Öffentliches RegisterMittel
Software-GesundheitsberichtSchema 0.17.0 · Metriken 1.13.0 · 2026-07-21 03:22 UTC
gtalarico / pyairtable
Python Api Client for Airtable
gtalarico/pyairtable erreicht einen Gesundheitsindex von 68 von 100 und liegt damit im Bereich Mittel. Am stärksten schneidet es bei Engineering Quality (100/100) ab, am schwächsten bei Security (21/100). Zuletzt vor 20 Tagen aktualisiert. Ein einzelner Mitwirkender trägt den Großteil der jüngsten Arbeit.
68
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.
68
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
Gui TalaricoPersönliches Konto
698 Follower55 öffentliche Reposseit Nov. 2014
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 | pyairtable | 3.4.0 | 3.880.650 | 46 | vor 48 Tagen | airtableapiclientpyairtable |
Metriken nach Kategorie
Vitalität
Lebt das Projekt — wird Code geschrieben und werden Releases ausgeliefert?
66
Entwicklungsaktivität
57Mittel
Wie die Bewertung erfolgt
| 28.8/36 | Push-Aktualität — letzter Push vor 20 Tagen |
| 7.6/36 | Commit-Rhythmus — 11/52 Wochen mit Commits |
| 15.1/18 | Commit-Volumen — 47 Commits im letzten Jahr |
| 0/10 | OpenSSF Scorecard: Maintained — keine Daten |
Verwendete Eingangsdaten
| commits_last_year | 47 |
| human_commit_share | — |
| days_since_last_push | 20 |
| active_weeks_last_year | 11 |
Release-Disziplin
80Gut
Wie die Bewertung erfolgt
| 16.2/27 | Liefert Releases aus — 42 Versions-Tags (keine GitHub-Releases) |
| 36/36 | Release-Aktualität — letztes Release vor 48 Tagen |
| 19.8/27 | Release-Rhythmus — ein Release etwa alle 63,1 Tage |
| 0/10 | OpenSSF Scorecard: Signed-Releases — keine Daten |
Verwendete Eingangsdaten
| releases_count | 42 |
| latest_release_tag | 3.4.0 |
| releases_from_tags | ja |
| days_since_latest_release | 48 |
| mean_days_between_releases | 63,1 |
Community & Verbreitung
Hat das Projekt Nutzer, Downloads, Aufmerksamkeit und ein einladendes Umfeld für Beitragende?
72
Wie die Bewertung erfolgt
| 47.9/60 | Stars — 892 Stars |
| 18.2/25 | Forks — 154 Forks |
| 7.4/15 | Watcher — 22 Watcher |
Verwendete Eingangsdaten
| forks | 154 |
| stars | 892 |
| watchers | 22 |
| growth_state | organic |
| growth_factor_pct | 100 |
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 |
Ökosystem-Verbreitung (Downloads)
100Exzellent
Wie die Bewertung erfolgt
| 80/80 | Downloads pro Monat — 3.880.650 Downloads/Monat über pypi |
| 0/20 | Abhängige in der Registry — von diesem Ökosystem nicht ausgewiesen |
Verwendete Eingangsdaten
| packages | pyairtable |
| dependents | — |
| ecosystems | pypi |
| total_downloads | — |
| monthly_downloads | 3.880.650 |
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?
