Öffentliches RegisterGut
Software-GesundheitsberichtSchema 0.16.0 · Metriken 1.13.0 · 2026-07-21 02:34 UTC
awslabs / gluonts
Probabilistic time series modeling in Python
awslabs/gluonts erreicht einen Gesundheitsindex von 79 von 100 und liegt damit im Bereich Gut. Am stärksten schneidet es bei Community & Adoption (95/100) ab, am schwächsten bei AI Readiness (48/100). Zuletzt heute aktualisiert. 4 Mitwirkende tragen den Großteil der jüngsten Arbeit.
79
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.
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)
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
Amazon Web Services - LabsOrganisation
11.285 Follower1.019 öffentliche Reposseit Jan. 2013
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 |
|---|---|---|---|---|---|
| PyPI | gluonts | 0.16.3 | 8.485.649 | 112 | vor 21 Tagen |
Metriken nach Kategorie
Vitalität
Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?
73
Entwicklungsaktivität
60Mittel
Wie die Bewertung erfolgt
| 36/36 | Push-Aktualität — letzter Push vor 0 Tagen |
| 4.2/36 | Commit-Rhythmus — 6/52 Wochen mit Commits |
| 11.1/18 | Commit-Volumen — 16 Commits im letzten Jahr |
| 9/10 | OpenSSF Scorecard: Maintained — 11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9 |
Verwendete Eingangsdaten
| commits_last_year | 16 |
| human_commit_share | — |
| days_since_last_push | 0 |
| active_weeks_last_year | 6 |
Release-Disziplin
92Exzellent
Wie die Bewertung erfolgt
| 27/27 | Liefert Releases aus — 100 Releases veröffentlicht |
| 36/36 | Release-Aktualität — letztes Release vor 21 Tagen |
| 19.8/27 | Release-Rhythmus — ein Release etwa alle 103,9 Tage |
| 0/10 | OpenSSF Scorecard: Signed-Releases — keine Daten |
Verwendete Eingangsdaten
| releases_count | 100 |
| latest_release_tag | v0.16.3 |
| releases_from_tags | nein |
| days_since_latest_release | 21 |
| mean_days_between_releases | 103,9 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): OpenSSF Scorecard: Signed-Releases. Die verbleibenden Gewichte wurden renormalisiert.
Community & Verbreitung
Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?
95
Popularität & Verbreitung
95Exzellent
Wie die Bewertung erfolgt
| 60/60 | Stars — 5.220 Stars |
| 24.3/25 | Forks — 823 Forks |
| 10.4/15 | Watcher — 74 Watcher |
Verwendete Eingangsdaten
| forks | 823 |
| stars | 5.220 |
| watchers | 74 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community-Gesundheit
92Exzellent
Wie die Bewertung erfolgt
| 22.5/22.5 | README |
| 22.5/22.5 | Lizenz — anerkannte Lizenz (Apache-2.0) |
| 18/18 | CONTRIBUTING-Leitfaden |
| 13.5/13.5 | Verhaltenskodex |
| 0/7.2 | Issue-Vorlage |
| 6.3/6.3 | PR-Vorlage |
Verwendete Eingangsdaten
| has_readme | ja |
| has_license | ja |
| has_contributing | ja |
| has_issue_template | nein |
| has_code_of_conduct | ja |
| has_pull_request_template | ja |
Ökosystem-Verbreitung (Downloads)
100Exzellent
Wie die Bewertung erfolgt
| 80/80 | Downloads pro Monat — 8.485.649 Downloads/Monat über pypi |
| 0/20 | Abhängige in der Registry — von diesem Ökosystem nicht ausgewiesen |
Verwendete Eingangsdaten
| packages | gluonts |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 8.485.649 |
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?
