Registro públicoModerado
Informe de salud del softwareesquema 0.26.0 · métricas 1.13.0 · 2026-07-21 23:20 UTC
tensorflow / fairness-indicators
Tensorflow's Fairness Evaluation and Visualization Toolkit
tensorflow/fairness-indicators tiene un índice de salud de 69 sobre 100, lo que lo sitúa en la banda Moderado. Su puntuación más alta es Engineering Quality (88/100) y la más baja, AI Readiness (29/100). Se actualizó por última vez hace 11 días. 3 personas concentran la mayor parte del trabajo reciente.
69
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.
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)
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
tensorflowOrganización
21.576 seguidores107 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
| Registro | Paquete | Versión | Descargas / mes | Versiones | Última publicación | Etiquetas |
|---|---|---|---|---|---|---|
| PyPI | fairness_indicators | 0.52.0 | - | 34 | hace 11 días | tensorflowmodelanalysisfairnessindicatorstensorboardmachinelearning |
| PyPI | tensorboard_plugin_fairness_indicators | 0.52.0 | 241 | 30 | hace 11 días | tensorflowmodelanalysisfairnessindicatorstensorboardmachinelearning |
Métricas por categoría
Vitalidad
¿Está vivo el proyecto: se escribe código y se publican versiones?
58
Actividad de desarrollo
41En riesgo
Cómo se puntúa
| 28.8/36 | Recencia de push — último push hace 11 días |
| 2.1/36 | Cadencia de commits — 3/52 semanas con commits |
| 9.7/18 | Volumen de commits — 11 commits en el último año |
| 0/10 | OpenSSF Scorecard: Maintained — 1 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0 |
Datos de entrada utilizados
| commits_last_year | 11 |
| human_commit_share | 1 |
| days_since_last_push | 11 |
| active_weeks_last_year | 3 |
Disciplina de publicación
84Bueno
Cómo se puntúa
| 27/27 | Publica versiones — 27 versiones publicadas |
| 36/36 | Recencia de las versiones — última versión hace 11 días |
| 12.6/27 | Cadencia de publicación — una versión cada ~167,2 días |
| 0/10 | OpenSSF Scorecard: Signed-Releases — sin datos |
Datos de entrada utilizados
| releases_count | 27 |
| latest_release_tag | v0.52.0 |
| releases_from_tags | no |
| days_since_latest_release | 11 |
| mean_days_between_releases | 167,2 |
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?
60
Popularidad y adopción
65Moderado
Cómo se puntúa
| 41.4/60 | Estrellas — 358 estrellas |
| 16.2/25 | Forks — 89 forks |
| 7.1/15 | Observadores — 20 observadores |
Datos de entrada utilizados
| forks | 89 |
| stars | 358 |
| watchers | 20 |
| growth_state | organic |
| growth_factor_pct | 100 |
Salud de la comunidad
70Bueno
Cómo se puntúa
| 22.5/22.5 | README |
| 22.5/22.5 | Licencia — licencia reconocida (Apache-2.0) |
| 18/18 | Guía CONTRIBUTING |
| 0/13.5 | Código de conducta |
| 0/7.2 | Plantilla de issues |
| 0/6.3 | Plantilla de PR |
Datos de entrada utilizados
| has_readme | sí |
| has_license | sí |
| has_contributing | sí |
| has_issue_template | no |
| has_code_of_conduct | no |
| has_pull_request_template | no |
Adopción en el ecosistema (descargas)
40En riesgo
Cómo se puntúa
| 31.8/80 | Descargas mensuales — 241 descargas/mes en pypi |
| 0/20 | Dependientes en el registro — no lo informa este ecosistema |
Datos de entrada utilizados
| packages | fairness_indicators, tensorboard_plugin_fairness_indicators |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 241 |
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?
