Deep Learning for humans
keras-team/keras tiene un índice de salud de 86 sobre 100, lo que lo sitúa en la banda Excelente. Su puntuación más alta es Vitality (100/100) y la más baja, AI Readiness (38/100). Se actualizó por última vez hoy. 3 personas concentran la mayor parte del trabajo reciente.
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.
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.
Este repositorio está respaldado por una organización: una custodia compartida y responsable que puede sobrevivir a cualquier mantenedor individual.
| Registro | Paquete | Versión | Descargas / mes | Versiones | Última publicación |
|---|---|---|---|---|---|
| PyPI | keras | 3.15.0 | 18.375.513 | 122 | hace 21 días |
¿Está vivo el proyecto: se escribe código y se publican versiones?
| 36/36 | Recencia de push — último push hace 0 días |
| 36/36 | Cadencia de commits — 52/52 semanas con commits |
| 18/18 | Volumen de commits — 935 commits en el último año |
| 0/10 | OpenSSF Scorecard: Maintained — sin datos |
| commits_last_year | 935 |
| human_commit_share | — |
| days_since_last_push | 0 |
| active_weeks_last_year | 52 |
| 27/27 | Publica versiones — 91 versiones publicadas |
| 36/36 | Recencia de las versiones — última versión hace 19 días |
| 27/27 | Cadencia de publicación — una versión cada ~26,9 días |
| 0/10 | OpenSSF Scorecard: Signed-Releases — sin datos |
| releases_count | 91 |
| latest_release_tag | v3.12.3 |
| releases_from_tags | no |
| days_since_latest_release | 19 |
| mean_days_between_releases | 26,9 |
¿Tiene el proyecto usuarios, descargas, atención y unas condiciones acogedoras para quienes contribuyen?
| 60/60 | Estrellas — 64.174 estrellas |
| 25/25 | Forks — 19.739 forks |
| 15/15 | Observadores — 1856 observadores |
| forks | 19.739 |
| stars | 64.174 |
| watchers | 1856 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
| 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 |
| 6.3/6.3 | Plantilla de PR |
| has_readme | sí |
| has_license | sí |
| has_contributing | sí |
| has_issue_template | no |
| has_code_of_conduct | no |
| has_pull_request_template | sí |
| 80/80 | Descargas mensuales — 18.375.513 descargas/mes en pypi |
| 0/20 | Dependientes en el registro — no lo informa este ecosistema |
| packages | keras |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 18.375.513 |
¿Sobrevivirá el proyecto a sus personas: factor bus, capacidad de respuesta, quién lo respalda y mantenimiento del paquete?
| 36/54 | Factor bus — la mitad de los commits recae en 3 contribuyente(s) |
| 13.3/22.5 | Distribución de commits — el principal contribuyente firma el 41% de los commits |
| 13.5/13.5 | Amplitud de contribuyentes — 100 contribuyentes |
| 0/10 | OpenSSF Scorecard: Contributors — sin datos |
| bus_factor | 3 |
| contributors_sampled | 100 |
| top_contributor_share | 0,408 |
| 46.3/46.8 | Resolución de issues — 99% de issues cerradas |
| 20.6/38.3 | Aceptación de PR — 5116/9488 PR decididos fusionados |
| 0/15 | OpenSSF Scorecard: Code-Review — sin datos |
| merged_prs | 5116 |
| open_issues | 127 |
| closed_issues | 12.697 |
| issue_closed_ratio | 0,99 |
| closed_unmerged_prs | 4372 |
| 30/30 | Respaldo de la propiedad — propiedad de una organización |
| 0/20 | Dominio verificado |
| 24.8/25 | Alcance del propietario — 2785 seguidores de keras-team |
| 21.8/25 | Trayectoria — 21 repos públicos, cuenta de ~8 años |
| followers | 2785 |
| owner_type | Organization |
| is_verified | — |
| owner_login | keras-team |
| public_repos | 21 |
| account_age_days | 3138 |
| 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 — 122 versiones en el registro |
| 20/20 | No obsoleto — activo, ni obsoleto ni retirado |
| packages | keras |
| ecosystems | pypi |
| any_deprecated | no |
| min_days_since_publish | 21 |
¿Existen unas prácticas mínimas de ingeniería y documentación?
| 24/24 | Flujos de trabajo de CI — 10 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 |
| 0/20 | OpenSSF Scorecard: CI-Tests — sin datos |
| has_ci | sí |
| has_tests | sí |
| has_editorconfig | no |
| has_linter_config | sí |
| has_precommit_config | sí |
| 30/30 | README |
| 0/25 | Directorio de documentación |
| 15/15 | Sitio de documentación / página del proyecto — http://keras.io/ |
| 10/10 | Descripción del repositorio |
| 10/10 | Topics — 8 topics |
| 10/10 | Wiki |
| topics | deep-learning, tensorflow, neural-networks, machine-learning, data-science, python, jax, pytorch |
| has_wiki | sí |
| homepage | http://keras.io/ |
| has_readme | sí |
| has_docs_dir | no |
| has_description | sí |
¿Son sólidas las prácticas visibles de seguridad y de cadena de suministro, sin exposición jurisdiccional de alto riesgo sin resolver?