84
Wie die Bewertung erfolgt
| 43.2/54 | Bus-Faktor — 4 Beitragende decken die Hälfte aller Commits ab |
| 14/22.5 | Commit-Verteilung — wichtigste beitragende Person verfasste 38 % der Commits |
| 13.5/13.5 | Breite der Beitragenden — 100 Beitragende |
| 10/10 | OpenSSF Scorecard: Contributors — project has 17 contributing companies or organizations |
Verwendete Eingangsdaten
| bus_factor | 4 |
| contributors_sampled | 100 |
| top_contributor_share | 0,377 |
Wie die Bewertung erfolgt
| 30.4/46.8 | Issue-Lösungsquote — 65 % der Issues geschlossen |
| 34.6/38.3 | PR-Annahme — 1.583/1.749 entschiedene PRs gemergt |
| 12/15 | OpenSSF Scorecard: Code-Review — Found 26/29 approved changesets -- score normalized to 8 |
Verwendete Eingangsdaten
| merged_prs | 1.583 |
| open_issues | 344 |
| closed_issues | 641 |
| issue_closed_ratio | 0,651 |
| closed_unmerged_prs | 166 |
Wie die Bewertung erfolgt
| 30/30 | Organisatorische Trägerschaft — im Besitz einer Organisation |
| 0/20 | Verifizierte Domain |
| 25/25 | Reichweite des Inhabers — 11.285 Follower von awslabs |
| 25/25 | Kontohistorie — 1.019 öffentliche Repos, Kontoalter ca. 13 Jahre |
Verwendete Eingangsdaten
| followers | 11.285 |
| owner_type | Organization |
| is_verified | — |
| owner_login | awslabs |
| public_repos | 1.019 |
| account_age_days | 4.932 |
Paketpflege
100Exzellent
Wie die Bewertung erfolgt
| 25/25 | Veröffentlicht & auflösbar — 1 Paket(e) auf pypi |
| 35/35 | Veröffentlichungsaktualität — letzte Veröffentlichung vor 21 Tagen |
| 20/20 | Versionshistorie — 112 veröffentlichte Versionen |
| 20/20 | Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen |
Verwendete Eingangsdaten
| packages | gluonts |
| ecosystems | pypi |
| any_deprecated | nein |
| min_days_since_publish | 21 |
Engineering-Qualität
Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?
72
Engineering-Praktiken
60Mittel
Wie die Bewertung erfolgt
| 24/24 | CI-Workflows — 13 Workflow(s) |
| 24/24 | Tests vorhanden |
| 0/16 | Linter-Konfiguration |
| 0/9.6 | Pre-Commit-Hooks |
| 0/6.4 | .editorconfig |
| 12/20 | OpenSSF Scorecard: CI-Tests — 18 out of 30 merged PRs checked by a CI test -- score normalized to 6 |
Verwendete Eingangsdaten
| has_ci | ja |
| has_tests | ja |
| has_editorconfig | nein |
| has_linter_config | nein |
| has_precommit_config | nein |
Dokumentation
90Exzellent
Wie die Bewertung erfolgt
| 30/30 | README |
| 25/25 | Dokumentationsverzeichnis |
| 15/15 | Dokumentations-/Homepage-Site — https://ts.gluon.ai |
| 10/10 | Repository-Beschreibung |
| 10/10 | Topics — 15 Topics |
| 0/10 | Wiki |
Verwendete Eingangsdaten
| topics | time-series, deep-learning, forecasting, neural-networks, machine-learning, time-series-prediction, time-series-forecasting, mxnet, pytorch, aws, sagemaker, timeseries, artificial-intelligence, data-science, torch |
| has_wiki | nein |
| homepage | https://ts.gluon.ai |
| has_readme | ja |
| has_docs_dir | ja |
| has_description | ja |
Sicherheit
Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?
71
Sicherheitslage
64Mittel
Wie die Bewertung erfolgt
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 4.5/7.5 | Branch-Protection — branch protection is not maximal on development and all release branches |
| 1.5/2.5 | CI-Tests — 18 out of 30 merged PRs checked by a CI test -- score normalized to 6 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 6/7.5 | Code-Review — Found 26/29 approved changesets -- score normalized to 8 |
| 2.5/2.5 | Contributors — project has 17 contributing companies or organizations |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 7.5/7.5 | Dependency-Update-Tool — update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | Lizenz — license file detected |
| 6.8/7.5 | Maintained — 11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9 |
| 5/5 | Packaging — packaging workflow detected |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 4/5 | SAST — SAST tool detected but not run on all commits |
| 5/5 | Security-Policy — security policy file detected |
| 0/7.5 | Signed-Releases — keine Daten |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 0/7.5 | Vulnerabilities — 24 existing vulnerabilities detected |
Verwendete Eingangsdaten
| source | openssf_scorecard |
| checks_evaluated | 17 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 1 |
| scorecard_aggregate | 6,4 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): signed_releases. Die verbleibenden Gewichte wurden renormalisiert.
