Öffentliches RegisterMittel
Software-GesundheitsberichtSchema 0.27.0 · Metriken 1.13.0 · 2026-07-29 04:13 UTC
mdefrance / AutoCarver
Automatic optimal discretization pipeline
mdefrance/AutoCarver erreicht einen Gesundheitsindex von 65 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Engineering Quality (96/100) ab, am schwächsten bei Community & Adoption (32/100). Zuletzt heute 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
Mario DefrancePersönliches Konto
10 Follower4 öffentliche Reposseit Nov. 2020Coface
Dieses Repository gehört einem persönlichen Konto. Ein Projekt mit nur einem Eigentümer trägt ein höheres Kontinuitätsrisiko als ein organisationsgetragenes.
Paket-Ökosysteme
| Registry | Paket | Version | Downloads / Monat | Versionen | Zuletzt veröffentlicht | Tags |
|---|---|---|---|---|---|---|
| PyPI | AutoCarver | 7.6.0 | - | 132 | vor 0 Tagen | binningdiscretizationfeature-engineeringcredit-scoringwoescorecardstschuprowtschuprow-tcramer-vinformation-valueivmonotonic-binningsupervised-discretizationbucketizationrisk-modelingcredit-riskfraud-detectioncategorical-encodingsupervised-binningweight-of-evidencefeature-selectionmcpmodel-context-protocol |
Metriken nach Kategorie
Vitalität
Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?
81
Entwicklungsaktivität
69Mittel
Wie die Bewertung erfolgt
| 36/36 | Push-Aktualität — letzter Push vor 0 Tagen |
| 6.2/36 | Commit-Rhythmus — 9/52 Wochen mit Commits |
| 16.4/18 | Commit-Volumen — 66 Commits im letzten Jahr |
| 10/10 | OpenSSF Scorecard: Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
Verwendete Eingangsdaten
| commits_last_year | 66 |
| human_commit_share | 1 |
| days_since_last_push | 0 |
| active_weeks_last_year | 9 |
Release-Disziplin
100Exzellent
Wie die Bewertung erfolgt
| 27/27 | Liefert Releases aus — 83 Releases veröffentlicht |
| 36/36 | Release-Aktualität — letztes Release vor 0 Tagen |
| 27/27 | Release-Rhythmus — ein Release etwa alle 3,4 Tage |
| 0/10 | OpenSSF Scorecard: Signed-Releases — keine Daten |
Verwendete Eingangsdaten
| releases_count | 83 |
| latest_release_tag | 7.6.0 |
| releases_from_tags | nein |
| days_since_latest_release | 0 |
| mean_days_between_releases | 3,4 |
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?
32
Popularität & Verbreitung
16Kritisch
Wie die Bewertung erfolgt
| 16.2/60 | Stars — 11 Stars |
| 0/25 | Forks — 0 Forks |
| 0/15 | Watcher — 2 Watcher |
Verwendete Eingangsdaten
| forks | 0 |
| stars | 11 |
| watchers | 2 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community-Gesundheit
50Mittel
Wie die Bewertung erfolgt
| 22.5/22.5 | README |
| 22.5/22.5 | Lizenz — anerkannte Lizenz (MIT) |
| 0/18 | CONTRIBUTING-Leitfaden |
| 0/13.5 | Verhaltenskodex |
| 0/7.2 | Issue-Vorlage |
| 0/6.3 | PR-Vorlage |
Verwendete Eingangsdaten
| has_readme | ja |
| has_license | ja |
| has_contributing | nein |
| has_issue_template | nein |
| has_code_of_conduct | nein |
| has_pull_request_template | nein |
Nachhaltigkeit & Governance
Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?
