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Software-GesundheitsberichtSchema 0.12.0 · Metriken 1.13.0 · 2026-07-18 13:34 UTC

google-deepmind / optax

Optax is a gradient processing and optimization library for JAX.

PythonApache-2.0★ 2.301 Sterne⑂ 345 Forksseit Juni 2020Auf GitHub ansehen ↗

google-deepmind/optax erreicht einen Gesundheitsindex von 85 von 100 und liegt damit im Bereich Exzellent. Am stärksten schneidet es bei Engineering Quality (96/100) ab, am schwächsten bei AI Readiness (40/100). Zuletzt vor 3 Tagen aktualisiert. 10 Mitwirkende tragen den Großteil der jüngsten Arbeit.

85
gesamt / 100
Exzellent

Software-Gesundheitsindex

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.

85
Exzellent85-100Vorbildlich; erfüllt im Wesentlichen alle geprüften Kriterien
Gut70-84Gesund; geringfügige Lücken
Mittel50-69Akzeptabel mit deutlichen Lücken; Überprüfung empfohlen
Gefährdet30-49Erhebliche Schwächen; eine Übernahme erfordert Vorsicht
Kritisch1-29Schwerwiegende Probleme (aufgegeben, nur ein Maintainer, keine Hygiene)
VitalitätCommunity &VerbreitungNachhaltigkeit &GovernanceEngineering-QualitätSicherheitAI Readiness

Bewertungsprofil

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.

Eigentümerschaft

Google DeepMindOrganisation
25.589 Follower397 öffentliche Reposseit Aug. 2014

Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlichtTags
PyPIoptax0.2.8-26vor 119 Tagenpythonmachine-learningreinforcement-learning

Metriken nach Kategorie

Vitalität

Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?

92Exzellent · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 3 Tagen
34.6/36Commit-Rhythmus — 50/52 Wochen mit Commits
18/18Commit-Volumen — 282 Commits im letzten Jahr
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
Verwendete Eingangsdaten
commits_last_year282
human_commit_share
days_since_last_push3
active_weeks_last_year50
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 24 Releases veröffentlicht
27/36Release-Aktualität — letztes Release vor 119 Tagen
19.8/27Release-Rhythmus — ein Release etwa alle 86,2 Tage
0/10OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count24
latest_release_tagv0.2.8
releases_from_tagsnein
days_since_latest_release119
mean_days_between_releases86,2
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): OpenSSF Scorecard: Signed-Releases. Die verbleibenden Gewichte wurden renormalisiert.

Community & Verbreitung

Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?

77Gut · 18 % des Gesamtindex
Wie die Bewertung erfolgt
54.5/60Stars — 2.301 Stars
21.1/25Forks — 345 Forks
8.4/15Watcher — 33 Watcher
Verwendete Eingangsdaten
forks345
stars2.301
watchers33
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (Apache-2.0)
18/18CONTRIBUTING-Leitfaden
0/13.5Verhaltenskodex
0/7.2Issue-Vorlage
0/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingja
has_issue_templatenein
has_code_of_conductnein
has_pull_request_templatenein

Nachhaltigkeit & Governance

Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?

88Exzellent · 24 % des Gesamtindex
Wie die Bewertung erfolgt
54/54Bus-Faktor — 10 Beitragende decken die Hälfte aller Commits ab
20.5/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 9 % der Commits
13.5/13.5Breite der Beitragenden — 100 Beitragende
10/10OpenSSF Scorecard: Contributors — project has 40 contributing companies or organizations
Verwendete Eingangsdaten
bus_factor10
contributors_sampled100
top_contributor_share0,088
Wie die Bewertung erfolgt
43.2/46.8Issue-Lösungsquote — 92 % der Issues geschlossen
24.2/38.3PR-Annahme — 772/1.219 entschiedene PRs gemergt
7.5/15OpenSSF Scorecard: Code-Review — Found 8/16 approved changesets -- score normalized to 5
Verwendete Eingangsdaten
merged_prs772
open_issues28
closed_issues335
issue_closed_ratio0,923
closed_unmerged_prs447
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
25/25Reichweite des Inhabers — 25.589 Follower von google-deepmind
25/25Kontohistorie — 397 öffentliche Repos, Kontoalter ca. 11 Jahre
Verwendete Eingangsdaten
followers25.589
owner_typeOrganization
is_verified
owner_logingoogle-deepmind
public_repos397
account_age_days4.340

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 119 Tagen
20/20Versionshistorie — 26 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagesoptax
ecosystemspypi
any_deprecatednein
min_days_since_publish119

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

96Exzellent · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 2 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration
9.6/9.6Pre-Commit-Hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 15 out of 15 merged PRs checked by a CI test -- score normalized to 10
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfignein
has_linter_configja
has_precommit_configja

Dokumentation

100Exzellent
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://optax.readthedocs.io
10/10Repository-Beschreibung
10/10Topics — 2 Topics
10/10Wiki
Verwendete Eingangsdaten
topicsmachine-learning, optimization
has_wikija
homepagehttps://optax.readthedocs.io
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?