Abhängigkeits-Advisories
100Exzellent
Wie die Bewertung erfolgt
| 35/35 | 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 | 13 |
| 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:gluonts@0.16.3 — das, was die Installation des veröffentlichten Pakets nach sich zieht — mit 13 Paketen. 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.
48
AI-Agentenkontext & Leitlinien
1Kritisch
Wie die Bewertung erfolgt
| 0/45 | Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln |
| 0/15 | Maschinenlesbare Doku (llms.txt) |
| 0/40 | Lesbare Commit-Historie — keine Daten |
Verwendete Eingangsdaten
| has_llms_txt | nein |
| 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
| 18/18 | Bootstrap mit einem Befehl — Justfile, docs/Makefile |
| 22/22 | Automatisierte Tests |
| 0/11 | Lint-/Format-Konfiguration |
| 11/11 | Statische Typprüfung — src/gluonts/core/py.typed |
| 10/10 | Reproduzierbare Umgebung — Dockerfile |
| 0/10 | Belegte Agentenpraxis — keine Daten |
| 0/8 | Automatisierte Wartung — keine Daten |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
Verwendete Eingangsdaten
| has_nix | nein |
| has_tests | ja |
| lockfiles | — |
| has_dockerfile | ja |
| typed_language | nein |
| bootstrap_files | Justfile, docs/Makefile |
| has_devcontainer | nein |
| has_linter_config | nein |
| typecheck_configs | src/gluonts/core/py.typed |
| 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
| 27/45 | Typprüfbarer Code — Python mit Typprüfungs-Konfiguration (src/gluonts/core/py.typed) |
| 54.9/55 | Handhabbare Dateigrößen — 1/863 Quelldateien über 60 KB |
Verwendete Eingangsdaten
| primary_language | Python |
| largest_source_bytes | 159.687 |
| source_files_sampled | 863 |
| oversized_source_files | 1 |
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
5.220GitHub-Sterne
100Mitwirkende
16Commits, letzte 12 Monate
0Tage seit letztem Push
100Releases
4Bus-Faktor
344offene Issues
PyPIPaket-Ökosysteme
Weitere Details
OpenSSF Scorecard 6.4 / 10
6.4Gesamtwert
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).
| 10 | Binary-Artifacts | no binaries found in the repo |
| 6 | Branch-Protection | branch protection is not maximal on development and all release branches |
| 6 | CI-Tests | 18 out of 30 merged PRs checked by a CI test -- score normalized to 6 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 8 | Code-Review | Found 26/29 approved changesets -- score normalized to 8 |
| 10 | Contributors | project has 17 contributing companies or organizations |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 10 | Dependency-Update-Tool | update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 9 | Maintained | 11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9 |
| 10 | Packaging | packaging workflow detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 8 | SAST | SAST tool detected but not run on all commits |
| 10 | Security-Policy | security policy file detected |
| k. A. | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 0 | Vulnerabilities | 24 existing vulnerabilities detected |
Direkte Abhängigkeiten 7
| Registry | Paket | Versionsvorgabe | Manifest |
|---|---|---|---|
| PyPI | numpy | >=1.24,<3 | pyproject.toml |
| PyPI | numpy | >=1.16,<3 | pyproject.toml |
| PyPI | pandas | >=1.4,<3 | pyproject.toml |
| PyPI | pydantic | >=1.7,<3 | pyproject.toml |
| PyPI | tqdm | ~=4.23 | pyproject.toml |
| PyPI | toolz | ~=0.10 | pyproject.toml |
| PyPI | typing-extensions | ~=4.0 | pyproject.toml |
Alle Abhängigkeiten 66
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 8 direkte und 58 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
| Registry | Paket | Version | Beziehung |
|---|---|---|---|
| PyPI | numpy | — | direkt |
| PyPI | numpy | 1.22.0 | direkt |
| PyPI | pandas | — | direkt |
| PyPI | pandas | 1.1.5 | direkt |
| PyPI | pydantic | — | direkt |
| PyPI | toolz | — | direkt |
| PyPI | tqdm | — | direkt |
| PyPI | typing-extensions | — | direkt |
| PyPI | autogluon-tabular | — | indirekt |
| PyPI | black | — | indirekt |
| PyPI | boto3 | — | indirekt |
| PyPI | botocore | — | indirekt |
| PyPI | catch22 | — | indirekt |
| PyPI | click | — | indirekt |
| PyPI | cython | — | indirekt |
| PyPI | docutils | — | indirekt |
| PyPI | flask | — | indirekt |
| PyPI | furo | 2022.6.4.1 | indirekt |
| PyPI | geomloss | — | indirekt |
| PyPI | gluonts | — | indirekt |
| PyPI | hierarchicalforecast | — | indirekt |
| PyPI | holidays | — | indirekt |
| PyPI | ipykernel | — | indirekt |
| PyPI | isort | — | indirekt |
| PyPI | jupyter | — | indirekt |
| PyPI | lightgbm | — | indirekt |
| PyPI | lightkit | — | indirekt |
| PyPI | lightning | — | indirekt |
| PyPI | lxml | — | indirekt |
| PyPI | matplotlib | — | indirekt |
| PyPI | matplotlib | 3.3.2 | indirekt |
| PyPI | mxnet | — | indirekt |
| PyPI | mypy | 1.8.0 | indirekt |
| PyPI | nbconvert | — | indirekt |
| PyPI | nbsphinx | — | indirekt |
| PyPI | optuna | — | indirekt |
| PyPI | prophet | — | indirekt |
| PyPI | pylint | — | indirekt |
| PyPI | pytest | — | indirekt |
| PyPI | pytest-cov | — | indirekt |
| PyPI | pytest-rerunfailures | — | indirekt |
| PyPI | pytest-runner | — | indirekt |
| PyPI | pytest-timeout | — | indirekt |
| PyPI | pytest-xdist | — | indirekt |
| PyPI | python-dotenv | — | indirekt |
| PyPI | pytorch-lightning | — | indirekt |
| PyPI | pytorchts | 0.2.0 | indirekt |
| PyPI | requests | — | indirekt |
| PyPI | rpy2 | — | indirekt |
| PyPI | ruff | 0.2.2 | indirekt |
| PyPI | s3fs | — | indirekt |
