Öffentliches RegisterMittel
Software-GesundheitsberichtSchema 0.27.0 · Metriken 1.13.0 · 2026-07-23 17:49 UTC
PreferredAI / cornac
A Comparative Framework for Multimodal Recommender Systems
PreferredAI/cornac erreicht einen Gesundheitsindex von 65 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Vitality (78/100) ab, am schwächsten bei Security (18/100). Zuletzt vor 5 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.
65
gesamt / 100Software-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.
65
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)
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
Preferred.AIOrganisation
62 Follower52 öffentliche Reposseit Nov. 2017
Dieses Repository wird von einer Organisation getragen — geteilte, rechenschaftspflichtige Trägerschaft, die jeden einzelnen Maintainer überdauern kann.
Paket-Ökosysteme
| Registry | Paket | Version | Downloads / Monat | Versionen | Zuletzt veröffentlicht | Tags |
|---|---|---|---|---|---|---|
| PyPI | cornac | 2.6.0 | - | 68 | vor 8 Tagen | recommender-systemcollaborative-filteringmultimodalpreference-learningrecommendation |
Metriken nach Kategorie
Vitalität
Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?
78
Entwicklungsaktivität
68Mittel
Wie die Bewertung erfolgt
| 36/36 | Push-Aktualität — letzter Push vor 5 Tagen |
| 11.1/36 | Commit-Rhythmus — 16/52 Wochen mit Commits |
| 14.1/18 | Commit-Volumen — 36 Commits im letzten Jahr |
| 0/10 | OpenSSF Scorecard: Maintained — keine Daten |
Verwendete Eingangsdaten
| commits_last_year | 36 |
| human_commit_share | 1 |
| days_since_last_push | 5 |
| active_weeks_last_year | 16 |
Release-Disziplin
92Exzellent
Wie die Bewertung erfolgt
| 27/27 | Liefert Releases aus — 63 Releases veröffentlicht |
| 36/36 | Release-Aktualität — letztes Release vor 8 Tagen |
| 19.8/27 | Release-Rhythmus — ein Release etwa alle 77,7 Tage |
| 0/10 | OpenSSF Scorecard: Signed-Releases — keine Daten |
Verwendete Eingangsdaten
| releases_count | 63 |
| latest_release_tag | v2.6.0 |
| releases_from_tags | nein |
| days_since_latest_release | 8 |
| mean_days_between_releases | 77,7 |
Community & Verbreitung
Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?
70
Wie die Bewertung erfolgt
| 49/60 | Stars — 1.052 Stars |
| 18.6/25 | Forks — 171 Forks |
| 7.4/15 | Watcher — 22 Watcher |
Verwendete Eingangsdaten
| forks | 171 |
| stars | 1.052 |
| watchers | 22 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community-Gesundheit
65Mittel
Wie die Bewertung erfolgt
| 22.5/22.5 | README |
| 22.5/22.5 | Lizenz — anerkannte Lizenz (Apache-2.0) |
| 0/18 | CONTRIBUTING-Leitfaden |
| 0/13.5 | Verhaltenskodex |
| 7.2/7.2 | Issue-Vorlage |
| 6.3/6.3 | PR-Vorlage |
Verwendete Eingangsdaten
| has_readme | ja |
| has_license | ja |
| has_contributing | nein |
| has_issue_template | ja |
| has_code_of_conduct | nein |
| has_pull_request_template | ja |
Nachhaltigkeit & Governance
Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?
