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Software-GesundheitsberichtSchema 0.12.0 · Metriken 1.13.0 · 2026-07-18 12:50 UTC

Lightning-AI / lightning

Pretrain, finetune ANY AI model of ANY size on 1 or 10,000+ GPUs with zero code changes.

PythonApache-2.0★ 31.238 Sterne⑂ 3.761 Forksseit März 2019Auf GitHub ansehen ↗

Lightning-AI/lightning erreicht einen Gesundheitsindex von 85 von 100 und liegt damit im Bereich Exzellent. Am stärksten schneidet es bei Community & Adoption (95/100) ab, am schwächsten bei AI Readiness (51/100). Zuletzt vor 1 Tag aktualisiert. 3 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

6.836 Follower29 öffentliche Reposseit Dez. 2019

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

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlicht
PyPIassistantverweist auf ein anderes Repo — nicht bewertet2.0.2b2-43vor 81 Tagen

Metriken nach Kategorie

Vitalität

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

93Exzellent · 22 % des Gesamtindex
Wie die Bewertung erfolgt
36/36Push-Aktualität — letzter Push vor 1 Tagen
31.2/36Commit-Rhythmus — 45/52 Wochen mit Commits
18/18Commit-Volumen — 426 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_year426
human_commit_share
days_since_last_push1
active_weeks_last_year45
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 100 Releases veröffentlicht
36/36Release-Aktualität — letztes Release vor 51 Tagen
27/27Release-Rhythmus — ein Release etwa alle 44,1 Tage
0/10OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.
Verwendete Eingangsdaten
releases_count100
latest_release_tag2.6.5
releases_from_tagsnein
days_since_latest_release51
mean_days_between_releases44,1

Community & Verbreitung

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

95Exzellent · 18 % des Gesamtindex
Wie die Bewertung erfolgt
60/60Stars — 31.238 Stars
25/25Forks — 3.761 Forks
13.4/15Watcher — 256 Watcher
Verwendete Eingangsdaten
forks3.761
stars31.238
watchers256
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
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?

81Gut · 24 % des Gesamtindex
Wie die Bewertung erfolgt
36/54Bus-Faktor — 3 Beitragende decken die Hälfte aller Commits ab
17/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 24 % der Commits
13.5/13.5Breite der Beitragenden — 100 Beitragende
10/10OpenSSF Scorecard: Contributors — project has 42 contributing companies or organizations
Verwendete Eingangsdaten
bus_factor3
contributors_sampled100
top_contributor_share0,245
Wie die Bewertung erfolgt
41.5/46.8Issue-Lösungsquote — 89 % der Issues geschlossen
32.8/38.3PR-Annahme — 9.438/11.020 entschiedene PRs gemergt
15/15OpenSSF Scorecard: Code-Review — all changesets reviewed
Verwendete Eingangsdaten
merged_prs9.438
open_issues843
closed_issues6.712
issue_closed_ratio0,888
closed_unmerged_prs1.582
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
25/25Reichweite des Inhabers — 6.836 Follower von Lightning-AI
22.8/25Kontohistorie — 29 öffentliche Repos, Kontoalter ca. 6 Jahre
Verwendete Eingangsdaten
followers6.836
owner_typeOrganization
is_verified
owner_loginLightning-AI
public_repos29
account_age_days2.421

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

92Exzellent · 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
20/20OpenSSF Scorecard: CI-Tests — 30 out of 30 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://lightning.ai/pytorch-lightning/?utm_source=ptl_readme&utm_medium=referral&utm_campaign=ptl_readme
10/10Repository-Beschreibung
10/10Topics — 7 Topics
0/10Wiki
Verwendete Eingangsdaten
topicspython, deep-learning, artificial-intelligence, ai, pytorch, data-science, machine-learning
has_wikinein
homepagehttps://lightning.ai/pytorch-lightning/?utm_source=ptl_readme&utm_medium=referral&utm_campaign=ptl_readme
has_readmeja
has_docs_dirja
has_descriptionja

Sicherheit

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

63Mittel · 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 — 30 out of 30 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
7.5/7.5Code-Review — all changesets reviewed
2.5/2.5Contributors — project has 42 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
3/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 6
0/5SAST — SAST tool is not run on all commits -- score normalized to 0
3/5Security-Policy — security policy file 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
3/7.5Vulnerabilities — 6 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated17
scorecard_versionv5.5.0
checks_inconclusive1
scorecard_aggregate6,3
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection. 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.