| PyPI | sagemaker | — | indirekt |
| PyPI | scikit-learn | — | indirekt |
| PyPI | scipy | 1.10.0 | indirekt |
| PyPI | seaborn | — | indirekt |
| PyPI | setuptools | — | indirekt |
| PyPI | sklearn | — | indirekt |
| PyPI | sphinx | — | indirekt |
| PyPI | statsforecast | — | indirekt |
| PyPI | statsmodels | — | indirekt |
| PyPI | tensorboard | — | indirekt |
| PyPI | tensorboard | 2.3.0 | indirekt |
| PyPI | torch | — | indirekt |
| PyPI | waitress | — | indirekt |
| PyPI | xgboost | — | indirekt |
| PyPI | xlrd | — | indirekt |
Abhängigkeits-Advisories 0
Die Installation von pypi:gluonts@0.16.3 zieht 13 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
{
"data": {
"repo": {
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"time-series",
"deep-learning",
"forecasting",
"neural-networks",
"machine-learning",
"time-series-prediction",
"time-series-forecasting",
"mxnet",
"pytorch",
"aws",
"sagemaker",
"timeseries",
"artificial-intelligence",
"data-science",
"torch"
],
"is_fork": false,
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"location": "Seattle, WA",
"followers": 11285,
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"created_at": "2013-01-17T19:11:21Z",
"is_verified": null,
"public_repos": 1019,
"account_age_days": 4932
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"license": {
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"scorecard_found": true,
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"activity": {
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},
"ecosystem": {
"packages": [
{
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"exists": true,
"license": "Apache License 2.0",
"keywords": [],
"ecosystem": "pypi",
"matches_repo": true,
"registry_url": "https://pypi.org/project/gluonts/",
"is_deprecated": false,
"latest_version": "0.16.3",
"repository_url": "https://github.com/awslabs/gluonts/",
"versions_count": 112,
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"dependents_count": null,
"deprecation_note": null,
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],
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]
}
],
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},
{
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"weight": 0.18,
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{
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}
],
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{
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"points": 24.3,
"status": "partial",
"details": [
{
"code": "forks",
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"count": 823
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}
],
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{
"key": "watchers",
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}
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]
},
{
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"note": null,
"notes": [],
"value": 92,
"inputs": {
"has_readme": true,
"has_license": true,
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"components": [
{
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{
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{
"code": "license_spdx",
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],
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{
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{
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{
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},
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"notes": [
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"count": 8485649,
"ecosystems": "pypi"
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}
],
"max_points": 80
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{
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"points": 0,
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],
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},
{
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"value": 84,
"weight": 0.24,
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{
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"note": null,
"notes": [],
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"contributors_sampled": 100,
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"components": [
{
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],
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{
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"status": "partial",
"details": [
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}
],
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{
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}
],
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{
"key": "openssf_scorecard_contributors",
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"status": "met",
"details": [],
"max_points": 10
}
]
},
{
"key": "responsiveness",
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"note": null,
"notes": [],
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"inputs": {
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"open_issues": 344,
"closed_issues": 641,
"issue_closed_ratio": 0.651,
"closed_unmerged_prs": 166
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"components": [
{
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"points": 30.4,
"status": "partial",
"details": [
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"share": 65
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}
],
