Registro públicoBueno
Informe de salud del softwareesquema 0.16.0 · métricas 1.13.0 · 2026-07-21 02:34 UTC
awslabs / gluonts
Probabilistic time series modeling in Python
awslabs/gluonts tiene un índice de salud de 79 sobre 100, lo que lo sitúa en la banda Bueno. Su puntuación más alta es Community & Adoption (95/100) y la más baja, AI Readiness (48/100). Se actualizó por última vez hoy. 4 personas concentran la mayor parte del trabajo reciente.
79
global / 100Índice 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.
79
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)
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
Amazon Web Services - LabsOrganización
11.285 seguidores1019 repositorios públicosdesde ene 2013
Este repositorio está respaldado por una organización: una custodia compartida y responsable que puede sobrevivir a cualquier mantenedor individual.
Ecosistemas de paquetes
| Registro | Paquete | Versión | Descargas / mes | Versiones | Última publicación |
|---|---|---|---|---|---|
| PyPI | gluonts | 0.16.3 | 8.485.649 | 112 | hace 21 días |
Métricas por categoría
Vitalidad
¿Está vivo el proyecto: se escribe código y se publican versiones?
73
Actividad de desarrollo
60Moderado
Cómo se puntúa
| 36/36 | Recencia de push — último push hace 0 días |
| 4.2/36 | Cadencia de commits — 6/52 semanas con commits |
| 11.1/18 | Volumen de commits — 16 commits en el último año |
| 9/10 | OpenSSF Scorecard: Maintained — 11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9 |
Datos de entrada utilizados
| commits_last_year | 16 |
| human_commit_share | — |
| days_since_last_push | 0 |
| active_weeks_last_year | 6 |
Disciplina de publicación
92Excelente
Cómo se puntúa
| 27/27 | Publica versiones — 100 versiones publicadas |
| 36/36 | Recencia de las versiones — última versión hace 21 días |
| 19.8/27 | Cadencia de publicación — una versión cada ~103,9 días |
| 0/10 | OpenSSF Scorecard: Signed-Releases — sin datos |
Datos de entrada utilizados
| releases_count | 100 |
| latest_release_tag | v0.16.3 |
| releases_from_tags | no |
| days_since_latest_release | 21 |
| mean_days_between_releases | 103,9 |
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?
95
Popularidad y adopción
95Excelente
Cómo se puntúa
| 60/60 | Estrellas — 5220 estrellas |
| 24.3/25 | Forks — 823 forks |
| 10.4/15 | Observadores — 74 observadores |
Datos de entrada utilizados
| forks | 823 |
| stars | 5220 |
| watchers | 74 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Salud de la comunidad
92Excelente
Cómo se puntúa
| 22.5/22.5 | README |
| 22.5/22.5 | Licencia — licencia reconocida (Apache-2.0) |
| 18/18 | Guía CONTRIBUTING |
| 13.5/13.5 | Código de conducta |
| 0/7.2 | Plantilla de issues |
| 6.3/6.3 | Plantilla de PR |
Datos de entrada utilizados
| has_readme | sí |
| has_license | sí |
| has_contributing | sí |
| has_issue_template | no |
| has_code_of_conduct | sí |
| has_pull_request_template | sí |
Adopción en el ecosistema (descargas)
100Excelente
Cómo se puntúa
| 80/80 | Descargas mensuales — 8.485.649 descargas/mes en pypi |
| 0/20 | Dependientes en el registro — no lo informa este ecosistema |
Datos de entrada utilizados
| packages | gluonts |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 8.485.649 |
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?
