Öffentliches RegisterMittel
Software-GesundheitsberichtSchema 0.11.0 · Metriken 1.13.0 · 2026-07-14 14:09 UTC
Project-AgML / AgML
AgML is a centralized framework for agricultural machine learning. AgML provides access to public agricultural datasets for common agricultural deep learning tasks, with standard benchmarks and pretrained models, as well the ability to generate synthetic data and annotations.
Project-AgML/AgML erreicht einen Gesundheitsindex von 67 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Engineering Quality (86/100) ab, am schwächsten bei Security (37/100). Zuletzt vor 3 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.
67
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.
67
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
AgMLOrganisation
49 Follower4 öffentliche Reposseit Dez. 2021
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 | agml | 0.8.0 | - | 30 | vor 3 Tagen |
Metriken nach Kategorie
Vitalität
Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?
73
Entwicklungsaktivität
66Mittel
Wie die Bewertung erfolgt
| 36/36 | Push-Aktualität — letzter Push vor 3 Tagen |
| 6.2/36 | Commit-Rhythmus — 9/52 Wochen mit Commits |
| 14/18 | Commit-Volumen — 35 Commits im letzten Jahr |
| 10/10 | OpenSSF Scorecard: Maintained — 22 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
Verwendete Eingangsdaten
| commits_last_year | 35 |
| human_commit_share | — |
| days_since_last_push | 3 |
| active_weeks_last_year | 9 |
Release-Disziplin
84Gut
Wie die Bewertung erfolgt
| 27/27 | Liefert Releases aus — 28 Releases veröffentlicht |
| 36/36 | Release-Aktualität — letztes Release vor 3 Tagen |
| 12.6/27 | Release-Rhythmus — ein Release etwa alle 121,3 Tage |
| 0/10 | OpenSSF Scorecard: Signed-Releases — keine Daten |
Verwendete Eingangsdaten
| releases_count | 28 |
| latest_release_tag | v0.8.0 |
| releases_from_tags | nein |
| days_since_latest_release | 3 |
| mean_days_between_releases | 121,3 |
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?
72
Popularität & Verbreitung
60Mittel
Wie die Bewertung erfolgt
| 39.9/60 | Stars — 291 Stars |
| 13.7/25 | Forks — 45 Forks |
| 6.4/15 | Watcher — 15 Watcher |
Verwendete Eingangsdaten
| forks | 45 |
| stars | 291 |
| watchers | 15 |
| growth_state | unverified |
| growth_factor_pct | 100 |
| growth_unverified_reason | no_history |
Community-Gesundheit
85Exzellent
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 |
| 0/6.3 | 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 | nein |
Nachhaltigkeit & Governance
Überdauert das Projekt die Menschen, die es tragen — Bus-Faktor, Reaktionsfähigkeit, Trägerschaft und Paketpflege?
61
Maintainer-Resilienz (Bus-Faktor)
33Gefährdet
Wie die Bewertung erfolgt
| 9/54 | Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab |
| 4.3/22.5 | Commit-Verteilung — wichtigste beitragende Person verfasste 81 % der Commits |
| 13.5/13.5 | Breite der Beitragenden — 15 Beitragende |
| 6/10 | OpenSSF Scorecard: Contributors — project has 2 contributing companies or organizations -- score normalized to 6 |
Verwendete Eingangsdaten
| bus_factor | 1 |
| contributors_sampled | 15 |
| top_contributor_share | 0,81 |
Wie die Bewertung erfolgt
| 31.2/46.8 | Issue-Lösungsquote — 67 % der Issues geschlossen |
| 36.8/38.3 | PR-Annahme — 51/53 entschiedene PRs gemergt |
| 0/15 | OpenSSF Scorecard: Code-Review — Found 0/7 approved changesets -- score normalized to 0 |
Verwendete Eingangsdaten
| merged_prs | 51 |
| open_issues | 10 |
| closed_issues | 20 |
| issue_closed_ratio | 0,667 |
| closed_unmerged_prs | 2 |
Eigentümerschaft & Trägerschaft
56Mittel
Wie die Bewertung erfolgt
| 30/30 | Organisatorische Trägerschaft — im Besitz einer Organisation |
| 0/20 | Verifizierte Domain |
| 12.2/25 | Reichweite des Inhabers — 49 Follower von Project-AgML |
| 14.2/25 | Kontohistorie — 4 öffentliche Repos, Kontoalter ca. 4 Jahre |
Verwendete Eingangsdaten
| followers | 49 |
| owner_type | Organization |
| is_verified | — |
| owner_login | Project-AgML |
| public_repos | 4 |
| account_age_days | 1.656 |
Paketpflege
100Exzellent
Wie die Bewertung erfolgt
| 25/25 | Veröffentlicht & auflösbar — 1 Paket(e) auf pypi |
| 35/35 | Veröffentlichungsaktualität — letzte Veröffentlichung vor 3 Tagen |
| 20/20 | Versionshistorie — 30 veröffentlichte Versionen |
| 20/20 | Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen |
Verwendete Eingangsdaten
| packages | agml |
| ecosystems | pypi |
| any_deprecated | nein |
| min_days_since_publish | 3 |
Engineering-Qualität
Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?