70
Maintainer-Resilienz (Bus-Faktor)
37Gefährdet
Wie die Bewertung erfolgt
| 9/54 | Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab |
| 10.6/22.5 | Commit-Verteilung — wichtigste beitragende Person verfasste 53 % der Commits |
| 13.5/13.5 | Breite der Beitragenden — 27 Beitragende |
| 0/10 | OpenSSF Scorecard: Contributors — keine Daten |
Verwendete Eingangsdaten
| bus_factor | 1 |
| contributors_sampled | 27 |
| top_contributor_share | 0,527 |
Reaktionsfähigkeit bei Issues & PRs
88Exzellent
Wie die Bewertung erfolgt
| 40/46.8 | Issue-Lösungsquote — 86 % der Issues geschlossen |
| 34.8/38.3 | PR-Annahme — 487/536 entschiedene PRs gemergt |
| 0/15 | OpenSSF Scorecard: Code-Review — keine Daten |
Verwendete Eingangsdaten
| merged_prs | 487 |
| open_issues | 25 |
| closed_issues | 148 |
| issue_closed_ratio | 0,855 |
| closed_unmerged_prs | 49 |
Eigentümerschaft & Trägerschaft
68Mittel
Wie die Bewertung erfolgt
| 30/30 | Organisatorische Trägerschaft — im Besitz einer Organisation |
| 0/20 | Verifizierte Domain |
| 12.9/25 | Reichweite des Inhabers — 62 Follower von PreferredAI |
| 24.6/25 | Kontohistorie — 52 öffentliche Repos, Kontoalter ca. 8 Jahre |
Verwendete Eingangsdaten
| followers | 62 |
| owner_type | Organization |
| is_verified | — |
| owner_login | PreferredAI |
| public_repos | 52 |
| account_age_days | 3.157 |
Paketpflege
100Exzellent
Wie die Bewertung erfolgt
| 25/25 | Veröffentlicht & auflösbar — 1 Paket(e) auf pypi |
| 35/35 | Veröffentlichungsaktualität — letzte Veröffentlichung vor 8 Tagen |
| 20/20 | Versionshistorie — 68 veröffentlichte Versionen |
| 20/20 | Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen |
Verwendete Eingangsdaten
| packages | cornac |
| ecosystems | pypi |
| any_deprecated | nein |
| min_days_since_publish | 8 |
Engineering-Qualität
Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?
76
Engineering-Praktiken
60Mittel
Wie die Bewertung erfolgt
| 24/24 | CI-Workflows — 5 Workflow(s) |
| 24/24 | Tests vorhanden |
| 0/16 | Linter-Konfiguration |
| 0/9.6 | Pre-Commit-Hooks |
| 0/6.4 | .editorconfig |
| 0/20 | OpenSSF Scorecard: CI-Tests — keine Daten |
Verwendete Eingangsdaten
| has_ci | ja |
| has_tests | ja |
| has_editorconfig | nein |
| has_linter_config | nein |
| has_precommit_config | nein |
Dokumentation
100Exzellent
Wie die Bewertung erfolgt
| 30/30 | README |
| 25/25 | Dokumentationsverzeichnis |
| 15/15 | Dokumentations-/Homepage-Site — https://cornac.preferred.ai |
| 10/10 | Repository-Beschreibung |
| 10/10 | Topics — 8 Topics |
| 10/10 | Wiki |
Verwendete Eingangsdaten
| topics | recommender-system, recommendation-algorithms, recommendation-engine, matrix-factorization, collaborative-filtering, multimodal-learning, recommendation-system, multimodality |
| has_wiki | ja |
| homepage | https://cornac.preferred.ai |
| has_readme | ja |
| has_docs_dir | ja |
| has_description | ja |
Sicherheit
Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?
18
Sicherheitslage
1Kritisch
Wie die Bewertung erfolgt
| 0/30 | Sicherheitsrichtlinie (SECURITY.md) |
| 0/25 | Dependabot-Konfiguration |
| 0/25 | Lockfiles für Abhängigkeiten — veröffentlichte Bibliothek — Lockfiles sind Sache der Anwendung, hier nicht erwartet |
| 0/20 | CodeQL-Workflow |
Verwendete Eingangsdaten
| source | file_signals |
| lockfiles | — |
| manifests | docs/requirements.txt, pyproject.toml, requirements.txt, setup.cfg, setup.py |
| has_codeql_workflow | nein |
| has_security_policy | nein |
| has_dependabot_config | nein |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lockfiles für Abhängigkeiten. Die verbleibenden Gewichte wurden renormalisiert.
