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Software-GesundheitsberichtSchema 0.12.0 · Metriken 1.13.0 · 2026-07-18 01:37 UTC

NVIDIA-NeMo / Gym

Evaluate and improve models and agents using environments

Python · MDXApache-2.0★ 1.055 Sterne⑂ 228 Forksseit Aug. 2025Auf GitHub ansehen ↗

NVIDIA-NeMo/Gym erreicht einen Gesundheitsindex von 79 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Vitality (94/100) ab, am schwächsten bei Security (40/100). Zuletzt heute aktualisiert. 6 Mitwirkende tragen den Großteil der jüngsten Arbeit.

79
gesamt / 100
Gut

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.

79
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

NVIDIA-NeMoOrganisation
1.350 Follower26 öffentliche Reposseit Mai 2025

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

Paket-Ökosysteme

Metriken nach Kategorie

Vitalität

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

94Exzellent · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 0 Tagen
31.8/36Commit-Rhythmus — 46/52 Wochen mit Commits
18/18Commit-Volumen — 801 Commits im letzten Jahr
0/10OpenSSF Scorecard: Maintained — keine Daten
Verwendete Eingangsdaten
commits_last_year801
human_commit_share
days_since_last_push0
active_weeks_last_year46
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 6 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 15 Tagen
19.8/27Release-Rhythmus — ein Release etwa alle 46 Tage
0/10OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count6
latest_release_tagv0.4.0
releases_from_tagsnein
days_since_latest_release15
mean_days_between_releases46

Community & Verbreitung

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

83Gut · 18 % des Gesamtindex
Wie die Bewertung erfolgt
49/60Stars — 1.055 Stars
19.6/25Forks — 228 Forks
5/15Watcher — 9 Watcher
Verwendete Eingangsdaten
forks228
stars1.055
watchers9
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
13.5/13.5Verhaltenskodex
0/7.2Issue-Vorlage
0/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingja
has_issue_templatenein
has_code_of_conductja
has_pull_request_templatenein
Wie die Bewertung erfolgt
74.8/80Downloads pro Monat — 406.438 Downloads/Monat über pypi
0/20Abhängige in der Registry — von diesem Ökosystem nicht ausgewiesen
Verwendete Eingangsdaten
packagesnemo-gym
dependents
ecosystemspypi
total_downloads
monthly_downloads406.438
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Abhängige in der Registry. Die verbleibenden Gewichte wurden renormalisiert.

Nachhaltigkeit & Governance

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

78Gut · 24 % des Gesamtindex
Wie die Bewertung erfolgt
48.6/54Bus-Faktor — 6 Beitragende decken die Hälfte aller Commits ab
18.7/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 17 % der Commits
13.5/13.5Breite der Beitragenden — 100 Beitragende
0/10OpenSSF Scorecard: Contributors — keine Daten
Verwendete Eingangsdaten
bus_factor6
contributors_sampled100
top_contributor_share0,168
Wie die Bewertung erfolgt
22.7/46.8Issue-Lösungsquote — 48 % der Issues geschlossen
27.1/38.3PR-Annahme — 872/1.233 entschiedene PRs gemergt
0/15OpenSSF Scorecard: Code-Review — keine Daten
Verwendete Eingangsdaten
merged_prs872
open_issues341
closed_issues321
issue_closed_ratio0,485
closed_unmerged_prs361
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
22.5/25Reichweite des Inhabers — 1.350 Follower von NVIDIA-NeMo
12.7/25Kontohistorie — 26 öffentliche Repos, Kontoalter ca. 1 Jahre
Verwendete Eingangsdaten
followers1.350
owner_typeOrganization
is_verified
owner_loginNVIDIA-NeMo
public_repos26
account_age_days416

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 15 Tagen
20/20Versionshistorie — 5 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagesnemo-gym
ecosystemspypi
any_deprecatednein
min_days_since_publish15

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

91Exzellent · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 18 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration
9.6/9.6Pre-Commit-Hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests — keine Daten
Verwendete Eingangsdaten
has_cija
has_testsja
has_editorconfignein
has_linter_configja
has_precommit_configja

Dokumentation

90Exzellent
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://docs.nvidia.com/nemo/gym/main/about/
10/10Repository-Beschreibung
10/10Topics — 10 Topics
0/10Wiki
Verwendete Eingangsdaten
topicsreinforcement-learning, reinforcement-learning-environments, rl-environment, rl-training, gym, agents, benchmarks, environments, evaluation, llm
has_wikinein
homepagehttps://docs.nvidia.com/nemo/gym/main/about/
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

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

40Gefährdet · 16 % des Gesamtindex

Sicherheitslage

40Gefährdet
Wie die Bewertung erfolgt
30/30Sicherheitsrichtlinie (SECURITY.md)
0/25Dependabot-Konfiguration
0/25Lockfiles für Abhängigkeiten — veröffentlichte Bibliothek — Lockfiles sind Sache der Anwendung, hier nicht erwartet
0/20CodeQL-Workflow
Verwendete Eingangsdaten
sourcefile_signals
lockfilesuv.lock
manifestsfern/package.json, pyproject.toml
has_codeql_workflownein
has_security_policyja
has_dependabot_confignein
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lockfiles für Abhängigkeiten. 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.

74Gut · 0 % des Gesamtindex
Wie die Bewertung erfolgt
45/45Agentenanweisungen — CLAUDE.md, resources_servers/terminal_multi_harness/docs/AGENTS.md
0/15Maschinenlesbare Doku (llms.txt)
0/40Lesbare Commit-Historie — keine Daten
Verwendete Eingangsdaten
has_llms_txtnein
legible_history_share
agent_instruction_filesCLAUDE.md, resources_servers/terminal_multi_harness/docs/AGENTS.md
agent_instruction_max_bytes8.267
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 — Makefile
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration
0/11Statische Typprüfung
10/10Reproduzierbare Umgebung — Dockerfile, lockfile
0/10Belegte Agentenpraxis — keine Daten
0/8Automatisierte Wartung — keine Daten
0/10OpenSSF Scorecard: Pinned-Dependencies — keine Daten
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfilesuv.lock
has_dockerfileja
typed_languagenein
bootstrap_filesMakefile
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
54.4/55Handhabbare Dateigrößen — 13/1.121 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes166.988
source_files_sampled1.121
oversized_source_files13
Wie die Bewertung erfolgt
0/40API-Schema (OpenAPI/GraphQL/proto)
20/20MCP-Server
40/40Lauffähige Beispiele — example, notebooks
Verwendete Eingangsdaten
example_dirsexample, notebooks
has_mcp_signalja
api_schema_files

Eckdaten

1.055GitHub-Sterne
100Mitwirkende
801Commits, letzte 12 Monate
0Tage seit letztem Push
6Releases
6Bus-Faktor
341offene Issues
npm, PyPIPaket-Ökosysteme

Warnungen zur Datenerhebung

  • GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository
  • OpenSSF Scorecard timed out after 240s; skipping Scorecard checks

Weitere Details

Direkte Abhängigkeiten 29
RegistryPaketVersionsvorgabeManifest
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PyPIdevtoolspyproject.toml
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PyPIrichpyproject.toml
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Alle Abhängigkeiten nicht erhoben

Der aufgelöste Abhängigkeitssatz konnte für diesen Bericht nicht erhoben werden: GitHub dependency-graph SBOM unavailable (404); the dependency graph may be disabled for this repository

JSON-Rohbericht maschinenlesbar
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