51Mittel · 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 — Makefile, docs/source-fabric/Makefile, docs/source-pytorch/Makefile
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration
11/11Statische Typprüfung — src/lightning/py.typed, src/lightning_fabric/py.typed, src/pytorch_lightning/py.typed
0/10Reproduzierbare Umgebung
0/10Belegte Agentenpraxis — keine Daten
5/8Automatisierte Wartung — Abhängigkeits-Automatisierung konfiguriert, in den erfassten Commits nicht beobachtet
6/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 6
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfiles
has_dockerfilenein
typed_languagenein
bootstrap_filesMakefile, docs/source-fabric/Makefile, docs/source-pytorch/Makefile
has_devcontainernein
has_linter_configja
typecheck_configssrc/lightning/py.typed, src/lightning_fabric/py.typed, src/pytorch_lightning/py.typed
agent_commit_share
toolchain_manifests
dependency_bot_commit_share0
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Belegte Agentenpraxis. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
27/45Typprüfbarer Code — Python mit Typprüfungs-Konfiguration (src/lightning/py.typed, src/lightning_fabric/py.typed, src/pytorch_lightning/py.typed)
54.6/55Handhabbare Dateigrößen — 5/648 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes82.856
source_files_sampled648
oversized_source_files5
Wie die Bewertung erfolgt
0/40API-Schema (OpenAPI/GraphQL/proto)
0/20MCP-Server
40/40Lauffähige Beispiele — demos, examples, notebooks
Verwendete Eingangsdaten
example_dirsdemos, examples, notebooks
has_mcp_signalnein
api_schema_files

Eckdaten

31.238GitHub-Sterne
100Mitwirkende
426Commits, letzte 12 Monate
1Tage seit letztem Push
100Releases
3Bus-Faktor
843offene Issues
PyPIPaket-Ökosysteme

Warnungen zur Datenerhebung

  • pypi package 'assistant' points at a different repository (https://gitlab.com/waser-technologies/technologies/assistant); excluded from ecosystem scoring

Weitere Details

OpenSSF Scorecard 6.3 / 10
6.3Gesamtwert

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 12:48 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-Tests30 out of 30 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
10Code-Reviewall changesets reviewed
10Contributorsproject has 42 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
6Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 6
0SASTSAST tool is not run on all commits -- score normalized to 0
6Security-Policysecurity policy file detected
0Signed-ReleasesProject has not signed or included provenance with any releases.
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
4Vulnerabilities6 existing vulnerabilities detected
Alle Abhängigkeiten 96