55
Maintainer-Resilienz (Bus-Faktor)
13Kritisch
Wie die Bewertung erfolgt
| 9/54 | Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab |
| 0/22.5 | Commit-Verteilung — wichtigste beitragende Person verfasste 100 % der Commits |
| 1.4/13.5 | Breite der Beitragenden — 1 Beitragende |
| 3/10 | OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3 |
Verwendete Eingangsdaten
| bus_factor | 1 |
| contributors_sampled | 1 |
| top_contributor_share | 1 |
Wie die Bewertung erfolgt
| 46.8/46.8 | Issue-Lösungsquote — 100 % der Issues geschlossen |
| 36.5/38.3 | PR-Annahme — 125/131 entschiedene PRs gemergt |
| 0/15 | OpenSSF Scorecard: Code-Review — Found 0/30 approved changesets -- score normalized to 0 |
Verwendete Eingangsdaten
| merged_prs | 125 |
| open_issues | 0 |
| closed_issues | 12 |
| issue_closed_ratio | 1 |
| closed_unmerged_prs | 6 |
Eigentümerschaft & Trägerschaft
42Gefährdet
Wie die Bewertung erfolgt
| 10/30 | Organisatorische Trägerschaft — persönliches (Nutzer-)Konto |
| 0/20 | Verifizierte Domain — für Nutzerkonten nicht anwendbar |
| 7.5/25 | Reichweite des Inhabers — 10 Follower von mdefrance |
| 16.5/25 | Kontohistorie — 4 öffentliche Repos, Kontoalter ca. 5 Jahre |
Verwendete Eingangsdaten
| followers | 10 |
| owner_type | User |
| is_verified | — |
| owner_login | mdefrance |
| public_repos | 4 |
| account_age_days | 2.081 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Verifizierte Domain. Die verbleibenden Gewichte wurden renormalisiert.
Paketpflege
100Exzellent
Wie die Bewertung erfolgt
| 25/25 | Veröffentlicht & auflösbar — 1 Paket(e) auf pypi |
| 35/35 | Veröffentlichungsaktualität — letzte Veröffentlichung vor 0 Tagen |
| 20/20 | Versionshistorie — 132 veröffentlichte Versionen |
| 20/20 | Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen |
Verwendete Eingangsdaten
| packages | AutoCarver |
| ecosystems | pypi |
| any_deprecated | nein |
| min_days_since_publish | 0 |
Engineering-Qualität
Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?
96
Engineering-Praktiken
94Exzellent
Wie die Bewertung erfolgt
| 24/24 | CI-Workflows — 2 Workflow(s) |
| 24/24 | Tests vorhanden |
| 16/16 | Linter-Konfiguration |
| 9.6/9.6 | Pre-Commit-Hooks |
| 0/6.4 | .editorconfig |
| 20/20 | OpenSSF Scorecard: CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10 |
Verwendete Eingangsdaten
| has_ci | ja |
| has_tests | ja |
| has_editorconfig | nein |
| has_linter_config | ja |
| has_precommit_config | ja |
Dokumentation
100Exzellent
Wie die Bewertung erfolgt
| 30/30 | README |
| 25/25 | Dokumentationsverzeichnis |
| 15/15 | Dokumentations-/Homepage-Site — https://autocarver.readthedocs.io |
| 10/10 | Repository-Beschreibung |
| 10/10 | Topics — 15 Topics |
| 10/10 | Wiki |
Verwendete Eingangsdaten
| topics | binning, categorical-encoding, cramer, credit-risk, discretization, feature-engineering, fraud-detection, information-value, risk-modeling, scorecard, scorecards, woe, bucketization, tschuprow, kurskal-wallis |
| has_wiki | ja |
| homepage | https://autocarver.readthedocs.io |
| has_readme | ja |
| has_docs_dir | ja |
| has_description | ja |
Sicherheit
Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?
