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Software-GesundheitsberichtSchema 0.17.0 · Metriken 1.13.0 · 2026-07-21 04:42 UTC

PriorLabs / tabpfn_common_utils

Shared Python utilities used across the TabPFN ecosystem — data helpers, regression result handling, cost estimation, and optional telemetry.

PythonApache-2.0★ 0 Sterne⑂ 4 Forksseit Aug. 2023Auf GitHub ansehen ↗

PriorLabs/tabpfn_common_utils erreicht einen Gesundheitsindex von 66 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Vitality (81/100) ab, am schwächsten bei Community & Adoption (29/100). Zuletzt vor 28 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.

66
gesamt / 100
Mittel

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.

66
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

Prior LabsOrganisation
380 Follower11 öffentliche Reposseit Sept. 2023

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

Paket-Ökosysteme

RegistryPaketVersionDownloads / MonatVersionenZuletzt veröffentlichtTags
PyPItabpfn-common-utils0.2.23-31vor 28 Tagenmachine-learningtabpfnutilities

Metriken nach Kategorie

Vitalität

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

81Gut · 22 % des Gesamtindex
Wie die Bewertung erfolgt
28.8/36Push-Aktualität — letzter Push vor 28 Tagen
18/36Commit-Rhythmus — 26/52 Wochen mit Commits
18/18Commit-Volumen — 223 Commits im letzten Jahr
10/10OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
Verwendete Eingangsdaten
commits_last_year223
human_commit_share
days_since_last_push28
active_weeks_last_year26
Wie die Bewertung erfolgt
27/27Liefert Releases aus — 6 Releases veröffentlicht
27/36Release-Aktualität — letztes Release vor 157 Tagen
27/27Release-Rhythmus — ein Release etwa alle 16,8 Tage
0/10OpenSSF Scorecard: Signed-Releases — keine Daten
Verwendete Eingangsdaten
releases_count6
latest_release_tagv0.2.16
releases_from_tagsnein
days_since_latest_release157
mean_days_between_releases16,8
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?

29Kritisch · 18 % des Gesamtindex
Wie die Bewertung erfolgt
0/60Stars — 0 Stars
4/25Forks — 4 Forks
0/15Watcher — 2 Watcher
Verwendete Eingangsdaten
forks4
stars0
watchers2
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)
0/18CONTRIBUTING-Leitfaden
0/13.5Verhaltenskodex
0/7.2Issue-Vorlage
6.3/6.3PR-Vorlage
Verwendete Eingangsdaten
has_readmeja
has_licenseja
has_contributingnein
has_issue_templatenein
has_code_of_conductnein
has_pull_request_templateja

Nachhaltigkeit & Governance

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

68Mittel · 24 % des Gesamtindex
Wie die Bewertung erfolgt
9/54Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab
7.1/22.5Commit-Verteilung — wichtigste beitragende Person verfasste 69 % der Commits
13.5/13.5Breite der Beitragenden — 14 Beitragende
6/10OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6
Verwendete Eingangsdaten
bus_factor1
contributors_sampled14
top_contributor_share0,686
Wie die Bewertung erfolgt
46.8/46.8Issue-Lösungsquote — 100 % der Issues geschlossen
34.7/38.3PR-Annahme — 69/76 entschiedene PRs gemergt
6/15OpenSSF Scorecard: Code-Review — Found 4/9 approved changesets -- score normalized to 4
Verwendete Eingangsdaten
merged_prs69
open_issues0
closed_issues1
issue_closed_ratio1
closed_unmerged_prs7
Wie die Bewertung erfolgt
30/30Organisatorische Trägerschaft — im Besitz einer Organisation
0/20Verifizierte Domain
18.6/25Reichweite des Inhabers — 380 Follower von PriorLabs
13.6/25Kontohistorie — 11 öffentliche Repos, Kontoalter ca. 2 Jahre
Verwendete Eingangsdaten
followers380
owner_typeOrganization
is_verified
owner_loginPriorLabs
public_repos11
account_age_days1.047

Paketpflege

100Exzellent
Wie die Bewertung erfolgt
25/25Veröffentlicht & auflösbar — 1 Paket(e) auf pypi
35/35Veröffentlichungsaktualität — letzte Veröffentlichung vor 28 Tagen
20/20Versionshistorie — 31 veröffentlichte Versionen
20/20Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen
Verwendete Eingangsdaten
packagestabpfn-common-utils
ecosystemspypi
any_deprecatednein
min_days_since_publish28

Engineering-Qualität

Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?