84
Cómo se puntúa
| 43.2/54 | Factor bus — la mitad de los commits recae en 4 contribuyente(s) |
| 14/22.5 | Distribución de commits — el principal contribuyente firma el 38% de los commits |
| 13.5/13.5 | Amplitud de contribuyentes — 100 contribuyentes |
| 10/10 | OpenSSF Scorecard: Contributors — project has 17 contributing companies or organizations |
Datos de entrada utilizados
| bus_factor | 4 |
| contributors_sampled | 100 |
| top_contributor_share | 0,377 |
Cómo se puntúa
| 30.4/46.8 | Resolución de issues — 65% de issues cerradas |
| 34.6/38.3 | Aceptación de PR — 1583/1749 PR decididos fusionados |
| 12/15 | OpenSSF Scorecard: Code-Review — Found 26/29 approved changesets -- score normalized to 8 |
Datos de entrada utilizados
| merged_prs | 1583 |
| open_issues | 344 |
| closed_issues | 641 |
| issue_closed_ratio | 0,651 |
| closed_unmerged_prs | 166 |
Propiedad y custodia
80Bueno
Cómo se puntúa
| 30/30 | Respaldo de la propiedad — propiedad de una organización |
| 0/20 | Dominio verificado |
| 25/25 | Alcance del propietario — 11.285 seguidores de awslabs |
| 25/25 | Trayectoria — 1019 repos públicos, cuenta de ~13 años |
Datos de entrada utilizados
| followers | 11.285 |
| owner_type | Organization |
| is_verified | — |
| owner_login | awslabs |
| public_repos | 1019 |
| account_age_days | 4932 |
Mantenimiento de paquetes
100Excelente
Cómo se puntúa
| 25/25 | Publicado y resoluble — 1 paquete(s) en pypi |
| 35/35 | Recencia de publicación — última publicación hace 21 días |
| 20/20 | Historial de versiones — 112 versiones en el registro |
| 20/20 | No obsoleto — activo, ni obsoleto ni retirado |
Datos de entrada utilizados
| packages | gluonts |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 21 |
Calidad de Ingeniería
¿Existen unas prácticas mínimas de ingeniería y documentación?
72
Prácticas de ingeniería
60Moderado
Cómo se puntúa
| 24/24 | Flujos de trabajo de CI — 13 flujo(s) de trabajo |
| 24/24 | Pruebas presentes |
| 0/16 | Configuración de linter |
| 0/9.6 | Hooks de pre-commit |
| 0/6.4 | .editorconfig |
| 12/20 | OpenSSF Scorecard: CI-Tests — 18 out of 30 merged PRs checked by a CI test -- score normalized to 6 |
Datos de entrada utilizados
| has_ci | sí |
| has_tests | sí |
| has_editorconfig | no |
| has_linter_config | no |
| has_precommit_config | no |
Documentación
90Excelente
Cómo se puntúa
| 30/30 | README |
| 25/25 | Directorio de documentación |
| 15/15 | Sitio de documentación / página del proyecto — https://ts.gluon.ai |
| 10/10 | Descripción del repositorio |
| 10/10 | Topics — 15 topics |
| 0/10 | Wiki |
Datos de entrada utilizados
| topics | time-series, deep-learning, forecasting, neural-networks, machine-learning, time-series-prediction, time-series-forecasting, mxnet, pytorch, aws, sagemaker, timeseries, artificial-intelligence, data-science, torch |
| has_wiki | no |
| homepage | https://ts.gluon.ai |
| has_readme | sí |
| has_docs_dir | sí |
| has_description | sí |
Seguridad
¿Son sólidas las prácticas visibles de seguridad y de cadena de suministro, sin exposición jurisdiccional de alto riesgo sin resolver?
71
Postura de seguridad
64Moderado
Cómo se puntúa
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 4.5/7.5 | Branch-Protection — branch protection is not maximal on development and all release branches |
| 1.5/2.5 | CI-Tests — 18 out of 30 merged PRs checked by a CI test -- score normalized to 6 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 6/7.5 | Code-Review — Found 26/29 approved changesets -- score normalized to 8 |
| 2.5/2.5 | Contributors — project has 17 contributing companies or organizations |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 7.5/7.5 | Dependency-Update-Tool — update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | Licencia — license file detected |
| 6.8/7.5 | Maintained — 11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9 |
| 5/5 | Packaging — packaging workflow detected |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 4/5 | SAST — SAST tool detected but not run on all commits |
| 5/5 | Security-Policy — security policy file detected |
| 0/7.5 | Signed-Releases — sin datos |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 0/7.5 | Vulnerabilities — 24 existing vulnerabilities detected |
Datos de entrada utilizados
| source | openssf_scorecard |
| checks_evaluated | 17 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 1 |
| scorecard_aggregate | 6,4 |
Excluidos de la puntuación (sin datos o no aplicable): signed_releases. Los pesos restantes se han renormalizado.
