Registro público
Informe de salud del softwareesquema 0.31.0 · métricas 2.5.0 · 2026-08-05 07:50 UTC

Quantinuum / pytket-quantinuum

pytket-quantinuum, extensions for pytket quantum SDK

Python · LLVMApache-2.0★ 35 estrellas⑂ 19 forksdesde jul 2022Ver en GitHub ↗
TipoBibliotecaHerramienta de línea de comandoscómo se determina

Quantinuum/pytket-quantinuum tiene un índice de salud de 88 sobre 100, lo que lo sitúa en la banda Excelente. Su puntuación más alta es Engineering Quality (86/100) y la más baja, AI Readiness (53/100). Se actualizó por última vez hoy. 3 personas concentran la mayor parte del trabajo reciente.

88
global / 100
Excelente

Índice de salud del software

Las métricas se agrupan en categorías ponderadas sobre una escala estandarizada de 1 a 100. El resultado global parte de su media ponderada, calibrada contra la distribución del registro público para que las bandas tengan significado percentil; cuando la evidencia pública activa la Política de Jurisdicciones de Alto Riesgo, la calificación se ajusta y recibe un límite «En riesgo» de 34.

88
Excepcional93-100El nivel más alto del registro (≈ el 5% superior); cumple prácticamente todos los criterios evaluados
Excelente80-92Sólido en todos los frentes; carencias menores
Bueno65-79Saludable; carencias limitadas y manejables
Moderado50-64Aceptable con carencias notables; se recomienda revisión
Débil35-49Debilidades sustanciales en varias áreas
En riesgo20-34Debilidades significativas; su adopción exige cautela
Crítico1-19Problemas 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.

El resultado global ponderado 74 se calibra a 88 en la escala publicada del índice (calibración del registro 2026-08-02).

Titularidad

Quantinuum LtdOrganización
329 seguidores203 repositorios públicosdesde nov 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
PyPIpytket-quantinuum0.59.117.88085hace 83 días

Métricas por categoría

Vitalidad

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

80Excelente · 21% del índice global
Cómo se puntúa
36/36Recencia de push — último push hace 0 días
13.2/36Cadencia de commits — 19/52 semanas con commits
14.8/18Volumen de commits — 43 commits en el último año
3/10OpenSSF Scorecard: Maintained — 3 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 3
Datos de entrada utilizados
commits_last_year43
human_commit_share0,93
days_since_last_push0
active_weeks_last_year19
Cómo se puntúa
27/27Publica versiones — 85 versiones publicadas
36/36Recencia de las versiones — última versión hace 0 días
27/27Cadencia de publicación — una versión cada ~13,2 días
0/10OpenSSF Scorecard: Signed-Releases — sin datos
Datos de entrada utilizados
releases_count85
latest_release_tagv0.55.8
releases_from_tagsno
days_since_latest_release0
mean_days_between_releases13,2
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?

54Moderado · 17% del índice global
Cómo se puntúa
24.8/60Estrellas — 35 estrellas
10.5/25Forks — 19 forks
4.3/15Observadores — 7 observadores
Datos de entrada utilizados
forks19
stars35
watchers7
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)
0/18Guía 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
readme_badges2
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesshields.io
has_pull_request_template
Cómo se puntúa
56.7/80Descargas mensuales — 17.880 descargas/mes en pypi
0/20Dependientes en el registro — no lo informa este ecosistema
Datos de entrada utilizados
packagespytket-quantinuum
dependents
ecosystemspypi
total_downloads
monthly_downloads17.880
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?