76Gut · 20 % des Gesamtindex
Wie die Bewertung erfolgt
24/24CI-Workflows — 2 Workflow(s)
24/24Tests vorhanden
16/16Linter-Konfiguration
9.6/9.6Pre-Commit-Hooks
0/6.4.editorconfig
20/20OpenSSF Scorecard: CI-Tests — 11 out of 11 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
Wie die Bewertung erfolgt
30/30README
0/25Dokumentationsverzeichnis
0/15Dokumentations-/Homepage-Site
10/10Repository-Beschreibung
0/10Topics
10/10Wiki
Verwendete Eingangsdaten
topics
has_wikija
homepage
has_readmeja
has_docs_dirnein
has_descriptionja

Sicherheit

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

69Mittel · 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 — 11 out of 11 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
3/7.5Code-Review — Found 4/9 approved changesets -- score normalized to 4
1.5/2.5Contributors — project has 2 contributing companies or organizations -- score normalized to 6
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 0 issue activity found in the last 90 days -- score normalized to 10
5/5Packaging — packaging workflow detected
0.5/5Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
1/5SAST — SAST tool is not run on all commits -- score normalized to 2
5/5Security-Policy — security policy file detected
0/7.5Signed-Releases — keine Daten
0/7.5Token-Permissions — detected GitHub workflow tokens with excessive permissions
1.5/7.5Vulnerabilities — 8 existing vulnerabilities detected
Verwendete Eingangsdaten
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate6,1
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection, signed_releases. Die verbleibenden Gewichte wurden renormalisiert.
Wie die Bewertung erfolgt
35/35Direkte Abhängigkeiten ohne bekannte Advisories — keine direkte Abhängigkeit trägt ein bekanntes Advisory
25/25Indirekte Abhängigkeiten ohne bekannte Advisories — keine indirekte Abhängigkeit trägt ein bekanntes Advisory
0/40Keine offenen Advisories — kein Advisory trägt ein Veröffentlichungsdatum
Verwendete Eingangsdaten
sourceosv
advisories0
affected_packages0
assessed_packages21
unassessed_packages0
affected_by_severitynone
direct_affected_packages0
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Keine offenen Advisories. Die verbleibenden Gewichte wurden renormalisiert. Abgeglichen wurde die Laufzeit-Abhängigkeitshülle von pypi:tabpfn-common-utils@0.2.23 — das, was die Installation des veröffentlichten Pakets nach sich zieht — mit 21 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.

46Gefährdet · 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
0/18Bootstrap mit einem Befehl
22/22Automatisierte Tests
11/11Lint-/Format-Konfiguration
11/11Statische Typprüfung — src/tabpfn_common_utils/py.typed
10/10Reproduzierbare Umgebung — lockfile
0/10Belegte Agentenpraxis — keine Daten
0/8Automatisierte Wartung — keine Daten
1/10OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 1
Verwendete Eingangsdaten
has_nixnein
has_testsja
lockfilesuv.lock
has_dockerfilenein
typed_languagenein
bootstrap_files
has_devcontainernein
has_linter_configja
typecheck_configssrc/tabpfn_common_utils/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
27/45Typprüfbarer Code — Python mit Typprüfungs-Konfiguration (src/tabpfn_common_utils/py.typed)
55/55Handhabbare Dateigrößen — 0/26 Quelldateien über 60 KB
Verwendete Eingangsdaten
primary_languagePython
largest_source_bytes17.783
source_files_sampled26
oversized_source_files0

Eckdaten

0GitHub-Sterne
14Mitwirkende
223Commits, letzte 12 Monate
28Tage seit letztem Push
6Releases
1Bus-Faktor
0offene Issues
PyPIPaket-Ökosysteme