71
Maintainer-Resilienz (Bus-Faktor)
37Gefährdet
Wie die Bewertung erfolgt
| 9/54 | Bus-Faktor — 1 Beitragende decken die Hälfte aller Commits ab |
| 11/22.5 | Commit-Verteilung — wichtigste beitragende Person verfasste 51 % der Commits |
| 13.5/13.5 | Breite der Beitragenden — 38 Beitragende |
| 0/10 | OpenSSF Scorecard: Contributors — keine Daten |
Verwendete Eingangsdaten
| bus_factor | 1 |
| contributors_sampled | 38 |
| top_contributor_share | 0,513 |
Reaktionsfähigkeit bei Issues & PRs
90Exzellent
Wie die Bewertung erfolgt
| 46.8/46.8 | Issue-Lösungsquote — 100 % der Issues geschlossen |
| 30.1/38.3 | PR-Annahme — 207/263 entschiedene PRs gemergt |
| 0/15 | OpenSSF Scorecard: Code-Review — keine Daten |
Verwendete Eingangsdaten
| merged_prs | 207 |
| open_issues | 0 |
| closed_issues | 195 |
| issue_closed_ratio | 1 |
| closed_unmerged_prs | 56 |
Eigentümerschaft & Trägerschaft
69Mittel
Wie die Bewertung erfolgt
| 10/30 | Organisatorische Trägerschaft — persönliches (Nutzer-)Konto |
| 0/20 | Verifizierte Domain — für Nutzerkonten nicht anwendbar |
| 20.5/25 | Reichweite des Inhabers — 698 Follower von gtalarico |
| 24.7/25 | Kontohistorie — 55 öffentliche Repos, Kontoalter ca. 11 Jahre |
Verwendete Eingangsdaten
| followers | 698 |
| owner_type | User |
| is_verified | — |
| owner_login | gtalarico |
| public_repos | 55 |
| account_age_days | 4.278 |
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 48 Tagen |
| 20/20 | Versionshistorie — 46 veröffentlichte Versionen |
| 20/20 | Nicht veraltet — aktiv, nicht veraltet oder zurückgezogen |
Verwendete Eingangsdaten
| packages | pyairtable |
| ecosystems | pypi |
| any_deprecated | nein |
| min_days_since_publish | 48 |
Engineering-Qualität
Sind grundlegende Engineering- und Dokumentationspraktiken vorhanden?
100
Engineering-Praktiken
100Exzellent
Wie die Bewertung erfolgt
| 24/24 | CI-Workflows — 1 Workflow(s) |
| 24/24 | Tests vorhanden |
| 16/16 | Linter-Konfiguration — tox.ini |
| 9.6/9.6 | Pre-Commit-Hooks |
| 6.4/6.4 | .editorconfig |
| 0/20 | OpenSSF Scorecard: CI-Tests — keine Daten |
Verwendete Eingangsdaten
| has_ci | ja |
| has_tests | ja |
| has_editorconfig | ja |
| 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://pyairtable.readthedocs.io |
| 10/10 | Repository-Beschreibung |
| 10/10 | Topics — 5 Topics |
| 10/10 | Wiki |
Verwendete Eingangsdaten
| topics | python, airtable, api, client, api-wrapper |
| has_wiki | ja |
| homepage | https://pyairtable.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?
21
Sicherheitslage
1Kritisch
Wie die Bewertung erfolgt
| 0/30 | Sicherheitsrichtlinie (SECURITY.md) |
| 0/25 | Dependabot-Konfiguration |
| 0/25 | Lockfiles für Abhängigkeiten — veröffentlichte Bibliothek — Lockfiles sind Sache der Anwendung, hier nicht erwartet |
| 0/20 | CodeQL-Workflow |
Verwendete Eingangsdaten
| source | file_signals |
| lockfiles | — |
| manifests | pyproject.toml, requirements-dev.txt, requirements-test.txt, setup.cfg, setup.py |
| has_codeql_workflow | nein |
| has_security_policy | nein |
| has_dependabot_config | nein |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lockfiles für Abhängigkeiten. 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 | 11 |
| 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:pyairtable@3.4.0 — das, was die Installation des veröffentlichten Pakets nach sich zieht — mit 11 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.
81
Wie die Bewertung erfolgt
| 45/45 | Agentenanweisungen — .claude/CLAUDE.md, AGENTS.md |
| 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 | .claude/CLAUDE.md, AGENTS.md |
| agent_instruction_max_bytes | 420 |
Von der Bewertung ausgeschlossen (keine Daten oder nicht anwendbar): Lesbare Commit-Historie. Die verbleibenden Gewichte wurden renormalisiert.