86
Wie die Bewertung erfolgt
| 24/24 | CI-Workflows — 2 Workflow(s) |
| 24/24 | Tests vorhanden |
| 16/16 | Linter-Konfiguration — ruff.toml |
| 0/9.6 | Pre-Commit-Hooks |
| 0/6.4 | .editorconfig |
| 20/20 | OpenSSF Scorecard: CI-Tests — 6 out of 6 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 | nein |
Dokumentation
90Exzellent
Wie die Bewertung erfolgt
| 30/30 | README |
| 25/25 | Dokumentationsverzeichnis |
| 15/15 | Dokumentations-/Homepage-Site — https://project-agml.github.io |
| 10/10 | Repository-Beschreibung |
| 10/10 | Topics — 9 Topics |
| 0/10 | Wiki |
Verwendete Eingangsdaten
| topics | agriculture, computer-vision, dataset, deep-learning, image-classification, object-detection, pytorch, semantic-segmentation, synthetic-data |
| has_wiki | nein |
| homepage | https://project-agml.github.io |
| has_readme | ja |
| has_docs_dir | ja |
| has_description | ja |
Sicherheit
Sind die sichtbaren Sicherheits- und Lieferkettenpraktiken belastbar, ohne ungeklärte Exposition gegenüber Hochrisikojurisdiktionen?
37
Sicherheitslage
37Gefährdet
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 — 6 out of 6 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 0/7 approved changesets -- score normalized to 0 |
| 1.5/2.5 | Contributors — project has 2 contributing companies or organizations -- score normalized to 6 |
| 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 — 22 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| 0/5 | Packaging — keine Daten |
| 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 |
| 0/7.5 | Vulnerabilities — 22 existing vulnerabilities detected |
Verwendete Eingangsdaten
| source | openssf_scorecard |
| checks_evaluated | 15 |
| scorecard_version | v5.5.0 |
| checks_inconclusive | 3 |
| scorecard_aggregate | 3,7 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): branch_protection, packaging, signed_releases. 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.
54
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.
