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Software-GesundheitsberichtSchema 0.11.0 · Metriken 1.13.0 · 2026-07-15 02:55 UTC

pytorch / rl

A modular, primitive-first, python-first PyTorch library for Reinforcement Learning.

PythonMIT★ 3.491 Sterne⑂ 468 Forksseit Feb. 2022Auf GitHub ansehen ↗

pytorch/rl 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 (46/100). Zuletzt heute aktualisiert. Ein einzelner Mitwirkender trägt 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

pytorchOrganisation
13.385 Follower70 öffentliche Reposseit Aug. 2016

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

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlichtTags
PyPItorchrl0.13.3-34vor 0 Tagenreinforcement-learningpytorchrlmachine-learning

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
33.2/36Commit-Rhythmus — 48/52 Wochen mit Commits
18/18Commit-Volumen — 678 Commits im letzten Jahr
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10
Verwendete Eingangsdaten
commits_last_year678
human_commit_share
days_since_last_push0
active_weeks_last_year48
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 35 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 0 Tagen
27/27Release-Rhythmus — ein Release etwa alle 40,2 Tage
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Verwendete Eingangsdaten
releases_count35
latest_release_tagv0.13.3
releases_from_tagsnein
days_since_latest_release0
mean_days_between_releases40,2

Community & Verbreitung

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

90Exzellent · 18 % des Gesamtindex
Wie die Bewertung erfolgt
57.5/60Stars — 3.491 Stars
22.2/25Forks — 468 Forks
9.1/15Watcher — 44 Watcher
Verwendete Eingangsdaten
forks468
stars3.491
watchers44
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
Wie die Bewertung erfolgt
22.5/22.5README
22.5/22.5Lizenz — anerkannte Lizenz (MIT)
18/18CONTRIBUTING-Leitfaden
13.5/13.5Verhaltenskodex
0/7.2Issue-Vorlage
6.3/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingja
has_issue_templatenein
has_code_of_conductja
has_pull_request_templateja

Nachhaltigkeit & Governance

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

70Gut · 24 % des Gesamtindex
Wie die Bewertung erfolgt
9/54Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab
8.3/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 63 % der Commits
13.5/13.5Breite der Beitragenden — 100 Beitragende
10/10OpenSSF Scorecard: Contributors — project has 21 contributing companies or organizations
Verwendete Eingangsdaten
bus_factor1
contributors_sampled100
top_contributor_share0,631
Wie die Bewertung erfolgt
35.8/46.8Issue-Lösungsquote — 77 % der Issues geschlossen
33.8/38.3PR-Annahme — 2.684/3.035 entschiedene PRs gemergt
1.5/15OpenSSF Scorecard: Code-Review — Found 4/29 approved changesets -- score normalized to 1
Verwendete Eingangsdaten
merged_prs2.684
open_issues192
closed_issues629
issue_closed_ratio0,766
closed_unmerged_prs351
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
25/25Reichweite des Inhabers — 13.385 Follower von pytorch
25/25Kontohistorie — 70 öffentliche Repos, Kontoalter ca. 9 Jahre
Verwendete Eingangsdaten
followers13.385
owner_typeOrganization
is_verified
owner_loginpytorch
public_repos70
account_age_days3.622

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 0 Tagen
20/20Versionshistorie — 34 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagestorchrl
ecosystemspypi
any_deprecatednein
min_days_since_publish0

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

92Exzellent · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 28 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration
9.6/9.6Pre-Commit-Hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 14 out of 14 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

90Exzellent
Wie die Bewertung erfolgt
30/30README
25/25Dokumentationsverzeichnis
15/15Dokumentations-/Homepage-Site — https://pytorch.org/rl
10/10Repository-Beschreibung
10/10Topics — 13 Topics
0/10Wiki
Verwendete Eingangsdaten
topicsai, control, decision-making, distributed-computing, machine-learning, marl, model-based-reinforcement-learning, multi-agent-reinforcement-learning, pytorch, reinforcement-learning, rl, robotics, torch
has_wikinein
homepagehttps://pytorch.org/rl
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