Avisos de dependencias
100Excelente
Cómo se puntúa
| 35/35 | Dependencias directas libres de avisos conocidos — ninguna dependencia directa tiene un aviso conocido |
| 25/25 | Dependencias indirectas libres de avisos conocidos — ninguna dependencia indirecta tiene un aviso conocido |
| 0/40 | Sin avisos pendientes — ningún aviso tiene fecha de publicación |
Datos de entrada utilizados
| source | osv |
| advisories | 0 |
| affected_packages | 0 |
| assessed_packages | 13 |
| unassessed_packages | 0 |
| affected_by_severity | none |
| direct_affected_packages | 0 |
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:gluonts@0.16.3 —lo que arrastra la instalación del paquete publicado—: 13 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.
48
Contexto y guía para agentes
1Crítico
Cómo se puntúa
| 0/45 | Instrucciones para agentes — sin CLAUDE.md / AGENTS.md / reglas de editor |
| 0/15 | Documentación legible por máquinas (llms.txt) |
| 0/40 | Historial de commits legible — sin datos |
Datos de entrada utilizados
| has_llms_txt | no |
| legible_history_share | — |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Excluidos de la puntuación (sin datos o no aplicable): Historial de commits legible. Los pesos restantes se han renormalizado.
Cómo se puntúa
| 18/18 | Arranque con un solo comando — Justfile, docs/Makefile |
| 22/22 | Pruebas automatizadas |
| 0/11 | Configuración de lint / formato |
| 11/11 | Verificación estática de tipos — src/gluonts/core/py.typed |
| 10/10 | Entorno reproducible — Dockerfile |
| 0/10 | Práctica demostrada con agentes — sin datos |
| 0/8 | Mantenimiento automatizado — sin datos |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
Datos de entrada utilizados
| has_nix | no |
| has_tests | sí |
| lockfiles | — |
| has_dockerfile | sí |
| typed_language | no |
| bootstrap_files | Justfile, docs/Makefile |
| has_devcontainer | no |
| has_linter_config | no |
| typecheck_configs | src/gluonts/core/py.typed |
| agent_commit_share | — |
| toolchain_manifests | — |
| dependency_bot_commit_share | — |
Excluidos de la puntuación (sin datos o no aplicable): Práctica demostrada con agentes, Mantenimiento automatizado. Los pesos restantes se han renormalizado.
Cómo se puntúa
| 27/45 | Código verificable por tipos — Python con configuración de verificación de tipos (src/gluonts/core/py.typed) |
| 54.9/55 | Tamaños de archivo manejables — 1/863 archivos fuente de más de 60 KB |
Datos de entrada utilizados
| primary_language | Python |
| largest_source_bytes | 159.687 |
| source_files_sampled | 863 |
| oversized_source_files | 1 |
Interfaces legibles por máquina
40En riesgo
Cómo se puntúa
| 0/40 | Esquema de API (OpenAPI/GraphQL/proto) |
| 0/20 | Servidor MCP |
| 40/40 | Ejemplos ejecutables — examples, notebooks |
Datos de entrada utilizados
| example_dirs | examples, notebooks |
| has_mcp_signal | no |
| api_schema_files | — |
Datos clave
5220estrellas de GitHub
100contribuidores
16commits en los últimos 12 meses
0días desde el último push
100versiones publicadas
4factor bus
344issues abiertas
PyPIecosistemas de paquetes
Más detalle
OpenSSF Scorecard 6.4 / 10
6.4agregado
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).