AI-Verify-Loop (Build / Test / Typprüfung)
86Exzellent
Wie die Bewertung erfolgt
| 18/18 | Bootstrap mit einem Befehl — Makefile |
| 22/22 | Automatisierte Tests |
| 11/11 | Lint-/Format-Konfiguration — tox.ini |
| 11/11 | Statische Typprüfung — pyairtable/py.typed |
| 0/10 | Reproduzierbare Umgebung |
| 0/10 | Belegte Agentenpraxis — keine Daten |
| 0/8 | Automatisierte Wartung — keine Daten |
| 0/10 | OpenSSF Scorecard: Pinned-Dependencies — keine Daten |
Verwendete Eingangsdaten
| has_nix | nein |
| has_tests | ja |
| lockfiles | — |
| has_dockerfile | nein |
| typed_language | nein |
| bootstrap_files | Makefile |
| has_devcontainer | nein |
| has_linter_config | ja |
| typecheck_configs | pyairtable/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 (pyairtable/py.typed) |
| 55/55 | Handhabbare Dateigrößen — 0/65 Quelldateien über 60 KB |
Verwendete Eingangsdaten
| primary_language | Python |
| largest_source_bytes | 50.303 |
| source_files_sampled | 65 |
| oversized_source_files | 0 |
Eckdaten
892GitHub-Sterne
38Mitwirkende
47Commits, letzte 12 Monate
20Tage seit letztem Push
42Releases
1Bus-Faktor
0offene Issues
PyPIPaket-Ökosysteme
Warnungen zur Datenerhebung
- OpenSSF Scorecard timed out after 240s; skipping Scorecard checks
Weitere Details
Stern- und Fork-Verlauf 892 ★ / 0 ⇿
892Sterne
Wann jeder Stern und Fork hinzugefügt wurde, von GitHub erfasst und nach Tagen gruppiert. Das kumulierte Wachstum steht direkt über den täglichen Zugängen, aus denen es besteht, sodass beide gegeneinander lesbar sind: stetiger organischer Zuwachs sieht ganz anders aus als ein abrupter, kurzlebiger Ausschlag. Wo dieser Unterschied messbar ist, wird er als Wachstumsauthentizität ausgewiesen.
Jeder Punkt umfasst 9 Tage.
Direkte Abhängigkeiten 5
| Registry | Paket | Versionsvorgabe | Manifest |
|---|---|---|---|
| PyPI | inflection | — | setup.cfg |
| PyPI | pydantic | >= 2, < 3 | setup.cfg |
| PyPI | requests | >= 2.22.0 | setup.cfg |
| PyPI | typing_extensions | — | setup.cfg |
| PyPI | urllib3 | >= 1.26 | setup.cfg |
Alle Abhängigkeiten 33
Vollständig aufgelöster Abhängigkeitssatz aus dem GitHub-Abhängigkeitsgraphen: 5 direkte und 28 indirekte (transitive) Pakete. Die transitive Hülle ist vollständig, wenn das Repository eine Lockfile eincheckt.
| Registry | Paket | Version | Beziehung |
|---|---|---|---|
| PyPI | inflection | — | direkt |
| PyPI | pydantic | — | direkt |
| PyPI | requests | — | direkt |
| PyPI | typing-extensions | — | direkt |
| PyPI | urllib3 | — | direkt |
| PyPI | autodoc-pydantic | — | indirekt |
| PyPI | black | — | indirekt |
| PyPI | build | 0.6.0.post1 | indirekt |
| PyPI | click | — | indirekt |
| PyPI | codecov | — | indirekt |
| PyPI | cogapp | — | indirekt |
| PyPI | flake8 | — | indirekt |
| PyPI | mock | — | indirekt |
| PyPI | mypy | — | indirekt |
| PyPI | pre-commit | — | indirekt |
| PyPI | pytest | — | indirekt |
| PyPI | pytest-cov | — | indirekt |
| PyPI | requests-mock | — | indirekt |
| PyPI | revitron-sphinx-theme | — | indirekt |
| PyPI | sphinx | 4.5.0 | indirekt |
| PyPI | sphinx-autoapi | — | indirekt |
| PyPI | sphinx-autodoc-typehints | — | indirekt |
| PyPI | sphinxcontrib-applehelp | 1.0.4 | indirekt |
| PyPI | sphinxcontrib-devhelp | 1.0.2 | indirekt |
| PyPI | sphinxcontrib-htmlhelp | 2.0.1 | indirekt |
| PyPI | sphinxcontrib-qthelp | 1.0.3 | indirekt |
| PyPI | sphinxcontrib-serializinghtml | 1.1.5 | indirekt |
| PyPI | sphinxext-opengraph | — | indirekt |
| PyPI | tox | — | indirekt |
| PyPI | twine | 3.3.0 | indirekt |
| PyPI | types-requests | — | indirekt |
| PyPI | types-urllib3 | — | indirekt |
| PyPI | wheel | 0.46.2 | indirekt |
Abhängigkeits-Advisories 0
Die Installation von pypi:pyairtable@3.4.0 zieht 11 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": "openssf_scorecard_contributors",
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"detail": "OpenSSF Scorecard unavailable",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
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],
"max_points": 10
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},
{
"key": "responsiveness",
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"name": "Issue & PR responsiveness",
"note": null,
"notes": [],
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"closed_issues": 195,
"issue_closed_ratio": 1,
"closed_unmerged_prs": 56
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"components": [
{
"key": "issue_resolution",
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"points": 46.8,
"status": "met",
"details": [
{
"code": "issues_closed_share",
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"share": 100
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}
],
"max_points": 46.75
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{
"key": "pr_acceptance",
"name": "PR acceptance",
"detail": "207/263 decided PRs merged",
"points": 30.1,
"status": "partial",
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{
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"max_points": 38.25
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{
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"points": 0,
"status": "excluded",
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"max_points": 15
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},
{
"key": "stewardship",
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"owner_login": "gtalarico",
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"account_age_days": 4278
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"components": [
{
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"points": 10,
"status": "partial",
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],
"max_points": 30
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{
"key": "verified_domain",
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"detail": "not applicable to user accounts",
"points": 0,
"status": "excluded",
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"code": "not_applicable_to_user_accounts",
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],
