shader-slang/slangpy erreicht einen Gesundheitsindex von 91 von 100 und liegt damit im Bereich Exzellent. Am stärksten schneidet es bei Vitality (93/100) ab, am schwächsten bei Security (58/100). Zuletzt heute aktualisiert. 2 Mitwirkende tragen den Großteil der jüngsten Arbeit.
91
gesamt / 100
Exzellent
Software-Gesundheitsindex
Metriken werden auf einer standardisierten Skala von 1–100 in gewichtete Kategorien gruppiert. Der Gesamtwert beginnt als ihr gewichtetes Mittel, kalibriert auf die Verteilung des öffentlichen Registers, sodass die Stufen Perzentilbedeutung tragen; sobald öffentliche Evidenz die Richtlinie für Hochrisikojurisdiktionen auslöst, wird die Bewertung angepasst und erhält die Obergrenze Gefährdet von 34.
91
Außergewöhnlich93-100Die Spitzengruppe des Registers (≈ obere 5 %); erfüllt im Wesentlichen alle geprüften Kriterien
Gut65-79Gesund; Lücken sind begrenzt und beherrschbar
Mittel50-64Akzeptabel mit deutlichen Lücken; Überprüfung empfohlen
Schwach35-49Wesentliche Schwächen in mehreren Bereichen
Gefährdet20-34Erhebliche Schwächen; eine Übernahme erfordert Vorsicht
Kritisch1-19Schwerwiegende Probleme (aufgegeben, nur ein Maintainer, keine Hygiene)
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.
Der gewichtete Gesamtwert 77 wird auf der veröffentlichten Indexskala auf 91 kalibriert (Register-Kalibrierung 2026-08-02).
Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.
Direkte Abhängigkeiten ohne bekannte Advisories — keine direkte Abhängigkeit trägt ein bekanntes Advisory
25/25
Indirekte Abhängigkeiten ohne bekannte Advisories — keine indirekte Abhängigkeit trägt ein bekanntes Advisory
0/40
Keine offenen Advisories — kein Advisory trägt ein Veröffentlichungsdatum
Verwendete Eingangsdaten
source
osv
advisories
0
affected_packages
0
assessed_packages
2
unassessed_packages
0
affected_by_severity
none
direct_affected_packages
0
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Keine offenen Advisories. Die verbleibenden Gewichte wurden renormalisiert. Abgeglichen wurde die Laufzeit-Abhängigkeitshülle von pypi:slangpy@0.43.1 — das, was die Installation des veröffentlichten Pakets nach sich zieht — mit 2 Paketen. Erreichbarkeit wird nicht analysiert.
Wie gut ist das Repository dafür ausgestattet, mit KI-Coding-Agenten entwickelt und gepflegt zu werden? Trägt ein bewusst kleines Gewicht (4 %): Agenten-Tooling ist ein echtes Pflegesignal, doch ein Repository ohne jedes Signal kann weiterhin 100/100 erreichen.
Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
Weitere Details
Stern- und Fork-Verlauf 0 ★ / 43 ⇿
0Sterne
43Forks
3Releases
Wann jeder Stern und Fork hinzugefügt wurde, von GitHub erfasst und nach Tagen gruppiert. Das kumulierte Wachstum steht direkt über den täglichen Zugängen, aus denen es besteht, sodass beide gegeneinander lesbar sind: stetiger organischer Zuwachs sieht ganz anders aus als ein abrupter, kurzlebiger Ausschlag. Wo dieser Unterschied messbar ist, wird er als Wachstumsauthentizität ausgewiesen.
Major 0Minor 0Patch 3
Jeder Punkt umfasst 2 Tage.
OpenSSF Scorecard 4.7 / 10
4.7Gesamtwert
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 · 2026-07-24 10:54 UTC
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 2 direkte und 19 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
Registry
Paket
Version
Beziehung
PyPI
numpy
—
direkt
PyPI
typing-extensions
—
direkt
PyPI
autoflake
—
indirekt
PyPI
cmake
3.31.6
indirekt
PyPI
deepdiff
—
indirekt
PyPI
furo
—
indirekt
PyPI
imageio
—
indirekt
PyPI
isort
—
indirekt
PyPI
libcst
—
indirekt
PyPI
nbsphinx
—
indirekt
PyPI
pandoc
—
indirekt
PyPI
pre-commit
—
indirekt
PyPI
pymongo
—
indirekt
PyPI
pyright
—
indirekt
PyPI
pytest
—
indirekt
PyPI
pytest-cov
—
indirekt
PyPI
pytest-xdist
—
indirekt
PyPI
setuptools
—
indirekt
PyPI
slangpy-torch
0.7.0
indirekt
PyPI
sphinx
—
indirekt
PyPI
sphinx-copybutton
—
indirekt
Abhängigkeits-Advisories 0
Die Installation von pypi:slangpy@0.43.1 zieht 2 Pakete nach sich, direkt und transitiv: 0 tragen bekannte Advisories, davon 0 direkte Abhängigkeiten.