| 10 | Binary-Artifacts | no binaries found in the repo |
| 6 | Branch-Protection | branch protection is not maximal on development and all release branches |
| 6 | CI-Tests | 18 out of 30 merged PRs checked by a CI test -- score normalized to 6 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 8 | Code-Review | Found 26/29 approved changesets -- score normalized to 8 |
| 10 | Contributors | project has 17 contributing companies or organizations |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 10 | Dependency-Update-Tool | update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 9 | Maintained | 11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9 |
| 10 | Packaging | packaging workflow detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 8 | SAST | SAST tool detected but not run on all commits |
| 10 | Security-Policy | security policy file detected |
| n/d | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 0 | Vulnerabilities | 24 existing vulnerabilities detected |
Dependencias directas 7
| Registro | Paquete | Restricción de versión | Manifiesto |
|---|---|---|---|
| PyPI | numpy | >=1.24,<3 | pyproject.toml |
| PyPI | numpy | >=1.16,<3 | pyproject.toml |
| PyPI | pandas | >=1.4,<3 | pyproject.toml |
| PyPI | pydantic | >=1.7,<3 | pyproject.toml |
| PyPI | tqdm | ~=4.23 | pyproject.toml |
| PyPI | toolz | ~=0.10 | pyproject.toml |
| PyPI | typing-extensions | ~=4.0 | pyproject.toml |
Todas las dependencias 66
Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 8 paquetes directos y 58 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.
| Registro | Paquete | Versión | Relación |
|---|---|---|---|
| PyPI | numpy | — | directa |
| PyPI | numpy | 1.22.0 | directa |
| PyPI | pandas | — | directa |
| PyPI | pandas | 1.1.5 | directa |
| PyPI | pydantic | — | directa |
| PyPI | toolz | — | directa |
| PyPI | tqdm | — | directa |
| PyPI | typing-extensions | — | directa |
| PyPI | autogluon-tabular | — | indirecta |
| PyPI | black | — | indirecta |
| PyPI | boto3 | — | indirecta |
| PyPI | botocore | — | indirecta |
| PyPI | catch22 | — | indirecta |
| PyPI | click | — | indirecta |
| PyPI | cython | — | indirecta |
| PyPI | docutils | — | indirecta |
| PyPI | flask | — | indirecta |
| PyPI | furo | 2022.6.4.1 | indirecta |
| PyPI | geomloss | — | indirecta |
| PyPI | gluonts | — | indirecta |
| PyPI | hierarchicalforecast | — | indirecta |
| PyPI | holidays | — | indirecta |
| PyPI | ipykernel | — | indirecta |
| PyPI | isort | — | indirecta |
| PyPI | jupyter | — | indirecta |
| PyPI | lightgbm | — | indirecta |
| PyPI | lightkit | — | indirecta |
| PyPI | lightning | — | indirecta |
| PyPI | lxml | — | indirecta |
| PyPI | matplotlib | — | indirecta |
| PyPI | matplotlib | 3.3.2 | indirecta |
| PyPI | mxnet | — | indirecta |
| PyPI | mypy | 1.8.0 | indirecta |
| PyPI | nbconvert | — | indirecta |
| PyPI | nbsphinx | — | indirecta |
| PyPI | optuna | — | indirecta |
| PyPI | prophet | — | indirecta |
| PyPI | pylint | — | indirecta |
| PyPI | pytest | — | indirecta |
| PyPI | pytest-cov | — | indirecta |
| PyPI | pytest-rerunfailures | — | indirecta |
| PyPI | pytest-runner | — | indirecta |
| PyPI | pytest-timeout | — | indirecta |
| PyPI | pytest-xdist | — | indirecta |
| PyPI | python-dotenv | — | indirecta |
| PyPI | pytorch-lightning | — | indirecta |
| PyPI | pytorchts | 0.2.0 | indirecta |
| PyPI | requests | — | indirecta |
| PyPI | rpy2 | — | indirecta |
| PyPI | ruff | 0.2.2 | indirecta |
| PyPI | s3fs | — | indirecta |
| PyPI | sagemaker | — | indirecta |
| PyPI | scikit-learn | — | indirecta |
| PyPI | scipy | 1.10.0 | indirecta |
| PyPI | seaborn | — | indirecta |
| PyPI | setuptools | — | indirecta |
| PyPI | sklearn | — | indirecta |
| PyPI | sphinx | — | indirecta |
| PyPI | statsforecast | — | indirecta |
| PyPI | statsmodels | — | indirecta |
| PyPI | tensorboard | — | indirecta |
| PyPI | tensorboard | 2.3.0 | indirecta |
| PyPI | torch | — | indirecta |
| PyPI | waitress | — | indirecta |
| PyPI | xgboost | — | indirecta |
| PyPI | xlrd | — | indirecta |
Avisos de dependencias 0
Instalar pypi:gluonts@0.16.3 arrastra 13 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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],
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{
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},
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"notes": [],
"value": 92,
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{
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{
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{
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{
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}
]
},
{
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{
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]
},
{
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"note": null,
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{
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},
{
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{
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{
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{
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}
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{
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]
}
],
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},
{
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"band": "good",
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"weight": 0.2,
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{
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"notes": [],
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{
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{
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{
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]
},
{
"key": "documentation",
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"notes": [],