80
Cómo se puntúa
| 36/54 | Factor bus — la mitad de los commits recae en 3 contribuyente(s) |
| 17.7/22.5 | Distribución de commits — el principal contribuyente firma el 21% de los commits |
| 13.5/13.5 | Amplitud de contribuyentes — 31 contribuyentes |
| 10/10 | OpenSSF Scorecard: Contributors — project has 7 contributing companies or organizations |
Datos de entrada utilizados
| bus_factor | 3 |
| contributors_sampled | 31 |
| top_contributor_share | 0,213 |
Capacidad de respuesta a issues y PR
69Moderado
Cómo se puntúa
| 27.5/46.8 | Resolución de issues — 59% de issues cerradas |
| 29.9/38.3 | Aceptación de PR — 274/350 PR decididos fusionados |
| 12/15 | OpenSSF Scorecard: Code-Review — Found 5/6 approved changesets -- score normalized to 8 |
Datos de entrada utilizados
| merged_prs | 274 |
| open_issues | 7 |
| closed_issues | 10 |
| issue_closed_ratio | 0,588 |
| closed_unmerged_prs | 76 |
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 — 21.576 seguidores de tensorflow |
| 25/25 | Trayectoria — 107 repos públicos, cuenta de ~10 años |
Datos de entrada utilizados
| followers | 21.576 |
| owner_type | Organization |
| is_verified | — |
| owner_login | tensorflow |
| public_repos | 107 |
| account_age_days | 3912 |
Mantenimiento de paquetes
100Excelente
Cómo se puntúa
| 25/25 | Publicado y resoluble — 2 paquete(s) en pypi |
| 35/35 | Recencia de publicación — última publicación hace 11 días |
| 20/20 | Historial de versiones — 34 versiones en el registro |
| 20/20 | No obsoleto — activo, ni obsoleto ni retirado |
Datos de entrada utilizados
| packages | fairness_indicators, tensorboard_plugin_fairness_indicators |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 11 |
Calidad de Ingeniería
¿Existen unas prácticas mínimas de ingeniería y documentación?
88
Prácticas de ingeniería
90Excelente
Cómo se puntúa
| 24/24 | Flujos de trabajo de CI — 4 flujo(s) de trabajo |
| 24/24 | Pruebas presentes |
| 16/16 | Configuración de linter |
| 9.6/9.6 | Hooks de pre-commit |
| 0/6.4 | .editorconfig |
| 16/20 | OpenSSF Scorecard: CI-Tests — 4 out of 5 merged PRs checked by a CI test -- score normalized to 8 |
Datos de entrada utilizados
| has_ci | sí |
| has_tests | sí |
| has_editorconfig | no |
| has_linter_config | sí |
| has_precommit_config | sí |
Documentación
85Excelente
Cómo se puntúa
| 30/30 | README |
| 25/25 | Directorio de documentación |
| 0/15 | Sitio de documentación / página del proyecto |
| 10/10 | Descripción del repositorio |
| 10/10 | Topics — 3 topics |
| 10/10 | Wiki |
Datos de entrada utilizados
| topics | tensorflow, fairness-ml, fairness-indicators |
| has_wiki | sí |
| homepage | — |
| 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?
52
Postura de seguridad
44En riesgo
Cómo se puntúa
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — branch protection not enabled on development/release branches |
| 2/2.5 | CI-Tests — 4 out of 5 merged PRs checked by a CI test -- score normalized to 8 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 6/7.5 | Code-Review — Found 5/6 approved changesets -- score normalized to 8 |
| 2.5/2.5 | Contributors — project has 7 contributing companies or organizations |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 0/7.5 | Dependency-Update-Tool — no update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | Licencia — license file detected |
| 0/7.5 | Maintained — 1 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0 |
| 5/5 | Packaging — packaging workflow detected |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 0/5 | SAST — SAST tool is not run on all commits -- score normalized to 0 |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — sin datos |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 7.5/7.5 | Vulnerabilities — 0 existing vulnerabilities detected |
Datos de entrada utilizados
| source | openssf_scorecard |
| checks_evaluated | 17 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 1 |
| scorecard_aggregate | 4,4 |
Excluidos de la puntuación (sin datos o no aplicable): signed_releases. Los pesos restantes se han renormalizado.
Avisos de dependencias
83Bueno
Cómo se puntúa
| 35/35 | Dependencias directas libres de avisos conocidos — ninguna dependencia directa tiene un aviso conocido |
| 8.4/25 | Dependencias indirectas libres de avisos conocidos — 2 afectados: cryptography 47.0.0 (high 7.5), httplib2 0.31.2 (high 7.5) |
| 40/40 | Sin avisos pendientes — ningún aviso lleva público más de 90 días |
Datos de entrada utilizados
| source | osv |
| advisories | 2 |
| affected_packages | 2 |
| assessed_packages | 162 |
| unassessed_packages | 0 |
| affected_by_severity | high 2 |
| direct_affected_packages | 0 |
Se cotejó el cierre de dependencias en tiempo de ejecución de pypi:fairness_indicators@0.52.0 —lo que arrastra la instalación del paquete publicado—: 162 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.