84Excelente · 23% del índice global
Cómo se puntúa
36/54Factor bus — la mitad de los commits recae en 3 contribuyente(s)
17.8/22.5Distribución de commits — el principal contribuyente firma el 21% de los commits
13.5/13.5Amplitud de contribuyentes — 16 contribuyentes
10/10OpenSSF Scorecard: Contributors — project has 5 contributing companies or organizations
Datos de entrada utilizados
bus_factor3
contributors_sampled16
top_contributor_share0,208
Cómo se puntúa
39.5/42Resolución de issues — 94% de issues cerradas
24.7/30Aceptación de PR — 462/562 PR decididos fusionados
0/13Newcomer PR acceptance — ningún PR de un contribuyente primerizo decidido en 30 d
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Datos de entrada utilizados
merged_prs462
open_issues8
closed_issues126
prs_merged_7d1
prs_decided_7d1
prs_merged_30d2
prs_decided_30d2
issue_closed_ratio0,94
closed_unmerged_prs100
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluidos de la puntuación (sin datos o no aplicable): newcomer_pr_acceptance. Los pesos restantes se han renormalizado.
Cómo se puntúa
30/30Respaldo de la propiedad — propiedad de una organización
0/20Dominio verificado
18.1/25Alcance del propietario — 329 seguidores de Quantinuum
25/25Trayectoria — 203 repos públicos, cuenta de ~10 años
Datos de entrada utilizados
followers329
owner_typeOrganization
is_verified
owner_loginQuantinuum
public_repos203
account_age_days3924
Cómo se puntúa
25/25Publicado y resoluble — 1 paquete(s) en pypi
35/35Recencia de publicación — última publicación hace 83 días
20/20Historial de versiones — 85 versiones en el registro
20/20No obsoleto — activo, ni obsoleto ni retirado
Datos de entrada utilizados
packagespytket-quantinuum
ecosystemspypi
any_deprecatedno
min_days_since_publish83

Calidad de Ingeniería

¿Existen unas prácticas mínimas de ingeniería y documentación?

86Excelente · 19% del índice global
Cómo se puntúa
24/24Flujos de trabajo de CI — 4 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 — 25 out of 25 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
Cómo se puntúa
30/30README
25/25Directorio de documentación
0/15Sitio de documentación / página del proyecto
10/10Descripción del repositorio
0/10Topics
10/10Wiki
Datos de entrada utilizados
topics
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?

65Bueno · 16% del índice global
Cómo se puntúa
5.2/7.5Binary-Artifacts — binaries present in source code
0/7.5Branch-Protection — sin datos
2.5/2.5CI-Tests — 25 out of 25 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 5 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
2.2/7.5Maintained — 3 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 3
0/5Packaging — sin datos
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_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate5,6
Excluidos de la puntuación (sin datos o no aplicable): branch_protection, packaging, 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_packages4
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:pytket-quantinuum@0.59.1 —lo que arrastra la instalación del paquete publicado—: 4 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? Tiene un peso deliberadamente pequeño (4%): las herramientas para agentes son una señal real de mantenimiento, pero un repositorio sin ninguna puede alcanzar igualmente 100/100.

53Moderado · 4% 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)
40/40Historial de commits legible — 80 de 93 commits humanos declaran su intención (asunto estructurado o cuerpo explicativo)
Datos de entrada utilizados
has_llms_txtno
legible_history_share0,86
agent_instruction_files
agent_instruction_max_bytes
Cómo se puntúa
0/18Arranque con un solo comando
22/22Pruebas automatizadas
11/11Configuración de lint / formato — ruff.toml
11/11Verificación estática de tipos — mypy.ini, pytket/extensions/quantinuum/py.typed
0/10Entorno reproducible
0/10Práctica demostrada con agentes — ningún commit con autoría de agente entre los últimos 100
8/8Mantenimiento automatizado — 7 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_files
has_devcontainerno
has_linter_config
typecheck_configsmypy.ini, pytket/extensions/quantinuum/py.typed
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0,07
Cómo se puntúa
27/45Código verificable por tipos — Python con configuración de verificación de tipos (mypy.ini, pytket/extensions/quantinuum/py.typed)
55/55Tamaños de archivo manejables — 0/18 archivos fuente de más de 60 KB
Datos de entrada utilizados
primary_languagePython
largest_source_bytes46.289
source_files_sampled18
oversized_source_files0

Datos clave

35estrellas de GitHub
16contribuidores
43commits en los últimos 12 meses
0días desde el último push
85versiones publicadas
3factor bus
8issues 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 ★ / 19 ⇿
0Estrellas
19Forks
65Versiones

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.

0481216201922022-082024-052026-01
Mayor 0Menor 49Parche 7

Cada punto abarca 4 días.

OpenSSF Scorecard 5.6 / 10
5.6agregado

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 · 2026-08-05 07:49 UTC

7Binary-Artifactsbinaries present in source code
n/dBranch-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-Tests25 out of 25 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 5 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
3Maintained3 commit(s) and 1 issue activity found in the last 90 days -- score normalized to 3
n/dPackagingpackaging workflow not 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
Dependencias directas 3
RegistroPaqueteRestricción de versiónManifiesto
PyPIpytket~= 2.17pyproject.toml
PyPIpytket-qir>= 1.0.0pyproject.toml
PyPInumpy>= 1.26.4pyproject.toml
Todas las dependencias 6

Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 3 paquetes directos y 3 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.