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{
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"status": "partial",
"details": [
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"code": "decided_prs_merged",
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"decided": 1749
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],
"max_points": 38.25
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{
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"status": "partial",
"details": [],
"max_points": 15
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]
},
{
"key": "stewardship",
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"note": null,
"notes": [],
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"inputs": {
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"is_verified": null,
"owner_login": "awslabs",
"public_repos": 1019,
"account_age_days": 4932
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"components": [
{
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{
"code": "owner_organization",
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}
],
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{
"key": "verified_domain",
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"detail": null,
"points": 0,
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},
{
"key": "owner_reach",
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{
"key": "track_record",
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"points": 25,
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},
{
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]
},
{
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"note": null,
"notes": [],
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"inputs": {
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"min_days_since_publish": 21
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"components": [
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"key": "published_resolvable",
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"code": "packages_published",
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"ecosystems": "pypi"
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}
],
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{
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{
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"days": 21
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}
],
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{
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{
"code": "published_versions",
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}
],
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{
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],
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}
],
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},
{
"key": "engineering",
"band": "good",
"name": "Engineering Quality",
"value": 72,
"weight": 0.2,
"metrics": [
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"key": "engineering_practices",
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"name": "Engineering practices",
"note": null,
"notes": [],
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"inputs": {
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"code": "ci_workflows",
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{
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{
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{
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{
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]
},
{
"key": "documentation",
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"notes": [],
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"inputs": {
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"components": [
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{
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}
],
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]
}
],
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{
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"value": 71,
"weight": 0.16,
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},
{
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],
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"components": [
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"status": "met",
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},
{
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"status": "partial",
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{
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{
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"points": 0,
"status": "missed",
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},
{
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"status": "partial",
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},
{
"key": "contributors",
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"details": [],
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},
{
"key": "dangerous_workflow",
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"details": [],
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},
{
"key": "dependency_update_tool",
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"detail": "update tool detected",
"points": 7.5,
"status": "met",
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},
{
"key": "fuzzing",
"name": "Fuzzing",
"detail": "project is not fuzzed",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "license",