"max_points": 20
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{
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"detail": "698 followers of gtalarico",
"points": 20.5,
"status": "partial",
"details": [
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"count": 698,
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],
"max_points": 25
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{
"key": "track_record",
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"points": 24.7,
"status": "partial",
"details": [
{
"code": "public_repos",
"params": {
"count": 55
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{
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}
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{
"key": "package_maintenance",
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"name": "Package maintenance",
"note": null,
"notes": [],
"value": 100,
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"any_deprecated": false,
"min_days_since_publish": 48
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"components": [
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"key": "published_resolvable",
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"points": 25,
"status": "met",
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{
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"points": 35,
"status": "met",
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{
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"detail": "46 published versions",
"points": 20,
"status": "met",
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{
"code": "published_versions",
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],
"max_points": 20
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{
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"points": 20,
"status": "met",
"details": [
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"max_points": 20
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}
],
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},
{
"key": "engineering",
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"name": "Engineering Quality",
"value": 100,
"weight": 0.2,
"metrics": [
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"key": "engineering_practices",
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"notes": [],
"value": 100,
"inputs": {
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"has_tests": true,
"has_editorconfig": true,
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"status": "met",
"details": [
{
"code": "ci_workflows",
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"max_points": 24
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{
"key": "tests_present",
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"points": 24,
"status": "met",
"details": [],
"max_points": 24
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{
"key": "linter_config",
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"detail": "tox.ini",
"points": 16,
"status": "met",
"details": [
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],
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{
"key": "pre_commit_hooks",
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"points": 9.6,
"status": "met",
"details": [],
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{
"key": "editorconfig",
"name": ".editorconfig",
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"points": 6.4,
"status": "met",
"details": [],
"max_points": 6.4
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{
"key": "openssf_scorecard_ci_tests",
"name": "OpenSSF Scorecard: CI-Tests",
"detail": "OpenSSF Scorecard unavailable",
"points": 0,
"status": "excluded",
"details": [
{
"code": "no_data",
"params": {}
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],
"max_points": 20
}
]
},
{
"key": "documentation",
"band": "excellent",
"name": "Documentation",
"note": null,
"notes": [],
"value": 100,
"inputs": {
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"airtable",
"api",
"client",
"api-wrapper"
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"has_wiki": true,
"homepage": "https://pyairtable.readthedocs.io",
"has_readme": true,
"has_docs_dir": true,
"has_description": true
},
"components": [
{
"key": "readme",
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"detail": null,
"points": 30,
"status": "met",
"details": [],
"max_points": 30
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{
"key": "documentation_directory",
"name": "Documentation directory",
"detail": null,
"points": 25,
"status": "met",
"details": [],
"max_points": 25
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{
"key": "documentation_homepage_site",
"name": "Documentation / homepage site",
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"status": "met",
"details": [],
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{
"key": "repository_description",
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"points": 10,
"status": "met",
"details": [],
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{
"key": "topics",
"name": "Topics",
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"points": 10,
"status": "met",
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"code": "topics_count",
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"max_points": 10
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{
"key": "wiki",
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"points": 10,
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}
],
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{
"key": "security",
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"name": "Security",
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"weight": 0.16,
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"inputs": {
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},
"components": [
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"points": 0,
"status": "missed",
"details": [],
"max_points": 30
},
{
"key": "dependabot_config",
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"detail": null,
