Deep Learning for humans
keras-team/keras erreicht einen Gesundheitsindex von 86 von 100 und liegt damit im Bereich Exzellent. Am stärksten schneidet es bei Vitality (100/100) ab, am schwächsten bei AI Readiness (38/100). Zuletzt heute aktualisiert. 3 Mitwirkende tragen den Großteil der jüngsten Arbeit.
Metriken werden auf einer Skala von 1–100 in gewichtete Kategorien gruppiert. Der Gesamtwert beginnt als ihr Mittel; sobald öffentliche Evidenz die Richtlinie für Hochrisikojurisdiktionen auslöst, wird die Bewertung angepasst und erhält die Obergrenze 49 (Gefährdet). AI Readiness liegt außerhalb.
Jede Achse ist eine Kategorie. Die Form zählt mehr als der Durchschnitt — ein gesundes Projekt füllt die gesamte Fläche, während ein Profil aus Spitzen und Kratern bedeutet, dass Stärke in einer Dimension Risiken in einer anderen verdeckt.
Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.
| Registry | Paket | Version | Downloads / Monat | Versionen | Zuletzt veröffentlicht |
|---|---|---|---|---|---|
| PyPI | keras | 3.15.0 | 18.375.513 | 122 | vor 21 Tagen |
Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?
| 36/36 | Push-Aktualität — letzter Push vor 0 Tagen |
| 36/36 | Commit-Rhythmus — 52/52 Wochen mit Commits |
| 18/18 | Commit-Volumen — 935 Commits im letzten Jahr |
| 0/10 | OpenSSF Scorecard: Maintained — keine Daten |
| commits_last_year | 935 |
| human_commit_share | — |
| days_since_last_push | 0 |
| active_weeks_last_year | 52 |
| 27/27 | Liefert Releases aus — 91 Releases veröffentlicht |
| 36/36 | Release-Aktualität — letztes Release vor 19 Tagen |
| 27/27 | Release-Rhythmus — ein Release etwa alle 26,9 Tage |
| 0/10 | OpenSSF Scorecard: Signed-Releases — keine Daten |
| releases_count | 91 |
| latest_release_tag | v3.12.3 |
| releases_from_tags | nein |
| days_since_latest_release | 19 |
| mean_days_between_releases | 26,9 |
Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?
| 60/60 | Stars — 64.174 Stars |
| 25/25 | Forks — 19.739 Forks |
| 15/15 | Watcher — 1.856 Watcher |
| forks | 19.739 |
| stars | 64.174 |
| watchers | 1.856 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
| 22.5/22.5 | README |
| 22.5/22.5 | Lizenz — anerkannte Lizenz (Apache-2.0) |
| 18/18 | CONTRIBUTING-Leitfaden |
| 0/13.5 | Verhaltenskodex |
| 0/7.2 | Issue-Vorlage |
| 6.3/6.3 | PR-Vorlage |
| has_readme | ja |
| has_license | ja |
| has_contributing | ja |
| has_issue_template | nein |
| has_code_of_conduct | nein |
| has_pull_request_template | ja |
| 80/80 | Downloads pro Monat — 18.375.513 Downloads/Monat über pypi |
| 0/20 | Abhängige in der Registry — von diesem Ökosystem nicht ausgewiesen |
| packages | keras |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 18.375.513 |
Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?
