyPIcuda-toolkitindirecta
PyPIcythonindirecta
PyPIml-dtypesindirecta
PyPInvidia-cudlaindirecta
PyPInvidia-nvshmem-cu12indirecta
PyPInvidia-nvshmem-cu13indirecta
PyPIpsutil7.2.2indirecta
PyPIpyglet2.1.14indirecta
PyPIpytest9.1.0indirecta
PyPIpytest-benchmark5.2.3indirecta
PyPIpytest-mock3.15.1indirecta
PyPIpytest-randomly4.1.0indirecta
PyPIpytest-repeat0.9.4indirecta
PyPIpytest-rerunfailures16.3indirecta
PyPIpytest-timeout2.4.0indirecta
PyPIsetuptoolsindirecta
PyPIsetuptools-scmindirecta
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                "key": "openssf_scorecard_contributors",
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              {
                "key": "owner_reach",
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                "key": "track_record",
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          {
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        ],
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                "key": "pre_commit_hooks",
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              {
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                "key": "openssf_scorecard_ci_tests",
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            "key": "documentation",
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                "key": "documentation_homepage_site",
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                "key": "wiki",
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            ]
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        ],
        "description": "Are baseline engineering and documentation practices in place?"
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      {
        "key": "security",
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                "key": "binary_artifacts",
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                "key": "branch_protection",
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                "key": "ci_tests",
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              {
                "key": "cii_best_practices",
                "name": "CII-Best-Practices",
                "detail": "no effort to earn an OpenSSF best practices badge detected",
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              {
                "key": "code_review",
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                "key": "contributors",
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                "detail": "project has 39 contributing companies or organizations",
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              {
                "key": "dangerous_workflow",
                "name": "Dangerous-Workflow",
                "detail": "no dangerous workflow patterns detected",
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                "details": [],
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              {
                "key": "dependency_update_tool",
                "name": "Dependency-Update-Tool",
                "detail": "update tool detected",
                "points": 7.5,
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                "details": [],
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              {
                "key": "fuzzing",
                "name": "Fuzzing",
                "detail": "project is not fuzzed",
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                "status": "missed",
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              },
              {
                "key": "license",
                "name": "License",
                "detail": "license file detected",
                "points": 2.5,
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              {
                "key": "maintained",
                "name": "Maintained",
                "detail": "30 commit(s) and 23 issue activity found in the last 90 days -- score normalized to 10",
                "points": 7.5,
                "status": "met",
                "details": [],
                "max_points": 7.5
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              {
                "key": "packaging",
                "name": "Packaging",
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              {
                "key": "pinned_dependencies",
                "name": "Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 5",
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                "status": "partial",
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              {
                "key": "sast",
                "name": "SAST",
                "detail": "SAST tool detected but not run on all commits",
                "points": 3.5,
                "status": "partial",
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              {
                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file detected",
                "points": 5,
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                "details": [],
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              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "Project has not signed or included provenance with any releases.",
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                "status": "missed",
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                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
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                "status": "missed",
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              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "0 existing vulnerabilities detected",
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            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
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                "code": "jurisdiction_evidence_limits",
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            ],
            "value": 100,
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                "key": "policy_exposure_multiplier",
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                "status": "met",
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        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
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      {
        "key": "ai_readiness",
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        "name": "AI Readiness",
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        "weight": 0,
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                "status": "met",
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                "max_points": 45
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                "key": "machine_readable_docs_llms_txt",
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                "key": "demonstrated_agent_practice",
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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 v0.11.0 — metodología completa · wiki de métricas.

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