Keine bekannten Advisories betreffen die bewerteten Abhängigkeiten.
Ein Advisory bedeutet, dass die im Abhängigkeitsgraphen erfasste Version in den betroffenen Bereich eines Advisories fällt. Erreichbarkeit wird nicht analysiert, und der Graph enthält Entwicklungs- und Test-Pins — ein Fund kann das Werkzeug betreffen und nicht die ausgelieferte Software.
JSON-Rohbericht maschinenlesbar
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"body": "The begin_render_pass/begin_compute_pass/begin_ray_tracing_pass methods on\nCommandEncoder dereferenced the underlying rhi command encoder without first\nchecking that the encoder was still open. Reusing a finished/closed encoder\ntherefore crashed with an opaque native backtrace instead of a clean error.\n\nAdd the same SGL_CHECK(m_open, ...) guard already used by every other\nCommandEncoder method, and a regression test.\n\nFixes #253",
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"headline": "Add error handling when reusing a finished command encoder (#1019)",
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"headline": "Update QueryPool interface (#1028)",
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"headline": "Update slang-rhi (#1027)",
"author_name": "Simon Kallweit",
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"is_bot": false,
"headline": "Global fix for g++ false positive (#1026)",
"author_name": "ccummingsNV",
"author_login": "ccummingsNV",
"committed_at": "2026-06-18T08:04:10Z",
"body_truncated": false,
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"is_bot": false,
"headline": "chore: Add AI-Assisted Contributions in CONTRIBUTING.md (#993)",
"author_name": "Khronos Group Web Services",
"author_login": "KhronosWebservices",
"committed_at": "2026-06-11T19:21:13Z",
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"oid": "9dd3d8caced2eeb50cf8a0a9cc3c1c7f6e44c06a",
"body": "* Change windows workflow to bridge\n\n* Change to bridge group\n\n* Change group again\n\n---------\n\nCo-authored-by: Chris Cummings <chriscummings@nvidia.com>",
"is_bot": false,
"headline": "Change windows workflow to bridge (#1022)",
"author_name": "ccummingsNV",
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"headline": "Add compilation reports API (#1015)",
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"headline": "Native conversion (#989)",
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"headline": "Test format acknowledgement (#985)",
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"headline": "Test pre-commit failure comment (#984)",
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"body": "* Improve SHA1 performance\n\n* Add additional sha1 testcase\n\n* Add arm64 implementation\n\n* Fix gcc build\n\n* Fix windows include\n\n* Fix static initialization\n\n* More heavy inlining",
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"headline": "Improve SHA1 performance (#971)",
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"body": "Co-authored-by: ccummingsNV <ccummings@nvidia.com>",
"is_bot": false,
"headline": "Add ASTC format support to the format enumeration and info table (#953)",
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"oid": "c409e5c4e84450b72cf9fadfa9b7a2fb4ec551b2",
"body": "…age (#937)\n\nnp.flipud returns a view with negative strides, which copy_from_numpy\nrejects. Ensure the returned array is always C-contiguous.\n\nRelates to #928\n\nMade-with: Cursor\n\nCo-authored-by: Jay Kwak <82421531+jkwak-work@users.noreply.github.com>",
"is_bot": false,
"headline": "Fix flip_y producing non-contiguous array in load_buffer_data_from_im…",
"author_name": "James Helferty (NVIDIA)",
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}
],
"max_points": 60
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{
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},
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"note": null,
"notes": [],
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"readme_badges": null,
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{
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"code": "license_custom",
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],
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{
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},
{
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{
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}
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{
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{
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"details": [
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"code": "top_contributor_share",
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"details": [],
"max_points": 10
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]
},
{
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}
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{
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{
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{
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{
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{
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"status": "met",
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{
"key": "pinned_dependencies",
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"points": 0,
"status": "missed",
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{
"key": "sast",
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"points": 0,
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{
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"points": 0,
"status": "missed",
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"max_points": 5
},
{
"key": "signed_releases",
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"points": 0,
"status": "missed",
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},
{
"key": "token_permissions",
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"points": 0,
"status": "missed",
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},
{
"key": "vulnerabilities",
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"code": "jurisdiction_no_match",
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],
"max_points": 100
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],
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"weight": 0.04,
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"key": "ai_agent_context",
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"note": null,
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"inputs": {
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"points": 0,
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{
"key": "legible_commit_history",
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"points": 40,
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{
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"points": 11,
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{
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"status": "met",
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{
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"points": 0,
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{
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"points": 6,
"status": "partial",
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{
"key": "automated_maintenance",
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"points": 0,
"status": "missed",
"details": [
{
"code": "no_dependency_automation",
"params": {}
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{
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"code": "statically_typed_language",
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{
"key": "manageable_file_sizes",
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"points": 53.3,
"status": "partial",
"details": [
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"code": "oversized_source_files",
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{
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{
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