RegistroPaqueteVersiónRelación
PyPInumpydirecta
PyPIpytketdirecta
PyPIpytket-qirdirecta
PyPIpytket-pecosindirecta
PyPIpytket-phirindirecta
PyPIquantum-pecos0.8.0.dev8indirecta
Avisos de dependencias 0

Instalar pypi:pytket-quantinuum@0.59.1 arrastra 4 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.

Informe JSON sin procesar legible por máquina
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                "key": "owner_reach",
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            "name": "Package maintenance",
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                "key": "publish_recency",
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                "key": "version_history",
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        "description": "Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?"
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                "name": "Maintained",
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            ]
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            "note": null,
            "notes": [],
            "value": 100,
            "inputs": {
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              "direct_malicious_packages": 0,
              "withdrawn_malicious_packages": 0,
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                "key": "no_dependency_reported_as_a_malicious_package",
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                "detail": "no dependency is reported as a malicious package",
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          },
          {
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            "notes": [
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            "value": 100,
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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": "openssf_scorecard_pinned_dependencies",
                "name": "OpenSSF Scorecard: Pinned-Dependencies",
                "detail": "dependency not pinned by hash detected -- score normalized to 0",
                "points": 0,
                "status": "missed",
                "details": [],
                "max_points": 10
              }
            ]
          },
          {
            "key": "ai_code_legibility",
            "band": "excellent",
            "name": "Code legibility for models",
            "note": null,
            "notes": [],
            "value": 82,
            "inputs": {
              "primary_language": "Python",
              "largest_source_bytes": 46289,
              "source_files_sampled": 18,
              "oversized_source_files": 0
            },
            "components": [
              {
                "key": "type_checkable_code",
                "name": "Type-checkable code",
                "detail": "Python with type-check config (mypy.ini, pytket/extensions/quantinuum/py.typed)",
                "points": 27,
                "status": "partial",
                "details": [
                  {
                    "code": "typecheck_config_language",
                    "params": {
                      "files": "mypy.ini, pytket/extensions/quantinuum/py.typed",
                      "language": "Python"
                    }
                  }
                ],
                "max_points": 45
              },
              {
                "key": "manageable_file_sizes",
                "name": "Manageable file sizes",
                "detail": "0/18 source files over 60KB",
                "points": 55,
                "status": "met",
                "details": [
                  {
                    "code": "oversized_source_files",
                    "params": {
                      "kb": 60,
                      "sampled": 18,
                      "oversized": 0
                    }
                  }
                ],
                "max_points": 55
              }
            ]
          }
        ],
        "description": "How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight: agent tooling is a real maintenance signal, but its absence must never gate the top of the scale (calibration saturates at raw 91, so 100/100 remains reachable with AI Readiness at zero)."
      }
    ],
    "classification": {
      "top": [
        "library",
        "application"
      ],
      "labels": [
        "library",
        "cli"
      ],
      "scores": {
        "cli": 6,
        "library": 8
      },
      "primary": "library",
      "evidence": [
        {
          "tier": "declared",
          "label": "cli",
          "source": "pypi.classifier:Environment :: Console",
          "weight": 6
        },
        {
          "tier": "distribution",
          "label": "library",
          "source": "registry:pypi",
          "weight": 6
        },
        {
          "tier": "description",
          "label": "library",
          "source": "description:library",
          "weight": 2
        }
      ],
      "artifacts": [
        {
          "path": "pyproject.toml",
          "labels": [
            "cli"
          ],
          "ecosystem": "pypi"
        }
      ],
      "confidence": "medium",
      "host_extension": false,
      "runs_as_process": true,
      "consumed_by_code": true
    },
    "metrics_version": "2.5.0"
  },
  "warnings": [
    "Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token"
  ],
  "report_type": "repository",
  "generated_at": "2026-08-05T07:50:05.733770Z",
  "schema_version": "0.31.0",
  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/q/Quantinuum/pytket-quantinuum.svg",
  "full_name": "Quantinuum/pytket-quantinuum",
  "license_state": "standard",
  "license_spdx": "Apache-2.0"
}

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 v2.5.0, esquema v0.31.0 — metodología completa · wiki de métricas.

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