| 30/30 | Política de seguridad (SECURITY.md) |
| 25/25 | Configuración de Dependabot |
| 0/25 | Lockfiles de dependencias — biblioteca publicada — los lockfiles son cosa de las aplicaciones, no se esperan aquí |
| 0/20 | Flujo de trabajo de CodeQL |
| source | file_signals |
| lockfiles | — |
| manifests | pyproject.toml, requirements-common.txt, requirements-jax-cuda.txt, requirements-jax-tpu.txt, requirements-tensorflow-cuda.txt, requirements-tensorflow-tpu.txt, requirements-torch-cuda.txt, requirements.txt |
| has_codeql_workflow | no |
| has_security_policy | sí |
| has_dependabot_config | sí |
¿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.
| 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 |
| has_llms_txt | no |
| legible_history_share | — |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
| 0/18 | Arranque con un solo comando |
| 22/22 | Pruebas automatizadas |
| 11/11 | Configuración de lint / formato |
| 0/11 | Verificación estática de tipos |
| 10/10 | Entorno reproducible — devcontainer |
| 0/10 | Práctica demostrada con agentes — sin datos |
| 5/8 | Mantenimiento automatizado — automatización de dependencias configurada, no observada en los commits muestreados |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — sin datos |
| has_nix | no |
| has_tests | sí |
| lockfiles | — |
| has_dockerfile | no |
| typed_language | no |
| bootstrap_files | — |
| has_devcontainer | sí |
| has_linter_config | sí |
| typecheck_configs | — |
| agent_commit_share | — |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
| 0/45 | Código verificable por tipos — Python sin configuración de verificación de tipos |
| 53.3/55 | Tamaños de archivo manejables — 30/975 archivos fuente de más de 60 KB |
| primary_language | Python |
| largest_source_bytes | 452.542 |
| source_files_sampled | 975 |
| oversized_source_files | 30 |
| 0/40 | Esquema de API (OpenAPI/GraphQL/proto) |
| 0/20 | Servidor MCP |
| 40/40 | Ejemplos ejecutables — examples |
| example_dirs | examples |
| has_mcp_signal | no |
| api_schema_files | — |
| Registro | Paquete | Restricción de versión | Manifiesto |
|---|---|---|---|
| PyPI | absl-py | — | pyproject.toml |
| PyPI | numpy | — | pyproject.toml |
| PyPI | rich | — | pyproject.toml |
| PyPI | namex | — | pyproject.toml |
| PyPI | h5py | — | pyproject.toml |
| PyPI | optree | — | pyproject.toml |
| PyPI | ml-dtypes | — | pyproject.toml |
| PyPI | packaging | — | pyproject.toml |
Conjunto completo de dependencias resueltas según el grafo de dependencias de GitHub: 8 paquetes directos y 33 indirectos (transitivos). El cierre transitivo es completo cuando el repositorio incluye un lockfile.
| Registro | Paquete | Versión | Relación |
|---|---|---|---|
| PyPI | absl-py | — | directa |
| PyPI | h5py | — | directa |
| PyPI | ml-dtypes | — | directa |
| PyPI | namex | — | directa |
| PyPI | numpy | — | directa |
| PyPI | optree | — | directa |
| PyPI | packaging | — | directa |
| PyPI | rich | — | directa |
| PyPI | ai-edge-litert | — | indirecta |
| PyPI | build | — | indirecta |
| PyPI | coverage | — | indirecta |
| PyPI | dm-tree | — | indirecta |
| PyPI | flax | — | indirecta |
| PyPI | grain | — | indirecta |
| PyPI | jax | — | indirecta |
| PyPI | jax2onnx | — | indirecta |
| PyPI | litert-torch | — | indirecta |
| PyPI | onnxruntime | — | indirecta |
| PyPI | onnxscript | — | indirecta |
| PyPI | openvino | — | indirecta |
| PyPI | orbax-checkpoint | — | indirecta |
| PyPI | pandas | — | indirecta |
| PyPI | pillow | — | indirecta |
| PyPI | pre-commit | — | indirecta |
| PyPI | protobuf | — | indirecta |
| PyPI | pytest | — | indirecta |
| PyPI | pytest-cov | — | indirecta |
| PyPI | pytest-xdist | — | indirecta |
| PyPI | requests | — | indirecta |
| PyPI | ruff | — | indirecta |
| PyPI | scikit-learn | — | indirecta |
| PyPI | scipy | — | indirecta |
| PyPI | setuptools | — | indirecta |
| PyPI | tensorboard | — | indirecta |
| PyPI | tensorboard-plugin-profile | — | indirecta |
| PyPI | tensorflow | 2.20.0 | indirecta |
| PyPI | tensorflow-cpu | — | indirecta |
| PyPI | tensorflow-tpu | 2.19.1 | indirecta |
| PyPI | tf2onnx | — | indirecta |
| PyPI | torch | — | indirecta |
| PyPI | torch-xla | — | indirecta |
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"key": "policy_exposure_multiplier",
"name": "Policy exposure multiplier",
"detail": "no confirmed policy-scope location match",
"points": 100,
"status": "met",
"details": [
{
"code": "jurisdiction_no_match",
"params": {}
}
],
"max_points": 100
}
]
}
],
"description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
},
{
"key": "ai_readiness",
"band": "at_risk",
"name": "AI Readiness",
"value": 38,
"weight": 0,
"metrics": [
{
"key": "ai_agent_context",
"band": "critical",
"name": "Agent context & guidance",
"note": "Excluded from scoring (no data or not applicable): Legible commit history. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
"legible_commit_history"
]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 1,