AI-Verify-Loop (Build / Test / Typprüfung)
88Exzellent
Wie die Bewertung erfolgt
| 18/18 | Bootstrap mit einem Befehl — Makefile |
| 22/22 | Automatisierte Tests |
| 11/11 | Lint-/Format-Konfiguration — ruff.toml |
| 11/11 | Statische Typprüfung — config/mypy.ini |
| 10/10 | Reproduzierbare Umgebung — lockfile |
| 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 | uv.lock |
| has_dockerfile | nein |
| typed_language | nein |
| bootstrap_files | Makefile |
| has_devcontainer | nein |
| has_linter_config | ja |
| typecheck_configs | config/mypy.ini |
| 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 (config/mypy.ini) |
| 53.7/55 | Handhabbare Dateigrößen — 3/125 Quelldateien über 60 KB |
Verwendete Eingangsdaten
| primary_language | Python |
| largest_source_bytes | 86.964 |
| source_files_sampled | 125 |
| oversized_source_files | 3 |
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
291GitHub-Sterne
15Mitwirkende
35Commits, letzte 12 Monate
3Tage seit letztem Push
28Releases
1Bus-Faktor
10offene Issues
PyPIPaket-Ökosysteme
Weitere Details
OpenSSF Scorecard 3.7 / 10
3.7Gesamtwert
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 | 6 out of 6 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 0/7 approved changesets -- score normalized to 0 |
| 6 | Contributors | project has 2 contributing companies or organizations -- score normalized to 6 |
| 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 | 22 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10 |
| k. A. | Packaging | packaging workflow not 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 |
| 0 | Vulnerabilities | 22 existing vulnerabilities detected |
Direkte Abhängigkeiten 11
| Registry | Paket | Versionsvorgabe | Manifest |
|---|---|---|---|
| PyPI | matplotlib | >=3.7.5 | pyproject.toml |
| PyPI | numpy | >=1.24.4 | pyproject.toml |
| PyPI | opencv-python | >=4.10.0.84 | pyproject.toml |
| PyPI | opencv-python-headless | >=4.10.0.84 | pyproject.toml |
| PyPI | requests | >=2.0.0 | pyproject.toml |
| PyPI | tqdm | >=4.67.0 | pyproject.toml |
| PyPI | pyyaml | >=6.0.2 | pyproject.toml |
| PyPI | albumentations | >=1.4.18 | pyproject.toml |
| PyPI | dict2xml | >=1.7.6 | pyproject.toml |
| PyPI | rich | >=14.0.0 | pyproject.toml |
| PyPI | datasets | — | pyproject.toml |
Alle Abhängigkeiten 90
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 11 direkte und 79 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
| Registry | Paket | Version | Beziehung |
|---|---|---|---|
| PyPI | albumentations | 2.0.5 | direkt |
| PyPI | datasets | 5.0.0 | direkt |
| PyPI | dict2xml | 1.7.6 | direkt |
| PyPI | matplotlib | 3.10.1 | direkt |
| PyPI | numpy | 2.2.4 | direkt |
| PyPI | opencv-python | 4.11.0.86 | direkt |
| PyPI | opencv-python-headless | 4.11.0.86 | direkt |
| PyPI | pyyaml | 6.0.2 | direkt |
| PyPI | requests | 2.32.3 | direkt |
| PyPI | rich | 14.0.0 | direkt |
| PyPI | tqdm | 4.67.1 | direkt |
| PyPI | agml | 0.8.0 | indirekt |
| PyPI | aiohappyeyeballs | 2.7.1 | indirekt |
| PyPI | aiohttp | 3.14.1 | indirekt |
| PyPI | aiosignal | 1.4.0 | indirekt |
| PyPI | albucore | 0.0.23 | indirekt |
| PyPI | annotated-types | 0.7.0 | indirekt |
| PyPI | anyio | 4.14.1 | indirekt |
| PyPI | async-timeout | 5.0.1 | indirekt |
| PyPI | attrs | 25.3.0 | indirekt |
| PyPI | boto3 | 1.37.31 | indirekt |
| PyPI | botocore | 1.37.31 | indirekt |
| PyPI | certifi | 2025.1.31 | indirekt |
| PyPI | charset-normalizer | 3.4.1 | indirekt |
| PyPI | click | 8.4.2 | indirekt |
| PyPI | colorama | 0.4.6 | indirekt |
| PyPI | contourpy | 1.3.1 | indirekt |
| PyPI | coverage | 7.8.0 | indirekt |
| PyPI | cycler | 0.12.1 | indirekt |
| PyPI | dill | 0.4.1 | indirekt |
| PyPI | exceptiongroup | 1.2.2 | indirekt |