Abhängigkeits-Advisories
85Exzellent
Wie die Bewertung erfolgt
| 26.6/35 | Direkte Abhängigkeiten ohne bekannte Advisories — 1 betroffen: scipy 1.2.1 (unknown) |
| 0/25 | Indirekte Abhängigkeiten ohne bekannte Advisories — transitive Menge in diesem Bereich nicht von Entwicklungs- und Test-Abhängigkeiten trennbar |
| 37.2/40 | Keine offenen Advisories — 1 Paket(e) mit Advisory seit über 90 Tagen unbehandelt; ältestes vor 1.114 Tagen veröffentlicht |
Verwendete Eingangsdaten
| source | osv |
| advisories | 755 |
| affected_packages | 7 |
| assessed_packages | 12 |
| unassessed_packages | 28 |
| affected_by_severity | critical 3, moderate 1, unknown 3 |
| direct_affected_packages | 1 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Indirekte Abhängigkeiten ohne bekannte Advisories. Die verbleibenden Gewichte wurden renormalisiert. 12 aufgelöste Abhängigkeiten wurden mit OSV abgeglichen. 28 konnten nicht bewertet werden — keine aufgelöste Version, ein nicht unterstütztes Ökosystem oder außerhalb der ausgewiesenen Paketliste. Dieses Repository veröffentlicht kein Paket, das der Index auflöst; bewertet wurde daher der Abhängigkeitsgraph des Repositorys. Dieser Graph vermischt Entwicklungs- und Test-Pins mit ausgelieferten Abhängigkeiten, daher werden nur die deklarierten Laufzeit-Abhängigkeiten bewertet; transitive Befunde werden als Kontext ausgewiesen und fließen nicht in die Bewertung ein. Erreichbarkeit wird nicht analysiert.
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.
50
AI-Agentenkontext & Leitlinien
38Gefährdet
Wie die Bewertung erfolgt
| 0/45 | Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln |
| 0/15 | Maschinenlesbare Doku (llms.txt) |
| 37.9/40 | Lesbare Commit-Historie — 71 von 100 menschlichen Commits benennen ihre Absicht (strukturierter Betreff oder erläuternder Text) |
Verwendete Eingangsdaten
| has_llms_txt | nein |
| legible_history_share | 0,71 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Wie die Bewertung erfolgt
| 18/18 | Bootstrap mit einem Befehl — docs/Makefile |
| 22/22 | Automatisierte Tests |
| 0/11 | Lint-/Format-Konfiguration |
| 0/11 | Statische Typprüfung |
| 10/10 | Reproduzierbare Umgebung — Dockerfile |
| 4/10 | Belegte Agentenpraxis — 2 der letzten 100 Commits von Agenten verfasst oder ihnen zugeschrieben |
| 0/8 | Automatisierte Wartung — keine automatisierten Abhängigkeits-Updates beobachtet |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — keine Daten |
Verwendete Eingangsdaten
| has_nix | nein |
| has_tests | ja |
| lockfiles | — |
| has_dockerfile | ja |
| typed_language | nein |
| bootstrap_files | docs/Makefile |
| has_devcontainer | nein |
| has_linter_config | nein |
| typecheck_configs | — |
| agent_commit_share | 0,02 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
AI-Code-Lesbarkeit für Modelle
54Mittel
Wie die Bewertung erfolgt
| 0/45 | Typprüfbarer Code — Python ohne Typprüfungs-Konfiguration |
| 54.3/55 | Handhabbare Dateigrößen — 44/3.562 Quelldateien über 60 KB |
Verwendete Eingangsdaten
| primary_language | Python |
| largest_source_bytes | 1.058.368 |
| source_files_sampled | 3.562 |
| oversized_source_files | 44 |
Maschinenlesbare AI-Schnittstellen
40Gefährdet
Wie die Bewertung erfolgt
| 0/40 | API-Schema (OpenAPI/GraphQL/proto) |
| 0/20 | MCP-Server |
| 40/40 | Lauffähige Beispiele — examples, notebooks |
Verwendete Eingangsdaten
| example_dirs | examples, notebooks |
| has_mcp_signal | nein |
| api_schema_files | — |
Eckdaten
1.052GitHub-Sterne
27Mitwirkende
36Commits, letzte 12 Monate
5Tage seit letztem Push
63Releases
1Bus-Faktor
25offene Issues
PyPIPaket-Ökosysteme
Warnungen zur Datenerhebung
- Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
- Could not fetch pypi package 'cornac.models.c2pf.c2pf' from its registry
- deps.dev does not index pypi:cornac@2.6.0; advisories assessed against the repository dependency graph instead
- Advisory severity resolved for 120 of 752 advisories (lookup cap); the remainder are reported as unknown severity
- OpenSSF Scorecard did not return a usable result (2026/07/23 17:48:33 Warning: PATs stored in env variables GITHUB_AUTH_TOKEN and GITHUB_TOKEN differ. Scorecard will use the former.); skipping Scorecard checks
Weitere Details
Stern- und Fork-Verlauf 0 ★ / 171 ⇿
0Sterne
171Forks
62Releases
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 2Minor 25Patch 34
Jeder Punkt umfasst 8 Tage.