"inputs": {
"has_llms_txt": false,
"legible_history_share": null,
"agent_instruction_files": [],
"agent_instruction_max_bytes": null
},
"components": [
{
"key": "agent_instructions",
"name": "Agent instructions",
"detail": "no CLAUDE.md / AGENTS.md / editor rules",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_agent_instructions",
"params": {}
}
],
"max_points": 45
},
{
"key": "machine_readable_docs_llms_txt",
"name": "Machine-readable docs (llms.txt)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 15
},
{
"key": "legible_commit_history",
"name": "Legible commit history",
"detail": "no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 40
}
]
},
{
"key": "ai_verify_loop",
"band": "moderate",
"name": "Verify loop (build / test / typecheck)",
"note": "Excluded from scoring (no data or not applicable): Demonstrated agent practice. Remaining weights renormalized.",
"notes": [
{
"code": "excluded_no_data",
"params": {
"components": [
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]
}
},
{
"code": "weights_renormalized",
"params": {}
}
],
"value": 60,
"inputs": {
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"has_tests": true,
"lockfiles": [],
"has_dockerfile": false,
"typed_language": false,
"bootstrap_files": [],
"has_devcontainer": true,
"has_linter_config": true,
"typecheck_configs": [],
"agent_commit_share": null,
"toolchain_manifests": [],
"dependency_bot_commit_share": 0
},
"components": [
{
"key": "one_command_bootstrap",
"name": "One-command bootstrap",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 18
},
{
"key": "automated_tests",
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"detail": null,
"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
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"points": 11,
"status": "met",
"details": [],
"max_points": 11
},
{
"key": "static_type_checking",
"name": "Static type checking",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 11
},
{
"key": "reproducible_environment",
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"detail": "devcontainer",
"points": 10,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "devcontainer"
}
}
],
"max_points": 10
},
{
"key": "demonstrated_agent_practice",
"name": "Demonstrated agent practice",
"detail": "no data",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 10
},
{
"key": "automated_maintenance",
"name": "Automated maintenance",
"detail": "dependency automation configured, none observed in the sampled commits",
"points": 5,
"status": "partial",
"details": [
{
"code": "dependency_bot_config_only",
"params": {}
}
],
"max_points": 8
},
{
"key": "openssf_scorecard_pinned_dependencies",
"name": "OpenSSF Scorecard: Pinned-Dependencies",
"detail": "OpenSSF Scorecard unavailable",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 10
}
]
},
{
"key": "ai_code_legibility",
"band": "moderate",
"name": "Code legibility for models",
"note": null,
"notes": [],
"value": 53,
"inputs": {
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"largest_source_bytes": 452542,
"source_files_sampled": 975,
"oversized_source_files": 30
},
"components": [
{
"key": "type_checkable_code",
"name": "Type-checkable code",
"detail": "Python without a type-check config",
"points": 0,
"status": "missed",
"details": [
{
"code": "no_typecheck_config_language",
"params": {
"language": "Python"
}
}
],
"max_points": 45
},
{
"key": "manageable_file_sizes",
"name": "Manageable file sizes",
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"points": 53.3,
"status": "partial",
"details": [
{
"code": "oversized_source_files",
"params": {
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"sampled": 975,
"oversized": 30
}
}
],
"max_points": 55
}
]
},
{
"key": "ai_interfaces",
"band": "at_risk",
"name": "Machine-readable interfaces",
"note": null,
"notes": [],
"value": 40,
"inputs": {
"example_dirs": [
"examples"
],
"has_mcp_signal": false,
"api_schema_files": []
},
"components": [
{
"key": "api_schema_openapi_graphql_proto",
"name": "API schema (OpenAPI/GraphQL/proto)",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 40
},
{
"key": "mcp_server",
"name": "MCP server",
"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 20
},
{
"key": "runnable_examples",
"name": "Runnable examples",
"detail": "examples",
"points": 40,
"status": "met",
"details": [
{
"code": "file_list",
"params": {
"files": "examples"
}
}
],
"max_points": 40
}
]
}
],
"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."
}
],
"metrics_version": "1.13.0"
},
"warnings": [
"OpenSSF Scorecard timed out after 240s; skipping Scorecard checks"
],
"report_type": "repository",
"generated_at": "2026-07-16T05:02:51.669843Z",
"schema_version": "0.11.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/k/keras-team/keras.svg",
"full_name": "keras-team/keras",
"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 v0.11.0 — metodología completa · wiki de métricas.
Cómo se sitúa un resultado dentro del registro general: estadísticas agregadas — PyPI.