58
Sicherheitslage
47Gefährdet
Wie die Bewertung erfolgt
| 7.5/7.5 | Binary-Artifacts — no binaries found in the repo |
| 0/7.5 | Branch-Protection — keine Daten |
| 2.5/2.5 | CI-Tests — 30 out of 30 merged PRs checked by a CI test -- score normalized to 10 |
| 0/2.5 | CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected |
| 0/7.5 | Code-Review — Found 0/30 approved changesets -- score normalized to 0 |
| 0.8/2.5 | Contributors — project has 1 contributing companies or organizations -- score normalized to 3 |
| 10/10 | Dangerous-Workflow — no dangerous workflow patterns detected |
| 0/7.5 | Dependency-Update-Tool — no update tool detected |
| 0/5 | Fuzzing — project is not fuzzed |
| 2.5/2.5 | Lizenz — license file detected |
| 7.5/7.5 | Maintained — 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| 5/5 | Packaging — packaging workflow detected |
| 0/5 | Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0 |
| 0/5 | SAST — SAST tool is not run on all commits -- score normalized to 0 |
| 0/5 | Security-Policy — security policy file not detected |
| 0/7.5 | Signed-Releases — keine Daten |
| 0/7.5 | Token-Permissions — detected GitHub workflow tokens with excessive permissions |
| 6.8/7.5 | Vulnerabilities — 1 existing vulnerabilities detected |
Verwendete Eingangsdaten
| source | openssf_scorecard |
| checks_evaluated | 16 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 2 |
| scorecard_aggregate | 4,7 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection, 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 |
| 0/25 | Indirekte Abhängigkeiten ohne bekannte Advisories — transitive Menge in diesem Bereich nicht von Entwicklungs- und Test-Abhängigkeiten trennbar |
| 0/40 | Keine offenen Advisories — kein Advisory trägt ein Veröffentlichungsdatum |
Verwendete Eingangsdaten
| source | osv |
| advisories | 2 |
| affected_packages | 1 |
| assessed_packages | 195 |
| unassessed_packages | 0 |
| affected_by_severity | moderate 1 |
| direct_affected_packages | 0 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Indirekte Abhängigkeiten ohne bekannte Advisories, Keine offenen Advisories. Die verbleibenden Gewichte wurden renormalisiert. 195 aufgelöste Abhängigkeiten wurden mit OSV abgeglichen. 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.
48
AI-Agentenkontext & Leitlinien
32Gefährdet
Wie die Bewertung erfolgt
| 0/45 | Agentenanweisungen — keine CLAUDE.md / AGENTS.md / Editor-Regeln |
| 0/15 | Maschinenlesbare Doku (llms.txt) |
| 31.5/40 | Lesbare Commit-Historie — 59 von 100 menschlichen Commits benennen ihre Absicht (strukturierter Betreff oder erläuternder Text) |
Verwendete Eingangsdaten
| has_llms_txt | nein |
| legible_history_share | 0,59 |
| agent_instruction_files | — |
| agent_instruction_max_bytes | — |
Wie die Bewertung erfolgt
| 18/18 | Bootstrap mit einem Befehl — docs/Makefile |
| 22/22 | Automatisierte Tests |
| 11/11 | Lint-/Format-Konfiguration |
| 0/11 | Statische Typprüfung |
| 10/10 | Reproduzierbare Umgebung — lockfile |
| 0/10 | Belegte Agentenpraxis — keine von Agenten verfassten Commits unter den letzten 100 |
| 0/8 | Automatisierte Wartung — keine automatisierten Abhängigkeits-Updates beobachtet |
| 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 | uv.lock |
| has_dockerfile | nein |
| typed_language | nein |
| bootstrap_files | docs/Makefile |
| has_devcontainer | nein |
| has_linter_config | ja |
| typecheck_configs | — |
| agent_commit_share | 0 |
| toolchain_manifests | — |
| dependency_bot_commit_share | 0 |
AI-Code-Lesbarkeit für Modelle
55Mittel
Wie die Bewertung erfolgt
| 0/45 | Typprüfbarer Code — Python ohne Typprüfungs-Konfiguration |
| 54.7/55 | Handhabbare Dateigrößen — 1/206 Quelldateien über 60 KB |
Verwendete Eingangsdaten
| primary_language | Python |
| largest_source_bytes | 63.423 |
| source_files_sampled | 206 |
| 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
11GitHub-Sterne
1Mitwirkende
66Commits, letzte 12 Monate
0Tage seit letztem Push
83Releases
1Bus-Faktor
0offene Issues
PyPIPaket-Ökosysteme
Warnungen zur Datenerhebung
- Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
- deps.dev does not index pypi:AutoCarver@7.6.0; advisories assessed against the repository dependency graph instead
Weitere Details
OpenSSF Scorecard 4.7 / 10
4.7Gesamtwert
Unabhängige, werkzeugneutrale Sicherheitsbewertung durch das quelloffene OpenSSF Scorecard. Jede Prüfung honoriert eine Sicherheits-Praxis, nicht das Werkzeug eines bestimmten Anbieters. Prüfungen, die Scorecard nicht ermitteln konnte, sind mit k. A. markiert und vom Sicherheitswert ausgeschlossen (nie als null gezählt).