| PyPI | filelock | 3.29.7 | indirekt |
| PyPI | fonttools | 4.57.0 | indirekt |
| PyPI | frozenlist | 1.8.0 | indirekt |
| PyPI | fsspec | 2026.4.0 | indirekt |
| PyPI | h11 | 0.16.0 | indirekt |
| PyPI | hf-xet | 1.5.1 | indirekt |
| PyPI | httpcore | 1.0.9 | indirekt |
| PyPI | httpx | 0.28.1 | indirekt |
| PyPI | huggingface-hub | 1.23.0 | indirekt |
| PyPI | idna | 3.10 | indirekt |
| PyPI | imageio | 2.37.0 | indirekt |
| PyPI | iniconfig | 2.1.0 | indirekt |
| PyPI | interrogate | 1.7.0 | indirekt |
| PyPI | jmespath | 1.0.1 | indirekt |
| PyPI | joblib | 1.4.2 | indirekt |
| PyPI | kiwisolver | 1.4.8 | indirekt |
| PyPI | lazy-loader | 0.4 | indirekt |
| PyPI | markdown-it-py | 3.0.0 | indirekt |
| PyPI | mdurl | 0.1.2 | indirekt |
| PyPI | multidict | 6.7.1 | indirekt |
| PyPI | multiprocess | 0.70.19 | indirekt |
| PyPI | mypy | 1.15.0 | indirekt |
| PyPI | mypy-extensions | 1.0.0 | indirekt |
| PyPI | networkx | 3.4.2 | indirekt |
| PyPI | packaging | 24.2 | indirekt |
| PyPI | pandas | 2.2.3 | indirekt |
| PyPI | pillow | 11.1.0 | indirekt |
| PyPI | pluggy | 1.5.0 | indirekt |
| PyPI | propcache | 0.5.2 | indirekt |
| PyPI | py | 1.11.0 | indirekt |
| PyPI | pyarrow | 25.0.0 | indirekt |
| PyPI | pydantic | 2.11.3 | indirekt |
| PyPI | pydantic-core | 2.33.1 | indirekt |
| PyPI | pygments | 2.19.1 | indirekt |
| PyPI | pyparsing | 3.2.3 | indirekt |
| PyPI | pytest | 8.3.5 | indirekt |
| PyPI | pytest-cov | 6.1.1 | indirekt |
| PyPI | pytest-order | 1.3.0 | indirekt |
| PyPI | python-dateutil | 2.9.0.post0 | indirekt |
| PyPI | pytz | 2025.2 | indirekt |
| PyPI | ruff | 0.11.5 | indirekt |
| PyPI | s3transfer | 0.11.4 | indirekt |
| PyPI | scikit-image | 0.25.2 | indirekt |
| PyPI | scikit-learn | 1.6.1 | indirekt |
| PyPI | scipy | 1.15.2 | indirekt |
| PyPI | shapely | 2.1.0 | indirekt |
| PyPI | simsimd | 6.2.1 | indirekt |
| PyPI | six | 1.17.0 | indirekt |
| PyPI | stringzilla | 3.12.3 | indirekt |
| PyPI | tabulate | 0.9.0 | indirekt |
| PyPI | threadpoolctl | 3.6.0 | indirekt |
| PyPI | tifffile | 2025.3.30 | indirekt |
| PyPI | tomli | 2.2.1 | indirekt |
| PyPI | typing-extensions | 4.13.2 | indirekt |
| PyPI | typing-inspection | 0.4.0 | indirekt |
| PyPI | tzdata | 2025.2 | indirekt |
| PyPI | urllib3 | 2.4.0 | indirekt |
| PyPI | xxhash | 3.8.1 | indirekt |
| PyPI | yarl | 1.24.2 | indirekt |
JSON-Rohbericht maschinenlesbar
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"computer-vision",
"dataset",
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{
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{
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{
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{
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{
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],
"description": "How well is the repo equipped to be developed and maintained with AI coding agents? An independent, experimental badge — weight 0.0, so it is surfaced on its own and does not affect the overall health score."
}
],
"metrics_version": "1.13.0"
},
"warnings": [],
"report_type": "repository",
"generated_at": "2026-07-14T14:09:16.743236Z",
"schema_version": "0.11.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/p/Project-AgML/AgML.svg",
"full_name": "Project-AgML/AgML",
"license_state": "standard",
"license_spdx": "Apache-2.0"
}Bewertungen sind Signale, keine Garantien. Sie spiegeln öffentlich sichtbare Praxis auf GitHub wider — kein Code-Audit und keine Sicherheitsgarantie.
Fehlende Daten werden ausgeschlossen und die Gewichte neu normiert, nie als null bewertet. Die Methodik ist versioniert und offen: Metriken v1.13.0, Schema v0.11.0 — vollständige Methodik · Metriken-Wiki.
Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken — PyPI.