Weitere Details

OpenSSF Scorecard 6.1 / 10
6.1Gesamtwert

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 · 2026-07-21 04:42 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-Tests11 out of 11 merged PRs checked by a CI test -- score normalized to 10
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
4Code-ReviewFound 4/9 approved changesets -- score normalized to 4
6Contributorsproject has 2 contributing companies or organizations -- score normalized to 6
10Dangerous-Workflowno dangerous workflow patterns detected
10Dependency-Update-Toolupdate tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
10Maintained30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10
10Packagingpackaging workflow detected
1Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 1
2SASTSAST tool is not run on all commits -- score normalized to 2
10Security-Policysecurity policy file detected
k. A.Signed-Releasesno releases found
0Token-Permissionsdetected GitHub workflow tokens with excessive permissions
2Vulnerabilities8 existing vulnerabilities detected
Direkte Abhängigkeiten 9
RegistryPaketVersionsvorgabeManifest
PyPInumpy>=1.21.6pyproject.toml
PyPIpandas>=1.4.0pyproject.toml
PyPIscikit-learn>=1.2.0pyproject.toml
PyPItyping-extensions>=4.12pyproject.toml
PyPIposthog>=6.7pyproject.toml
PyPIplatformdirs>=4pyproject.toml
PyPIfilelock>=3.19.1pyproject.toml
PyPIrequests>=2.32.5pyproject.toml
PyPInvidia-ml-py>=13.590.48pyproject.toml
Alle Abhängigkeiten 68

Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 9 direkte und 59 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.

RegistryPaketVersionBeziehung
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PyPIpandas2.3.3direkt
PyPIplatformdirs4.4.0direkt
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PyPItyping-extensions4.15.0direkt
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PyPIcertifi2026.2.25indirekt
PyPIcffi2.0.0indirekt
PyPIcharset-normalizer3.4.7indirekt
PyPIcolorama0.4.6indirekt
PyPIcoverage7.10.7indirekt
PyPIcryptography46.0.7indirekt
PyPIdistro1.9.0indirekt
PyPIdocutils0.22.4indirekt
PyPIexceptiongroup1.3.1indirekt
PyPIhatch-vcs0.5.0indirekt
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PyPIidna3.15indirekt
PyPIimportlib-metadata8.7.1indirekt
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PyPIkeyring25.7.0indirekt
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PyPImore-itertools10.8.0indirekt
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PyPIpackaging26.0indirekt
PyPIpathspec1.0.4indirekt
PyPIpluggy1.6.0indirekt
PyPIpycparser2.23indirekt
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PyPIpyproject-hooks1.2.0indirekt
PyPIpyright1.1.408indirekt
PyPIpytest8.4.2indirekt
PyPIpytest-cov7.1.0indirekt
PyPIpython-dateutil2.9.0.post0indirekt
PyPIpytz2026.1.post1indirekt
PyPIpywin32-ctypes0.2.3indirekt
PyPIreadme-renderer44.0indirekt
PyPIrequests-toolbelt1.0.0indirekt
PyPIrfc39862.0.0indirekt
PyPIrich15.0.0indirekt
PyPIruff0.15.10indirekt
PyPIscipy1.13.1indirekt
PyPIsecretstorage3.3.3indirekt
PyPIsetuptools82.0.1indirekt
PyPIsetuptools-scm9.2.2indirekt
PyPIsix1.17.0indirekt
PyPIthreadpoolctl3.6.0indirekt
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PyPItrove-classifiers2026.1.14.14indirekt
PyPItwine6.2.0indirekt
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PyPIvcs-versioning1.1.1indirekt
PyPIzipp3.23.1indirekt
Abhängigkeits-Advisories 0

Die Installation von pypi:tabpfn-common-utils@0.2.23 zieht 21 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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                "key": "fuzzing",
                "name": "Fuzzing",
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                "max_points": 7.5
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                "key": "token_permissions",
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                "key": "vulnerabilities",
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            "value": 100,
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              "affected_by_severity": "none",
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            "components": [
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