| 10 | Binary-Artifacts | no binaries found in the repo |
| k. A. | Branch-Protection | internal 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 |
| 10 | CI-Tests | 30 out of 30 merged PRs checked by a CI test -- score normalized to 10 |
| 0 | CII-Best-Practices | no effort to earn an OpenSSF best practices badge detected |
| 0 | Code-Review | Found 0/30 approved changesets -- score normalized to 0 |
| 3 | Contributors | project has 1 contributing companies or organizations -- score normalized to 3 |
| 10 | Dangerous-Workflow | no dangerous workflow patterns detected |
| 0 | Dependency-Update-Tool | no update tool detected |
| 0 | Fuzzing | project is not fuzzed |
| 10 | License | license file detected |
| 10 | Maintained | 30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| 10 | Packaging | packaging workflow detected |
| 0 | Pinned-Dependencies | dependency not pinned by hash detected -- score normalized to 0 |
| 0 | SAST | SAST tool is not run on all commits -- score normalized to 0 |
| 0 | Security-Policy | security policy file not detected |
| k. A. | Signed-Releases | no releases found |
| 0 | Token-Permissions | detected GitHub workflow tokens with excessive permissions |
| 9 | Vulnerabilities | 1 existing vulnerabilities detected |
Direkte Abhängigkeiten 6
| Registry | Paket | Versionsvorgabe | Manifest |
|---|---|---|---|
| PyPI | numpy | >=2.1,<2.5 | pyproject.toml |
| PyPI | scipy | >=1.15,<1.18 | pyproject.toml |
| PyPI | pandas | >=2.3,<3.1,!=3.0.4 | pyproject.toml |
| PyPI | scikit-learn | >=1.6,<1.9 | pyproject.toml |
| PyPI | statsmodels | >=0.14.1,<1 | pyproject.toml |
| PyPI | tqdm | >=4.66,<5 | pyproject.toml |
Alle Abhängigkeiten 195
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 6 direkte und 189 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
| Registry | Paket | Version | Beziehung |
|---|---|---|---|
| PyPI | numpy | 2.4.6 | direkt |
| PyPI | pandas | 3.0.3 | direkt |
| PyPI | scikit-learn | 1.8.0 | direkt |
| PyPI | scipy | 1.17.1 | direkt |
| PyPI | statsmodels | 0.14.6 | direkt |
| PyPI | tqdm | 4.68.4 | direkt |
| PyPI | absl-py | 2.5.0 | indirekt |
| PyPI | aiofile | 3.11.1 | indirekt |
| PyPI | alabaster | 0.7.16 | indirekt |
| PyPI | annotated-types | 0.7.0 | indirekt |
| PyPI | anyio | 4.14.1 | indirekt |
| PyPI | appnope | 0.1.4 | indirekt |
| PyPI | asttokens | 3.0.1 | indirekt |
| PyPI | attrs | 26.1.0 | indirekt |
| PyPI | authlib | 1.7.2 | indirekt |
| PyPI | autocarver | 7.6.0 | indirekt |
| PyPI | babel | 2.18.0 | indirekt |
| PyPI | backports-tarfile | 1.2.0 | indirekt |
| PyPI | beartype | 0.22.9 | indirekt |
| PyPI | beautifulsoup4 | 4.15.0 | indirekt |
| PyPI | bleach | 6.4.0 | indirekt |
| PyPI | cachetools | 7.1.4 | indirekt |
| PyPI | caio | 0.9.25 | indirekt |
| PyPI | certifi | 2026.6.17 | indirekt |
| PyPI | cffi | 2.1.0 | indirekt |
| PyPI | charset-normalizer | 3.4.9 | indirekt |
| PyPI | clarabel | 0.11.1 | indirekt |
| PyPI | click | 8.4.2 | indirekt |
| PyPI | colorama | 0.4.6 | indirekt |
| PyPI | comm | 0.2.3 | indirekt |
| PyPI | contourpy | 1.3.3 | indirekt |
| PyPI | coverage | 7.15.0 | indirekt |
| PyPI | cryptography | 49.0.0 | indirekt |
| PyPI | cvxpy | 1.9.2 | indirekt |
| PyPI | cycler | 0.12.1 | indirekt |
| PyPI | cyclopts | 4.21.0 | indirekt |
| PyPI | debugpy | 1.8.21 | indirekt |
| PyPI | decorator | 5.3.1 | indirekt |
| PyPI | defusedxml | 0.7.1 | indirekt |
| PyPI | dnspython | 2.8.0 | indirekt |
| PyPI | docstring-parser | 0.18.0 | indirekt |