Direkte Abhängigkeiten 4
| Registry | Paket | Versionsvorgabe | Manifest |
|---|---|---|---|
| PyPI | numpy | >2.0.0 | pyproject.toml |
| PyPI | scipy | — | pyproject.toml |
| PyPI | tqdm | — | pyproject.toml |
| PyPI | powerlaw | — | pyproject.toml |
Alle Abhängigkeiten 40
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 5 direkte und 35 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
| Registry | Paket | Version | Beziehung |
|---|---|---|---|
| PyPI | numpy | — | direkt |
| PyPI | powerlaw | — | direkt |
| PyPI | scipy | — | direkt |
| PyPI | scipy | 1.2.1 | direkt |
| PyPI | tqdm | — | direkt |
| PyPI | cython | — | indirekt |
| PyPI | dcor | — | indirekt |
| PyPI | dgl | — | indirekt |
| PyPI | dgl | 1.1.0 | indirekt |
| PyPI | dgl | 2.4.0 | indirekt |
| PyPI | dgl | 2.4.0+cu118 | indirekt |
| PyPI | filelock | 3.8.2 | indirekt |
| PyPI | flask | — | indirekt |
| PyPI | huggingface-hub | — | indirekt |
| PyPI | myst-parser | — | indirekt |
| PyPI | nltk | — | indirekt |
| PyPI | pandas | — | indirekt |
| PyPI | pandas | 2.2.3 | indirekt |
| PyPI | pydata-sphinx-theme | — | indirekt |
| PyPI | pytest | — | indirekt |
| PyPI | pytest-cov | — | indirekt |
| PyPI | pytest-xdist | — | indirekt |
| PyPI | requests | — | indirekt |
| PyPI | sansa | — | indirekt |
| PyPI | scikit-learn | — | indirekt |
| PyPI | sentence-transformers | — | indirekt |
| PyPI | sentence-transformers | 2.2.2 | indirekt |
| PyPI | setuptools | — | indirekt |
| PyPI | similaripy | 0.1.3 | indirekt |
| PyPI | sphinx-copybutton | — | indirekt |
| PyPI | sphinx-design | — | indirekt |
| PyPI | tensorflow | — | indirekt |
| PyPI | tensorflow | 1.15.4 | indirekt |
| PyPI | tensorflow | 2.12.0 | indirekt |
| PyPI | tensorflow | 2.21.0 | indirekt |
| PyPI | torch | — | indirekt |
| PyPI | torch | 2.0.0 | indirekt |
| PyPI | torch | 2.3.* | indirekt |
| PyPI | torchvision | — | indirekt |
| PyPI | transformers | — | indirekt |
Abhängigkeits-Advisories 7
Dieses Repository veröffentlicht kein vom Index auflösbares Paket, daher wurde sein eigener Abhängigkeitsgraph bewertet – 12 Pakete, darunter auch Entwicklungs- und Test-Pins, die nie ausgeliefert werden: 7 tragen bekannte Advisories, davon 1 direkte. 28 konnten nicht bewertet werden – keine aufgelöste Version, ein nicht unterstütztes Ökosystem, oder außerhalb der ausgewiesenen Paketliste.