29
Contexto y guía para agentes
4Crítico
Cómo se puntúa
| 0/45 | Instrucciones para agentes — sin CLAUDE.md / AGENTS.md / reglas de editor |
| 0/15 | Documentación legible por máquinas (llms.txt) |
| 4.3/40 | Historial de commits legible — 8 de 100 commits humanos declaran su intención (asunto estructurado o cuerpo explicativo) |
Datos de entrada utilizados
| has_llms_txt | no |
| legible_history_share | 0,08 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Cómo se puntúa
| 0/18 | Arranque con un solo comando |
| 22/22 | Pruebas automatizadas |
| 11/11 | Configuración de lint / formato |
| 0/11 | Verificación estática de tipos |
| 0/10 | Entorno reproducible |
| 0/10 | Práctica demostrada con agentes — ningún commit con autoría de agente entre los últimos 100 |
| 0/8 | Mantenimiento automatizado — no se observan actualizaciones automáticas de dependencias |
| 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 | no |
| typed_language | no |
| bootstrap_files | — |
| has_devcontainer | no |
| has_linter_config | sí |
| typecheck_configs | — |
| agent_commit_share | 0 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
Legibilidad del código para modelos
55Moderado
Cómo se puntúa
| 0/45 | Código verificable por tipos — Python sin configuración de verificación de tipos |
| 55/55 | Tamaños de archivo manejables — 0/25 archivos fuente de más de 60 KB |
Datos de entrada utilizados
| primary_language | Python |
| largest_source_bytes | 11.671 |
| source_files_sampled | 25 |
| oversized_source_files | 0 |
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 — notebooks |
Datos de entrada utilizados
| example_dirs | notebooks |
| has_mcp_signal | no |
| api_schema_files | — |
Datos clave
358estrellas de GitHub
31contribuidores
11commits en los últimos 12 meses
11días desde el último push
27versiones publicadas
3factor bus
7issues abiertas
PyPIecosistemas de paquetes
Más detalle
Historial de estrellas y forks 358 ★ / 89 ⇿
358Estrellas
89Forks
26Versiones
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.
Mayor 0Menor 23Parche 3
Cada punto abarca 7 días.
OpenSSF Scorecard 4.4 / 10
4.4agregado
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 |
| 0 | Branch-Protection | branch protection not enabled on development/release branches |
| 8 | CI-Tests | 4 out of 5 merged PRs checked by a CI test -- score normalized to 8 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 8 | Code-Review | Found 5/6 approved changesets -- score normalized to 8 |
| 10 | Contributors | project has 7 contributing companies or organizations |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 0 | Dependency-Update-Tool | no update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 0 | Maintained | 1 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0 |
| 10 | Packaging | packaging workflow detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 0 | SAST | SAST tool is not run on all commits -- score normalized to 0 |
| 0 | Security-Policy | security policy file not detected |
| n/d | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 10 | Vulnerabilities | 0 existing vulnerabilities detected |
Todas las dependencias 14
Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 0 paquetes directos y 14 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.
| Registro | Paquete | Versión | Relación |
|---|---|---|---|
| PyPI | mkdocs | — | indirecta |
| PyPI | mkdocs-jupyter | — | indirecta |
| PyPI | mkdocs-material | — | indirecta |
| PyPI | numpy | — | indirecta |
| PyPI | protobuf | — | indirecta |
| PyPI | pytest | — | indirecta |
| PyPI | tensorboard | — | indirecta |
| PyPI | tensorflow | — | indirecta |
| PyPI | tensorflow-data-validation | — | indirecta |
| PyPI | tensorflow-hub | — | indirecta |
| PyPI | tensorflow-model-analysis | — | indirecta |
| PyPI | tf-keras | — | indirecta |
| PyPI | werkzeug | — | indirecta |
| PyPI | witwidget | — | indirecta |
Avisos de dependencias 2
Instalar pypi:fairness_indicators@0.52.0 arrastra 162 paquetes, directos y transitivos: 2 tienen avisos conocidos, de los cuales 0 son dependencias directas.
| Paquete | Versión | Relación | Gravedad | Avisos | Corregido en |
|---|---|---|---|---|---|
| cryptography | 47.0.0 | indirecta | alta | 1 | 48.0.1 |
| httplib2 | 0.31.2 | indirecta | alta | 1 | 0.32.0 |
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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{
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{
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]
},
{
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"notes": [],
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"inputs": {
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"direct_malicious_packages": 0,
"withdrawn_malicious_packages": 0,
"installable_malicious_packages": 0
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"components": [
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"details": [
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},
{
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"notes": [
{
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],
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"inputs": {
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{
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{
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{
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},
{
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{
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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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},
"warnings": [],
"report_type": "repository",
"generated_at": "2026-07-21T23:20:31.288245Z",
"schema_version": "0.26.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/t/tensorflow/fairness-indicators.svg",
"full_name": "tensorflow/fairness-indicators",
"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 v1.13.0, esquema v0.26.0 — metodología completa · wiki de métricas.
Cómo se sitúa un resultado dentro del registro general: estadísticas agregadas — PyPI.