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"inputs": {
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"components": [
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{
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}
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{
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}
]
}
],
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{
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},
{
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"components": [
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{
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{
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{
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{
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{
"key": "contributors",
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},
{
"key": "dangerous_workflow",
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},
{
"key": "dependency_update_tool",
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},
{
"key": "fuzzing",
"name": "Fuzzing",
"detail": "project is not fuzzed",
"points": 0,
"status": "missed",
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},
{
"key": "license",
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{
"key": "maintained",
"name": "Maintained",
"detail": "11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9",
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},
{
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},
{
"key": "pinned_dependencies",
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"points": 0,
"status": "missed",
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},
{
"key": "sast",
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},
{
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{
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"code": "no_data",
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],
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{
"key": "vulnerabilities",
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]
},
{
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"notes": [
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"code": "excluded_no_data",
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{
"code": "weights_renormalized",
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{
"code": "advisories_scope_published",
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},
{
"code": "advisories_reachability",
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}
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"inputs": {
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"direct_affected_packages": 0
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"components": [
{
"key": "direct_dependencies_free_of_known_advisories",
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"details": [
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}
],
"max_points": 35
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{
"key": "indirect_dependencies_free_of_known_advisories",
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"details": [
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"code": "no_indirect_advisories",
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}
],
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},
{
"key": "no_advisories_left_outstanding",
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"status": "excluded",
"details": [
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"code": "advisories_no_publication_date",
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],
"max_points": 40
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]
},
{
"key": "malicious_dependencies",
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"note": null,
"notes": [],
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"inputs": {
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"direct_malicious_packages": 0,
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"components": [
{
"key": "no_dependency_reported_as_a_malicious_package",
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]
},
{
"key": "high_risk_jurisdiction_exposure",
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"notes": [
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"code": "jurisdiction_evidence_limits",
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}
],
"value": 100,
"inputs": {
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"exposures": [],
"policy_countries": [
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"review_only_matches": 0,
"assessed_self_published_locations": 9
},
"components": [
{
"key": "policy_exposure_multiplier",
"name": "Policy exposure multiplier",
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"status": "met",
"details": [
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"code": "jurisdiction_no_match",
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}
],
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}
]
}
],
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},
{
"key": "ai_readiness",
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"name": "AI Readiness",
"value": 48,
"weight": 0,
"metrics": [
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"key": "ai_agent_context",
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},
{
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],
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"components": [
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"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."
}
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"full_name": "awslabs/gluonts",
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"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 v1.13.0, esquema v0.16.0 — metodología completa · wiki de métricas.
Cómo se sitúa un resultado dentro del registro general: estadísticas agregadas — PyPI.