| Paket | Version | Beziehung | Schweregrad | Advisories | Behoben in |
|---|---|---|---|---|---|
| dgl | 1.1.0 | indirekt | kritisch | 1 | — |
| dgl | 2.4.0 | indirekt | kritisch | 1 | — |
| tensorflow | 1.15.4 | indirekt | kritisch | 717 | 2.11.1 |
| filelock | 3.8.2 | indirekt | mittel | 4 | 3.20.3 |
| scipy | 1.2.1 | direkt | unbekannt | 2 | 1.10.0 |
| tensorflow | 2.12.0 | indirekt | unbekannt | 2 | — |
| torch | 2.0.0 | indirekt | unbekannt | 28 | — |
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
{
"data": {
"repo": {
"topics": [
"recommender-system",
"recommendation-algorithms",
"recommendation-engine",
"matrix-factorization",
"collaborative-filtering",
"multimodal-learning",
"recommendation-system",
"multimodality"
],
"is_fork": false,
"size_kb": 27772,
"has_wiki": true,
"homepage": "https://cornac.preferred.ai",
"languages": {
"C": 5411,
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"Cython": 336665,
"Python": 1596320,
"Dockerfile": 981,
"Jupyter Notebook": 89405
},
"pushed_at": "2026-07-18T09:55:42Z",
"created_at": "2018-07-17T06:31:35Z",
"owner_type": "Organization",
"updated_at": "2026-07-18T09:55:47Z",
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"license": {
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},
"activity": {
"releases": [
{
"tag": "v2.6.0",
"kind": "minor",
"published_at": "2026-07-15T05:56:27Z"
},
{
"tag": "v2.5.0",
"kind": "minor",
"published_at": "2026-06-04T14:57:06Z"
},
{
"tag": "v2.4.0",
"kind": "minor",
"published_at": "2026-05-27T16:43:47Z"
},
{
"tag": "v2.3.5",
"kind": "patch",
"published_at": "2025-10-04T22:15:55Z"
},
{
"tag": "v2.3.4",
"kind": "patch",
"published_at": "2025-10-02T19:54:45Z"
},
{
"tag": "v2.3.3",
"kind": "patch",
"published_at": "2025-04-26T17:10:43Z"
},
{
"tag": "v2.3.2",
"kind": "patch",
"published_at": "2025-04-15T05:57:39Z"
},
{
"tag": "v2.3.1",
"kind": "patch",
"published_at": "2025-04-15T00:30:15Z"
},
{
"tag": "v2.3.0",
"kind": "minor",
"published_at": "2024-12-24T18:14:45Z"
},
{
"tag": "v2.2.2",
"kind": "patch",
"published_at": "2024-08-15T06:25:57Z"
},
{
"tag": "v2.2.1",
"kind": "patch",
"published_at": "2024-05-24T10:07:10Z"
},
{
"tag": "v2.2.0",
"kind": "minor",
"published_at": "2024-05-06T22:24:15Z"
},
{
"tag": "v2.1.0",
"kind": "minor",
"published_at": "2024-03-21T07:26:15Z"
},
{
"tag": "v2.0.0",
"kind": "major",
"published_at": "2024-03-05T06:52:53Z"
},
{
"tag": "v1.18.0",
"kind": "minor",
"published_at": "2023-12-12T07:49:26Z"
},
{
"tag": "v1.17.0",
"kind": "minor",
"published_at": "2023-10-20T02:59:14Z"
},
{
"tag": "v1.16.0",
"kind": "minor",
"published_at": "2023-07-22T18:22:54Z"
},
{
"tag": "v1.15.4",
"kind": "patch",
"published_at": "2023-05-13T06:40:19Z"
},
{
"tag": "v1.15.3",
"kind": "patch",
"published_at": "2023-05-13T05:51:19Z"
},
{
"tag": "v1.15.2",
"kind": "patch",
"published_at": "2023-05-12T21:10:01Z"
},
{
"tag": "v1.15.1",
"kind": "patch",
"published_at": "2023-04-16T03:27:20Z"
},
{
"tag": "v1.15.0",
"kind": "minor",
"published_at": "2023-04-01T18:58:12Z"
},
{
"tag": "v1.14.2",
"kind": "patch",
"published_at": "2022-02-19T03:37:13Z"
},
{
"tag": "v1.14.1",
"kind": "patch",
"published_at": "2021-09-26T07:01:44Z"
},
{
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],
"report_type": "repository",
"generated_at": "2026-07-23T17:49:19.916297Z",
"schema_version": "0.27.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/p/PreferredAI/cornac.svg",
"full_name": "PreferredAI/cornac",
"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 v0.27.0 — vollständige Methodik · Metriken-Wiki.
Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken — PyPI.