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

46Gefährdet · 16 % des Gesamtindex

Sicherheitslage

46Gefährdet
Wie die Bewertung erfolgt
7.5/7.5Binary-Artifacts — no binaries found in the repo
0/7.5Branch-Protection — branch protection not enabled on development/release branches
2.5/2.5CI-Tests — 14 out of 14 merged PRs checked by a CI test -- score normalized to 10
0/2.5CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0.8/7.5Code-Review — Found 4/29 approved changesets -- score normalized to 1
2.5/2.5Contributors — project has 21 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 5 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
3/5SAST — SAST tool is not run on all commits -- score normalized to 6
0/5Security-Policy — security policy file not detected
0/7.5Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5Vulnerabilities — 16 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated18
scorecard_versionv5.5.0
checks_inconclusive0
scorecard_aggregate4,6

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.

71Gut · 0 % des Gesamtindex
Wie die Bewertung erfolgt
45/45Agentenanweisungen — AGENTS.md, CLAUDE.md
0/15Maschinenlesbare Doku (llms.txt)
0/40Lesbare Commit-Historie — keine Daten
Verwendete Eingangsdaten
has_llms_txtnein
legible_history_share
agent_instruction_filesAGENTS.md, CLAUDE.md
agent_instruction_max_bytes8.363
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, docs/Makefile
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration
11/11Statische Typprüfung — mypy.ini
0/10Reproduzierbare Umgebung
0/10Belegte Agentenpraxis — keine Daten
0/8Automatisierte Wartung — keine Daten
0/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfiles
has_dockerfilenein
typed_languagenein
bootstrap_filesMakefile, docs/Makefile
has_devcontainernein
has_linter_configja
typecheck_configsmypy.ini
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
27/45Typprüfbarer Code — Python mit Typprüfungs-Konfiguration (mypy.ini)
51/55Handhabbare Dateigrößen — 58/796 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes298.120
source_files_sampled796
oversized_source_files58
Wie die Bewertung erfolgt
0/40API-Schema (OpenAPI/GraphQL/proto)
0/20MCP-Server
40/40Lauffähige Beispiele — examples, recipes
Verwendete Eingangsdaten
example_dirsexamples, recipes
has_mcp_signalnein
api_schema_files

Eckdaten

3.491GitHub-Sterne
100Mitwirkende
678Commits, letzte 12 Monate
0Tage seit letztem Push
35Releases
1Bus-Faktor
192offene Issues
PyPIPaket-Ökosysteme

Weitere Details

OpenSSF Scorecard 4.6 / 10
4.6Gesamtwert

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 · 2026-07-15 02:52 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
10CI-Tests14 out of 14 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
1Code-ReviewFound 4/29 approved changesets -- score normalized to 1
10Contributorsproject has 21 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 5 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
6SASTSAST tool is not run on all commits -- score normalized to 6
0Security-Policysecurity policy file not detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
0Vulnerabilities16 existing vulnerabilities detected
Direkte Abhängigkeiten 7
RegistryPaketVersionsvorgabeManifest
PyPItorch>=2.1.0pyproject.toml
PyPIpyvers>=0.2.3pyproject.toml
PyPIhoptorch>=0.1.4pyproject.toml
PyPInumpypyproject.toml
PyPIpackagingpyproject.toml
PyPIcloudpicklepyproject.toml
PyPItensordict>=0.13.0,<0.14.0pyproject.toml
Alle Abhängigkeiten 103

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 9 direkte und 94 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
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JSON-Rohbericht maschinenlesbar
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                "key": "fuzzing",
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                "key": "vulnerabilities",
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                "key": "automated_maintenance",
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                "key": "openssf_scorecard_pinned_dependencies",
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            "notes": [],
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      }
    ],
    "metrics_version": "1.13.0"
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  "report_type": "repository",
  "generated_at": "2026-07-15T02:55:59.332161Z",
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  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/p/pytorch/rl.svg",
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}

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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.

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