| 36/54 | Bus-Faktor — 3 Beitragende decken die Hälfte aller Commits ab |
| 13.3/22.5 | Commit-Verteilung — wichtigste beitragende Person verfasste 41 % der Commits |
| 13.5/13.5 | Breite der Beitragenden — 100 Beitragende |
| 0/10 | OpenSSF Scorecard: Contributors — keine Daten |
| bus_factor | 3 |
| contributors_sampled | 100 |
| top_contributor_share | 0,408 |
| 46.3/46.8 | Issue-Lösungsquote — 99 % der Issues geschlossen |
| 20.6/38.3 | PR-Annahme — 5.116/9.488 entschiedene PRs gemergt |
| 0/15 | OpenSSF Scorecard: Code-Review — keine Daten |
| merged_prs | 5.116 |
| open_issues | 127 |
| closed_issues | 12.697 |
| issue_closed_ratio | 0,99 |
| closed_unmerged_prs | 4.372 |
| 30/30 | Organisatorische Trägerschaft — im Besitz einer Organisation |
| 0/20 | Verifizierte Domain |
| 24.8/25 | Reichweite des Inhabers — 2.785 Follower von keras-team |
| 21.8/25 | Kontohistorie — 21 öffentliche Repos, Kontoalter ca. 8 Jahre |
| followers | 2.785 |
| owner_type | Organization |
| is_verified | — |
| owner_login | keras-team |
| public_repos | 21 |
| account_age_days | 3.138 |
| 25/25 | Veröffentlicht & auflösbar — 1 Paket(e) auf pypi |
| 35/35 | Veröffentlichungsaktualität — letzte Veröffentlichung vor 21 Tagen |
| 20/20 | Versionshistorie — 122 veröffentlichte Versionen |
| 20/20 | Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen |
| packages | keras |
| ecosystems | pypi |
| any_deprecated | nein |
| min_days_since_publish | 21 |
Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?
| 24/24 | CI-Workflows — 10 Workflow(s) |
| 24/24 | Tests vorhanden |
| 16/16 | Linter-Konfiguration |
| 9.6/9.6 | Pre-Commit-Hooks |
| 0/6.4 | .editorconfig |
| 0/20 | OpenSSF Scorecard: CI-Tests — keine Daten |
| has_ci | ja |
| has_tests | ja |
| has_editorconfig | nein |
| has_linter_config | ja |
| has_precommit_config | ja |
| 30/30 | README |
| 0/25 | Dokumentationsverzeichnis |
| 15/15 | Dokumentations-/Homepage-Site — http://keras.io/ |
| 10/10 | Repository-Beschreibung |
| 10/10 | Topics — 8 Topics |
| 10/10 | Wiki |
| topics | deep-learning, tensorflow, neural-networks, machine-learning, data-science, python, jax, pytorch |
| has_wiki | ja |
| homepage | http://keras.io/ |
| has_readme | ja |
| has_docs_dir | nein |
| has_description | ja |
Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?
| 30/30 | Sicherheitsrichtlinie (SECURITY.md) |
| 25/25 | Dependabot-Konfiguration |
| 0/25 | Lockfiles für Abhängigkeiten — veröffentlichte Bibliothek — Lockfiles sind Sache der Anwendung, hier nicht erwartet |
| 0/20 | CodeQL-Workflow |
| 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 | nein |
| has_security_policy | ja |
| has_dependabot_config | ja |
Wie gut ist das Repository dafür ausgestattet, mit KI-Coding-Agenten entwickelt und gepflegt zu werden? Ein unabhängiges, experimentelles Badge — Gewicht 0,0, es wird eigenständig ausgewiesen und verändert den Gesamt-Gesundheitswert nicht.