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 0 direkte und 96 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
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PyPIlightningindirekt
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PyPIlitdataindirekt
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PyPIpandasindirekt
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PyPIpkginfo1.12.1.2indirekt
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PyPIpytest-doctestplus1.7.1indirekt
PyPIpytest-random-order1.2.0indirekt
PyPIpytest-rerunfailures16.0.1indirekt
PyPIpytest-rerunfailures16.1indirekt
PyPIpytest-timeout2.4.0indirekt
PyPIpyyamlindirekt
PyPIrequestsindirekt
PyPIrichindirekt
PyPIscikit-learnindirekt
PyPIsetuptoolsindirekt
PyPIsphinxindirekt
PyPIsphinx-autobuildindirekt
PyPIsphinx-autodoc-typehintsindirekt
PyPIsphinx-copybuttonindirekt
PyPIsphinx-multiprojectindirekt
PyPIsphinx-paramlinksindirekt
PyPIsphinx-rtd-dark-modeindirekt
PyPIsphinx-togglebuttonindirekt
PyPIsphinx-toolbox4.1.2indirekt
PyPIsphinxcontrib-fulltocindirekt
PyPIsphinxcontrib-mockautodocindirekt
PyPIsphinxcontrib-video0.4.2indirekt
PyPItensorboardindirekt
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PyPItomlkitindirekt
PyPItorchindirekt
PyPItorch2.9.1indirekt
PyPItorch-tensorrtindirekt
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PyPItwine6.2.0indirekt
PyPItypes-bleachindirekt
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PyPIwgetindirekt
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JSON-Rohbericht maschinenlesbar
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                "key": "release_cadence",
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                "key": "openssf_scorecard_signed_releases",
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          {
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              "cap": null,
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        ],
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      {
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              {
                "key": "watchers",
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                    "code": "watchers",
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                "max_points": 15
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          },
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            "key": "community_health",
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                "points": 22.5,
                "status": "met",
                "details": [
                  {
                    "code": "license_standard",
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                  {
                    "code": "license_spdx",
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                "max_points": 22.5
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                "key": "contributing_guide",
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                "key": "code_of_conduct",
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              {
                "key": "issue_template",
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        ],
        "description": "Does the project have users, downloads, attention, and a welcoming setup for contributors?"
      },
      {
        "key": "governance",
        "band": "good",
        "name": "Sustainability & Governance",
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        "metrics": [
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              "top_contributor_share": 0.245
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                "key": "bus_factor",
                "name": "Bus factor",
                "detail": "3 contributor(s) cover half of all commits",
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                    "code": "bus_factor",
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                "key": "commit_distribution",
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                "max_points": 22.5
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                    "code": "contributors_sampled",
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                "max_points": 13.5
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                "key": "openssf_scorecard_contributors",
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                "max_points": 10
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            ]
          },
          {
            "key": "responsiveness",
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            "name": "Issue & PR responsiveness",
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            "notes": [],
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              "merged_prs": 9438,
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              "closed_unmerged_prs": 1582
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                "key": "issue_resolution",
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                "detail": "89% of issues closed",
                "points": 41.5,
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                    "code": "issues_closed_share",
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                "max_points": 46.75
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              {
                "key": "pr_acceptance",
                "name": "PR acceptance",
                "detail": "9438/11020 decided PRs merged",
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                    "code": "decided_prs_merged",
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                "max_points": 38.25
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              {
                "key": "openssf_scorecard_code_review",
                "name": "OpenSSF Scorecard: Code-Review",
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                "points": 15,
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                "details": [],
                "max_points": 15
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            ]
          },
          {
            "key": "stewardship",
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            "notes": [],
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              "followers": 6836,
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              "is_verified": null,
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            "components": [
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                "key": "ownership_backing",
                "name": "Ownership backing",
                "detail": "organization-owned",
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                "details": [
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                    "code": "owner_organization",
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                ],
                "max_points": 30
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              {
                "key": "verified_domain",
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                "status": "missed",
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              },
              {
                "key": "owner_reach",
                "name": "Owner reach",
                "detail": "6,836 followers of Lightning-AI",
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                    "code": "owner_followers",
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                      "count": 6836,
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                "max_points": 25
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              {
                "key": "track_record",
                "name": "Track record",
                "detail": "29 public repos, account ~6 yr old",
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                    "code": "account_age_years",
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                "max_points": 25
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        ],
        "description": "Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?"
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      {
        "key": "engineering",
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        "name": "Engineering Quality",
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        "weight": 0.2,
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                "key": "ci_workflows",
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                "key": "tests_present",
                "name": "Tests present",
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              {
                "key": "linter_config",
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                "key": "pre_commit_hooks",
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              {
                "key": "editorconfig",
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                "key": "openssf_scorecard_ci_tests",
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          },
          {
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            "components": [
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                "key": "documentation_directory",
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                "key": "documentation_homepage_site",
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          }
        ],
        "description": "Are baseline engineering and documentation practices in place?"
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            "value": 63,
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                "key": "code_review",
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                "key": "contributors",
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                "detail": "project has 42 contributing companies or organizations",
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                "key": "dangerous_workflow",
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                "points": 10,
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              },
              {
                "key": "dependency_update_tool",
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                "key": "fuzzing",
                "name": "Fuzzing",
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              },
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                "key": "license",
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              },
              {
                "key": "maintained",
                "name": "Maintained",
                "detail": "30 commit(s) and 5 issue activity found in the last 90 days -- score normalized to 10",
                "points": 7.5,
                "status": "met",
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              {
                "key": "packaging",
                "name": "Packaging",
                "detail": "packaging workflow detected",
                "points": 5,
                "status": "met",
                "details": [],
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              },
              {
                "key": "pinned_dependencies",
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                "status": "partial",
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              },
              {
                "key": "sast",
                "name": "SAST",
                "detail": "SAST tool is not run on all commits -- score normalized to 0",
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                "status": "missed",
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              },
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                "key": "security_policy",
                "name": "Security-Policy",
                "detail": "security policy file detected",
                "points": 3,
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                "details": [],
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              },
              {
                "key": "signed_releases",
                "name": "Signed-Releases",
                "detail": "Project has not signed or included provenance with any releases.",
                "points": 0,
                "status": "missed",
                "details": [],
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              {
                "key": "token_permissions",
                "name": "Token-Permissions",
                "detail": "detected GitHub workflow tokens with excessive permissions",
                "points": 0,
                "status": "missed",
                "details": [],
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              },
              {
                "key": "vulnerabilities",
                "name": "Vulnerabilities",
                "detail": "6 existing vulnerabilities detected",
                "points": 3,
                "status": "partial",
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              }
            ]
          },
          {
            "key": "high_risk_jurisdiction_exposure",
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            "notes": [
              {
                "code": "jurisdiction_evidence_limits",
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            ],
            "value": 100,
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              "meaning": "self-published location evidence; not nationality or citizenship",
              "red_flag": false,
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              "policy_countries": [
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                "North Korea"
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              "review_only_matches": 0,
              "assessed_self_published_locations": 8
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            "components": [
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                "key": "policy_exposure_multiplier",
                "name": "Policy exposure multiplier",
                "detail": "no confirmed policy-scope location match",
                "points": 100,
                "status": "met",
                "details": [
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                    "code": "jurisdiction_no_match",
                    "params": {}
                  }
                ],
                "max_points": 100
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            ]
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        ],
        "description": "Are visible security and supply-chain practices strong, with no malicious dependency and no unresolved high-risk jurisdiction exposure?"
      },
      {
        "key": "ai_readiness",
        "band": "moderate",
        "name": "AI Readiness",
        "value": 51,
        "weight": 0,
        "metrics": [
          {
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  "warnings": [
    "pypi package 'assistant' points at a different repository (https://gitlab.com/waser-technologies/technologies/assistant); excluded from ecosystem scoring"
  ],
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  "generated_at": "2026-07-18T12:50:45.353076Z",
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  "badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/l/Lightning-AI/lightning.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 v0.12.0 — vollständige Methodik · Metriken-Wiki.

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