"name": "License",
"detail": "license file detected",
"points": 2.5,
"status": "met",
"details": [],
"max_points": 2.5
},
{
"key": "maintained",
"name": "Maintained",
"detail": "11 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 9",
"points": 6.8,
"status": "partial",
"details": [],
"max_points": 7.5
},
{
"key": "packaging",
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"detail": "packaging workflow detected",
"points": 5,
"status": "met",
"details": [],
"max_points": 5
},
{
"key": "pinned_dependencies",
"name": "Pinned-Dependencies",
"detail": "dependency not pinned by hash detected -- score normalized to 0",
"points": 0,
"status": "missed",
"details": [],
"max_points": 5
},
{
"key": "sast",
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"detail": "SAST tool detected but not run on all commits",
"points": 4,
"status": "partial",
"details": [],
"max_points": 5
},
{
"key": "security_policy",
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"detail": "security policy file detected",
"points": 5,
"status": "met",
"details": [],
"max_points": 5
},
{
"key": "signed_releases",
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"detail": "no releases found",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
}
],
"max_points": 7.5
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{
"key": "token_permissions",
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"detail": "detected GitHub workflow tokens with excessive permissions",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
},
{
"key": "vulnerabilities",
"name": "Vulnerabilities",
"detail": "24 existing vulnerabilities detected",
"points": 0,
"status": "missed",
"details": [],
"max_points": 7.5
}
]
},
{
"key": "dependency_advisories",
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"name": "Dependency advisories",
"note": "Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:gluonts@0.16.3 runtime dependency closure — what installing the published package pulls in — 13 packages. Reachability is not analyzed.",
"notes": [
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"code": "excluded_no_data",
"params": {
"components": [
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}
},
{
"code": "weights_renormalized",
"params": {}
},
{
"code": "advisories_scope_published",
"params": {
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"assessed": 13
}
},
{
"code": "advisories_reachability",
"params": {}
}
],
"value": 100,
"inputs": {
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"advisories": 0,
"affected_packages": 0,
"assessed_packages": 13,
"unassessed_packages": 0,
"affected_by_severity": "none",
"direct_affected_packages": 0
},
"components": [
{
"key": "direct_dependencies_free_of_known_advisories",
"name": "Direct dependencies free of known advisories",
"detail": "no direct dependency carries a known advisory",
"points": 35,
"status": "met",
"details": [
{
"code": "no_direct_advisories",
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}
],
"max_points": 35
},
{
"key": "indirect_dependencies_free_of_known_advisories",
"name": "Indirect dependencies free of known advisories",
"detail": "no indirect dependency carries a known advisory",
"points": 25,
"status": "met",
"details": [
{
"code": "no_indirect_advisories",
"params": {}
}
],
"max_points": 25
},
{
"key": "no_advisories_left_outstanding",
"name": "No advisories left outstanding",
"detail": "no advisory carries a publication date",
"points": 0,
"status": "excluded",
"details": [
{
"code": "advisories_no_publication_date",
"params": {}
}
],
"max_points": 40
}
]
},
{
"key": "malicious_dependencies",
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"name": "Malicious dependencies",
"note": null,
"notes": [],
"value": 100,
"inputs": {
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"packages": [],
"red_flag": false,
"assessed_packages": 13,
"malicious_packages": 0,
"direct_malicious_packages": 0,
"withdrawn_malicious_packages": 0,
"installable_malicious_packages": 0
},
"components": [
{
"key": "no_dependency_reported_as_a_malicious_package",
"name": "No dependency reported as a malicious package",
"detail": "no dependency is reported as a malicious package",
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"details": [
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"code": "no_malicious_dependencies",
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}
],
"max_points": 100
}
]
},
{
"key": "high_risk_jurisdiction_exposure",
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"name": "High-Risk Jurisdiction Exposure",
"note": "Only high-confidence self-published location evidence affects this multiplier. Ambiguous matches are review-only; country evidence is not proof of nationality, citizenship, legal registration, malicious intent, or sanctions status.",
"notes": [
{
"code": "jurisdiction_evidence_limits",
"params": {}
}
],
"value": 100,
"inputs": {
"meaning": "self-published location evidence; not nationality or citizenship",
"red_flag": false,
"exposures": [],
"policy_countries": [
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"Iran",
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"review_only_matches": 0,
"assessed_self_published_locations": 9
},
"components": [
{
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}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 v0.16.0 — vollständige Methodik · Metriken-Wiki.
Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken — PyPI.