| 0/45 | Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln |
| 0/15 | Maschinenlesbare Doku (llms.txt) |
| 0/40 | Lesbare Commit-Historie — keine Daten |
| has_llms_txt | nein |
| legible_history_share | — |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
| 0/18 | Bootstrap mit einem Befehl |
| 22/22 | Automatisierte Tests |
| 11/11 | Lint-/Format-Konfiguration |
| 0/11 | Statische Typprüfung |
| 10/10 | Reproduzierbare Umgebung — devcontainer |
| 0/10 | Belegte Agentenpraxis — keine Daten |
| 5/8 | Automatisierte Wartung — Abhängigkeits-Automatisierung konfiguriert, in den erfassten Commits nicht beobachtet |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — keine Daten |
| has_nix | nein |
| has_tests | ja |
| lockfiles | — |
| has_dockerfile | nein |
| typed_language | nein |
| bootstrap_files | — |
| has_devcontainer | ja |
| has_linter_config | ja |
| typecheck_configs | — |
| agent_commit_share | — |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
| 0/45 | Typprüfbarer Code — Python ohne Typprüfungs-Konfiguration |
| 53.3/55 | Handhabbare Dateigrößen — 30/975 Quelldateien über 60 KB |
| primary_language | Python |
| largest_source_bytes | 452.542 |
| source_files_sampled | 975 |
| oversized_source_files | 30 |
| 0/40 | API-Schema (OpenAPI/GraphQL/proto) |
| 0/20 | MCP-Server |
| 40/40 | Lauffähige Beispiele — examples |
| example_dirs | examples |
| has_mcp_signal | nein |
| api_schema_files | — |
| Registry | Paket | Versionsvorgabe | Manifest |
|---|---|---|---|
| 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 |
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 8 direkte und 33 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
| Registry | Paket | Version | Beziehung |
|---|---|---|---|
| PyPI | absl-py | — | direkt |
| PyPI | h5py | — | direkt |
| PyPI | ml-dtypes | — | direkt |
| PyPI | namex | — | direkt |
| PyPI | numpy | — | direkt |
| PyPI | optree | — | direkt |
| PyPI | packaging | — | direkt |
| PyPI | rich | — | direkt |
| PyPI | ai-edge-litert | — | indirekt |
| PyPI | build | — | indirekt |
| PyPI | coverage | — | indirekt |
| PyPI | dm-tree | — | indirekt |
| PyPI | flax | — | indirekt |
| PyPI | grain | — | indirekt |
| PyPI | jax | — | indirekt |
| PyPI | jax2onnx | — | indirekt |
| PyPI | litert-torch | — | indirekt |
| PyPI | onnxruntime | — | indirekt |
| PyPI | onnxscript | — | indirekt |
| PyPI | openvino | — | indirekt |
| PyPI | orbax-checkpoint | — | indirekt |
| PyPI | pandas | — | indirekt |
| PyPI | pillow | — | indirekt |
| PyPI | pre-commit | — | indirekt |
| PyPI | protobuf | — | indirekt |
| PyPI | pytest | — | indirekt |
| PyPI | pytest-cov | — | indirekt |
| PyPI | pytest-xdist | — | indirekt |
| PyPI | requests | — | indirekt |
| PyPI | ruff | — | indirekt |
| PyPI | scikit-learn | — | indirekt |
| PyPI | scipy | — | indirekt |
| PyPI | setuptools | — | indirekt |
| PyPI | tensorboard | — | indirekt |
| PyPI | tensorboard-plugin-profile | — | indirekt |
| PyPI | tensorflow | 2.20.0 | indirekt |
| PyPI | tensorflow-cpu | — | indirekt |
| PyPI | tensorflow-tpu | 2.19.1 | indirekt |
| PyPI | tf2onnx | — | indirekt |
| PyPI | torch | — | indirekt |
| PyPI | torch-xla | — | indirekt |
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"note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
"notes": [
{
"code": "jurisdiction_evidence_limits",
"params": {}
}
],
"value": 100,
"inputs": {
"meaning": "self-published location evidence; not nationality or citizenship",
"red_flag": false,
"exposures": [],
"policy_countries": [
"Russia",
"Iran",
"North Korea"
],
"review_only_matches": 0,
"assessed_self_published_locations": 7
},
"components": [
{
"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": [
"demonstrated_agent_practice"
]
}
},
{
"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",
"name": "Automated tests",
"detail": null,
"points": 22,
"status": "met",
"details": [],
"max_points": 22
},
{
"key": "lint_format_config",
"name": "Lint / format config",
"detail": null,
"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",
"name": "Reproducible environment",
"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": {
"primary_language": "Python",
"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",
"detail": "30/975 source files over 60KB",
"points": 53.3,
"status": "partial",
"details": [
{
"code": "oversized_source_files",
"params": {
"kb": 60,
"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"
}Bewertungen sind Signale, keine Garantien. Sie spiegeln öffentlich sichtbare Praxis auf GitHub wider — kein Code-Audit und keine Sicherheitsgarantie.
Fehlende Daten werden ausgeschlossen und die Gewichte neu normiert, nie als null bewertet. Die Methodik ist versioniert und offen: Metriken v1.13.0, Schema v0.11.0 — vollständige Methodik · Metriken-Wiki.
Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken — PyPI.