"points": 0,
"status": "missed",
"details": [],
"max_points": 25
},
{
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"points": 0,
"status": "excluded",
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"max_points": 25
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{
"key": "codeql_workflow",
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"points": 0,
"status": "missed",
"details": [],
"max_points": 20
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]
},
{
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"note": "Excluded from scoring (no data or not applicable): No advisories left outstanding. Remaining weights renormalized. Matched the pypi:pyairtable@3.4.0 runtime dependency closure — what installing the published package pulls in — 11 packages. Reachability is not analyzed.",
"notes": [
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"code": "excluded_no_data",
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},
{
"code": "weights_renormalized",
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{
"code": "advisories_scope_published",
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},
{
"code": "advisories_reachability",
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],
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"inputs": {
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"affected_packages": 0,
"assessed_packages": 11,
"unassessed_packages": 0,
"affected_by_severity": "none",
"direct_affected_packages": 0
},
"components": [
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"value": 100,
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"code": "jurisdiction_evidence_limits",
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"details": [
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"code": "jurisdiction_no_match",
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],
"max_points": 100
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]
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],
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{
"key": "ai_readiness",
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"name": "AI Readiness",
"value": 81,
"weight": 0,
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"components": [
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"code": "weights_renormalized",
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"status": "excluded",
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"code": "no_data",
"params": {}
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"max_points": 40
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]
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"code": "excluded_no_data",
"params": {
"components": [
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},
{
"code": "weights_renormalized",
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"value": 86,
"inputs": {
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"lockfiles": [],
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"typed_language": false,
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"components": [
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"points": 18,
"status": "met",
"details": [
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"points": 22,
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"details": [],
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{
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"status": "met",
"details": [
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"code": "file_list",
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"status": "met",
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"code": "file_list",
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"max_points": 11
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{
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"points": 0,
"status": "missed",
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"max_points": 10
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"key": "demonstrated_agent_practice",
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"status": "excluded",
"details": [
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"code": "no_data",
"params": {}
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"max_points": 10
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{
"key": "automated_maintenance",
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"points": 0,
"status": "excluded",
"details": [
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"code": "no_data",
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],
"max_points": 8
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{
"key": "openssf_scorecard_pinned_dependencies",
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"points": 0,
"status": "excluded",
"details": [
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"code": "no_data",
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"max_points": 10
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"notes": [],
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"largest_source_bytes": 50303,
"source_files_sampled": 65,
"oversized_source_files": 0
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"components": [
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"status": "partial",
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"code": "typecheck_config_language",
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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."
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],
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"warnings": [
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"schema_version": "0.17.0",
"badge_url": "https://raw.githubusercontent.com/inspect-software/badges/main/v1/g/gtalarico/pyairtable.svg",
"full_name": "gtalarico/pyairtable",
"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 v0.17.0 — vollständige Methodik · Metriken-Wiki.
Wie ein einzelnes Ergebnis im Gesamtregister steht: aggregierte Statistiken — PyPI.