| PyPI | docutils | 0.20.1 | indirekt |
| PyPI | email-validator | 2.3.0 | indirekt |
| PyPI | exceptiongroup | 1.3.1 | indirekt |
| PyPI | execnet | 2.1.2 | indirekt |
| PyPI | executing | 2.2.1 | indirekt |
| PyPI | fastjsonschema | 2.21.2 | indirekt |
| PyPI | fastmcp | 3.4.4 | indirekt |
| PyPI | fastmcp-slim | 3.4.4 | indirekt |
| PyPI | fonttools | 4.63.0 | indirekt |
| PyPI | griffelib | 2.1.0 | indirekt |
| PyPI | h11 | 0.16.0 | indirekt |
| PyPI | highspy | 1.15.1 | indirekt |
| PyPI | httpcore | 1.0.9 | indirekt |
| PyPI | httpx | 0.28.1 | indirekt |
| PyPI | httpx-sse | 0.4.3 | indirekt |
| PyPI | hypothesis | 6.156.6 | indirekt |
| PyPI | icecream | 2.2.0 | indirekt |
| PyPI | idna | 3.18 | indirekt |
| PyPI | imagesize | 2.0.0 | indirekt |
| PyPI | immutabledict | 4.3.1 | indirekt |
| PyPI | importlib-metadata | 9.0.0 | indirekt |
| PyPI | iniconfig | 2.3.0 | indirekt |
| PyPI | ipykernel | 6.31.0 | indirekt |
| PyPI | ipython | 9.10.1 | indirekt |
| PyPI | ipython-pygments-lexers | 1.1.1 | indirekt |
| PyPI | ipywidgets | 8.1.8 | indirekt |
| PyPI | jaraco-classes | 3.4.0 | indirekt |
| PyPI | jaraco-context | 6.1.2 | indirekt |
| PyPI | jaraco-functools | 4.5.0 | indirekt |
| PyPI | jedi | 0.20.0 | indirekt |
| PyPI | jeepney | 0.9.0 | indirekt |
| PyPI | jinja2 | 3.1.6 | indirekt |
| PyPI | joblib | 1.5.3 | indirekt |
| PyPI | joserfc | 1.7.3 | indirekt |
| PyPI | jsonref | 1.1.0 | indirekt |
| PyPI | jsonschema | 4.26.0 | indirekt |
| PyPI | jsonschema-path | 0.5.0 | indirekt |
| PyPI | jsonschema-specifications | 2025.9.1 | indirekt |
| PyPI | jupyter-client | 8.9.1 | indirekt |
| PyPI | jupyter-core | 5.9.1 | indirekt |
| PyPI | jupyterlab-pygments | 0.3.0 | indirekt |
| PyPI | jupyterlab-widgets | 3.0.16 | indirekt |
| PyPI | jupytext | 1.19.4 | indirekt |
| PyPI | kaggle | 2.2.3 | indirekt |
| PyPI | kagglesdk | 0.1.34 | indirekt |
| PyPI | keyring | 25.7.0 | indirekt |
| PyPI | kiwisolver | 1.5.0 | indirekt |
| PyPI | markdown-it-py | 4.2.0 | indirekt |
| PyPI | markupsafe | 3.0.3 | indirekt |
| PyPI | matplotlib | 3.10.9 | indirekt |
| PyPI | matplotlib-inline | 0.2.2 | indirekt |
| PyPI | mcp | 1.28.1 | indirekt |
| PyPI | mdit-py-plugins | 0.6.1 | indirekt |
| PyPI | mdurl | 0.1.2 | indirekt |
| PyPI | mistune | 3.3.3 | indirekt |
| PyPI | more-itertools | 11.1.0 | indirekt |
| PyPI | nbclient | 0.11.0 | indirekt |
| PyPI | nbconvert | 7.17.1 | indirekt |
| PyPI | nbformat | 5.10.4 | indirekt |
| PyPI | nbsphinx | 0.9.6 | indirekt |
| PyPI | nest-asyncio | 1.6.0 | indirekt |
| PyPI | nvidia-nccl-cu12 | 2.30.7 | indirekt |
| PyPI | openapi-pydantic | 0.5.1 | indirekt |
| PyPI | opentelemetry-api | 1.43.0 | indirekt |
| PyPI | optbinning | 0.21.0 | indirekt |
| PyPI | ortools | 9.10.4067 | indirekt |
| PyPI | osqp | 1.1.3 | indirekt |
| PyPI | packaging | 26.2 | indirekt |
| PyPI | pandocfilters | 1.5.1 | indirekt |
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Abhängigkeits-Advisories 1
Dieses Repository veröffentlicht kein vom Index auflösbares Paket, daher wurde sein eigener Abhängigkeitsgraph bewertet – 195 Pakete, darunter auch Entwicklungs- und Test-Pins, die nie ausgeliefert werden: 1 tragen bekannte Advisories, davon 0 direkte.
| Paket | Version | Beziehung | Schweregrad | Advisories | Behoben in |
|---|---|---|---|---|---|
| pytest | 7.4.4 | indirekt | mittel | 2 | 9.0.3 |
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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{
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{
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#dangerous-workflow"
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{
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{
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{
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{
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{
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{
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{
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#sast"
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{
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#security-policy"
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{
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{
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"documentation_url": "https://github.com/ossf/scorecard/blob/c395761df6afe1a69e476bc60a013a94bcbc153f/docs/checks.md#token-permissions"
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{
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{
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{
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{
"key": "openssf_scorecard_contributors",
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]
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{
"key": "responsiveness",
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"notes": [],
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{
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"inputs": {
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"components": [
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]
},
{
"key": "documentation",
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"note": null,
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],
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{
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"weight": 0.16,
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{
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{
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"key": "dangerous_workflow",
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{
"key": "dependency_update_tool",
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"points": 0,
"status": "missed",
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{
"key": "fuzzing",
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"status": "missed",
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{
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{
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"points": 7.5,
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"status": "missed",
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"direct_affected_packages": 0
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"code": "no_direct_advisories",
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"max_points": 35
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{
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"warnings": [
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],
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"schema_version": "0.27.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/m/mdefrance/AutoCarver.svg",
"full_name": "mdefrance/AutoCarver",
"license_state": "standard",
"license_spdx": "MIT"
}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.