67Mittel · 16 % des Gesamtindex
Wie die Bewertung erfolgt
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — keine Daten
2.5/2.5CI-Tests — 15 out of 15 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — keine Daten
3.8/7.5Code-Review — Found 8/16 approved changesets -- score normalized to 5
2.5/2.5Contributors — project has 40 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
2.5/2.5Lizenz — license file detected
7.5/7.5Maintained — 30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
1/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 2
1/5SAST — SAST tool is not run on all commits -- score normalized to 2
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — keine Daten
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
7.5/7.5Vulnerabilities — 0 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated15
scorecard_versionv5.5.0
checks_inconclusive3
scorecard_aggregate6,7
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection, cii_best_practices, signed_releases. Die verbleibenden Gewichte wurden renormalisiert.

AI Readiness

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.

40Gefährdet · 0 % des Gesamtindex
Wie die Bewertung erfolgt
0/45Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln
0/15Maschinenlesbare Doku (llms.txt)
0/40Lesbare Commit-Historie — keine Daten
Verwendete Eingangsdaten
has_llms_txtnein
legible_history_share
agent_instruction_files
agent_instruction_max_bytes
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lesbare Commit-Historie. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
18/18Bootstrap mit einem Befehl — docs/Makefile
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration
0/11Statische Typprüfung
0/10Reproduzierbare Umgebung
0/10Belegte Agentenpraxis — keine Daten
0/8Automatisierte Wartung — keine Daten
2/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 2
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfiles
has_dockerfilenein
typed_languagenein
bootstrap_filesdocs/Makefile
has_devcontainernein
has_linter_configja
typecheck_configs
agent_commit_share
toolchain_manifests
dependency_bot_commit_share
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Belegte Agentenpraxis, Automatisierte Wartung. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
0/45Typprüfbarer Code — Python ohne Typprüfungs-Konfiguration
53.8/55Handhabbare Dateigrößen — 3/135 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes112.954
source_files_sampled135
oversized_source_files3
Wie die Bewertung erfolgt
0/40API-Schema (OpenAPI/GraphQL/proto)
0/20MCP-Server
40/40Lauffähige Beispiele — examples, notebooks
Verwendete Eingangsdaten
example_dirsexamples, notebooks
has_mcp_signalnein
api_schema_files

Eckdaten

2.301GitHub-Sterne
100Mitwirkende
282Commits, letzte 12 Monate
3Tage seit letztem Push
24Releases
10Bus-Faktor
28offene Issues
PyPIPaket-Ökosysteme

Weitere Details

OpenSSF Scorecard 6.7 / 10
6.7Gesamtwert

Unabhängige, werkzeugneutrale Sicherheitsbewertung durch das quelloffene OpenSSF Scorecard. Jede Prüfung honoriert eine Sicherheits-Praxis, nicht das Werkzeug eines bestimmten Anbieters. Prüfungen, die Scorecard nicht ermitteln konnte, sind mit k. A. markiert und vom Sicherheitswert ausgeschlossen (nie als null gezählt).Scorecard v5.5.0 · 2026-07-18 13:33 UTC

10Binary-Artifactsno binaries found in the repo
k. A.Branch-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-Tests15 out of 15 merged PRs checked by a CI test -- score normalized to 10
k. A.CII-Best-Practicesinternal error: error during json parsing: error during json.Unmarshal: invalid character '<' looking for beginning of value
5Code-ReviewFound 8/16 approved changesets -- score normalized to 5
10Contributorsproject has 40 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 4 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
2Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 2
2SASTSAST tool is not run on all commits -- score normalized to 2
0Security-Policysecurity policy file not detected
k. A.Signed-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
10Vulnerabilities0 existing vulnerabilities detected
Direkte Abhängigkeiten 4
RegistryPaketVersionsvorgabeManifest
PyPIabsl-py>=0.7.1pyproject.toml
PyPIjax>=0.5.3pyproject.toml
PyPIjaxlib>=0.5.3pyproject.toml
PyPInumpy>=1.18.0pyproject.toml
Alle Abhängigkeiten 14

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 4 direkte und 10 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
PyPIabsl-pydirekt
PyPIjaxdirekt
PyPIjaxlibdirekt
PyPInumpydirekt
PyPIflaxindirekt
PyPIflit-coreindirekt
PyPIipythonindirekt
PyPImatplotlibindirekt
PyPImyst-nbindirekt
PyPIscipyindirekt
PyPIsphinxindirekt
PyPIsphinx-book-themeindirekt
PyPIsphinx-collectionsindirekt
PyPIsphinx-galleryindirekt
JSON-Rohbericht maschinenlesbar
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        {
          "type": "User",
          "login": "mkunesch",
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                "key": "owner_reach",
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                "key": "track_record",
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            "key": "package_maintenance",
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            "note": null,
            "notes": [],
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            "inputs": {
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              "ecosystems": "pypi",
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                "key": "publish_recency",
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}

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